ELAIA: Volumes 5/6

ELAIA

Honors Program Administration

Stephen Case, Editor and Director

Melody Grimm, Administrative Assistant

Honors Faculty Council

Justin Brown, Mathematics

Pam Greenlee, Benner Library

Tiffany Greer, Nursing

Laurie Hofman, Education

Dave Horton, Accounting

Dave Johnson, English

Chad Maxson, Philosophy

Dan Sharda, Biology

Neal Woodruff, Music

Honors Program Teaching Faculty

Stephen Case, Earth and Space Sciences

Ryan Himes, Biology

Dave Johnson, English

Karen Leonard, Modern Languages

Chad Maxson, Philosophy

Charles Perabeau, Theology and Christian Ministry

Kyle Robinson, History

Jon Seals, Art and Digital Media

Dan Sharda, Biology

Nicole Vander Schaaf, Biology

Laura Widstrom, Christian Ministry

DIRECTOR’S LETTER FOR ELAIA VOLUME 5/6

I am very pleased to introduce the latest issue of ELAIA: the Honors Journal of Olivet Nazarene University, featuring the Honors research projects of the graduating classes of 2022 and 2023. The Honors Program at Olivet exists to provide students the opportunity to grow and develop as Christian scholars, completing a sequence of interdisciplinary courses and pursuing a two-year mentored research project, ultimately equipping them to take their place as servant-leaders in their professional and academic communities.

Elaia is the Greek word for olive, and it is a privilege to see the lives of these students, like the olive branch, bear the fruits of scholarship year after year. I congratulate them all and pray that God blesses their lives and their work for continued and anointed fruitfulness!

I also want to give a special thanks to all of the faculty at Olivet—past and present—who have made and continue to make the work of the Honors Program possible: the Honors teaching cohort, the Honors Council, and all the faculty who have served as research mentors for the students whose work is represented in this volume. In your guidance, expertise, example, and service you shape the next generation of Christian scholars and contribute to the academic life of the university—thank you!

VOLUME 5

Impact of Mindfulness Training on Test Anxiety in College Students

ACKNOWLEDGEMENTS

I would like to extend my sincere gratitude to all those who stood by me throughout this project. I would specifically like to thank Dr. Kristian Veit, who has been my mentor and cheerleader for over two years. I have learned an immeasurable amount under his guidance. Dr. Elizabeth Schurman and the Honors Program faculty were pivotal in the development and refining of my project. This project would not be what it is today without Dr. Schurman’s guidance on writing a thesis and creating a project. I would also like to thank Dr. Russ Lovett for allowing me to use his classes to conduct research; without him, there would be no data.

Additionally, I am grateful for the encouragement and support provided by my parents throughout every step and by my sisters, Kimberly and Emma, who were always willing to listen to my project ideas and future goals. To my roommates and friends that constantly supported me and helped me staple questionnaires for data collection, thank you! Caitlyn, Kelli, Sarah, Ashley, and Matt, you guys mean the world to me, and I am so thankful for your friendship. Finally, Cohort 12, you have become some of my most cherished friends and have shaped my college career. I cannot wait to see where you all go, and I am honored to be graduating beside you.

ABSTRACT

Background

Mindfulness is defined as the state of giving full attention to a stimulus, internal or external, without inducing judgment or becoming reactional about the feelings experienced, positive or negative (Davis & Hayes, 2012). Previous studies have investigated the relationship between mindfulness techniques and the reduction of anxiety (Chambers et al., 2008; Macdonald & Olsen, 2020); a smaller number of studies have considered test anxiety (Cho et al., 2016; Sparks, 2017). Prior research has used multiple mindfulness techniques to measure the impact on test anxiety, but few have isolated mindfulness trainings to compare the relative impact of each type on test anxiety. The present study utilized two different types of mindfulness trainings to analyze their impact on test anxiety in comparison with each other and a control group; it was hypothesized that mindfulness would increase, and test anxiety would decrease for students in the experimental conditions. The Fog Rolling In training group was hypothesized to experience greater decreases in test anxiety compared to the Counting Breaths and control group.

Methods

Forty-two individuals from three sections of a general education class participated. Students were asked to participate in the study through the completion of the Mindful Attention Awareness Scale (MAAS) and a shortened form of the Test Anxiety Inventory (TAI—5). Both forms were given to each class before trainings began and again at the end of data collection. In the weeks between measures, a class-specific mindfulness training was presented three times.

Results

Data were analyzed using 2x3 mixed factorial ANOVA. There was a non-significant interaction (p = .466), non-significant main effects for mindfulness (p = .501) and test anxiety (p = .611), and non-significant main effect for time (p = .484). Mindfulness and test anxiety variables also failed to reach significance when using a paired-samples t-test to exclude the control group (p = .064; p = .960).

Conclusions

Neither mindfulness nor test anxiety changed after participants were exposed to a mindfulness training. In addition, no significant differences were found between two different forms of mindfulness training and a control group on mindfulness and test anxiety.

Keywords: mindfulness, test anxiety, anxiety, college students

Discussions of mindfulness can be found in a plethora of settings: from self-help books to phone applications, a poster at the doctor’s office, or a video on YouTube; mindfulness is easy to come by. The practice of being mindful has become prevalent in American society, prompting research to explore the effectiveness and benefits of mindfulness techniques. Even so, mindfulness is not a new concept, and neither is research on this topic; many researchers have investigated the impact of mindfulness on one’s mental state and have been doing so for over two decades (Brown & Ryan, 2003), leading to a rich field of research.

Mindfulness

Mindfulness focuses on acknowledging the present through techniques such as deep breathing, directed attention, and meditation. It can be defined as the state of giving full attention to an internal or external event without inducing judgment or becoming reactional about what feelings these stimuli cause, regardless of whether the emotion is positive or negative (Davis & Hayes, 2012). Mindfulness has been used in efforts to improve workplace satisfaction (Hülsheger et al., 2013), improve life satisfaction (Felsman, et al. 2017), reduce aggression (Milani, et al., 2013), reduce rumination (Long & Christian, 2015), and decrease test anxiety in students (Sparks, 2017; Cho et al., 2016). In each of the studies listed above, individuals have become more aware of their surroundings, their current emotional state, and times when they are content as opposed to times when they are not. These interventions have promoted emotional regulation in participants and deeper levels of self-understanding.

In addition to being used in various settings, mindfulness programs span varying lengths of time; some programs are under fifteen minutes (Polizzi et al., 2019), whereas others are structured as intensive ten-day retreats (Chambers, et al. 2008). The shorter programs are often used in classroom or work settings (Sparks, 2017; Zalaznick, 2017), whereas the longer programs are typically used in clinical settings (Chambers et al., 2008). There has been success in interventions of varying length; in fact, Dawson et al. found in their 2020 meta-analysis of seventeen mindfulness studies that intervention length did not significantly predict mindfulness outcomes or effects for participants. The longest mindfulness intervention in the above study was 27.5 hours and the shortest was ten minutes. Some training programs were a single session, whereas the longest running program lasted ten weeks. No further information was given on how long each session was in comparison to how long the program ran (Dawson et al., 2020).

In one intervention several mindfulness techniques are often used, allowing the client to experience multiple facets of mindfulness. As a result of techniques being used together, few have been tested independently to discover the impact of specific types of mindfulness. Breathing exercises are the most common form of mindfulness

(Sparks, 2017), which could be rooted in their familiar and relatively self-explanatory nature (Zalaznick, 2017). Different types of exercises work with different skill sets; some forms of mindfulness target acceptance, present-awareness, bodily awareness, or overcoming obstacles (Apsche & Jennings, 2013). These are a limited number of examples of mindfulness facets that have been explored.

In the same vein, MacDonald and Olsen published a study on the impacts of different mindfulness skills. The researchers discovered that specific mindfulness-related skills, such as non-judgmental thinking and awareness, can lead to better attentional control, which can reduce anxiety in students (2020). Mindfulness techniques can have a lasting impact beyond the completion of a training program, and there were no significant differences in mindfulness based on whether the interventions were instructor-run or self-run (Dawson et al, 2020). However, in 2021, Lothes presented conflicting data, stating that if mindfulness techniques are abandoned, the benefits of mindfulness will not endure, suggesting that continual practice is needed for long-lasting benefits. Regardless of the lasting impacts, both studies found mindfulness to be beneficial to those who practiced it (Dawson et al., 2020; Lothes, 2021).

Test Anxiety

Test anxiety impacts students of all ages. Some students are impacted as early as elementary school, whereas others experience anxious feelings about exams later in high school, college, or even during graduate programs (Zalaznick, 2017). The American Psychological Association (APA) conducted a study in 2014 assessing student anxiety and stress, finding that 31% of teens believed their stress levels increased during the school year and that only 50% of teens felt confident in their ability to handle personal problems and stress. Educators have been noticing an increase in student anxiety; one in ten students believe their grades reflected a lower understanding of material than what they possess (Sparks, 2017). The gap between knowledge and performance is especially relevant when talking about student testing, which can be a source of stress and anxiety for many students.

Test anxiety is generally accepted as having two subcategories: worry and emotionality (Morris et al., 1981). These subcategories can further be broken down into state and trait characteristics. These determine whether an experience is typical of a person because of their nature or if the current emotion is situational, adding to the complexities of test anxiety (Morris et al., 1981). The amount of variation in experiences makes test anxiety difficult to treat; however, there has been success with mindfulness practices. Test anxiety closely resembles an emotional state, an in-the-moment affliction, rather than a disorder, which allows it to be targeted by mindfulness techniques promoting calmness and awareness (Cho et al., 2016).

Mindfulness and Test Anxiety

A major benefit of mindfulness is the ability to reduce test anxiety as shown by significant drops in student anxiety in several studies (Dawson et al., 2020; Sparks, 2017;

Cho et al., 2016). Students experience anxiety for many reasons, but test anxiety is a prominent affliction. Testing anxiety can lead to lower test grades, diminished self-efficacy, and other unpleasant feelings related to anxiety that can prohibit students from accurately portraying their knowledge of class material (Dawson et al, 2020). Many students are impacted by feelings of anxiety, especially regarding class work, creating a need for an intervention (MacDonald & Olsen, 2020).

Since test anxiety most affects those taking tests, classroom programs and promotion of mindfulness can easily reach the target audience. Mindfulness is easy to use in the classroom, because it does not need to be time consuming to be effective (Long & Christian, 2015). It is also inexpensive, which is useful for school districts with limited resources. Mindfulness can reach a large group of people in a limited amount of time while still yielding improvements in areas like one’s anxiety levels and emotional distress (Dawson et al., 2020).

Mindfulness can help students in the classroom while providing lasting skills that can be applied throughout school and in future careers (Zalaznick, 2017). According to Sparks, student mindfulness grew quickly in the 2015-16 school year in a school district in Austin, Texas, due to a new mindfulness curriculum called “Mindful Classrooms” (2017). This 36-week curriculum was initially used in twenty classrooms, later expanding to 130 classrooms of all age ranges; this expansion took place in less than two years because of the success in the initial classes (Sparks, 2017). This district in Austin experienced calmer and less stressed students in every grade, from kindergarten to high school (Sparks, 2017).

Research has also been applied to college students and the reduction of test anxiety through mindfulness. In Cho et al. (2016), university students practiced mindfulness independently for six days and attend one educational session with a researcher before measuring test anxiety levels and positive thoughts. By the end of the study, those in the mindfulness condition experienced more positive thoughts and less test anxiety than those in a control or cognitive reappraisal group (Cho et al., 2016).

In a 2020 meta-analysis Dawson et al. analyzed different Mindfulness Based Interventions (MBIs) used by colleges and college students. The researchers found that MBIs have a significant impact on distress and state anxiety when compared with control groups. Similarly, Lothes et al. had college students practice mindfulness using Dialectical Behavior Therapy (DBT) techniques through an eight-week m indfulness program (2021). Students in the mindfulness condition demonstrated significant within-group improvements of general and test anxiety (Lothes et al., 2021).

The current body of research emphasizes many benefits of mindfulness, each using a different mindfulness technique to do so. After reading Apsche and Jennings’ 2013 study, which employed multiple types of mindfulness activities within one session, the principal researcher of the current study became curious about the differing impacts, if any, of different types of mindfulness practices on test anxiety. The 2013 study used

a variety of mindfulness trainings, but the Counting Breaths training was used in the majority of sessions (Apsche & Jennings) and was chosen to be included in the present study. This technique is reminiscent of many breath trainings, which are frequently used in mindfulness programs because of the high level of accessibility.

The other training chosen in this study to measure the effectiveness of mindfulness techniques was the Rolling In training. This training has participants focus on a thick cloud of fog that is approaching, which is symbolic of an aversive event. For many students, tests are anxiety inducing and stressful events. By practicing overcoming an inevitable and worrying event, students can practice working through emotions similar to what they might feel before taking a big test.

Even though there are many different techniques associated with mindfulness, there is little data about what types of techniques provide the best results. There is a gap in research regarding specific data on the effectiveness of different types of mindfulness trainings. The lack of such research inspired the researcher of this study to isolate specific mindfulness activities that use different approaches to regulating emotions to test for a difference in effectiveness of the trainings. The focus on the different effects of training led to three main hypotheses:

1. Students in the experimental groups will show improvements in mindfulness throughout the semester. These differences will be greater than those displayed by the control group.

2. Students in the experimental groups will show decreases in test anxiety throughout the semester. These differences will be greater than those displayed by the control group.

3. Students in the Fog Rolling In training will display greater decreases in test anxiety than those in the Counting Breaths training or in the control group.

METHODS

Participants

This quasi-experimental study utilized forty-two undergraduate students (twenty-one male, twenty-one female) at a small, denominationally affiliated university in the Midwest. Throughout the study, seventy-two students filled out at least one measure, however, only forty-two students filled out every measure, therefore being included as a participant. Those who did not complete all measures were excluded from the data analysis. The mean age of participants was 19.6 years. The majority of participants were white, 76.2%, though 9.5% were African American, 7.1% were Hispanic, 4.8% were Asian, and 2.4% identified as both Hispanic and White. There were fourteen participants in the Fog Rolling In training, fifteen for Counting Breaths, and thirteen participants in the control group.

Participants were drawn from a general education course on Biblical Studies. To increase the amount of control in the study, three class sections of the same course taught by the same professor at various times throughout the day were used. Students were asked to sign an informed consent document if they wished to participate in the study. Students were incentivized to participate with the chance to win one of nine $10 gift cards that would be awarded at the end of the study to three participants per class.

Materials

In order to measure mindfulness, the Mindful Attention Awareness Scale (MAAS) was used (α = .87; r = .81) (Brown & Ryan, 2002). The MAAS is scored by averaging the participant’s self-reported degree of mindfulness across fifteen items rated on a six-point scale with endpoints ranging from 1 (almost always) to 6 (almost never); the higher the average, the more mindful a participant is said to be.

Test Anxiety was measured using the TAI—5 (α = .88; r = .53) (Taylor & Deane, 2002). This questionnaire measures how likely one is to experience symptoms of test anxiety. A four-point scale with endpoints of 1 (Strongly Disagree) to 4 (Strongly Agree) is used. The TAI—5 is a five-question scale that includes two questions to measure worry, two measures of emotionality, and one question that asks the responder if they feel they experience anxious feelings regarding test taking. The higher participants score on the TAI—5, the more test anxiety they experience. Although the scale measures both subcategories of test anxiety, this study only considered overall test anxiety scores.

The two mindfulness trainings, Fog Rolling In and Counting Breaths, are from Apsche and Jenning’s book, The Mindfulness Toolkit: For counselors, teachers, coaches, and clinicians of youth (2013). The first class received a training focused on overcoming aversive events, called the Fog Rolling In training. This training guided students through the process of mindfulness using imagery such as “The fog slowly rolls toward you. Soon the trees close to you disappear in the white mist. You observe the fog. You don’t judge it. It is neither good nor bad. It just is what it is” (Apsche & Jennings, 2013). The second class used an intentional breathing exercise called Counting Breaths. This guided breathing exercise aimed to induce a calm and relaxed state in students, using instructions like, “Take a long, deep breath and as you inhale, mentally count ‘one.’ Then, as you slowly exhale, count ‘two.’” (Apsche & Jennings, 2013). Both trainings were recorded in separate audio files, so they could be played on training days without variation of content. The final class was the control group and received the same explanation of mindfulness as the treatment groups at the beginning of the study; however, the control group did not receive any further information other than being asked to fill out the forms provided. Participants were asked to fill out their demographic information including age, sex, and ethnicity. To measure age, participants wrote how old they were, whereas they were asked to check a box for sex (male or female) and could check as many boxes as applied to them for ethnicity. Participants were given the option “Prefer not to answer”

for each question. Hughes et al.’s measure of ethnicity was used to be inclusive of many different origins and included options to select more than one ethnicity for those it applied to (2016).

Procedure

This study is a 2x3 mixed-subjects quasi-experiment. Participants did not choose their class, as the mindfulness group they were in could not be randomly assigned. The study started a week before the second class-wide exam of the semester. After learning about the study, their rights as a participant, the voluntary nature of the study, and finally signing the informed consent, participants filled out two questionnaires, the MAAS (Brown & Ryan, 2002) and the TAI—5 (Taylor & Deane, 2002), to measure initial mindfulness and test anxiety levels. Students also provided demographic information after completing the first two measures.

During the same class period as the initial introduction, the two experimental groups heard their class-specific mindfulness training. Both trainings were between four and five minutes in length. The control group did not hear a mindfulness training; instead, the researcher offered a brief explanation of mindfulness before leaving.

Approximately two weeks later, halfway between the second and third exam of the semester, the professor played the class-specific mindfulness training at the beginning of class. The experimental groups heard the same training as before, whereas the control group started class as they would any other day. The mindfulness trainings were played for a third and final time the class period before the third course exam, which occurred roughly three weeks after the second course exam. One week after the third exam, the researcher returned to each class and asked participants to fill out the MAAS and TAI—5 for a second time. The two experimental groups had heard their mindfulness trainings a total of three times, whereas the control group had filled out the initial assessments and did not hear any more about the study until the posttest assessment. At the end of this, the researcher collected the questionnaires from all three classes, concluding data collection.

RESULTS

A 2x3 mixed-subjects ANOVA was used to analyze the interaction between mindfulness training and time. One ANOVA was conducted with mindfulness as the dependent variable, and a second ANOVA treated test anxiety as the dependent variable.

The first hypothesis predicted that students in the mindfulness conditions would become more mindful. This was not supported, F(1, 39) = .50, p = .484, η²p = .013 (Table 1). However, because the main effect of time in this ANOVA includes the control group, a paired-samples t-test was conducted to examine the difference in mindfulness over

Within Subjects Effects

Note. Type 3 Sums of Squares

Variable: Mindfulness

Between Subjects Effects

Note. Type 3 Sums of Squares

Dependent Variable: Mindfulness

time for the experimental groups. Still, there was no significant difference in mindfulness from before to after the mindfulness training, t(28) = -1.93, p = .064, d = -.36 (Table 2).

The second hypothesis predicted that students in the mindfulness conditions would have lower levels of test anxiety. This was also not supported, F (1, 39) = .00, p = .989 (Table 3). When just considering the two experimental groups, excluding the control group, the results remained the same, t (41) = .05, p = .96, d = .008 (Table 4).

The third hypothesis considered the difference between mindfulness trainings, stating that those in the Fog Rolling In training would show less test anxiety than the other two groups. The main effect for mindfulness from the between subjects ANOVA did not reach significance (p = .501) (Table 1).

Within Subjects Effects

Note. Type 3 Sums of Squares

Between Subjects Effects

Mixed Subjects ANOVA

Note. Type 3 Sums of Squares

DISCUSSION

The present study examined three hypotheses regarding the implications of mindfulness training on mindfulness and test anxiety in college students. The first hypothesis stated that students in the mindfulness conditions would become more mindful throughout the progression of the study, as compared to individuals in the control group. Despite other studies that had significant changes in levels of mindfulness after short trainings (Long & Christian, 2015; Polizzi et al., 2019), this study failed to discover a significant difference in mindfulness levels over time. Previous studies have utilized longer trainings that were about fifteen minutes (Polizzi et al., 2019) as opposed to five, which could be a potential source of difference.

The researcher predicted that test anxiety would decrease for students who participated in a mindfulness condition. Despite the potential of mindfulness to increase attentional awareness and decrease test anxiety, none of the groups reported a change in mindfulness; rather, the means of each group remained almost entirely the same. This result is inconsistent with previous research by Jennings and Jennings and Davis and Hayes, which supports that mindfulness trainings can reduce test anxiety (2013; 2012). It also conflicts with Apsche and Jennings’ study that originally used the mindfulness trainings evaluated in this study, although the two studies differed in method (2013). The initial data collection for this study occurred near the beginning of the spring semester, whereas the posttest information was gathered slightly after midterms; although it is possible the difference in workload could have had an impact on anxiety levels, previous studies with similar timelines have achieved significant decreases in test anxiety in the face of mindfulness (Lothes, 2021). Jennings and Jennings’ original study (2013) demonstrated a 30% decrease in overall anxiety on the Beck Anxiety Inventory (BAI) for senior high school students who attended four mindfulness training sessions over three weeks, with two mindfulness exercises per session. The current study’s inconsistency with previous data suggests that both the trainings used, and the time spent on the trainings could be major covariates in the reduction of test anxiety.

The third hypothesis was specific to the trainings used, two variables that had not been isolated prior to the study at hand. The Fog Rolling In training introduced an aversive event that gradually passed, allowing for feelings reminiscent of those before a test. On the other hand, breath trainings are frequently used mindfulness interventions, but are generally studied for effectiveness, not in comparison with other techniques (Polizzi et al., 2019; Sparks, 2017). Due to its similarity to the conditions before a test, the Fog Rolling In training was hypothesized to have a greater impact on reducing test anxiety compared to the Counting Breaths training. No significant differences were found between the groups’ levels of test anxiety from pre- to posttest, or between experimental and control groups. This section of the study analyzed techniques that had not previously been isolated to the researcher’s knowledge.

The lack of significance in the results could suggest that mindfulness trainings are most useful when used together, or that the specific trainings used were not effective, as there are few studies that use the same trainings as this study (Jennings & Jennings 2013). Regardless, these speculations go beyond the scope of the research at hand.

The present study had several limitations, including the impact of Covid-19 upon the study. There was a high attrition rate, some of which can be attributed to students entering quarantine and not being in class at the time of the second data collection. Additionally, the trainings used were shorter than previous examples. Future studies should use a different training all together or add a second training within the same category of intervention, such as a breathing technique or guided imagery from Apsche and Jennings’s workbook (2013). This study was time-limited, spanning about

a month and a half with three trainings and two data collection dates. Future studies should increase the time spent on training, the frequency of trainings, or both. The present research aimed to answer an understudied question about the effectiveness of different kinds of mindfulness trainings on students; although the current study was unsuccessful in identifying differences, future researchers should continue this type of research using different trainings or an increased amount of training, potentially using mindfulness in multiple classes a day.

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Sparks, S. D. (2017). Teaching students to de-stress over tests: Some districts are taking steps to help students better cope with test anxiety and other stresses of school. Education Week, 36(32), 11–14.

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Sport Specialization and Injury Risk in NAIA Athletes

ACKNOWLEDGEMENTS

I would like to thank God first and foremost for carrying me through all the hardship and growth throughout all of college and the Honors Program especially. I would also like to thank Dr. Long for his support and guidance throughout the entire process of this project, trying to accomplish it, finding a problem with the design, and then redoing the process again. I would also like to thank the Honors Program for guidance and funding. Finally, I would like to thank my friends and family for all of their support, especially Rachel Shepard, who throughout this process both distracted and focused me at different times.

ABSTRACT

Background

Sport specialization is defined as intense year-round training in a single sport while excluding other sports. Though some studies have supported a relationship between increased levels of sport specialization and injury risk, others have contradicted this. Previous literature has also suggested that sport specialization levels increase dramatically throughout high school, though this hypothesized increase and possible relationship between sport specialization and injury risk has not been investigated in posthigh school athletes at the NAIA level.

Methods

This study aimed to investigate the possible relationship between sport specialization and injury risk, as well as how sport specialization levels change throughout college. A questionnaire was distributed online to 251 undergraduate NAIA athletes, and participants were assessed according to their levels of specialization using a three-point scale. The injury history of participants was also gathered and compared to their level of specialization.

Results

The data were analyzed using correlational tests, showing a significant increase in specialization and a R2 value of 0.94 between injury frequency and level of specialization, though there were not enough unspecialized athletes to investigate a relationship between sport specialization and injury risk with regards to unspecialized athletes vs. specialized athletes.

Conclusion

It is difficult to draw conclusions regarding a relationship between sport specialization and injury risk. However, the increase in both specialization and injury rates within the levels of specialization shows the need for further research into both sport specialization and injury risk, as well as research into NAIA athletes specifically.

INTRODUCTION

Studies have indicated that sport specialization can lead to an increased risk of injury in athletes compared to non-specialized athletes (Bell et al., 2016; Hall et al., 2015; Post et al., 2017). However, other studies contradict this claim (Frome et al., 2019), indicating no link between sport specialization and injury rates. These studies indicate that additional research is needed to determine the extent of a possible link between sport specialization and injury rates. Studies have also shown that specialization increases

with age throughout high school (Post et al., 2017). It is likely that specialization continues to increase throughout college.

Research on specialization has been conducted on elite Division I athletes regarding the prevalence and effects of sport specialization (Post et al., 2017), but no research has been conducted that explores specialization in NAIA athletes. This is a significant gap, as approximately 60,000 college athletes compete at this level. In addition, the NAIA is comparable in terms of the skill level of its participants to the Division III level, which itself holds another 188,000 athletes. The NAIA and Division III together account for approximately 70,000 more athletes than the Division I level, making this a significant body of athletes to examine that have been neglected in previous research.

Given the correlation between sport specialization, age, and injury rates in Division I athletes, it is likely that the same increased trend of both specialization and injury rates studied in research involving Division I and high school athletes will be observed in NAIA athletes. The extent of this hypothesized increase and its comparison to injury rates among elite athletes at the collegiate level is unknown. The aim of this study is to assess the percentage of highly specialized athletes at a NAIA university in Illinois and determine if there is a correlation between high levels of sport specialization and injury risk in NAIA athletes. This paper will examine the concept of sport specialization, its context, and previous and related research on the topic. The importance of this current research project, its results and limitations, and further areas to explore will also be discussed.

LITERATURE REVIEW

Concept

Sport specialization is defined as intense, year-round training in a single sport while excluding other sports (Jayanthi et al., 2015). Specialization is thought to increase injury rates in highly specialized athletes compared to non-specialized athletes, though this relationship has only been studied in high school, elite college, and among professional athletes. The primary type of injuries caused by sport specialization are overuse injuries, which are defined as damage and pain caused by repetitive movement and overuse (Niams Health Information on Sports Injuries, 2022). The current theory explaining the prevalence of this type of injury among highly specialized athletes is that such athletes are more likely to repeat the same motions over and over again, wearing down specific joints and eventually resulting in injury.

Non-specialized athletes are believed to be less susceptible to overuse injury because the multiple sports they play often use different motions, allowing their joints time to rest and heal after repeating a motion many times over an athletic season. For example, a player who plays baseball for part of the year may make significant use of the elbow joints. If that player is not specialized, they may then spend another p ortion

of the year playing soccer, which makes less use of the elbow joints and allows time for healing, thus preventing overuse injury. Acute injuries, generally defined as a severe injury with a sudden onset, such as a torn ACL or broken bone, are also more likely in highly specialized athletes (Wilhelm et al., 2017). The researchers noted that pinpointing one specific cause for increased acute injuries is extremely difficult but theorized that specializing early may cause athletes to fail to develop sound functional movement patterns, increasing the risk of acute injuries.

The ultimate goal of this research is to give coaches and athletic directors the information necessary to create and improve training programs to reduce injuries. This research helps to show the dangers of over-specialization and could be used to help stress the importance of variety for athletes to avoid specialization and reduce injuries.

Context

There have been relatively few studies regarding the relationship between sport specialization and injury risk. Most studies have been on high school age or younger athletes and have found that increasing levels of sport specialization increased the risk of injury in athletes, especially overuse injuries.

In one study, Hall et al. (2015) studied the effects of sport specialization, specifically on knee injuries, in adolescent females. They used a retrospective survey and medical diagnoses and examinations from registered physicians to determine the specific injury caused. The researchers found that sport specialization increased the risk of some, but not all, of the injuries they tested for. Injuries and conditions such as Sinding Larsen Johansson/patellar tendinopathy, Osgood Schlatter disease, and general patellofemoral pain showed an increased risk due to sport specialization, but other injuries/ conditions such as Fat Pad, Plica Trauma, Pes Anserine Bursitis, and IT Band Tendonitis showed no difference between highly specialized and non-specialized athletes. The study authors coordinated with physicians to help confirm and diagnose injuries, removing recall bias from their study.

In another study, Jayanthi et al. (2015) demonstrated the effect of sport specialization on injury rates by using a questionnaire on 1,190 pre-college athletes to determine if sport specialization was associated with an increased risk of injuries, especially overuse injuries. They also developed a three-point survey to identify the athletes’ degree of specialization, which was adapted for use in this study. Jayanthi et al. found that athletes with overuse injuries were 1.9 times more likely to be highly specialized and 1.45 time more likely to be injured in general when compared to moderate and low specialized athletes. Highly specialized athletes did not have a greater risk of acute injuries, though the researchers believed more research is needed to both confirm these findings and determine the exact reasons behind them, as other factors may be influencing the data gathered. One strength of the study is that it did not require a great amount of resources or coordination with physicians

or medical records, though this may have allowed recall bias from the participants to skew the data.

Other studies have observed a particular school or athletic team for an extended period of time, noting the specialization levels of athletes and recording injuries as they occur. Bell et al. (2016) studied the prevalence of sport specialization in two high schools, one large and one small, by following athletic teams for one year and reviewing their responses to a survey regarding injury rates with a certified athletic trainer. They found that athletes from the smaller school were more likely to be in the low specialization group (43%) than the medium (32%) or high specialization group (25%) than the larger school (low, 26%; medium, 26%; high, 48%). As a secondary goal however, the researchers found that highly specialized athletes were more than twice as likely to report knee and hip overuse injuries. Though this study was limited by the small sample size (302 athletes), it shows the effects of sport specialization in high school athletes.

In another study, McGuine et al. (2017) demonstrated how sport specialization affected lower extremity injury (LEI) rates in 1,544 high school athletes. The researchers collected data by first using a questionnaire to determine the athletes’ level of specialization and injury history and then by staying in contact with the athletic trainers of those athletes who reported any LEI injuries sustained by the athletes during each sport season over one school year. The study found that players classified as moderately specialized had 50% higher incidence of LEIs, and high specialized athletes had an 85% higher incidence rate than athletes classified as low specialization.

Though this type of study is more accurate, it has several major limitations. The first of these is adequate sample size. It is very difficult to gather a large enough sample size to achieve statistical significance while closely monitoring several groups to ensure accuracy. Researchers must also spend significant time observing each group, which can be challenging since overuse injuries take a long time to develop. Given this challenge, I decided to conduct a survey-based study and control for recall bias by asking athletes to list only injuries they experienced during their college and high school athletic career.

Besides the limitations of any potential study on specialization and injury, there are also contradicting studies that indicate that sport specialization actually has no effect on injury rates in athletes. One notable example is the study done by Frome et al., who surveyed 2,099 elite male soccer athletes between the ages of seven and seventeen to determine if there was a relationship between sport specialization and injury history (Frome et al., 2019). They found no significant difference between specialized and unspecialized athletes regarding likelihood to have experienced a past lower extremity overuse injury (31.8% injury rate among specialized athletes versus a 34.6% injury rate among non-specialized athletes). Moreover, they discovered that specialized athletes had an approximately 20% less chance of reporting any type of previous injury than unspecialized athletes.

Frome et al. noted the discrepancy of their data compared to other studies and suggested that it could have resulted from their study’s focus on a single sport, sex, and competitive level. This may be especially significant, as Frome et al. studied male soccer players and other studies have shown that female athletes are more likely to specialize and have high training volumes (Post et al., 2017), which also increases injury risk (Bell et al., 2018; Post et al., 2017). Frome et al. also suggested that studying soccer specifically may have resulted in a phenomenon that is not applicable to other sports. Finally, the researchers also suggested that other sports such as tennis and gymnastics, where more technical motions are required, could lead to an increased risk of injury compared to soccer, which has a greater variety of movement patterns. These various considerations led the authors of the study to conclude that there was a significant need for more research on the relationship between sport specialization and injury risk.

There is also a significant lack of studies assessing sport specialization in athletes after high school. A small number of studies involving professional and Division I athletes found a positive correlation between sport specialization and injury rates (Rugg et al., 2018; Wilhelm et al., 2017), but all these studies suffer from a small sample size due to the elite status (and therefore scarcity) of possible participants. The exclusivity of Division I by definition is not representative of most athletes. A study by Post et a l. (2016) on Division I athletes found that specialization increased throughout high school by 24.2% from 9th to 12th grade. It seems likely to assume that collegiate athletes would be more specialized than high school athletes, but without further study it’s impossible to conclude whether this is unique to students who go on to play for elite Division I teams.

Few studies have examined NAIA athletes or Division III athletes, for example, though these populations contain a larger sample size and the athletes examined would represent a wider segment of the population. This population may also differ from Division I athletes in average levels of specialization. Studies have shown an average of at least 80% of Division I athletes to be specialized (Post et al., 2016), though the prevalence of specialization in NAIA and Division III athletes is unknown and would likely influence injury rates. In the current study, a small Midwest liberal art university, consisting of approximately 500 athletes, was surveyed to determine the prevalence of sport specialization and a possible relationship between sport specialization and injury risk.

Importance

Current studies on sport specialization are not representative of the majority of college athletes, who continue to compete after high school in the NAIA or Division III level. Together, these organizations represent a group of 248,000 athletes. The current study aims to fill the gap in knowledge on NAIA athletes regarding sport specialization and injury rates by surveying a subsample of this previously overlooked population. If the

relationship between sport specialization and injury risk is shown to be significant in NAIA athletes, coaches and athletes will be able to make more informed decisions regarding training volume and specialization levels. This work also could inspire further studies to investigate safer ways for athletes to train. Finally, this study will help clarify the possible relationship between sport specialization and injury risk as a whole. A related outcome of this study will also be to determine if NAIA athletes continue to become more specialized after high school.

METHODS

Participants

Participants were selected based upon their status as both a student and athlete at an NAIA university. To be eligible for the study, participants had to qualify as both a full-time student and be on a varsity or junior varsity athletic team for the university. Approximately 500 athletes received the survey, soliciting 255 responses in total and 251 responses used in the survey.

Materials

Sport specialization was assessed using a scale developed by Jayanthi et al. This scale uses three questions, marked with an asterisk in appendix A, to determine participants’ level of specialization. A positive response to each of these questions adds one point to the athlete’s level of specialization, with zero points indicating very low/no specialization and three points a very high level of specialization. The Jayanthi scale was selected due to several factors. Firstly, it has been used in several other reliable studies (Post et al., 2017: Wilhelm et al., 2017; McGuine et al., 2017). It is also a brief survey, which is intended to boost participation by lowering time commitment. The survey was also simple and straightforward, allowing it to be easily adapted to college athletes.

Procedure

Participants received an email briefly describing the study and requesting their participation. Participants could then follow the link to an online survey and opt into the study to complete the survey. Participants were given the option to enter their email address for the chance to win one of five $10 Amazon gift cards. A reminder email was sent twice to students whose link had not been used after at two and four weeks after the initial email. This method of soliciting responses obtained responses from approximately 50% of eligible student athletes.

In addition to data regarding specialization, the survey solicited responses regarding injury history. This allowed percentages of highly specialized athletes with injuries to be compared to medium and low specialized athletes with injuries. The data from the survey were then analyzed using R2 values to assess the correlation between sport

specialization and injured athletes. Outliers in the data were analyzed and controlled for using the Grubbs test for outliers to exclude very unlikely answers that greatly affected the data. Some responses were also excluded due to extremely unlikely/impossible answers, such as participants reporting having practiced over 168 hours per week.

RESULTS

Participants included 251 undergraduate student athletes at a NAIA university in the Midwest, recruited using an online survey sent to their school email address. Figure 1 shows the number of participants for each sport. Thirty-four participants reported specializing before age 14, 118 reported specializing after age 14 (i.e., during high school or college). Figure 2 shows the sports played in high school by the participants.

Sport Specialization and Injury Rates

Participants in this study had an average specialization level of 2.375 on the adapted Jayanthi scale. Data on other collegiate level athletes using this scale of specialization is not available. However, there was a large increase of 0.475 when compared to precollege athletes in the original Jayanthi study. Overall, an increase in injury a ssociated with specialization was observed (Figure 3), with nearly half (40.5%) of participants reporting sports related injuries in the past year that prevented them from playing. Participants with a specialization score of 1 (low specialization) had an injury frequency rate of 25% (n=24). Participants with a score of 2 (medium specialization)

There is a similar distribution of athletes across sports when compared to Figure 1. However, though the proportions are similar, there are almost twice as many athletes in most sports as compared to Figure 1. For example, the number of track and field athletes decreased from 109 in high school to 60 in college. This drop in numbers indicates an increase in levels of specialization.

Participants’ injury history was compared to their level of specialization, showing a positive correlation between injury frequency and level of specialization, with the exception of level zero. Level zero is likely an outlier due to the low sample size. The number of participants for each level is indicated above each bar.

had an injury frequency rate of 31.5% (n= 92). Participants with a score of 3 (high specialization) had an injury frequency rate of 48% (n= 127). Though a higher injury frequency rate of 40% among non-specialized athletes (n=5) was observed, small sample size may have skewed the data for that group. When assessed in aggregate, specialization was positively correlated with injury risk (Figure 4; R2 = 0.94 when participants with a score of 0 were excluded due to the low sample size). This trend seems to support the expected relationship between specialization and injury. With the exception of participants with a score of 0, injury frequency increased as specialization increased. The small sample size, which was only 2% of the total sample size, is unlikely to represent unspecialized athletes as a whole or even athletes in this local population. The small sample size also causes a large degree of uncertainty. If one more participant in that sample had reported an injury, the injury frequency would have increased by 20%.

Prevalence of Sport Specialization

According to the survey, in 2021, study participants spent an average of 13.2 hours in practice, 0.68 hours in intramurals, and 6.4 hours in competitive sports each week. The average age that participants began playing sports was approximately eight years old. A large majority of participants agreed with a statement asking if they believed they spent seventy-five percent of their practice time training for one sport, further supporting the prevalence of sport specialization in NAIA athletes.

Participated In High School And College

Data were gathered using responses to the survey. The data shows a large decrease in sports participated in from high school to college, indicating a large increase in specialization.

More than half also agreed that learning a new skill at practice was more important than having fun with their friends at practice, that they would not play sports if they did not receive a scholarship, and that they miss opportunities to hang out with friends because of sports related obligations. A majority of athletes reported that they had quit other sports to focus on one sport. The average age of quitting other sports for those athletes was approximately fifteen years old, showing that average NAIA athlete specialized early in high school. Most athletes also said that one main sport was more important than other (Table 1). The participants spent an average of 10.7 months per year training for sports and six months per year competing in a sport. Overall, this data shows that the average NAIA athlete would classify as highly specialized and helps underscore the prevalence of specialization in NAIA athletes.

Table 3: Responses To Survey Questions

Data were gathered using responses to the survey. Overall, the data indicates high levels of specialization in the surveyed population, highlighting the prevalence of sport specialization.

“I spend more than 75% of my training in only one organized sport.”

“At practice, I think learning something new or improving my skill is more important than having fun with my friends.”

“I would play sports in college even if I did not receive a scholarship for doing so.”

“I often miss spending time with my friends that don’t play sports because I have practice or competition (games, matches, tournaments, etc.) for my sport.”

DISCUSSION

This study assessed the prevalence of sport specialization and its relationship with injury rates in NAIA athletes. As expected, both a significant increase in specialization after high school and a positive correlation between specialization and injury rates was found. This supports the research hypotheses and agrees with the current literature on sport specialization and injury rates in Division I athletes. It also demonstrates a high degree of specialization among NAIA athletes, highlighting the importance of this work and indicating the need for further studies on sport specialization in NAIA athletes. The study also found a positive correlation between injury frequency and specialization within low, medium, and highly athletes.

The results of this study may be limited by several factors. First, the study was distributed online, which may have affected the data’s accuracy. The study may also be limited by the aspect of self-reporting used to gather data. The survey tool used appears to be capable of improvement, with some of the questions leading to incorrect classifications of athletes. One possible way the survey tool could be improved is by clarifying the questions and making them more specific and clearer to the participants. By clarifying some of the questions and allowing for multiple options rather than a binary choice, the survey’s effectiveness would increase. For example, one question asked if athletes had quit other sports to focus on one main sport and used a positive response

to indicates specialization. The problem with this is that some athletes had never played multiple sports to begin with, and therefore truthfully gave a negative response. This is a large flaw in the survey tool, as those athletes that had never played multiple sports are likely more specialized than athletes that had played multiple sports at some point.

Further studies could modify the existing survey tool or create a new tool to be used for college or high school athletes by examining and accounting for the challenges presented above. A potential improved survey based on the tool used in this study and incorporating the improvements suggested is presented in Appendix C. Further studies could also address weaknesses in the tool by connecting directly with medical professionals treating student athletes for the organization, removing possible recall bias from the data. By accessing student medical data with permission, medical records could be compared to the survey results to give an accurate comparison between injury history and level of specialization.

Based on the data from this study, there are strong implications for coaches and athletes at the NAIA level regarding how athletes train and compete in order to minimize injuries. These implications include being aware of the effects of year-long training on athletes, the importance of playing multiple sports, and understanding the prevalence of specialization and its consequences. There are also implications for high school athletes due to the large increase in specialization after high school. High school athletes, coaches, or parents may want to plan how the athlete will prepare for or avoid a large increase in specialization after high school. If students, parents, and coaches are made aware of the strong positive correlation between specialization and injury, and the fact that this holds even for non-Division I schools, then new training regimens could be developed to minimize injury risk, and athletes could make a more informed choice when considering specializing for one sport.

REFERENCES

Bell, D. R., Lang, P. J., McLeod, T. C. V., McCaffrey, K. A., Zaslow, T. L., Mckay, S. D., & Group, Pr. S. S. I. (2018). Sport specialization is associated with injury history in youth soccer athletes. Athletic Training and Sports Health Care 10(6), 241–246.

Bell, D. R., Post, E. G., Trigsted, S. M., Hetzel, S., McGuine, T. A., & Brooks, M. A. (2016). Prevalence of sport specialization in high school athletics: A 1-year observational study. The American Journal of Sports Medicine 44(6), 1469–1474.

Buckley, P. S., Bishop, M., Kane, P., Ciccotti, M. C., Selverian, S., Exume, D., Emper, W., Freedman, K. B., Hammoud, S., Cohen, S. B., & Ciccotti, M. G. (2017). Early singlesport specialization: A survey of 3090 high school, collegiate, and professional athletes. Orthopaedic Journal of Sports Medicine 5(7).

Frome, D., Rychlik, K., Fokas, J., Chiampas, G., Jayanthi, N., & LaBella, C. (2019). Sports specialization is not associated with greater odds of previous injury in elite male youth soccer players. Clinical Journal of Sport Medicine 29(5), 368–373.

Hall, R., Foss, K. B., Hewett, T. E., & Myer, G. D. (2015). Sport specialization’s association with an increased risk of developing anterior knee pain in adolescent female athletes. Journal of Sport Rehabilitation 24(1), 31–35.

Jayanthi, N. A., LaBella, C. R., Fischer, D., Pasulka, J., & Dugas, L. R. (2015). Sportsspecialized intensive training and the risk of injury in young athletes: A Clinical CaseControl Study. The American Journal of Sports Medicine 43(4), 794–801.

McGuine, T. A., Post, E. G., Hetzel, S. J., Brooks, M. A., Trigsted, S., & Bell, D. R. (2017). A prospective study on the effect of sport specialization on lower extremity injury rates in high school athletes. The American Journal of Sports Medicine 45(12), 2706–2712.

Post, E. G., Bell, D. R., Trigsted, S. M., Pfaller, A. Y., Hetzel, S. J., Brooks, M. A., & McGuine, T. A. (2017). Association of competition volume, club sports, and sport specialization with sex and lower extremity injury history in high school athletes. Sports Health 9(6), 518–523.

Post, E. G., Thein-Nissenbaum, J. M., Stiffler, M. R., Brooks, M. A., Bell, D. R., Sanfilippo, J. L., Trigsted, S. M., Heiderscheit, B. C., & McGuine, T. A. (2017). High school sport specialization patterns of current division I athletes. Sports Health 9(2), 148–153.

Rugg, C., Kadoor, A., Feeley, B. T., & Pandya, N. K. (2018). The effects of playing multiple high school sports on national basketball association players’ propensity for injury and athletic performance. The American Journal of Sports Medicine 46(2), 402–408.

U.S. Department of Health and Human Services. (2022, March 3). Niams health information on sports injuries. National Institute of Arthritis and Musculoskeletal and Skin Diseases.

Wilhelm, A., Choi, C., & Deitch, J. (2017). Early sport specialization: effectiveness and risk of injury in professional baseball players. Orthopaedic Journal of Sports Medicine 5(9)

Original Jayanthi Survey

1. What sports do you compete in during the course of the year?

2. During the last six months, in a typical week, how many hours per week did you spend in gym class? Playing sports just for fun? Playing competitive sports?

3. How old were you when you started to participate in competitive sports?

4. Have you had an injury in the last six months related to sports that has prevented you from playing sports?

5. Would you agree or disagree with the following statement: “I spend more than 75% of my training in only one organized sport”?

6. Do you agree with the following statement: “At practice, I think learning something new or improving my skill is more important than having fun with my friends”?

7. Do you agree with the following statement: “I often miss spending time with my friends that don’t play sports because I have practice or competition (games, matches, tournaments, etc.) for my sport”?

*8. Have you quit other sports to focus on one main sport? If yes, how old were you when you quit other sports?

*9. Is one main sport more important to you than any other?

10. Do you regularly travel to other states to compete in your sport?

*11. How many months per year do you train for one main sport?

12. How many months per year do you compete in one main sport?

13. On a scale of 1-10 mark how much you enjoy playing sports.

* Answers to these “sports specialization questions” form the basis for determining the athlete’s degree of sports specialization.

APPENDIX B

Adapted Jayanthi Survey

1. What sports do you compete in during the course of the year?

2. What sports did you compete in during high school?

3. During the last six months, in a typical week, how many hours per week did you spend in practice? Playing intramurals? Playing competitive sports?

4. How old were you when you started to participate in competitive sports?

5. Have you had an injury in the last six months related to sports that has prevented you from playing sports?

6. Would you agree or disagree with the following statement: “I spend more than 75% of my training in only one organized sport”?

7. Do you agree with the following statement: “At practice, I think learning something new or improving my skill is more important than having fun with my friends”?

8. Do you agree with the following statement: “I would play sports in college even if I did not receive a scholarship for doing so”?

9. Do you agree with the following statement: “I often miss spending time with my friends that don’t play sports because I have practice or competition (games, matches, tournaments, etc.) for my sport”?

*10. Have you quit other sports to focus on one main sport? If yes, how old were you when you quit other sports?

*11. Is one main sport more important to you than any other?

12. Do you regularly travel to other states to compete in your sport?

*13. How many months per year do you train for one main sport?

14. How many months per year do you compete in one main sport?

15. On a scale of 1-10, indicate how much you enjoy playing sports.

* Answers to these “sports specialization questions” form the basis for determining the athlete’s degree of sports specialization.

Improved Jayanthi Survey

1. What sports do you compete in during the course of the year?

2. During the last six months, in a typical week, how many hours per week did you spend in gym class? Playing sports just for fun? Playing competitive sports?

3. How old were you when you started to participate in competitive sports?

4. Have you had an injury in the last six months related to sports that has prevented you from playing sports?

5. Would you agree or disagree with the following statement: “I spend more than 75% of my training in only one organized sport”?

6. Do you agree with the following statement: “At practice, I think learning something new or improving my skill is more important than having fun with my friends”?

7. Do you agree with the following statement: “I often miss spending time with my friends that don’t play sports because I have practice or competition (games, matches, tournaments, etc.) for my sport”?

*†8. Have you competed in more than one sport?

*9. Have you quit other sports to focus on one main sport? If yes, how old were you when you quit other sports?

*10. Is one main sport more important to you than any other?

11. Do you regularly travel to other states to compete in your sport?

*12. How many months per year do you train for one main sport?

13. How many months per year do you compete in one main sport?

14. On a scale of 1-10, indicate how much you enjoy playing sports.

* Answers to these “sports specialization questions” form the basis for determining the athlete’s degree of sports specialization.

† Added question to improve accuracy of the survey

Effects of the Tax Cuts and Jobs Act of 2017 on Nonprofits’ Charitable Contributions

ACKNOWLEDGEMENTS

Thank you to the Olivet Nazarene University Honors Program for giving me the opportunity to complete this research. Thank you to Prof. Nielsen, my research mentor, for his unceasing encouragement and dedication, his expertise, and his excitement for the research process. I would also like to thank Dr. Williams for providing me with the original idea for this project and for his enthusiasm for accounting. Thank you to my fellow cohort members for their support and friendship throughout this experience, as well as my Honors professors for their teachings that have been crucial to my Olivet experience. Thank you to my roommates and family who have believed in me and cheered me on to see this project to completion.

ABSTRACT

Background

The Tax Cuts and Jobs Act (TCJA), passed in 2017, significantly altered individuals’ taxes for all filing statuses, notably increasing the standard deduction. By nearly doubling the standard deduction, it considerably decreased those individuals choosing the itemized deduction. Due to this, it may impact charitable contributions, a major source of nonprofits’ revenues. Prior studies projected a variety of stances regarding changes in giving levels due to the TCJA. This study attempted to determine the overall effect of the TCJA on nonprofits, as well as within the National Taxonomy of Exempt Entities (NTEE) major groups Education, Health, Human Services, Public and Societal Benefit, and Religion Related.

Methodology

This study utilized paired t-tests to determine if a statistically significant positive difference in charitable contributions occurred post-TCJA, meaning more individuals gave to nonprofits prior to the TCJA than after the TCJA. Additionally, ANOVA analysis was used to determine if the TCJA’s effects were widespread or more material to a selected segment.

Results

All t-tests performed evidenced no statistically significant positive difference in charitable contributions before and after the TCJA. All ANOVA tests were rejected at the 99% level of confidence, showing that there were statistically significant differences in charitable contributions between groups.

Conclusion

The findings of the t-tests are in alignment with prior research that indicated no change in overall giving as a result of the TCJA (Hodge, 2020). Though the researchers failed to reject all of the t-tests, the Public and Societal Benefit tests displayed p-values less than .01, which may evidence greater contributions post-TCJA in that sector. Following the ANOVA analysis, post hoc tests identified one nonprofit within each NTEE group that received significantly greater contributions. These nonprofits were Teach for America, American Lebanese Syrian Associated Charities Inc/St. Jude Children’s Research Hospital, Feeding America, The Rotary Foundation, and Samaritan’s Purse.

Keywords: Tax Cuts and Jobs Act, TCJA, charitable contributions, standard deduction, itemized deduction, charitable contribution deduction.

INTRODUCTION

In 2017, the Tax Cuts and Jobs Act (TCJA) was enacted and involved major tax code changes. As a result, it drastically reduced the number of taxpayers claiming itemized deductions, which therefore reduced the number of taxpayers eligible to claim the charitable contribution deduction. Nonprofits specifically have been concerned about the impacts of the TCJA on the charitable contributions they receive, because they rely on these donations in order to pursue their organizational purpose. In 2016, donations made up 15.1% of nonprofit sector revenues (NCCS Project Team, 2020). However, nonprofits that provide services that are public in nature have a greater dependence on charitable contributions than other revenue sources when compared to nonprofits providing private services (Fischer et al., 2011). These donations are prone to instability from donor preferences, the current economy, and tax code changes like the TCJA (Tuckman & Chang, 1991). High incidences of instability can cause nonprofits to be financially vulnerable (Tuckman & Chang, 1991). Thus, the volatility of charitable contributions can greatly impact a nonprofit’s operations. Though these concerns were expressed prior to the passing of the TCJA, the true impacts could not be discovered until a few years post-TCJA. Given this, this study sought to examine the effects of the TCJA on charitable contributions as reported as revenue on the nonprofit organizations’ tax returns known as Form 990. This research will determine if a statistically significant positive difference in donation levels exists between pre- and post-TCJA within varying nonprofit sectors and whether statistical differences in charitable contributions exist between the individual nonprofit organizations.

REVIEW OF LITERATURE

The following sections will describe the Tax Cuts and Jobs Act (TCJA) and its effects on the standard deduction. Additionally, the following sections will provide further details on current experts’ estimated extent of impact on nonprofits’ charitable contributions as caused by the TCJA.

The Tax Cuts and Jobs Act

The TCJA is the largest change in the U.S. tax code since the Tax Reform Act of 1986. It was passed in December 2017 and will remain in effect from 2018-2025. A significant change under the TCJA was the reduction of the top marginal individual tax rate from 39.6% to 37%, along with a decrease in the other tax brackets (Gale et al., 2018). In addition, the TCJA enacted a flat 21% corporate income tax rate (Gale et al., 2018). Several itemized deductions for individuals, including those for state and local taxes (SALT) and miscellaneous itemized de ductions, changed drastically. Under the

TCJA, SALT deductions are limited to $10,000 annual for both single and married filing jointly filers (Gale et al., 2018). The TCJA completely removed the deduction for miscellaneous itemized deductions, such as unreimbursed employee expenses (Gale et al., 2018). Thus, this landmark legislation considerably altered both the individual and corporate tax codes.

Effects of the Tax Cuts and Jobs Act on the standard deduction

One provision of the TCJA was an increase in the standard deduction that nearly doubled the previous deduction amount for most taxpayers. The standard deduction reduces taxable income by a select amount defined yearly by the Internal Revenue Service (IRS) (US Department of Treasury, 2021b). This deduction amount changes periodically due to inflation and can increase depending on filing status, age, and disability (US Department of Treasury, 2021b). Itemized deductions, however, depend on taxpayer behavior and can increase due to changes in items such as state and local tax paid, medical expenses paid, and charitable contributions made (US Department of Treasury, 2021b). Taxpayers benefit from claiming the standard deduction only if the standard deduction amount is greater than the itemized deductions they are eligible to claim.

Under the TCJA, the standard deduction for single filers increased in 2018 from $6,350 to $12,000. The deduction for married couples filing jointly also increased from $12,700 to $24,000. Due to this increase, many itemizing taxpayers shifted to claim the standard deduction because itemized deductions no longer benefited them if they could claim a higher deduction using the standard deduction. Gleckman (2018) projected that in 2018, 21 million taxpayers would no longer itemize deductions, representing a decrease of 11.5%. A similar projection for 2018 showing an 11.9% decrease of itemizing households was made by Gale et al. (2018). For the 2019 tax year, an overwhelming majority, 87.6%, of individual returns used the standard deduction (U.S. Department of Treasury, 2021a). This increased use of the standard deduction further impacts itemized deductions, such as the charitable contribution deduction, by decreasing their use.

Charitable contribution deduction

The charitable contribution deduction began in 1917 and has changed very little since. A charitable contribution is defined by the IRS as “a donation or gift to, or for the use of, a qualified organization. It is voluntary and is made without getting, or expecting to get, anything of equal value” (U.S. Department of Treasury, 2019). However, this tax benefit is only available to taxpayers who itemize deductions. Schedule A, which lists taxpayers’ itemized deductions, is not required when claiming the standard deduction, making the tax benefit of charitable contributions only available on tax returns where taxpayers itemize deductions. Claiming the charitable contribution deduction

effectively lowers the taxpayer’s tax liability and the cost of the donation. For example, a taxpayer in the 32% tax bracket who makes a $100 donation to a qualifying 501(c) (3) organization would reduce their tax liability by $32 and decrease the cost of their donation to $68. Thus, both nonprofits and itemizing taxpayers benefit when making charitable contributions.

High-income taxpayers have traditionally been the main users of the deduction since its inception. The deduction was implemented to prevent taxpayers from hoarding their after-tax income as a result of high income tax rates during World War I (Brill, 2019). An increase in the charitable contribution deductibility was passed in 1952, which increased the adjusted gross income (AGI) limitation from 15% of income to 20% (Crandall-Hollick, 2020). This increase occurred due to the introduction of the standard deduction a few years earlier (Crandall-Hollick, 2020). Congress was concerned that the standard deduction would lead to a decrease in charitable contributions made, so the AGI limitation was increased (Crandall-Hollick, 2020). Another large wave of tax code change occurred in the 1980s. President Reagan emphasized voluntarism to Americans, which was evidenced by the Economic Recovery Act of 1981 that allowed taxpayers claiming the standard deduction to deduct up to 25% of charitable contributions up to a maximum of $100 in donations, later increased to $300 in 1984 (Duquette, 2019). During this time, the top income tax bracket fell significantly (Duquette, 2019). Due to the lowered tax rate, the tax benefit for charitable contributions decreased. This caused charitable contributions by the top 0.1% of taxpayers to fall 50% from 1980 to 1990, evidencing the impact of tax code legislation on charitable giving (Duquette, 2019).

Charitable contributions under the Tax Cuts and Jobs Act

The significant change in tax code that was the TCJA resulted in many concerns, including the concern that nonprofits would see lower levels of contributions due to the change in standard deduction. The increase in the standard deduction effectively eliminates the tax benefit of charitable contributions for taxpayers who elect to take the standard deduction. Brill and Choe (2018) projected a decrease in charitable contributions by 4% because of the increase in the standard deduction, equating an estimated loss in charitable donations from individuals of $16.3 billion to $17.2 billion. Ricco (2018), on the other hand, projected a 5.1% reduction in charitable giving under the TCJA. Fidelity Charitable (2019) surveyed taxpayers who reported donating less to nonprofits in 2018 than in 2017, of which 48% cited doing so due to the TCJA, indicating the effect of tax code changes on taxpayers’ giving habits. Additionally, empirical results indicate that taxpayers in the highest and lowest tax brackets are more likely to donate under the new legislation than taxpayers in other brackets (Nickerson, 2018). However, other estimations projected increases in total charitable giving, including a rise of 4.2% in 2019 following the implementation of the TCJA (Giving

USA, 2020). Furthermore, an analysis of 2019 U.S. charitable giving data found individual giving remained at a steady $310 billion donated and did not decrease from 2018 (Hodge, 2020). Overall, there are studies that support and refute the notion that charitable contributions will decrease due to the increase of the standard deduction from the historic TCJA. This study attempted to resolve this ambiguity by comparing the charitable contributions before and after the TCJA.

METHODS

Sampling

This study examined fifty U.S.-based nonprofits. These nonprofits are of varying revenue sizes and are segmented by National Taxonomy of Exempt Entities (NTEE) organizational major groups. NTEE major group codes are used by the IRS to classify tax-exempt organizations according to their purposes. Within each major group studied, ten nonprofits were selected. The NTEE groups analyzed were Education, Health, Human Services, Public and Societal Benefit, and Religion Related. These NTEE major groups were selected to provide a broad representation of different nonprofit sectors. The total contributions and total contributions less government contributions were examined for these five groups. Nonprofits’ charitable contributions received were collected from Form 990, which is the organization’s tax return. The use of Form 990 provides a more accurate depiction of changes in giving trends because unclaimed contributions made by taxpayers who do not itemize deductions are included in nonprofits’ revenues on the Form 990. Form 990 from 2016-2019 were selected to examine two years pre- and post-TCJA. Charitable contribution revenue was gathered from GuideStar, a database storing Form 990 and other financial information of over 2.5 million nonprofit organizations, and the IRS.

Statistical process

An average of charitable contributions received was calculated by individual nonprofits for pre-TCJA years 2016 and 2017 and the same time-frame post-TCJA, filing years 2018 and 2019. These pre- and post-TCJA averages were used to perform paired differences t-tests on each of the NTEE segmentations. Paired t-tests were utilized to determine if a significant change in charitable contributions has occurred post-TCJA within each segmentation, which would indicate more giving before the TCJA than after (see Appendix A.1). The use of t-tests allows for the comparison of the magnitudes of impact the TCJA made on individual NTEE groups studied. In order to determine if one segment received a significantly different amount of contributions, an analysis of variance (ANOVA) was conducted on each segment. The supplemental analysis using ANOVA was selected to determine if the TCJA’s effects were widespread across each segmentation or were more material to a selected segment (see Appendix A.2).

RESULTS

Paired differences t-tests

Paired t-tests were performed for each NTEE major group and were segmented by total contributions and non-government contributions. Table 1 shows the t-statistic and p-value results of each test. All tests performed failed to reject the null, evidencing no significant difference in contributions before and after the TCJA. Even though both Public and Societal Benefit tests appear to be significant, this is irrelevant for the upper tail t-test performed (see Appendix B).

ANOVA

An ANOVA was performed on each NTEE group for total contributions received and non-government contributions. Results indicated to reject the null hypotheses (see Appendix A.2) in all tests at the 99% level (see Table 2). Additionally, post hoc tests were used to determine what nonprofits received significant contributions, indicating one nonprofit in each category received greater amounts of charitable contributions. The groups that were significant were Teach for America, American Lebanese Syrian Associated Charities Inc/St. Jude Children’s Research Hospital, Feeding America, The Rotary Foundation, and Samaritan’s Purse (see Appendix C).

DISCUSSION

This study sought to determine if a statistically significant positive difference in donation levels exists between pre- and post-TCJA within varying nonprofit sectors, as well as whether statistical differences in charitable contributions exist between the

Significance at the 0.99 level is denoted with ***, at the 0.95 level with **, and at the 0.9 level with *.

individual nonprofit organizations. The t-tests in this study were used to determine if a significant change in charitable contributions has occurred post-TCJA within NTEE sectors. The t-tests conducted failed to reject the null hypothesis, illustrating that there was not a significant difference in charitable contributions pre- and postTCJA (see Appendix A.1). Though the Public and Societal Benefit t-tests displayed low p-values of 0.0088 and 0.0112, these results are not significant due to the onetail, upper-tail nature of these tests. Additionally, the t-statistic did not exceed the critical value, so we failed to reject the hypotheses. This may be evidence of more contributions after the TCJA for Public and Societal Benefit nonprofits, which could indicate that charitable contributions increased post-TCJA. This is consistent with prior research that indicated increases in charitable giving or no change at all (Giving USA, 2020; Hodge, 2020).

The ANOVAs in this study determined if one segmentation received a significantly different amount of contributions. The ANOVAs performed rejected the null hypothesis of every test at the 99% level (see appendix A.2). Post hoc Tukey tests were performed on each ANOVA to determine which nonprofits received significant contributions within the NTEE group (see appendix C). Within each test, one nonprofit received significantly greater contributions. The nonprofits that received these significant amounts were Teach for America, American Lebanese Syrian Associated Charities Inc/St. Jude Children’s Research Hospital, Feeding America, The Rotary Foundation, and Samaritan’s Purse. These results indicate that nonprofits within an NTEE group did receive varying levels of charitable contributions from 2016-2019 and did not experience a consistent level of giving, meaning that the TCJA did have an effect on charitable contributions.

Future research would benefit from an increased data pool that contains more nonprofits overall, as well as a longer period of time studying pre- and post-TCJA. As the TCJA was newly implemented at the start of this study, there was limited data available to analyze the true effects of the TCJA. Two years pre- and post-TCJA is a short time frame that is not representative of other factors affecting charitable contributions, such as donors bunching several years’ worth of donations into a single tax year. Additionally, due to the extensions available for Form 990 filings, many nonprofits could not be included in this study because Form 990 was not available to the public for the time period studied. An increase in the number of nonprofits studied would allow for a larger sample that may indicate more trends within varying NTEE major groups.

CONCLUSION

This study focused on the overall impact of the TCJA on the charitable contributions reported by nonprofits, as well as the impact on five NTEE major groups. The analysis from this study evidenced no statistically significant positive difference in charitable contributions pre- and post-TCJA. However, the Public and Societal Benefit NTEE major group was indicative of increased charitable contributions post-TCJA. Additionally, this study determined that Teach for America, American Lebanese Syrian Associated Charities Inc/St. Jude Children’s Research Hospital, Feeding America, The Rotary Foundation, and Samaritan’s Purse received statistically significant greater contributions within their respective NTEE groups, indicating that specific nonprofits within each NTEE group received more contributions relative to the others. These findings are important to nonprofits, as charitable contributions make up 15.1% of nonprofit sector revenues (NCCS Project Team, 2020). Additionally, these findings may impact future tax code legislation by examining its unintended effects on nonprofits. Further studies may provide additional information about these trends in order to determine long-term effects of the TCJA on nonprofits’ charitable contributions.

REFERENCES

Brill, A., & Choe, D. (2018). Charitable giving and the Tax Cuts and Jobs Act. Washington: American Enterprise Institute for Public Policy Research.

Crandall-Hollick, M. L. (2020, June 26). The charitable deduction for individuals: A brief legislative history. Congressional Research Service.

Duquette, N. J. (2019). Founders’ fortunes and philanthropy: A history of the U.S. charitable-contribution deduction. Business History Review, 93(3), 553–584.

Fidelity Charitable. (2019). Adapting to tax reform: How donors responded and their plans for the future.

Fischer, R. L., Wilsker, A., & Young, D. R. (2011). Exploring the revenue mix of nonprofit organizations: Does it relate to publicness. Nonprofit and Voluntary Sector Quarterly, 40(4), 662–681.

Gale, W. G., Gelfond, H., Krupkin, A., Mazur, M. J., & Toder, E. J. (2018, June 13). Effects of the Tax Cuts and Jobs Act: A preliminary analysis. Tax Policy Center.

Giving USA. (2020, June 16). Giving USA 2020: Charitable giving showed solid growth, climbing to $449.64 billion in 2019, one of the highest years for giving on record. Giving USA Foundation.

Gleckman, H. (2018, January 8). 21 Million taxpayers will stop taking the charitable deduction under the TCJA. Tax Policy Center.

Hodge, S. A. (2020, June 22). Latest data shows that the Tax Cuts and Jobs Act didn’t dampen charitable giving. Tax Foundation.

NCCS Project Team. (2020, June). The nonprofit sector in brief 2019. Urban Institute: National Center for Charitable Statistics. https://nccs.urban.org/publication/nonprofitsector-brief-2019#the-nonprofit-sector-in-brief-2019

Nickerson, M. A. (2018). First look at the Tax Cuts and Jobs Act: Impact on individual charitable giving. The CPA Journal, 88(4), 10-12.

Ricco, J. (2018). TCJA projected to lower 2018 charity giving by $22 billion. Penn Wharton Budget Model.

Tuckman, H. P., & Chang, C. F. (1991). A methodology for measuring the financial vulnerability of charitable nonprofit organizations. Nonprofit and Voluntary Sector Quarterly, 20(4), 445–460.

U.S. Department of Treasury. Internal Revenue Service. (2019, March 12). Publication 526: Charitable contributions. (Cat. No. 15050A).

U.S. Department of Treasury. Internal Revenue Service. (2021a). Publication 1304: Statistics of income – 2019 Individual income tax returns. (Cat. No. 63338H).

U.S. Department of Treasury. Internal Revenue Service. (2021b, February 22). Things taxpayers should know when choosing between standard and itemized deductions.

Paired t-test hypotheses

Education total contributions

H o : There is no statistically significant positive difference in the total charitable contributions with the Education group before and after the TCJA.

H a : There is a statistically significant positive difference in the total charitable contributions within the Education group before and after the TCJA.

Education non-government contributions

H o : There is no statistically significant positive difference in the non-government charitable contributions with the Education group before and after the TCJA.

H a : There is a statistically significant positive difference in the non-government charitable contributions within the Education group before and after the TCJA.

Health total contributions

H o : There is no statistically significant positive difference in the total charitable contributions with the Health group before and after the TCJA.

H a : There is a statistically significant positive difference in the total charitable contributions within the Health group before and after the TCJA.

Health non-government contributions

H o : There is no statistically significant positive difference in the non-government charitable contributions with the Health group before and after the TCJA.

H a : There is a statistically significant positive difference in the non-government charitable contributions within the Health group before and after the TCJA.

Human Services total contributions

H o : There is no statistically significant positive difference in the total charitable contributions with the Human Services group before and after the TCJA.

H a : There is a statistically significant positive difference in the total charitable contributions within the Human Services group before and after the TCJA.

Human Services non-government contributions

H o : There is no statistically significant positive difference in the non-government charitable contributions with the Human Services group before and after the TCJA.

H a : There is a statistically significant positive difference in the non-government charitable contributions within the Human Services group before and after the TCJA.

Public and Societal Benefit total contributions

H o : There is no statistically significant positive difference in the total charitable contributions with the Public and Societal Benefit group before and after the TCJA.

H a : There is a statistically significant positive difference in the total charitable contributions within the Public and Societal Benefit group before and after the TCJA.

Public and Societal Benefit non-government contributions

H o : There is no statistically significant positive difference in the non-government charitable contributions with the Public and Societal Benefit group before and after the TCJA.

H a : There is a statistically significant positive difference in the non-government charitable contributions within the Public and Societal Benefit group before and after the TCJA.

Religion Related total contributions

H o : There is no statistically significant positive difference in the total charitable contributions with the Religion Related group before and after the TCJA.

H a : There is a statistically significant positive difference in the total charitable contributions within the Religion Related group before and after the TCJA.

Religion Related non-government contributions

H o : There is no statistically significant positive difference in the non-government charitable contributions with the Religion Related group before and after the TCJA.

H a : There is a statistically significant positive difference in the non-government charitable contributions within the Religion Related group before and after the TCJA.

ANOVA hypotheses

Education total contributions

H o : There are no statistically significant differences in the mean total charitable contributions between the groups in Education.

H a : At least two of the mean total charitable contributions in the Education group differ.

Education non-government contributions

H o : There are no statistically significant differences in the mean non-government charitable contributions between the groups in Education.

H a : At least two of the mean non-government charitable contributions in the Education group differ.

Health total contributions

H o : There are no statistically significant differences in the mean total charitable contributions between the groups in Health.

H a : At least two of the mean total charitable contributions in the Health group differ.

Health non-government contributions

H o : There are no statistically significant differences in the mean non-government charitable contributions between the groups in Health.

H a : At least two of the mean non-government charitable contributions in the Health group differ.

Human Services total contributions

H o : There are no statistically significant differences in the mean total charitable contributions between the groups in Human Services.

H a : At least two of the mean total charitable contributions in the Human Services group differ.

Human Services non-government contributions

H o : There are no statistically significant differences in the mean non-government charitable contributions between the groups in Human Services.

H a : At least two of the mean non-government charitable contributions in the Human Services group differ.

Public and Societal Benefit total contributions

H o : There are no statistically significant differences in the mean total charitable contributions between the groups in Public and Societal Benefit.

H a : At least two of the mean total charitable contributions in the Public and Societal Benefit group differ.

Public and Societal Benefit non-government contributions

H o : There are no statistically significant differences in the mean non-government charitable contributions between the groups in Public and Societal Benefit.

H a : At least two of the mean non-government charitable contributions in the Public and Societal Benefit group differ.

Religion Related total contributions

H o : There are no statistically significant differences in the mean total charitable contributions between the groups in Religion Related.

H a : At least two of the mean total charitable contributions in the Religion Related group differ.

Religion Related non-government contributions

H o : There are no statistically significant differences in the mean non-government charitable contributions between the groups in Religion Related.

H a : At least two of the mean non-government charitable contributions in the Religion Related group differ.

T-test results

The reported results indicated to fail to reject the null hypothesis. This shows that there was no significant difference in total charitable contributions pre- and post-TCJA within the Education NTEE group studied.

The reported results indicated to fail to reject the null hypothesis. This shows that there was no significant difference in non-government charitable contributions pre- and post-TCJA within the Education NTEE group studied.

Table B.3: Results Of The Health Total Contributions T-Test

The reported results indicated to fail to reject the null hypothesis. This shows that there was no significant difference in total charitable contributions pre- and post-TCJA within the Health NTEE group studied.

Table B.4:

Of The Health Non-Government Contributions T-Test

The reported results indicated to fail to reject the null hypothesis. This shows that there was no significant difference in non-government charitable contributions pre- and post-TCJA within the Health NTEE group studied.

Total Contributions T-Test

The reported results indicated to fail to reject the null hypothesis. This shows that there was no significant difference in total charitable contributions pre- and post-TCJA within the Human Services NTEE group studied.

The reported results indicated to fail to reject the null hypothesis. This shows that there was no significant difference in non-government charitable contributions pre- and post-TCJA within the Human Services NTEE group studied.

Table B.7: Results Of The Public And Societal Benefit Total Contributions T-Test

The reported results indicated to fail to reject the null hypothesis. The results may appear significant, but because this study was a one tail, upper tail test, the results are not statistically significant. This shows that there was no significant difference in total charitable contributions pre- and post-TCJA within the Public and Societal Benefit NTEE group studied.

Table B.8: Results Of The Public And Societal Benefit Non-Government Contributions T-Test

The reported results indicated to fail to reject the null hypothesis. The results may appear significant, but because this study was a one tail, upper tail test, the results are not statistically significant. This shows that there was no significant difference in non-government charitable contributions pre- and post-TCJA within the Human Services NTEE group studied.

Table B.9: Results Of The Religion Related Total Contributions T-Test

The reported results indicated to fail to reject the null hypothesis. This shows that there was no significant difference in total charitable contributions pre- and post-TCJA within the Religion Related NTEE group studied.

Table B.10: Results Of The Religion Related Non-Government Contributions T-Test

The reported results indicated to fail to reject the null hypothesis. This shows that there was no significant difference in non-government charitable contributions pre- and post-TCJA within the Religion Related NTEE group studied.

ANOVA test results

Table C.1: Results Of Education Total Contributions ANOVA

The reported results indicated to reject the null hypothesis at the 99% confidence level. This shows that there are statistically significant differences in the total charitable contributions between the nonprofits of the Education group.

Table C.2: Results Of Education Non-Government Contributions ANOVA

The reported results indicated to reject the null hypothesis at the 99% confidence level. This shows that there are statistically significant differences in the non-government charitable contributions between the nonprofits of the Education group.

Table C.3: Results Of Health Total Contributions ANOVA

The reported results indicated to reject the null hypothesis at the 99% confidence level. This shows that there are statistically significant differences in the total charitable contributions between the nonprofits of the Health group.

Table C.4: Results Of Health And Non-Government Contributions ANOVA

The reported results indicated to reject the null hypothesis at the 99% confidence level. This shows that there are statistically significant differences in the non-government charitable contributions between the nonprofits of the Health group.

Table C.5: Results Of Human Services Total Contributions ANOVA

The reported results indicated to reject the null hypothesis at the 99% confidence level. This shows that there are statistically significant differences in the total charitable contributions between the nonprofits of the Human Services group.

Table C.6: Results Of Human Services Non-Government Contributions ANOVA

The reported results indicated to reject the null hypothesis at the 99% confidence level. This shows that there are statistically significant differences in the non-government charitable contributions between the nonprofits of the Human Services group.

Table C.7: Results Of Public And Societal Benefit Total Contributions ANOVA

The reported results indicated to reject the null hypothesis at the 99% confidence level. This shows that there are statistically significant differences in the total charitable contributions between the nonprofits of the Public and Societal Benefit group.

Table C.8: Results Of Public And Societal Benefit Non-Government Contributions ANOVA

The reported results indicated to reject the null hypothesis at the 99% confidence level. This shows that there are statistically significant differences in the non-government charitable contributions between the nonprofits of the Public and Societal Benefit group.

Table C.9: Results Of Religion Related Total Contributions ANOVA

The reported results indicated to reject the null hypothesis at the 99% confidence level. This shows that there are statistically significant differences in the total charitable contributions between the nonprofits of the Religion Related group.

Table C.10: Results Of Religion Related Non-Government ANOVA

The reported results indicated to reject the null hypothesis at the 99% confidence level. This shows that there are statistically significant differences in the non-government charitable contributions between the nonprofits of the Religion Related group.

The nonprofits included in this Education grouping were First Book (E1), National Merit Scholarship Corporation (E2), Harlem Children’s Zone, Inc. (E3), ScriptEd Inc (E4), Teach for America Inc (E5), The New Teacher Project, Inc. (E6), Kahn Academy Inc (E7), The Education Trust (E8), Olivet Nazarene University Foundation (E9), and American Library Association (E10). Teach for America received a significantly greater level of contributions in all comparisons to nonprofits within the Education group.

The nonprofits included in this Education grouping were First Book (E1), National Merit Scholarship Corporation (E2), Harlem Children’s Zone, Inc. (E3), ScriptEd Inc (E4), Teach for America Inc (E5), The New Teacher Project, Inc. (E6), Kahn Academy Inc (E7), The Education Trust (E8), Olivet Nazarene University Foundation (E9), and American Library Association (E10). Teach for America received a significantly greater level of contributions in all comparisons to nonprofits within the Education group.

ANOVA.

The nonprofits included in this Health grouping were American Lebanese Syrian Associated Charities Inc/St. Jude Children’s Research Hospital (H1), American Cancer Society Inc (H2), Upper Midwest Organ Procurement Organization Inc/Lifesource (H3), Chronic Disease Fund Inc (H4), Patient Access Network Foundation (H5), March of Dimes Foundation (H6), American Heart Association Inc (H7), Mental Health America Inc (H8), Duane Dean Behavioral Treatment Health Center (H9), and The Helen Wheeler Center for Community Mental Health (H10). American Lebanese Syrian Associated Charities Inc/St. Jude Children’s Research Hospital received a significantly greater level of contributions in all comparisons to nonprofits within the Health group.

The nonprofits included in this Health grouping were American Lebanese Syrian Associated Charities Inc/St. Jude Children’s Research Hospital (H1), American Cancer Society Inc (H2), Upper Midwest Organ Procurement Organization Inc/Lifesource (H3), Chronic Disease Fund Inc (H4), Patient Access Network Foundation (H5), March of Dimes Foundation (H6), American Heart Association Inc (H7), Mental Health America Inc (H8), Duane Dean Behavioral Treatment Health Center (H9), and The Helen Wheeler Center for Community Mental Health (H10). American Lebanese Syrian Associated Charities Inc/St. Jude Children’s Research Hospital received a significantly greater level of contributions in all comparisons to nonprofits within the Health group.

ANOVA.

The nonprofits included in this Human Services grouping were The Salvation Army World Service Office (HS1), Goodwill Industries International Inc (HS2), Feeding America (HS3), National Coalition Against Domestic Violence (HS4), Covenant House (HS5), National Able Network Inc (HS6), Unbound (HS7), Meals on Wheels America (HS8), Compassionate Ministries Center of Hope (HS9), and Kankakee County Coalition Against Domestic Violence (HS10). Feeding America received a significantly greater level of contributions in all comparisons to nonprofits within the Human Services group.

The nonprofits included in this Human Services grouping were The Salvation Army World Service Office (HS1), Goodwill Industries International Inc (HS2), Feeding America (HS3), National Coalition Against Domestic Violence (HS4), Covenant House (HS5), National Able Network Inc (HS6), Unbound (HS7), Meals on Wheels America (HS8), Compassionate Ministries Center of Hope (HS9), and Kankakee County Coalition Against Domestic Violence (HS10). Feeding America received a significantly

of contributions in all comparisons to nonprofits within the Human Services group.

The nonprofits included in this Public and Societal Benefit grouping were Plan International USA Inc (PSB1), Local Initiatives Support Corporation (PSB2), American Civil Liberties Union Foundation Inc (PSB3), United Way Worldwide (PSB4), The Urban Institute (PSB5), Vera Institute of Justice Inc (PSB6), The Rotary Foundation of Rotary International (PSB7), Disabled American Veterans (PSB8),

and

(PSB9), and

The nonprofits included in this Public and Societal Benefit grouping were Plan International USA Inc (PSB1), Local Initiatives Support Corporation (PSB2), American Civil Liberties Union Foundation Inc (PSB3), United Way Worldwide (PSB4), The Urban Institute (PSB5), Vera Institute of Justice Inc (PSB6), The Rotary Foundation of Rotary International (PSB7), Disabled American Veterans (PSB8),

(PSB9), and

ANOVA.

The nonprofits included in this Religion Related grouping were Samaritan’s Purse (R1), Educational Media Foundation (R2), One Collective (R3), World Vision Inc (R4), Habitat for Humanity International Inc (R5), Prison Fellowship Ministries (R6), Young Life (R7), Food for the Poor Inc (R8), South Pointe Youth for Christ (R9), and Warm Blankets Children’s Foundation Inc (R10). Samaritan’s Purse received a significantly greater level of contributions in all comparisons to nonprofits within the Religion Related group.

The nonprofits included in this Religion Related grouping were Samaritan’s Purse (R1), Educational Media Foundation (R2), One Collective (R3), World Vision Inc (R4), Habitat for Humanity International Inc (R5), Prison Fellowship Ministries (R6), Young Life (R7), Food for the Poor Inc (R8), South Pointe Youth for Christ (R9), and Warm Blankets Children’s Foundation Inc (R10). Samaritan’s Purse received a significantly greater level of contributions in all comparisons to nonprofits within the Religion Related group.

Analysis of Botulinum Toxin A and Interacting Proteins in Skeletal Muscle Cells: An Investigation into the Mechanisms of Botulinum Toxin A as a Treatment for Chronic Exertional Compartment Syndrome

ACKNOWLEDGEMENTS

I would like to thank my mentor, Dr. Harper, for her support, encouragement, and guidance throughout this research process. Thanks also to Dr. Heyen for his assistance and advice on my project, especially with statistical analysis. I would also like to thank the Pence-Boyce Undergraduate Summer Research Program, Honors Program, and Chemistry and Geosciences Department of Olivet Nazarene University for providing financial support for my research. Finally, thank you to Dr. Case, Dr. Stipp, Dr. Ingram, Dr. Schurman, Dr. Sharda, and Dr. Vander Schaaf for investing in me and this project, as well as my roommates, Megan Drenth and Rachel Meyer, and friends in Cohort 12 for their solidarity and motivation throughout my time in the ONU Honors Program.

ABSTRACT

Background

Chronic exertional compartment syndrome (CECS) is a condition in which muscle tissue expands against the surrounding fascia during activity and is compressed along with the nerves and blood vessels within the muscle compartment, leading to abnormally high intracompartmental pressure (ICP) and debilitating pain. Treatment typically includes fasciotomy, which results in significant levels of CECS recurrence; however, botulinum toxin A (BoNT-A) injection has recently been seen to decrease both ICP and pain through an unknown mechanism with little to no recurrence.

Methods

In this study, PyRosetta was used to model the probability of docking interaction between BoNT-A light or heavy chain and enzymes cyclooxygenase-1 (COX-1), cyclooxygenase-2 (COX-2), prostaglandin E2 receptor 4 (EP4), endothelial nitric oxide synthase (eNOS), and inducible nitric oxide synthase (iNOS). Subsequently, myoblasts (HSkM) were treated with BoNT-A and assayed based on PyRosetta predicted interactions.

Results

The EP4/BoNT-A heavy chain combination was found to have reaction scores most comparable to known interactions of BoNT-A in neural cells. In accordance with this finding, levels of cyclic adenosine monophosphate (cAMP), a downstream effector of EP4, consistently increased in myoblasts treated with BoNT-A.

Conclusion

Altogether, these data uncover an area of future research in determining the interaction of BoNT-A and the EP4 pathway in muscle cells, as well as the implications this may have on CECS and its treatment.

Keywords: chronic exertional compartment syndrome, CECS, botulinum toxin A, BoNT-A, Botox, prostaglandin E2 receptor 4, EP4, cyclooxygenase-1, COX-1, cyclooxygenase-2, COX-2, endothelial nitric oxide synthase, eNOS, inducible nitric oxide synthase, iNOS, cyclic adenosine monophosphate, cAMP, human skeletal muscle myoblast, PyRosetta

INTRODUCTION

Chronic exertional compartment syndrome (CECS) is a condition in which muscle tissue expands against the surrounding fascia during activity and is compressed along with the nerves and blood vessels within the muscle compartment leading to abnormally

high intracompartmental pressure (ICP). Proposed causes of CECS include ischemia, muscle hypertrophy, and fascial resistance or hypersensitivity, although the triggers are unknown. This condition is characterized by debilitating pain and cramping of the affected muscles during exercise that is relieved quickly with rest, and diagnosis is based on occurrence of these symptoms and high ICP measurements shortly post-activity. Typical treatment involves cessation of activity or fasciotomy, both of which have high levels of CECS recurrence that vary significantly between various studies but are often 20-50% (Wuellner, et al., 2017).

REVIEW OF LITERATURE

BoNT-A as a treatment for chronic exertional compartment syndrome

Botulinum toxin A (BoNT-A) has recently been demonstrated to reduce symptoms of CECS and ICP levels when injected into the affected muscles, but the mechanisms behind this treatment are not well understood. In one study, fifteen out of sixteen patients diagnosed with CECS and treated with BoNT-A had reduced pain and normal ICP during activity three to nine months post-injection. Proposed causes for symptom relief include reduced release of acetylcholine (causing muscle atrophy), reduction of muscle hypotonia, and/or induced muscle relaxation leading to increased blood flow to the affected muscles (Isner-Horobeti, et al., 2013). Another case study demonstrated long-lasting relief of severe CECS symptoms with BoNT-A injection, with ultrasound showing no signs of muscle atrophy or texture changes (Baria & Sellon, 2016). This challenges previously accepted assumptions that ICP decrease is due to atrophy of the injected muscles and indicates that another mechanism of BoNT-A is present, potentially at the cellular, neural, or vascular level. Finally, a case study of CECS in the hand demonstrated reduced ICP, full strength recovery, and decreased hypertrophy fifteen months post-injection. The mechanisms of BoNT-A hypothesized were amyotrophy due to reduction of acetylcholine (ACh) release, improved blood supply to limit muscle ischemia, and analgesic action (Orta, et al., 2018). However, not all of these mechanisms would decrease ICP, so the researchers suggested that these effects might be combined with each other or work in addition to other mechanisms. Thus, the exact mechanisms of BoNT-A on CECS symptom management remains unclear and highlights areas for further research.

Mechanisms of botulinum toxin type A

BoNT-A is most understood through its application at the neuromuscular junction. In normal activity of the neuromuscular junction, muscle contraction is initiated as synaptic vesicles filled with ACh are released via exocytosis across the nerve-muscle synapse. In order for this to occur, synaptic vessels are loaded and docked onto the presynaptic membrane, where they are primed by ATP so that they can undergo calciumregulated exocytosis. Soluble NSF (N-ethylmaleimide sensitive factor) attachment protein (SNAP) receptors (SNAREs) are essential to transporting the vesicle membrane

near the plasma membrane, and dissociation of the SNARE complex by binding of SNAPs and NSF is necessary for this process to be carried out (Dolly, 2003).

When neural cells are treated with BoNT-A, the heavy chain of BoNT-A binds to distinct G-protein coupled receptors (GPCRs) on the cell membrane. This allows the toxin to enter the cytosol, where the SNAP-25 protein is cleaved by the light chain of BoNT-A, which contains a selective, zinc-dependent protease. Therefore, the release of ACh from peripheral nerves is inhibited. This blockage of ACh is typically long-lasting and highly selective, and beneficial effects may last three to six months depending on the condition being treated (Dolly, 2003). However, the effect of BoNT-A outside of the neuromuscular junction is not well understood or researched, although other potential applications include its antinociceptive and anti-inflammatory effects (Aoki, 2005; Matak, et al., 2019). As discussed previously, researchers who have treated CECS with BoNT-A have proposed interactions between BoNT-A and skeletal muscle at the cellular, neural, or vascular levels. These interactions may replace or occur in addition to the interaction at the neuromuscular junction (Baria & Sellon, 2016; Isner-Horobeti, et al., 2013; Orta, et al., 2018).

Relevant pathways and receptors within skeletal muscle

Since BoNT-A interacts at the neuromuscular junction through a GPCR, it is possible that BoNT-A may interact with other GPCRs present on skeletal muscle cells and cause downstream effects or enter the cell and affect intracellular proteins. Many prostaglandins (PGs), which are synthesized through the cyclooxygenase (COX) pathway, as well as endothelial and inducible nitric oxide synthase (eNOS and iNOS, respectively) are influenced by GPCRs and directly involved in relief and regulation of the symptoms of CECS through regulation of blood flow, inflammation, muscle cell expansion, and nociception (Liu, et al., 2016; Mortensen, González-Alonso, et al., 2007; Mortensen, Nyberg, et al., 2009; Sun & Ye, 2012). Prostaglandin E2 receptor 4 (EP4), in particular, is a PG receptor and GPCR that can cause inflammation and be involved in inflammatory diseases and responses, and it activates adenyl cyclase (AC) to upregulate cyclic adenosine monophosphate (cAMP) within the cell. Increases in cAMP can lead to hypertrophic responses of myofibers in skeletal muscle, an issue seen in patients with CECS (Berdeaux & Stewart, 2012; Yokoyama, et al., 2013).

Additionally, novel studies of BoNT-A treatment on chronic visceral pain through injection to peripheral organs have demonstrated inhibition of COX-2 and EP4 expression. When prostatitis was induced in rats, injection of BoNT-A led to an 89.4% decrease of COX-2 expression in the prostate and a 90.5% decrease in the L6 spinal cord (Chuang, et al., 2008). A similar study of BoNT-A injection after induced cystitis in rats found that COX-2 expression was reduced by 77.8%, 61.7%, and 54.8%, whereas EP4 expression was reduced by 56.8%, 26.9%, and 84.2% in the bladder, L6 spinal cord, and S1 spinal cord, respectively. This indicates that BoNT-A

inhibits COX-2 and EP4 expression in visceral organs and the L6 and S1 spinal cord and suppresses inflammation and hyperactivity (Chuang, et al., 2009). Another study of BoNT-A treatment on human myoblasts and fibroblasts in vitro demonstrated that BoNT-A modulated the cell cycle and transcriptome within myoblasts through direct interactions between the toxin and different cellular surface receptors, intracellular targets, and signaling pathways (Zanotti, et al., 2018).

Altogether, these studies suggest it is reasonable to hypothesize that upregulation of cAMP, EP4, COX-2 and similar proteins such as COX-1, iNOS, or eNOS could cause symptoms of CECS and could therefore be modulated by direct BoNT-A treatment if BoNT-A can bind to surface protein receptors such as EP4 and inhibit further signaling and activation of cAMP or intracellular proteins such as COX-1, COX-2, iNOS, or eNOS.

Effects of BoNT-A on human skeletal muscle cells in vitro

Therefore, the present study aimed to determine if COX-1, COX-2, eNOS, iNOS, or EP4 are likely to interact directly with BoNT-A, by creating and analyzing protein models using protein-protein and protein-ligand docking programs from PyRosetta, a computational chemistry program. These results indicated an interaction between BoNT-A heavy chain and EP4, which was subsequently confirmed as levels of cAMP in human skeletal muscle myoblasts increased after treatment with BoNT-A.

METHODS

Computational analysis

In order to analyze probability of interaction between BoNT-A light chain (LC) or heavy chain (HC) and COX-1, COX-2, eNOS, iNOS, or EP4, protein and ligand structures were first obtained from the Protein Data Bank (PDB). The specific PDB IDs used were 2IMC for BoNT-A LC (Silvaggi, et al. 2007), 2VUA for BoNT-A HC (Stenmark, et al. 2008), 6Y3C for COX-1 (Miciaccia, et al., 2021), 5IKR for COX-2 (Orlando & Malkowski, 2016), 4D1O for eNOS (Li, et al., 2014), 2NSI for iNOS (Li, et al., 1999), and 7D7M for EP4 (Nojima, et al., 2021). BoNT-A LC was combined with COX-1, COX-2, iNOS, and eNOS based on their location within the cell cytoplasm and the mechanism of BoNT-A LC within the cell, whereas BoNT-A HC was combined with EP4 based on its location within the cell membrane and the mechanism of BoNT-A HC to bind and allow entrance into the cell. BoNT-A LC was also combined with synaptosome associated protein 25 (SNAP25) (PDB ID: 3DDA; Kumaran, et al., 2008), and BoNT-A HC was combined with ganglioside co-receptor GT1B (PDB ID: 2VU9; Stenmark, et al., 2008). These combinations have known interactions in vivo, allowing them to be used as control comparisons for output data. Using a virtual machine enabled with PyRosetta (PyRosetta4.Release.python38.inux.

release-275; Chadbury, et al., 2010) and PyMOL (The PyMOL Molecular Graphics System, Version 2.0, n.d.), proteins were combined into a joint file, cleaned from additional H2O or interfering ligand molecules, and filled with any missing amino acid residues. Finally, joint files were run through protein-protein (for all combinations including BoNT-A LC) or protein-ligand (for all combinations including BoNT-A HC) docking programs from PyRosetta software.

Human skeletal myoblast differentiation culture

After thawing, human skeletal myoblasts (HSkM, Cat. no. A12555 & A11440; Gibco) were differentiated in Dulbecco’s Modified Eagle Medium (Gibco) supplemented with 2% horse serum (Gibco), plated on an untreated 24-well plate with a density of 240,000 cells per well, and incubated at 37°C with 5% CO2. After 48 hours, HSkM cells became elongated, indicating their differentiation was complete and allowing further treatments to proceed.

Preparation of botulinum toxin A dilutions

An original vial containing 100 IU of BoNT-A (Creative BioMart) was diluted with 5 mL of bacteriostatic 0.9% sodium chloride solution (Hospira) to a concentration of 20 IU/mL. Then, a serial dilution in differentiation medium was made to produce dilutions of 0, 0.24, 0.48, 1.2, 2.4, 4.8, 7.2, and 9.6 IU/mL, which corresponds to 0, 0.5, 1, 2.5, 5, 10, 15, or 20 IU BoNT-A per 106 cells, based on the dilutions tested in previous models (Zanotti et al., 2018).

Cytotoxic assessment with DAPI and PI fluorescence assay

After differentiation, cells were treated in triplicate with 0.5 mL per well of 0, 0.5, 1, 2.5, 5, 10, 15, or 20 IU per 106 cells, as prepared above. Cells were incubated at 37°C with 5% CO 2 for 24 hours, aspirated, stained with a solution containing 1 μL/1 mL 4’,6-diamidino-2-phenylindole (DAPI; ThermoFisher) and 1 μL/1 mL propidium iodide (PI; ThermoFisher) in 1X PBS, and incubated for 10 minutes before aspirating and washing twice with 1X PBS. Cells were imaged using a Nikon Ti-E Fluorescent Microscope and counted using cell counting software to determine cytotoxicity of treatments.

cAMP direct immunoassay

In order to investigate the effects of BoNT-A on EP4, the levels of cAMP in cells with or without BoNT-A treatment were analyzed through the cAMP Direct Immunoassay Kit (Colorimetric) (Cat. no. K371; BioVision). HSkM were differentiated, treated with either 0 IU (control cells) or 1 IU BoNT-A per 106 cells diluted in bacteriostatic 0.9% sodium chloride solution (Hospira) and differentiation medium as prepared above for the cytotoxicity assay, and incubated at 37 °C with 5% CO2 for 24 hours.

Medium was aspirated, and cells were treated with 50 μL of 0.1 M HCl per well and incubated at room temperature. Cells were scraped, collected, and centrifuged, and the supernatant was assayed directly. The standard cAMP curve and quantification of cAMP in samples was achieved following the protocol included in the kit.

Statistical analysis

Statistical analysis of cAMP concentration data was performed using an F-test and Student’s t-test assuming equal variances on Microsoft Excel. Through these tests, both one-tailed and two-tailed p-values were obtained and compared.

RESULTS

Computational data indicates HC-EP4 interaction

Computational data outputs were received as total weighted scores measured in Rosetta Energy Units (REU). These scores had values similar to exothermic and endothermic reaction energy values: more negative values indicated a more stable and therefore more likely interaction between the molecules tested. Each combination tested gave three to six scores based on different docking positions. Therefore, an average of

Combinations are between either BoNT-A light chain (LC) or heavy chain (HC) and SNAP25, EP4, GT1B, iNOS, eNOS, COX2, or COX1 based on their location within the cell. The lowest total weighted score was taken from each combination. If this score was negative, the log of the absolute value was taken. For positive scores, the negative log was taken. Therefore, in this graph, a more positive score corresponds with a more probable docking position and interaction.

these values would not be relevant, as each value represented a distinct position of interaction and only the most probable position of interaction should be considered. The lowest value from each combination was compared in order to determine the most likely interaction to be further tested. As seen in Figure 1, the total weighted score of HC-EP4 was most comparable to the controls, LC-SNAP25 and HC-GT1B, whereas other test combinations were significantly different from the controls. The lowest values for control combinations were -585.193 REU and -128.517 REU for LC-SNAP25 and HC-GT1B, respectively, and the lowest value for test combinations was -677.325 REU for HC-EP4 (Table 1). Consequently, EP4 was chosen to be further investigated through its secondary effector, cAMP, during in vitro testing.

Cytotoxicity assessment of HSkM treated with BoNT-A

Cytotoxicity was determined through fluorescence microscope imaging, as seen in Figure 2. In Figure 3, BoNT-A concentrations of 0-5 IU per 106 cells were seen to be most consistent at causing minimal cytotoxicity, whereas concentrations of 10-20 IU per 106 cells were more variable. Average cytotoxicity of cells treated with 1 IU BoNT-A was 0.997 ± 1.421%, whereas average cytotoxicity of cells treated with 20 IU BoNT-A was 80.5 ± 10.5%.

cAMP direct immunoassay

PyRosetta’s predicted interaction between BoNT-A HC and EP4 was investigated in vitro through activity assessment of cAMP, a secondary messenger of EP4. Based on high cell viability, a treatment of 1 IU BoNT-A per 106 cells was selected for analysis with the cAMP direct immunoassay. Control samples had cAMP concentrations of 3.498 fmol/well and 2.665 fmol/well for an average of 3.081 ± 0.589 fmol/well, whereas the two wells containing samples treated with 1 IU BoNT-A had cAMP

Concentrations of 0, 0.5, 1, 2.5, 5, 10, 15, and 20 IU BoNT-A per 106 cells were incubated at 37°C with 5% CO2 for 24 hours, aspirated, stained with DAPI and PI in 1X PBS, and incubated for 10 minutes before aspirating and washing with 1X PBS. Cells were imaged using a Nikon Ti-E Fluorescent Microscope and counted to determine cytotoxicity of treatments. Results shown indicate the mean ± standard deviation of cell death for each treatment.

cAMP standards were used to form a standard curve and regression line. The equation of this line was used to determine cAMP concentration in control and 1 IU BoNT-A treated cells based on OD 450 nm readings, and these data points are also displayed. Data points in light gray represent the standard cAMP curve, whereas the data point in dark gray represents the average cAMP in control cells, 3.081 ± 0.589 fmol/well, and the data point in medium gray represents the average cAMP in cells treated with 1 IU BoNT-A, 8.000 ± 2.090 fmol/well. Results shown indicate the mean ± standard deviation of OD 450 nm readings for each standard, control, and treatment.

concentrations of 9.478 fmol/well and 6.522 fmol/well for an average of 8.000 ± 2.090 fmo l/well, showing a consistent increase in cAMP (Fig. 4). In a two-sample F-test for variances, Fstat < Fcrit, indicating that the variances were equal. According to the one-tail two-sample t-test assuming equal variances, p = 0.04, indicating that cAMP concentration in c ells treated with 1 IU BoNT-A was significantly higher than cAMP concentration in control cells.

DISCUSSION

The results of this research indicate that BoNT-A could likely be interacting with EP4 within HSkM, but the extent and mechanisms of this interaction are still unclear based on this data. Computational analysis suggests that BoNT-A HC and EP4 could have a stable interaction. Although previous data demonstrates that BoNT-A may reduce EP4 expression in the spinal cord and visceral organs (Chuang, et al., 2009), this is the first research to propose direct molecular interactions between EP4 and BoNT-A HC. In

contrast, high total weighted scores from BoNT-A LC and COX-1, COX-2, eNOS, and iNOS were significantly less stable. However, previous research indicates BoNT-A does affect COX-2 in vivo (Chuang, et al., 2008; Chuang, et al., 2009), so this data could instead imply either no interaction or a momentary, unstable interaction between these molecules. Additionally, these molecules could be affected indirectly, which was not investigated in this study. Finally, this data could also represent a context-dependent interaction, in which BoNT-A may only interact with these molecules under certain cellular conditions, such as the stress of exercise on muscle cells.

Data from the cAMP immunoassay suggests BoNT-A treatment correlates with increased cAMP within HSkM in vitro, but more research is needed to determine the significance of this increase, as well as whether different dilutions of BoNT-A result in different increases of cAMP. Because upregulation of cAMP can cause hypertrophy in skeletal muscle myofibers (Berdeax & Stewart, 2012), this data is surprising since BoNT-A treatment in vivo leads to reduced hypertrophy in patients with CECS (Baria & Sellon, 2016; Isner-Horobeti, et al., 2013; Orta, et al., 2018). Furthermore, it is unclear whether this increase is caused by activation of EP4 or by a different mechanism, as cAMP is involved with many cellular processes. Additionally, this study was limited by a small number of experimental samples, so future research should include a greater number of samples for clearer significance and meaning of results.

The specific interaction of BoNT-A with EP4 is a topic of further investigation regarding the mechanisms of BoNT-A within skeletal muscle. This could be achieved through similar experiments in EP4 knockout mice with cAMP monitoring, as well as experiments involving increased dosage of cAMP and symptom monitoring. Additionally, other studies involving BoNT-A’s effects in vivo have analyzed the expression of proteins after treatment in both the affected organs and spinal cord, as well as in individual cell transcriptomes (Chuang, et al., 2008; Chuang, et al., 2009; Zanotti, et a l., 2018). Therefore, analysis of mRNA and spinal cord protein expression in addition to tracking symptom management after affected skeletal muscle cells are treated with BoNT-A may provide more insight in determining its mechanism in relation to its therapeutic effects in treating CECS.

Finally, only normal HSkM were examined within this study. Since the mechanisms and progression of CECS in skeletal muscle is largely misunderstood, HSkM affected by CECS could interact with BoNT-A differently than normal HSkM. Thus, further research should include analysis and comparison of cAMP and EP4 expression in both normal and CECS-affected HSkM in order to explore CECS and the causes of this condition.

CONCLUSION

Overall, more data is needed to fully determine the mechanisms and effects of BoNT-A on HSkM in vitro, especially in regards to EP4 interaction and cAMP concentration.

Most importantly, however, the data from this study indicates BoNT-A may influence skeletal muscle cells outside of its effect at the neuromuscular junction through novel computational evidence of EP4 and BoNT-A HC molecular interaction, as well as increased levels of cAMP in HSkM treated with BoNT-A, with p = 0.04 in the one-tail t-test. Further investigation into the specific results of BoNT-A treatment on skeletal muscle can provide valuable implications to both the uses of BoNT-A as a treatment in a variety of diseases as well as the mechanisms of diseases such as CECS that observe symptom reduction through therapeutic uses of BoNT-A.

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Deepfake It Til You Make It: How To Make A Short Film

ACKNOWLEDGEMENTS

The success of this project is entirely due to the hard work and support of all those who are subsequently listed. Financial support was provided by the Olivet Nazarene University (ONU) Honors Program. Mentorship and guidance were provided by Dr. Heather McLaughlin, ONU Communication Department Chair. Filming equipment was supplied by the ONU Communication Department. Filming locations were generously offered by ONU and Alyssa Laidler. My film crew, both on and off set, consisted of Brady Jones and John Stuhlmacher. Special thanks to John for his incredible editing work. Credit goes to Drew Case for his stellar musicianship in writing the film, as well as Isaiah Clampitt and Eric Pendleton for providing their own music for the film. Cast and extras (in order of appearance) included Abriella Caravette, Andrew McBurnie, Michael Murray, Case Koerner, Autumn Bentz, Daria Caravette, Professor Deb Stafford, Heather Simpson, Sydni Gaskill, Simphiwe Bhebhe, John Stuhlmacher, Eric Pendleton, Brady Jones, Dr. Mark Frisius, Tyler Comfort, and Anne Whalen.

ABSTRACT

A recent development in the realm of computer technology is the deepfake. Deepfakes, which train a computer model to digitally superimpose one person’s face onto another body in a separate video, has its uses for good and for ill, with the unfortunate tendency to the latter. The vast majority of deepfakes are used for pornography, most commonly depicting female celebrities as the subjects. At the less notable level, it is also often used for revenge pornography. These aspects of deepfake technology are rarely discussed in mainstream media, which tends to focus on the less harmful uses, such as those for comedic celebrity impersonations or for beneficial uses in film. Based on the background research, this project created a short film addressing these issues within a fictional but compelling story with the intention of raising awareness among the public.

INTRODUCTION

The world of computer technology is constantly changing and adapting. Many changes are created with the intent to improve the lives of users, for practical or entertainment purposes. However, changes may cause harm. One such area is the field of deepfakes. Deepfakes are created by taking an image or video of a person’s face— most often a celebrity—and super-imposing it on the face and body of an actor. This results in a relatively convincing video of the original person doing and saying something they did not. Deepfakes are a growing industry in technology, with applications and ramifications increasing rapidly with changing technology. Sometimes celebrity deepfakes manifest as comedic videos, in which celebrities appear to be doing and saying things they have not. These can be a good tool for creating content without having direct access to a celebrity actor, or for possibly “resurrecting” an actor or individual who has died. A vast majority of deepfakes, however, are harmful in nature. As of 2019, nearly 96% of all deepfakes were categorized as non-consensual pornography, most often depicting female celebrities (Khalid, 2019). A common use in this category of deepfakes is revenge porn. Few people know the full effects of deepfake uses, which affects public perception and results in the lack of legislation regarding deepfakes. The topic of deepfakes is current and timely, providing a wide variety of story concepts. The purpose of this research project is to develop and create a short student film that exposes the widely unknown problems of deepfake videos, particularly in revenge pornography. The plot of the film revolves around a young college girl who falls victim to deepfake revenge porn from her ex-boyfriend. Since no one knows about deepfakes, the protagonist struggles to convince people the video is fake. With lack of legislation pertaining to deepfakes, there is also a struggle for her to get justice. This film conveys the issues surrounding deepfakes and revenge porn through the lens of an appealing story.

LITERATURE REVIEW

Though deepfakes are relatively new in the field of computer technology, there are still quite a few areas in which research has been conducted, as well several environments where their ramifications have significant effects. After discussing the origins and common uses of deepfakes, this literature review will detail the current and potential dangers and effects, how they are created and function, detection methods, current legislation, and finally the significance of the to-be-discussed research.

Origins and common uses

Deepfakes are a recent development in the realm of the internet and computer technology. The term itself was coined in 2017 and is derived from the words “deep learning” and “fake.” This combination of words relates to the process of creating a deepfake, which will is described in detail below. The first internet-documented deepfake was found on Reddit on November 2, 2017. This user was a regular poster of content on the /r/deepfakes subreddit, on subjects that were sexually explicit and portrayed female celebrities. New applications were developed to allow users to create deepfakes more easily on their own. The deepfake became popular after the following January, particularly in the field of fake pornography (Cavuoto, 2019).

Some of the most popular non-pornographic applications of deepfakes include face-swapping apps such as the FaceApp and Zao (Antoniou, 2019). These apps still fall under the category of deepfakes, even though they pertain mostly to singular images, whereas most deepfakes pertain to the digital doctoring of videos. Such applications allow users to upload photos and add filters to make individuals look younger, older, or the opposite gender, as well as adding facial hair or applying various hair styles. Other more nefarious and sexual applications appeared as well, the most common and popular being one called DeepNude. DeepNude, along with other similarly named and used services, allows the user to upload a photo, and the app’s software will render a nude photo. The apps encourage the user to upload a photo that already reveals as much skin as possible of the subject, such as a photo of the subject wearing a bikini or other revealing clothes. Such photos make the final product more realistic. The software for the DeepNude apps outputs nudes exclusively with female genitalia, even when the photo of a male subject is uploaded. Originally, DeepNude charged twenty dollars per month for unlimited access to the service. The specific DeepNude app has been taken down, mainly due to the inability of the creators to keep up with the massive amounts of internet traffic to the site. However, other services exist that serve the same purpose, some of which are completely free to the user (Khalid, 2019).

Not all deepfake uses are sexual in nature or even harmful. Westerlund (2019) explains the various areas where deepfakes can be used for good. Immediate benefits

mainly appear in the entertainment industry, with uses for “resurrecting” dead actors, de-aging actors, or substituting actors for reshoots. There are several uses within the medical field as well, such as creating footage of a deceased loved one to aid in the grieving process. Deepfakes can be utilized in treating patients with Alzheimer’s disease by making people who visit them appear younger, thus making the patient more likely to recognize them. In fashion, deepfake technology can be used to allow customers to virtually try on clothes and accessories in the comfort of their own home.

A Los Angeles-based visual effects studio named Corridor Digital has done significant work on the process of creating deepfakes. Corridor’s first deepfake video was released in 2019 and used Tom Cruise as its celebrity subject. To make the deepfake, the staff brought in a professional Tom Cruise impersonator as the live actor and used a free software program called DeepFaceLab. This created a realistic visual, as there was not much difference between the actor’s and Tom Cruise’s face (Corridor, 2019). The use of a professional impersonator provided realistic audio, necessary because deepfake software does not fabricate voices. This specific video was made for comedic purposes, much like some of Corridor’s other deepfake videos. They have also done professional work. In the spring of 2020, famous rapper Snoop Dogg asked Corridor Digital to create a deepfake of Tupac for his upcoming music video. The process was the same as the Tom Cruise video. They hired a Tupac impersonator to be the live actor. However, creating this video came with some challenges. There was very little high-quality video footage available of the late Tupac before his death in 1996. This gave the crew little to work with and did not portray complete coverage of Tupac’s entire face. Corridor’s creators eventually had to create some of their own footage and use mirroring effects on Tupac’s face to match the footage they needed for the deepfake.

Dangers and effects

With myriad uses for deepfakes, dangers and problematic effects are present. These can be detrimental to an individual’s reputation, mental well-being, and even personal safety. Additionally, their deceptive nature renders them difficult to track and control when used inappropriately.

According to a 2019 report from an Amsterdam-based cybersecurity company called Deeptrace Labs, 96% of the nearly 15,000 known deepfakes on the internet at the time could be categorized as “non-consensual” pornography, with women overwhelmingly the subject matter. American and British actresses and several South Korean K-pop singers were the most common celebrities used in deepfake pornography on mainstream pornographic websites (Khalid, 2019). Very few public figures have made any statements regarding deepfake pornography, even those who have become victims of it themselves. Scarlett Johansson, however, has. In January of 2019, in an interview with The Washington Post, Johansson commented on the deepfakes made of

her. In short, she stated that deepfakes on the internet are simply a new realm where people are exploited, and little can be done about them. There are worse things on the dark web, she said, and there is nothing people can do to stop deepfakes being made of them. Even if one could remove a video from the U.S., for example, it is not possible to legally do the same in Germany. In Johansson’s opinion, resistance was futile (Sharf, 2019). Public uses of deepfake pornography pertain to the publicly recognized celebrities, but other uses affect private citizens.

The story of Noelle Martin of Australia is one such case. In 2012, at the age of 18, Martin ran a reverse Google image search of herself out of curiosity to see what she would find. She discovered several nude images of herself for which she had never posed or consented. However, comments and tags on the images indicated she had consented. Further research uncovered more images that were inappropriate and graphic. Personal information such as her name and home address were posted in the comments. It was not until a few years later that the emergence of deepfake technology haunted Martin. Martin was informed there were pornographic videos of her on the internet. These were even harder to combat. Upon viewing them, Martin herself was taken aback by how convincing the videos seemed. Martin tried to pursue action on her own by creating accounts on the hosting websites asking for them to be removed. All requests were denied, and one webmaster bargained to remove them only if Martin provided him with actual nude videos and images for his personal collection. In the years since, Martin has dedicated her life to raising awareness about deepfakes and campaigning for legislation to criminalize deepfake pornography in Australia, which came to fruition in 2017 (Scott, 2020).

As referenced by Khalid (2019), applications like DeepNude tend to affect women who are not famous. These apps allow individual users to create nude photos of their own friends or romantic interests simply from something like a spring break beach picture. The extent of deepfake usage for personal use and purposes is hard to track, as it is rarely posted publicly on the internet. However, many women have spoken out privately about the effects of deepfake pornography on them as victims (McGlynn et al., 2019).

Another common pornographic use is revenge porn (McGlynn et al., 2019). Even though revenge porn falls within 96% of pornographic deepfakes, as cited by Deeptrace Labs, it is difficult to track how prevalent it is because many instances are never published publicly but are distributed within small social groups. Revenge porn is not an area unique to deepfakes, but it is one way it manifests. The idea of revenge porn is the release or creation of pornographic content to get back at or harm another individual. The most common instance of this is after a breakup, when an individual sends or posts inappropriate or nude photos or videos of other party without their consent. Sometimes, this is content that was given to the individual consensually but only for their viewing. With the emergence of deepfake technology, however, people are now

able to create their own content without any explicit source material. This is the aspect of this technology mainly addressed in the film.

Other interviews and research have shown that the effects on victims of imagebased sexual abuse are very similar to survivors of physical sexual abuse. McGlynn et al. (2019) state that though they know that image-based sexual abuse causes harm, victims underestimated the effects. Victims described their lives as being entirely disrupted with constant nightmares and internal torture. Many made a distinct separation between their lives before and after the images were posted. A great deal of fear trauma comes from the knowledge that images are still on the internet forever and that they can never truly be taken down.

Creation and mechanics

Deepfake technology runs on Generative Adversarial Networks (GANs), which are essentially the basis of all digitally generated imagery. They are algorithmic architectures that pit two neural networks against each other to create new instances that can pass for real data. The two components, dubbed the “generator” and the “discriminator,” mainly work within a double feedback loop. It is the job of the generator to take in random numbers and return an image to the discriminator. The discriminator takes in said data along with ground-truth data to determine the probability of the generator’s image being fake, which is represented by a number between 0 and 1, 0 being fake and 1 being passible as real. The intention of both components is to learn from each other, which results in more and more efficient images (Nicholson, n.d.). It is this process that provokes the creation of the term “deepfake” by combining “deep learning” with “fake.” DeepFaceLab is a software program that is publicly available for free and is the same program initially used by Corridor Digital in its Tom Cruise deepfake. To render a convincing deepfake, the first requirement is to have sufficient footage of the subject whose face the creator is using. Getting full shots of every conceivable facial expression and contortion is best and teaches the program what the subject’s face will look like when digitally placed on the second actor. Both the faces of the original subject and the actor need to be extracted using facial recognition to isolate the individual faces. The program then takes footage from both faces and learns to super-impose the first face realistically onto the second. The two sequences of footage will finally be merged and produce the final deepfake (Corridor Crew, 2019).

Detection and defense

Knowing how deepfakes work and the dangers they pose, the question becomes how to detect and combat them. Fortunately, determining if a video is in fact a deepfake is simple and viable, with the data required to do so being accessible through most computer devices.

A common and simple method is to detect face warping artifacts, as was used and exemplified in a deepfake detection system developed by Li and Lyu (2018). This is superior to most systems in its scope. Most detection systems target specific types of deepfakes, whereas this method targets nearly any kind. Li and Lyu’s system uses a Convolutional Neural Network (CNN) model, which utilized four individual computer models trained by inputting over 24,000 JPEG images. Three of the four were pretrained, whereas the fourth was directly trained by the data from the researchers. The results showed the fourth to be the most accurate in deepfake detection but still lacked in consistent accuracy.

Another method of deepfake detection is the use of blockchains and smart contracts. The goal in using these is to track a video back to its original computer source, determining if the video is real or fake. Hasan and Salah (2019) sought to improve the shortcomings of Li and Lyu’s system, using this method as their tool. The blockchain system analyzes the metadata within a video back to the original parent contract of the “artist’s” work. The researchers specifically looked at the public Ethereum variation of smart contracts and the Ethereum address of the artists, which allowed investigation into on-chain and off-chain sources. Ethereum blockchains are a system in the realm of internet data intended to be used as a third-party service for storing information. When individuals download an app, for example, their digital information is sent to a third-party service for storage by companies such as Apple or Google or stored by the companies themselves. The purpose of Ethereum is to return the control of the information to the owner. By doing this, the storing of internet data is decentralized, with changes only being made by the user. The system is very similar to the protocol and design of bitcoin, as it reveals a record of the whole transaction history. Records of transactions are held in networks of thousands of computers throughout the process, which allows for easier tracking (Hertig, 2017). Through on-chain sources, one can use the Ethereum Name Service (ENS) to find the artist’s original name, user profile, and company. Off-chain sources such as a Decentralized Reputation System does much the same thing through a voter-based system of authenticity. Hasan and Salah (2019) advise that if none of the above information can be found, the source is not reputable.

Legislation

On an international level, Australia is one of the only nations to have strict and direct legislation pertaining to deepfakes, as mentioned in the case of Noelle Martin (Scott, 2020). The United States, however, is severely lacking.

On a federal level, no deepfake laws directly deal with the pornographic aspect. The National Defense Authorization Act for Fiscal Year 2020 (NDAA), signed into law on December 20, 2019, is the only federal legislation mentioning deepfakes. In

this case, the Director of National Intelligence (DNI) is instructed to give an annual report to Congress on the latest research on deepfakes, specifically as it pertains to national security and the potential use by foreign powers. Monetary incentives have been established to encourage a continual and progressing competition among deepfake researchers (Chipman, et al., n.d.). At the time of this writing, the Identifying Outputs of Generative Adversarial Networks (IOGAN) Act has passed the House of the Representatives, and the Deepfake Report Act of 2019 has passed the Senate. Both pieces of legislation pertain to national security issues and have yet to pass both houses of Congress, at the time of this writing.

On the state level, legislation on pornographic deepfakes is slightly more evident. On July 1, 2019, a Virginia law deemed the distribution of nonconsensual “falsely created” explicit images and videos to be a Class 1 misdemeanor. Two months later, on September 1, Texas criminalized the use deepfakes that specifically target or harm public officials or influence elections. In October of the same year, California passed two separate laws regarding deepfakes, both of which allow the victims of deepfake pornography and candidates for public office to sue individuals or companies for spreading deepfakes “with actual malice” (Chipman, et al., n.d.). These are the only states in America that have any sort of legislation on these matters.

Significance

The significance of my project was to take all this information and research and present it in the form of a fictional narrative to create awareness of the topic to those outside of scientific or computer-technology fields. According to a 2015 interview with Tom Sherak, the President of the Academy of Motion Picture Arts and Sciences, film has a unique advantage in accomplishing this. He observed that stories have always been a part of society, having the ability to reflect or lead it. Film as a visually pleasing medium provides a ready audience to see the message a film has to offer. Films can educate an audience on an issue, present it from only one side and create controversy, or encourage and nurture conversation (MBE, 2015). My film will follow in this tradition of storytelling and educate the audience on the prevalence and dangers of deepfake revenge pornography and the effects they can have on the individual.

CREATIVE PROCESS

Introduction/research

My introduction to the concept of deepfakes was from a YouTube video by Corridor Digital. Their video entitled, “We made the best deepfake on the internet” depicted a deepfake impersonation of Tom Cruise (Corridor Crew, 2019). Though I found this

video entertaining and educational, I was curious about the nefarious implications of such technology.

As a part of Olivet’s Honors Program, I delved into potential topics for our senior research projects. At that time, I looked into the academic research on deepfakes and prevalent uses within the pornography industry.

It was easy to find research, as demonstrated in the literature review. I was surprised how little deepfake applications were discussed in mainstream media. This revelation, and my desire to apply my film studies concentration, prompted me to pursue creating a film detailing the harms of deepfake pornography.

Pre-production

As with any film revolving around a specific topic, I continued my research. I needed to know every detail of how deepfakes worked, and how they could be used so I would have the most accurate depiction in my film.

I began working with Dr. Heather McLaughlin as my professorial mentor on the project. Through discussion with her I determined that I wanted to make a film with a fictional story rather than create an information-based documentary. Dr. McLaughlin provided resources to help in the processes of filmmaking, and suggested individuals to cast in the film.

In the fall of 2020, I reached out to classmates and recent graduates of Olivet who Dr. McLaughlin and I thought would work well. I reached out to the recommended actors, and they all agreed to be a part of the project. During this time, I wrote the script based on a basic outline for the film I had developed earlier in the year. I completed a rough draft around April of 2021 and made revisions continuously.

To get ready for shooting the film, I laid out a detailed schedule of times and locations. I developed locations by keeping Olivet’s campus in mind for the settings of the scenes. I decided to begin filming two weeks after the end of the spring semester to accommodate the cast and crew’s schedules and have easier access to locations on campus. I also scouted locations off campus.

I planned the sound and musical tone I wanted for the film and enlisted Andrew Case to write an original score. The main influence for the score was a musical version of Psalm 13, the theme Scripture for the film, which was composed by Eric Pendleton and his band. Motifs from their song were used throughout the progression of the film and the soundtrack.

I had to coordinate housing for cast and crew. Initially I reached out to Olivet Housing to receive permission for my crew to stay in summer apartments for the duration of filming, which would have required payment for the time they spent there. When the final cast and crew were determined, it worked out that everyone could either commute on their own, or they could stay in my own apartment.

Finally, I acquired film equipment from the ONU Communication Department.

Production

Filming was set to officially began on Monday May 10, 2021. The night before I received an email from the main supporting actress apologizing profusely and saying she would not be able to be a part of the film because of the COVID-19 vaccine side effects. Fortunately, she was able to recommend a friend, Case Koerner, who took over her role.

The first day of filming was the longest and most strenuous. It was the only 12-hour day we had, beginning at 8 a.m. and concluding shortly after 8 p.m. We spent the entire day at the on-campus Starbucks, where a majority of the film took place. We filmed several different scenes, all involving Abriella, Case, and a few with Eric. Cinematographer Brady Jones and editor John Stuhlmacher worked on set.

Throughout the entire filming process, adaptability became the name of the game. Almost every day, someone withdrew from the project or we lost a filming location. The daily ritual was to film for five to six hours, then spend the rest of the night emailing friends and faculty to fill acting roles or volunteer for the film crew. Yet, help always eventually came. Alyssa Laidler offered her home as a filming location, and several Olivet faculty and students took part in filming, including Professor Deb Stafford, Dr. Mark Frisius, Anne Whalen, Tyler Comfort, Autumn Bentz, Michael Murray, Daria Caravette, Sydni Gaskill, Heather Simpson, and Simphiwe Bhebhe.

Post-production

The post-production process began while we were still in production. John, the editor for the film, worked on the early stages of the rough edit when we were not on set. He was able to finish the rough edit before classes began for the fall semester of 2021. Though this was complete some additional footage was required for the final cut.

Filming was completed with reshoots in late September. There were also several scenes involving images on a computer screen, which needed to be drawn up and rendered into the film.

Eric and his band were able to begin the recording process for their song. Once it was completed, it was sent on to Andrew for the development of the score. The goal with this is to use the song as inspiration for the entire film, with motifs developing and growing as the film progresses and the full song finally being played at length in the ending credits.

Before the final version of the song was recorded, I received a demo recording of a few of the band’s jam sessions for developing the song, which Andrew and I used to get an overall idea of what the score would sound like. The fully recorded song enabled us to finalize the score.

A limited screening was conducted for the honors cohorts. Eight underclassmen attended and gave their feedback of the film. Expert reviews were received from Professors Ashley Sarver and Chris Retts.

RESULTS AND ANALYSIS

Professional critiques

Professor Sarver’s feedback was largely positive. She thought the story covered the topic in an engaging way while also giving important information on a prevalent issue.

In her opinion, the fact that this story was written by a man involving a male antagonist could cause better reception from the male audience, who might be more likely to dismiss such a topic as addressed from a female perspective. She noted that actions taken by the female characters did not seem unrealistic and that the story did not seem like it was written by a man.

Her constructive critiques focused on sound design, her area of expertise. She noted the overall low-quality audio, which she said could be fixed by more consistent mic direction. She also suggested more intentionality in sound design, rather than simply ensuring the audio does not sound bad.

Professor Retts’ feedback was very directed. He gave general critiques, such as his feeling that the film could have served better as a 30-minute short film than the 55-minute final runtime. In addition to this, he gave specific critiques with the timestamps from the film. This was beneficial in gaining insight on the minutiae of the film, as opposed to Professor Sarver’s feedback, which was more geared toward the overarching concepts of filmmaking.

Peer critiques

The feedback from the honors underclassmen was largely positive. They all applauded the effort it took to pull off such a production and agreed that the story was engaging and kept them invested throughout.

Their critiques were constructive and helpful. One student, a computer science major, gave some insight into the mechanics of metadata and Ethereum blockchains that would make the story more accurate. Many acknowledged the fact that the script was underdeveloped. Their suggestions focused on adding more subplots to fill in the gaps in the story, and some gave specific ideas on what that could look like.

Personal critiques

My most notable personal critique is the script and its initial development. When first writing the script, I was unable to dedicate the proper amount of time to work out the glaring errors, which resulted in the final script put to film essentially being a cleaned up first draft.

Another prominent short sight on my part was a lack of storyboarding for the film. Though I had a few general shots in mind while writing the script, I never fully put in the effort to plan out each shot with the artistic focus they deserved. Fortunately, my cinematographer, Brady, had some creative ideas.

As a director, I believe I fell short in working with the actors to bring out the best in their performances. The results were still wonderful, but that was entirely due to the skills of my cast, rather than my direction. Due to time constraints, we spent as little time as I felt was possible on each scene to ensure we got through everything. This resulted in a lack of shot variety and, therefore, an overall lower quality in content.

Where I believed I excelled in this project was the scheduling, problem solving, and coordination. There were quite a few setbacks in the project that forced us to change plans and locations on the daily. Many people would have been overwhelmed with the stress and change, but I was able to push through it. Because of this, my overall stress tolerance has significantly increased.

My personal faith in Jesus Christ also benefited from this process. In many of the stressful situations, things got to the point that was literally nothing else I could do to make things happen. In these moments, all I could do was submit myself and pray for God’s provision. Every time this happened, an affirmative answer was given within a few short hours. God’s involvement in the completion of this project was very evident throughout.

Future directions

Much has changed with deepfake technology in the years since this project began. The developments have been so stark as to make much of this research outdated. As this evolution continues, research must develop with it and stay up to date, especially as the nefarious uses of deepfakes change.

The various types of deepfakes have changed. The creators of the DeepFaceLab program created another program called DeepFaceLive. The program contains several pretrained deepfake models depicting celebrities that can be used in real time on a live video conference. The program also enables users to train their own models for this use. Along with this, audio deepfakes have become more prominent. These are created mostly through the manipulation of artificial intelligence voices, rather than a program specifically designed for audio deepfakes, but these methods still result in audio deepfakes. The impacts of these developments on deepfake pornography, as well as other negative uses, have yet to be fully realized.

As awareness of deepfakes has become more common to the public, more research has been done on the psychological impacts on those depicted in the deepfakes. This field was extremely limited when the research for this project was conducted.

Finally, methods of detection and potential legal action continue to broaden. There is some evidence that Ethereum blockchains are not a reliable method of detection, and that much of the metadata used to determine the legitimacy of a video can be altered or deleted. There do not seem to have been many significant developments in deepfake detection or legislation. As deepfake technology grows, these areas must be kept up to date.

REFERENCES

Antoniou, A. (2019, September 26). “Zao’s deepfake face-swapping app shows uploading your photos is riskier than ever,” The Conversation. https://www.theconversation.com/zaosdeepfake-face-swapping-app-shows-uploading-your-photos-is-riskier-than-ever-122334

Ascher, S., & Pincus, E. (2012). The filmmaker’s handbook: a comprehensive guide for the digital age, Fourth edition, 2013 edition. New York, New York: Plume

BuzzFeedVideo. (2018, April 17). “You won’t believe what Obama says in this video!” YouTube

https://www.youtube.com/watch?v=cQ54GDm1eL0

Cavuoto, N. M. (2019). The era of disinformation: Deep fakes (Order No. 22622678). Available from ProQuest Dissertations & Theses Global. (2312231288).

Chesney, R., & Citron, D. K. (2018). “Deep fakes: A looming challenge for privacy, democracy, and national security,” SSRN Electronic Journal. Doi: 10.2139/ssrn.3213954

Chipman, J., Ferraro, M., & Preston, S. (n.d.). “First federal legislation on deepfakes signed into law,” JD Supra. https://www.jdsupra.com/legalnews/first-federal-legislationon-deepfakes-42346/

Corridor Crew. (2019, June 20). “We made the best deepfake on the internet,” YouTube.

https://www.youtube.com/watch?v=3vHvOyZ0GbY

Corridor Crew. (2020, March 6). “Snoop dogg had us bring 2pac back to life!” YouTube

https://www.youtube.com/watch?v=NbjE5wXT3RE

Deepfake. https://www.merriam-webster.com/dictionary/deepfake.

Hasan, H. R., & Salah, K. (2019). “Combating deepfake videos using blockchain and smart contracts,” IEEE Access, 7, 41596–41606. Doi: 10.1109/ACCESS.2019.2905689

Hertig, A. (2017, March 30). “Ethereum 101,” https://www.coindesk.com/learn/ ethereum-101/what-is-ethereum

Hueth, A. C. (2019). Scriptwriting for film, television, and new media. Abingdon, Oxon: Routledge

Khalid, A. (2019, October 9). “Deepfake videos are a far, far bigger problem for women,” Quartz. https://www.qz.com/1723476/deepfake-videos-feature-mostly-porn-accordingto-new-study-from-deeptrace-labs/

Li, Y., & Lyu, S. (2018). “Exposing deepfake videos by detecting face warping artifacts,” arXiv preprint arXiv:1811.00656.

MBE, V. S. (2015, June 3). “The Role of Film in Society,” https://www. thoughteconomics.com/the-role-of-film-in-society/.

McGlynn, C., Rackley, E., & Johnson, K. (2019, June 30). “Sexual abuse happens online, too –but current laws leave too many victims unprotected,” The Conversation. https:// www.theconversation.com/sexual-abuse-happens-online-too-but-current-laws-leave-toomany-victims-unprotected-119604

Morris, A. (2019). “Going deep: In a world of ‘fake news’ accusations, deepfakes may soon be a very real problem for journalists. Quill, 107(2), 21–25

Nicholson, C. (n.d.). “A beginner’s guide to generative adversarial networks (GANs),” Pathmind. https://www.pathmind.com/wiki/generative-adversarial-network-gan

Sandler, M. (2018). Visual storytelling: how to speak to your audience without saying a word. Studio City, CA: Michael Wiese Productions.

Scott, A. told to D. (2020, February 6). “Deepfake porn nearly ruined my life,” ELLE. https://www.elle.com/uk/life-and-culture/a30748079/deepfake-porn/

Sharf, Z. (2019, January 2). “Deepfake porn videos are using Scarlett Johansson’s face, but she says it’s useless to fight back,” https://www.indiewire.com/2019/01/scarlettjohansson-deepfakes-face-porn-videos-1202031678/

Westerlund, M. (2019). “The emergence of deepfake technology: A review,” Technology Innovation Management Review; 9(11), 39–52

APPENDIX – SCRIPT EXCERPT

INT. GIRLS’ APARTMENT - DAY

Scene is shot on a smart phone and is seen through the perspective of the camera.

HANNAH DAVIS is on screen, sitting in a comforter in the living room of the apartment she shares with VANESSA GREENE.

Vanessa is shooting the video on her phone and is speaking off-screen.

VANESSA (off-screen) Okay, it’s on.

HANNAH It’s on?

VANESSA Yeah, you’re live.

HANNAH Wait, live? I thought we were recording it first, then posting it!

VANESSA I thought you said you wanted it live!

HANNAH No! (Beat) Is it still going?

VANESSA Yeah, do you want me to turn it off?

HANNAH (Sighs) Ugh, no. We need to just get this done. Hannah tries to compose herself and get serious.

HANNAH (CONT’D) (to camera) Okay, so this is a response to Joshua Mills’ post, and just the whole situation in general...

CUT TO BLACK.

TITLE SCREEN

INT. HANNAH’S APARTMENT BEDROOM - MORNING

Overlay music, “Reasons” by Isaiah Clampitt, plays throughout opening scene with little background sound. The scene opens on Hannah asleep in her dorm room bed. There is only one bed in the room. The lights are off. There is a wooden night stand next to the bed on which there is a lamp, an ornately designed diary, and a cell phone.

An alarm goes off on cell phone, indicating the time is 6:00 AM. Hannah turns off alarm and rolls out of bed. She is wearing running shorts and a t-shirt.

EXT. OUTSIDE OF APARTMENT - MORNING

Hannah is outside apartment in running shorts and an athletic tank-top. She stretches briefly and inputs something into smart watch on her wrist. She begins running.

INT. JOSHUA’S APARTMENT BEDROOM - MORNING

The apartment is off-campus and is therefore nicer. There is a single bed in the middle of the room. The room is professionally adorned. JOSHUA MILLS sits at computer desk; only light in the room is the computer screen.

He reaches for cell phone and opens text message conversation with Hannah. All of the recent texts are from him. The various messages read things like “Hey, can we talk?”, “Are you available to talk?”, “Can we talk about this?”

Joshua taps on the screen to send a message. He hesitates, then shuts off cell phone. He goes back to the desktop computer and we see he is working on some kind of animation program.

INT. VANESSA’S APARTMENT BEDROOM - MORNING

This is the same apartment as Hannah, but a different bedroom. There is a single bed in the room with a full dresser next to it. There are various houseplants and pictures of family/pets, as well as Vanessa’s cell phone. Vanessa is asleep in dorm room bed. Her cell phone alarm goes off. The screen shows that it is 6:45 am. Vanessa is clearly tired as she reaches to pick up the phone. She snoozes alarm, then collapses back in the bed.

INT. COFFEE SHOP - MORNING

Hannah walks into coffee shop after her run. The coffee shop is a couple miles off campus and is a regular place to which Hannah runs in the morning. The atmosphere is meant to model an average Starbucks, with similar interior design and lighting.

She is out of breath and waves to employees as she walks to the counter. Employees wave back. By the way they greet her, we can tell that Hannah is a regular. Her

coffee is soon ready, which she grabs and walks toward a seat. She sits at a table to the side with bench seats similar to a couch.

INT. JOSHUA’S APARTMENT BEDROOM - MORNING

Joshua is still working on animation program.

He pauses to think and looks at cell phone again. After a few moments, he picks it up and opens conversation with Hannah. We see cell phone screen as he types out text message that says, “Hey, I’m really sorry. Can we talk sometime?” He sends the text.

INT. VANESSA’S APARTMENT BEDROOM - MORNING

Vanessa’s phone goes off again. The time is now 6:55 am. After turning off alarm, Vanessa rolls her eyes and gets out of bed. She is wearing baggy pajama pants and an over-sized sweatshirt.

EXT. OUTSIDE OF APARTMENT - MORNING

Vanessa is now wearing jeans, a t-shirt, and a book-bag thrown over shoulder. Her hair is in a ponytail and she is wearing a baseball cap.

Vanessa walks to parking lot in front of apartment building. She goes to her car and gets in, putting her backpack in passenger seat. She starts car and begins to pull out of parking spot.

INT. JOSHUA’S APARTMENT BEDROOM - MORNING

Joshua is still working at computer. He glances at cell phone and checks if any new messages have arrived. He leans on his elbows with his head between his hands. He is clearly anxious.

He sighs and switches to a pornographic website. Nothing explicit is shown, but we see the header for the site, indicating its nature.

EXT. OUTSIDE COFFEE SHOP - MORNING

Vanessa pulls into parking spot in front of coffee shop and gets out of car. She walks to the door.

INT. COFFEE SHOP - MORNING

Vanessa enters coffee shop and walks to the table where Hannah is seated.

Hannah still sits at table and looks up. They wave at each other.

After setting backpack down, Vanessa reaches in and pulls out notebook and Bible.

VANESSA Sorry, I overslept...

BOTH ...again!

VANESSA (laughing) Hey!

HANNAH You act like this is unusual!

Vanessa smiles and rolls her eyes.

VANESSA So, how was the run?

HANNAH It was good. You should have joined me.

Hannah leans forward.

HANNAH (CONT’D) Like you said you would.

Vanessa puts her hands up in submission.

VANESSA I know, I know! You could have woken me up!

HANNAH Would that have worked, though?

They both shake their heads and laugh.

VANESSA Well, I’ll be right back. I’m gonna get a drink.

HANNAH Mmkay.

Vanessa stands up walks to counter. Hannah takes a drink of her coffee and looks out the window.

A notification goes off on her cell phone. She picks it up and sees it is a message from Joshua. She sighs and unlocks her phone. We see the message on her screen. She taps the screen to send a message, hesitates, then turns off the phone. She turns the screen face down forcefully on the table in frustration.

Vanessa returns and sits down.

VANESSA You okay?

HANNAH (frustrated) Yeah, (indicates to phone) it’s just Joshua.

VANESSA Oh, goodness, he didn’t send another one, did he?

Hannah nods.

Vanessa shakes her head.

VANESSA (CONT’D) Are you gonna talk to him?

HANNAH (exhales heavily) Maybe, if it’d shut him up!

VANESSA Don’t! Don’t give him the chance to rope you into anything!

HANNAH I won’t let him...

VANESSA Yes! You will!

HANNAH No, I won’t!

VANESSA You know how charismatic and manipulative he can be! Not realizing it soon enough is what got you into this mess in the first place!

HANNAH Yeah, but remember he apologized for that! It doesn’t make it any better, and I don’t want to get back together. But when he explained his whole...

Hannah feels awkward saying the words.

Vanessa interjects for her.

VANESSA ...porn addiction.

HANNAH (still uncomfortable) Yeah. It just makes explains a lot of his attitude. And he said he’s working on it.

VANESSA And it took two years for him to even mention it! Like you said at the time, it came out of nowhere. How can you trust a guy who can fool you so easily for so long?

HANNAH I didn’t say I trusted him! I don’t want him back! Just lay off, it’s not my fault you don’t have a boyfriend who wants to sleep with you!

Vanessa gives Hannah a stern look and crosses her arms.

VANESSA What did we talk about?

HANNAH Yeah, I know.

VANESSA I need you to say it for me.

Hannah is frustrated. She knows Vanessa is right but hates being called out by her.

Hannah delivers the line, which has clearly had to have been repeated many times before.

HANNAH I need to stop lashing out at people just because I’m stressed.

VANESSA Good.

Vanessa smiles as she reaches over and touches Hannah’s hand.

VANESSA (CONT’D) And you really are doing better. Hannah smiles and nods.

VANESSA (CONT’D) Now, just promise me you won’t give Joshua the time of day.

HANNAH (halfheartedly) I won’t...

VANESSA Promise me!

HANNAH Fine! I won’t!

VANESSA Good.

Vanessa opens her Bible and begins flipping through the pages.

VANESSA (CONT’D) So, what are we on today?

Hannah looks at the Bible app on her phone.

HANNAH Um, Psalm 13.

VANESSA Right.

Vanessa flips to the right page.

VANESSA (CONT’D) Do you want to read it?

HANNAH Sure. (Beat) “How long, Lord? Will you forget me forever? How long will you hide your face from me? How long must I wrestle with my thoughts and day after day have sorrow in my heart? How long will my enemy triumph over me? Look on me and answer, Lord my God. Give me light to my eyes, or I will sleep in death, and my enemy will say, ‘I have overcome him,’ and my foes will rejoice when I fall. But I trust in your unfailing love; my heart rejoices in your salvation. I will sing the Lord’s praise, for he has been good to me.” (Beat) Wow, that’s quite the turnaround.

VANESSA Yeah, it is. I don’t know that I could do it that easily.

HANNAH Trust God through hard times?

VANESSA Yeah, but like, through really hard times. Most of us haven’t gone through anything like David did when he wrote this. It’s easy enough to say I’ll trust God through something like stressing about a test. But these are some terrible things he’s dealing with in this passage, and he’s still able to end it all with praising God. I just think that would be a lot harder to do than we realize.

HANNAH Yeah, I get that. It would be hard. But, I don’t know, I’d like to think I could do it.

Vanessa seems skeptical.

VANESSA You really think so?

HANNAH Yeah. You don’t think I could?

VANESSA I’m not saying that. I just remember how you were after the break-up. You weren’t exactly cursing God, but you were pretty discouraged.

Hannah starts to say something, but stops. She knows there’s some truth to Vanessa’s words, she just doesn’t want to admit it.

Hannah thinks for a moment, then nods.

HANNAH So, is this the next one going on the wrist?

VANESSA It’d be a good one.

HANNAH Got a marker?

VANESSA Yeah.

Vanessa reaches into her backpack and pulls out a black marker and hands it to Hannah.

Hannah turns her left wrist facing up. We see the remnants of another marking on her wrist. The writing is calligraphic and flourished. It is faded and smudged. We can only read “1 Co” and part of a “3.”

Hannah licks her thumb and wipes away the markings. Once it is clean, Hannah begins writing “Psalm 13” in the same flamboyant style.

PAISLEY FULLER enters through coffee shop entrance. She is wearing sweatpants and a tight-fitting t-shirt. Her hair is somewhat unkempt.

She rushes over to Hannah and Vanessa. She is very apparently frustrated.

Paisley punches Hannah in the arm.

The bump caused Hannah to mess up on her wrist art.

Hannah exhales in frustration.

PAISLEY Excuse me, young lady, but why didn’t you tell me?

HANNAH I’m sorry, what?

PAISLEY You and Josh! You really thought I wouldn’t find out?

Paisley abruptly sits down, forcing Hannah to scoot over.

PAISLEY (CONT’D) You cannot believe how shocked I was! Especially since I had to hear about it from someone else!

Hannah and Vanessa appear very confused. They try to interject, but Paisley keeps talking.

PAISLEY (CONT’D) I thought we were good enough friends to at least here it from you! This does seem like something you’d keep secret, but—

VANESSA What are you talking about??

PAISLEY (to HANNAH) You had sex with Josh!

HANNAH (extremely confused) No, I definitely did not!

PAISLEY Uh, yeah, you did!

HANNAH (firmly) No, I didn’t. (exasperated) Did he tell you this?

PAISLEY No, I saw it!

VANESSA You saw it?

PAISLEY Yes! Someone else showed me the video! Which makes it even more insulting that you didn’t tell me!

HANNAH Who showed you a video? What video? We never had sex!

PAISLEY My roommate!

HANNAH Let me see the video!

PAISLEY What, you don’t have it?

HANNAH Just show me!

PAISLEY (sassy) Fine!

Paisley pulls out her phone and brings up the video. This is the initial deepfake around which the film revolves, but none of the characters know it is fake.

Paisley hands the phone to Hannah and steps back. She doesn’t want to see the video again.

Vanessa joins Hannah on the other side of the table to see the video.

The video is shot with a singular person holding the camera in a “Point of View” style. The camera quality is low and rather shaky.

Based on Paisley’s description, it is assumed Joshua is holding the camera, but his face cannot be seen in the video.

VIDEO HANNAH is seated on a bed as the camera walks toward her.

VIDEO JOSHUA, holding the camera, speaks off-screen.

VIDEO JOSHUA Alright, it’s ready. You sure you’re cool with this?

Preprocessing of Astronomical Images from the NEOWISE Survey for Near-Earth Asteroid Detection with Machine Learning

ACKNOWLEDGEMENTS

Financial support for this project was provided by the Craighton T. and Linda G. Hippenhammer Faculty Scholarship Grant, as well as the Honors Department of Olivet Nazarene University. The Pence-Boyce STEM Student Scholarship also provided the opportunity to work on this project full-time as an internship. Mentorship and guidance were provided by Dr. José Manjarrés, Assistant Professor in the Department of Engineering in the School of STEM. This project would not be complete without his knowledge and assistance. I would also like to acknowledge Dr. Stephen Case for his guidance and expertise in astronomy. Thank you to the other students and professors in my honors cohort, Cohort XII: The Imposters. I would also like to thank my roommates, Megan Drenth and Lauren Kee, for sticking with me through this process, and encouraging me the whole time. Lastly, I would like to thank Mani Martinez for the many nights he stayed up with me and supported me while I worked on this research. I couldn’t have done it without you all.

ABSTRACT

Asteroid detection is a common field in astronomy for planetary defense, requiring observations from survey telescopes to detect and classify different objects. The amount of data collected each night is continually increasing as new and better-designed telescopes begin collecting information each year. This amount of data is quickly becoming unmanageable, and researchers are looking for ways to better process this data. The most feasible current solution is to implement computer algorithms to automatically detect these sources and then use machine learning to create a more efficient and accurate method of classification. Implementation of such methods has previously focused on larger asteroids, but this leads to less accuracy in classifying smaller and slower-moving asteroids. We use the source data from the Near-Earth Object Widefield Infrared Survey Explorer (NEOWISE) survey telescope to create a preprocessing pipeline allowing for better training and testing data for machine learning algorithms. We were able to create a pipeline that finds sources on an image within 0.02 degrees as well as a collection of data on the known sources. Next, we used several machine learning classifying models, including a logistic regression classifier, a support vector machine (SVM), a naïve Bayes classifier, and a random forest. Finally, we present and discuss these results as a confusion matrix for each model, describing the ability to classify a source as an asteroid or not. This was done with only the numerical data collected. In the future, to create a better classifier, we would use this data along with classified images to develop a system that could predict the possibility of a detected source within a NEOWISE image being an asteroid or not.

Keywords: machine learning, asteroid detection, astronomy, near-earth object

INTRODUCTION

Improving asteroid detection has become increasingly important, as near-Earth asteroids (NEAs) have proven dangerous even at small sizes and velocities. For example, the Chelyabinsk meteor that exploded over a town in Russia that caused structural damage as well as many injuries was only twenty meters, or sixty-six feet, in diameter. All information collected about these asteroids is beneficial either for impact prevention or potential asteroid mining, which is becoming a desirable option for gathering natural resources for use on Earth. There is an increase in data each year used to detect NEAs and potentially hazardous asteroids (PHAs), and the incoming images and the additional data from survey telescopes are quickly becoming unmanageable to process via human analysis [1], [2]. In 1998, the Very Large Telescope (VLT) produced 10 G B of data, whereas in 2019 the Large Synoptic Survey Telescope (LSST) produced around 20 TB or 20,000 GB of data per night. Recent studies have investigated the

implementation of machine learning to decipher images collected from these telescopes to show that there are more accurate and faster ways to detect NEAs. Previous studies have demonstrated the effectiveness of machine learning for the detection and classification of NEAs in survey data [3], [4], [5]. The present research project first explores the astronomy behind asteroids, including their magnitude and other astronomical units such as right ascension and declination, before discussing the application of machine learning and the different models and algorithms used to classify asteroids.

Asteroid surveys

The primary type of data in previous asteroid detection research has been image surveys, created either with the intent to observe all types of transient objects or to observe asteroids specifically. In such study, the survey telescope images the same part of the night sky multiple times per night with the intention of observing any transients moving over time [1], [9], [10], [13]. Astronomers and researchers often processed the raw data in different ways to fit better with the objective of the research. For example, Duev et al. converted survey images into grayscale, because color was not necessary for the detection of the bright pixels and ultimately simplified the data and therefore the processing [2]. In multiple approaches, researchers subtracted known sources such as stars, planets, or satellites from images [6], [7], [8], [13]. The researchers then utilized these subtracted or differenced images, focusing solely on the transients or unknowns that remained after the knowns were subtracted out. Another example of data preparation is the use of random horizontal and vertical image flipping rotations to avoid bias in the results [3]. The purpose of flipping the orientation of the images allowed for a better image set because there were source image examples from a variety of different perspectives that could then be used for processing. The most common sources of data that were used for these surveys included the Zwicky Transient Facility survey [2], [7] and the images collected from the Linear Synoptic Survey Telescope [9], [10]. Larger amounts of data are available for use for researchers as well as the general public, but, as made clear in previous studies, this raw data must be tweaked and manipulated with preprocessing steps in order to best serve the objective of the research and ultimate goal of the researcher.

The Near-Earth Object Widefield Infrared Survey Explorer (NEOWISE) was created to find NEAs and provides much of the sky pictured in two infrared wavelength bands (3.4 and 4.6 μm) as well as data on multiple types of sources. The two different infrared bands capture different features based on the wavelengths given off from each source, allowing for more features to be observed on each source. Each image taken with NEOWISE has a specific scan identification as well as a frame number, allowing each image to have a unique name or identification number. Some of the data provided for each image include the location of the image in right ascension and declination, absolute magnitude and visual magnitude of the objects in the image, and the difference in intensity of the infrared bands for each image object. Right ascension and

declination are absolute units used to locate objects in the sky. Right ascension can be measured in hours, minutes, and seconds (0 to 24 hours) as well as in degrees (0 to 360 degrees), whereas declination is measured only in degrees (-90 to 90 degrees). Absolute magnitude is the brightness of a celestial object as seen from a set distance and gives information about the true luminosity of the object, whereas visual magnitude is the brightness of the object as viewed from Earth. The smaller the magnitude the brighter the object. Most of the stars in our night sky have visual magnitudes from one to six, whereas our Sun has a magnitude of -26.

Previous asteroid-detection work has focused on faster-moving asteroids, often to the detriment of detecting slower-moving asteroids [6], [11], [12]. In survey images, faster asteroids show up as trails or streaks; the faster the asteroid is moving, the longer the streak. A common detection method is recognizing these streaks, but this method performs poorly on slower-moving asteroids that may appear as only a couple of pixels and can look very similar to other stars. A better way to detect slower-moving asteroids is to recognize moving pixels between sets of images from the same portion of the night sky allowing a small amount of time to elapse between each image. The NEOWISE survey dataset contains considerable overlap between images, allowing for tracklets of images (string of images with the moving object) to be created. These tracklets allow for better detection of slower asteroids, which appear as “moving pixels” when the images in each tracklet are compared.

Detection of most asteroids has historically relied on human interaction in terms of viewing the images and picking out each image that included streaks or pixels moving over time. This method is quite time-consuming and requires multiple human reviews for each image. Speeding up this process is beneficial in the long run because it would allow for same night follow-up, allowing further observation of the object of interest before it moves out of view and is unable to be seen. Multiple researchers point to machine learning as the solution to quicken and improve the asteroid-detection process [3], [4], [5].

Use of machine learning

Researchers have previously used algorithms such as random forest [1], [7], k-Nearest Neighbors [1], [8], [9], and support vector machines [10] for the classification of detected sources. These methods have sped up the process of classification as compared to previous systems that relied heavily on human interaction.

One example of machine learning that could be fruitfully applied to asteroid detection is logistic regression. Logistic regression is a binary classifier that uses a logistic function (a common sigmoid curve) to model a dependent variable. The output of logistic regression model is the classification of a source as an asteroid or not (true or false). The goal is to determine the boundary that divides classes of data based on fixed values of the model parameters.

Another machine learning algorithm that could be applied to asteroid detection is a support vector machine. To train a support vector machine, a user must use datasets that are marked as belonging to two distinct categories. The model can then predict the possibility of a new data point (in this case, an object in an image) belonging to one class or another (e.g., “asteroid or not”) based on where it falls on a graph created using the features of both classes. The goal of a support vector machine is to find a hyperplane, or an area of overlap, within a space that distinctly classifies the source points with the maximum margin, or the maximum distance between both points. The dimension of the hyperplane depends on the number of features. A support vector machine kernel transforms the data and finds the process, beyond a linear hyperplane, that best separates the data based on the user-defined classes. This becomes very useful when dealing with a non-linear classification problem.

The naïve Bayes classifier can be used for source classification by applying the Bayes Theorem, which describes the probability of an event based on the prior knowledge of the conditions that are related to the event (in this case being an asteroid) with the assumption of conditional independence between every pair of features given the value of the class variable. For example, the features for an asteroid might include the location, brightness, or size of the asteroid. The Gaussian naïve Bayes algorithm assumes the likelihood of the features to be Gaussian, a function that is visualized as a symmetric bell curve.

Finally, decision trees offer another aspect of machine learning that could usefully be applied to asteroid detection. Decisions trees use a tree-like model of decisions in order to reach a conclusion about the classification of a source. A common example is the classification of iris flowers. First, the tree looks at the sepal petal length and sets a threshold that splits the possible values into two different categories, and the next decisions are based on the sepal width, petal length, petal width until every picture is classified into one of three different categories. The model should be able to predict the class of a source by creating simple decision rules assumed from the data features. A random forest is a model of machine learning that constructs a multitude of decision trees for the classification of the data points.

In each of these models, results are displayed using confusion matrices. In order to convey the number of correct and incorrect predictions, the results are broken into classes: true positives (sources that are true and classified as true), true negatives (sources that are false and classified as false), false positives (sources that are false but classified as true) and false negatives (sources that are true but classified as false). Each of these categories are depicted in the confusion matrix. These can then be used to calculate other important aspects of the classifier, such as accuracy, precision, and recall.

A machine learning model that has proven especially efficient in the field of image classification is Convolutional Neural Networks (CNNs). CNNs are a type of machine learning architecture that implement convolution kernels, or filters, on the input features of the data to create feature maps. A CNN model needs training data

to establish training weights and testing data to check its performance. Each image input passes through convolutional layers with filters or kernels. The process involves both convolution layers and pooling layers, which reduce the dimensions of the data by combining outputs at one layer into a single neuron, which is just one part of the larger neural layer, in the next layer, and finally a fully connected layer that applies the sigmoid function, an s-type curve activation function used to add non-linearity, to classify a source with a binary value of 1 or 0. For this research we are concerned with binary classification (asteroid or not an asteroid) and smaller images, so this would lead to fewer layers overall in a CNN.

CNNs can speed up processing by providing more accurate predictions than human-based classification by eliminating the need for a person to check anomalies and asteroid candidates in each image. Previous research has shown that a CNNbased approach is more accurate at classifying streaks and other abnormal pixels as asteroids [5], [6], [10], [11]. The CNN architecture can perform better with image classification than more simple machine learning algorithms, such as the ones previously mentioned, because of its hierarchical model that works on building a complex network.

Given the limitations of the current asteroid-detection approaches, this research attempted to develop a pipeline that could more accurately detect slow-moving asteroids. To detect the slower and dimmer asteroids, the images from the NEOWISE survey from multiple years were processed using machine learning to become more efficient at detecting slower and dimmer asteroids. This included a focus on the images, as well as the metadata from the database on each individual object such as the visible magnitude, absolute magnitude, and the magnitude of the object in the first and second wavelength bands. Our work builds on existing efforts in implementing deep learning to detect transients and possible asteroid candidates in asteroid surveys and improving the ability to recognize irregular moving asteroids, by exploring the different machine learning models outlined here with data collected from the NEOWISE asteroid survey.

METHODS

Data collection

Data was collected from the NASA/IPAC Infrared Science Archive (IRSA) database, specifically the Near-Earth Object Wide-Infrared Explorer (NEOWISE) survey. To retrieve the images and other source data, we used MySQL programming to perform database inquiries. This allowed us to collect images that contained different types of sources. The images collected were single-frame images from a range of -50 to 50 degrees in declination and the full range of right ascension. This allowed full coverage of the celestial equator around the entire celestial sphere. We kept the range of

declination smaller to reduce the number of images needed, and we noticed that there were less asteroids in the areas that we did not observe.

Within these images, we collected data on 550,264 sources, which included asteroids, comets, planets, and planetary satellites. Data on each source included the object’s location (in right ascension and declination) and its absolute and visual magnitude. In addition, data included the object’s magnitude in infrared bands 1 and 2, the difference between these band values of each object, the image identification, and the x and y coordinates of the source within its image. To convert astronomical coordinates into pixels, we first converted the right ascension and declination values that were originally in degrees into arcseconds. These values were then converted to pixels using the NEOWISE pixel scale of 2.75 arcseconds per pixel. To save the images and data as workable files, we saved them as NumPy arrays and saved the data separately as CSV files. Both file names were named as the unique source identification and frame number of that image to keep them coordinated. We then applied a logarithmic filter to the image to improve visualization, scaling the values down to readable values and leaving the background and sources on the image.

Initial data analysis

To better understand the collected data, we began by analyzing the sources separately by their specified labels. For this dataset, the labels were asteroid (A), comet (C), planet (P), and planetary satellite (S). To analyze the data, we calculate the minimum, median, and maximum for each different measurement collected for the source. Figures 1 to 3

Dots represent non-asteroids, whereas crosses represent asteroids. Asteroids seem to have a higher absolute magnitude on average, but visual magnitude seems to be distributed evenly for both classes. This shows that asteroids are dimmer than other types of sources.

Dots represent non-asteroids, whereas crosses represent asteroids. Most of the non-asteroids lie within a smaller

show some of the different features plotted for both asteroids and non-asteroids. Figure 1 shows the general location of the objects, indicating that many of the nonasteroids lie within the region of the asteroids in the solar system, along the ecliptic in the night sky. Figure 2 plots the absolute and visual magnitude of each source, and there is more of a definitive difference in this graph. Asteroids are shown to have higher absolute magnitudes, which indicates that they are usually dimmer than the nonasteroids. Finally, Figure 3 shows the difference between the magnitude of the objects in the two different wavelengths of infrared, indicating that the properties of the non-asteroids still lie within the area of the plotted asteroid data points.

Preprocessing pipeline

Our image preprocessing pipeline started with the input of a 1016x1016 pixels grayscale image collected from the database with final goal of detecting the point sources directly on the image and comparing them with known sources collected from the IRSA database stored in the CSV file. If we are able to create a pipeline that can accurately detect the sources that are already in the IRSA database, we then can rely on that processor to find new data points that can be used to test other machine learning classifiers.

The first step of the pipeline was data conditioning. The data contained negative numbers representing broken pixels, so we limited the arrays to contain only positive numbers to allow for image visualization. The second portion of the conditioning was limiting the data to values of 0 to 255, the standard values used in image processing. We accomplished this by converting all the images to 8-bit integers (whole numbers ranging from 0 to 255).

Next, we fed the images into a source detection algorithm called DAOStarfinder [14]. This algorithm can detect stars and other point-like sources. The sources can be detected by first calculating the median value of pixels, which is then assigned as the value of the background. Points that lie outside of the full width half maximum (FWHM) of this value are then flagged as sources. The last step of the pipeline was to add a threshold. We applied a threshold to pixels with values over five times the standard deviation. The output of this algorithm was a table with the x and y coordinates of each detected source on the image. At this point in the processing pipeline, our algorithm should have picked out all the point sources in the images. These could include stars, comets, asteroids, planets, and planetary satellites.

Finally, to compare the actual locations of the sources and the sources detected from the algorithm outlined above, we used the coordinates stored in each individual CSV file and compared that with the closest point possible from the source table generated. This comparison was done by calculating the smallest Euclidian distance (the length of the line segment between the two points). The final output was an image with all the sources circled in blue and the sources of interest (asteroids, comets, planets, planetary satellites) circled in red, as well as the value of the Euclidian distance of

the original point to the detected point provided. Figure 4 is a visual representation of this pipeline.

Numerical source data classification

The next step in our research was to test our data with the various types of machine learning algorithms discussed above to determine if any of these models were viable systems to classify our numerical data on each source. The first model we tested was logistic regression. To begin, we imported all of the known data for each source into a Pandas data frame. The imported CSV file included information on all 550,264 sources. To split the data into the training and testing sets we used the train_test_split function from sklearn.model_selection and set the test size to 0.2 of the original data frame. This meant the testing data was 20% of randomly selected data from the original

dataset, while the rest of the data made up the training data. We want the training data to be a majority of the available data because more data means more training, which should lead to a more efficient classifier. The features included the ‘ra,’ ‘dec,’ ‘amag,’ ‘vmag,’ ‘w1mpro,’ ‘w1sgmp,’ ‘w2mpro,’ ‘w2sgmp,’ and ‘band_difference’ columns, whereas the target only included the label column labeled ‘t’.

The collected NEOWISE data is heavily biased towards asteroids. There were 438,960 asteroids and only 1,251 non-asteroids in this training set. (This bias and its implication for the results are explained more in-depth in the discussion section of this thesis.) Finally, we trained and tested the data with the LogisticRegression model from Scikit Learn. The output is a confusion matrix described in the results section. We then followed a similar process for the SVM, naïve Bayes, and random forest classifiers. For each classifier we generated a training and testing dataset and then used the respective model from Scikit Learn to generate a confusion matrix.

The next step in our system was to use a convolutional neural network to classify the images. We anticipated using the probability from the CNN as well as the best machine learning classifier in order to create a precise source classification system, but we were ultimately unable to perform the CNN on the images for reasons explained in the results section.

RESULTS

The preprocessing pipeline contained 548,700 asteroids, 1,331 comets, 35 planets, and 198 planetary satellites in the images used. The average distance estimated between the object source location and the actual location on the image was 26.76 pixels, or 73.6 arcseconds. The standard deviation was 29.62 pixels or 81.4 arcseconds. This indicates that our process was accurate and can continue to be used. Along with the estimated distances of the sources of interest we also gathered and analyzed information on all of the sources, summarized in Table 1.

Most machine learning models returned a confusion matrix. The total number of sources labeled true or false changes slightly for each model. The matrices for the various machine learning models are given in the figures that follow. These matrices show a lot of correctly labeled true cases (asteroids). However, even with the relatively high number of true positives there was still a considerable number of sources incorrectly labeled within the context of our data, explained in the discussion.

DISCUSSION

Our analysis showed that the preprocessing pipeline utilized in this research was useful at finding sources, as the mean average of the distance between the real source coordinate and the detected source coordinate was around 73.6 arcseconds (around .02 degrees in

TABLE 1: Source Data Statistics

This table shows the different data associated with each source type. The minimum, medium, and maximum are reported for each feature.

Asteroids

Comets

Planets

the sky) or 26.76 pixels. Since we know the pipeline is able to detect the asteroids with some accuracy, we can be confident in using it to train future machine learning algorithms to detect other asteroids. However, there is still some work needed to ensure that more of the sources of interest are detected in the images. One possibility is making sure there are no anomalies, such as diffraction spikes or other lensing errors in the images, and no mistakes when collecting the coordinates of the sources from the database.

Another factor to note is that the NEOWISE survey data has a large bias towards asteroids, as there is a considerably larger amount of data collected for that source as compared to the other types of objects. We can also use the data statistics previously outlined in Table 1 to determine certain parameters for common asteroids that should be used in training for machine learning and what the threshold might be for these parameters. For example, looking at the data collected in Table 1, there are some clear

differences between asteroids and planets and planetary satellites, but the data is similar for asteroids and comets. This implies comets will be hardest to distinguished from asteroids in the images.

We can see from the results of the different classification algorithms that there are a lot of true positives or true negatives, showing that each classifier was able to identify a majority of the asteroids. However, even though each confusion matrix showed a large

percentage of asteroids identified, this does not necessarily mean these algorithms were successful. Because the training set has around 439,000 asteroids and only 1,300 nonasteroids, any algorithm had a good chance of labeling a source an asteroid simply due to the large amount of them. Because of this, we are more interested in the other boxes of the confusion matrix. There are non-asteroids on the order of 1000 instead of 100,000, so even a small number of non-asteroids incorrectly identified is an issue. In every model above there are a couple hundred, if not more, incorrectly identified. Adding the probability of

the classified sources from a CNN used on the images would be able to lower the incorrectly classified sources, but there were issues on implementing this system.

For a CNN image classifier, a clear training set of images is essential. The detected source should be in the center of the image, and there should be no other objects pictured. In our data, after creating an image with the collected source coordinates at the center, the source of interest was not in the center. This meant there was some loss in precision converting the center of the object to degrees and then pixels on the image. At the moment we are unsure where this loss occurs, since the coordinates of the object and the coordinates of the center of the image are pulled directly from the IRSA database. We converted both coordinates into the same unit and then found the difference of the coordinates of the source from the center and then created an image by drawing a 90-by-90-pixel box around the supposed location of the object. Without being able to center the image on the intended object, we cannot assure that only the object will appear in the image because we cannot locate where the object is exactly without looking at the image and zooming in. There are also a lot of background sources that would need to be removed if in the future we are to use a CNN with the images. Therefore, we cannot ensure an accurate system using a CNN, due to the error in our images. Some of these images are pictured in Figure 9, there is a brighter object in each image, but it is not at the center.

To continue this research, we would need to figure out how to calibrate these images to work well with the CNN, which would allow us to create a more in-depth classification system along with the numerical data analysis. We would first start by checking the coordinates from the original database, or we could use the detected centers used from before. But this brings up the issue of which is more accurate, the provided coordinates or the detected sources. The end goal of this research would have been to use the images to classify an asteroid in Figure 9 and 10 and a non-asteroid which is shown in Figure 11. Future researchers could combine the probability of the correct class from the image CNN classifier with one of the other machine learning algorithms used on the numerical data to create a more precise classifier that would be useful on other NEOWISE source and image data. Based on our collected results from each of the machine learning classifiers, there is not one that outperforms the others significantly and that can confidently be chosen to be part of the combined system. For future development of this research there should be more investigation into these different classifiers as well as other options not explored in this research. This combined system would then be able to detect the smaller and slower-moving asteroids with the help of the preprocessing steps as well.

This image shows how a non-asteroid might look as compared to the previous images of asteroids.

REFERENCES

[1] Ruprecht, J., “Asteroid Detection Results Using the Space Surveillance Telescope,” in Advanced Maui Optical and Space Surveillance Technologies Conference, 2015.

[2] D. A. Duev et al., “DeepStreaks: Identifying Fast-Moving Objects in the Zwicky Transient Facility Data with Deep Learning,” Mon. Not. R. Astron. Soc., vol. 486, no. 3, pp. 4158–4165, 2019, doi: 10.1093/mnras/stz1096.

[3] A.C. Rabeendran and L. Denneau, “A Two-Stage Deep Learning Detection Classifier for the Atlas Asteroid Survey,” Publ. Astron. Soc. Pacific, vol. 133, no. 1021, 2021, doi: 10.1088/1538-3873/abc900.

[4] C. J. Fluke and C. Jacobs, “Surveying the Reach and Maturity of Machine Learning and Artificial Intelligence in Astronomy,” Wiley Interdiscip. Rev. Data Min. Knowl. Discov., vol. 10, no. 2, pp. 1–40, 2020, doi: 10.1002/widm.1349.

[5] J. Kremer, K. Stensbo-Smidt, F. Gieseke, K. S. Pedersen, and C. Igel, “Big Universe, Big Data: Machine Learning and Image Analysis for Astronomy,” IEEE Intell. Syst., vol. 32, no. 2, pp. 16–22, 2017, doi: 10.1109/MIS.2017.40.

[6] J. R. Masiero, A. K. Mainzer, J. M. Bauer, R. M. Cutri, T. Grav, E. Kramer, J. Pittichová, and E. L. Wright, “Asteroid Diameters and Albedos from NEOWISE Reactivation Mission Years Six and Seven,” The Planetary Science Journal, vol. 2, no. 4, p. 162, 2021.

[7] A. Mahabal et al., “Machine Learning for the Zwicky Transient Facility,” Publ. Astron. Soc. Pacific, vol. 131, no. 997, p. 38002, 2019, doi: 10.1088/1538-3873/aaf3fa.

[8] E. A. Smirnov and A. B. Markov, “Identification of Asteroids Trapped Inside ThreeBody Mean Motion Resonances: A Machine-Learning Approach,” Mon. Not. R. Astron. Soc., vol. 469, no. 2, pp. 2024–2031, 2017, doi: 10.1093/mnras/stx999.

[9] J. D. Ruprecht, H. E. M. Viggh, J. Varey, and M. E. Cornell, “SST Asteroid Search Performance 2014-2017,” IEEE Aerosp. Conf. Proc., vol. 2018-March, pp. 1–8, 2018, doi: 10.1109/AERO.2018.8396388.

[10] R. L. Jones et al., “The Large Synoptic Survey Telescope as a Near-Earth Object Discovery Machine,” Icarus, vol. 303, pp. 181–202, 2018, doi: 10.1016/j. icarus.2017.11.033.

[11] M. Lieu, L. Conversi, B. Altieri, and B. Carry, “Detecting Solar System Objects with Convolutional Neural Networks,” Mon. Not. R. Astron. Soc., vol. 485, no. 4, pp. 5831–5842, 2019, doi: 10.1093/mnras/stz761.

[12] P. Vereš, R. Jedicke, L. Denneau, R. Wainscoat, M. J. Holman, and H.-W. Lin, “Improved Asteroid Astrometry and Photometry with Trail Fitting,” Publ. Astron. Soc. Pacific, vol. 124, no. 921, pp. 1197–1207, 2012, doi: 10.1086/668616.

[13] A. Waszczak et al., “Small Near-Earth Asteroids in the Palomar Transient Factory Survey: A Real-Time Streak-Detection System,” Publ. Astron. Soc. Pacific, vol. 129, no. 973, 2017, doi: 10.1088/1538-3873/129/973/034402

[14] Stetson, P. B., “DAOPHOT: A Computer Program for Crowded-Field Stellar Photometry”, Publ. Astron.l Soc.Pacific, vol. 99, p. 191, 1987. doi:10.1086/131977.

Kankakee in Deindustrialization: An Oral History Approach

ACKNOWLEDGEMENTS

I would like to thank my Lord and Savior Jesus Christ for the opportunity, ability, and perseverance to see this project to completion. It was through His strength and guidance that I have made it to where I am. I would also like to thank my mentor professor, Dr. Case, for the help, patience, and expertise he brought to me and my project. I thank Olivet Nazarene University’s Honors Program and supporting professors and staff who aided in the completion of this project. Lastly, I would like to thank my fiancé, Connor Cavanaugh, for listening to me as I discussed my project for hours with him. It was his listening ear and encouragement that kept me going even when I didn’t see finished results of my work.

ABSTRACT

The City of Kankakee was an industrialized city that prospered economically for decades. Throughout the late 1970s and 1980s, economic trends shifted for Kankakee and the surrounding communities. The major factories, such as Roper Corporation and A.O. Smith, migrated their source of production from Kankakee to other regions of the United States and abroad during the 1970s and 1980s. As a result, the declining industrial economic activity led to changing community perceptions. Kankakee is an example of the “Rust Belt” region, a region in the Midwestern and Northeastern States of the United States where declining industrial activity occurred throughout the 1970s and 1980s. The paper uses an Oral History Approach to investigate the changing economic landscape and community and individual perceptions of Kankakee during the Deindustrialization period.

INTRODUCTION

Kankakee: Home of the Twin Gazebos

The story of a city is formed by the people who came before, by the people who live there now, and from people outside the community, contextualizing the place within a greater geographic and historical context. Kankakee is one such city with a varied past with varied stories. While the name “Kankakee” remains the same, the reputation, culture, economy, structure, and people change over time. The city continually transforms, never staying stagnant. However, there are some moments in the history of a city that are catalysts for more significant change. Such was the case in Kankakee back almost forty years ago. But before arriving to tell those stories, there is another story to be told.

The year was 1999, and Places Rated Almanac had just released their “Guide to Finding the Best Places to Live in the United States and Canada.” Out of 354 designated metropolitan areas, Kankakee, Illinois, ranked last. This was a blow to the community, and the embarrassment was increased when late night comedy host David Letterman mocked Kankakee on live television. In a segment called “Top 10 slogans for Kankakee, Illinois,” Letterman offered these potentials, “You’ll come for a pay phone. You’ll stay because your car’s been stolen . . . Ask about our staggering unemployment rate . . . We put the ill in Illinois . . . We also put the annoy in Illinois.”1

David Letterman called the mayor of Kankakee, Donald Green, and broadcasted the conversation on The Letterman Show. Letterman asked if the rating had had a negative impact on the community. As Mayor Green explained, Letterman interrupted and asked, “Do you think it has anything to do with the name itself, Kan-ka-kee?” “No,

1. Ira Glass, “554: Not It!” This American Life, April 10, 2015. https://www.thisamericanlife. org/554/transcript.

Kankakee is a fine name!” exclaimed Mayor Green. When Letterman asked Green if he knew what the name meant, there was short pause before Mayor Green declared, “It means middle class factory town,” which received a host of claps and laughter from the crowd.2

David Letterman proceeded to donate two gazebos to Kankakee so the city could henceforth be known as the “Home of the Twin Gazebos,” a mocking attempt at helping to change the reputation of the “middle class factory town.”3 Kankakee had been publicly humiliated by the whole situation. But this raises the question of how Kankakee arrived at the place where it was considered the worst place to live in the United States and Canada. What was the context that led to Kankakee being ranked the worst place to live and being nationally mocked on television? What were the events that led up to this? And, just as Letterman asked Green, how did these events affect the Kankakee community?

As Mayor Green stated, Kankakee was known as a “middle class factory town,” one of many in the Midwestern region. Kankakee was once a booming metropolis of industry, productivity, and wealth. What happened to change this trend? And how did this affect the people of Kankakee? The poor livability rating Kankakee received in 1999 was influenced by changes in the community twenty years prior, back in the 1970s and 1980s.

During the 1980s, national economic trends were transforming the economy of Kankakee, resulting in visible changes in its physical landscape and that of its two closest suburbs, Bourbonnais and Bradley, as well as change in the community’s self-assessment. The city’s prosperity was built on industrial power, supported by a strong blue collar employment base and the railroad lines that stretched to Chicago and beyond. During the 1980s, Kankakee’s industrial economic base transformed as industries left the area, a process known as deindustrialization. Deindustrialization took place not only in Kankakee but in the greater Midwestern and Northeastern regions of the United States. As these different parts of Kankakee’s history fit into the puzzling question of how Kankakee reached this point of being the lowest ranked metropolitan region in the nation, the guiding questions for the research became,

1. How did the deindustrialization process of Kankakee in the 1980s affect the lives of Kankakee residents?

2. How did residents respond to the economic conditions?

3. How have personal histories and memories of these events shaped the history of the deindustrialization time period in Kankakee into the present day?

Places Rated Almanac uses statistics to give metropolitan areas a livability score. But a place is far more than its statistics. To truly understand a place and its people, one must hear the stories its people have to share. Statistics, while useful, do not paint the full picture. It is through the lived experiences of those people who have spent their lives in a community that a community’s past, present, and future can be understood. The stories recalled and recounted in this project are stories of people who have lived in Kankakee throughout the economic changes of the 1970s and 80s. These are the voices of interest here, because they are the voices gathered from those who saw the changes in the community firsthand.

Oral history approach

The stories portrayed by people from Kankakee yield conclusions on the state of the community throughout a time of change. These stories are memories of the past: the words, artifacts, feelings, and thoughts that resonated with people so greatly they become part of the history of Kankakee. There are different classes of historical evidence, but “of the three general classes of historical evidence (documents, artifacts, and memories), evidence in the human memory is the most fragile and ephemeral. The oral history interview transforms fragile memory into a permanent record of the past that is both valuable and—given the passage of time—quite irreplaceable.”4 Once the people who lived during deindustrialization are gone, unless documented by oral history, their stories and memories are gone as well. As such, listening to and recording the stories of the past for communal posterity is of great importance.

Oral history is the active participation of people telling the stories of the past that they witnessed or experienced. According to the Oral History Association, the best practices for oral history research include four key elements: preparation, interviewing, preservation, and access and use.5 With the four elements in mind, oral history becomes a rich source of information in telling the story of Kankakee during the deindustrialization period.

The value of oral history lies in how it helps “place people’s experiences within a larger social and historical context. The interview becomes a record useful for documenting past events, individual or collective experiences, and understandings of the ways that history is constructed.”6 The deindustrialization period in Kankakee was

4. Thad Sitton, George L. Mehaffy, and O. L. Davis. Oral History: a Guide for Teachers (and Others) 1st ed. Austin: University of Texas Press, 1983.

5. Oral History Association, “Best Practices,” 2021, https://www.oralhistory.org/best-practices/.

6. Oral History Association, “OHA Core Principles,” 2021, https://www.oralhistory.org/ oha-core-principles/.

comprised of both specific events and a prolonged trend in the community. Gathering the perceptions of Kankakee residents who stayed in the region even as the large manufacturing companies left provides insight into how a community recovers from national trends that Kankakee residents could not control. The events which transpired in Kankakee in the late 1970s and early 1980s were an example of larger regional and national trends in economic policy and corporate decisions to move sources of production from the Midwestern region.

Changing trends in economic policy

United States’ national economy policy shifted throughout the 1970s and into the 1980s. Throughout the 1970s, it went from being dominated by Keynesian economics, focusing on aggregate demand determining market activity to remedy downturns in the market through monetary and fiscal policy, to Neoliberal economics, focused on allowing the market to correct itself without aid from government intervention.7 This shift in economic thought occurred due to several characteristics present throughout the 1970s. During the 1970s, “the U.S. economy experienced high and fluctuating inflation, lagging productivity growth, increased regulation, and stifling of economic incentives.”

Rising national inflation rates throughout the 1970s were attributed to increased monetary expansion, a result of government intervention in the economy. In addition to rising inflation, national economic goals changed from increasing to redistributing income and wealth to American citizens, rather than focusing on expanding American industry. By the end of the 1970s, “the federal government was spending more on transfer payments to individuals than on purchase of goods and services . . . [B]y dollar volume, the government’s major role was to redistribute income, not provide goods and services.”8 The redistribution, rather than generating new wealth, is significant because it is an example of the national economic slowdown. In response to national changes, Americans increasingly looked to another economic school of thought to pull the nation out of this slowdown and reinvigorate economic growth.

Neoliberal economics became the school of thought most prevalent in national economic decisions when Ronald Reagan, a proponent of the neoliberal economic policies, was elected president in 1980. Neoliberal economic policies follow from the idea that the federal government should be less involved in the work of the state and local governments; thus, the federal government should offer less financial help to state and local municipalities. One goal of Reagan’s efforts in the economic sector was to push fiscal responsibility of local programs onto local governments rather than keeping responsibility at the federal level. Federal government funding cuts affected

7. Palley, T. I. “From Keynesianism to Neoliberalism.” In Saad-Filho, A., & Johnston, D. (Eds.). Neoliberalism: A Critical Reader (Pluto Press, London, 2015): 20-30.

8. Michael Boskin, Reagan and the Economy: The Successes, Failures, and Unfinished Agenda. (San Francisco: I.C.S. Press, 1987), 18.

services for local municipalities with a low potential for generating revenue within the municipality. Municipalities that were able to generate sufficient revenue were not as affected since they were more financially independent.9 Though one goal of these economic policies was to correct prior economic initiatives, several outcomes generally led to less desirable economic environments for working classes. For example, Neoliberal economic policies allowed the real value of the minimum wage to fall, undermined unions, and created a labor market of employment insecurity.10

The changes in economic policy under Reagan contributed to the conditions for deindustrialization, as well as worsening the economic effect on people due to the departure of industry. Throughout the 1970s and 80s, the Midwestern and Northeastern regions of the United States, commonly referred to as the Rust Belt region, slowly lost their industrial employers. The loss of industries that were pillars of economic progress in the region resulted due to several factors in addition to the changes in national economic policy.

Examination of the Rust Belt

The Rust Belt refers to a region within the Northeast and Midwest states where factories and other manufacturing facilities once operated but have since been abandoned for areas such as the Southern states, leaving rusting factories, declining populations, and high unemployment rates.11 The events that put the creation of the Rust Belt into motion began in the 1970s as economic trends began to change, continuing into the 1980s when many manufacturing facilities moved their industries to other regions. There are several overarching causes for these regional trends besides the influence of neoliberal economic policies.

One plausible reason for the decline of industry in what would become the Rust Belt was due to the reduction in the location-specific advantages in the goods-producing sector.12 As the world became more globalized, there was less need to keep production facilities close to places of commerce. The Midwest was geographically positioned to be a hub for manufacturing and exporting products to other regions of the country due to its extensive waterways and railroads. However, the Midwest’s geographic advantage decreased due to globalization. Globalization allowed goods to be transported at a reduced cost. Additionally, some historians argue the Rust Belt region declined due to the rapid technological change and economic globalization in the manufacturing

9. John P. Forrester. and Charles J. Spindler, “Managing Municipal Services in an Era of Declining Federal Assistance,” Policy Studies Review, 1990, 63-64.

10. Palley, “From Keynesianism to Neoliberalism,” 22.

11. Thomas Quain, “Leaving College without a Degree: Oral Histories from the Rust-Belt.” PhD diss., State University of New York at Binghamton, 2020.

12. Chamna Yoon, “The Decline of the Rust Belt: A Dynamic Spatial Equilibrium.” PhD diss., University of Pennsylvania, 2013, 475.

industry.13 Other reasons include a significant decline in the aggregate and manufacturing employment share, higher wage premiums than other regions, and low productivity growth within Rust Belt industries leading up to the 1980s.14 This is significant because the Rust Belt region was the hub of domestic manufacturing in the United States throughout the 1960s, and when the hub of the manufacturing enterprises moved so did a significant proportion of the wealth of the Rust Belt region. Additionally, wage premiums were generally higher in the Rust Belt region due to larger and more prominent union influences than in the Southern states to which many manufacturers migrated. This was due in part to the long establishment of manufacturing in the Rust Belt region, as opposed to the South which was not yet a hub of domestic manufacturing. The redistribution of wealth in terms of industrial production benefitting the geographic area in which it resides to other regions left lasting implications on the Rust Belt metropolitan areas.

Manufacturing employers within the Northeast and Midwest industrialized cities moved the centers of their operations to other regions across the United States and throughout the world. In the United States, the aggregate employment share of the Rust Belt dropped from 39% in 1960 to 29% in 1990. The Rust Belt’s manufacturing share as a percentage of total US manufacturing dropped from 47% in 1960 to 38% in 1990.15 For example, deindustrialization of Pittsburgh, a hub of steel manufacturing, began in the 1970s but increased significantly in the 1980s. The Allegheny Conference, an organization founded to improve the economic prospects of Pittsburgh’s future, found it difficult to maintain the economic vitality of Pittsburgh, competing against the allures of the suburbs and a continued dependence on mills and mines, two of the industries still in production after the closing of steel factories.16

Similar trends unfolded in Flint, Michigan, where the city’s deindustrialization and economic downturn was affected by suburbanization and the building of new highways along with the outsourcing of jobs to the surrounding suburbs and a subsequent erosion of the city’s tax base.17 From 1978 to 1989, 30,000 people lost their jobs in Flint when General Motors moved their source of production. In total, GM moved eleven U.S. based plants to Mexico. One GM lobbyist commented that GM moved b ecause it “wouldn’t be doing anyone any favors if [GM] goes bankrupt. [GM needed to move] in order to stay competitive in today’s economic climate.” Ronald Reagan

13. Chamna Yoon, “The Decline of the Rust Belt,” 475.

14. Simeon Alder, David Lagakos, and Lee Ohanian, ”Competitive Pressure and the Decline of the Rust Belt: A Macroeconomic Analysis,” National Bureau of Economic Research, (2014): 10.

15. Alder, Lagakos, and Ohanian, ”Competitive Pressure and the Decline of the Rust Belt,” 6.

16. Allen Dietrich-Ward, Beyond Rust: Metropolitan Pittsburgh and the Fate of Industrial America (University of Pennsylvania Press, 2017).

17. Andrew Highsmith, Demolition Means Progress: Flint, Michigan and the Fate of the American Metropolis (The University of Chicago Press, 2015).

visited Flint to speak with the GM workers who were let go, urging workers to remain positive through the tough times workers were experiencing. Additionally, Reagan informed the workers of manufacturing possibilities in the South. However, few, if any, of the workers Reagan spoke with ever returned to manufacturing work. Though the efforts were received in mixed terms, some which sided favorably with Reagan’s efforts to meet the issues of the let go workers, there is no evidence these meetings resulted in prolonged economic recovery and change for the workers.18

Dozens of other industrialized cities in the Midwest faced the consequences of declining industrial activity during the 1970s and 1980s. Despite overall trends of Rust Belt cities, each is unique in terms of the industries which left, its geographic location, socioeconomic makeup, and responses to the process of deindustrialization. Kankakee was another that had to alter once industry left.

Kankakee’s manufacturing base consisted of several key employers that altered the trajectory of the city once they departed. These included A.O. Smith, a water heater plant, Roper Corporation’s two facilities, one in Bradley and one in Kankakee, producing kitchen stoves and outdoor power equipment, and Kroehler, an upholstered furniture manufacturer.19 Amongst these major manufacturing facilities as well as more minor manufacturing facilities, the total number of workers employed in manufacturing numbered close to 10,400 in 1978. All three of the manufacturing facilities closed within a ten-year period, leaving high unemployment rates in Kankakee, up to 21.4% in February of 1983.20 Kankakee was a textbook example of an industrial city seeing the effects of deindustrialization.

METHODS

Investigating the stories of Kankakee in the 1970s and 1980s and into the twenty-first century involved conducting interviews with Kankakee County residents. In keeping with Oral History Association guidelines, interviews were conducted with the four key components in mind: preparation, interviewing, preservation, access and use. Preparation for the interviews included primary and secondary research into the history of deindustrialization in Kankakee. Preparatory research allowed for deeper discussions into aspects of deindustrialization in Kankakee with a working knowledge of the key employers in the area and the story behind how and why factories left Kankakee. Interviewing included seeking out potential interviewees, informing them of the purpose and intent of the research, then conducting the interviews with the participants. Interviews ranged from half an hour to two hours in length. In total, eight formal interviews

18. Michael Moore, director. Roger and Me. Dog Eat Dog Films, 1989. 1 hr., 31 min.

19. Steve Benscoter, “Learning Lessons the Hard Way: An Analysis of the Economic Plight of City of Kankakee,” Undergraduate Review 3, no. 1 (1989), 33.

20. Vic Johnson, An Illustrated Sesquicentennial Reader: Kankakee County, Illinois, 1853-2003, (Kankakee County Historical Society, 2004).

were conducted. Interviews were recorded for the sake of gathering accurate quotes and statements from the interviewees. The interviewee’s statements are preserved within the remaining portions of the paper. The knowledge gained from the oral history interviews is to be accessed and used through ONU’s Honors Program journal, ELAIA. Oral history interview recordings are normally made accessible for public use, but for the sake of confidentiality of the interviewee’s identities the recordings of the interviews conducted for this project will not be made accessible. Instead, the recollections of the people interviewed are captured through the quotes and stories told in the thesis. All four of these aspects of the oral history process honor the people who told their stories.

Eight people from Kankakee and the surrounding villages, Bourbonnais and Bradley, were interviewed. All interviewees received an informed consent form describing the purpose and procedures of the research. All interviewers signed the informed consent form before the interview began. All interviewees lived in Kankakee throughout the deindustrialization period, ranging from the late 1970s to late 1980s. The professions of the interviewees varied, though a considerable portion of jobs were service oriented. One of the participants worked in one of the manufacturing facilities and lost her job due to deindustrialization. The other interviewees, though influenced by the loss of industry, did not directly work in manufacturing. As a result, most of the participants did not lose their jobs. All the participants saw visible changes in the community as the process of deindustrialization took place in Kankakee County. The interviews were conducted either in person in several locations throughout Kankakee County or over Zoom.

Interview questions focused on perceptions and recollections of when industry left Kankakee and how the community changed once the industries left. The openended questions asked for thoughts on the tone of the community, their own personal reflections on the loss of industry, and the visible changes they saw in Kankakee during and after the process of deindustrialization.

The methods for the project were inspired by John Hershey’s journal articles that were turned into a novel on the bombing of Hiroshima, titled Hiroshima. John Hershey (1914–1993) was a journalist who travelled to Japan to collect first-hand accounts of the bombing of Hiroshima through interviews. In his articles, he interwove the stories of six people who each had a unique background and location in the city when the bomb fell. Hershey’s documentation of the bombing earned him acclaim in the United States. From this acclaim, a school board in a suburb of Chicago chose to name a newly built school in his honor. As a freshman in that high school, I read Hiroshima and was struck by how Hershey interwove personal stories into a cohesive narrative. His recounting of the stories resonated with me and inspired me to pursue the oral history project on Kankakee’s deindustrialization.

Additional inspiration came from Lauret Savoy’s Trace: Memory, History, Race, and the American Landscape, a retrospective look on how the stories and memories of

the people and the land in America have been told and preserved. In her book, Savoy explores what it means to “re-member”: to know there are traces and patterns of the past that can be uncovered. She laments the loss of past voices, the untold stories of people who have gone before. This idea also resonated with me and fed my interest in oral history. I find it extremely important to retain the stories of the past from people who lived through the events. The combination of these two interests led me to exploring the oral histories of Kankakee residents during a time of economic change.

Interviews

1960s

Throughout the 1960s, Kankakee’s economic growth manifested in the busy downtown streets and continued construction of industrial and commercial buildings. The physical landscape, as well as the economic outlook of Kankakee, looked productive and thriving, steadied upon industries with a strong employment base of industrial laborers. Sarah P., born in the 1940s, grew up in Bradley, a village adjacent to the City of Kankakee. Bradley used to be named North Kankakee, but this changed in 1895 when the David Bradley Plow Works factory relocated to the village, an early indication of the importance industry would play in the village’s development. Sarah grew up in a union household, her father a supervisor at the Bear Brand hosiery company that produced women’s hosiery. The factory, located in downtown Kankakee on West Avenue and in operation since the early 1900s, closed its doors in 1968 due to increasing production costs and overseas competition.21 Sarah recalls as a teenager in the late 1960s walking from Bradley to Schuyler Street in downtown Kankakee to shop with her friends. She recalls the bustling of the stores in downtown Kankakee as well as the 8-block radius called ‘the square’ where young people would go to drive their cars and hang out.22 She remembers going to the Paramount theatre with her friends, as well as the candy store downtown called Johnson’s Candy Kitchen. Of these places Sarah explored as a young woman, only the Paramount theater remains.

The geographic periphery of downtown Kankakee was where the major industries of Kankakee were located, industries which made the bustling of the downtown area possible. The industries, though on the periphery of the geographical landscape of Kankakee, were anything but peripheral to the economic achievements of Kankakee’s growth, evidenced by several economic achievements of the manufacturers in Kankakee County. In 1964, the Kankakee Industrial Development Association organized for the purpose of encouraging continued industrial expansion.23 Then, in 1965, Kroehler

21. Jack Klasey, “Remembering ‘The Bear Brand,’” Daily Journal, October 29, 2016, https:// www.daily-journal.com/news/local/remembering-the-bear-brand/article_3b506af8-bd99-5 e86-916a-66eed9e59fdc.html

22. Sarah P., interview, December 10, 2021.

23. Johnson, An Illustrated Sesquicentennial Reader, 280.

Manufacturing Company, an upholstered furniture manufacturer in Bradley, became the first furniture factory in history to reach a sales volume of over $100,000,000 in one year.24 It was during this period of Kroehler’s economic prosperity that Sarah, a high school graduate in 1967, started her work as a payroll supervisor at Kroehler Manufacturing, a job she held for 18 years.25 In the same year, Roper Corporation announced plans for a $500,000 addition to their product engineering building, an implication that Roper was investing in not only the company but in its presence in the Kankakee community.26 The physical landscape of Kankakee and its surrounding suburbs grew just as the manufacturers that benefitted from the infrastructure of Kankakee continued to grow and prosper.

Corporations manufacturing goods were not the only ones benefiting economically. The manufacturing corporations of Kankakee were unionized, leading to higher wage premiums for union workers. In 1969, the hourly wage for a Roper factory worker was $5.94 per hour, while Southern plants paid $2.97 per hour.27 The union presence in Kankakee manufacturing was strong, and the relationship between management and union workers led to numerous strikes throughout the decades. In 1966, six unions within Roper’s facilities struck, leading the Roper plants to close for thirteen weeks.28 Several years later, in 1969, another strike at Roper closes the plant for several weeks. The strikes were common knowledge in town, as Mark J., another interviewee, recalled several bitter strikes taking place throughout the years.29

1970s

As Kankakee moved into the next decade economic growth continued. Michael J., a pastor and then president of Olivet Nazarene University who moved out of Kankakee in 1972, echoed similar remarks to that of Sarah P., recalling that, “Kankakee was still vibrant, the downtown Kankakee was really a kind of a destination. The mall had not been built for one thing. There were department stores and restaurants, [downtown Kankakee] was very positive.”30 One unique business that continued to prosper in the 70s was the Yesteryear, a fine dining restaurant located at Frank Lloyd Wright’s house located on the Kankakee River, just South of Kankakee’s downtown area. Yesteryear had been in operation since 1952. Sarah recalled going to the Yesteryear Restaurant for Kroehler’s company holiday party. A few decades later, however, this would be the site of a horrific crime that cast its shadow on the town.

24. Mary Jean Houde and John Klasey, Of the People: A Popular History of Kankakee County (Kankakee County Board of Supervisors, 1968), 419.

25. Sarah P., interview, December 10, 2021.

26. Houde and Klasey, Of the People, 419.

27. Steve Benscoter, “Learning Lessons the Hard Way,” 33.

28. Johnson, An Illustrated Sesquicentennial Reader, 281.

29. Mark J., interview, October 6, 2021.

30. Michael J., interview, November 10, 2021.

One of the major factories and employers in Kankakee, Roper Corporation, continued its expansion in 1970. But Roper expanded its sources of operation elsewhere. Roper announced its plans in 1970 to open a new facility in LaFayette, Georgia. Questions immediately arose in Kankakee whether the opening of a new facility in LaFayette meant Roper’s Kankakee facilities would close. There were important differences between the Kankakee and LaFayette facilities. Though the Kankakee factories had operated for several decades, the LaFayette factories would be newly built. The acquisition of the new southern Roper factory came about because of a decision made by the newly appointed Chief Executive of Roper in 1967, Max Hoover. In a press release in 1969, Hoover stated that the Kankakee plant, “has the highest labor rate in the stove manufacturing business and the worst productivity. We possibly could have lived with the rate, but not both of them . . . We decided we couldn’t win here. We decided to restructure the company.” One of the decisions of “restructuring” included the initial acquisition of new factories and then relocation of Roper facilities. The acquisition of the plant in LaFayette proved to be profitable when Roper Corporation’s total productivity in 1974 increased from 15 to 18 percent. According to Crain Chicago Business, “Max Hoover had revitalized his company, Roper production costs were cut by building southern plants.”31 But back in 1969, Roper’s corporate office had not yet made the decision to relocate down to the South. At the time, it simply looked as if Roper was expanding their places of production.

It did not take long for Roper union workers to catch on a possible decision by Roper to leave the area. In 1971, the Stovemounters Local union at Roper argued that, “we could produce so much more than they [the South] could, so it was cheaper on a stove by stove basis than down South.”32 Kankakee unions felt the need to justify their importance to Roper Corporation. Their pitch was that even though wages were higher in the North than in the South, the Kankakee union workers produced stoves faster than other workers in other regions like the South would.

In addition to tensions between the corporations and the local union chapters, rising inflation, a characteristic of the late 1970s national economic climate, affected the corporations located in Kankakee. In one Daily Journal article, Hoover discussed the outlook for 1974, saying, “we talk to a lot of economists in order to forecast our future performance. In previous years many of them were willing to predict trends in the economy with few, if any, qualifications. There is more reluctance in 1974. Most economists frankly admit ‘we don’t know’ about the oil supply and price and wage controls which are the major causes of current material and parts shortages and inflation.”33 National changes were beginning to see their effects in Kankakee’s employment as the nation moved into the next decade.

31. Johnson, An Illustrated Sesquicentennial Reader, 320, 318.

32. Johnson, An Illustrated Sesquicentennial Reader, 280.

33. Daily Journal, “Roper”, February 5, 1974.

1980s

At the turn of the decade, the job employment situation became one of the most discussed issues in Kankakee County. An article in the Daily Journal stated, “the region that was built on the backs of blue-collar men and women would never be quite the same.” From 1978 to 1983, the number of industrial jobs in Kankakee dropped from 10,400 to 6,400.34 In just six years, 4,000 jobs were lost due to the slow removal of the larger manufacturing employers in Kankakee. As the number of manufacturing jobs decreased, so too did the number of people residing in Kankakee. In 1980, there were 102,926 residents in Kankakee County. By 1986, the number of residents fell to 95,926.35

There were several reasons Roper Corporation and A.O. Smith left the area. One was tensions between management and the unions within the factories, leading to strikes over the years. In addition to lower wage costs, another plausible explanation for the choice of manufacturers to leave Kankakee was aging facilities. In one article from the Daily Journal , Robert Wood, the chief attorney for Roper Corporation, acknowledged that the functions of the Kankakee facilities moving to Tennessee and Georgia, had “more favorable worker compensation, unemployment insurance and tax rates . . . in addition to the Kankakee and Bradley facilities are older and less efficiently laid out than Roper’s newer plants in the South.” 36 David R., another interviewee and an architect by trade, reflected on his time working at an office close to A.O. Smith’s factory. He would walk around the industrial park during his lunch breaks and noticed several aspects of the architectural design of the older facilities. He explained how the factories had been built during the World War II period which were a combination of masonry and steel. “Being the 1940ish buildings, they were not as open-spaced-planning as modern buildings, which are steel columns, wide spans, and I can have a dynamic building. So the design of the building and the materials used would inhibit some dynamics, some open planning, some growth and change. But, at the same time, to say ‘my building is old and falling apart and decrepit, therefore I’m moving’—whose fault is that for not replacing the roof, for not painting, for not upgrading the electrical?” 37

Kankakee community leaders saw that given the state of their buildings, it was most likely the manufacturers would leave within the next several years. In the Kankakee Area Chamber of Commerce Annual Report for 1982, Donald McCann from First Bank of Meadowview and past Chairman of the Board wrote, “It is my forecast that the Kankakee area will lose 1,500 manufacturing jobs in the next three years. Depending on what statistical evidence you wish to use, the capital investment that it takes to

34. Johnson, An Illustrated Sesquicentennial Reader, 386, 387.

35. Federal Reserve Bank of St. Louis, “Resident Population in Kankakee County, Illinois,” https://fred.stlouisfed.org/series/ILKANK0POP

36. Jerry Morgan, “Local Roper shutdowns permanent,” The Daily Journal, June 18, 1982. 37. David R., interview, November 8, 2021.

create 1,500 manufacturing jobs is between $60,000 and $75,000. It is quite unlikely that during this same three-year period $60,000 to $75,000 will be spent by manufacturers relocating to our area.”38 McCann understood that the fabric of the community was about the alter and the community needed to prepare for these changes. Even with investment from the city in manufacturing, there was an awareness that bringing new jobs to Kankakee would not cover the loss of well-established industries like Roper and A.O. Smith.

Crain’s Chicago Business wrote a rather critical account of Kankakee’s attempts to keep Roper and A.O. Smith in Kankakee. One portion of the editorial was titled “Kankakee: A City and State of Mind,” highlighting several of the misconceptions Kankakee residents had about the industries’ choice to leave Kankakee. The four myths Crain’s Chicago Business pointed out were “there’s nothing we could have done to keep the plants here that move South,” “Just wait. What happened to us [the Midwest] will happen to them [the South],” “Our manufacturing plants really were productive,” and “(Fill in name of CEO) is a jerk.”39 These sorts of sentiments were echoed by interviewee David R., who stated that within Kankakee’s community, “There were rumors that the wages in the South were half of those in Kankakee because they only worked half the time. Who benefits from that story? The people who used to be workers. Then you hear of plants closing ‘okay, Smith or Roper, maybe the deal wasn’t as good as you thought.’”40 There was talk that the workers at the new Roper Plant would frequently take time off, resulting in the closing of the plant. Whether this was fact or fiction, Kankakee residents still believed themselves to be a more profitable “factory town” than the locations to which Roper and A.O. Smith moved. There was, at least in a portion of the Kankakee population, a desire to preserve the reputation of the Kankakee workers who had supported the actions of the unions throughout the decades leading up to the closing of factories in the 1980s. Additionally, many of the workers never thought that the talk of the factories leaving would ever come to fruition. Interviewee Michael J. commented that since many people did not actually believe the factories would leave, when the factories did leave, it sent shockwaves through the community.41 Throughout the 1980s, the population of Kankakee County slowly declined. During the decline in population, there was a lack of need for new housing. Charles S. was a young commercial realtor in Bourbonnais during the 1980s who witnessed the stagnation of the housing market when the factories left. When he was in college, he had a job helping with the construction of the Grand apartments near ONU as well as the Olde Oak and Oak Run apartments. Charles recalled that the Briar Cliff and Plum

38. Kankakee Area Chamber of Commerce, “Annual Report for 1982 and Program of Work for 1983,” 1982.

39. Crain’s Chicago Business, “Kankakee: What happened to the Midwest... and why,” April, 29, 1984.

40. David R., interview, November 8, 2021.

41. Michael J., interview, November 10, 2021.

Creek subdivisions of Bourbonnais that had been planned to be built were put on hold for ten to fifteen years, since there was no need to build new houses if people were not moving in. Many of the roads had already been paved, but the lots largely sat empty with the exception of intermingled houses which had already been sold and built.

Thomas B. was in grade school when Roper Corporation and A.O. Smith left Kankakee. As a child, he did not fully comprehend the economic changes taking place in his community. What he did know was that as his school year progressed, there were classmates who were missing. He remembers that as the school year went on there were kids in his classes who never came back. He always wondered what happened to them and how their families were doing.42

David R. also saw the effects of the loss of employment within Kankakee’s schools meant to support the Kankakee community. The local church David attends also has a school, which suffered when the major industries left. The members of the church were comprised of blue-collar laborers who, when they lost their jobs, left the area. As a result, the school that had more than 200 children dropped to around 125 within several years. It was evident that the decrease in enrollment was due to the loss of jobs of many of the church’s members. David recalled that at many of the factories in the area, there were second and third generation factory workers, “So when those factories closed, Grandpa was out of work, Dad was out of work, and the young Son was out of work. Major hit to the families.”43

In addition to educational facilities, what was once the hub of Kankakee’s local commerce altered with the changes brought about by deindustrialization. William D. was a young attorney during the 1980s who saw the downtown area alter significantly through the decade. He lamented how downtown Kankakee was one of the cultural casualties for Kankakee County. The downtown area represented the collapse of Kankakee. The residents of Kankakee began to view Kankakee in a less desirable light. He also recalled a ridiculous picture of Court Street, devoid of people, with a tumbleweed blowing across the street. The sensationalized picture reflected views people had of the Kankakee area. Kankakee’s downtown, once a center for commerce and gatherings, appeared to be deserted. Deindustrialization alone was not the cause of the desertion of the downtown area. Even as the manufacturing jobs in Kankakee disappeared, Roper’s presence lingered in the community up until 1988, when Roper Corporation was bought out by General Electric and Whirlpool. With the change in ownership, the seventy corporate Roper workers in Kankakee were “phased out” over a few months in 1988.44

Even amongst the hard times in Kankakee, local community leaders attempted to boost the community’s spirits. One such man was Stephen Small (1947–1987), a

42. Thomas B., interview, December 8, 2021.

43. David R., interview, November 8, 2021.

44. Marx Gibson, “Roper tells 70 workers here: ‘Thanks, bye,’” April 14, 1988.

local businessman and owner of the Daily Journal, who bought the deteriorating Frank Lloyd Wright house, once the Yesteryear restaurant. Small’s goal was to renovate the home. But before the project was completed, disaster struck. In September of 1987, Stephen Small was kidnapped at the Frank Lloyd Wright property and held for a ransom of one million dollars in cash by another man from Kankakee. Unfortunately, he died within several hours of being buried alive underground. Several of the interviewees mentioned the impact Stephen Small’s murder had upon the already fluctuating community. Michael J. remarked that the kidnapping and murder of Stephen Small, “created a snowball with Kankakee’s bad reputation.”45 The kidnapping and murder of Stephen Small made national news and “shook the community” further.

William D. described how the perceptions of a dangerous downtown Kankakee contributed to “white flight” to Bourbonnais and Manteno. Thomas B.’s family lived close to the downtown area of Kankakee. They moved briefly to another Illinois city before moving back, except this time their home was outside of the downtown area. Thomas recalls seeing his childhood home boarded up, the surrounding homes also in disrepair. It is a memory that has stuck with him into his adulthood, a memory that bothered him as a child and continues to make him reflect on the state of Kankakee.46

Speaking to the interviewees, there was one common thread which bound their stories together. Amongst all the changes in Kankakee in the 1980s, there was a phrase which stood out to the members of the community, a phrase which seems to be engrained in the minds of the people who live in Kankakee today: “Last one out of Kankakee, turn out the lights.” A silly sounding phrase, and yet it was echoed again and again by the interviewees who recalled their memories from Kankakee’s deindustrialized past.

The phrase “Last one out of Kankakee, turn out the lights” had been printed onto bumper stickers, visibly displayed on passing vehicles on the streets of Kankakee, Bradley, and Bourbonnais. The interviewees did not know who made or distributed the bumper stickers, though some speculated union workers’ involvement. The bumper stickers encapsulate the general tone of the community during this period, reflecting a lamenting of what Kankakee used to be before deindustrialization. As other memories faded in the minds of the interviewees, this phrase remained in the memories of residents even as Kankakee has bounced back economically from the challenges it faced in the height of deindustrialization. The progress of recovery was slow, and there were difficulties along the way, but Kankakee slowly recovered from the events of the 1980s.

1990s and Beyond

The effects of the events which transpired in Kankakee in 1980s continued into the 1990s. William D., attorney and city council member during the 1990s, remarked how in the summers of 1994 and 1995, he distinctly remembered there were around 26

45. Michael J., interview, November 10, 2021.

46. William D., interview, November 9, 2021.

to 27 murders each of those summers. Many of the murders were unsolved and were a result of individuals from Chicago coming to sell drugs in the streets of Kankakee. There was a specific house in Kankakee used as a point of distribution by a Chicago gang. Once the house was no longer used for drug activity, “the house was demolished, since it was such a bad symbol for the area.”47

However, there were glimpses of hope during a hard time for Kankakee. Michael J recognized the need for Olivet Nazarene University to play a larger part in the community. He helped ONU become a part of the Kankakee community by joining several board of directors of Kankakee organizations such as the Kankakee Chamber of Commerce and hospital boards.

In more recent years, plans are in the works to utilize the Kankakee Riverfront area. The people who have made Kankakee their home, who weathered the changes during the time of deindustrialization, crimes, burnt buildings, and bad perceptions adamantly supported using the Kankakee riverfront to help the Kankakee community and draw in business.

Outside revenue coming into the Kankakee community within the past twenty years has contributed to Kankakee’s continued economic recovery and revitalization after the post-industrial period. Olivet Nazarene University wove more fully into the fabric of the Kankakee community with the help of university leadership. When ONU became the summer home for the Chicago Bears, there was a realization in the community that this decision would impact the broader perception of the Kankakee area. Michael J. was a focal participant in the agreement with the Chicago Bears in coming to ONU. He knew that though ONU would benefit, the community would be the real winners with the deal.

Additionally, the perception of Kankakee has altered in recent years as Kankakee and its surrounding suburbs have come to be perceived as a part of the larger Chicago metropolitan area. As Mark J. explained to me, “The northeastern part of Bourbonnais, it became a suburb of a sorts, where people commute to Kankakee from Bourbonnais. I’ve noticed this through the years, that over the years we have been termed a suburb of Chicago. We suddenly moved a lot closer than we were. And I think that is part of mindset that has driven an increase in the number of people here who use this a basis for commuting to other suburbs or [Chicago].”48

Like Kankakee’s perception shifting due to the inclusion of the Chicago Bears summer home at Olivet Nazarene University, the riverfront plan to utilize the Kankakee River more effectively, and Kankakee’s inclusion in the wider Chicagoland suburban area, the removal of aspects of Kankakee also contributed to a new perception for Kankakee. For example, Roper’s Kankakee Division facility was demolished in 2016. The Roper facility, which had stood empty and deteriorating since its closing in 1982, was a reminder to the community of the trouble caused by the removal of Roper in the community. When the

47. William D., interview, November 9, 2021.

48. Mark J., interview, October 6, 2021.

buildings were all leveled to the ground, the mayor of Kankakee applauded the action, never believing she would see the day when the facility would be torn down.49

The Roper facility has not been the only structure in recent years to be demolished to pave a way forward for Kankakee’s development. Thomas B. worked in the Kankakee school system as well as in an economic development role for the City of Kankakee. Thomas, one of many residents looking towards the future growth of Kankakee, learned the history of the David Letterman gazebos. He was shocked to find that the gazebos were mocking the Kankakee community. He wasn’t alone in his sentiment. Students at the Kankakee High School learned the history of the gazebos and decided enough was enough: they would tear down the twin gazebos of Kankakee, physical symbols of the laughingstock Kankakee was back in 1999. A compromise was reached between the students and the Park District of Kankakee where the students were allowed to tear down the gazebo located at Depot Park. It so happened that David Letterman was retiring around the time of the demolition of the Depot Park gazebo. A brilliant idea was born: the wood boards of the demolished gazebo would serve as the material to create a rocking chair to commemorate Letterman’s retirement.50 The Paramount Theatre which Sarah P. had enjoyed as a young woman in the 1960s served as the space for the unveiling of the completed rocking chair bequeathed to Letterman with a host of fanfare from Kankakee residents attending the event in addition to Letterman’s camera crew filming the ceremony for the Letterman’s show.

The demolition of the Roper facility and the Depot Park gazebo are symbols of Kankakee residents choosing to move Kankakee into the future rather than dwelling upon the events of the past. Though the events of deindustrialization in Kankakee will not be forgotten, the residents of Kankakee have chosen to focus on the future development of their community.

CONCLUSION

The process of deindustrialization in Kankakee is intricate, weaving together different aspects of the culture of Kankakee. The stories told are but a few out of hundreds, even thousands of stories from individuals who witnessed the changes in the community they called home. The people on the periphery of the manufacturing decisions made become the focus when it is realized that these were a few of the many people who willingly remained in the Kankakee community, using their skills, time, and energy to create a new perception for Kankakee. There was a resounding agreement from the interviewees that Kankakee has developed significantly since the time of Roper, A.O. Smith, and Kroehler leaving.

49. Lee Provost, “Bittersweet moment for Kankakee as landmark manufacturing site comes down,” Daily Journal, March 3, 2016.

50. Mary Schmich, “Regifting Kankakee gazebo back to Letterman an act of pride,” Daily Journal, March 17, 2015.

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APPENDIX

Initial Interview Questions

· What was your occupation(s) throughout the late 1970s and 1980s within the Kankakee area? Were you involved in any governmental units?

 From your recollection, what the role of the government in the deindustrialization of Kankakee?

· Were you involved in any local unions?

 From your recollection, what was the role of unions in the deindustrialization of Kankakee?

· Do you recall the closing of Roper, A.O. Smith, and other industries in Kankakee?

 From your recollection, what contributed to the removal of Roper and A.O. Smith?

· What were your initial thoughts on the closing of the manufacturing plants?

· What was the overall tone of the community before, during, and after the closing of the manufacturing plants? Do you have any examples?

· How did the closing of major manufacturing employment affect you, your family, or other people you knew? Do you have any examples?

· In 1974, there was a national recession which affected industry in Kankakee. From your perspective, how did the economic recession of 1974 and the 1980s affect your communities? (work, neighborhood, school, church, etc.)

· Were there any ways in which you actively helped those around you during the deindustrialization period? (Any initiatives taken?)

· Do you have any further thoughts on the deindustrialization of Kankakee? Any other stories you would like to share?

· Since the 1970s and 1980s, how have you seen Kankakee change? (industries, communities, the overall tone of the community, etc.)

VOLUME 6

The Effect of Education on Support for TNR as a Method of Feral Cat Management

ACKNOWLEDGEMENTS

I would like to thank Olivet Nazarene University and the Honors Program for the opportunity to complete a research project while obtaining my undergraduate degree. I would also like to thank Dr. Lisa Gassin, my research mentor, for her guidance and support in research methodology, the process of statistical analysis, troubleshooting and talking through frustrations, and sharing her expertise during this process. Finally, I would like to thank Dr. Stephanie Lupo, Dr. Dale Smith, and Professor Mark Bishop for allowing me to take time out of their classes to recruit participants.

ABSTRACT

A feral cat is a cat that is untamed and not suitable for placement in a home. Through their naturally high rate of reproduction and lack of population management, feral cat populations have grown exponentially, leading to overpopulation. Feral cats effect their communities through their impact on wildlife, financial burden, and health risk to both humans and other animals. Due to the impact feral cats place on their communities, multiple management methods have been suggested. Trap-Neuter-Return (TNR) is a humane, effective method of management; however, controversy surrounds its use. Existing studies have determined that age, gender, and past experiences with cats can be predictors for which management method an individual prefers. To assess whether targeted education impacts support for TNR, sixty-five undergraduate students were administered a series of surveys prior to and following watching a video on either TNR (treatment) or cat breeds (control). The survey included questions about participants’ past experiences with cats, views on cats and their management, and knowledge about cats. Participants were recruited by the researcher visiting multiple general education classes and passing around a sign-up sheet. Informed consent was given before participants continued to the rest of the survey. Data was analyzed using repeated measures ANOVA, followed by post-hoc comparisons for items with significance in the interaction terms. Significant interaction terms were observed for the survey items that directly asked about TNR. This suggests that the treatment video was effective in producing both cognitive and attitudinal changes in participants.

Keywords: education, feral cat, Trap-Neuter-Return

INTRODUCTION

Domestication of cats

Cats began their relationship with humans around ten to twelve thousand years ago in the Fertile Crescent, where agriculture was developed. As agricultural practices grew, mice and rats began to colonize near these farming towns. Cats, being opportunistic feeders, also colonized near these towns to capitalize on this localized food source (Alley Cat Allies, history; Deak et al., 2019). This created a mutualistic relationship between humans and cats, and soon cats were kept around intentionally to control populations of pests such as mice, rats, and other small mammals in homes and aboard ships. It was through this utilitarian use of cats that they were introduced to regions of all continents and many islands worldwide. Cats have readily adapted to these new environments and, in many cases, have established invasive populations (Deak et al., 2019, Robertson, 2008). Left unchecked, these cats were able to reproduce freely, increasing their populations exponentially.

Feral cats

A feral cat is defined as a cat that is untamed and evasive toward humans. Another definition describes a feral cat as a cat that cannot be handled and is not suitable for placement in a home as a pet. They are either born in the wild and lack socialization or are abandoned and lose trust in humans (Robertson, 2008). Cats have a high reproductive capacity as they reach sexual maturity around five to six months of age and can produce a litter of between one and six kittens approximately 1.6 times a year (Robertson, 2008). To further illustrate this, it is estimated that a single fertile cat and her offspring can collectively produce around 420,000 kittens in a seven-year period (Coleman et a l., 2010). Their high reproductive rate easily explains how feral cat populations have risen to extreme heights. Feral cat overpopulation has also been exacerbated due to owners allowing their cats to roam freely and breed with feral cats, and even further by abandonment (Coleman et al., 2010; Robertson, 2008).

The exact number of feral cats in the United States is unknown; however, it is estimated to be about one-third to one-half of the owned population. This would mean that there are anywhere between thirty million to forty-five million feral cats living in the United States right now (Robertson, 2008). Some more recent studies estimate the number to be even higher, being closer to seventy-four million (Spehar & Wolf, 2017). Regardless of the exact number of feral cats living in the United States, these cats are affecting the communities in which they live.

Feral cats and their communities

One aspect of their communities that feral cats can impact is the native wildlife in the area. Feral cats impact wildlife through competition for food, the spread of disease, and, primarily, predation (Robertson, 2008). As previously mentioned, cats are opportunistic feeders. They also require a high protein diet to sustain themselves, as they are not able to synthesize many essential vitamins and minerals. This is one of the reasons that, in 2001, cats were placed on the International Union of Conservation for Nature’s (IUCN) list of the top 100 worst invasive species. At that time, they had a partial role in the extinction of 14% of native bird, mammal, and reptile species worldwide (Deak et al., 2019). The effect of feral cats on wildlife is one of the most controversial issues regarding these cats. This argument has been so polarizing that ‘pro-cat’ and ‘pro-wildlife’ groups have formed. Pro-cat advocates are concerned with the welfare of feral cats, whereas pro-wildlife advocates argue for the removal of cats from the environment as cats are an invasive species and threaten native species (Robertson, 2008).

Feral cats also place a large financial burden on the communities in which they live. Every year local governments spend money providing animal control services and catching, euthanizing, and disposing of homeless cats (Coleman et al., 2010). For example, in 2020 animal control expenses alone for Kankakee County,

Illinois, were around $260,000 (Kankakee County Online). In bigger cities, or places with higher populations of feral cats, this cost can be much higher. Feral cats can also pose a threat to the livestock industry. Cats can transfer diseases to other animals, including toxoplasmosis. Toxoplasmosis can cause abortions in sheep or weaken newborn lambs, which can economically harm farming communities (Deak et al., 2019).

Because cats are the primary hosts of several diseases, they endanger not only the health of other animals but humans as well. Some diseases that cats carry have the potential to spread to humans, including rabies, toxoplasmosis, and Sarcocystis (Deak et al., 2019; Levy & Crawford, 2004). Parasitism is the most common transmissible problem of feral cats. Increased bite risk also correlates with increased feral cat populations. Most reported cat bites come from provoked feral cats (Levy & Crawford, 2004), meaning that an increased number of feral cats in an area increases the risk of those in the community getting bitten and the health complications that can arise from this. Although it is not extremely common for humans to get diseases or parasites directly from the feral cats themselves, an increase in their population increases this risk.

Management methods

Over the years, different management methods have been proposed to control the growing feral cat populations. One such solution is implementing Trap-RemoveEuthanize programs.

Trap-Remove-Euthanize

Trap-Remove-Euthanize, or Catch-and-Kill, is a lethal method of management where cats are trapped, removed from their original location, and euthanized, usually by a veterinarian or animal control (Robertson, 2008). Some people are under the impression that the life of a feral cat is full of risks and, therefore, not acceptable on welfare grounds, leading them to favor ‘pre-emptive euthanasia’ to prevent cats from suffering. Others favor this method because they believe that since cats are a non-native species, they should be removed from the environment to prevent predation on wildlife (Robertson, 2008). Although lethal methods of management may seem more effective initially, they almost always ignore a phenomenon called the ‘vacuum effect.’ The vacuum effect is based on the idea that individuals are drawn to resources. Feral cats live where resources such as food, shelter, and water are present. When a population is removed and killed, it creates a vacuum, attracting other feral cats living in surrounding areas. These new individuals, and any remaining members from the original population, fill the vacuum and resume reproducing. Before long, the area fills back to capacity and it is as if the cats were never removed to begin with (Alley Cat Allies, vacuum).

Trap-Neuter-Return (TNR)

The other prominent method of management is implementing Trap-Neuter-Return (TNR) programs where populations of feral cats are high. TNR is a non-lethal method of managing feral cat populations that involves humanely trapping, surgically sterilizing, and returning cats to their original location. These programs often vaccinate cats against rabies as well (Spehar & Wolf, 2020). TNR is the only current management method that factors in the vacuum effect. By returning cats to their original location, the vacuum remains full. This allows for populations to be stabilized and, eventually, decline (Alley Cat Allies, vacuum; Robertson, 2008). Although TNR is a relatively new method of management, only gaining popularity within the last twenty-five years, there is research showing that it is effective at controlling feral cat populations.

One such study examined a TNR program that took place in Newburyport, Massachusetts. This program is one of the most well-known and longest-running TNR programs in the United States. The program began in June of 1992 and went until December of 2009. The program included a TNR campaign in a targeted area called the Waterfront as well as facilitating the adoption of sociable cats that were trapped. By 1998, the last two known litters of kittens were born on the Waterfront. The program ended in 2009 when the last known cat on the Waterfront died (Spehar & Wolf, 2017). This program was able to completely eradicate feral cats in the targeted area.

Another example of an effective TNR program is taking place in Chicago, Illinois. This program was conducted by a citizen of Chicago in the neighborhood in which she lived. She worked with her neighbors to spay and neuter cats that lived near their homes. Twenty cat colonies were involved in the program over a ten-year period. The last known litter to be produced by cats in the program was in 2009, just two years after the program started. The program was able to completely eliminate eight of the twenty colonies. Of the colonies that were not eliminated, there was an average reduction of 54% from colony entry levels (Spehar & Wolf, 2018).

Controversy

Although research supports the efficacy of TNR programs, this management method is still somewhat controversial. As previously mentioned, controversy stems from the arguments between pro-cat advocates and pro-wildlife advocates. Pro-cat advocates tend to favor non-lethal management methods like TNR, whereas pro-wildlife advocates tend to favor lethal methods of management (Loyd & Hernandez, 2012). Other factors that are predictors of people’s attitudes towards TNR are age, gender, and their experiences with feral cats. For example, one study found that 47% of females preferred TNR over lethal management methods, whereas only 20% of men surveyed preferred TNR (Loyd & Miller, 2010). Negative perceptions of TNR programs have also been correlated with a lack of knowledge on the topic or a perceived lack of need (McDonald & Clements, 2019). Due to this correlation, many studies have noted that it would be

beneficial to study the relationship between education programs about feral cats/TNR and community support (Deak, et al., 2019; Loyd & Hernandez, 2012; Loyd & Miller, 2010). The present study attempts to answer the question of whether education on feral cats and TNR leads to increased support for TNR as a management method for feral cats. This was measured by administering a series of surveys prior to, and following, watching an educational video on either TNR (treatment) or cat breeds (control).

METHODS

Participants

The participants included sixty-five undergraduate students attending a mid-sized liberal arts university near Chicago, Illinois, recruited through general education courses. The average age of the students was 19, and all students were between the ages of 17 and 22. Of the participants, forty-six were female and nineteen were male. Freshmen accounted for 53.8% of participants, followed by sophomores at 23.1%, seniors at 12.3%, and juniors at 10.8%.

Among the participants, seventeen areas of study were represented. Eleven participants were studying in both the department of behavioral sciences and exercise science. Seven were in the department of biology, six were in the department of business, and five were in the department of education. The departments of nursing and music both had four participants. The departments of social work and criminal justice and chemistry and geosciences both had three participants. The departments of history and political science, art and digital media, and engineering all had two participants. The departments of art, mathematics, family and consumer sciences, communications, and general studies all had one participant.

Procedures

Upon receiving approval from the Institutional Review Board, participants were recruited from various general education classes. After giving a brief description of the study, a sign-up sheet was passed around requesting students’ participation. Participants wrote their name and email address. Participants were then emailed two links; one to complete the first survey and another to sign up for a thirty-minute time slot to participate in the second phase of the study. The first survey included an informed consent question that gave a brief overview of the procedures, the objectives of the study, and explained the completely voluntary nature of their participation. The first survey also included a demographic section. The time between participants taking the first survey and coming to complete the second phase varied because the first survey was administered to all participants at once. Some participants were offered extra credit in a course, and all participants were entered into a drawing for one of five $50 amazon gift cards upon completion of the study.

Once students arrived to participate in the second phase of the study they were allowed to choose one of six available rooms, separating them into two groups. Three of the available rooms were set up for the control group and three were set up for the treatment group. Once participants selected their room, they were instructed to watch the video on the computer in their respective room and complete a survey after watching the video. Those in the control group watched a video titled ‘Cat Breeds’ and those in the treatment group watched a video titled ‘Trap-Neuter-Return.’ One week following participants’ completion of the second phase, they were emailed a link to complete a third, final survey. This survey included a few questions at the end for participants to enter their name for extra credit and to be entered in the gift card drawing.

Materials

Survey

All three surveys administered to participants included most of the same questions apart from the informed consent and demographics portions of the first survey and a question asking which video participants watched in the second survey. The survey used came from a study assessing public perception of domestic cats and preferences for feral cat management (Loyd & Hernandez, 2012). Some questions on the survey used by Loyd and Hernandez were not included in this study, as they pertained to the specific county in which their study was conducted. This left three sections to collect information on participants: past experiences with cats (seven questions), views about cats and their management (eight questions, some with multiple statements), and knowledge about cats (twelve statements and five concepts). This survey was administered using a pre- and post-survey format.

Videos

The control video used was titled ‘Cat Breeds.’ The video was thirteen minutes and thirty-eight seconds long. The video began with a brief overview of cat domestication and then went on to describe four cat breeds. The breeds discussed were Siamese, Maine Coon, Domestic shorthair, and Persian. For each breed, its origin, job/reason for breeding, temperament, and common health concerns were discussed. (Link to control video: https://youtu.be/KZG-at4znII)

The treatment video was titled ‘Trap-Neuter-Return.’ This video was seventeen minutes and ten seconds long. This video began with the same overview of cat domestication as the control video. This video then went on to describe feral cat overpopulation. The video then briefly described the difference between a feral and stray cat, followed by reasons that feral cat populations need to be managed. The rest of the video discussed TNR as a management method, including controversy surrounding the method and research supporting TNR. The video ended with some additional benefits of TNR. (Link to treatment video: https://youtu.be/QuIbKIBzP6M)

Analysis

Survey items that the treatment video addressed directly were chosen for analysis along with a few select items that were indirectly addressed. Repeated measures ANOVA tests were run to determine relationships between each time the survey was administered, separated by video group. A p-value of ≤ 0.05 was used to determine significance.

The items that were chosen for analysis were item 7 parts a, b, c, d, and f; item 11 parts a, b, d, and e; and item 8 (see Appendix for items). For items 7 and 11 each part was analyzed separately. For question 8, a ‘total score’ was calculated for each administration of the survey and a repeated measures ANOVA test was run to determine the relationship between the total scores, separated by video group. The total score was calculated by giving one point each time the participant chose TNR and zero points for each other answer. For item 8, a Cronbach’s alpha internal consistency analysis was conducted for each administration. For administration one (T1) Cronbach’s alpha was 0.724, for administration two (T2) Cronbach’s alpha was 0.577, and for administration three (T3) Cronbach’s alpha was 0.726. The reliability of T1 and T3 are acceptable for research purposes. The reliability of the T2 measure is less than desired, however, we are still fairly confident in any significant changes seen during T2 because they remained consistent through T3, which had an acceptable Cronbach’s alpha value.

The remaining items in the survey served as distractions to participants to prevent them from guessing the hypothesis or purpose of the study, which could have affected how they answered. These items could also be used for future, more general analysis.

RESULTS

Given the research design being used, the key test in our repeated measures ANOVA is the interaction term, which determines the difference between groups’ change over time. When an interaction term was significant, post-hoc tests were used to identify group change over time and at what points groups differed from one another. The patterns in post-hoc tests that would establish that the treatment had its intended effect were the following: at T1, groups are not different; for the TNR group, endorsement significantly increases between T1 and T2; maintenance of T2 scores at T3 suggests persistence of attitudinal change; at T2, TNR endorses significantly more than Cat Breeds; finally, at T3, TNR endorses significantly more than Cat Breeds, which suggests persistent change in attitudes. For parts a, b, c, and f of item 7 and part d of 11, the test of interaction term was not significant. In the rest of this section, only those tests of interaction that were significant will be discussed.

Note. Item 7d assesses how much participants support TNR on a five-point Likert-scale. Table contains the pairwise comparisons used to determine treatment video efficacy. (*p < 0.05, **p < 0.01, ***p ≤ 0.001)

Post-Hoc Pairwise Comparisons for Significant Interaction terms

For item 7d, all necessary patterns to determine treatment efficacy were observed. During T1, no difference between the groups was observed (table 1, figure 1). For the TNR video, endorsement significantly increased between T1 and T2 (table 1, figure 1). The T2 score was also maintained at T3 for the TNR video (table 1, figure 1). When comparing between video groups, TNR endorses significantly more than cat breeds at T2 and maintains this endorsement at T3 (table 1, figure 1).

Note. Item 11e assessed participants’ perceived ability to explain TNR; on a three-point Likertscale. Table contains the pairwise comparisons used to determine treatment video efficacy. (*p < 0.05, **p < 0.01, ***p ≤ 0.001)

All necessary patterns to establish treatment efficacy were also observed for item 11e. T1 showed no significant difference between groups (table 2, figure 2). The TNR group experienced a significant increase in endorsement at T2, and maintained its score at T3 (table 2, figure 2). Also, at T2, TNR endorsed significantly more than Cat Breeds. At T3, TNR endorsed more than Cat Breeds, which suggests persistent change in attitudes (table 2, figure 2).

For item 8, all patterns to determine treatment efficacy were observed. At T1, there was no significant difference between groups (table 3, figure 3). The TNR group

Note. Item 8 assesses participants’ likelihood of choosing TNR as a management method in five different scenarios; total score was calculated with a maximum score of five. Table contains the pairwise comparisons used to determine treatment video efficacy. (*p < 0.05, **p < 0.01, ***p ≤ 0.001)

experienced a significant increase in endorsement from T1 to T2 (figure 3, table 3). Maintenance of the T2 score was also observed at T3, which suggests persistence of attitudinal change (table 3, figure 3). Between video groups, TNR showed significantly more endorsement than Cat Breeds at T2 (table 3, figure 3). At T3, TNR endorsed significantly more than Cat Breeds, which suggests persistent change in attitudes (table 3, figure 3).

Note. Item 11a assesses participants’ perceived ability to explain how non-native species impact an ecosystem; on a three-point Likert-scale. Table contains the pairwise comparisons used to determine treatment video efficacy. (**p < 0.01)

Post-Hoc Pairwise Comparisons for TNR Group Over Time

In this section, results are discussed suggesting that the TNR group changed on items that the Cat Breeds group didn’t, but the difference between these groups over time either did not reach significance or were uninterpretable.

For item 11a, only a few of the patterns necessary to determine treatment efficacy were observed. At T1, there was no significant difference observed between groups (table 4). For the TNR video group, a significant increase in endorsement was observed between T1 and T2 (table 4). This increase was also maintained at T3 (table 4). The difference between groups over time, however, did not reach significance (table 4).

Some of the patterns necessary to determine treatment efficacy were observed for item 11b. At T1, no significant difference was observed between groups (table 5). A significant increase in endorsement was observed at T2 for the TNR group and was maintained at T3 (table 5). Some pairwise comparisons on the post-hoc test showed

Note. Item 11b assessed participants’ perceived ability to explain the interactions between cats and wildlife; on a three-point Likert-scale. Pairwise comparisons of importance are outlined in red. (*p < 0.05, **p < 0.01, ***p ≤ 0.001)

significant difference between the groups over time; however, this significance is uninterpretable.

DISCUSSION

This study assessed the effect of targeted education on participants’ knowledge and attitudes towards TNR as a method of feral cat management. A positive correlation was observed between the treatment video and preference for TNR. This result correlates with a study done on education on invasive species, which also found that increased knowledge was accompanied by attitudinal change toward management (Waliczeck et a l., 2018). The present result also correlates with a study that determined an association between awareness of a management program and increased participation in the program (McDonald & Clements, 2019). This study also noted the absence of change in the control group, which is consistent with past studies that have noted that general knowledge of domestic cats did not appear to influence or be a predictor for support for management (Loyd & Hernandez, 2012).

Another interesting thing to note is the correlation between items in which all necessary patterns to determine treatment efficacy were observed and the ones in which only some were observed. The items that showed significance in all of the important pairwise comparisons, 7d, 11e, and 8, all asked about support, understanding, or preference for TNR as a management method, which is the majority of what the treatment video covered. The items that showed significance in some of the important pairwise interactions, 11a and 11b, asked about understanding of how invasive species, specifically cats, affect wildlife, which was only briefly discussed in the treatment video. This observation suggests that the treatment video was effective in educating on this topic, however, not drastically enough to be significant when comparing between the groups. Finally, the items that showed no significance (7a, 7b, 7c, 7f, and 11d) asked about topics that were indirectly related to the treatment video. These observations suggest that the treatment video was most effective in producing cognitive and attitudinal changes in areas that it most directly addressed.

This study may be hindered by several limitations, one of which being small sample sizes. Having approximately thirty participants in each group allowed some confidence in analysis; however, more participants would increase that confidence. There were also a few items that were close to being significant during analysis, which may have been significant with more participants. Another limitation to this study was that a survey from a different study was used. Although the survey used assessed the correlations desired in this study, it was a more general survey than was necessary for this study. A survey written with this study’s hypothesis in mind may have allowed for more specific results. There are also a few confounding factors to be aware of, one being that video assignment was not completely random. For the second step of the study, rooms on

the left were set up with the TNR video, while rooms on the right were set up with the cat breeds video. Since participants were allowed to choose which room they watched the video in during this phase, it is possible that those who preferred to go into a room on the left somehow differed from those who chose a room on the right. Logically, it seems unlikely that this affected my results, however in a future study it would be better to randomly assign participants to rooms. Another confounding factor to consider is that the experimental (TNR) video was a few minutes longer than the control video. This difference in video length could suggest that the differences seen might be a result of the extra exposure to information about cats. Logically, the difference seen would be due to the content of each video, however, the length is still something to consider. In a future study, it would be beneficial to make each video the same length to avoid this possibility.

Future research in this area would benefit from pairing an educational program with a TNR program. The results of the present study determined significance in cognitive and attitudinal change in hypothetical scenarios. By studying the effects of an educational program being run alongside a TNR program, behavioral changes could also be assessed. Further, since topics addressed most directly in the treatment video produced the most significant changes, additional research could be done to determine the amount of education needed to obtain the desired changes. For example, different methods of education could be compared to determine the most effective way to distribute information during an educational program. Management programs often rely on public funding, so community support is imperative. Community support is also needed to help TNR programs run more smoothly and end up being more successful in the long run (Deak et al., 2019). This need for community support emphasizes the importance of studying education and its relation to participation and support for feral cat management.

REFERENCES

Alley Cat Allies. (n.d.). The History of the Domestic Cat. Retrieved February 12, 2023, from https://www.alleycat.org/resources/the-natural-history-of-the-cat/

Alley Cat Allies. (n.d.). The Vacuum Effect. Retrieved February 12, 2023, from https:// www.alleycat.org/resources/the-vacuum-effect-why-catch-and-kill-doesnt-work/

Coleman, P., Veleanu, H., & Wolkov, S. K. (2010). Its training cats and dogs... Government lawyers take note: Different licensing laws generate revenue, reduce costs, protect citizens, and save lives. Stetson L. Rev., 40, 393.

Comprehensive Annual Financial Report. Kankakee County Online. (n.d.). Retrieved October 16, 2021, from https://ww.k3county.net/files/113020_comprehensive_annual_ financial_report.pdf.

Deak, B. P., Ostendorf, B., Taggart, D. A., Peacock, D. E., & Bardsley, D. K. (2019). The significance of social perceptions in implementing successful feral cat management strategies: a global review. Animals, 9(9), 617.

Levy, J. K., & Crawford, P. C. (2004). Humane strategies for controlling feral cat populations. Journal of the American Veterinary Medical Association, 225(9), 1354–60 .

Loyd, K. A. T., & Hernandez, S. M. (2012). Public perceptions of domestic cats and preferences for feral cat management in the southeastern United States. Anthrozoös, 25(3), 337–51

Loyd, K. A., & Miller, C. A. (2010). Factors related to preferences for Trap‐Neuter–Release management of feral cats among Illinois homeowners. The Journal of Wildlife Management, 74(1), 160–65.

McDonald, J. L., & Clements, J. (2019). Engaging with socio-economically disadvantaged communities and their cats: Human behaviour change for animal and human benefit. Animals, 9(4), 175.

Robertson, S. A. (2008). A review of feral cat control. Journal of Feline Medicine and Surgery, 10(4), 366–75

Spehar, D. D., & Wolf, P. J. (2017). An examination of an iconic trap-neuter-return program: The Newburyport, Massachusetts case study. Animals, 7(11), 81.

Spehar, D. D., & Wolf, P. J. (2018). A case study in citizen science: The effectiveness of a trap-neuter-return program in a Chicago neighborhood. Animals 8(1), 14.

Spehar, D. D., & Wolf, P. J. (2020). The impact of Return-to-Field and targeted TrapNeuter-Return on feline intake and euthanasia at a municipal animal shelter in Jefferson County, Kentucky. Animals, 10(8), 1395.

Waliczek, T. M., Parsley, K. M., Williamson, P. S., & Oxley, F. M. (2018). Curricula influence college student knowledge and attitudes regarding invasive species.

HortTechnology, 28(4), 548–56.

Items of the Survey used for Analysis

7. How much do you support the following actions regarding the management of feral cats?

a. Capture and euthanize feral cats

b. Capture and place feral cats in a sanctuary created for them

c. Educate the public about feral cats and wildlife

d. Trap, sterilize (neuter), and re-release feral cats

f. Leave cats alone

8. Please pick the choice that corresponds to the management option you choose to each question.

Trap-Neuter-Return (capture, sterilize, and re-release cats) Capture and euthanize I am unsure Other

a. Which do you believe would be the most effective at cat population reduction?

b. Which do you believe is more humane to cats?

c. Which management option do you believe is more humane to wildlife?

d. Which option would you prefer tax-payer money be spent on?

e. Which option would you donate money to? (NOTE: we are not soliciting donations; we only care about your potential to donate money)

11. How well would you be able to explain the following concepts to a friend? Could not explain Could somewhat explain Could explain well

a. How non-native species impact an ecosystem

b. Interactions between cats and wildlife

d. Causes of the songbird decline in the US

e. Trap-Neuter-Return

Identifying the Optimal Pedagogy for Preparing Undergraduates for the MCAT Exam

ACKNOWLEDGEMENTS

I would foremost like to thank Dr. Himes for his undying patience and insight as we have collaborated on this project for the last three years. I would also like to thank all who have believed in me these past four years as well as the Honors Program for giving me this opportunity.

ABSTRACT

Excelling on the MCAT is an essential step for undergraduate students preparing for a future as a physician in the medical field. Previous research has made links to MCAT performance and success in the medical field, yet there is a lack of research on how to best prepare undergraduate students for this extensive exam. Various research has been done on assessing the most effective studying strategies for undergraduates on typical collegiate exams, which students often translate to their MCAT studying. To assess the effectiveness of these practiced pedagogies on the MCAT, a social science experiment using a pre- and post-test format based upon MCAT questions and test conditions was used to support or negate the ability of reading text, using memorization tasks, test-enhanced learning, and instructor-led courses to improve MCAT performance. Forty students were recruited from Olivet Nazarene University to participate in one of five experimental groups testing these researched methods. Using a t-test and Bonferroni correction to assess pre- and post-test average, the only strategy that made a statistically significant difference in pre- and post-test average was using an instructor-led course to enhance performance. The findings of this study could encourage students and universities to begin using instructor-led course material to improve MCAT performance for students aspiring to be physicians.

Keywords: MCAT, study, pedagogy, strategies, test-enhanced learning, memorization, instructor-led course

INTRODUCTION

The Medical College Admission Test (MCAT) is a graduate-entry exam that assesses a student’s scientific knowledge and critical analysis skills to act as a predictor of success in medical school (Swan Sein et al., 2020). In rare cases, students are not required to take the MCAT exam to receive acceptance into medical school. Students who apply and get accepted into BA/MD or BS/MD programs will be automatically placed into medical schools contingent on their ability to maintain the academic and extracurricular standards of these programs (International Medical Aid, 2022). Despite the existence of these programs, most students who pursue a medical degree will be required to take the MCAT, as BS/MD programs have excessive requirements for their incoming classes to ensure they have the leadership, academic, and research experience required of prospective medical students. Though the MCAT is one of many factors used to access medical school acceptance, most schools require the exam and use it as a measure of knowledge learned from a student’s undergraduate degree to predict success in medical school (Murphy, 2019). The exam itself includes four sections: chemical and physical foundations of biological systems; critical analysis and reasoning skills; biological and

biochemical foundations of living systems; and psychological, social, and biological foundations of behavior. Because the exam is so information heavy, it typically lasts around seven hours. There is not a lot of published research about MCAT preparation, particularly for the newest version, which was revised in 2015. Much of the research surrounding the MCAT involves ensuring the test remains fair and maintains a certain level of equity for all students who take the exam rather than the most effective preparation strategies (Girotti et al., 2020).

Lack of proven preparatory strategies

The majority of the information concerning how to prepare for the MCAT includes non-scholarly blogs and non-peer reviewed articles about how to set deadlines for the amount one should study, ensuring that the quality of study is better than the quantity, and other general tips that do not explicitly state how to learn the information for this exam. Furthermore, students do not always have access to low-cost, proven, direct instruction on how to study. For example, students who understand and apply retrieval strategies, or tasks that enhance memorization by repetitive exposure, are proven to perform much better than those who do not, but students lack the ability to effectively use these strategies when they experience illusions of competency by simply rereading their notes or class texts (Karpicke et al., 2009). Because of the evident lack of MCAT preparatory research, the topic is open for investigation. Without evidence-based research, students often misuse study time or suggested preparatory methods. This often results in lower scores and therefore lower potential for medical school acceptance (Jones, 1986). Researching the best methods for preparing for the MCAT is fundamental to student success in their future medical careers.

General overview of studying strategies

Some common methods of studying for the MCAT include completing a set of books that overview and discuss the MCAT topics, pre-made flashcards or student-made flashcards, practice exams or section bank questions, and even preparatory courses offered online or in-person. All these strategies come with a cost from tens to hundreds of dollars depending on what materials each student desires and can afford. These strategies also vary in length of time to complete. The longest strategy is likely reviewing the textbooks and practice exams, as reviewing the textbooks takes months and each practice exam is about seven hours in length. Some of the shorter strategies can include reviewing flashcards or brief problem sets. Each strategy mentioned is modeled off commonly used study methods such as retrieval strategies, test-enhanced learning, and instructor-led courses.

Research assessing the best general methods of studying for undergraduate students does exist. A study found that self-testing, scheduling time to study, and rereading notes and text had a large contribution to undergraduate students’ GPA and overall

success in college; most notably when self-testing was used, over 86% of students who reported using self-testing had a GPA of 3.7 or above (Hartwig & Dunlosky, 2011). Though this research did not directly address graduate-entry standardized testing, these results offer useful information on what methods may enhance studying habits, further improving overall test scores on the MCAT. Furthermore, some universities have already incorporated instructor-led courses with the intent of earning higher MCAT scores, demonstrating a potential method to boost scores for the students who participate. Because of the proven efficacy of repeated testing, information review, and time management, these methods offer an ideal model for research that involves the relearning and retention of information that must be recalled for standardized graduate-entry exams such as the MCAT (Karpicke et al., 2009; Roediger & Karpicke, 2006; Roediger & Butler 2011).

One of the strategies implemented in instructor-led courses is called a “test-enhanced learning cycle,” which includes studying with a set of topic-specific MCAT questions to begin, reviewing weak areas based on results from the questions, summarizing the learned material, then taking a cumulative test including many topics, and, finally, repeating the process as needed (Swan Sein et al., 2020). Because of the wide range of concepts that the MCAT entails, this study strategy is beneficial for students as they prepare and will be utilized within this study. In addition, instructor-led courses, whether they are online courses or in-person, have been shown to improve student confidence about MCAT topics; when an instructor-led course is offered, 89.9% of students report a higher confidence level concerning their understanding of MCAT material while also having access to an array of study materials and practices within the concise, convenient format of a classroom setting (Shipley et al., 2019).

Potential improvement for underprivileged individuals

A prevalent issue with the MCAT is that accessing the highest quality preparatory material requires a large monetary commitment. Underprivileged students, with low socioeconomic statuses, may not be able to invest the minimum amount of money to acquire materials that would enable them for success. If a preparatory strategy can be identified that may be offered at low or no cost, then students should have an equal opportunity to demonstrate their scientific knowledge and critical thinking skills, which are necessary for success on the MCAT and in medical school.

Overview of the study

This study will focus on how undergraduates prepare for the test by gathering data through five test groups (four experimental groups and a control) that could answer questions about performance on the MCAT, explore the effectiveness of MCAT study sessions and materials on students, and yield data that contributes to the benefits of beginning an MCAT preparatory course at Olivet Nazarene University, a small private

Christian university in the Midwest. The experimental groups included a reading-text group, a memorization task group, a test-enhanced learning group, and an instructor-led group that were compared to the control that did not use any study method. With changes in the most recent version of the MCAT such as extending the previous three sections, adding a fourth section, and a heavier emphasis on biochemistry, research is needed to understand how these changes have affected scores. Currently, there is a gap in the research concerning the newest version of the MCAT and how college students can most effectively prepare for it. Upon investigation, it was noted that most studies assess MCAT performance relating to future success in the medical field or medical school. Whereas these studies use GPA and MCAT score as predictive measures of medical school performance, this study proposes to investigate the question of what the most effective and accessible means are for preparing for the MCAT by examining student responses to a variety of free or low-cost sources. By analyzing the pre- and post-tests given to the participants before and after they had received MCAT-based information through one of the four study methods, conclusions can be drawn to understand which method yields the most success. Using a null hypothesis, we hypothesized there is no statistically significant positive effect on MCAT performance using any of the proposed methods on MCAT preparation in comparison to the control.

METHODS

Study site and population

Recruitment for student participants included freshmen through juniors at Olivet Nazarene University. The original sample size was fifty students, with ten participants in each of the five groups. After the last of the data was collected, ten students were omitted for non-compliance with the treatment or post-test expectations. The students were randomized into groups based on pre-test average so that the average was similar for each group to account for good test-taking skills and difference in academic level. This was done using a complex sort function where the standard deviation between the group averages was less than one. Students involved in the study were required to have taken a minimum of one semester equivalent to a college-level science course. Any student who had taken biochemistry was not allowed to participate in the study, as the topic for the experiment was biochemistry related. To encourage student participation, each student from Groups 2-5 received a $10 gift card, whereas students in the control group received a $5 gift card.

Experimental set up

An experiment using five groups of students was used to test the hypothesis as summarized in Table 1. Each group took a pre- and post-test using a set of MCAT-style biochemistry questions. The pre- and post-exams had identical questions; each student took

Note that all students took the pre- and post-tests, which were identical. The differences between pre- and post-test scores for each group were analyzed in search for the study strategy that yields the greatest improvement in scores. N Pre-

the same exam before and after treatment, and participants were given ninety seconds per question according to the approximate time allotted for each question on the MCAT (Association of American Medical Colleges, 2021). The specific topic within the subject of biochemistry was Michaelis-Menten enzyme kinetics. The students in the control group only took the pre- and post-tests without any additional instruction or reading. The second group was given an assigned textbook reading from an MCAT preparatory book on Michaelis-Menten kinetics between the pre- and post-tests to determine how topic-related readings increase test scores. The third group was given the same reading in addition to a memorization exercise in the form of a Quizlet, which recycles questions answered incorrectly, to complete for about thirty minutes in between the pre- and posttests to assess the advantages of memorizing information (Rawson & Dunlosky, 2011). A fourth group was given the same reading and memorization task as the previous group but also utilized test-enhanced learning by taking a separate set of biochemistry practice questions and receiving feedback in the form of correct answers with explanations (Roediger & Karpicke, 2006). The final group integrated a combination of the reading, memorization task, and test-enhanced learning exercise into a student-instructor environment (Roediger & Butler, 2011; Steed and Kadavakollu, 2019). For this group, a onehour lecture on the chosen topic was taught to the students by a professor in the Biological Sciences Department to determine the benefits of an instructor-led course (McCabe, 2010). Throughout a period of four weeks, the initial pre-test phase, treatment phase, and post-test phase were completed. Weeks zero and one included the pre-test phase; the treatment and post-test phases extended throughout weeks three and four.

Statistical analysis

To analyze the results, participants’ pre- and post-test scores were compared using a paired t-test to determine the significance of each post-test average in comparison to

the pre-test average for each individual group. Since five treatments were conducted with a post-exam for each, a Bonferroni correction was employed in order to reduce the occurrence of false positives; therefore, significance was noted when p < 0.01 (Girotti et. al). The hypothesis was rejected or accepted based on the p-value for each group.

RESULTS

The data from Figure 1 shows that the pre- and post-test average for Group 1 (control group) were only 0.74% different, which indicates the students were not exposed to information on the biochemistry topic between the pre- and post-test phase. Furthermore, the students’ averages are what would be expected if they were to guess on each question, as they are close to 25%. Based on the data for Group 2, students’ averages after the reading text treatment were seen to improve. The difference between the two was about 9.7% after reading the given text and immediately taking the post-test. Though the average did increase, the improvement was not statistically significant (p > 0.05).

The table below contains the determined p-value for each group in comparison of the post-test average to the pre-test average. A

The data obtained from Figure 1 concerning Group 3 was contrary to the expected results of the memorization task treatment. Instead of showing improvement, the posttest average decreased by about 2.4% even with a repetition of information. This was not seen for any of the other treatments. Despite the decrease in average from preto post-test, the change was not statistically significant. Like the reading text group, the test-enhanced drill (Group 4) did show an improvement by about 7.8%, which was similar to the amount of improvement seen in the reading text group. Though the treatment did seem to improve the overall scores, the increase was not statistically significant. The data for Group 5 shows a significant improvement in score from the instructor-led course. Students improved by about 47.5%, more than tripling their score average from pre- to post-test. Compared to the other treatments, the instructor-led course was the only treatment to have achieved statistical significance.

Based on the data shown in Table 2, the only treatment group found to have statistical significance was the instructor-led course with a p-value of 5.67x10-4, which also remained under the Bonferroni correction value 0.01, proving that the value is still significant under these conditions. The other treatments showed a p-value far over the 0.05 designation, indicating they did not show statistically significant improvement.

DISCUSSION

Throughout this study, MCAT performance based on various strategies was assessed to understand the benefit to exam average when using a progression of information format. By utilizing commonly used and researched study methods, the intention of the study was to find methods that would increase the overall average on a curated post-exam that could translate to overall MCAT performance. The null hypothesis states that none of the methods will result in a statistically significant increase in the post-exam average, with the purpose to negate the hypothesis with one or more of the proposed methods.

According to Table 2, the null hypothesis is supported for the first four groups, indicating that there is no statistically significant positive effect on the average post-test score using the reading text method, memorization task method, or the test-enhanced drill method. Despite an increase in average from the pre-test exam to the post-test exam for the reading-text method seen in Figure 2, Group 2, the p-value was still above 0.05. Similar to the reading text group, the test-enhanced learning method did result in an overall increase in average by about 7.8% (Figure 1 Group 4), yet this is not statistically significant. As shown in Figure 1, Group 3, the memorization task group shows a decreased average from pre-test to post-test, which is contrary to previous findings by Karpicke et al. 2009 and Rawson & Dunslosky 2011. These studies found that recalling strategies (memorization tasks) are effective in higher level education, and the results seen for the memorization task indicate that this study method was not effective for the exam created for this study as the exam average decreased after treatment. This could be a result from the students only completing the memorization task once instead of multiple times in various settings. Furthermore, the memorization task was secondary exposure to the material, as the participants also received the reading before completing the memorization task in which it is assumed that the average would have increased from the reading text group. The resulting lower average for this group could indicate that recall tasks are not ideal for the MCAT because the exam has a higher proportion of application questions instead of information recall questions. A more directed study to evaluate MCAT recall tasks would be needed to further investigate these findings.

In Figure 1, Group 5 represents the instructor-led course data, and this is the only method used within the study to have rejected the null-hypothesis. The p-value of 0.0000567 seen in Table 2 is below the Bonferroni correction value (p < 0.01), indicating that the instructor-led course does have a statistically significant overall positive effect on the post-score average. This aligns with research from Jones (1986) and McCabe (2010) that claim that instructor-led courses are effective in improving student test scores, especially for the MCAT in which Jones (1986) saw a 5-point increase in MCAT scores based on the coaching effect. The instructor-led course seems to yield a significant increase in overall performance, as the pre-test average was 21.66667% with the post-test average rising to 69.16667%. The significant increase in student performance for this group could be due to a variety of factors based on speculation. One major benefit of an instructor-led course is that the professor can adequately explain information to allow students to fully grasp the concept and ask questions for clarity (Kennette & Redd, 2015). The self-study methods exemplified by the reading group, memorization task group, and test-enhanced learning group are devoid of this opportunity for deeper comprehension. Furthermore, Kennette and Redd (2015) note that a sense of presence, described as a sense of being together, can be influential on student engagement and is often not present when an instructor is absent. Based on the apparent success of the instructor-led course group, Olivet Nazarene University has received

a grant from a generous donor which provides the funding and materials for the course beginning in Spring of 2023.

In comparison to the other experimental methods, the instructor-led course is the only one proven to significantly increase the average test score between the pre- and post-scores. Though the research shows miniscule increase in overall average for the reading text, the test-enhanced learning, and the instructor-led course, the instructor-led course data is the only to yield a significant increase. Furthermore, because of the progressive increase in exposure to the information with each experimental group, the averages were expected to increase incrementally from the reading group to the memorization task and so on. This is not seen for the post-test averages as the reading group post-test average was 31.67%, the memorization task average was 22.22%, and the test-enhanced learning average was 33.333%.

Overall, the study supports the efficacy of instructor-led courses as a beneficial means to prepare for a standardized exam but leads to questions about the other study methods. Further research could investigate using recall tasks for MCAT-based material. Though this variable could not be addressed through the present study because of time constraints and student population, future research could uncover solutions to allowing students equal access to study materials despite the diverse backgrounds of medical school applicants. Most schools do not offer MCAT preparation courses. Undergraduate pre-medical programs with low MCAT scores could potentially incorporate a class which not only may improve the MCAT score average for the students, but also recruit more students to their pre-med programs. A study analyzing socioeconomic disadvantage showed that those at a larger disadvantage yielded lower test scores on the standardized U.S. Medical Licensing Examination (USMLE) (Jerant et al., 2019). This research was performed using a different standardized test, yet the results can be applied to the MCAT as well, since those with higher socioeconomic advantage usually can afford materials, tutoring, and other beneficial services. Because of evident differences in scoring, the test bias within the exam itself was investigated, in which the test bias theory for this particular exam was rejected. Davis et al. (2013) concluded that despite test score differences between racial minority and majority students, the general composition and information encompassed on the MCAT did not pose a barrier for minority students. If colleges were to offer instructor led MCAT courses with the same materials provided for students of all socioeconomic backgrounds, further research assessing the socioeconomic and ethnic background in relation to student performance could answer questions concerning the variance in performance based on socioeconomic status.

Though the study was directed with utmost concern for any confounding variables, limitations still exist. A prominent limitation to the study included a time constraint on data collection. An educational study involving an evaluation of information retention would usually take place over the course of months to years. This study was

restricted to only four weeks where only one treatment session was given. The lack of consistent increase in post-test average could be a result of the time constraints of the study. Moreover, student motivation towards the study may have been inconsistent as well as their current grade point average, so there could be some variance in the amount of material retained in each group because not all participants had the same level of investment towards the study. A large majority of the participants were nursing majors or freshman students, which may inaccurately represent the type of students who typically take the MCAT. Furthermore, students could not be prevented from receiving any exposure to material that was related to the chosen biochemistry topic between the pre- and post-test phase. The students were asked to refrain from researching questions they were asked throughout the exam phases but were not monitored to ensure no exposure to the biochemistry topic occurred. The most prominent limitation is likely that the sample size did not exceed ten individuals for each group, which decreases the power of the study. Only fifty students total completed the pre- and post-test phases according to the parameters established. Further studies to establish a larger sample size, longer treatment time, and more consistent student population would support and strengthen the results established throughout this research.

REFERENCES

Association of American Medical Colleges. (2021, July). Using MCAT data in 2022 medical student selection - AAMC. Retrieved October 14, 2021 from https://www.aamc. org/media/18901/download.

Bonner, M. J., Stinnett, S. S., Cullins, M. D., & Andolsek, K. M. (2019). The duke master of biomedical sciences enhances student MCAT performance.

https://sites.duke.edu/mbsmcats/files/2019/08/DukeAHEAD_2019-PosterAbstract__-MCAT.8.19.2019-1.pdf

Davis, D., Dorsey, J. K., Franks, R. D., Sackett, P. R., Searcy, C. A., & Zhao, X. (2013). Do racial and ethnic group differences in performance on the MCAT exam reflect test bias? Academic Medicine, 88(5), 593–602.

Girotti, J. A., Chanatry, J. A., Clinchot, D. M., McClure, S. C., Swan Sein, A., Walker, I. W., & Searcy, C. A. (2020). Investigating group differences in examinees’ preparation for and performance on the new MCAT exam. Academic Medicine, 95(3), 365–74.

Hartwig, M. K., & Dunlosky, J. (2011). Study strategies of college students: Are self-testing and scheduling related to achievement? Psychonomic Bulletin & Review, 19(1), 126–34.

International Medical Aid. (2022, November 28). Medical schools that don’t require the MCAT in 2022: Definitive guide. International Medical Aid. Retrieved December 4, 2022, from https://medicalaid.org/medical-schools-that-dont-require-the-mcat-in-2022the-definitive-guide/

Jones, R. F. (1986). The effect of commercial coaching courses on performance on the MCAT. Journal of Medical Education, 61(4), 273–84.

Karpicke, J. D., Butler, A. C., & Roediger III, H. L. (2009). Metacognitive strategies in student learning: Do students practice retrieval when they study on their own? Memory, 17(4), 471–79.

Kennette, L. K., & Redd, B. R. (2015). Instructor presence helps bridge the gap between online and on-campus learning. College Quarterly, 18(4).

McCabe, J. (2010). Metacognitive awareness of learning strategies in undergraduates. Memory & Cognition, 39(3), 462–76.

Murphy, B. (2019, July 22). Beyond the MCAT: Here’s what else med schools are looking for. American Medical Association. Retrieved December 4, 2022, from https://www. ama-assn.org/medical-students/preparing-medical-school/beyond-mcat-heres-what-elsemed-schools-are-looking

Rawson, K. A., & Dunlosky, J. (2011). Retrieval practice for durable and efficient student learning: How much is enough? PsycEXTRA Dataset.

Roediger, H. L., & Butler, A. C. (2011). The critical role of retrieval practice in long-term retention. Trends in Cognitive Sciences, 15(1), 20–27.

Roediger, H. L., & Karpicke, J. D. (2006). Test-enhanced learning. Psychological Science, 17(3), 249–55.

Shipley, T. W., Phu, N., Etters, A. M., & Kadavakollu, S. (2019). Comprehensive Medical College Admission Test Preparatory course as a strategy to encourage premedical students to pursue osteopathic medicine in rural areas. Journal of Osteopathic Medicine, 119(4), 243–49.

Steed, K. S., & Kadavakollu, S. (2019). How to prepare for the Medical College Admissions Test (MCAT): Six important tips for pre-medical students from rural areas. Medical Science Educator, 29(4), 1147–53.

Swan Sein, A., Cuffney, F., & Clinchot, D. (2020). How to help students strategically prepare for the MCAT exam and learn foundational knowledge needed for medical school. Academic Medicine, 95(3), 484.

White, C. B., Dey, E. L., & Fantone, J. C. (2009). Analysis of factors that predict clinical performance in medical school. Advances in Health Sciences Education, 14(4), 623–23.

APPENDIX A

Informed consent document for IRB application

Project Title: Identifying the optimal pedagogy for preparing undergraduates for the MCAT exam

Principal Investigators: Dr. Ryan Himes and Alyssa Black

You are being asked to participate in a research project conducted through Olivet Nazarene University. The University requires that you give your signed agreement to participate in this project.

The investigators will explain to you in detail the purpose of the project, the procedures to be used, and the potential benefits and possible risks of participation. You may ask them any questions you have to help you understand the project. A basic explanation of the project is written below. Please read this explanation and discuss with the researchers any questions you may have.

If you then decide to participate in the project, please sign on the last page of this form in the presence of the person who explained the project to you. You should be given a copy of this form to keep.

1. Nature and Purpose of the Project:

The purpose of “Identifying the optimal pedagogy for preparing undergraduates for the MCAT exam” is to investigate the best preparation strategies for the Medical College Admission Test (MCAT).

2. Explanation of Procedures:

An experiment using five groups of students will help us to determine the most effective study strategy for the MCAT exam. Each group will take a pre- and post-test using a set of MCAT style biochemistry questions. Participants will be given ninety seconds per question according to the approximate time allotted for each question on the MCAT. The students in the control group will only take the pre- and post-tests without any instruction or reading. A second group will be given an assigned textbook reading from an MCAT preparatory book between taking the pre- and post-tests to determine how beneficial reading is to the test score. The third group will be given the same reading in addition to a memorization exercise to complete for one hour in between the pre- and post-tests to assess the advantages of memorizing information. A fourth group will be given the same reading and memorization task as the previous group but will also utilize test-enhanced learning by taking a separate set of biochemistry practice questions and receiving feedback. The final group will integrate the reading, memorization task, and test-enhanced learning exercise into a student-instructor

environment. For this group, a one-hour lecture on the decided topic will be taught to the students by an instructor to determine the benefits of an instructor-led course. Students participating in the study must have a minimum of one semester of college level science course but have not taken biochemistry.

3. Discomfort and Risks:

Participants will be required to make some time commitment between thirty minutes to three hours total. There are no evident risks to the participant but if time commitment or test anxiety are a concern, participants should withdraw from the study.

4. Benefits:

Students who are interested in taking the MCAT or other graduate-entry exam may benefit from the results of this study. Determining the best study strategy for this standardized exam may help students better prepare for any other standardized post-undergraduate assessment. Those who participate for more than 30 minutes will also receive a $10 gift card as incentive for their time commitment.

5. Confidentiality:

Any explicit identification such as names or student ID number will not be recorded. Any information received from the study will remain anonymous.

6. Refusal/Withdrawal:

Refusal to participate in this study will have no effect on any future services you may be entitled to from the University. Anyone who agrees to participate in this study is free to withdraw from the study at any time with no penalty.

You understand also that it is not possible to identify all potential risks in an experimental procedure, and you believe that reasonable safeguards have been taken to minimize both the known and potential but unknown risks.

Signature of Participant

Witness

Date

Date

THE DATED APPROVAL ON THIS CONSENT FORM INDICATES THAT THIS PROJECT HAS BEEN REVIEWED AND APPROVED BY THE OLIVET NAZARENE UNIVERSITY INSTITUTIONAL REVIEW BOARD

Pre- and post-test questions

Name _________________________________

For the following questions, please circle the correct answer. You have 23 minutes to complete this quiz.

1. Which of the following is the correct equation for deriving the K m from a Lineweaver-Burk plot, such as the one shown below?

A. K m = 1 / slope

B. K m = -1 / x-intercept

C. K m = slope * y-intercept

D. K m = -1 * x-intercept / slope

2. Based on the following graph, what type of inhibitor is represented by the red line ?

A. mixed

B. noncompetitive

C. uncompetitive

D. competitive

3. If an enzyme has a low catalytic efficiency, you would expect it to have which of the following characteristics?

A. L ow k cat and high K m

B. L ow k cat and low K m

C. High k cat and low K m

D. High k cat and high K m

4. An enzyme is operating close to its maximal rate. Which of the following is most likely true of [S] and [ES]?

A. [S] is near zero, and [ES] is high

B. Both [S] and [ES] are near zero

C. [S] is high, and [ES] is near zero

D. Both [S] and [ES] are high

5. If the reaction velocity of an enzyme is at half of its V max when [S] = 14 mM, what is the K m for this enzyme?

A. K m = 21 mM

B. K m = 28 mM

C. K m = 14 mM

D. K m = 7 mM

6. Which of the following best describes a competitive inhibitor of an enzyme?

A. Binds irreversibly to the active site of the enzyme

B. Binds reversibly to the active site of the enzyme

C. Binds irreversibly to an allosteric site on the enzyme

D. Binds reversibly to an allosteric site on the enzyme

7. For a given reaction catalyzed by an enzyme, what would be the effect of decreasing [Enzyme]? Assume that the reaction is allowed to reach equilibrium.

A. The reaction rate would decrease

B. The total amount of product formed would decrease

C. Both the reaction rate and the amount of product formed would decrease

D. Neither the reaction rate and the amount of product formed would decrease

8. The effe ct of a noncompetitive inhibitor on an enzyme is to ______.

A. R aise V max and K m

B. L ower V max and K m

C. L ower V max only

D. R aise K m only

9. The K m of enzyme A is 12 mM, while the K m of enzyme B is 20 mM. Which of the following is true?

A. Enzyme A has lower affinity for its substrate

B. Enzyme B has lower affinity for its substrate

C. Enzyme B binds to a different substrate than enzyme A

D. There is not enough information given to make a comparison between the enzymes.

10. A p articular enzyme has a K m value of 6.0 mM and a V max of 30 mmol/sec. If the substrate concentration is 600 mM, the rate of reaction is most likely to be ______.

A. 15 mmol/sec.

B. 29 mmol/sec.

C. 58 mmol/sec.

D. 180 mmol/sec.

11. Which of the following has the largest impact on the specificity of an enzyme?

A. The K m value

B. The shape of the active site

C. The k cat value

D. The presence of a competitive inhibitor

12. The optimal temperature for a given chemical reaction with an enzyme catalyst will generally be _______ the optimal temperature for the same reaction without an enzyme.

A. e qual to

B. g reater than

C. lower than

D. Not enough information is provided to make a comparison.

13. The reaction rate for a chemical reaction catalyzed by an enzyme is measured for a range of substrate concentrations, shown in the table at right. What is the approximate K m for this enzyme?

14. The following graph depicts reaction rates of an enzyme as a function of substrate concentration, with and without two inhibitors A and B.

Which of the following can be said of the inhibitors, based on the data?

A. Inhibitor A decreased the affinity of the enzyme for its substrate more than Inhibitor B.

B. Both inhibitors had an equal effect on the affinity of the enzyme for its substrate.

C. Inhibitor A decreased the V max of the enzyme more than Inhibitor B.

D. Both inhibitors are competitive inhibitors of the enzyme.

15. What is the effect of an enzyme on the ΔGʹ° value for a chemical reaction?

A. The enzyme causes the ΔGʹ° value to increase.

B. The enzyme changes the ΔGʹ° value to zero.

C. The presence of an enzyme does not affect the ΔGʹ° value.

D. The enzyme causes the ΔGʹ° value to decrease.

Analysis of the Population Structure and Migration Habits of the Northern Leopard Frog (Lithobates Pipiens) at Midewin National Tallgrass Prairie

ACKNOWLEDGEMENTS

Special thanks are due to the Pence-Boyce Research Grant bestowed on this project in the summer of 2022, which financially supported essential research expenses necessary to complete this project. I would also like to express appreciation for the Hippenhammer Grant providers for granting this project consistent financial support throughout the years of its development and completion. Thanks also to the University of Utah’s Core Genomics Facility for working with me to supply genotyping/sequencing data for such a large data set. Without this help, the level of analysis required for this research would have been nearly unattainable. I also greatly appreciate the constant support the faculty and members of the Honors Program at Olivet Nazarene University have given me throughout my entire undergraduate experience. All your patience, guidance, and pushes for improvement are what have allowed this thesis to come to fruition—something I will always be grateful for.

Finally, my deepest thanks to my mentor, Dr. Troendle, who has guided through highs and lows, supported me during failures, and helped me tremendously with the sample collections required to complete this project. Not only has working with my mentor allowed me to complete a project of this size, but Dr. Troendle has also cultivated a passion for this area of study within me. I cannot thank you enough for being the guiding light towards my creation of a research project that I am immensely proud of.

ABSTRACT

Massive amphibian declines of recent years have pushed researchers to pursue population genetics surveys and assess the status of these essential components of many ecosystems. The Northern Leopard Frog (Lithobates pipiens) has continuously experienced population declines across the continental United States due to a combination of habitat losses and environmental changes. Midewin National Tallgrass Prairie houses a considerable portion of L. pipiens in Illinois, and the two creek watersheds studied within this location provide ideal conditions to support these animals. Because this prairie restoration project is a relatively recent development, further assessments regarding the population structure and degree of migration within these L. pipiens populations are needed. Analysis of seven microsatellite loci specific to L. pipiens revealed significant deviation in Hardy-Weinberg Equilibrium for most populations, supporting the large estimated migration rate of 7.197 migrants per generation. Genotype clustering analysis also implied large instances of gene flow between populations—a likely effect of many migration events. Additionally, high levels of genetic diversity (H o = 0.7920.873) and total private alleles (46) were surprisingly maintained in all observed populations, suggesting large population sizes. These findings indicate the presence of an incredibly large, dynamic, and biodiverse L. pipiens population that has not previously been defined in this area. With this information, further protection of the Midewin populations can be achieved to avoid the genetic diversity and population size loss associated with L. pipiens groups located in the western United States.

Keywords: Population genetics, L. pipiens, Midewin National Tallgrass Prairie, Illinois, migration, microsatellite loci, gene flow, genetic diversity

INTRODUCTION

Scientists have recorded global amphibian population declines since the 1980s and early 1990s, when concerns about amphibian disappearances influenced an increase in observational studies (Hayes & Jennings 1986). At around this time, reports of over 500 frog and salamander populations considered their declines to be of special conservation concern (Blaustein & Kiesecker 2002). In a more recent study, upwards of 1,000 data-deficient amphibian species were determined to be threatened with extinction (González-del-Pliego et al. 2019). Amphibians play many important roles in ecosystems, and the continual population losses will have critical future implications on ecological function (Rogers and Peacock 2012). These consistent downward trends have greatly effected biodiversity and species health, leading to urgent calls for population research and conservation efforts (Seaborn & Goldberg 2020; González-del-Pliego et al. 2019; Beebee & Griffiths 2005; Blaustein & Kiesecker 2002). Additionally, because

they are frequently exposed to various contaminants when using ponds to reproduce, amphibian population trends are often used as biological indicators. In these cases, researchers can preemptively identify potential dangers in an environment by observing how amphibian populations respond to them (Smith 2003). Ultimately, the scientific and environmental purpose of amphibians—in addition to their intrinsic value, should encourage further goals of protecting their biodiversity worldwide.

Specifically within the class Amphibia, species in the family Ranidae (or true frogs) that are native to North America have experienced repeated instances of local population declines and range reductions since the late 1800s (Hayes & Jennings 1986). As a member of the Ranidae family, the Northern Leopard Frog (Lithobates pipiens) has not escaped this fate. Many researchers have reported declines of these populations in Nevada (Rogers & Peacock 2012), Washington state (Seaborn & Goldberg 2020), and the national parks of South Dakota and Wyoming (Smith 2003). In some areas, previously identified populations have disappeared completely (Werner 2003). In 2012, a petition to list the L. pipiens as threatened in the western United States under the Endangered Species Act of 1973 was submitted to the United States Fish and Wildlife Service (U.S. Fish and Wildlife Service 2012). After reviewing a previous petition from 2009, the U.S. Fish and Wildlife Service concluded that the proposed threatened status L. pipiens was not warranted in this twelve-month finding, regardless of the concerning population losses in western states (U.S. Fish and Wildlife Service 2012). Because L. pipiens is experiencing declines, continuous research on population health must be conducted to potentially aid their protection from further losses.

Likely causes of ranid frog declines

Many hypotheses have been brought forward to explain the dramatic and continuous amphibian declines worldwide. Some of these hypotheses include competition, habitat alteration, predation, exploitation, contaminants, and pathogens as major contributors to amphibian population loss (Hayes & Jennings 1986). For example, the resource competition and predation of North American ranid frogs by the American Bullfrog (Lithobates catesbeianus) has been noted to have the potential to eliminate L. pipiens populations, along with many other factors (Hayes & Jennings 1986). Habitat changes are the most probable cause of the loss of western ranid populations. This is frequently observed as a loss of suitable nursery environments and refuges for hibernating adult frogs, resulting in a major negative impact on the species’ overall survival (Rogers & Peacock 2012; Hayes & Jennings 1986). Similarly, excessive road traffic can also have an impact on amphibian migrations critical to locating suitable breeding environments (Beebee & Griffiths 2005). Dynamic climate changes are another instance of habitat change, and these changes can heavily influence amphibian populations by causing a varying yet detectable effect on amphibian breeding phenology (Beebee & Griffiths 2005). Additionally, droughts and unusually dry seasons have been speculated to even

cause the extinction of some non-ranid amphibians and could be yet another origin of stress on ranid populations (Smith 2003). Finally, viruses and fungal infections are another probable influence on L. pipiens populations, with these types of diseases being frequently identified in mass mortality events (Smith 2003). Chytridiomycosis, one of these lethal fungal infections, has been blamed for worldwide amphibian declines (Smith 2003; Rogers & Peacock 2012) and has been known to negatively impact some L. pipiens populations as well (Voordouw et al. 2010). Because of the damage these external factors can have on any species of ranid frog, it is incredibly important to understand what could be influencing populations while conducting a genetic assessment on L. pipiens populations.

The Northern Leopard Frog (Lithobates pipiens)

L. pipiens is a species of frog taxonomically grouped into the family Ranidae. These frogs are characterized by round, white-margined dark spots on the dorsal side and dorsolateral folds with some occasional pigment variations between isolated populations (Rogers & Peacock 2012). L. pipiens is a slim, medium-sized frog with average weights ranging from 16 to 80 grams and average lengths ranging from 5 to 11 centimeters in adults (U.S. Fish and Wildlife Service, n.d.). This species of frog has previously been known to range from the northern half of the United States far into the north of Canada with some of the southernmost populations located in the western United States (Smith 2003). Populations have been steadily declining nationwide, however, and the presumed distribution of these frogs has been dramatically altered after extensive population research (Seaborn & Goldberg 2020; Rogers & Peacock 2012; Smith 2003; Werner 2003). With sightings of living populations varying so wildly between researchers, a recent, more accurate map of L. pipiens distribution has yet to be accepted.

Previous research has identified that the migration habits of L. pipiens generally consist of an initial movement from overwintering sites to breeding sites in the spring, then a dispersal to grassy meadows during the warm summer, and finally a fall migration where adults return to overwintering sites once again (Smith 2003). Migrations between upland sites occur seasonally within their home range, and the frogs often prefer habitats with adequate moisture during summer temperatures to aid in reproductive success (Smith 2003). Since L. pipiens generally have breeding periods from the middle of March through the entirety of May, shallow water systems such as streams, ponds, and creeks help retain necessary moisture (Illinois Department of Natural Resources 2020).

Survey locations

As mentioned previously, L. pipiens prefers to inhabit areas with adequate moisture and shallow water systems to aid in survival in summers and breeding periods. Within

Midewin National Tallgrass Prairie, where these frogs are abundant, both aquatic and terrestrial environments fulfill the requirements necessary for L. pipiens survival. Midewin National Tallgrass Prairie was established in 1996, making it one of the first national tallgrass prairies developed within the United States (The Nature Conservancy, n.d.). The location is a large-scale prairie restoration project aiming to restore approximately 20,000 acres of farmland into functional tallgrass prairie that can support a variety of native or previously threatened species (The Nature Conservancy, n.d.). Because of the land’s protection of environmentally sensitive and endangered midwestern plant and animal species, Midewin also has the continued protection of the Nature Conservancy (The Nature Conservancy, n.d.). The area of Midewin National Tallgrass Prairie is mostly separated into two distinct watershed environments, Grant Creek and Prairie Creek, the predominant L. pipiens collecting locations. Prairie Creek runs through a majority of Midewin National Tallgrass Prairie before meeting with the Kankakee River. Alternatively, only a portion of Grant Creek runs through Midewin before also merging into the Kankakee River. Before the dry summers, both creeks branch out, forming small streams and ponds throughout Midewin National Tallgrass Prairie. This event creates optimal breeding sites for L. pipiens populations throughout the tallgrass prairie.

Research objective

Identifying the environmental influences on populations is essential to further understanding how differing conditions can shape genetic variation within a species. In restoration areas like Midewin National Tallgrass Prairie, L. pipiens has populations that are geographically isolated by watershed environments. These individual watersheds act as experimental replicates with varying resources, competing populations, and levels of contamination. Aquatic-bound organisms, like L. pipiens, often experience a strong influence in their population structure due to their heavy reproductive reliance on water sources and the terrestrial areas draining into these water sources (Loxterman & Keeley 2012). Although previous research has identified significant genetic diversity in other aquatic organisms separated by watersheds (Seaborn & Goldberg 2020; Kremer et al. 2017; Loxterman & Keeley 2012; Rogers & Peacock 2012), there is a lack of knowledge on how L. pipiens at Midewin National Tallgrass Prairie is affected by these barriers, specifically because the two surveyed watersheds are geographically close— with a small overall survey radius of about 1.5 km (Figure 1, Table 1). The goal of this research is to determine the population structure of the Prairie Creek and Grant Creek watersheds at Midewin National Tallgrass Prairie and to assess the degree of migration between four L. pipiens subpopulations within these two watersheds environments.

L. pipiens survey locations at Midewin National Tallgrass Prairie (Wilmington, IL, USA). Included are the Prairie Creek (P and Po) and Grant Creek (Gm and G) watershed populations.

METHODOLOGY

Sample collection

At Midewin National Tallgrass Prairie (Wilmington, Illinois), toe clip and dorsal dermal swab collections of L. pipiens were obtained within two locations at each of the two observed watershed regions—Grant Creek (labelled G and Gm) and Prairie Creek (labelled P and Po). L. pipiens specimens were collected using dip nets from a variety of aquatic and terrestrial environments. After the frogs were captured with dip nets and then restrained with gloved hands, sterile omniswabs were used to collect the frog’s dermal cells and surgical grade scissors were used to collect 2-3 mm of toe tissue from each organism. To collect an adequate quantity of dermal cells, the sterile omniswabs were run back and forth along the frog’s dorsal surface five times (Ringler 2018) and

Pairwise representation of approximate distances in meters between each of the four L. pipiens survey locations at Midewin National Tallgrass Prairie.

then ejected into a 1.5 mL microcentrifuge tube similarly to the toe clip samples to be stored at 0°C until further analysis (Prunier et al., 2012). A total of 71 frogs were sampled at Midewin using these methods; of these 71 frogs, 36 were sampled in the Prairie Creek watershed and 35 were sampled in the Grant Creek watershed. Additionally, for easy identification of each frog’s exact location, the latitude and longitude coordinates of the collection site were recorded for each specimen (Appendix A).

DNA extraction and PCR amplification

The DNA extraction of toe clip samples utilized QIAGEN’s DNeasy® Blood and Tissue Kit and the corresponding tissue extraction protocol provided in the handbook. Dermal swab samples were extracted using the same kit; however, the kit’s alternative protocol specifically for omniswabs was used instead. After extraction, samples were only used in the following downstream reactions if they surpassed the limit of 5 ng/µL DNA in 50 µL aliquots. DNA concentrations of each sample were quantified using the ThermoFisher NanoDropTM UV-vis spectrophotometer. A total of seven fluorescently labelled microsatellite primer pairs for L. pipiens were used to amplify the extracted DNA samples as shown in Table 2 (Hoffman et al. 2003). These seven microsatellite primers were chosen for both their previous successful uses in many studies involving the genotyping of L. pipiens and for their relatively similar annealing temperatures. Each PCR reaction mixture contained 0.5 U PromegaTM Taq Polymerase,

Table 2: Microsatellite primer pairs

Microsatellite sequence information for L. pipiens as described by Hoffman et al. in 2003. The annealing temperature (Ta), number of base pairs, and number of alleles are also provided. An asterisk indicates a 5ʹ fluorescent-labelled primer.

1 PromegaTM PCR buffer mix, 1.5 mM MgCl2, 0.1 mM of each dNTP, and 0.8 mM of each primer (Hoffman et al. 2003). The reactions occurred in 25 µL volumes that contained 1-6 µL of previously extracted template DNA to ensure approximately 30 ng of DNA were in each reaction. The specific parameters for the subsequent PCR amplification are as follows: an initial cycle at 94°C (2 min); 36 cycles of 94°C (30s), then the specific annealing temperature (30s), then 72°C (1 min); and a final extension of 72°C (2 min). After completion of PCR, 5 µL of each reaction was run through 2% agarose gel to confirm that DNA amplification had occurred correctly.

DNA genotyping and statistical analysis

After amplification was confirmed, each sample was prepared as per the request of the University of Utah’s Genomics Core Facility for genotyping. Once the genotypes were obtained, population analysis of the L. pipiens at Midewin National Tallgrass Prairie was conducted using a combination of the software packages GENEPOP (Rousset 2008, Raymond & Rousset 1995; version 4.8.2), GenAlEx (Peakall & Smouse 2006, 2012; version 6.51), and STRUCTURE (Hubisz et al. 2009; Falush et al. 2007, 2003; Pritchard et al. 2000; version 2.3.4). Each program calculated various measurements needed to assess genetic diversity, population structure, and degrees of migration.

GENEPOP was utilized to test each L. pipiens population for Hardy-Weinberg Equilibrium (HWE), determine the presence of linkage disequilibrium (LD) among all loci, and calculate the average number of L. pipiens migrants per generation. HWE is a denotation given to populations that have exhibited genotype frequencies that remain constant between subsequent generations due to a lack of external, genotype disturbing events such as mutation, migration, selection pressure, or genetic drift (Edwards 2008). This is one of the most commonly used methods of confirming genetic stability, and any deviations of HWE usually indicates events that have decreased heterozygosity, usually via genetic drifting. Increased observed heterozygosities can also occur in response to genotype disturbing events—typically in instances of high mutation or migration. Measurements of LD are used in combination with HWE assessments and provide information on the independence of alleles. When there is no evidence for LD, populations are often simultaneously in HWE, and a proportionally large heterozygote frequency is maintained (Slatkin 2008). HWE tests were conducted using the Markov chain method using 1000 batches and 10,000 iterations per batch. The presence of LD was determined using the same batch and iteration per batch number. Finally, the number of migrants per generation, when within the constraints of one to ten migrants per generation as described by Mills and Allendorf, determines whether the risk for deleterious allele fixation or genetic drift events is decreased (1996).

The GenAlEx program was used to calculate F-statistics (F is, F it, and F st), Nei’s G-statistics (Nei 1973), the number of different alleles (N a), the number of effective alleles (N e), the number of private alleles of each locus and population, the number

of migrants (Nm) per locus, and the expected (H e) and observed (H o) heterozygosity. Most of these measurements were taken to observe the levels of genetic diversity between populations and microsatellite loci, and in the case of the F-statistics and Nei’s G-statistics, the genetic differences between the sampled locations.

Finally, the STRUCTURE program was utilized to develop an estimated genotype cluster (k) bar plot of the subpopulations’ allele distributions using Bayesian analysis. The orientation and number of k genotype clusters aids in determining the levels of gene flow between populations and to what degree any instances of genetic isolation occur at. The results from this program are primarily used to support and connect the data received from the previous two programs, GENEPOP and GenAlEx.

RESULTS

Population genetic diversity

Genotypes of all L. pipiens samples from each sampling location at Midewin National Tallgrass Prairie (populations abbreviated G , Gm , P , and Po ) were obtained for each microsatellite locus. The average expected heterozygosity ( H e) of all seven loci across each population was at expected levels of approximately 84.3-88.2%, but they were slightly lower than those noted for other northeastern L. pipiens populations at 89.3-91.5% (Hoffman et al. 2004). Average observed heterozygosity ( H o) ranged from 79.2-87.3%. These two values ( H e and H o) were then compared to assess whether each population was in Hardy-Weinberg Equilibrium (HWE), and by using GENEPOP and GenAlEx software, it was revealed that most of the sampled L. pipiens populations appeared to be significantly out of HWE. Significant deviations from HWE existed in populations Gm ( p = 6.981E03), P ( p = 3.80E-08), and Po ( p = 6.10E-04), and only one population ( G ) was in HWE ( p = 0.148) as shown in Table 3. Additionally, the GENEPOP and GenAlEx

The mean (SE) over all microsatellite loci in each of the four L. pipiens locations at Midewin National Tallgrass Prairie (Wilmington, IL, USA). N = population size, N a = number of different alleles, N e = number of effective alleles, H o = observed heterozygosity, and H e = expected heterozygosity. Note deviations in HWE: *** p ≤ 5E-08, ** p ≤ 0.005, * p ≤ 0.05

The F-statistics of all L. pipiens populations at Midewin National Tallgrass Prairie (Wilmington, IL) for each microsatellite locus. F is = inbreeding coefficient of individual to subpopulation, F it = inbreeding coefficient of individual to total population, F st = fixation index, Nm = number of migrants.

Total number of private alleles found within each sampled L. pipiens population. Population

Pairwise population matrix of genetic variance (F st ) values between the four sampled locations of L. pipiens to measure population structure.

Bayesian genotype clustering for the L. pipiens populations at Midewin National Tallgrass Prairie. Population 1 is G of Grant Creek, population 2 is Gm of Grant Creek, population 3 is P of Prairie Creek, and population 4 is Po of Prairie Creek

programs revealed little evidence for the presence of linkage disequilibrium ( LD ) between any alleles.

Inbreeding coefficients (F is) were also obtained for all populations across each of the seven microsatellite loci and ranged from -0.066 to 0.171 (mean [SE] = 0.011 [0.030]) with Rpi107 representing the maximum. Measurements of F it were also taken across each locus and ranged from -0.017 to 0.204 (mean [SE] = 0.045 [0.029]) with Rpi107 once again representing the maximum (Table 4). The fixation index was taken for each microsatellite locus, appearing slightly larger for each locus rather than each population (mean [SE] = 0.035 [0.003]; Table 4). Private alleles were present in every surveyed L. pipiens population (Table 5).

Population structure and degree of migration

A pairwise F st test reveals consistently low values throughout all compared populations (0.018-0.029), indicating high levels of interbreeding between the sampled locations (Table 6). This is further supported through STRUCTURE Bayesian genotype clustering (k = 3) of the populations, showing evidence of population differentiation (Figure 2). A pairwise test based on Nei’s measurements of genetic identity and distance revealed relatively high levels of similarity between most populations (Table 7). An average of approximately seven migrants were estimated to have occurred between all four L. pipiens populations per generation (Table 4).

DISCUSSION

Population genetic diversity

Although average H e for all microsatellite loci across each population was lower than previously recorded measurements of L. pipiens populations in the northeastern United States (0.893-0.915; Hoffman 2004), Midewin populations exhibited a relatively high H e range of 0.843 in population Po to 0.882 in population G (Table 3). Additionally, the H e of Midewin populations was quite similar to those measured

from North Dakota (0.81-0.88; Mushet et al. 2013) and were noticeably higher than the H e of Nevada’s drastically declining remnant populations (0.411-0.482; Rogers and Peacock 2012). These generally high H e values for L. pipiens at Midewin indicate similarly high levels of genetic diversity within all populations. From this, population G was found to have the highest H e and subsequently the highest genetic diversity of the four populations. The H o for populations Gm, P, and Po significantly diverted from the corresponding H e, indicating Hardy-Weinberg Disequilibrium (HWD)— that of which can be induced by mutations, selection pressures, migrations, or genetic drifting events within these populations (Table 3). Population G, on the other hand, was the only tested subpopulation that remained in HWE. Of the populations out of HWE, two (Po and Gm) showed significantly higher H o while one (P) showed significantly lower H o which could both be influenced by the events mentioned previously (Table 3).

Opposing evidence for genetic drifting events being the cause of the observed HWD was indicated by the low F-statistics (F it and F st) average for all populations. These low, and sometimes even negative, values imply high levels of genetic diversity that are consistent with low genetic differentiation of the individual or subpopulation to the total sampled group (Table 4). Essentially, because each population has high genetic diversity in these circumstances, it is unlikely that they are recovering from or currently experiencing a genetic drifting event. This is because in those scenarios, very few genotypes survive and drastically lower overall genetic diversity. Additionally, the inbreeding coefficients (F is) for each population also opposed the possibility for genetic drift since they were quite low for each microsatellite locus, consistent with previous conclusions of the relatively high genetic diversity within Midewin populations. Low F is values, like those shown for all loci, indicate a general avoidance of inbreeding and overall high levels of heterozygosity for each locus (Table 4). Private allele analyses indicated a larger number of rare genotypes—thus larger population sizes and higher preservation of diversity—present in all measured populations at Midewin National Tallgrass Prairie (Table 5).

Population structure and degree of migration

Each sampled population of the Prairie and Grant Creeks largely appear to be interbreeding (rather than inbreeding) between each other when observing pairwise F st values (0.018-0.029, Table 6). Compared to contemporary measurements of genetic divergence in other northeastern L. pipiens populations (0.043 average), the surveyed Midewin populations were less genetically differentiated (Hoffman et al. 2004). This difference can likely be attributed towards the small survey radius of about 1.5 km compared to the larger distances of the study in 2004 by Hoffman et al., and this data largely supports the likelihood that migration could be causing HWD in these

populations. Additionally, L. pipiens populations in the northwestern United States, particularly the remnant populations of Nevada, experienced some instances of low pairwise F st values between sampling locations of a similar distance as the Midewin populations (F st = 0.0124), and these were considered indicative of minimal differentiation (Rogers & Peacock 2012). Next, pairwise representations of Nei’s original measurements on genetic distance and identity were taken from the GenAlEx program (Table 7). These values also revealed generally high levels of relative genetic similarity between all sampled locations at an average of 0.713. This average opposes the likelihood of a barrier (whether that be sympatric or allopatric) between populations that is preventing interaction and encouraging subsequent speciation. Of the Nei’s genetic identity measurements, the two Prairie Creek locations were the most genetically similar, whereas populations Gm and Po were the least similar (Table 7). The least genetically similar populations, Gm and Po, were simultaneously the farthest in distance from one another (≈ 3 km), likely attributing to the relatively lower—albeit considerably high—genetic similarity. All results of these measurements (the F-statistics and Nei’s measurements) support the idea that the L. pipiens survey locations at Midewin National Tallgrass Prairie are likely a singular, interbreeding population rather than multiple, isolated subpopulations.

STRUCTURE Bayesian genotype clustering analysis (where k = 3) additionally provides further evidence of minimal genetic differentiation between the surveyed populations at Midewin. The horizontal genotype clusters that are fairly consistent sizes across all populations, which indicates high levels of gene flow and expression between all populations (Figure 2). In the case that these survey locations were genotypically isolated, k clusters would appear vertically, and in some cases colored clusters would appear solid throughout a designated population. The STRUCTURE genotype clustering histograms of L. pipiens throughout North Dakota are an example of these highly genetically isolated populations. This is primarily due to landscape and geographical isolation of subgroups via large rivers and long distances—variables that are not present throughout the surveyed locations of Midewin (Waraniak et al. 2019). Furthermore, the cluster number k of the Midewin populations was chosen based off logarithmic possibilities as shown further in Appendix B. Migration rates between Midewin populations were also estimated to be about 7.197 migrants per generation when accounting for the size of the populations studied. This is well within recommended migrations between populations (one to ten migrants per generation) to maintain adequate levels of genetic diversity and avoid the effects of deleterious allele fixation (Mills and Allendorf 1996). When considering the number of private alleles for each population in addition to the number of migrants, the overall population sizes of each sampled location at Midewin must be incredibly large to maintain such a high degree of genetic variability.

CONCLUSION

The maintenance and preservation of genetic diversity of L. pipiens is considered to be essential for the western regions of the United States where researchers have noted drastic losses of populations and diversity (Seaborn & Goldberg 2020, Rogers & Peacock 2012, Smith 2003 & Werner 2003). To avoid any similar degradation events, areas in the eastern United States must encourage a similar mindset. The L. pipiens populations of Midewin National Tallgrass Prairie show signs of large, genetically diverse, and ultimately healthy populations of these animals. Even though there are significant deviations in Hardy-Weinberg Equilibrium, none appear to be the result of bottlenecking, colonization, or other genetic drifting events. Instead, large instances of migration per generation appear to be the influence of these deviations while surprisingly avoiding any loss of population-specific, private alleles. These two characteristics of the Midewin L. pipiens populations heavily implies the possibility for enormous population sizes, which is an essential component for the maintenance of their genetic diversity. The tested locations of both the Grant Creek and Prairie Creek watersheds also showed a high instance of gene flow—likely an effect of the high migration rate— that suggests the watersheds are quite interconnected and provide no geographic barriers to prevent interbreeding. Additionally, an interesting relationship between Nei’s original measurements on genetic distance and identity hints at the possibility of a potential genetic distance/geographic distance relationship within these populations. This potential relationship, as well as further analyses into genetic development of the populations over time could both be investigated to further understand the dynamics of the L. pipiens populations at Midewin National Tallgrass Prairie.

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SUPPLEMENTAL MATERIALS

Appendix: A Latitude and longitude coordinates of each L. pipiens survey location at Midewin National Tallgrass Prairie.

Appendix: B Logarithmic likelihoods for k and Δk for the Bayesian genotype clustering analysis.

Assessment Of Walls with Phase Change Materials Through Synergistic and Performance Measures Using Experimental and Simulated Test Houses

ACKNOWLEDGEMENTS

I would like to acknowledge and thank Dr. Mario Medina from Kansas University for allowing me to utilize his data and research for my Olivet Honors thesis and for acting as an additional faculty mentor. Dr. Medina provided guidance, background knowledge, and comments throughout the research process that were integral for the success of the project. Without Dr. Medina’s support, this project would not have been possible.

Additionally, I would like to thank Dr. Giraldo from Messiah University for being my on-campus mentor during the research process. While Dr. Giraldo was at Olivet, he was my main contact for any questions or problems I ran into. Without Dr. Giraldo’s expertise, the code used for the simulation and the final paper would not have been as polished.

ABSTRACT

Current research on living and working spaces continues to strive to identify the most energy-efficient methods for heating and cooling, and many novel technologies have emerged from the research. One of the most promising, and the topic of this quantitative analysis, is the retrofitting of phase change materials (PCMs) into the walls of structures. Research has shown positive results, such as a reduced transfer of heat through walls, when PCMs are retrofitted into wall construction. The present research takes previously gathered data from test houses, built with typical North American framing, and simulates an additional fourteen test houses from the gathered data. The simulated houses consisted of a unique combination of walls retrofitted with and without PCM in them. The fourteen unique simulations allowed for seven metrics, such as max heat flux, time delays (start, peak, and end), total heat, heat flux average, and standard deviation, to be measured. Most of the measure indicated a positive correlation with the addition of PCM being retrofitted into a wall. From the results, the east, west and south walls emerged to be the most influential when it came to the seven measures, and it is recommended that at least one of these three walls be included when retrofitting buildings.

INTRODUCTION

Combating climate change has become increasingly difficult as energy consumption rates continue to rise. Of the energy being consumed, nearly forty percent can be directly attributed to buildings, with about half of the energy consumed by buildings related to the heating and cooling of the structure [1,2]. Because of this, researchers have identified current building comfort practices as energy inefficient; additionally, researchers have identified elements within buildings, such as walls, that can be improved to elevate the energy efficiency of individual buildings. Elevated wall efficiency typically requires a wall medium that resists thermal inequalities between the indoor and outdoor temperatures. A higher thermal resistance helps to keep indoor temperature at the desired level for longer. Because of walls’ unique ability to maintain indoor air temperatures, researchers have focused on improving walls’ efficiency through the integration of phase change materials (PCMs) into the wall cavities. PCMs have been shown to significantly reduce the transfer of heat in and out of structures. A reduction of heat transfer in walls yields more consistent indoor temperatures, which reduces the energy load required by an HVAC system. Despite the positive results of walls with PCMs, further work is needed to show that retrofitting PCMs in walls has a profitable return on investment (i.e., reduction of energy cost in the long term). This analysis aims to quantify synergy between walls and their capabilities of keeping the heat transfer rate close to zero. Additionally, the study aims to determine an optimal

combination of walls, using data collected from the synergy analysis, to reduce the cost of retrofitting while still maintaining the desired energy saving qualities.

BACKGROUND

Energy background

Currently, the United States is the world’s second-largest consumer of energy, consuming over one-hundred quadrillion BTU (British Thermal Units) (about 17% of the world’s energy) annually. By the year 2050, energy consumption in the United States is expected to increase by nearly 50% due to population growth, economic growth, and climatic factors [1], [2]. As a result, researchers have begun to look for solutions that reduce the consumption of energy. Buildings consume a large portion of the total energy produced and have the most potential for energy consumption reduction. In the United States, buildings consume around 40% of all produced energy with nearly half of that energy going to maintaining thermal comfort for humans [1], [2]. For this reason, advancements in construction techniques and technology are needed to reduce energy consumption. These advances are happening in heating, ventilation, and air conditioning (HVAC) system improvements, renewable and clean energy, and improvement in construction methods.

Current solutions to decrease energy consumption

There are currently at least five novel technologies that improve the energy efficiency of HVAC systems. They are independent temperature and humidity controls, stratified ventilation, thermal energy storage (TES), heat recovery ventilation, and indirect evaporation cooling. These five technologies have improved HVAC systems and have shown the potential for reducing energy consumption in buildings without sacrificing the comfort and benefits of controlled interior climate [3]. The most recent solution being researched is the incorporation of TES into the construction of buildings, which increases the efficiency of building insulation. TES can occur through a chemical or physical process, such as a material going through a phase change or an endothermic or exothermic chemical reaction. Whatever the reaction chosen, the TES acts as a storage medium for the incoming heat, thus acting not only as an improved insulation but as a heat reservoir. The stored heat is then released when external temperatures drop, which allows the stored heat to flow out of the walls into the living space. In the case of most studies, the physical process of a phase change is used for building incorporation because of the complexities and dangers of incorporating a chemical process into building materials [4]. To harness and exploit the phase change process, in which energy can be stored and released in a material when it changes from one phase to another, PCMs are utilized in walls by way of retrofitting them into the construction to store incoming thermal energy [5], [6].

PCMs, by increasing thermal mass and thermal inertia, make it more difficult to change the indoor temperature of a building, thus allowing for easier climate control with less energy being consumed [6], [7]. PCMs can experience a variety of phase changes depending on the type chosen. For example, PCMs can experience a liquidto-vapor phase change, a solid-to-solid phase change, and lastly a solid-to-liquid phase change [4]. For most building applications, a solid-to-liquid PCM is used to absorb heat. Essentially, the PCM absorbs sensible heat until its melting point is reached, which is when the phase change begins. As the PCM changes from solid to liquid, it absorbs and stores heat as latent heat. Once the PCM is fully liquid, it goes back to absorbing sensible heat until it reaches its thermal capacity [4], [8]. While the PCM is undergoing its phase change, heat is being stored but the temperature is not rising (Figure 1). Once the PCM has completed its phase change, it stores heat sensible heat, and the temperature begins to increase again.

When incorporated into buildings, PCMs store the heat that would enter the building and reduce the need for cooling (i.e., lower energy consumption). Then, when the temperatures drop below the melting point or the freezing point (e.g., night hours), the PCMs revert to their solid state, which releases the heat back into the space reducing the need for heating.

PCM background

The type of PCM and incorporation method alters the PCMs’ effectiveness when retrofitted into walls. PCMs can be organic (paraffins and fatty acids), inorganic (salt hydrates and alloys), or eutectic (mixtures of organic and inorganic PCMs) and can be incorporated in walls using micro-encapsulation, macro-encapsulation, and porous

inclusion (wallboards soaked in PCMs) [4]–[7]. Selecting a PCM type is dependent on the conditions it will experience (e.g., weather patterns and incorporation methods). Milder climates would require a PCM with a higher melting point so that it will begin its phase change process during the hottest parts of the day. Similarly, in a cooler climate, a PCM with a lower melting point would be recommended for the same reasons. In fact, the PCM type can be selected to match the conditions it will experience without the need for intensive field research. However, researchers must still consider the thermal (melting point, specific heat, etc.), physical (volume change, vapor pressure, etc.), kinetic (supercooling, nucleation and crystallization rate), and chemical (chemical stability, non-toxic, etc.) properties when choosing PCMs to ensure the desired results [6].

Many of the properties mentioned previously can carry considerable drawbacks when considering incorporating PCMs into building construction. The physical properties, for instance, can significantly affect how the PCM will be incorporated and the longevity of the storage methods. Ensuring the incorporated PCM has a small volume change and a low vapor pressure is critical for the success of the selected incorporation method. Kinetic and thermal properties relate more to the effectiveness of the PCM in reducing the gained heat. Thermal properties are important for being effective in the climate in which it is used, and kinetic properties relate to the effectiveness of a PCM’s phase change. The chemical properties raise the most concerns and could have the most potential drawbacks. PCMs must be chosen to ensure the health and safety of the building’s occupants, which means the selected PCM should not be corrosive, toxic, flammable, or explosive; furthermore, it needs to be compatible with the chosen construction materials, have long-term stability, and have reversible phase change cycles. Though all the properties are important to the success of the PCM, the chemical properties have the most potential for having adverse effects on the building and its occupants.

Incorporation methods also require more testing to determine the most effective strategy, since incorporation methods range greatly (Figure 2) and are not reliant on weather conditions. Rather, incorporation methods are often left to the designer and are dependent upon the needs and wants of the architect. Micro-encapsulation is generally used when the PCM is contained by a coating or shell and then added directly to the wallboard. This is done either during the wallboard’s manufacturing or added to the insulation after manufacturing [6]. Macro-encapsulation can be anything from thin reflective foil sheets, to piping in the walls, to structurally insulated panels (SIPs) or masonry bricks [4], [7].

PCM research

Previous research has tested various combinations of PCM types and incorporation methods, and the consensus has been positive. When testing the effectiveness of PCMs, researchers focus on metrics such as average heat flux, peak heat flux, time delays in

terms of peak heat flux, energy efficiency, and a variety of temperature comparisons (e.g., indoor wall temperatures versus outdoor temperatures) [9]. The most common types of encapsulation methods in research are incorporated PCM in wallboards, pipes containing PCM, reflective foil sheets, metal casings, structurally insulated panels (SIPs), and masonry bricks.

PCM wallboard research indicates that PCM reduces indoor air temperature fluctuations and that PCM can shift the peak thermal loads to a later time when compared to control walls (i.e., walls without PCM) [10], [11]. Pipes containing PCMs showed capability to reduce both the total heat flux and the peak heat flux by 20-35%. In addition, pipes with PCM were also able to create a time delay in the peak heat fluxes [12], [13]. Like the piping method, SIPs and masonry brick enhanced with PCMs were able to achieve peak heat flux reductions up to 37% as well as peak temperature reductions [14]–[16]. Using reflective foil or metal casings for an incorporation method was found to reduce maximum temperatures by 17-67% depending on the season, smooth out temperature fluctuations, reduce heat fluxes by 29-51%, and achieve time delays ranging from two to six hours [17]–[19]. For all incorporation methods, PCM enhancements helped reduce peak heat fluxes, temperatures, and/or cause a time delay that shifts the max load later.

These results strongly indicate that buildings with PCM walls can experience more consistent thermal levels, yielding less strain on the heating and cooling systems. In addition, these results show that structures with PCM experience time shifts for the peak hours of energy demands and reduces the overall positive heat flux, allowing for the heavy energy loads to occur when energy is cheaper, thus saving consumers money while conserving energy. The culmination of each metric reduction in favor of PCMs translates into significant energy and money-saving potential.

The initial investment of installing PCMs on average can be paid back within a 7-to-10-year period, but this period can vary depending on geographic location and the initial investment [20]. Furthermore, the load shifting many PCM walls experience can access energy rates that are 20-35% of the peak energy price [21], [22]. On top of this, one study found that during a 12-day study, ten of those days experienced energy conservation ranging from 16% to 100% for an office building outfitted with PCMs [23].

Despite the positive results of PCMs in walls, there are still challenges that must be solved before PCMs can be widely used. Lack of knowledge about PCMs cost to retrofit into existing buildings, corrosion, and flammability plague the incorporation of PCMs [24]. However, an evident challenge comes from the fact that most research has been conducted under extreme conditions (summer and winter days) and not over everyday conditions. One study estimates that PCMs are only effective for about 40% of the entire year because of the different seasons and weather conditions experienced throughout the year [14]. Tackling this issue requires a different type of research that focuses on best practices.

One way of conducting this research would be through the creation of a new metric that measures how each wall works in conjunction with the others towards the goal of limiting heat transfer. The current metrics for PCM wall effectiveness looks at how well individual walls are at reducing heat transfer, but these measures do not consider the synergy of the walls with each other. In other words, the current measures do not consider if all walls are working together to attain the main goal of keeping heat transfer close to zero. Studying the synergy of the walls could reveal if there is a more optimal combination of walls, some retrofitted with PCM and some not, that could lead to more energy efficient buildings.

METHODOLOGY

Data acquisition

The data used in this study was collected in a previous study at the University of Kansas in Lawrence, Kansas [25]. Briefly, two test houses (Figure 3) were constructed using typical North American construction practices (Figure 4). One house was constructed as the control house and did not contain any enhancement from PCMs. The second house, the PCM house, was constructed with PCM pouches embedded within the wall insulation. Paraffin PCM (n-Octadecane) (Tm (K) = 301.2; Cp (J/kg*K) = 2150 (Solid-phase), 2180 (Liquid phase); k (W/m*K) = 0.358 (Solid-phase), 0.152 (Liquid phase) [27]) was encapsulated in reflective foil PCM pouches and chosen for its ideal properties and cost effectiveness (Figure 5) [25]. The houses were both outfitted with a south-facing window, chilled water cooler, and asphalt shingles and were insulated with a fiberglass and cellulose mixture [25].

Data on heat transfer was collected from the four cardinal orientations of the homes (North, East, South, and West) in a 3x3 grid pattern (Figure 6) [25]. Data was collected every thirty minutes over two days in September. The experiment collected temperature, relative humidity, and heat flux over the course of the test period utilizing Type T thermocouples, relative humidity transducers, and thermal flux meters respectively [25]. The sensors were attached directly to the walls on both the inside and the outside of the wall in a three-by-three grid pattern. All the data is available for all cardinal directions but for this study only heat fluxes were used.

Data Analysis

The analysis was run using seven measures, including heat flux reduction, time delays, averages of the heat flux, and standard deviation of the heat flux, to fully understand the impacts of incorporating PCM into homes. Reducing heat flux means reducing the flow of energy, or heat in this case, in and out of the building to help reduce the wear and tear on HVAC systems. Time delays work by utilizing the heat storing capacities of PCMs to delay when the heat begins to infiltrate the living space. This delay, called a time delay, shrinks the positive heat flux curve (heat entering the living space), which also delays when the positive heat flux first occurs. The time delays result in reduced stress on HVAC equipment, reduced energy cost, and a reduced maximum heat flux. The last two metrics are the typical averages and standard deviations used in statistics, which measured how close to zero each simulation could get. A heat flux of zero is the ideal condition because it indicates that there is no loss or gain of heat for the house.

For all analyses, MATLAB R2021a (MathWorks, MA) was used. First, fourteen test houses were simulated using the experimental data previously collected. Previous data covered a control home and a home with PCM in all walls. The fourteen simulated houses were created using a sequence of four binary numbers, where a 0 equated to a control wall and a 1 equated to a PCM wall. Using this numbering system, the control home can be designated 0000, whereas the home with PCM in all walls can

be desig nated as 1111. The order of the numbers in the four-digit combination corresponded to the cardinal directions of the walls: west, south, east, and north. For example, the simulated test home 5 corresponded to the binary combination 0101, which translates to a simulated house with control walls (no PCMs) for the west and east wall, and PCM walls for the south and north walls.

For each of the simulated (14) and tested (2) houses, the previous seven measures were used to gauge the effectiveness and synergy of PCM with different simulated wall configurations. Before extracting the measures, the heat fluxes for the four walls were added together to create one heat flux curve to simplify the analysis and directly compare the houses rather than individual walls. For each house and day, the following measures were extracted: maximum heat flux, total heat flux, time delays (start of positive heat flux, peak time, and end of positive heat flux), average heat flux, and the standard deviation. The first five measures are the most common measures used by researchers working on the effectiveness of PCMs, and the last two were added to determine how close the simulations were to the ideal heat flux scenario, which would be zero heat flux.

Using the two experimental and the fourteen simulated homes, the contribution of each wall towards reducing heat transfer and keeping it close to zero was determined. To measure a wall’s contribution, the percent difference between the control house and the measured value was found by taking a wall combination and subtracting it from an identical wall configuration differing only by omission of the wall of interest. For example, if the wall of interest was the northern wall and the home combination was 0011 (WSEN), the percent difference for each of the extracted measures was (0011-0010)/0010 (i.e., comparing it to a home identical except for lacking PCM in the northern wall). Using this method in all combinations where the north wall had PCM, the wall’s contribution was quantified. This process was repeated for the four walls and for each of the seven measures, allowing us to understand in detail how particular walls contributed to the simulated heat flow in or out of the home.

RESULTS

Heat flux heat map

The graphic above depicts the heat flux for each day using a heat map to show the heating periods throughout the day. Some simulations experienced two heating periods, heating both in the morning hours and during afternoon period (i.e., the typical heating period). The eight simulations above that experienced two heating periods all lacked a PCM wall in the eastern direction. Similarly, the eight simulations containing an eastern PCM wall only had one heating period (the afternoon period), and the addition of the eastern wall helped reduce the overall heating period. Furthermore, an eastern PCM wall also showed heating occurring later in the day compared to other simulations without an eastern PCM wall. Additional investigation reveals that the

western wall had a similar effect when retrofitted with PCMs, but it influenced the back half of the heating curve (late afternoon) rather than the beginning (morning). Additionally, the southern wall when outfitted with PCMs was observed to lower the peak heat flux values more than other walls when added to simulations. Overall, the heat map revealed that by adding more PCM walls to a simulation, the peaks could be reduced and the home could experience more consistent temperatures. This result was expected, but additional insights arise in evaluating specific measurements.

Graphs of the seven measures

The figure below depicts the seven measures in a graphical manner, starting with the peak heat flux and continuing to time delays, total heat, average heat flux, and heat flux standard deviation. Each graph is set up the same way, showing the results for both test days with the house simulation number on the x-axis and the unit measure on the y-axis. The x-axis starts with the control house (simulation 0) and finishes with the full PCM house (simulation 15). The final graph represents the number of walls in each simulation, which shows an inverse trend compared to the heat flux measurements. Further detail is given on the individual measures below.

Maximum heat flux

Maximum heat flux refers to the peak heat flux record for each simulation during each day. One of the main objectives of adding PCMs to wall production is to lower the peak heat flux homes experience during the day. Both days followed the same general trend downward as more PCMs were added with only small deviations occurring due to differences in temperature and weather conditions. The graph below represents each of the max heat fluxes for each simulation during each test day.

As more PCMs were added to each simulation the maximum heat flux decreased; however, the graph does not show a steady decrease in maximum heat flux. This phenomenon can be explained by two ideas. Firstly, simulations rotated between one, two and three PCM walls until simulation 15 (refer to Figure 7 for number of PCM walls per simulation), which would affect the results, and secondly, the walls with PCMs also alternated between west, south, east, and north with each wall contributing differently to the main objective. Moreover, this trend is repeated in the other graphs depicting heat flux data. Because the x-axis does not represent a simple linear increase in PCM but rather these variations, the trend line of decreasing heat flux is not straight.

With this in mind, a few data points still showed intriguing results. The first few data points of interest were simulations 1 and 2. Though their results did not decrease significantly from the control house, an interesting phenomenon occurred within the simulations. Both simulations had only one PCM wall, but the results for each simulation were surprisingly different. Simulation 2 (0010) had a peak result that was like

the control house’s peak even though it contained a PCM wall. Meanwhile, simulation 1 (0001) had a peak that was less than both the control house and simulation 2. A similar occurrence happened on the opposite side of the spectrum, leading to a more positive result. Simulation 13 (1101) had a result that was comparable to the full PCM house, whereas simulation 14 (1110) had a higher result than both simulation 13 and

the PCM house. The only difference in these two instances were which walls had PCMs incorporated into them which implies the potential existence of synergy between walls.

Time delays

Time delays deal with the shifting of heating load away from peak load times (typical in the early to midafternoon) so that homeowners can utilizes the cheaper energy prices offered in later parts of the day. Time delays are achieved by reducing the heating

period and delaying when heat begins to enter the building. However, a time delay can also affect when the peak heat flux occurs or when the house stops gaining heat. Time delays in any case save money and reduce energy consumption. Regarding the peak heat flux time delays, only the first day showed any evidence of shifting the peak time away from typical peak times. Furthermore, only simulations with two or more PCMs achieved any delay for the peak heat flux.

Start time delays are the most common and easiest to achieve with the use of PCMs. Despite this, results showed that to achieve any sort of significant delay required the use of two or more PCM walls. Similarly, like most of the measures in this study, the addition of more PCM walls resulted in better results overall. Interestingly, the start

time delays were one of the only measures to have a significant and noticeable difference between day one and day two.

The first day saw simulations 6 (0110), 7 (0111), and 14 (1110) registering results similar to the full PCM house though not utilizing PCM walls in every wall. The three simulations mentioned contained more than two PCM walls and always had PCMs in the Southern and Eastern wall. For day two, more simulations registered positive results. Simulations 2 through 7 and 10 through 14 had very similar delays to one another and to the full PCM house. Similar to the first day, these simulations contained either an Eastern wall or a combination of a Western and Southern wall.

The final time delay evaluated was the end time delay, or when the house was no longer gaining heat. Unlike the start time delay, which pushes the start of heating back, end time delay pushes the end of heating forward. In other words, the house will stop gaining heat sooner and begin the cooling process sooner. End delays had a steady rise across the simulations has more PCMs were added to each test house. Simulation 8 (1000), performed as well as the control house even though the simulation contained a PCM wall. Typically, the most effective test homes were those that utilized three or more PCMs retrofitted into the walls. In this study, simulations 7 (0111), 13 (1101), and 14 (1110) had results comparable in end time delays to the full PCM house during the first test day. The same simulations also had very good performances during the second day of testing; however, the results during day two were not as impressive as day one.

Total heat

Total heat was found by taking the integral across all positive heat fluxes for each day. The integral allowed for heat flux to be transformed into heat entering per square foot.

This allowed determination of the total heat entering during a day’s heating period. Due to wall combinations, some house experienced a morning heating period and an afternoon heating period, but for research purposes, any positive heat flux was used for the integral’s results.

In previous results, adding more PCMs helped reduce the measured value, in this case heat entering the building. From control house to full PCM house, results show an almost twenty-four [btu/ft^2] reduction in heat entering the building for an entire heating period. Simulations performing the best usually contained a western and southern wall or a western and eastern wall. Not significant outliers were found within under these measuring parameters.

Average heat flux

Averages were gathered by summing the entire test day and averaging the heat flux values for each simulation. In every case, the simulations spend most of the time experiencing negative heat fluxes, resulting in every simulation having a negative average. In this study’s case, negative heat flux represents heat flowing out of the built and into the natural environment. Though heat is being lost the majority of the time, the heat gained during the heating period has a larger impact on indoor environment than the heat lost during the cooling period.

The addition of more PCMs resulted in a lower average heat flux and thus was more likely to reverse the flow of heat. The simulations that produced the lowest averages were those with three PCMs. With this in mind, simulations 7 (0111) and simulation 14 (1110) produced averages comparable to the full PCM house without having to utilize four PCM walls. Furthermore, if simulations did not employ three PCM walls, utilizing an eastern PCM wall or a combination containing the western and southern PCM wall would result in a lower heat flux average like houses with three or more PCM walls.

Standard deviation

Standard deviation, like average, compared the data for the entire day and gauged its consistency throughout the day. For this measure, a value close to zero meant more consistent indoor temperatures. It is important to note that a low standard deviation does not translate to a lower heat flux but rather that the heat flux stays at a more consistent value. Consistency is key in reducing the stress on HVACs and reducing energy consumption.

Again, the addition of more PCMs resulted in a more positive result for the measure. In general, having three PCM walls meant a result comparable to the full PCM house, but simulation 7 (0111) did not perform as well as its three PCM simulations counterparts. Upon further investigation, the combinations of walls revealed that simulation 7 lacked a western facing wall.

Quantification of wall contributions (non-time delay measures)

Figure 17 depicts the wall contribution for each individual wall across the four measures without time. The walls are shown individually starting with the west wall on the left followed by the south, east and north walls. From the figure, the west wall (furthest left) contributed most to the reduction of the peak heat flux and the standard deviation values of the home. In both these measures, the southern wall contributed the second most to the aforementioned measures. The east facing wall, however, contributed the most to the heat flux averages, or in other words helped to reduce the average heat fluxes, and again the southern wall followed behind being the second largest contributor. For the last measure, total heat, the west, south, and east facing walls all had comparable results to one another. The northern wall made little contribution to the main goal of the measures usually contributing the least or second-to-least.

Wall contribution (time delays)

Like the last figure, Figure 18 depicts the individual walls and their contributions to the time delays for the start, peak and end of the heat flux curve. Again, the figure starts with the west wall and finishes with the north wall. The contribution of having PCM in specific walls to energy efficiency was most noticeable in delays to the start of the heating periods of each day. These delays were led by the southern wall and eastern wall, respectively. Little to no contribution was seen by individual walls for peak time delays and end time delays. Walls were unable to effectively delay the timing of heating on their own and often required the combination of multiple PCM walls to achieve a significant and meaningful delay.

DISCUSSION

Synergistic trends

The research presented simulated fourteen unique test houses by alternating nonPCM and PCM wall combinations. One of the goals of this study was to determine if there existed a synergistic trend between walls, and though the results were inconclusive, some promising patterns emerged that imply the existence of synergy between specific walls. Performance for each measure was heavily influenced by the number of PCMs used and the location of the PCMs in the simulated house. Simulations had varied results across the board, with some performing well in one measure but poor in another measure. Through analysis of the results, patterns of synergy emerged among wall combinations and their performance in specific measures. Each measure saw different simulations performing better, which supports the idea that a synergy exists between certain walls for certain measures, summarized below.

Max heat flux

Some simulations, even though they contained a PCM wall, performed similarly to the control house or worse than its counterparts. Simulations with the eastern wall resulted in a higher peak fall compared to simulations with a similar wall combination. Logically, this does not make sense: with the sun rising in the east, it is assumed that the eastern wall would receive the most sunning; however, due to the reheating of the earth’s surface in the morning, the heating process does not contribute as much to the building as it does when the earth’s surface is sufficiently heated. Furthermore, simulations with the southward or westward facing wall did see significant reductions in the maximum heat flux value.

Time delays

Time delays provided the least significant results across the board. Overall, it was difficult to find a trend among the results, and often the data revealed no significant patterns. Delaying the peak, start, and end of the heat flux is imperative for achieving maximum savings. A delay in any of these can shift the curve to access a cheaper energy and shorten the time the house is experiencing heat gained. Achieving a significant delay for the timing of when the peak heat flux occurs is one of the most difficult yet most beneficial time delays. A delay in the peak can move the heaviest loading time from the most expensive period for energy cost, which allows for consumers to access cheaper energy. Though no individual wall contributed directly to a significant peak delay, using a combination of PCM walls, usually including three or more, would directly result in a peak time delay.

Like the peak time delay, having a start time delay could result in consumers accessing cheaper energy. Achieving the most significant time delay required reducing the heat flux gained in the early part of the days. Logically, including the eastern wall should be the best option, but the results showed significant delays in simulations that included the western and southern wall retrofitted with PCMs. These combinations can reduce the heat gained by the building during the morning periods, which reduces the heat entering the living space. The reduction of heat flux in the morning hours shortens the overall positive heat flux curve thus requiring less HVAC intervention to keep indoor temperatures stable.

Delaying the end of the heat flux curve worked identically to the start delay except reversed. For significant end time delays, the western wall would be utilized to capture the warm afternoon sun’s heat. Additionally, like the peak time delays, utilizing three or more PCM walls typically resulted in more favorable time delays. Furthermore, like the start time delays, simulations containing the west south PCM wall combination resulted in more positive time delays. Using time delays can help to shrink the amount of time heat is entering the building and moves the peak to a part of the day when the grid is under less strain resulting in cheaper energy prices.

Total heat

Prioritizing walls that will receive the most sunning throughout the day is ideal for reducing the total heat entering the building, but the sun’s intensity should also be considered when thinking about adding a PCM wall. For instance, the west wall will receive the more intense afternoon sun, but the eastern facing wall will receive sunning for longer periods of time. The results showed a synergistic trend between the west, east, and south facing walls and their ability to reduce the amount of heat entering the simulated home. For these reasons, ensuring that a combination of the aforementioned walls will result in more favorable heat results.

Average heat flux and standard deviation

Most of the measures strive at reducing the heat flux as much as possible, and though heat flux will never truly be stabilized at zero, due to infiltration, or the phenomena of air seeping through existing crevices in the structure. Standard deviation and average heat flux aim to achieve a heat flux of zero despite the issue of infiltration. The other measures look at only a portion of the data, typically the heating period during the day, but average heat flux and standard deviation consider the whole data set. For the measures to register positive results, the data needs to be as close to zero as possible. A near-zero average means heat is not entering or escaping the home, which translates to constancy in indoor air temperatures. Similarly, standard deviation measures strive to be as close to zero as possible.

Having a positive or negative average heat flux describes the direction of heat flow the simulation experienced the most over a twenty-four-hour period. A positive average heat flux indicates the heat is flowing into the house, whereas a negative heat flux indicates that heat is flowing out of the house. Initially, the simulations with little to no PCM involvement had the best averages (averages closest to zero but still negative) but considering how the averages were taken this can be easily explained. Simulations without PCMs experienced more extreme highs than simulations with PCMs, so the extreme peaks helped to pull the average up closer to zero resulting in skewed results. To combat these ambiguous results, focusing on a balance between infiltrating and escaping air will help keep heat flux averages close to zero.

Standard deviation works identically to average heat fluxes. Though the standard deviation results are positive, it is ideal for the results to be as close to zero as possible. Results registering close to zero indicate indoor air temperatures are remaining more consistent. Attaining zero for standard deviation translates into zero heat loss or gained.

Overall, the goal of finding a synergistic measure between walls was a partial success. Trends began to become clearer as the data was analyzed. When broken down by simulations, certain wall combinations begin to appear more frequently and hint at a synergistic trend with that combination. For more concrete evidence of a synergistic

trend, more data needs to be analyzed over a longer period to show the trend continues beyond the two days used in this study.

Recommendations

The most important thing to consider is the purpose of adding PCM walls to a structure. Is reducing heat flux the main goal, achieving a time delay, having consistent indoor air temperatures, or a combination of these? The most obvious answer is to use the full PCM house to achieve the best case for all scenarios, but PCMs are expensive and there may be a more cost-efficient method for achieving the same results. Simulations with one wall performed similar to the control house, so recommending and utilizing a single PCM wall would be a waste of resources. Two-walled and three-walled simulations had resulted most similar to the full PCM house. The best two-walled simulation was simulation 6, which corresponded to (0110) Other twowalled simulations had lower results than the control house, but the results were not significant enough to warrant implementation. For three-walled simulations, simulations 13 and 14, which corresponded to (1101) and (1110), respectively, had the best combinations.

Wall contribution

The results, as discussed in the previous section, clearly showed the contributions of each wall for each of the measures. This portion of the study can be considered a success because walls can now be recommended with some degree of confidence based on their contribution to the goal. Contribution can also be used to identify synergistic trends. Where one wall may lack in a measure, another wall could be exceptional in it. By combining these two walls together a more powerful combinations can be attained. The following section pertains to recommendations based on a wall’s contribution to a measure and its synergy with other walls.

Based on contributions and overall results, the south facing wall performed the best or second-best in all measures. Additionally, the western wall also proved very positive and should be highly considered when retrofitting buildings with PCMs. The eastern wall also had comparable results to the western and southern walls. The northern wall, however, contributed little to most measures and could be considered to be left out with little to no noticeable negative effects. Some results showed no or little contribution from a specific wall, yet for the measures overall the results varied widely. This phenomenon points to the need of walls being used in conjunction and a synergistic connection between walls. One of the most notable occurrences of this was during time delays, especially for peak time delays. Though there are recorded occurrences of time delays occurring, significant results were only attained when multiple walls were used together.

CONCLUSION

The aim of this study was to determine synergistic trends between individual walls and each wall’s contributions for individual measures. Because of the strong results from the wall contribution study, the existence of wall synergistic trends likely exists between walls. Some of the walls with the strongest synergy included the west, south and east wall. When in combination with one another, they performed extremely well and simulation 14, which contained all the three walls, had results comparable to the full PCM house. Wall contributions strengthened the previous results by showing the strengths of individual walls. From the wall contribution study, the western and southern facing walls contributed the most in the seven measures studied, and they were the walls that showed the most synergy. When these two walls were utilized within a simulation, that simulation performed the best. (Refer to simulations 12, 13, and 14). Therefore, utilizing wall contribution and synergistic measures can be used to advise the best combination of PCM wall to use. Based on the recommendations, investors can use less PCM to get the same results, which can save money and energy.

Further research

The introduction new measuring techniques and simulations would allow further and more in-depth research on new and existing data. Furthermore, the concept of simulations can be applied to other data including wall temperatures and wall humidity. The simulated house also gives insight on unique wall combinations to consider testing in real life applications. Researchers should also consider running longer studies that encompass multiple seasons. Finally, a comprehensive cost analysis for wall inclusion could be beneficial for determining best practices for incorporating PCM walls into structures.

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Police Officers’ Perceptions Regarding their Interactions with the Disabled in Kankakee County

ACKNOWLEDGEMENTS

First, I want to thank my Lord and Savior Jesus Christ for dying on the cross that I might find salvation and hope in Him. I am also thankful that He gave me a heart for service and a passion to help those who are neglected, which has encouraged me to complete such a project. I thank Him for the skills and abilities He has given me to accomplish good things.

I would like to thank my research mentor, Dr. Shelly Stroud, for her continued support, encouragement, and assistance throughout the course of this project and for joyfully taking on the significant task of mentoring me. Without her valuable insight, continued excitement, and professional connections, I do not think I could have persevered through the setbacks.

This study would not have been possible without the gracious participation of the police departments in Kankakee County. I would like to thank them for the generosity of giving their time and for their sincere interest in improving the lives of those in their communities. I appreciate the willingness of the participating officers to be open and honest in the survey, with the goal of bettering Kankakee County.

In addition, my success in completing this project is partially due to the help of Taylor Zeck, a student at Olivet Nazarene University who helped me navigate

the statistical analysis of my results. This included helping me determine the tests I needed to use, teaching me to run and check the tests myself, and proofreading my interpretation of those test results to ensure I accurately depicted my research.

I also want to acknowledge the role of the Honors Program and its faculty in my completion of this study. Had the program itself not challenged me to complete such a project, I would not have known I had the capability to do so. In addition, the direction and grace given by the Honors faculty helped me navigate such an intimidating task with the assurance that I had the support I needed to succeed.

I truly must thank my parents, Tim and Gayla English, who have continuously loved and invested in me and who have equipped me to accomplish all I have achieved today. I would be lost without them and am forever grateful for everything they have bestowed upon me. More specifically, I would like to thank my mom for the countless time she spent listening to me, brainstorming ideas, praying with me, encouraging me, reading my work, and proofreading my submissions, all of which motivated me and helped me to refine my project.

Finally, I want to thank my family, friends, and classmates for their support. Even in the simplest ways, they kept me moving forward. They gave me relief in the midst of stress and reminded me that though I was quite capable of completing this study, my worth is not tied to finishing this project. My worth is founded in Christ, and it is by His goodness that I can complete such works.

ABSTRACT

Background

Previous research shows the rate of crime against people with disabilities is significantly higher than the general population. Despite this, gaps in the training and resources for officers to assist those with disabilities may exist. Eadens et al. (2008) explored this issue by evaluating officer attitudes towards intellectual disabilities. Kankakee County has a significant disabled population, and Illinois is ranked very low in the improvement of related policies, making this a valuable area of interest.

Methods

This study utilized the modified version of the Social Distance Questionnaire (SDQ) used by Eadens et al. (2008), which is both qualitative and quantitative. The survey was sent out to the five police departments in Kankakee County, and it received 37 responses. Data was coded in Microsoft Excel, and statistical tests were run through R Studio.

Results

Though distributions varied, the resulting mean scores trended toward the higher end of the SDQ scale, indicating more positive attitudes toward people with disabilities. Additionally, the evaluation of training and average survey scores as grouped by department suggested a positive correlation. However, due to the sample size these and other results did not meet the threshold of statistical significance.

Conclusions

Kankakee County’s participating officers appeared mostly to have positive attitudes towards intellectual disabilities. A positive correlation may exist between the officers’ scores and the amount of disability training they have received. To determine this, a study with a larger sample must be conducted.

Keywords: criminal justice, law enforcement, police, disabilities, intellectual disabilities, perceptions

LITERATURE REVIEW

Law enforcement and the community

In many service careers, people are taught how to handle situations based on who they are helping and the needs of that person. This is especially evident in the field of law enforcement, in which a person’s capacity to understand and willingness to cooperate can have an immediate effect on a situation and its outcome. In an attempt to better meet the needs of the people they are helping, many law enforcement

officials have recently shifted to a model of community policing, which seeks to improve communities through close relationships between officers and citizens. Community policing has three main components: proactively implementing problem solving, engaging with community organizations, and reorganizing institutional rules (Schuck, 2017). This model encourages officers to improve their communication and engagement with the community through good interpersonal skills. Additionally, it not only promotes collaboration between officers and the public, but also works to increase accountability and to “dismantle symbolic and institutional barriers” (Cheng, 2019).

Though officers are trained quite extensively and this approach to policing appears to be making a positive change in creating safe and comfortable communities, there is still a concerning gap in training and resources available to officers when it comes to handling situations involving mental and intellectual disabilities (Gardner, Campbell, and Westdal, 2019).

Law enforcement and the disabled

According to the Americans with Disabilities Amendment Act of 2008, a disability is “a physical or mental impairment that substantially limits one or more major life activities” of a person (Equal Opportunity for Individuals with Disabilities, 2008). Whether a disability is physical or mental, it affects a person’s way of life and his or her environment. Due to the circumstances and vulnerability of the disabled, they are often more susceptible to crimes against them, especially interpersonal violence (IPV), which is often committed by someone close to them, such as a caregiver (Child, Oschwald, Curry, Hughes, Powers, 2011). In fact, the rate of violent crime against those with disabilities is more than three times the rate for those without disabilities (Bureau of Justice Statistics, 2017). Though the number of disabled victims is prevalent, officers still struggle to provide them with the assistance they need.

Research by Eadens et al. (2016) helped to highlight this gap. Their project consisted of 157 officers from the Southeastern U.S. who completed a modified version of the Social Distance Questionnaire regarding their interactions with the mentally disabled. The findings of these surveys indicated that although most officers showed a willingness to socially interact with the intellectually disabled, a majority of them had very little, if any, training on how to handle calls and crimes involving people with such disabilities (Eadens et al., 2016).

Another study with a similar goal, completed by Hughes et al. (2016), created focus groups of twenty-five police officers in the Northwestern U.S. The researchers discovered seventeen themes related to officer experience handling violence against people with disabilities, which divided into three categories: 1) the situational context, 2) multiple challenges, and 3) investigational and prosecutorial difficulties. Amidst officer responses, there was a commonality indicating that officers expressed more frustration with the system, its

policies, and its training, than they did with the victims themselves (Hughes et al., 2016). This reveals not only the prevalence of a lack of training but also a hopeful insight that officers view crime victims as people who need help, regardless of their disability.

Though officer training for working with the disabled seems to have been neglected, the addition of specific training has shown promising results. One study by Gardener, Campbell, and Westdal (2019) interviewed seventy-two officers and found that the nineteen participants who had received training about autism felt more adequately prepared for such calls than the fifty-three participants without training. Another study by Scantlebury et al. (2017) provided an extra day of mental health training to police officers in England. Though the training did not reduce the number of incidents reported within the study period, they found that the set of officers who received the extra training were much more likely to accurately mark incidents with the necessary mental health tags (Scantlebury et al., 2017).

In spite of these positive findings, however, Oschwald et al. (2011) discovered that, of the 133 U.S. police departments that they surveyed, a majority did not have protocols or training in place for serving disabled crime victims and some departments even lacked a formal definition of disability. Effective training on handling disabled victims and offenders is incredibly important because of the extra barriers that exist in situations that include the disabled. Research done by Child et al. (2011) involved interviewing disabled adults who had reported interpersonal violence to police. Through these interviews, the researchers found substantial, additional barriers beyond what is normally seen in officer-victim interactions. Some of the most prominent barriers identified were that victims were afraid to identify a disability, had previously been blamed for crimes against them, felt that their credibility was questioned by officers, and faced communication and accommodation difficulties. These barriers and a lack of training on how to overcome them make handling cases of crimes involving the intellectually disabled more difficult and, as discovered by Koskela, Pettit, and Drennan (2016), likely lead to the significant underreporting of such crimes.

Kankakee County

Though it is not a universal slogan for all police, a motto that can be found at almost any police department is “To Protect and Serve.” By purposely being so open-ended, this saying helps officers recognize their duty to protect and serve not just specific members of their community but all members as best they can. This undoubtedly includes the mentally and intellectually disabled, who frequently need extra assistance but often do not receive it. Though officers may want to help, they commonly lack the training to do so. Limited resources and insufficient training impair law enforcement interactions with the disabled which likely affects their ability to find justice. When these issues arise, victims with disabilities are often discouraged from reporting crimes against them (Child et al., 2011). This leaves the offenders untouched and thus affects everyone else in the community.

Although this impacts law enforcement in general, it has a specific impact on the people in Kankakee County. According to the Community Health Status Assessment for Kankakee County in 2018, 16.78% of the population was listed as having a disability, which is higher than Illinois’s 10.73% (CHSA, 2018). To put this in perspective, 12.6% of the U.S. population overall was listed as having a disability in 2020 (United States Census Bureau, 2020). Though Illinois has such a significant disabled population, a report by the American Network of Community Options and Resources in 2019, noted that the state had “taken no significant steps to improve policies” that better the lives of the intellectually and developmentally disabled (ANCOR, 2019). This, the report argues, caused Illinois to rank 44th among all states in efforts to serve intellectually and developmentally disabled individuals by The Case for Inclusion (ANCOR, 2019).

With Illinois being ranked so poorly in its assistance to the disabled, it is likely that there is a need for the state to re-examine its policies, and with the disabled population of Kankakee County being so high, the area provides a good sample that offers ample opportunity for research and improvement.

This very need and opportunity led to the following study, which investigated the perceptions by members of Kankakee County law enforcement regarding their interactions with mentally and intellectually disabled members of the community, as well as explored whether gaps exist in their training for handling such cases.

METHODOLOGY

Participants

Participants of this study included thirty-seven police officers in Kankakee County. They consisted of officers from Kankakee Police Department, Bradley Police Department, Bourbonnais Police Department, Manteno Police Department, and Kankakee County Sheriff. In the Results section, Table 1 shows the number of participants from each department and Tables 2 through 4 illustrate the remaining demographics of position, gender, and race amongst respondents. There were initially thirty-nine survey responses, but because one of the responders was a public safety officer for Kankakee Community College and not a sworn officer in one of the targeted departments, that response was not included in the analysis. Additionally, a second participant was removed for not having met the response criteria outlined in the Data Analysis portion to follow. Demographic data was also collected, which included information such as years of experience, race, and position of the officer. These factors are discussed in further detail in the Results section.

Materials

This study was conducted as a survey of the participants, using a modified version of the Social Distance Questionnaire (SDQ). This tool, which was adjusted and utilized by Eadens et al. (2008), examines officer perceptions of disabilities in four sections:

1) knowledge, 2) social willingness, 3) contact, and 4) affect. The first domain, knowledge, pertains to whether participants have accurate knowledge about people with disabilities, including an understanding of the indicators of individual disabilities, such as intellectual disabilities. The next domain, social willingness, indicates an individual’s

inclination to interact with people with disabilities. The third domain, contact, solicits information about the respondents’ actual interactions with people with disabilities. The final domain, affect, probes the feelings of participants towards people with disabilities. The domains of knowledge and contact are considered objective, while affect and social willingness are more subjective.

For the purposes of this study, Eadens’ 2008 survey was shortened to forty questions to increase its approachability, and the terminology was updated. The full list of quantitative questions used for this study is located in Appendix D. In addition to the quantitative survey questions, all of which were answered on a Likert scale, the researchers added five qualitative questions, which were included in this study as well. Those questions, which were created to better assess officer understanding and training, are listed in Appendix C.

Procedures

Before this research was conducted, a chief, deputy chief, or lieutenant was contacted at each department to introduce them to the project and ask about participation. Each person responded with interest in the study and agreed to have their officers participate in it once it was approved by the Institutional Review Board.

The survey was created in Microsoft Forms and distributed to the police departments via each contact person’s email. The contacts then dispersed the survey to individual officers through their internal email lists. The first page of the survey consisted of the Informed Consent for the study, which is included in Appendix A. By reading the document and continuing with the study, they provided their consent to participate. They were then given the option to enter demographic information, which included elements such as years of experience and department, but there was no request for the individuals’ names. These demographic questions are listed in Appendix B. They were then prompted to answer the five qualitative questions and forty quantitative questions before submitting all their responses. The officers were given a three-week time frame in which they could complete the study before the form would close. As the surveys were completed, their responses were anonymously submitted to the researcher, who compiled the results for analysis.

Data analysis

The initial step of data analysis came in assigning numeric values to the survey responses. This was first done for the quantitative questions. Because the Likert scale with which answers were given contained four options and no neutral choice, the responses were coded one through four. More specifically, I disagree strongly equaled one, I disagree a little equaled two, I agree a little equaled three, and I agree strongly equaled four. This was the coding used on a majority of the quantitative survey questions. However, for some of the questions, a higher level of disagreement actually

indicated a positive, rather than negative, response. For these questions, the coding was inverted, meaning that I disagree strongly equaled four, I disagree a little equaled three, I agree a little equaled two, and I agree strongly equaled one. The inverted questions were numbers 1, 3, 6, 9, 12, 16, 20, 23, 24, 30, and 37. These questions are noted in Appendix D.

Coding the qualitative questions to numeric values was a more complex process. Following the methods used by Eadens et al. (2008), the responses were classified into categories and then themes based on each specific question. The categories referred to specific types of information in the response; those designated categories fit into themes that indicated whether the participant had the desired level of the intended trait. For example, in the Knowledge domain, response categories included “n/a,” “speech difficulties,” “physical characteristics,” and “cognitive characteristics.” These were then grouped into the themes of “no knowledge,” “some knowledge,” and “accurate knowledge.” The researcher read through the participant answers and noted the theme that best aligned with each, assigning the designated value for that theme. These themes are outlined and numbered by question in Appendix F.

Across both the quantitative and qualitative aspects, each question of the survey correlated to a particular domain (excluding the question about training). These domains, which are defined in the materials section of the methodology, are Knowledge, Social Willingness, Contact, and Affect. The domains of each question on the survey are illustrated in Appendix E.

Excluded responses

When the participants submitted their responses to the survey, some neglected to answer some of the questions. In order to make the analysis and results as accurate as possible, there was a threshold for the number of questions that could be unanswered before an individual’s responses were omitted. If a response was missing the demographics section, it was left blank, and the participant’s information was not used in analyses involving the demographics. If it was missing in the quantitative section of the survey, the following rule was applied: if four or more of the forty questions were unanswered, that participant was excluded from the results. If there were less than four questions blank, the participant’s average score of that domain was entered for the missing value. This rule was applied to all thirty-nine respondents and resulted in the removal of one participant. Besides that removal, three participants were missing a response to one question, and one participant was missing a response to two questions. A similar rule was applied to blank responses in the qualitative section of questions. If four or more questions were unanswered, the participant’s responses in that section were excluded from the quantitative-qualitative comparisons. However, if fewer than four questions were unanswered, then each blank response was coded as “I don’t know,” which equaled one in the analysis. In addition to these criteria, one of the participants was a public safety officer from

Kankakee Community College, which did not fit the desired participant criteria, so that set of responses were excluded as well. Thus, there were thirty-seven responses analyzed in total.

Analysis tools

The survey responses were first collected in a Microsoft Excel spreadsheet, which offered the capability to perform basic functions and make initial observations. Excel was also used to code the survey responses so that they were represented as numeric values and ready for analysis. To assist with the data analysis, the researcher utilized R Studio, which is a development program that operates with the programming language R. It aids in the calculation of statistics and can be used to efficiently generate tables and graphs based on the designated data. For this study, the program was used for most of the statistical tests and to create the graphs that follow. In addition, the results garnered through the program were compared to the input data located in the spreadsheets to assure that the results were an accurate representation of the survey responses. In all relevant statistical tests, a p-value of ≤ 0.05 was used to determine significance.

RESULTS

Description of the sample Response rate

For the purposes of this study, the five police departments within Kankakee County were surveyed. This included Bourbonnais Police Department, Bradley Police Department, Manteno Police Department, Kankakee Police Department, and Kankakee County Sheriff’s Office. The rate of responses from each department are outlined in the tables above.

Participant demographics

In the demographics section, the survey respondents were asked whether they were a patrol officer or held another position. For those that designated a non-patrol position, they were given another blank in which to enter their role in the department. Such responses included Chief of Police, Investigations, Administration, Sergeant, Lieutenant, and Corrections, a number of which had duplicates. Table 2 lists the number of participants in patrol and other positions, as well as each group’s percentage of the whole.

From an examination of officers in both sets of positions, the years of experience ranged from one to thirty-five years. Additionally, the mean years of experience overall was twelve years.

The gender of the participants was generally representative of the police population, and thus in line with what the researcher expected. Table 3 illustrates the distribution of gender in respondents.

Similar to gender, the race of participants aligned with the researcher’s expectations and was generally representative of the police population. This is indicated in the fact that a majority of respondents were White/Caucasian, while a small number of respondents were other races. Table 4 illustrates the distribution of race in participants.

Summary of demographics

Of the thirty-seven officers who responded to the study, the greatest number of participants came from Kankakee Sheriff and Kankakee PD, followed by Manteno PD, Bradley PD, and Bourbonnais PD. A slight majority (59.46%) labeled themselves as patrol officers, with the remaining respondents indicating another position, and the average years of experience overall was twelve years. The gender and race of participants confirmed the researcher’s expectations and aligned with the perceived police population, with 86.5% being male and a majority (81.1%) identifying as White/Caucasian.

Findings

Perspectives by domain

The crux of this study was to determine the perspectives of officers in Kankakee County towards people with intellectual disabilities in the domains of knowledge, so cial willingness, contact, and affect. To analyze this, a univariate descriptive analysis was performed. This included evaluations of the score distribution for individuals in each subscale and in the SDQ overall, which is outlined in Table 5 below. An understanding of this data was aided by creating Figures 1 through 6, which illustrate the frequency of scores amongst the participants. The descriptive statistics for subscales show that the distribution of the average scores varied quite a bit by domain but that all of them consisted of scores in the higher range.

Gender and attitude

One interest in the examination of survey results was the correlation between an officer’s gender and his or her attitudes toward people with disabilities. The sample size, having thirty-two male respondents and five females, appears to be proportionally representative of the desired population. However, because the number of each gender is still so low, the results of analysis may not be indicative of the larger population. Despite this, these values were still investigated through independent samples t-tests, which determine whether two populations have equal means. In this case, the two populations were the male and female officers. The results of this analysis are outlined in Table 6. The independent samples t-test was used to examine the effect of gender on both the scores in individual domains and the overall attitudinal score. As illustrated in Table 6 above, because no test indicated a p value below 0.05, none of the tests were considered significant. This means that there is no indication that one gender scored

This figure shows that the average knowledge

This figure shows that the average contact score is somewhat skewed towards the higher scores.

This figure shows that the average affect score is skewed towards the higher scores, similar to the knowledge and contact histograms but with a unique distribution.

This figure shows that the average social willingness score is significantly skewed towards the higher scores, similar to that of the knowledge histogram.

This figure shows that the average total score on the Social Distance Questionnaire (SDQ), which indicates the attitudes towards people with intellectual disabilities, resembles the individual domain scores in that it is considerably skewed to the higher end of values.

The affect domain closely resembles the average overall attitudinal score. The mean knowledge score is slightly higher than the overall mean, whereas the contact scores are somewhat lower. Meanwhile, the average social willingness scores are significantly higher than the overall attitudinal scores.

significantly higher in a domain or overall score than the other. Thus, the null hypothesis that gender had no influence on an officer’s attitude towards those with disabilities could not be rejected.

Race and attitude

Another interest in the examination of survey results was the correlation between an officer’s race and his or her attitudes toward people with disabilities. Through the demographic questionnaire, the racial self-identification of the thirty-seven qualified participants totaled thirty White/Caucasian, four Black/African American, two Hispanic/ Latino, and one multiracial. Although these values appear representative of the Kankakee County officer population and a comparison of their scores was a point of curiosity, the low number of participants in each race might skew the test results. Thus, there were no statistical tests run on the correlation between race and survey scores.

Age, years of experience, and attitude

A consideration across all participants was the potential association between an officer’s age and years of experience would have on their scores in each domain and

overall attitudes towards those with disabilities. To address this, a Pearson ProductMoment correlation test was performed on these variables. Table 7 below illustrates the results of this analysis.

This table demonstrates that overall, there were no strong correlations between the police officers’ age and years of experience and their survey scores. However, there are some small positive correlations between age and knowledge, age and contact, age and affect, and age and total attitude score. There is also a small positive correlation between years of experience and affect. Though these values do indicate correlations, they meet the criteria so closely that it is difficult to draw a significant theme from them. The only large positive correlation is between age and years of experience, which is to mostly be expected.

Domain relationships

Because the officers’ domain scores are combined to determine their overall attitude scores, it is valuable to compare the domains and see how they relate to and correlate with one another. Thus, a Pearson correlation test was performed on the mean scores of

each domain in the pattern of a four-by-four matrix. Table 8 uses those results to illustrate the relationships between the various domains. It demonstrates that each domain is significantly related to the others. The lowest domain correlation was between knowledge and contact and the highest domain correlation was between contact and social willingness. Additionally, each domain had a similarly strong correlation with the total score, but the greatest correlation of those was the relationship between social willingness and the total.

Qualitative findings

Following the coding and analysis methods previously outlined, the qualitative questions were examined and grouped based on the categories and themes outlined in Appendix F. Frequency distributions were used to analyze the response category of each question, which is displayed in histograms, and its respective theme, which is displayed in tables that follow. These results are summarized below.

Knowledge domain frequency distribution. The first qualitative question addressed the knowledge domain by asking the question, “How do you know if someone with whom you are interacting has an intellectual disability?” Figure 7 shows the frequency distribution of the categories, and Table 9 indicates the frequency of responses in each theme.

Table 9 illustrates that most of the officers that participated in the study (81.1%) had either some or accurate knowledge of intellectual disabilities. This determination was based on the themes in Appendix F. The data trend of these results appears consistent with the quantitative knowledge results, but the scores are slightly more spread out.

Contact domain frequency distribution. The se cond qualitative question addressed the Contact domain by asking the question, “Please describe any personal experience you have had with a person who has an intellectual disability.” Figure 8 shows the frequency distribution of the categories, and Table 10 indicates the frequency of responses in each theme.

Table 10 illustrates that just over half of the officers that participated in the study (51.4%) had personal contact with people with mental disabilities, while the second largest result (37.8%) had no contact. This varies a bit from the quantitative results but not majorly so.

Affect domain frequency distribution. The third qualitative question addressed the Affect domain by asking the question, “Under what conditions would you adopt a child with an intellectual disability?” Figure 9 shows the frequency distribution of the categories, and Table 11 indicates the frequency of responses in each theme.

Table 11 illustrates that the personal affect of participants varied widely but that most officers (81%) had a neutral or positive personal affect towards people with

disabilities. However, the results in this section are not very similar to those represented in the quantitative questions.

Social willingness domain frequency distribution. The fourth qualitative question addressed the Social Willingness domain by giving the prompt, “If your significant other befriended a person with an intellectual disability, describe the kind of social events you would be willing to attend with your significant other and his/her new friend.” Figure 10 shows the frequency distribution of the categories, and Table 12 indicates the frequency of responses in each theme.

Table 12 illustrates that the majority of participating officers (70.3%) indicated positive social willingness to interact with people with disabilities in casual settings.

This is followed by a smaller percentage (21.6%) having minimal social willingness and only three respondents (8.1%) having negative social willingness. Though there are no higher mid-range values here, these results seem consistent in overall trend with the quantitative results. Together, they also show the greatest contrast between high and low participant scores.

Training frequency distribution. The fifth qualitative question did not address a specific domain but rather inquired about officer training by giving the prompt, “Please describe any previous disability training you have received.” Figure 11 shows the frequency distribution of the categories of training, and Table 13 indicates the frequency of responses in each theme.

Figure 11 and Table 13 illustrate that the participating officers have vastly differing levels of training, with 40.5% scoring as having disability-specific training and yet

45.9% scoring as having no disability training at all. This leaves a mere five respondents (13.5%) with the central position of having received minimal training.

Departmental findings

Though all five of the police departments involved in the survey reside in Kankakee County, they each have their differences in community makeup and policing approach, whether major or minor. For this reason, another point of investigation was a comparison of average scores and overall attitudes across departments to see whether a single department scored higher or lower than the others. Due to small sample sizes, most observations about a single department cannot be said to

represent the overall department. However, with nearly half (42.9%) of Manteno PD’s officers participating in the study, their scores have the potential to be more representative.

Quantitative survey results by department. After initial analysis, the quantitative survey results from the Likert scales were grouped by police department, and a mean departmental score was derived from the mean score of its affiliated participants in each subdomain and overall score. The results of this examination are outlined in Table 14 below.

The data in this table shows that across all five departments in Kankakee County, the participants in this study have relatively similar average scores in each domain and in overall attitude towards those with disabilities. Due to the small sample sizes of most departments, though, these values cannot be said to represent the score of the officer population at large in each department.

Qualitative survey results by department. As with the quantitative scores assessed, the survey results for the qualitative questions were grouped by police department, and a mean departmental score was derived from the mean score of its affiliated participants in each subdomain and overall score. The results of this examination are outlined in Table 15 below. Additionally, an average training score was determined in the same manner as the other departmental results.

The data in this table shows some more variance between the scores of each department than the quantitative averages did. Most notably, some departments differed by more than a whole point value in some subscales. However, these observations still retain the same concern that with such small sample sizes of some departments, these results cannot be said to represent the departmental scores as a whole. In addition, these results differ somewhat from those in Table 14, but that is partially to be expected considering these scores were based on singular questions, rather than multiple.

An important note when looking at Table 15 is that while the quantitative questions were all measured on a Likert scale with a maximum value of four, the qualitative questions depicted had varied scales. For example, the highest possible score in social willingness is a four, whereas the highest possible score in training is a six. To take these differences into consideration while looking at the table, see Appendix F.

Correlations between training and mean total scores. To address the study interest of whether training level is correlated with overall attitude, a Pearson Product-Moment Correlation test was performed on the mean training scores and mean total scores as they had been grouped by department. The results of this test, which assesses whether the relationship between variables is significant, are outlined in Table 16 below.

These results indicate that based on the averages grouped by department, there is a small positive correlation (0.15) between the mean training scores and mean quantitative survey scores, and there is a large positive correlation (0.61) between the mean training scores and mean qualitative survey scores. There is also an indication of a similarly large positive correlation when considering the average of both scores together (0.59). However, because the p values are well over 0.05, these observations are not statistically significant. Along with the total scores, there was an interest in running a Pearson test for the correlations between training and each subscale, but due to these results not being significant, those further tests were not completed.

DISCUSSION

This study evaluated officer attitudes towards people with intellectual disabilities in four main categories: Knowledge, Contact, Affect, and Social Willingness. Overall, the participating officers demonstrated relatively high scores in each domain. Every officer averaged higher than 50% (of a 4.0 maximum) on each scale, with a majority of respondents averaging higher than 3.0 on every scale except Contact. Though the mean domain scores were reasonably close to one another, the highest mean, which was about 3.5, was in the Social Willingness subscale, which illustrates a strong willingness

of the officers to interact with the intellectually disabled. These observations, paired with the fact that all officers scored similarly high in their overall averages, indicates a positive trend in officer attitudes toward those with intellectual disabilities. Even so, the fact that some officers earned much lower scores shows there is still room for improvement. In total, though these results contain generally high scores and seem similar to previously examined populations, a much larger sample would be needed to confirm these observations.

Due to the small sample size and the even smaller number of participants in the pertaining subgroups, the examination of the effects of gender on survey scores yielded no significant results, and an examination of the effects of race on scores was not performed. Although the analysis of the effects of age and years of experience on officer scores resulted in some small positive correlations, they were not large enough from which to draw any significant theme.

To aid an understanding of the individual scores and how a higher score in one area might influence the score in another area, an evaluation of these potential correlations was conducted. It found that all domains were significantly positively related to each other, meaning someone scoring high in one area might score high in another area based on the strength of the relationship between the two. This test found that among close similarities in correlation, the greatest positive relationship was found between Contact and Social Willingness, and Social Willingness appeared to have the greatest correlation with a participant’s total score.

When given the opportunity to give more open-ended responses to prompts from each domain in the study, officers appeared to have a much larger fluctuation in their scores. Despite the answers being more spread out, the trends of the qualitative results seem generally consistent with what was discovered in the quantitative section except for the scores in the Affect domain. One notable observation from the qualitative results is that in the Knowledge domain, though most participants had at least some knowledge of intellectual disabilities, less than one-third of them registered as having accurate knowledge of these disabilities. This suggests that there may be room for improvement in officer understanding of intellectual disabilities. In contrast, a key finding from the Social Willingness question demonstrated an overwhelmingly positive willingness to socially interact with those with intellectual disabilities, with only three officers indicating negative willingness. This determination is an encouraging indicator that the participating officers have positive attitudes towards these members of the community. It is important to note that these qualitative scores were drawn from singular questions, rather than as an average of multiple questions as was done in the quantitative section. However, due to the lack of restraint on participant responses to these questions, each person had the opportunity to answer them as fully and truthfully as possible, making it reasonable to view their contents as accurate for that individual. These conclusions, as well as the trends illustrated in the results of the quantitative

portion, appear to be fairly consistent with the study by Eadens et al. (2008), which demonstrates a similarity in perspectives as the officers previously studied as well as an apparent consistency of perspectives over time.

The qualitative inquiry of whether officers had received disability-focused training found vastly differing results among participants, with almost equal portions designating disability-specific training and no training at all. Though the sample was relatively small, this wide range of training responses indicates the potential room for growth in disability training for officers in Kankakee County.

By grouping respondent scores based on department, the quantitative results exhibited relatively similar average scores in each domain and the total, regardless of the department affiliation. If the sample had been more substantial, this may have indicated similar attitudes towards intellectual disabilities across departments. However, due to the low response rates, these results cannot be said to represent the departments as a whole. Additionally, the qualitative results exhibited more variance between the department scores than in the quantitative, which would be an interesting point of further research, but the sample size again could prevent these results from being significant. Thus, to complete an accurate departmental comparison and assess of the impact of training, a study with many more participants would need to be performed.

The final section of findings looked at the possible correlations between training scores and total attitude scores as grouped by department. This analysis suggested positive correlations between training scores and total scores, which may have shown that more training was connected to more positive attitudes. However, these results were far outside the range of statistical significance, meaning no such conclusion can be drawn. Despite the lack of significance, though, these correlations indicate the potential for a positive correlation between training and officer attitudes, which may prompt significant research on the subject.

Regardless of the limitations and shortcomings of this study, it began the necessary investigation of officer perceptions of intellectual disabilities in Kankakee County, which is a major step in addressing and improving the way cases involving the intellectually disabled are handled. This is especially valuable in the context of the county’s high disabled population and Illinois’s lack of improved policies. These limitations, however, prompt ideas for future research. Many of these ideas are centered around conducting a similar study in a comparable population but with a significant increase in participants. Many of the results and correlations gathered from this survey’s data trended towards meaningful results but did not have the backing of a substantial population to make those results significant. Thus, a larger sample would not only ensure that the assessment of officer attitudes in such a population is more accurate, but also make the results carry more significance should they indicate influences similar to those found in this study. Some ideas that could increase the number of respondents are to make the survey available for a longer period of

time or to more directly incentivize efficient participation more directly. When a more significant sample is established, the door is opened for researching influences like gender and race, as well as more accurately comparing departments and assessing the impact of training on officer attitudes. Further, a study could look at the more individual influences of types of training by comparing the training to each domain and by viewing the possible correlations based on the participant rather than the department.

Finally, if the tool in this study is used in the future, it is recommended that the researchers evaluate and adjust the wording of some questions to ensure a single interpretation is evident. For example, the question regarding years of experience in the demographics section could be answered in different ways if not read thoroughly and thus could use clarification. As part of this, if the survey is distributed online, it would help to have the demographics section include drop-down choices, when possible, to ensure accuracy and consistency during the interpretation of responses.

REFERENCES

ANCOR. (2019, January 10). Illinois ranks 44th among all states in efforts to serve individuals with intellectual and developmental disabilities. American Network of Community Options and Resources. https://caseforinclusion.org/application/ files/6115/4690/0035/Illinois_2019_Case_for_Inclusion_Press_Release.pdf

Bureau of Justice Statistics. (2017). Crime against persons with disabilities, 2009-2015 –Statistical Tables. Retrieved May 2, 2020, from https://www.bjs.gov/content/pub/pdf/ capd0915st_sum.pdf

Cheng, T. (2020). Input without influence: The silence and scripts of police and community relations. Social Problems, 67(1), 171–89.

Child, B., Oschwald, M., Curry, M., Hughes, R., & Powers, L. (2011). Understanding the experience of crime victims with disabilities and deaf victims. Journal of Policy Practice, 10(4), 247–67.

CHSA Kankakee County. (2018). Community health status assessment – Kankakee County. https://www.kankakeehealth.org/documents/about-3/community-healthneeds-assessment-and-improvement-plan-1/mapp/2018-3/300-community-healthstatus-assessment-1/file#:~:text=In%20Kankakee%20County%2C%2016.78%25%20 of,higher%20than%20Illinois%20(10.73%25).

Eadens, D. M. (2008). Police officers’ perceptions regarding persons with mental retardation. Graduate Theses and Dissertations. https://digitalcommons.usf.edu/ etd/224/

Eadens, D. M., Cranston-Gingras, A., Dupoux, E., & Eadens, D. W. (2016). Police officer perspectives on intellectual disability. Policing: An International Journal, 39(1), 222–35.

Equal Opportunity for Individuals with Disabilities, 42 U.S.C.§ 12102 (2008).

Gardner, L., Campbell, J. M., & Westdal, J. (2019). Brief report: Descriptive analysis of law enforcement officers’ experiences with and knowledge of autism. Journal of Autism & Developmental Disorders, 49(3), 1278–83.

Hughes, R., Curry, M., Oschwald, M., Child, B., Lund, E., Sullivan, M., & Powers, L. (2011). Responding to crime victims with disabilities: The perspective of law enforcement. Journal of Policy Practice, 10(3), 185–205.

Koskela, S. A., Pettitt, B., & Drennan, V. M. (2016). The experiences of people with mental health problems who are victims of crime with the police in England: A qualitative study. British Journal of Criminology, 56(5), 1014–33.

Oschwald, M., Curry, M. A., Hughes, R., Arthur, A., & Powers, L. (2011). Law enforcement’s response to crime reporting by people with disabilities. Police Practice & Research, 12(6), 527–42.

Scantlebury, A., Fairhurst, C., Booth, A., McDaid, C., Moran, N., Parker, A., Payne, R., Scott, W. J., Torgerson, D., Webber, M., & Hewitt, C. (2017). Effectiveness of a training program for police officers who come into contact with people with mental health problems: A pragmatic randomised controlled trial. PLoS ONE, 12(9), 1–17.

Schuck, A. M. (2017). Female officers and community policing: Examining the connection between gender diversity and organizational change. Women & Criminal Justice, 27(5), 341–62.

United States Census Bureau. (2020, June 17). Anniversary of Americans with Disabilities Act: July 26, 2020. https://www.census.gov/newsroom/facts-forfeatures/2020/disabilities-act.html

APPENDIX A: INFORMED CONSENT

Informed Consent to Participate in Research Information to Consider Before Taking Part in this Research Study

Dear Research Participant:

Your participation in a research project is requested by Jill English, an Honors Student in the Computer Science and Criminal Justice departments of Olivet Nazarene University who is seeking information that will be useful in the field of criminal justice. The aim of the research is to examine and explain the attitudes towards disabilities held by police officers, specifically regarding intellectual and developmental disabilities. In accordance with this aim, the following procedures will be used: police officers across Kankakee County will answer demographic and survey questionnaires.

If you decide to participate in this research, you will be asked to answer demographic and survey questionnaires. These forms can be completed in 20 minutes and will be confidentially submitted before the end of your shift.

Your consent to be a research participant is strictly voluntary and should you decline to participate or should you choose to drop out at any time during the study, there will be no adverse effects on your employment. The only risks to you are the potential for the survey to trigger feelings of guilt or frustration regarding how you or your department have previously handled such cases. If you feel any emotional support would be helpful to you, a community resource line is available by dialing 288. Although there are no direct benefits to you, your participation in this study will help our understanding of police officers’ attitudes towards disability and ways in which interactions between them may be improved. Participants will not be financially compensated.

As a research participant, the information you provide will be held in confidence to the extent permitted by law. Any published results of the research will refer to group averages only, and no names will be collected or used in the study. Data will be kept in a locked file in the research mentor’s office. The researcher may publish what is learned from the study, but if so, it will not identify names or other information that would let people know who you are.

You should only take part in this study if you want to volunteer. You should not feel that there is any pressure to take part in this study. You are free to participate in this research or withdraw at any time. There will be no penalty or loss of benefits you are entitled to receive if you decide not to take part in this study.

If you have any questions or concerns regarding this study or your participation in it, you may contact me, Jill English at jmenglish@olivet.edu or my project mentor, Dr. Stroud at rmstroud@olivet.edu.

Completion of the demographic questionnaire and survey questions will constitute consent to participate in the study. By completing the forms, you agree with the statement: “I freely give my consent to take part in this study. I understand that by

completing this form I am agreeing to take part in research. I have received a copy of this form to take with me.”

Sincerely,

Jill English, Honors Cohort 13, Olivet Nazarene University

Demographics

APPENDIX B: DEMOGRAPHICS

1. Please mark your job description:

Today’s Date:

 Police officer (Patrol)  Police officer (Other):

2. Years of Experience in current position:

3. Gender (Circle one): Male Female

4. In what year were you born?

5. Please circle your ethnic origin:

Black/African American White/Caucasian Hispanic/Latino

6. For which department do you work?

Other:

APPENDIX C: QUALITATIVE QUESTIONS

Qualitative Questions

1. How do you know if someone with whom you are interacting has an intellectual disability?

2. Please describe any personal experience you have had with a person who has an intellectual disability:

3. Under what conditions would you adopt a child with an intellectual disability?

4. If your significant other befriended a person with an intellectual disability, describe the kind of social events you would be willing to attend with your significant other and his/her new friend.

5. Please describe any previous disability training you have received.

APPENDIX D: QUANTITATIVE QUESTIONS

Quantitative Questionnaire

Directions: Please rate your level of agreement with the statements below by circling the number representing your opinion of the given statement.

Please respond to every statement.

KEY

1: I disagree strongly. 2: I disagree a little. 3: I a gree a little. 4: Iagree stongly.

1. People with intellectual disability usually act crazy.

2. I would talk to a person with intellectual disability during a break at work.

3. I avoid looking at or walking by people with intellectual disabilities when I see them in the street.

4. I would stand next to a person with an intellectual disability while I was talking to my friends or coworkers.

5. I would like to be a teaching assistant in a special education class for students with intellectual disabilities.

6. I was scared by a person with an intellectual disability who bothered me.

7. Someone in my family has an intellectual disability.

8. I think that people with intellectual disabilities should accompany regular social groups on outings.

9. I just feel sorry for people with intellectual disabilities.

10. I have spoken with a person who has an intellectual disability during the last month.

11. I have given money to a person with an intellectual disability on the street.

12. People usually become intellectually disabled from head injuries that occurred in accidents.

13. It can be rewarding for me to talk with or help people with intellectual disabilities.

14. I would go to a movie with a person with an intellectual disability.

15. During the last year, I have helped people with intellectual disabilities who needed assistance.

16. Poor people are more likely to have children with intellectual disabilities.

17. I would invite a person with intellectual disabilities to visit my home.

18. I think you can learn a lot about people in general by being with people who have intellectual disabilities.

19. I would sit next to a person with intellectual disabilities in a social situation.

20. I have had an unpleasant experience with people who have intellectual disabilities; for example, being yelled at or bothered during the past year.

21. When I have seen a person with an intellectual disability needing help, I did what I could help.

22. I would eat lunch with a person who has an intellectual disability.

23. It makes me feel a little sick being around people who are significantly disabled or have severe intellectual disabilities.

24. I have been warned to stay away from people with intellectual disabilities because they do weird things.

25. I would help a person with an intellectual disability if we were in a leisure setting together.

26. I like having people with intellectual disabilities participate in the same leisure activities I do.

27. When I was a child, I saw my parents spent time with people who have intellectual disabilities.

28. I would invite a person with an intellectual disability to eat dinner with my family.

29. When watching telethons about people with intellectual disabilities, I have felt like giving money.

30. I have seen people with intellectual disabilities being ridiculed or made fun of by other people in social situations.

31. I have seen a person with an intellectual disability at the beach or park.

32. I think I know enough about how to help a person with an intellectual disability do something like find something in a store.

33. I would eat dinner with a person who has an intellectual disability who invited me to dinner in his/her home.

34. I have seen or heard about people with intellectual disabilities in social settings.

35. I have talked to a person with an intellectual disability around town.

36. I would give a person with an intellectual disability a ride home in my personal vehicle.

37. When the subject comes up, I have heard people say bad things about people with intellectual disabilities.

38. I would be friends with a person who has an intellectual disability.

39. We had a person with an intellectual disability visit our home.

40. I would like voluntarily to spend time once a week with a child who has an intellectual disability.

APPENDIX

E: SURVEY

Qualitative Questions

QUESTIONS SORTED BY DOMAIN

Domain codes: Knowledge ~ Contact ~ Affect ~ Social Willingness

Knowledge

1. How do you know if someone with whom you are interacting has an intellectual disability?

Contact

2. Please describe any personal experience you have had with a person who has an intellectual disability.

Affect

3. Under what conditions would you adopt a child with an intellectual disability?

Social Willingness

4. If your significant other befriended a person with an intellectual disability, describe the kind of social events you would be willing to attend with your significant other and his/her new friend.

Training Question (Not affiliated with a domain)

5. Please describe any previous disability training you have received.

Quantitative Questionnaire

Domain codes: Knowledge ~ Social Willingness ~ Contact ~ Affect

Knowledge

1. People with intellectual disability usually act crazy.

12. People usually become intellectually disabled from head injuries that occurred in accidents.

16. Poor people are more likely to have children with intellectual disabilities.

Social Willingness

2. I would talk to a person with intellectual disability during a break at work.

4. I would stand next to a person with an intellectual disability while I was talking to my friends or coworkers.

5. I would like to be a teaching assistant in a special education class for students with intellectual disabilities.

8. I think that people with intellectual disabilities should accompany regular social groups on outings.

14. I would go to a movie with a person with an intellectual disability.

17. I would invite a person with intellectual disabilities to visit my home.

19. I would sit next to a person with intellectual disabilities in a social situation.

22. I would eat lunch with a person who has an intellectual disability.

25. I would help a person with an intellectual disability if we were in a leisure setting together.

28. I would invite a person with an intellectual disability to eat dinner with my family.

32. I think I know enough about how to help a person with an intellectual disability do something like find something in a store.

33. I would eat dinner with a person who has an intellectual disability who invited me to dinner in his/her home.

36. I would give a person with an intellectual disability a ride home in my personal vehicle.

38. I would be friends with a person who has an intellectual disability.

40. I would like voluntarily to spend time once a week with a child who has an intellectual disability.

Contact

3. I avoid looking at or walking by people with intellectual disabilities when I see them in the street.

7. Someone in my family has an intellectual disability.

10. I have spoken with a person who has an intellectual disability during the last month.

11. I have given money to a person with an intellectual disability on the street.

15. During the last year, I have helped people with intellectual disabilities who needed assistance.

20. I have had an unpleasant experience with people who have intellectual disabilities; for example, being yelled at or bothered during the past year.

21. When I have seen a person with an intellectual disability needing help, I did what I could to help.

24. I have been warned to stay away from people with intellectual disabilities because they do weird things.

27. When I was a child, I saw my parents spent time with people who have intellectual disabilities.

30. I have seen people with intellectual disabilities being ridiculed or made fun of by other people in social situations.

31. I have seen a person with an intellectual disability at the beach or park.

34. I have seen or heard about people with intellectual disabilities in social settings.

35. I have talked to a person with an intellectual disability around town.

37. When the subject comes up, I have heard people say bad things about people with intellectual disabilities.

39. We had a person with an intellectual disability visit our home.

Affect

6. I was scared by a person with an intellectual disability who bothered me.

9. I just feel sorry for people with intellectual disabilities.

13. It can be rewarding for me to talk with or help people with intellectual disabilities.

18. I think you can learn a lot about people in general by being with people who have intellectual disabilities.

23. It makes me feel a little sick being around people who are significantly disabled or have severe intellectual disabilities.

26. I like having people with intellectual disabilities participate in the same leisure activities I do.

29. When watching telethons about people with intellectual disabilities, I have felt like giving money.

APPENDIX F: QUALITATIVE RESULTS CODING KEY

Coding for the Qualitative Response Categories and their Associated Themes

Question 1 – Knowledge

How do you know if someone with whom you are interacting with whom you are interacting has an intellectual disability?

Knowledge Response Categories:

1 – don’t know person has an intellectual disability, N/A

2 – speech difficulties

3 – behavioral characteristics

4 – speech and behavioral characteristics

5 – cognitive characteristics / content of conversation

Knowledge by Theme:

No knowledge – category 1

Some knowledge – categories 2, 3, 4

Accurate knowledge – category 5

Question 2 – Contact

Please describe any personal experience you have had with a person who has an intellectual disability.

Contact Response Categories:

1 – no contact with intellectual disability

2 – listed experience w/ mental illness

3 – minimal contact / working as an officer contact

4 – worked/volunteered with disabilities

5 – know someone (family, friend, etc.)

Contact by Theme:

No contact – category 1, 2

Little contact – category 3

Personal contact – categories 4, 5

Question 3 – Affect

Under what conditions would you adopt a child with an intellectual disability?

Affect Response Categories:

1 – don’t know / no conditions would make me adopt with intellectual disability

2 – no kids/adoption of any kind / too old to parent

3 – necessity

4 – circumstances (finances, time, lack of proper training to raise intellectual disability)

5 – would adopt with intellectual disability

Affect by Theme:

Negative personal affect – category 1

Neutral personal affect – categories 2, 3

Positive personal affect – categories 4, 5

Question 4 – Social Willingness

If your significant other befriended a person with an intellectual disability, describe the kind of social events you would be willing to attend with your significant other and his/ her new friend.

Social Willingness Response Categories:

1 – none / not applicable

2 – specific events only

3 – any, but would be uncomfortable

4 – any events

Social Willingness by Theme:

Negative social willingness – category 1

Minimal social willingness – categories 2, 3

Positive social willingness – category 4

Question 5 – Training

Please describe any previous disability training you have received.

Training Response Categories:

1 – none

2 – little / experience as training

3 – named other trainings (empathy, mental illness, etc)

4 – police academy

5 – disability training session

6 – formal disability training (college, etc.)

Training by Theme:

No training – categories 1, 2

Minimal training – categories 3, 4

Disability-specific training – categories 5, 6

A Curriculum Designed to Teach Elementary-Age Children in Diverse Settings the Kingdom Concept of Loving One’s Neighbor

ACKNOWLEDGEMENTS

Thank you first and foremost to my family. To my parents, for being the very first ones to model what it looks like to meet Jesus next door. Our table was never too small to pull up extra chairs for people from across the city and around the world to come break bread with us and share stories of God’s faithfulness. That simple act shaped me in profound ways. To my sister Hannah, you have always inspired me more than you know. You may have moved halfway across the globe, but it somehow only made the world seem smaller. Thank you for showing me that there are no borders when it comes to meeting Jesus next door.

To the Olivet Honors Program professors and faculty that have walked with us each step of the way, from our first class as freshman through to graduating with university honors, thank you. You have taught us how to think deeply, engage actively, and believe we have the power to make a difference.

To Dr. Blanchette, you might be my project mentor and advisor, but you are also teacher, encourager, and shepherd. My ministry is what it is today because of the ways you have poured into me. Thank you for welcoming me into your office week after week. From offering to be my honors project mentor back at freshman

orientation, all the way to signing the cover page of my thesis. You have encouraged me and empowered me to dream ever bigger for the future God has for me.

To my project reviewers- Scottie May, Tyrell Shoemaker, Jeffery Stark, Steve and Debra Sudworth, Simone Twibell, and Montague Williams, thank you. The feedback you provided for my project shaped it into something that will be sounder and more impactful than I could have achieved on my own. To my professors in the School of Theology and Christian Ministry, thank you for fanning the flame of this passion and compelling me to live into the Kingdom of God.

Finally, thank you to Anthem Church, especially the staff and elders. You saw potential in me and believed in what God is doing in my life. Thank you for trusting me and working with me while I finished my degree. The best is yet to come!

ABSTRACT

United States Census data from 2020 show that the country is becoming increasingly diverse and urbanized. Other research shows children are aware of race from an early age and can pick up biases and stereotypes by watching the adults around them. However, there are no children’s ministry curricula that specifically address how children should navigate differences from a biblical perspective. To fill this gap, a children’s ministry curriculum was written to model how children can love their neighbors like Jesus did, especially those who look different from themselves. The curriculum is comprised of an introduction for the ministry leader, five weekly lessons, and a resource list. The weekly lessons include an introduction, a leader note and devotion, preparation instructions, opening activity ideas, the large group lesson, prayer and reflection stations, a closing, and family take-home sheets. The curriculum was reviewed by seven practitioners and professors and revised according to their comments. The goal of this curriculum is to be a valuable resource to churches, parachurch organizations, and families as they seek to point children to where God is already at work in their neighborhoods and how they can make Jesus known there.

Keywords: Jesus, diversity, race, children, children’s ministry, curriculum, neighbors, lessons, family, church

INTRODUCTION

The 2020 US Census provided statistical evidence confirming what many practitioners already knew.1 The United States of America is becoming increasingly diverse and urbanized. Given this trend, children should be intentionally taught how to respond in love to the racial, ethnic, and cultural differences they see in their friends.

After looking at several of the leading children’s ministry curriculum publishers, it became evident that there is a lack of multi-ethnic curricula. No curricula were found that specifically address how children can love their neighbor across racial, ethnic, social, and economic differences, in a way consistent with the Kingdom of God. This is a gap in children’s ministry that needs to be bridged. The goal of this project is to develop and write a children’s ministry curriculum that can be used in churches or parachurch organizations that will begin to build that bridge. This curriculum will help the Church start conversations about how to respond to the diversity present in the communities around them. Further, it will provide children’s pastors and para-church

1. United States Census Bureau. August 12, 2021. “2020 Census Statistics Highlight Local Population Changes and Nation’s Racial and Ethnic Diversity.” United States Census Bureau. Accessed September 21, 2021. https://www.census.gov/newsroom/press-releases/2021/population-changes-nations-diversity.html.

children’s workers with a theologically grounded curriculum designed to teach not just white students, but students of all races and ethnicities, how to love one’s neighbor as oneself in a diversifying world.

Many theme-focused children’s ministry curricula are written to be one month long. Following the typical format, this curriculum is a total of five weeks, with the final week being focused on action. It is written for kindergarten through fifth-grade age audiences. Each week is built upon a Bible passage from the Gospel of Luke. Luke was chosen because it is where many of Jesus’ parables are found, specifically the parable of the Good Samaritan. The curriculum will walk children through four parables taught by Jesus, showing them what it looks like to be citizens of the Kingdom of God, in their neighborhoods.

The curriculum itself includes several elements. There is an introduction for the ministry leader who will be teaching. Then each week’s lesson includes a beginning section with the big idea, objectives (written in the know, be, do format), Biblical basis, and the memory verse for the month. Following that guiding section, there is a devotion for the leader to prepare their own heart before teaching. Finally, for each week’s lesson, there are prep instructions, opening activity recommendations, a script for the large group lesson, small group guides, prayer and reflection stations, and a take-home guide for families to use throughout the week. Each of these elements contributes toward a holistic experience for the children who would get to learn from the curriculum.

Upon completion, the curriculum was reviewed by seven qualified individuals, each of whom offered a unique voice and perspective. Represented among the reviewers were professors from various institutions who specialize in Christian Formation and Ministry, Church, Culture, and Society, Missional Theology, and Intercultural Studies. These professors come from diverse backgrounds, carrying with them years of practical ministry experience as well. Additionally, several of the other reviewers are urban ministry practitioners in the city of Chicago, one at an inner-city para-church organization and two on staff at a diverse, multi-ethnic church. These are individuals who have already experienced the trends shown by the U.S. census. Their input offered valuable, practical feedback. These seven reviewers are not only diverse in the experience they bring, but also in demographics. Four were men and three were women, and they represent a small array of national and racial backgrounds. Given the nature of the curriculum, having this diversity of reviewers was pertinent.

The following review of literature provides a background in the areas of Biblical foundations, children’s ministry, curriculum development, multi-ethnic ministry, and sociology. Gaining an understanding of each of these topics and what already exists in the field is important. Seeing the gaps in present research lays the foundation for the bridge this curriculum seeks to build.

REVIEW OF LITERATURE

Biblical foundations

When it comes to the Biblical foundation of loving one’s neighbor, the book of Luke is a vital place to turn. Central to the Gospel of Luke is the parable of the Good Samaritan. It is in this passage that Jesus challenges the law expert’s perception of who his neighbor is. David A. Neale has written a commentary on Luke 9-24 that offered guidance for the project from a Biblical, theological perspective.2 In the context of Jesus’ time, the Samaritan would have been seen as a sinner simply because of his ethnic identity. Yet it was he, the man on the margins, who displayed the love of God. This concept forms some of the foundations for the curriculum.

Another helpful resource when it comes to writing a curriculum on diversity and inclusion is The Bible Story Handbook by John H. and Kim E. Walton.3 In this resource, there is a section on the parable of the Good Samaritan that further establishes the faithful application of the Bible. Both resources, along with others, are important in ensuring that the curriculum is not just a helpful resource when it comes to race, but even more importantly is grounded in authentic, Scriptural exegesis.

Children’s ministry

Diana R. Garland, former dean of Baylor University’s School of Social Work, has written a comprehensive guidebook for family ministry in which she devotes a section to culture and family identity.4 She reinforces the need for congregations to be a place where families learn to share their stories with one another as well as learn about and be a part of the story of the church. When speaking about racism, how to love one’s neighbor, and how to engage those around us, stories are the catalyst for relationships and connection. The Church must learn how to continue sharing stories in ways that inspire and honor one another all while drawing us closer to each other and Christ. Garland’s writing on the importance of storytelling and families will shape how this curriculum approaches stories.

Bob Goff, a well-known lawyer, speaker, and author, has written a children’s book about what it looks like to show love to our neighbors, illustrated through stories from his and his children’s lives.5 In the introduction, Goff lays out his Biblical and Gospelcentered incentives in writing the book. He tells of how God picked a little kid,

2. David A. Neale, “Examples of Love for Neighbor and God (10:25-42),” in Luke 9-24: A Commentary in the Wesleyan Tradition (Kansas City: Beacon Hill Press, 2013), 64–71.

3. John H. and Kim E. Walton, “Good Samaritan (Luke 10:25-37),” in The Bible Story Handbook (Wheaton: Crossway, 2010), 347–50.

4. Diana R. Garland, “Culture and Family Identity: Implications for Family Ministry,” in Family Ministry: A Comprehensive Guide (Downers Grove: IVP Academic, 2012), 333–34.

5. Bob Goff, “Introduction” in Love Does for Kids (Nashville: Thomas Nelson, 2018), 1–3.

Jesus, to save the world. Goff refers to the verses from the Gospel books in which Jesus says that to enter the Kingdom of Heaven, one must change and become like little children. In this Kingdom, the humblest people, like children, will be the greatest. This book provided helpful information when writing the current curriculum because it is full of stories of Christians loving their neighbor. Such an inspiring piece of literature can also serve as a resource to be recommended to families. Finally, it provides a Biblical imperative for the importance of love through the posture of humility. This curriculum will remind students that they can be leaders in love because they carry faith, grace, love, and forgiveness.

David Swanson, pastor of New Community Covenant Church (an intentionally multiracial congregation on the South Side of Chicago) describes how individuals of various backgrounds first become aware of race and its societal implications. 6 It is very different for white individuals, who often do not think about race until young adulthood, than for children of color who can often describe an unforgettable encounter with racism as a young child. If parents and adults in the Church are silent about race, it will be interpreted by the children as an approval of the way things are. Swanson stresses the importance of intergenerational, corporate worship as a catalyst for change. To practice a children’s ministry of reconciliation, churches must recognize how our culture’s racial discipleship keeps white churches silent, equip parents and caregivers to disciple and lead their children toward the Kingdom of God, evaluate what our worship service looks like to children and whether white children ever see their parents or pastors submitting to people of color, and understand that we cannot afford to wait. David Swanson’s chapter is one of the few resources available that specifically addresses race within children’s ministry.

Martin Luther King Jr. is quoted saying, “Every day I meet young people whose disappointment with the church has turned into outright disgust”.7 Montage R. Williams’ book, Church in Color, serves to share the realities of race in multiracial and multiethnic youth ministries and to provide a path for how to engage this with the work of theology. He takes a practical, theological investigation approach as he studies three congregational youth ministries in three different contexts. Williams is arguing that doing theology faithfully requires the work of intentionally seeing how race, racism, and racial identity are at work in congregations and ecclesial communities. As he studied the three congregations, two main patterns emerged. First, young people in the congregations have had many experiences with race and often wonder about matters of race. Second, while young people in these congregations were mostly thankful for

6. David W. Swanson, “Practicing Children’s Ministry of Reconciliation,” in Rediscipling the White Church from Cheap Diversity to True Solidarity (Downers Grove: IVP, 2020), 114–31.

7. Montague R. Williams, “Introduction,” in Church in Color: Youth Ministry, Race, and the Theology of Martin Luther King Jr. (Waco: Baylor University Press, 2020), 1–10.

their youth groups and youth workers, they hardly found any space to engage their experiences and wonders meaningfully regarding race, racism, and racial identity. Williams’ book both honestly addresses multiracial and multiethnic congregational life and points toward a hopeful vision of multiracial and multiethnic congregational life in which the lens of color-blindness is actively resisted in favor of discipleship that can meaningfully engage race.

Curriculum development

When writing a curriculum for a church setting, there are several considerations in how to accurately and systematically teach believers to be disciples of Christ. Andrew Burggraff has identified four problems that the Church needs to identify when it comes to discipleship.8 These include a decline in Biblical literacy, an exodus of believers from evangelical churches, an acceptance of inactivity among current evangelical Christians, and a de-emphasis on discipleship training within the church. In response to that, Burggraff has laid out a ten-step process for curriculum writing that was an important consideration in writing the present curriculum.

Several resources have attempted to direct children on how they can navigate race in the Kingdom of God, but none of them are curricula. Trillia Newbell has written a book for children and families called Creative God, Colorful Us that helps make the idea of God making humanity in His image something that children can grasp and understand.9 This resource is incredibly helpful in framing what already exists on the topic while also being a book listed on a supplemental family reading list in the curriculum itself.

Another similar resource, while not a curriculum, is Margot Starbuck’s book Small Things with Great Love: Adventures in Loving Your Neighbor.10 Three chapters within the book specifically cover how to love your neighbor in the context of parents, caregivers, and family values. Children notice cues from their parents about how to relate to others, so parents need to be intentional in how they love their neighbors. Loving neighbors is the lens through which this curriculum was written. Starbuck’s book helps frame and build up the foundation of that discussion.

Multi-ethnic ministry

In addition to considering children’s ministry and curriculum development, it is also necessary to look at what resources exist in the context of multi-ethnic ministry.

8. Andrew Burggraff, “Developing Discipleship Curriculum: Applying the Systems Approach Model for Designing Instructions by Dicky, Carey, and Carey to the Construction of Church Discipleship Courses,” in The Christian Education Journal 12, no. 2 (Fall 2015).

9. Trillia J. Newbell and Chase Williamson, “God Made You (And He Made Your Friends Too!)” in Creative God, Colorful Us (Chicago: Moody Publishers, 2021), 13–24.

10. Margot Starbuck, Small Things with Great Love: Adventures in Loving Your Neighbor, (Downers Grove: InterVarsity Press, 2011), 153–74.

Extensive research made it clear that many resources exist on how to navigate this with adult congregations, but few to none discuss how to walk through multi-ethnic ministry with children. This is certainly a deep need within the field of ministry, especially in the Western world as it becomes more and more diverse.

Barber Leroy has called for diversity in Christian missions and ministry, with a focus on the missio Dei, or mission of God, which in its present state is hindered by racism.11 He laments how the missions community has failed to listen to communities of color and failed to install broadly diverse leadership. One of Barber’s key claims is that silence is the weapon of racism today and stories of those who have been hurt need to be shared and exchanged. This claim builds into the necessity for a children’s ministry curriculum that speaks to the imago Dei of every child.

Mark DeYmaz is another key leading voice in paving the way for multi-ethnic ministry. In his book Building a Healthy Multi-Ethnic Church he describes how the Biblical church in Antioch, referenced in the book of Acts, in many ways set the precedent for multi-ethnic churches to follow. The five main leaders of the church in Antioch are listed not only by their gifting, but also by their ethnicity, representing Africa, the Mediterranean, the Middle East, and Asia Minor. From the very beginning, DeYmaz proves that the New Testament church was both ethnically and economically diverse. He calls churches in the U.S. towards and into multi-ethnic ministry, to turn from the segregation that is present in ninety percent of churches in the United States.12 The goal of this curriculum is to grow connections between different groups and to start these connections young, from within the children’s ministry.

DeYmaz has written another book alongside Harry Li called Ethnic Blends: Mixing Diversity into Your Local Church which walks through the practical challenges that churches will face as they pursue diversity. They briefly touch on how this affects children by writing, “[T]he fact is that much of the curricula being developed for children today do not represent the increasing diversity of the North American church, much less that of our culture.”13 This is a very clear call for a curriculum such as the one I have written to be implemented into the culture of the church.

One final important voice in the conversation of multi-ethnic ministry is Sandra Maria Van Opstal. Her book The Next Worship: Glorifying God in a Diverse World

11. Leroy Barber, “Hurt but Hopeful,” in Red, Brown, Yellow, Black, White–Who’s More Precious in God’s Sight? A Call for Diversity in Christian Missions and Ministry (New York: Jericho Books, 2014), 163–200.

12. Mark DeYmaz, “The Pattern at Antioch,” in Building a Healthy Multi-Ethnic Church: Mandate, Commitments, and Practices of a Diverse Congregation (San Francisco: Jossey-Bass, 2007), 13–26.

13. Mark DeYmaz and Harry Li, “Can I Pour You a Cup? Overcoming the Practical Obstacles,” in Ethnic Blends: Mixing Diversity into Your Local Church (Grand Rapids: Zondervan, 2010), 125–46.

provides another cornerstone in the building of multi-ethnic ministry.14 Throughout her text, she weaves in the metaphor of gathering at a table for a big family meal where people from every walk of life and social status come together by God’s invitation. However, just because everyone is invited does not mean it will be void of cultural tension. Van Opstal cites research from the Public Religion Research Institute stating that over half of young American Christians are people of color. This is a trend that will only increase as today’s children grow up. Finally, Van Opstal adds an eschatological calling to her argument for multicultural worship. In the end, according to Revelation 7:9, people from every nation, tribe, people, and language will worship God together. The church can begin living into this eschatological vision here and now. This children’s ministry curriculum will seek to help lead the way toward this vision.

Sociological considerations

There is much to be considered from a sociological perspective on the necessity of writing such a curriculum. Marian Wright Edelman, president of the Children’s Defense Fund, calls on faith leaders specifically to take up their responsibility of caring for children in radical ways.15 Children need the church to be present in their lives and to stand against those that treat them unjustly, to challenge culture, and to raise the Church’s counter-cultural voice in a world of false prophets. The Church has such a profound opportunity to be that voice in children’s lives, but it has been failing. The current curriculum attempts to push churches and church leaders to take up that call. Margaret A. Hagerman, professor of Sociology at Mississippi State University, has published a journal article on the way that children perceive, understand, and experience race in the U.S.16 Whether or not parents and teachers speak with kids about race, young children notice racial differences at very young ages and learn societal rules about race throughout their childhoods. Through Hagerman’s research, she discovered that not all white kids have the same ideas about race and that kids of color reported a sense of pervasive anxiety, citing racism as the underlying cause. Children as young as three years old can racially categorize people, at five they are conscious of existing racist stereotypes about their group, and by eight, white kids have learned that it is socially unacceptable to express explicit forms of racial bias and exhibit an increase in implicit forms of racial bias. Kids need to be provided with a sociological imagination, new knowledge systems, and the stories and voices of families and communities of color.

14. Sandra Maria Van Opstal, “Tension at the Table: Challenges and Opportunities in Diverse Worship,” in The Next Worship: Glorifying God in a Diverse World (Downers Grove: IVP, 2016), 19–37.

15. Marian Wright Edelman, “A Letter to Faith Leaders,” in The Sea is So Wide and My Boat is So Small (New York: Hyperion Books, 2008), 37–49.

16. Margaret A, Hagerman, “American Childhoods Today: Conversations with Kids about Race,” Phi Delta Kappan 100, no. 7 (April 2019): 17–21

Hagerman’s studies, and her entire article, are further evidence that this curriculum is necessary for children’s ministries throughout the country. Children need to be given a space to understand, process, and form sociological imaginations, especially from a theological perspective. There is no better place for this to be done than the Church.

A study was done by Adam Heaton, an educator, that dove into how teachers can play a role in helping their students relearn positive views of the negative stereotypes they previously held.17 Though this curriculum will be for primarily American audiences, this study from Australia is still helpful in seeing how children’s prejudices can change. The results of this study, though in the field of education, prove that children do show racism but through carefully crafted and facilitated learning experiences it can show young students an alternative way of seeing people who are culturally and ethnically different from themselves.

The Public Religion Research Institute found that, as of 2020, seven in ten Americans identify as Christian with more than four in ten identifying as white Christian and more than one-quarter of Americans identifying as Christians of color.18 Over the last few decades, the proportion of the US population that is white Christian has declined by one-third, and by 2020, one in four Americans were Christians of color (26%). Americans ages eighteen to twenty-nine are the most religiously diverse age group. A majority (54%) of young Americans (ages eighteen to twenty-nine) are Christians but only 28% are white Christians while 26% are Christians of color. These numbers show the increasing diversity of America and the need for a curriculum that takes more than just the majority voice into consideration.

Well-known psychologist Beverly Daniel Tatum acknowledges the paralysis of fear that exists in addressing racism. But she insists that for there to be meaningful dialogue, fear must eventually be given way to risk and trust.19 After Tatum lays this foundation, she asserts that we need to find courage for social change. This is not easy but can be done by looking for courage in the lives of others and seeking role models for how to be an effective agent of change.

In Ken Wytsma’s book The Myth of Equality, he offers a framework for pursuing racial reconciliation.20 The four steps Wytsma provides include 1) Listening and Learning, 2) Lament, 3) Confession and 4) Laying Down Privilege. Though it is not geared toward ministry with children, these steps can still be helpful in how to

17. Adam Heaton, “Kids can show Prejudice and Teachers can show them another Path,” in Issues in Educational Research 28, no. 4 (2018): 940–52.

18. PRRI Staff. July 8, 2021. “The 2020 Census of American Religion.” Public Religion Research Institute. Accessed September 21, 2021.

19. Beverly Daniel Tatum, “Embracing a Cross-Racial Dialogue: We Were Struggling for the Words,” in Why Are All the Black Kids Sitting Together in the Cafeteria? (New York: Basic Books, 2017), 331-342.

20. Ken Wytsma, “Finding Ourselves in the Other,” in The Myth of Equality (Downers Grove: IVP Books, 2017), 167-83.

approach teaching children how to theologically and sacrificially love their neighbor. The background on equality and privilege that Wytsma provides in his book was essential to understand when writing a diversity-based curriculum as a white woman.

The 2020 census showed an increase in the population of U.S. metro areas compared to a decade ago.21 The population of U.S. metro areas grew by nine percent from 2010 to 2020, resulting in eighty-six percent of the population living in metro areas. Additionally, changes to question design and updated data processing revealed that the U.S. population is much more multiracial and more diverse than has been measured in the past. The white population remained the largest race or ethnic group with 204.3 million people identifying as white alone, but the white alone population has decreased by 8.6% since 2010. Conversely, the multiracial (two or more races) population, which measured at nine million people in 2010, is now at 33.8 million people in 2020, showing a 276% increase. These demographics show that the racial and ethnic makeup of Americans is changing. There is a growing likelihood that the children whom students sit next to in church, play with at recess, and pass by on the street do not look like themselves or come from the same background. This is exactly why it is so important to create a curriculum that caters not just to the majority-white voice but is written with a diverse, multi-ethnic audience in mind.

METHODOLOGY

The curriculum itself was written in late spring and early summer, following my junior year of university. In May 2022, two days were set aside every week to sit down and work on writing the lessons themselves, based on the research and exegesis of Scripture that had been done throughout the school year. Several times throughout the month, the project to date would be sent to the project mentor, Dr. Leon Blanchette. Then a video call would be scheduled to review his comments and give continued direction to the project. By early June, the curriculum draft was complete, edits had been made, and it was emailed off to the seven reviewers for their expert feedback.

EXPERT REVIEWS AND RESPONSE

As the curriculum was being written, the seven individuals were contacted to inquire if they would be willing to offer an expert review of the completed curriculum. All seven individuals agreed. Listed alphabetically below are the names and positions of each reviewer to give credibility to their experience that spoke to the present curriculum.

21. United States Census Bureau. August 12, 2021. “2020 Census Statistics Highlight Local Population Changes and Nation’s Racial and Ethnic Diversity.” United States Census Bureau. Accessed September 21, 2021. https://www.census.gov/newsroom/press-releases/2021/population-changes-nations-diversity.html.

1. S cottie May, Ph.D.

Associate Professor Emerita, Christian Formation and Ministry at Wheaton College

2. Tyrell Shoemaker

Program Director at Inner City Impact Chicago

3. R ev. Jeffery Stark, D.Min

Associate Professor of Christian Ministry and Director of the Center for Theological Leadership at Olivet Nazarene University

4. Debra Sudworth

Anthem Church Chicago

5. Steve Sudworth

Anthem Church Chicago

6. R ev. Simone Twibell, Ph.D.

Assistant Professor of Intercultural Studies at Olivet Nazarene University

7. Montague R. Williams, Ph.D.

Professor of Church, Culture, and Society at Point Loma Nazarene University

When the curriculum was completed, it was sent to them via email, and they were asked to answer the following questions after reading the material:

1. What are areas of strength in this curriculum?

2. What are areas that are lacking or should be added to?

3. In 1-3 sentences, how could this curriculum make an impact?

4. Additional Comments:

Discussion of expert reviews

The reviewers identified many areas of strength in the curriculum. First, many of them named the importance of a curriculum like this in the present societal context. It is extremely relevant to be pointing toward how the Kingdom of God is manifesting and advancing in cities and urban contexts, amid diversity and racism. The focus on “neighborhood” is needed and offers kids an invitation to a theology of place. Additionally, it brings much-needed awareness and biblical teaching to racism. A second strength named in the curriculum was its organization. The reviewers thought the lessons were well-built and ideas were reinforced throughout with clear learning objectives and directions. Repetition of the same key verse with accompanying motions aids in promoting retention and internalization. Lessons themselves are just long enough to provide substantial content and many reviewers pointed to the value of the take-home sheets for families. Thirdly, reviewers appreciated the way that the curriculum supports ministry leaders. The leader devotions, ministry leader introduction, lesson objectives, and detailed instructions were all valuable.

Fourth, there was a strong Biblical emphasis carried throughout the curriculum. The narrow focus from Luke, and even further on Jesus’ teaching in Luke, was seen

as essential in navigating social issues. It is the call as followers of Jesus to live as Jesus would, so the response is then to advance God’s Kingdom rather than superficially deal with issues. Similarly, reviewers found it valuable that each lesson was placed within the perspective of God’s big story. One reviewer wrote that the curriculum had important theological affirmations as well, with pneumatology (theology of the Holy Spirit), ecclesiology (theology of the Church), and soteriology (theology of salvation) all being alluded to. Through the teachings from parables, children are invited to locate themselves within the parables. The themes of Kingdom and Neighborhood are strong, age-appropriate, and missional. Finally, the fifth strength that many reviewers named is in the activities themselves. Response stations allow children to connect the story to their own lives. The use of games, activities, response stations and final move to engage one’s neighborhood do a great job of involving the whole person and allowing all children to engage their learning preference at some point in each lesson.

In terms of what was lacking in the curriculum, or could be improved upon, there were a few themes that emerged from the reviewers. Several reviewers named some small clarity changes like making the vocabulary more understandable for children because words like “ethnic” and “race” can be hard enough for adults to understand, let alone elementary-age children. Another place to create more clarity is just by ensuring that the aim of each lesson is followed through every single step, including the games and take-home sheets.

Some reviewers also urged a deeper clarity of the purpose of the curriculum. For example, I set out to teach children how to love their neighbors, but many scholars believe that love is not something that can be taught but is rather caught through experiences, encounters, modeling, mentoring, and relationships. However, emotional awareness is something that can be taught. The concept of “teaching love” was coming through in the lessons when there should have been a greater emphasis on emotional awareness instead, especially in the debriefing times of the lessons. Additionally, small group times could have included a more intentional invitation for the kids to wonder about each parable, and each character, and even wonder why Jesus taught that parable. There would not be correct answers here; it would merely be an invitation for the kids to think deeper.

Another concern that came up in multiple reviews was an unclear focus on race and racism. The learning objective of the first lesson very clearly addressed race whereas the later lessons focused more on Kingdom inclusion. If the primary intention of the curriculum was to address racism, then it was not woven throughout. However, the primary theme coming through the curriculum was Kingdom inclusion, which is a solid foundation because it is theological. The first lesson was then reframed and rewritten to fit more into the grand scheme of Kingdom inclusion. And from that place of the Kingdom of God, racism, diversity, and other societal issues will be naturally addressed, still fitting in with the overall goal of the project. But the focus would be

on Jesus first, and then through a relationship with Christ, families will be compelled to make a difference in their neighborhoods and honor the diversity with which God has created us.

The final thing that many reviewers found to be lacking in the curriculum is its length. Repeatedly they wrote that they finished reading it and were left wanting more. One reviewer said it should be increased to six or eight weeks because it is so good. Another said it could be extended to three or six months to encompass an entire journey through Luke’s Gospel or a focus specifically on Jesus’ parables. Still another reviewer said that they hope all the content can come through in the short five weeks that it is currently because the content is so good. They would hate for any of it to be left out. Increasing the length of the curriculum was outside the scope of this project but might be done in the future.

When asked about the impact that the curriculum could have, many reviewers pointed to how it helps families, and specifically, children, move from being observers in their communities to being active members. It challenges the students to better love and care for everyone around them, not just those who look or act similarly. Specifically, the take-home sheets provide parents with guidance on how to continue the conversation at home. Many parents feel awkward or challenged when attempting to talk about diversity, and this curriculum and its accompanying take-home sheets can help families navigate that. They help families create ties between Christian faithfulness and loving neighbors. Additionally, the present curriculum helps foster children’s belief that the Kingdom of God is a place of invitation and inclusion. That their neighborhoods are places for mission. And that the parables of Jesus are places where they can orient themselves.

Reviewers recognized how significant of an impact diversity has on today’s children. The present curriculum centers the conversation in the church, on the Kingdom of God and God’s perspective on difference. These lessons help form a child’s worldview and the imago Dei (image of God) in all people. It is an incredibly timely contribution because the engaging, thoughtful, and biblical lessons will prepare and equip families to be more sensitive, aware, and knowledgeable about those who live in their neighborhoods and might differ ethnically or racially. One reviewer noted that they only became aware of the biases and issues involved in racism as an adult. So, for children to be taught about how diversity fits within the Kingdom of God in a non-threatening, non-judgmental, and Jesus-centered way is a blessing and has an exponential opportunity to have a lasting impact.

The final question asked of reviewers was if they had any additional comments. Some downloaded the curriculum and filled the margins with comments and suggestions of what to sharpen or fix. Another reviewer wisely mentioned that Jesus should be the focus and center of any action that is called for from the curriculum. The call of Jesus is not to immediately go and do likewise. It is first to follow Jesus and in doing so,

issues such as racism are confronted. This is an important concept to be aware of when writing a curriculum that will shape children’s theology of mission. Another reviewer offered commendation for tackling a project like this because they know firsthand from experience that writing lesson plans that someone else will teach is a challenging, learned skill. In their comments, they offered many tips on how to do this well. Overall, reviewers were impressed with the quality of the curriculum, and some were even ministered to personally as they read and reviewed.

Based on reviews and suggestions, the curriculum was edited, revised, and formally formatted on a design website called Canva. From there, it will be ready to distribute, publish, or send to children’s ministries to begin using with their families.

CURRICULUM

A sample curriculum lesson is provided, unformatted, in Appendix A. The fully formatted curriculum will one day be published and printed or made available on a church website for other ministries to access and use.

CONCLUSION

The U.S. is seeing its demographics change rapidly as the country becomes more ethnically and racially diverse. This is especially seen amongst the nation’s children and yet, not many churches or children’s ministry curricula are talking about it. The goal of this present project and written curriculum is to begin a conversation about how children can love their neighbors as themselves in a diversifying world, living as citizens of the Kingdom of God. It is important for this conversation to start within the church and be centered on Jesus and what He taught about the Kingdom of God in the Bible.

The curriculum was critically reviewed by seven experts in the field and was edited based on their feedback. Their feedback supports that the curriculum is a valuable contribution to the area of children’s ministry and the conversation of diversity within the Kingdom of God. The goal is that the curriculum will soon be published or made available in its entirety for ministries to begin using. Further research could include lengthening the present curriculum or producing other curricula that address the intersection of society, children’s ministry, and the Kingdom of God.

REFERENCES

Barber, Leroy. “Hurt but Hopeful.” In Red, Brown, Yellow, Black, White--Who’s More Preciouin God’s Sight?: a Call for Diversity in Christian Missions and Ministry, 163–200. New York, NY: Jericho Books, 2014.

Burggraff, Andrew. “Developing Discipleship Curriculum: Applying the Systems Approach Model for Designing Instructions by Dick, Carey, and Carey to the Construction of Church Discipleship Courses,” Christian Education Journal 12, no. 2 (Fall 2015).

DeYmaz, Mark. “The Pattern at Antioch.” In Building a Healthy Multi-Ethnic Church: Mandate, Commitments, and Practices of a Diverse Congregation, 13–26. San Francisco, CA: Jossey-Bass, 2007.

DeYmaz, Mark, and Harry Li. “Can I Pour You a Cup? Overcoming the Practical Obstacles.” In Ethnic Blends: Mixing Diversity into Your Local Church, 125–46. Grand Rapids, MI: Zondervan, 2010.

Edelman, Marian Wright. “A Letter to Faith Leaders.” In The Sea Is So Wide and My Boat Is So Small: Charting a Course for the Next Generation, 37–49. New York, NY: Hyperion Books, 2008.

Garland, Diana R. “Culture and Family Identity: Implications for Family Ministry.” In Family Ministry: A Comprehensive Guide, 333–34. Downers Grove, IL: IVP Academic, 2012.

Goff, Bob. “Introduction.” In Love Does for Kids, 1–3. Nashville, TN: Nelson Incorporated, Thomas, 218.

Hagerman, Margaret A. “American Childhoods Today: Conversations with Kids about Race.” Phi Delta Kappan 100, no. 7 (April 2019): 17–21.

Heaton, Adam. “Kids can show Prejudice and Teachers can show them another Path.” Issues in Educational Research 28, no. 4 (2018): 940–52.

Neale, David A. “Examples of Love for Neighbor and God (10:25-42).” In Luke 9-24: A Commentary in the Wesleyan Tradition, 64–71. Kansas City, MO: Beacon Hill Press, 2013.

Newbell, Trillia J., and Chase Williamson. “God Made You (And He Made Your FriendsToo!).” In Creative God, Colorful Us, 13–24. Chicago, IL: Moody Publishers, 2021.

PRRI Staff. July 8, 2021. “The 2020 Census of American Religion.” Public Religion Research Institute. Accessed September 21, 2021.

Starbuck, Margot. In Small Things with Great Love: Adventures in Loving Your Neighbor, 153–74. Downers Grove, IL: InterVarsity Press, 2011.

Swanson, David W. “Practicing Children’s Ministry of Reconciliation.” In Rediscipling the White Church from Cheap Diversity to True Solidarity, 114–31. Downers Grove, IL: IVP, an imprint of InterVarsity Press, 2020.

Tatum, Beverly Daniel. “Embracing a Cross-Racial Dialogue: We Were Struggling for the Words.” In Why Are All the Black Kids Sitting Together in the Cafeteria? 331–42. Rev. ed. New York, NY: Basic Books, 2017.

United States Census Bureau. August 12, 2021. “2020 Census Statistics Highlight Local Population Changes and Nation’s Racial and Ethnic Diversity.” United States Census Bureau. Accessed September 21, 2021.

Van Opstal, Sandra Maria. “Tension at the Table: Challenges and Opportunities in Diverse Worship.” In The Next Worship: Glorifying God in a Diverse World, 19–37. Downers Grove, IL: IVP Books, an imprint of InterVarsity Press, 2016.

Walton, John H. and Kim E. Walton. “Good Samaritan (Luke 10:25-37)” In The Bible Story Handbook, 347–50. Wheaton, IL: Crossway, 2010.

Williams, Montague R. “Introduction.” In Church in Color: Youth Ministry, Race, and the Theology of Martin Luther King Jr., 1–10. Waco, TX: Baylor University Press, 2020.

Wytsma, Ken. “Finding Ourselves in the Other.” In The Myth of Equality: Uncovering the Roots of Injustice and Privilege, 167–83. Downers Grove, IL: IVP Books, an imprint of InterVarsity Press, 2017.

APPENDIX

Week One: 4 Neighbors

THE PARABLE OF THE GOOD SAMARITAN

BIG IDEA: When we follow Jesus, we join the big, beautiful family of the Kingdom of God. OBJECTIVES:

Know: The Kingdom is a big, beautiful family

Be: a family member in God’s Kingdom

Do: go and do as Jesus did

BIBLE BASIS: Luke 10:25-37

MEMORY VERSE (for the month): ‘He answered, “‘Love the Lord your God with all your heart and with all your soul and with all your strength and with all your mind’; and, ‘Love your neighbor as yourself.’’ -Luke 10:27

Motions-

Love the Lord: make a heart with hands

Your God: points to the sky

With all your heart: put hands on your heart

And with all your soul: hands on hips like a superhero

And with all your strength: flex muscles

And with all your mind: point to temples

And love your neighbor: point out

As yourself: point towards self with thumbs

Luke 10:27: hold hands open like a Bible

LEADER NOTE/DEVOTION

So, this week’s lesson comes from Luke 10:25-37. Head on over to that and spend some time in it. Then come back to this leader’s devotion for a little bit of encouragement and challenge.

Where do you see yourself in this story? Are you like the priest and Levite? The Samaritan? Maybe at times, you feel like the man who fell and was injured. It’s an uncomfortable question to think about, but it’s important. Ask God to reveal what prejudice you may be carrying and ask for the courage to break it down and find a new and better way. Ask God for humility as you prepare to teach this lesson to your kids. Trust the Holy Spirit to imprint this week’s message on the hearts of your kids, inspiring transformation through ripples of change that we won’t often see and understand this side of Heaven.

PREP INSTRUCTIONS

Feel free to move around the elements of the lesson to best fit your children’s worship service.

Supply List:

• PowerPoint/Slides with worship songs and images for lesson

• 4 cardboard boxes painted to look like different types of homes (more details below)

• Kids’ prayer journals and pens/pencils

 [*Note: every child should receive their own prayer journal. A small notebook that they will put their name on and keep at church. They will use it to write (or draw) prayers to God or record things they believe God is telling them.]

• Construction paper/Scissors/Glue/Markers

• Bibles (one per child)

OPENING ACTIVITIES AS KIDS COME IN

If your budget allows, purchase some new board games and card games for this unit to have out during free time before or after the lesson. Some ideas include:

• Mister Rogers’ Neighborhood: The Game (younger kids)

• Friends and Neighbors: The Helping Game (younger kids)

• Sesame Street: Neighborhood Journey Board Game (younger kids)

• Monopoly (older kids)

• Games Specific to Your City:

 S ome Chicago examples

 LOOP: The Elevated Card Game (older kids)

 Puzzles of your City (age is dependent on the difficulty of the puzzle)

 Chicago-Opoly

LARGE GROUP LESSON

Alright, welcome to [kids program name] today! I’m so glad to see you all and get to learn about and worship God together this morning. I want to hear the best part of your week! Raise your hand and tell me what it was. [allow several children to answer, depending on time. Affirm them and try to include the whole group even if only a couple of children speak]

Worship (a fun, upbeat song would be fitting here)

Announcements (any upcoming things the students should be aware of)

Offering (talk about where the children’s offering goes and pray over it)

Today we are starting a new series that we are going to be talking about this month. It’s called Meeting Jesus Next Door! Let’s play a little game about neighborhoods.

Intro Game/Activity: 4 Neighbors

This game is just like 4 corners, with a neighborhood spin!

Instead of numbered corners, make each corner a different neighborhood or house style.

Beforehand, paint cardboard boxes to look like different styles of homes. They can be different styles of homes you would find in your neighborhood (like apartments, townhomes, single-family homes, studios, duplexes, etc.) or different types of homes from around the world (such as American apartment buildings, Syrian courtyard houses, South African Cape Dutch architecture, Hanok traditional Korean houses, Mexican adobe houses, Irish stone cottages, English thatched cottages, Chinese Sihe yuan houses, central Asian yurts, Dutch canal houses, German timber-frame houses, Vietnamese tube houses. This list could go on and on! Do a quick online search for some more inspiration).

Your cardboard houses do not need to be art museum quality. Just put together some simple models. Another option is to print pictures of 4 different homes/neighborhoods, or even put them up on the screen and then just label each corner with the corresponding names. The goal is to show the kids that different people live in all sorts of different places. After you choose the types of homes, make sure you have done a little bit of research on them so that you can tell your students about them. Point to the aspects of these homes that are unique or different than what your students are used to. Explain why those differences make sense in that culture. This is a beautiful opportunity for you and your students to learn about other cultures and how people live in different ways.

Directions-

1. Divide kids evenly into the 4 neighborhoods (corners)

2. Do a practice round with the leader in the middle

3. The person in the middle closes their eyes and slowly counts down from 10 to 0

4. While they are counting, the kids can stay where they are or quietly move to another neighborhood

5. If people are still moving when the player in the middle finishes counting, they must sit down

6. After counting, the player in the middle points to a neighborhood (corner) while their eyes are closed, and then opens their eyes. All players at that corner must sit down

7. If the corner pointed to has no players, ALL players sitting down anywhere can get up and rejoin the game

8. When only one player is left standing, they become the counter for the next round.

9. Play additional rounds as time allows

Lesson

Great job guys, that was fun! It was cool to learn a little bit about different types of homes and neighborhoods without even leaving church! It reminded us that there are all sorts of people, and not everyone lives the same way we do. Sometimes when we haven’t seen the way that different people live, it’s easy to think that the way we live is the only way. But that’s not true. There are all sorts of different people around the world, and even in our own city!

In our Bible story today, we are going to see how Jesus wants us to treat people who are different.

Teaching Time

Raise your hand to show me if you’ve ever heard about the Kingdom of God before? Okay, awesome! It sounds a little weird because we aren’t used to kingdoms, right? We don’t have a king or queen in the U.S. and so lots of us don’t know how kingdoms work. But God’s Kingdom looks totally different than anything else we have ever heard of before!

Let’s look at our memory verse for the month. [put it on the screen]. I’m going to read it out loud and all my volunteers are going to come up and join me to teach you the motions. [do it once as leaders. Then have the kids stand up and do it twice as a whole group.]

Every Sunday this month, we will learn more about how the Kingdom of God works and how we get to be family members in it. We’re going to learn about it through some of the parables of Jesus. Who knows what a parable is? [allow for a few answers if kids know] Yeah, great job! Parables are stories that Jesus used to tell his listeners what the Kingdom of God is like. Jesus told these stories to invite people to see what God was doing in the world from a new perspective. As we read them today, they still show us what God is doing in our world. The Bible is the Word of God, and it is just as meaningful today as it was when each part of it was written.

The parable we’re going to look at today comes from Luke 10, verses 25-37. Is Luke in the New Testament or the Old Testament? That’s right, the New Testament!

Alright, go ahead and grab your Bible and let’s turn there together. So, remember, Luke is in the New Testament so it’s in the back half of your Bible and it’s one of the Gospel books so it’s towards the beginning of the New Testament. In Luke, look for the big number 10 and the little number 25. Once you get it, put your bookmark and in hold your arms up in the shape of a house so I know you’re ready. [have volunteers and preteens go around and help kids find it]. Yay, great job guys! You can put your arms down and open your Bible back up. [If it fits your ministry set-up, you can also put the Biblical text on the screen.]

Let’s read verses 25-28

25 One day an authority on the law stood up to test Jesus. “Teacher,” he asked, “what must I do to receive eternal life?”

26 “What is written in the Law?” Jesus replied. “How do you understand it?”

27 He answered, “‘Love the Lord your God with all your heart and with all your soul. Love him with all your strength and with all your mind.’ (Deuteronomy 6:5) And ‘Love your neighbor as you love yourself.’” (Leviticus 19:18)

28 “You have answered correctly,” Jesus replied. “Do that, and you will live.” Did you all notice that we just read our memory verse for the month? This is where it comes from! Let’s stand up and say it once more together. [say the verse and have it on the screen] Awesome job, now go ahead and take a seat.

Let’s look at what comes next in our story. The lawyer was not entirely satisfied with Jesus’ answer about how to inherit eternal life; he wanted to know for sure what would happen when he died and how he could be absolutely certain he would get to Heaven. S o, the lawyer asked, “And who is my neighbor?” This is where the parable begins!

Jesus tells a story of a man who was traveling down from Jerusalem to Jericho. [show a picture of what this road looks like]. This is what it looked like when Jesus told this story. Here in Chicago [or name of the city you’re in, if applicable], we do not have any mountains, and we hardly even have any hills! Has anyone been somewhere that has big mountains? [allow for a few short answers]. Yeah! Could you imagine having to walk SEVENTEEN MILES down a mountain, through the wilderness, where robbers sometimes like to hide? It would be kind of scary, and really hard!

So, this man who was walking – can everyone move their feet while you’re sitting to pretend that you’re walking? – so this man was walking down the road when he was attacked by some of the robbers that were hiding in the forest. He was hurt and the robbers left him there all alone. Can everyone hold up a number one? The injured man is the FIRST character we want to remember in our story today.

Now, lots of people had to walk up and down this road because it was the only way to get between the cities of Jerusalem and Jericho. So not very much time passed before a priest walked by. Can everyone hold up a number two? Great! The priest is the SECOND character to remember in our story. At that time, priests represented God and were very respected people. It would have been nice of the priest to stop by and help the injured man, but instead, he crossed all the way to the other side of the road and kept walking so he wouldn’t have to talk to the injured man.

A little while later, another man walked by. Okay, last time you held up a number two, now make it a number three. We’re about to hear about the THIRD character in our story. This time, he was a Levite which meant he was also a religious person. But

once again, the Levite saw the injured man, crossed to the other side of the road, and kept walking without stopping to help.

Finally, one more man walked by. So now turn your number three into a number four; hold up four fingers. Great job! Who are the FOUR characters in our story? (Allow for answers: 1- the man who was hurt, 2- the priest, 3- the Levite, 4- this one/ the Samaritan). Okay, you can put your hands down now. Something was different about the man walking by this time. He was a Samaritan. He came from a different racial and ethnic group than the other Jewish people.

Those are some pretty big words. They mean that the Samaritan man (our 4th character) looked different than the first 3 characters. He lived his life differently than them and had a different religion. He had a different culture. Culture is the way that different people live. It can be their food, the way they dress, the language they speak. Anything that makes that group of people who they are!

It reminds me of our 4 Neighbors game earlier. We saw that different people live in different types of homes. That can be part of their culture, too. Can anybody tell me something about their own culture? [allow for a couple of short answers. Maybe even call on a few volunteers and share something from your own culture, too.] It is so beautiful to learn these things about you!

Unfortunately, sometimes when people don’t understand why other people are different, they get mad at each other. They don’t treat each other fairly. But in our Bible story today, Jesus shows us that people who are different actually can care for each other!

Remember the hurt man (our first character) that is still lying on the side of the steep road? Well, when the Samaritan man walked by (our 4th character), he stopped to care for the hurt man. It did not matter that he was different. He just saw somebody that needed help, so he helped.

Let’s open our Bibles back to where your bookmarks are and finish reading the story. We’ll start at verse 33, the little number 33, and read through verse 37.

33 But a Samaritan came to the place where the man was. When he saw the man, he felt sorry for him. 34 He went to him, poured olive oil and wine on his wounds and bandaged them. Then he put the man on his own donkey. He brought him to an inn and took care of him. 35 The next day he took out two silver coins. He gave them to the owner of the inn. ‘Take care of him,’ he said. ‘When I return, I will pay you back for any extra expense you may have.’

36 “Which of the three do you think was a neighbor to the man who was attacked by robbers?”

37 The authority on the law replied, “The one who felt sorry for him.”

Jesus told him, “Go and do as he did.”

The Samaritan man did not let his differences get in the way of helping and loving other people. There were 4 different people in our story, 4 neighbors. They were all close to each other, but they didn’t all love each other. Jesus finishes the story by saying, what… right at the end of verse 37? [allow them to shout it out] That’s right, “Go and do as he did!”

When we follow Jesus and have a relationship with Jesus, he invites us to act like Him, too. In the Kingdom of God, Jesus shows us how to act the opposite way that most people in our world act. Jesus modeled it first when He died on the cross! Jesus died on the cross for our sins. It was the ultimate act of loving His neighbors. He loved the people who were different from Him, so much so that He died so we wouldn’t have to.

In the parable we learned today, the Samaritan man showed that kind of love too. And guess what? By following Jesus, we also get to love people who are different. We get to love everyone as if they were part of our family. Because in the Kingdom of God, we are all a part of God’s family!

When we follow Jesus, we join the big, beautiful family of the Kingdom of God. What are some ways that we can care for people who are different than ourselves? (Have several children answer. Have a few of your own answers in mind too, if they’re slow to get going at first.)

Worship Song (choose one that relates to loving God and loving others) Send the kids to their small groups.

1. What new words did you discover today?

1. (Ex : parable, Kingdom of God, culture, neighbor, Samaritan, etc.)

2. What is happening in the passage we studied?

3. Why do you think Jesus told this parable?

4. How does today’s Bible story fit into God’s BIG story?

1. (Ex : Parables teach us how to see what God is doing in the world from a new perspective.)

5. What does today’s lesson tell us about God?

6. What does today’s lesson say about us?

a . (Ex : We are family members in the Kingdom of God)

b. Emphasize that the culture of each child is valued and important! Allow each one to share a little bit about their culture (Leader, you too!).

From small groups, have leaders dismiss the kids to prayer stations. Each leader will have their group’s prayer journals and hand these to them before sending them to the stations. Play soft worship music in the background.

PRAYER & REFLECTION STATIONS:

Journal Station: kids can write prayers to God in their journals and record what they believe God is telling them.

Bible Station: allow kids to take another look at today’s Bible story on their own. Have a small sign with the reference to it.

Art Station: 1) allow kids to create their own neighborhood from their imagination or make a replica of their real one. They can do this by drawing it on paper or cutting and gluing pieces of construction paper. 2) Alternatively, have coloring sheets of the church’s city/neighborhood or just a generic neighborhood. For either option, instruct the kids to be praying quietly for their neighborhood as they work.

At the end of prayer time, instruct kids to quietly come back to their seats. Pray as a group, then do a closing prayer.

Show a slide of the big idea one more time.

When we follow Jesus, we join the big, beautiful family of the Kingdom of God. Have a fun video related to the lesson to show at the end as kids wait to be dismissed. (Something along the lines of kids from different races/cultures/ethnicities doing things together)

Give a discussion guide to every family as they come to pick up their kids.

Weekly Take Home Sheet

WEEK ONE: 4 NEIGHBORS

The Parable of the Good Samaritan

BIG IDEA: When we follow Jesus, we join the big, beautiful family of the Kingdom of God.

OBJECTIVES:

Know: The Kingdom is a big, beautiful family

Be: a family member in God’s Kingdom

Do: go and do as Jesus did

BIBLE BASIS: Luke 10:25-37

MEMORY VERSE (for the month): ‘He answered, “‘Love the Lord your God with all your heart and with all your soul and with all your strength and with all your mind’; and ‘Love your neighbor as yourself.’’ -Luke 10:27

Motions-

Love the Lord: make a heart with hands

Your God: points to the sky

With all your heart: put hands on your heart

And with all your soul: hands on hips like a superhero

And with all your strength: flex muscles

And with all your mind: point to temples

And love your neighbor: point out

As yourself: point towards self with thumbs

Luke 10:27: hold hands open like a Bible

FAMILY ACTIVITY: Go on an “I-Spy” prayer walk of your neighborhood as a family. Play the game, “I spy with my little eye…” and then once the family spies it, pray together for what you see. Look for the places God is already at work in your neighborhood. Pray for the people in each house that you walk by. Pray for the workers in the businesses that you walk by. Pray for eyes to see more clearly what God is doing in your neighborhood. Thank Jesus for the ways that He loves your family and your neighborhood! And pray for courage to love your neighbors like Jesus loves them.

Also, choose some of the books from the resource list to read together. Have open conversations with your kids about their own culture and how Jesus invites everyone to be a family member in the Kingdom of God. Allow them to ask questions and process with you. Pray together, bringing any of their concerns (if they have them) to God and thanking God for the beautiful ways He has created your children.

DINNERTIME QUESTION: How does learning about the Kingdom of God help us understand God’s desire for people who are different than us? (It gives us hope and reminds us that God loves everyone. We can be like Jesus and love our neighbors, etc.)

Evaluating College Students’ Health Literacy and its Effects on Their Perceptions of Information Concerning Mask-wearing in the COVID-19 Pandemic

ACKNOWLEDGEMENTS

Thank you to Dr. McLaughlin for coming alongside my project from the beginning and guiding me through the last two years with wisdom and encouragement. Thank you for your constant support and always instilling confidence and providing reassurance when things seemed impossible. Thank you to Dr. Himes, Dr. Perabeau, Dr. Brown, Dr. Sharda, Dr. Schurman, Dr. Case, Dr. Vander Schaaf, and the Olivet Nazarene University Honors Program for fostering my curiosity in the world around me and cultivating my passion for knowledge. Thank you to my parents for always believing in me and my abilities and thank you to my classmates and peers for supporting my project. Thank you also to Mark Pickering for assisting with the data analysis process, which was integral to drawing my conclusions and finishing my work.

ABSTRACT

Background

Mask-wearing was a controversial and polarizing phenomenon during the COVID-19 pandemic. Beliefs concerning mask-wearing differed depending on sources of information concerning the pandemic, levels of health literacy, political leaning, demographics, or other factors. This project attempted to connect college students’ level of health literacy to their understanding of and adherence to mask-wearing in the COVID19 pandemic. There is a gap in research connecting health literacy to understanding information concerning pandemics and an even bigger lack of studies conducted that relate college students’ health literacy to their perception of illnesses or pandemics. It is important to understand the impact of public health literacy on intake of information about illnesses and pandemics for future health crises to avoid polarization and the spread of misinformation.

Methods

An IRB-approved qualitative survey was sent to the entire student population of Olivet Nazarene University consisting of three sections: evaluation of health literacy, knowledge and adherence to masks-wearing, and demographics and psychographics. The survey received 262 responses over three weeks. Out of the 262 responses, 234 qualified for analysis. The results were compiled into a coded spreadsheet and R-studio was used to draw correlations.

Results

219 students were evaluated as having “adequate” health literacy, and among those students twenty were determined to have a “correct” level of knowledge of and attitude toward mask-wearing. Twelve students were evaluated as likely having limited health literacy and three students as most likely having limited literacy. Females were more likely to wear masks than males, and Democrats and Independents were more likely to wear masks than Republicans. Of students with adequate health literacy, most obtained information about the pandemic through the internet, news websites and apps, and social media, and students who had a likelihood of having limited health literacy obtained most of their information from social media and the internet.

Conclusions

Health literacy did not have a statistically significant impact on a college student’s perception of mask-wearing in the COVID-19 pandemic. Sources of information like social media were used more by students with low to limited health literacy, whereas the internet and news websites and apps were consulted more by students with a higher

level of health literacy. The implications of these results show that the public’s level of health literacy may have little to no impact on polarization and controversy surrounding the pandemic.

Keywords: health literacy, mask-wearing, COVID-19, college students, misinformation

LITERATURE REVIEW

Introduction

Throughout the COVID-19 pandemic, misinformation surrounding the disease was conveyed through news outlets and social media platforms (Scherer & Pennycook, 2020). Mask-wearing became a topic of debate regarding its effectiveness of preventing viral spread, as well as their mandated use in public settings being a violation of people’s rights (Ike et al., 2021; Taylor & Asmundson, 2021). Because of these phenomena created by the pandemic, the need for research concerning public health literacy, media bias, and misinformation has increased significantly.

Health literacy is the extent that one can differentiate information related to health and wellness and incorporate it into one’s own knowledge for decision-making (Health literacy in healthy people 2030, n.d.). Its effects on public perception and knowledge of a global pandemic is a new field of research, and there is a large need for data and analysis to strengthen the results of other studies (Banker & Park, 2020; Haischer et al., 2020; Silva & Santos, 2021). Additionally, college communities are rife with various illnesses, and it is crucial to understand how to effectively educate college-aged adults on important health topics. If health literacy is a factor in information absorption, it must be addressed in future research in order to educate college students successfully and perhaps decrease illness on college campuses. This project will address the correlation between college students’ level of health literacy and its influence on their knowledge of and adherence to mask-wearing during the COVID-19 pandemic.

Health literacy

Recent studies have taken the opportunity presented by COVID-19 to analyze health literacy in relation to the pandemic. A survey by Hornik et al. (2021) analyzed how misinformation as a factor in the public’s adherence to suggested preventative measures compared to levels of health literacy and determined that proper education and promotion of the benefits of the health measures were more effective than misinformation (Hornik et al., 2021). A separate study by Silva and Santos (2021) also illustrated how a higher level of health literacy made college students more likely to have better perceptions of preventative measures for COVID-19. However, there have been no studies thus far that have researched health literacy and adherence to mask-wearing during the pandemic, only about how health literacy affects the broad concept of preventative

measures against COVID-19. Conducting a survey focusing on health literacy and mask-wearing will create new data and contribute to existing data collected about preventative measures against COVID-19.

In addition, there are currently few studies correlating college students’ health literacy with their sources of information, but one study did so for adolescents. Ghaddar et al. (2012) measured a group of South Texas high school students’ level of health literacy using the Newest Vital Sign (NVS) tool and eHealth literacy using the eHealth Literacy Scale (eHEALS) tool and compared the results to whether the subjects had ever heard of MedlinePlus®, a resource provided by the school district for finding credible information concerning healthcare. The study found that the students who had been exposed to MedlinePlus® had a higher eHEALS score and were more likely to seek out information about healthcare (Ghaddar et al., 2012).

Mask-wearing

Wearing a mask during the pandemic was one of the key factors in decreasing spread of the virus. Joo et al. (2021) provides evidence of mask mandates being effective in decreasing hospitalization rates associated with COVID-19. By examining mask mandates in ten different states from March 2020 to October 2020, they found that hospitalization growth due to COVID-19 decreased by 2.9 percent after the first two weeks of the mandate being enforced among 40–64-year-old adults. After mask mandates had been in place for longer than three weeks, the transmission rate declined by 5.5 percent among the age groups of 18–39- and 40–64-year-olds (Joo et al., 2021).

Kanu et al. (2020) focused on the correlation between Delaware’s mitigation measures of COVID-19 and hospitalization and death rates concerning COVID-19 between March and June 2020. When the mask-mandate was introduced along with contact tracing, hospitalization related to COVID-19 decreased by 88% and mortality decreased by 100% (Kanu et al., 2020). Van Dyke et al. (2020) examined data from Kansas and each county’s level of state-wide mask mandate compliance from June 1 to August 23, 2020. Twenty-four of Kansas’s 105 counties complied with the mask mandate, and the remaining eighty-one counties opted out. They found that COVID-19 cases decreased overall in the counties with a mask mandate and increased overall in counties without a mask mandate (Van Dyke et al., 2020).

There are many factors that influenced wearing masks. Banker and Park (2020) evaluated different online ads by the Centers for Disease Control (CDC) promoting protective measures against COVID-19. They found that ads emphasizing using protective measures to ensure the safety of “loved ones” as well as ensuring one’s own safety were more effective than promoting community safety and health (Banker & Park, 2020). This study raised the question of whether participants’ level of health literacy is as effective as emotions in decision-making concerning health habits like wearing a mask. According to Ike et al. (2021), common beliefs concerning mask-wearing

during the pandemic differed: for some, masks symbolized their faith in science and goodwill towards others, and for others, they symbolized control by the government and loss of personal freedoms. Taylor and Asmundson (2021) examined the different reasons behind negative attitudes towards masks. In a survey done in both the US and Canada, they found that 16% of the subjects did not wear masks, with their reasonings varied between the idea that masks are ineffective against COVID-19 and “psychological reactance . . . an aversion to being forced to wear masks” (Taylor & Asmundson, 2021).

Demographics also influence how likely someone is to wear a mask. According to a study that observed shoppers of multiple retail stores from June 2020 to August 2020, females were more likely than men to wear masks, older people were more likely than younger people to wear masks, and people in cities were more likely to wear masks than people in rural areas (Haischer et al., 2021). Additional demographic data for mask-wearing adherence was found through a survey conducted by Pew Research Center that supported these demographics and highlighted additional demographics such as political affiliation and race (Kramer, 2020). For instance, Republicans were 16% less likely to wear masks than Democrat subjects, and Caucasian subjects were 8–9% less likely to wear masks than Black, Hispanic, and Asian subjects.

RESEARCH QUESTIONS AND HYPOTHESES

RQ1: How does health literacy of college students influence their knowledge of and adherence to mask-wearing in the COVID-19 pandemic?

RQ2: How do sources of information influence health literacy concerning COVID19?

RQ3: How do demographics influence adherence to mask-wearing guidelines in the COVID-19 pandemic? Does gender have an effect on either or both knowledge and adherence to mask-wearing? Is there an interaction between gender and political party that influences knowledge and/or adherence to mask-wearing? Are there preferred sources of information about the COVID-19 based on gender?

H1: Students who score a high probability of health literacy on the NVS tool will be more apt to have a higher level of knowledge and adherence to mask-wearing in the COVID-19 pandemic.

H2: Students who receive most information concerning COVID-19 from social media have lower health literacy than students who receive their information from other COVID-19 information sources.

H3: R esults will correlate with the results of Haischer et al. (2021). Females will be more likely than males to wear masks. It was also hypothesized that students of higher health literacy will be more likely to adhere to mask-wearing guidelines.

METHODOLOGY

This study surveyed all students attending Olivet Nazarene University. It was sent out after being approved by the Olivet Nazarene University IRB board for three weeks between April and May of 2022. The study was separated into three parts after the informed consent, similar to the study created by Silva and Santos (2021). The informed consent ensured the participants agreed to have their answers recorded and analyzed, and that they were above the age of 18.

The first portion of the survey assessed participants’ health literacy using the NVS instrument (Shah et al., 2010; Silva & Santos, 2021). The NVS is a three-minute survey using six questions to determine the subject’s health literacy. The subject’s level of health literacy is determined by the number of correct answers; specifically, zero to one correct answers indicated a high probability of a low health literacy, two to three correct answers indicated only a possibility of a low level of health literacy, and four to six correct answers indicated a high probability of an adequate level of health literacy. The NVS was devised by Pfizer and has been used since 2005. According to the U.S. Department of Health and Human Services, no permission is needed to utilize the NVS if it is not modified or translated (U.S. Department of Health and Human Services, 2021). There are several studies that validate its usefulness in measuring health literacy for HIV (Kordovski et al., 2017), for family medicine (Shah et al., 2010), and COVID-19 preventative strategies (Silva & Santos, 2021).

The second part of the survey used a questionnaire to evaluate participants’ level of knowledge of masks, with questions modeled after the official CDC guidelines for wearing masks (Centers for Disease Control and Prevention., n.d.) and their adherence to mask-wearing. Level of knowledge was analyzed using a 5-point Likert scale based on participants’ level of agreement (from strongly disagree (1) to strongly agree (5)) in six various factual statements concerning functions of masks written based on CDC guidelines. A response to these Likert-scaled questions was considered correct if the participant answered 4 or 5 (agree or strongly agree) and incorrect if they answered 1–3 (strongly disagree, disagree, or neutral). If the subject answered five out of six statements correctly, they were considered to have an adequate level of knowledge of masks. Their attitude toward masks was also assessed by a 5-point Likert scale on seven statements based on how often (never (1) to always (5)) the participants’ complied to mask suggestions/requirements. A response to these Likert-scaled questions were considered correct if the participant answered 4 and 5 (often or always), while 1–3 were considered incorrect (never, rarely, or sometimes). Six out of seven statements answered correctly indicated an adequate attitude toward masks. The entire second portion of the survey was patterned after the Silva and Santos (2021) knowledge and attitudes section of their survey and adapted to US CDC guidelines, specific to mask-wearing. The CDC guidelines for masks were updated frequently as the pandemic continued

and science developed. The questions were developed to be accurate according to the CDC guidelines at the time the survey was sent.

The third portion evaluated the demographics and psychographics of the participants such as age, gender, whether they or a loved one had been affected by COVID19, and where they typically derived their information (TV news, news websites, social media like Twitter, Instagram, etc.). The participants’ hometowns were also evaluated for being rural or urban. One Pew Research Center study analyzed how often Americans get their news from social media through a randomized survey (Walker & Matsa, 2021). Some of the questions from this survey about sources of information were utilized, but not all due to survey length. The original survey by Walker and Matsa (2021) was created and reviewed rigorously by the Pew Research Center and had an error percentage of 1.4% of an unweighted sample size of 11,178 participants, making it a reliable survey from which to derive questions for this survey. A total of 262 students participated in the survey over three weeks. Two of the responses were eliminated from the data due to underage responses (when asked their age, two responses answered 17 years old), and twenty-eight responses were unable to be analyzed due to their responses of “Prefer not to answer” for certain demographics which eliminated them from the data analysis pool. The results from the survey were compiled into a spreadsheet, binarily coded, and analyzed using R studio and ANOVA functions. A p-value of less than or equal to 0.05 was used to determine statistical significance.

RESULTS

Health literacy and mask-wearing

Out of the 234 responses that were eligible to be analyzed, 219 (93.59%) students were determined to have a high probability of adequate health literacy. Twelve (5.13%) students had a possibility of adequate health literacy, and three (1.28%) students had a high probability of low health literacy.

Out of the 234 responses that were eligible to be analyzed, seventy-five (32.05%) had an adequate level of knowledge about mask-wearing, and 159 (67.94%) had an inadequate level of knowledge about mask-wearing. Out of the 234 responses that were eligible to be analyzed, thirty-seven (15.81%) students had an adequate level of adherence to mask-wearing and 197 (84.19%) had an inadequate level of adherence to mask-wearing.

Of the 219 students that were determined to have a high likelihood of adequate health literacy, seventy (31.96%) were determined to have an adequate level of knowledge of mask-wearing and twenty-eight (12.78%) were determined to have an adequate level of adherence to mask-wearing in the COVID-19 pandemic. Twenty (9.13%) had both adequate levels of knowledge and adherence to mask-wearing ( Table 1). Fifty (22.83%) students had an adequate level of knowledge and an

Table 1

Interactions between adherence to and knowledge of mask-wearing in the COVID-19 pandemic in students who scored a high likelihood of adequate health literacy according to the NVS tool.

Adequate level of adherence

Inadequate level of adherence

Total

inadequate level of ad herence to mask-wearing, and eight (3.65%) students had an inadequate level of knowledge with an adequate level of adherence (Table 1). Of the 219 students with a high likelihood of adequate health literacy, 141 (64.39%) had inadequate levels of both knowledge and adherence to mask-wearing in the COVID-19 pandemic (Table 1).

Of the students who had a high likelihood of adequate health literacy, there was no significant relationship between health literacy and level of knowledge of mask-wearing beyond what is expected by chance (p=0.918). Health literacy also did not impact the subject’s adherence to mask-wearing beyond what is expected by chance (p=0.121). However, gender played a much larger role in adhering to mask-wearing during the pandemic.

Demographics

Gender

Regardless of health literacy, females were much more likely to wear masks than males. The average knowledge of masks of females was 0.3657, and the average of the males was 0.1864, indicating that females know more about masks than what is expected by chance (p=0.0051). Similarly, the relationship between gender and adherence towards mask-wearing indicated females (avg=0.1657) had a higher score than males (avg=0.0508) (p=0.00494), also indicating a significant difference beyond what is expected by chance. These results are similar to the Haischer et al. (2021) study, which found that females are more likely to wear masks than males.

Multiple significant relationships were found between gender and the various sources (Figure 1). The average of female subjects who obtain information from television was 2.6971, whereas the average of male subjects receiving information from television was 2.0678, indicating that females seem to rely on television more than males beyond what is expected by chance (p<0.001). Similarly, the female average of listening to the radio for information was 1.9657, while the male average was

1.6271, with females listening to the radio more than males beyond what is expected by chance (p=0.0188). Females (avg=2.2171) were more likely to obtain information about COVID-19 from print sources than males (avg=1.7288) (p=0.0018). Females (avg=3.5086) were also more likely to consult news websites or apps than males (avg=3.0847) (p=0.0070). Social media was significantly used by more females (avg=3.5314) than males (avg=2.9661) (p<0.001). The only source of information that males consulted more than females was podcasts, with the male average being 1.9661 and the female average as 1.6000 (p=0.012). There was no significant difference between the genders in consulting the internet as a source of information about COVID-19 (p=0.2540).

Political leaning

Political affiliation also had a significant relationship to knowledge about mask-wearing, beyond what is expected by chance (p=0.0117). Students who identified as Democrats were most likely to have an adequate knowledge of masks. After Democrats, the independent students and students with no political affiliation were likely to have an adequate knowledge of masks. Republican students were last, being least likely to have an adequate knowledge of masks. There was not a significant relationship between political party and adherence to mask-wearing beyond what is expected by chance (p=0.0523). Kramer (2020) found similar results in the Pew Research Center survey about demographics and mask-wearing with Democrats being more likely than Republicans to wear masks; however, in this study, Democrats were more likely to have adequate knowledge rather than adherence.

Sources of information

Although connecting the subject’s preferred sources of information about COVID19 with health literacy was not the primary intent of this survey, the responses yielded interesting results. According to the responses (Figure 2), those with a high probability of high health literacy mostly obtained their information concerning COVID-19 from the internet, news websites or apps, or social media. Those with a probable lower level of health literacy mostly obtained their information from social media as well as the internet and news websites or apps.

DISCUSSION AND RECOMMENDATIONS

In the future, a more diverse population with varied backgrounds in terms of education level and socioeconomic level could produce different results. Because Olivet Nazarene University students all have a higher likelihood of having similar socioeconomic levels due to the tuition rate, the level of variation in responses is not as high as a randomized survey sent out to a larger population at a state school, community college, or one with a higher likelihood of students with varied backgrounds. Also, because college students have a higher education level than those who did not graduate high school or obtain a GED, it would be intriguing to see how different education levels impact level of health literacy. Additionally, there were too few rural students for significant correlations to be drawn from the data set, so it is possible that a larger, randomized population’s responses to the survey would be similar to the results from Haischer et al. (2020).

Even though this survey was specifically created to determine the influence of health literacy on mask-wearing in the COVID-19 pandemic specifically with college students, the results of this survey being sent out to a randomized population with varied levels of education would possibly yield different results. The results from sending this survey out to a completely randomized population could help predict influences on the general public’s health literacy for future health crises as well, not just college students. With varying levels of education and health-literacy, it would also be interesting to see if the connections to sources of information about the COVID-19 pandemic would remain consistent or change at all.

It would seem reasonable that the logical correlation between one’s level of health literacy and complying to scientific recommendations to wear a mask during a global pandemic would be positive, but there may be more to be researched about the human need for unfiltered communication. Perhaps there is a stronger connection between human willpower and need for relationship that can overpower knowledge of scientific fact. A study by Crandall et al. (2022) suggests that masks don’t affect human interaction during a short period of time, but it is possible that the duration of masks being worn could be an unknown factor that the pandemic exacerbated.

CONCLUSION

After analyzing the results of the survey, the main hypothesis of this project was disproven. The students with the highest likelihood of adequate health literacy were no more likely to have a higher level of knowledge of or adherence to mask-wearing in the COVID-19 pandemic than students with a lower likelihood of adequate health literacy since there was no significant relationship between health literacy and level of knowledge or adherence. However, significant relationships were found between demographics of the participants and their knowledge of and adherence to mask-wearing in the COVID-19 pandemic. It was also observed that the students in each of the three levels of health literacy consulted different main sources of information pertaining to the COVID-19 pandemic.

The main intent of this project was to observe how a college student’s level of health literacy affected their knowledge of mask-wearing in the COVID-19 pandemic as well as their adherence to mask-wearing in order to find a pattern to apply to future health crises. If health literacy indeed has an effect on the public’s understanding and application of a specific health issue, information could hopefully be spread and understood faster and easier. Due to the population of the survey having little diversity in terms of health literacy level, it is difficult to draw definitive conclusions from the data set, but with more research conducted on the subject,

hopefully controversy and polarization decrease in future health crises and information can be spread more quickly and be understood better by the public. It is naïve to believe that COVID-19 will be the last pandemic or even wide-spread illness, so preparing for how to handle the distribution of knowledge and increasing adherence to health measures is key to succeeding in the future.

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APPENDIX

Survey Questions:

First part of the survey: Use the image below to answer the following questions.

This information is on the back of a container of a pint of ice cream.

1. If you eat the entire container, how many calories will you eat?

2. If you are allowed to eat 60 grams of carbohydrates as a snack, how much ice cream could you have?

3. Your doctor advises you to reduce the amount of saturated fat in your diet. You usually have 42 g of saturated fat each day, which includes one serving of ice cream, how many grams of saturated fat would you be consuming each day?

4. If you usually eat 2,500 calories in a day, what percentage of your daily value of calories will you be eating if you eat one serving?

5. Pretend that you are allergic to the following substances: penicillin, peanuts, latex gloves, and bee stings.

6. Is it safe for you to eat this ice cream? (Skip Question 6 if you answered ‘yes’.)

7. If no, why not?

Second part of the survey: Overall, how much trust do you have in the following statements?

1. Masks are effective in decreasing the transmission of SARS-COV2 when worn consistently and correctly.

a. Strongly Disagree

b. Disagree

c. Neutral

d. Agree

e. Strongly Agree

2. If you are not up to date with your vaccine, you should wear a mask.

a. Strongly Disagree

b. Disagree

c. Neutral

d. Agree

e. Strongly Agree

3. If you are fully vaccinated but have a weakened immune system, you should wear a mask.

a. Strongly Disagree

b. Disagree

c. Neutral

d. Agree

e. Strongly Agree

4. Masks are safe for people with asthma.

a. Strongly Disagree

b. Disagree

c. Neutral

d. Agree

e. Strongly Agree

5. Wearing a mask does not raise the level of CO₂ in the air you breathe.

a. Strongly Disagree

b. Disagree

c. Neutral

d. Agree

e. Strongly Agree

6. If you are sick with COVID and need to be around others, you should wear a mask.

a. Strongly Disagree

b. Disagree

c. Neutral

d. Agree

e. Strongly Agree

How often do you:

1. Wear a mask that completely covers your mouth, nose, and chin?

a. Never

b. Rarely

c. Sometimes

d. Often

e. Always

2. Wear a mask where it is mandated?

a. Never

b. Rarely

c. Sometimes

d. Often

e. Always

3. Wear a mask at crowded social events?

a. Never

b. Rarely

c. Sometimes

d. Often

e. Always

4. Wear a mask when social distancing wasn’t possible?

a. Never

b. Rarely

c. Sometimes

d. Often

e. Always

5. Wear a CDC-approved mask (clean cloth with two or more layers of washable, breathable fabric, surgical mask, KN-95, N-95)?

a. Never

b. Rarely

c. Sometimes

d. Often

e. Always

6. Wear a mask outdoors in areas of low-transmission for protection against COVID-19?

a. Never

b. Rarely

c. Sometimes

d. Often

e. Always

7. Wear a mask on public transportation (planes, buses, trains, and other forms of transportation) when traveling?

a. Never

b. Rarely

c. Sometimes

d. Often

e. Always

Third part of the survey:

Finally:

1. What is your age?

a. Fill in the blank

2. What is your gender?

a. Male

b. Female

c. Prefer not to answer

3. What is your race?

a. White

b. Black or African American

c. Hispanic or Latino

d. Asian

e. Other

f. Prefer not to answer

4. Where do you consider your hometown? (Please include your zip-code.)

a. Fill in the blank

5. Have you or a loved one been affected by COVID-19?

a. Yes

b. No

6. What is your political leaning?

a. Republican

b. Democrat

c. Independent

d. Something else

e. No answer

7. How often do you get information concerning COVID-19 from the following?

a. Television

i. Never

ii. Rarely

iii. Sometimes

iv. Often

v. Always

b. Radio

i. Never

ii. Rarely

iii. Sometimes

iv. Often

v. Always

c. Print publications

i. Never

ii. Rarely

iii. Sometimes

iv. Often

v. Always

d. News websites or apps

i. Never

ii. Rarely

iii. Sometimes

iv. Often

v. Always

e. Social media, such as Facebook, Twitter, Instagram, etc.

i. Never

ii. Rarely

iii. Sometimes

iv. Often

v. Always

f. Search through Google or other search engines

i. Never

ii. Rarely

iii. Sometimes

iv. Often

v. Always

g. Podcasts

i. Never

ii. Rarely

iii. Sometimes

iv. Often

v. Always

8. Which source of information do you prefer?

a. Television

b. Radio

c. Print publications

d. News websites or apps

e. Social media, such as Facebook, Twitter, Instagram, etc.

f. Search through Google or other search engines

g. Podcasts

9. How important to you, if at all, is keeping up with news regarding COVID19?

a. Very important

b. Important

c. Not important

d. No answer

The Effect of Masks on Allergic Rhinitis Symptoms Related to Ragweed and its Influence on College Students

ACKNOWLEDGEMENTS

I would like to thank my mentor, Dr. Deanna VanKuren for her support and encouragement throughout these past two years. I would also like to thank Dr. Vander Schaaf and Dr. Schurman for their insightful feedback and constant dedication to my project. Thank you to Dr. Himes, Dr. Perabeau, Dr. McLaughlin, Dr. Brown, and Dr. Case for their guidance throughout the Honors Program. Thank you to Dr. Dillinger for providing KN95s to use for research. Thank you to the Honors Program for supplying funds and resources to conduct research. Thank you to my fellow Honors students for comradery, passion, and inspiration and to all of those who participated in my project, listened about it, or supported the process.

ABSTRACT

Background

This study explored the effect of masks on allergic rhinitis related to ragweed. Research shows surgical and KN95 masks reduce nasal symptoms arising from dust, pollen, and ragweed. Other studies have contradictory findings about the effect of masks on ocular symptoms. Very few studies have examined the effect of masks on early and late allergic rhinitis.

Methods

This qualitative study involved thirty college students aged 18 to 25 from Olivet Nazarene University with self-reported or physician-diagnosed allergic rhinitis on November 15, 2022. Participants were randomly assigned to a control (no mask), surgical, or KN95 mask group and walked around Perry Farm Park for an hour to assess ragweed sensitivity. Data was collected manually using a modified survey from allergy specialists and summarized in the results as an outline for future study. Survey questions were sent via school-wide email and disseminated through flyers distributed in nursing classes and to the men and women’s soccer teams.

Results

The surgical mask preliminarily trended a higher correlation on decreasing nasal allergic rhinitis symptoms than the KN95 masks, majority reporting mild nasal symptoms during the experience and no nasal symptoms after the experience. Most surgical mask-wearers felt the mask helped moderately during the experience or reduced one to two symptoms. Surgical mask-wearers reported a likeliness to wear the mask in the future.

Conclusion

The study implies that the surgical mask may effectively reduce nasal allergic rhinitis symptoms related to ragweed. A broader study and repetition of the study in the future is necessary to examine the effects of environmental change, such as low or high ragweed counts, and how late allergic rhinitis is affected by mask-wearing.

Keywords: Allergic rhinitis, ragweed, masks, surgical, KN95, late allergic rhinitis

LITERATURE REVIEW

Introduction

Allergic rhinitis (AR), seasonal allergies, or hay fever is one of the most common chronic illnesses in the United States, and there are few interventions to avoid exposure to allergens (dust, pollen, mold, animal dander, ragweed, etc.). Allergic diseases require

constant mitigation and treatment. Accompanied by symptoms such as itchy eyes, runny nose, and sore throat, AR can interfere with the quality of life of students. I examined how mask-wearing impacts ragweed allergies in college-aged students to determine the effectiveness of masks in deterring ragweed-induced AR. The review of current medical literature indicated that masks decrease the number of allergens exposed to, such as pollen and dust, although there has been limited research on the effect of masks on ragweed allergy for the general population.

Allergic rhinitis

Allergic rhinitis is a disease affecting about 15% of the United States population on physician-based diagnoses and as high as 30% based on self-reported nasal symptoms (Wheatley & Togias, 2015). Common symptoms of AR include sneezing, pruritus (itching), nasal congestion, rhinorrhea (runny nose), feeling unfocused or tired, chronic viral infections, congestion, eye rubbing, and dark skin underneath the eyes (allergic shiners). Some common causes of AR are dust, mold, animal dander, and pollen. Allergic rhinitis functions relatively the same no matter the trigger allergen and the allergic response varies based on its severity. There are three types: allergic rhinitis, nonallergic rhinitis, or localized allergic rhinitis.

Localized allergic rhinitis is associated with comorbidities in other mucosal organs. It means there are symptoms related to allergic rhinitis but the individual tests negative in allergy tests except for the nasal allergen challenge (Eguiluz-Gracia et al., 2019). Allergic rhinitis varies in severity from mild to moderate to severe. AR occurs intermittently or persistently and is seasonal, perennial, or occupational. AR is a complex condition affecting all aspects of life: physiological, psychological, cultural, and social. As a multicomplex disease, it has been found that rhinitis “decreases daytime arousal, cognition, mood, and overall social functioning” (Patterson et al., 2014). Allergic rhinitis can also have a large impact on daily activity, making it harder to breathe, exercise, or be involved in school activities.

The effect of AR on daily activity depends on its severity and can be explained in more detail based on quality of life (QoL) criteria. AR severity is based on four QoL conditions including the level of sleep disturbance; impairment of daily activities, leisure, or sports; impairment of school or work; and troublesome symptoms and diagnosed as mild for patients with none of the conditions met or moderate-severe for patients suffering from one or more conditions. Moderate-severe AR is more prevalent in patients with persistent AR, though mild AR is more prevalent in patients with intermittent disease (Cuvillo et al., 2017). AR is considered serious if it is a “persistent allergic rhinitis” in that the symptoms occur “at least 4 days a week and over a period of at least 4 weeks” (Klimek et al., 2019).

The quality of life conditions associated with allergic rhinitis are represented with a visual analog scale (VAS) that measures the severity. Zero is the lowest score and reflects no quality of life affected by AR, and 10 is the highest score as every QoL

condition is affected by AR. It works similarly to a pain scale with 0 as no pain experienced to 10 as worst pain imaginable. These values reflect patients with mild AR would have zero to four QoL conditions impacted out of the 10. Moderate AR would have between four and seven, and severe would be between seven to 10. Overall, the visual analog scale provides quality of life context with the delineation of the allergic rhinitis severity relationship.

Masks and allergic rhinitis

Masks became more readily accessible post-pandemic. COVID-19 changed the lifestyle of the average adult population and how their allergic diseases are treated or addressed (Zhang, Lan, & Zhang, 2021). Previously, there was limited data on the effect of masks on allergic rhinitis symptoms (Gani et al., 2019). However, current studies show that masks decrease allergic rhinitis symptoms for multiple allergens. According to a study conducted in Israel on 1,824 nurses, Dror et al. found 16.5% of the nurses reported having dust-related AR symptoms. They also found for nurses with mild, moderate, or severe allergic rhinitis symptoms, wearing a surgical or KN95 mask demonstrated a mild decrease in allergic rhinitis symptoms. Lastly, they found the N95 masks alone resulted in a significant reduction of AR symptoms.

In another study from Mengi et al. (2022), the use of surgical masks was studied for pollen allergy patients symptomatic from March to April during COVID-19 with data collected in April of 2020. Mengi et al. (2022) found 86% of surgical-mask wearers reduced their frequency of nasal (sneezing and nasal discharge) symptoms related to pollen allergy. Bergmann et al. (2021) focused on those with pollen allergies. Subjects were exposed to grass pollen for two hours—wearing no mask, a medical mask, or a Filtering Face Piece 2 (FFP2), and both masks had no significant differences and shared the avoidance of nasal and conjunctival symptoms. The literature suggests that masks decrease allergic rhinitis symptoms for pollen allergies.

Dubini et al. (2022) studied the effect of a mask on ragweed-related allergic rhinitis for patients from European countries in heavily populated ragweed areas (Eastern France, Northern Italy). Claiming to always use masks since the outbreak of the Coronavirus Disease 2019 (COVID-19), the self-reported burden of ragweed oculorhinitis decreased significantly and all nasal screening symptoms (sneezing, rhinorrhea, nasal obstruction, and nasal itching) improved significantly. No change was found for ocular symptoms (watering, itching, soreness) compared to the previous year. This is consistent with the function of the face masks to protect the airway from inspiratory particles and supports my thesis that masks decrease symptoms of allergic rhinitis. Although this evidence supports the reduction of allergic rhinitis symptoms from wearing a mask, it may not be the most reliable due to the political nature of the pandemic and mask-wearing.

Although the COVID-19 pandemic had conflicting views related to mask-wearing, there are possible additional health benefits to their usage besides prevention of

COVID-19. Mask-usage may lower the exposure to inhaled airborne particles with the physical filtering out of allergens or air pollutants and humidification of the breathing (Choi et al., 2019). Masks block the allergen particles from entering the lungs of the person and reduce the amount that is inhaled. Decreasing the length of exposure to an allergen with a mask may decrease allergic rhinitis symptoms. Liccardi et al. (2021) found that the daily amount of outdoor mask use from self-reported allergic rhinitis participants during the COVID-19 pandemic was from one to ten hours.

Another benefit of wearing a mask is that it could help to avoid early and late phase AR. Early phase AR can occur within minutes of allergen exposure from antibodies that initiate inflammation. This induces sneezing, pruritus (itching), rhinorrhea (runny nose), and nasal congestion. Avoiding these irritating symptoms can improve the quality of life of students. Late phase AR begins at four hours and peaks six to twelve hours after exposure. Late phase AR induces one of the most irritating AR symptoms of nasal congestion due to the release of inflammatory agents. Other late AR symptoms are feeling tired, chronic viral infections, sniffing, eye rubbing, blinking, congested voice, snoring, or dark skin beneath the eyes called allergic shiners (Minor 2013). Conditions that may interfere with the effects of mask-wearing on allergic rhinitis symptoms are related to the environment.

Confounding factors

Increasing time indoors and household ventilation are likely to be favorable in decreasing AR symptoms. The use of face masks and low air pollution emissions from the initial COVID-19 lockdowns in 2020 may have decreased symptom severity in patients with AR (Choi et al., 2019). The concurrence of pollen season and the beginning of the COVID-19 pandemic may have led people to spend less time outdoors and may have reduced allergic symptoms. Additionally, face masks may protect against allergens, yet few studies have examined their effect. Even though initial research finds dust allergy patients appear to benefit from mask usage, house dust mite (HDM) allergy patients being more confined to the home environment may have increased their AR course (Gani et al., 2022). Health risks associated with mask-usage include a lowered absolute concentration of oxygen in the air under the masks compared to room air. There are also increases in heart rate, respiratory rate, and carbon dioxide (Kisielinski et al., 2021). This study will focus on the effect of masks related to the effect of ragweed-induced AR in college students.

Ragweed

Ragweed pollen is the most important cause of allergic rhinitis and pollen asthma in North America. Specifically, Ambrosia artemisiifolia (short ragweed) and Ambrosia trifida ( giant ragweed) are the most prevalent ragweed pollen allergens. The size of the pollen particles and route of exposure determines the manifestation of the allergic

response. Basically, particles of less than seven micrometers can get into the airway and cause asthma or difficulty breathing. Lei & Grammer (2019) share that pollen grains are approximately sixteen to twenty micrometers in diameter and are notorious for triggering allergic symptoms in the central and eastern United States. In the United States, weed pollen is emitted in the morning during the autumn season based on seasonal variations in daylight. A single ragweed plant can expel one million pollen grains in one day (Baxi, 2010). According to Damialis et al. (2017), pollen can travel hundreds of miles from its source. In the Chicagoland area, where this study was conducted, ragweed pollen is prevalent from August to early November and varies based on the year. Ragweed counts are measured by the local pollen counts online. The adaption of a mask can help to target this issue.

METHODS

Overview

This study consisted of thirty college students aged 18 to 25 from Olivet Nazarene University and was approved by the Institutional Review Board. Participants suffered from allergic rhinitis of all types (allergic, nonallergic, localized). Participants were chosen by responding “yes” to the question: “During the fall of 2022, have you experienced rhinitis symptoms such as sneezing, rhinorrhea, nasal obstruction, and nasal itching that were unrelated to the common cold (fever, sore throat) or COVID-19?”

Evidence of a positive test for at least one allergen specific IgE (antibody) was not required for participation but was asked after this question. These questions were sent via school-wide email and spread through flyers handed out in nursing classes and through the men and women’s soccer teams. The research question was as follows: is there a relationship between wearing a mask and experiencing allergic rhinitis symptoms (itchy, watery eyes, sneezing, runny nose, sore throat) related to ragweed for college students?

Participants

The population of college students was chosen and involved thirty participants male or female ages ranged from 18 to 23 with a mean age of 21. College students were chosen because of the interference of allergic rhinitis with school performance by decreasing alertness and cognition (Patterson et al., 2014). Participants were recruited by flyers and a school-wide email that inquired if they had a diagnosis of allergic rhinitis or were experiencing symptoms currently (within the past six months). Participants were not told the purpose of the experiment to avoid confounding variables. The incentive for the participants was to be entered into a drawing for one of two $50 Amazon gift cards. They were then told to report to Perry Farm Park on a day where they would walk around the park for an hour. Once they arrived at Perry Farm Park, they were

given a surgical mask, KN95, or no mask and encouraged to write down their allergic symptoms as they walked around. They were randomly assigned to an experimental or control group for the purposes of the study and did not know that there were two kinds of masks involved: KN95 mask and surgical mask. Participants were informed of the risks associated with mask usage (Kisielinski et al., 2021). The consent form delineated the risks associated with mask wearing. Participants were advised to consult with a doctor if having health conditions such as asthma, migraines, pregnancy and more, and were encouraged to seek for further clarification. Participants were asked to not take allergy medication during the day(s) of the experiment, but this was not a requirement and was up to their own discretion. The participants avoidance of allergy medications was displayed in the results section to avoid confounding results. Participants were also requested to keep a diary of the day to document their allergic symptoms including the type of symptom, the time of their occurrence, their severity, how long they lasted, and the effect of the mask on their symptoms.

Design

Participants wore two kinds of masks, a KN95 or a surgical mask, or no mask from one trip to Perry Farm Park in early November, which nears the end of the peak period for ragweed. The participants were divided in thirds, with two groups as the experimental groups, one group wearing a KN95 mask, another group wearing a surgical mask, and the third or control group wearing no mask on a day when ragweed was low because of lack of park availability. To control for placebo effect, the control group wore no mask to see the effect of the ragweed without an intervention. When they arrived, participants walked around Perry Farm Park for one hour in the morning, when ragweed is usually the highest (Lei & Grammer, 2019). However, on this day the overall ragweed count was low compared to higher ragweed count days. Participants arrived between 8 and 11 AM, checked in with me when they got there, received their KN95 or surgical mask, or none, and then walked around the park for an hour.

The first group came from 8 to 9 AM and wore the KN95 mask. The second group wearing the KN95 mask came from 10 to 11 to ensure that the initial group did not see them because their survey responses might be influenced by seeing or communicating with the other groups. Control group or no mask came between the two groups. Even though the groups came at different times, the experiment was completed in the morning hours, so the ragweed count did not vary significantly between the groups. Once the experience was complete, the groups checked out with me and took off their masks if desired. I sent them an email with the Survey Monkey to complete before midnight. Once they got home, they were encouraged to change their clothes and shower to remove allergens from their clothing to avoid further allergen exposure or stay inside for most of the day if possible or desired.

Survey

Survey responses included how many hours each participant spent outside later and the possible symptoms they experienced. If they were not wearing a mask at that time, the responses monitored the effect their allergens might interfere with the results of the study. For instance, if they went outside again later and were exposed to their allergen again, they may report nasal congestion on their survey, which was not related to the Perry Farm Park experience. Participants were required to fill out a Survey Monkey on their phone about their symptoms before the end of the day at 11:59 PM.

Data collection

The questionnaire was modified from one developed and vetted by a team experienced in allergic rhinitis research for another mask study (Mengi et al., 2022). My survey questions included a Survey Monkey, located at the bottom of Appendix A. The questionnaire measured the effect of masks on allergic rhinitis symptoms related to ragweed and the relationship between wearing a mask and experiencing AR symptoms. The summary below is indicative of the future implications of the research. The data warranted studying the effect of early and late allergic rhinitis further. Data was on a personal computer that is password protected in a folder that encrypts with another password for confidentiality purposes.

RESULTS

Statistical analysis did not quantify the preliminary data due to the limited number of participants, although the data can serve as an outline for future research. The Perry Farm Park trip had ten participants for each group of control, surgical-mask wearers, and KN95. Four participants (one in the control group, two in the surgical group, and one in the KN95) usually took daily allergy medication, and all decided to skip their med-

Nasal symptoms experienced during Perry Farm Park

Nasal symptoms experienced after Perry Farm Park

Surgical mask

No nasal symptoms (5/10)

Mild nasal symptoms (5/10)

No nasal symtoms (7/10)

Mild nasal symptoms (3/10)

KN95

No nasal symptoms (2/10)

Mild nasal symptoms (8/10)

No nasal symptoms (3/10)

Mild nasal symptoms (4/10)

Moderate nasal symptoms (3/10)

Control or on mask

No nasal symptoms (5/10)

Mild nasal symptoms (5/10)

No nasal symptoms (5/10)

Mild nasal symptoms (5/10)

Perceived effect of mask during experience

Likelihood to wear mask in future

Surgical Mask KN95

Made no difference (1/10)

Mask helped a little (2/10)

Mask helped moderately (6/10)

Mask helped a lot (1/10)

Very unlikely (1/10)

Unlikely (2/10)

Neither likely nor unlikely (1/10)

Likely (1/10)

Made no difference (5/10)

Mask helped a little (5/10)

Mask helped moderately (0/10)

Mask helped a lot (0/10)

Very unlikely (2/10)

Unlikely (5/10)

Neither likely nor unlikely (3/10)

Likely (0/10)

ication on the day of the experiment. Most surgical mask-wearer results were trending with the hypothesis; this group will be the focus of the discussion. It is crucial to notice that the surgical mask group may have received better results because they came later in the morning when the severity of ragweed had lessened. The KN95 group may not have seen a significant decrease in allergic rhinitis symptoms because they came earlier in the morning and may have endured higher ragweed counts. The tables below summarize the surgical mask participants, KN95, and control study data. The first table discusses the nasal symptoms before and after Perry Farm Park. The second describes the perceived effect of mask usage and the likelihood the individual would wear them in the future.

DISCUSSION

Overall, nasal symptoms experienced during and after the experience was trending to imply that there may be a relationship between wearing a surgical mask and reducing nasal symptoms during and after exposure to a low pollen count. Due to the limited number of participants, statistical values were underdefined for nasal symptoms experienced during the Perry Farm Park experience. Statistical significance was unquantified in the number and severity of nasal symptoms experienced after the visit to Perry Farm Park or the late allergic rhinitis.

Other research supports the trend in reducing nasal symptoms related to mask-wearing. Dubini et al.’s 2022 study aligns with the nasal symptom-reducing effect from wearing a surgical or KN95 mask. Bergmann et al.’s 2021 study supported the findings by focusing on those with pollen allergies wearing a medical mask or a Filtering Face Piece 2 (FFP2), and both masks shared the avoidance of nasal and conjunctival symptoms. Dror et al. (2020) found KN95 respirators provided no additional reductions in allergic rhinitis symptoms over standard surgical masks.

Another category studied was the perceived effect of the mask on symptoms experienced during the Perry Farm Park experience. Most surgical mask-wearers felt their

mask helped a little or reduced at least one symptom during the experience. However, most KN95 mask-users felt the masks made no difference to their allergic symptoms after the experience, which is unclear. The participants assigned to the KN95 group may not have had as severe allergic rhinitis as the surgical mask wearers or may have been uncomfortable wearing them. The relationship between late allergic rhinitis and experiencing nasal or ocular symptoms and their degrees of severity was considered, but further research and analysis is necessary. Most surgical mask-wearers reported being likely to wear the mask in the future to prevent allergic rhinitis. Additional data found the most disturbing symptom overall for the KN95, surgical, and control groups to be nasal-related.

Statistical analysis ceased to quantify due to the limited number of participants and the low ragweed count on the day of data collection. However, the surgical mask-wearers still appeared to trend with the hypothesis. Another study on a day with a high ragweed count and an ampler number of participants may reflect the decrease in allergic rhinitis symptoms associated with mask usage. However, high ragweed counts might overcome preventive measures, so a mask designed for high ragweed days could be beneficial. A future study would benefit from surgical and KN95 mask-wearers completing the experiment simultaneously to prevent the groups from having different pollen exposures due to pollen being more prevalent in the morning. It would also benefit future research to examine the relationship between early and late allergic rhinitis.

Overall, the relationship between mask-wearing and experiencing allergic rhinitis symptoms associated to ragweed for college students was inconclusive, but the surgical-mask data was trending with the hypothesis. Some additional questions for further consideration or future studies would entail: Are masks helpful or harmful in promoting an improved quality of life through symptom reduction for college students with allergic rhinitis? Can masks relieve aggravating allergic rhinitis symptoms when engaging college activities outside? Lastly, do masks provide a similar extent of symptom reduction with the participants wearing masks during the high ragweed count as previous studies? Therefore, further research is necessary to determine if masks influence late allergic rhinitis, decrease allergic rhinitis symptoms, and their influence on quality of life.

REFERENCES

Baxi, S. N., & Phipatanakul, W. (2010). The role of allergen exposure and avoidance in asthma. Adolescent Medicine: State of the Art Reviews, 21(1), 57–ix.

Bergmann, K.-C., Kugler, S., Zuberbier, T., & Becker, S. (2021). Face masks suitable for preventing covid-19 and pollen allergy. A study in the exposure chamber. Allergo Journal International, 30(5), 176–82.

Choi, H. G., & Kong, I. G. (2021). Asthma, allergic rhinitis, and atopic dermatitis incidence in Korean adolescents before and after covid-19. Journal of Clinical Medicine, 10(15), 34–46.

Cuvillo, A., Santos, V., Montoro, J., Bartra, J., Dávila, I., Ferrer, M., Jáuregui, I., Sastre, J., Mullol, J., Valero, A. (2017). Allergic rhinitis severity can be assessed using a visual analogue scale in mild, moderate, and severe. Rhinology Journal, 55(1), 34–38.

Damialis, A., Kaimakamis, E., Konoglou, M., Akritidis, I., Traidl-Hoffmann, C., & Gioulekas, D. (2017). Estimating the abundance of airborne pollen and fungal spores at variable elevations using an aircraft: How high can they fly? Scientific Reports, (7), 44535.

Dror, A. A., Eisenbach, N., Marshak, T., Layous, E., Zigron, A., Shivatzki, S., Morozov, N. G., Taiber, S., Alon, E. E., Ronen, O., Zusman, E., Srouji, S., & Sela, E. (2020). Reduction of allergic rhinitis symptoms with face mask usage during the COVID-19 pandemic. The Journal of Allergy and Clinical Immunology: In Practice, 8(10), 3590–93.

Dubini, M., Robotti, C., Benazzo, M., & Rivolta, F. (2022). Impact of quarantine and face masks on ragweed induced oculorhinitis during the COVID-19 pandemic in northern Italy. International Forum of Allergy & Rhinology, 12(2), 220–22.

Eguiluz-Gracia, I., Pérez-Sánchez, N., Bogas, G., Campo, P., & Rondón, C. (2019). How to diagnose and treat local allergic rhinitis: A challenge for clinicians. Journal of Clinical Medicine, 8(7), 1062.

Gani, F., Cottini, M., Landi, M., Berti, A., Comberiati, P., Peroni, D., Senna, G., & Lombardi, C. (2021). Allergic rhinitis and COVID-19: Friends or foes? European Annuals of Allergy and Clinical Immunology, 54(2): 53–59.

Kisielinski, K., Giboni, P., Prescher, A., Klosterhalfen, B., Graessel, D., Funken, S., & Hirsch, O. (2021). Is a mask that covers the mouth and nose free from undesirable side effects in everyday use and free of potential hazards? International Journal of Environmental Research and Public Health, 18(8), 4344.

Klimek, L., Bergmann, K.-C., Biedermann, T., Bousquet, J., Hellings, P., Jung, K., Merk, H., Olze, H., Schlenter, W., Stock, P., Ring, J., Wagenmann, M., Wehrmann, W., Mösges, R., & Pfaar, O. (2017). Visual analogue scales (VAS): Measuring instruments for

the documentation of symptoms and therapy monitoring in cases of allergic rhinitis in everyday health care. Allergo Journal International, 26(1), 16–24.

Lei, D. K., & Grammer, L. C. (2019). An overview of allergens. Allergy and Asthma Proceedings, 40(6), 362–65.

Liccardi, G., Bilo, M. B., Milanese, M., Martini, M., Calzetta, L., Califano, F., Carucci, L., Cicarelli, A., Cutajar, M., D’Auria, P., De Bartolomeis, F., Dello Iacono, I., Franzese, A., Gargano, D., Inciso, G., Giordano, A. C., Iannaccone, R., Lo Schiavo, M., Nappi, L., & Madonna, F. (2021). Face masks during COVID-19 pandemic lockdown and selfreported seasonal allergic rhinitis symptoms. Rhinology Journal, 59(5), 481–84.

Mengi, E., Kara, C. O., Alptürk, U., & Topuz, B. (2022). The effect of face mask usage on the allergic rhinitis symptoms in patients with pollen allergy during the COVID-19 pandemic. American Journal of Otolaryngology, 43(1), 103206.

Minor, S. (2013). Allergic rhinitis: What’s best for your patient? Journal of Family Practice, 62(3), E1–10.

Patterson, A. M., Yildiz, V. O., Klatt, M. D., & Malarkey, W. B. (2014). Perceived stress predicts allergy flares. Annuals of Allergy, Asthma & Immunology, 112(4), 317–21.

Wheatley, L. M., & Togias, A. (2015). Clinical practice. Allergic rhinitis. The New England Journal of Medicine, 372(5), 456–63.

Zhang, Y., Lan, F., & Zhang, L. (2021). Advances and highlights in allergic rhinitis. Allergy, 76(11), 3383–89.

Survey Questions

•

 Other: please specify___

• Question 2: Gender?

 Male

 Female

 Other:____

• Question 3: Do you receive medical treatment for your allergic symptoms?

 Yes

 No

• Question 4: If yes to the previous question, did you take your allergy medication today and if so, what times of the day is it active (for this day)? Please include the number of hours that it is active in the spaces below. If no, please respond no in the space below.

 No

 Morning (0600-1159);___

 Afternoon (1200-1759);___

 Night (1800-2359);___

 Other:___

• Question 5: How would you describe your allergic nasal symptoms during this experience (the time spent at Perry Farm Park)? Please indicate the number of symptoms as well.

 No nasal symptoms

 Mild or class I nasal symptoms (runny nose and sneezing);___

 Moderate or class II nasal symptoms (more severe runny nose and sneezing);___

 Moderate, persistent or class III nasal symptoms (constant nasal stuffiness that is severe and limits the ability to do daily activities);___

 Moderate-severe, persistent, or severe-persistent, class IV nasal symptoms (severe ongoing nasal stuffiness, congestion, sinus drainage);___

• Question 6: How would you describe your allergic nasal symptoms after the time spent at Perry Farm Park? Please indicate the number of symptoms as well.

 No nasal symptoms

 Mild or class I nasal symptoms (runny nose and sneezing);___

 Moderate or class II nasal symptoms (more severe runny nose and sneezing);___

 Moderate, persistent or class III nasal symptoms (constant nasal stuffiness that is severe and limits the ability to do daily activities);___

 Moderate-severe, persistent, or severe-persistent, class IV nasal symptoms (severe ongoing nasal stuffiness, congestion, sinus drainage);___

• Question 7: How would you describe your allergic eye symptoms during this experience (the time spent at Perry Farm Park)? Please indicate the number of symptoms as well.

 No eye symptoms

 Mild or class I eyes symptoms (itchy, watery eyes);___

 Moderate or class II eye symptoms (more severe watery eyes);___

 Moderate, persistent or class III eye symptoms (severe watery eyes and limits the ability to do daily activities);___

 Moderate-severe, persistent, or severe-persistent, class IV eye symptoms (severe sinus drainage impairing eyesight);___

• Question 8: How would you describe your allergic eye symptoms after the time spent at Perry Farm Park? Please indicate the number of symptoms as well.

 No eye symptoms

 Mild or class I eyes symptoms (itchy, watery eyes);___

 Moderate or class II eye symptoms (more severe watery eyes);___

 Moderate, persistent or class III eye symptoms (severe watery eyes and limits the ability to do daily activities);___

 Moderate-severe, persistent, or severe-persistent, class IV, persistent eye symptoms (severe sinus drainage impairing eyesight);___

• Question 9: What was your most disturbing allergic symptom during this experience (the time spent at Perry Farm Park)?

 Nasal;____

 Eye;____

 None;____

 Other: please specify___

• Question 10: What was your most disturbing allergic symptom after the time spent at Perry Farm Park and at what time did this occur?

 Nasal: time occurred___

 Eye: time occurred___

 None

 Other: please specify___; hour of day it occurred____

• Question 11: How did the mask affect your allergic symptoms during the time spent at Perry Farm Park?

 Eliminated symptoms

 Partially eliminated symptoms

 No change in symptoms

 Other: please specify___

• Question 12: How did the mask affect your allergic symptoms after the time spent at Perry Farm Park experience?

 Eliminated symptoms

 Partially eliminated symptoms

 No change in symptoms

 Other: please specify___

• Question 13: How would you describe the relationship of the mask to the allergy symptoms you experienced this day?

 Made no difference

 Helped a little (reduced at least one symptom)

 Helped moderately (reduced 1-2 symptoms)

 Helped a lot (reduced 3+ symptoms)

 Completely eliminated

• Question 14: How likely are you to wear a mask while outdoors in the future to prevent allergy symptoms?

 Never

 Not likely

 Likely

 Very likely

• Question 15: After going to Perry Farm Park, if you went outside, did you wear a mask? Insert the amount of time in hours you were outside in the blank space please.

 No, I did not go outside

 No, I did not wear a mask outside;______

 Yes, I wore a mask outside;_____

• Question 16: If you answered yes to going outside whether wearing a mask or not, how were your eye symptoms being outside after Perry Farm Park with/ without a mask? Please indicate the number of symptoms as well. If you did not go outside, please choose not applicable.

 Not applicable

 No eye symptoms

 Mild or class I eyes symptoms (itchy, watery eyes, ); ____

 Moderate or class II eye symptoms (more severe watery eyes); ___

 Moderate, persistent or class III eye symptoms (severe watery eyes and limits the ability to do daily activities); ___

 Moderate-severe, persistent, or severe-persistent, class IV, persistent eye symptoms (severe sinus drainage impairing eyesight); ___

• Question 17: If you answered yes to going outside whether wearing a mask or not, how were your nasal symptoms being outside after Perry Farm Park with/ without a mask? Please indicate the number of symptoms as well. If you did not go outside, please choose not applicable.

 Not applicable

 Mild or class I nasal symptoms (runny nose and sneezing); ___

 Moderate or class II nasal symptoms (more severe runny nose and sneezing); ___

 Moderate, persistent or class III nasal symptoms (constant nasal stuffiness that is severe and limits the ability to do daily activities); ___

 Moderate-severe, persistent, or severe-persistent, class IV nasal symptoms (severe ongoing nasal stuffiness, congestion, sinus drainage); ___

• Question 18: Is there anything else you would like to add? Include empty space for response.

Tracking Simulated Somatosensory Deficiencies that Affect Postural Stability through Detrended Fluctuation Analysis

ACKNOWLEDGEMENTS

I would like to acknowledge everyone who got me to the point of being able to complete a project as intensive as this.

I would first like to thank my mentor, Dr. Camilo Giraldo. He was a very valuable resource to me, and I would not have made it through this project without his help throughout the entire thing. Even with switching universities Dr. Giraldo was still available to help me at any moment. He never stopped meeting with me and aiding me in my research. He is one of the best researchers I have met and instilled solid researching practices in me.

I would also like to thank Eryn Gerber, Ph.D., University of Kansas. Eryn analyzed the same data in her thesis and was available to answer questions I had regarding the data. Some aspects of the data were very difficult to understand, and she was able to comfort me by sharing her struggles to understand it and helping to overcome that difficulty.

I would like to thank the University of Kansas. The data was collected at this institution, and they were willing to sign me onto the IRB and allow me to analyze the data as well. Without them I would not have ever been able to collect data as intensive as this and they made this project a possibility.

Last, I would like to thank the entirety of the Olivet Nazarene University Honors Program. The program really takes a smaller university and takes a select group of academic students and turns them into researchers. The program challenged me and introduced me into the field of research, and I would never do something like this project if it were not for the program.

ABSTRACT

Falls are a prevalent problem among elderly populations. Falls increase the cost of healthcare, frequently cause severe injuries, and negatively affect quality of life. Lack of postural stability is a major contributing factor to falls, with postural stability defined as the correct biomechanical execution based on sensory feedback. Types of sensory feedback include vision, vestibular, proprioceptive, and somatosensory. This study focuses on the lack of postural stability in quiet standing (standing upright and still) due to somatosensory and vision deficiencies. To track these deficiencies, fifty-one subjects stood for sixty seconds on two force plates, and their center of pressure (COP) time series were extracted. All subjects completed three trials with eyes closed or open while standing on five foam thicknesses that simulated various levels of somatosensory deficiencies at the feet, a common symptom in people with a high risk of falling (e.g., diabetic populations). To quantify these somatosensory deficiencies, Detrended Fluctuation Analysis (DFA) was performed on all COP time series. It is hypothesized that DFA on COP time series can track deficiencies in the somatosensory and vision feedbacks. Though this study does not cover actual somatosensory deficiencies, it could offer a validated measure to future studies comprised of participants who suffer from peripheral neuropathy (e.g., diabetic populations).

REVIEW OF LITERATURE

Falls are prevalent amongst the elderly population, particularly in the United States due to the Baby Boomer generation’s current age. These falls result in a high cost for the United States government in Medicare expenditures for fall treatment. One-third of adults over the age of sixty-five are expected to fall at least once per year. On top of this, the Baby Boomer population will soon result in an even higher population of elderly persons. With these considerations, the U.S. Department of Housing and Urban Development estimated in 2017 that the cost of falls in 2020 would be $59.7 billion and would only increase as time progresses [1]. Research to prevent falls will thus not only help improve the quality of life for aging citizens but has the potential to greatly decrease health costs.

Falls are caused by deficiencies or faults within the body’s feedback system or central nervous system. The body’s sensory feedback is comprised of four different systems: the visual, proprioceptive, vestibular, and somatosensory systems. The visual system is perceived with the eyes. The proprioceptive system is perceived through receptors on the skin, joints, and muscles. The vestibular system is perceived through the cochlea in the ear. Finally, the somatosensory system is perceived by the skin or internal organs. These systems work together to achieve desired biomechanical tasks, such as standing in place. However, it has been shown that as one feedback system is removed the others perform at a higher level to compensate [2]. For example, if the visual and

somatosensory feedback systems are removed or damaged, the proprioceptive and vestibular feedback systems will perform at a higher level.

To study the somatosensory feedback in human balance, Center of Pressure (COP) or Center of Mass (COM) is extracted while subjects stand on a force plate. COP indicates the position of the vertical force projected onto a two-dimensional axis. COM is different than COP because it considers the entire body. While COP is two-dimensional, COM is three-dimensional, as the COM of the body is above the feet (somewhere in the positive z direction). See Figure 1 for a visual comparison of COP and COM. The COP can be separated into the anteroposterior (AP) and mediolateral directions (ML). Relative to a person’s body, the AP direction is in front of and behind, while the ML direction is from side to side.

Testing is performed with the somatosensory feedback altered or unaltered. Force plate ground reaction forces and moments are used to calculate COP [4]–[6] or COM [2], [4] data. To simulate a deficiency in the somatosensory feedback experienced by a fall-prone elderly person or someone suffering from diabetes, studies either freeze the feet to numb them [7] or use foam between the feet and force plate [2], [7]–[11]. Foam has been proven to be more effective when simulating somatosensory deficiencies compared to freezing feet [7].

The COP changes over time and cannot be defined as a function; therefore, it is considered a time series. Once the COP time series is extracted, it must be analyzed by extracting metrics that can translate to a medical meaning. Some meaningful metrics in human balance are entropy [11], fractal analysis [5], [12], [13], and detrended fluctuation analysis (DFA) [14]. This line of research suggests using non-linear measures to analyze COP is effective. However, there seems to be a lack of research using DFA as the metric to study the COP time series.

DFA defines the complexity of a time series by classifying the signal as white, pink, or brown noise [14]. In short, DFA linearizes partitions of a time series, and the root mean square (RMS) fluctuation is taken from this linearization. This is repeated for various partitions, and the partitions are combined back together in a log-log graph (RMS fluctuation vs. partition width). The slope of the log-log graph is α, the main extracted value from DFA. An α value of 0.5 is white noise, a value of 1 is pink noise, and a value of 1.5 is brown noise. The results and some steps of a DFA analysis are shown below. Various studies on biological systems within humans have determined that pink noise is found in healthy systems. For example, pink noise has been proven to help people fall asleep [15]. Most importantly, dynamics similar to pink noise demonstrate healthy characteristics of human walking [16]. This information suggests that during quiet standing, healthy subjects should show a pink noise pattern. As the foam thickness is increased, simulating a greater deficiency in the somatosensory feedback, the DFA is expected to deviate from an α value of 1 (pink noise) to a different value (white or brown noise). If there is a deviation between healthy subjects’ α values and subjects that are “diseased” (standing on foam) then there is potential for early tracking of somatosensory deficiencies through DFA on COP time series. This could also have the potential to diagnose postural deficiencies in diabetes earlier because a decrease in somatosensory feedback at the feet is common to those with the disease. Using DFA on the COP time-series could show potential to diagnose somatosensory deficiencies. If the α value varies significantly as the foam thickness is increased, it can be assumed that the α value would also change the greater the somatosensory deficiency is in a patient.

METHODS

The data analyzed in this study was obtained at the University of Kansas [11]. Fifty-two young and healthy participants stood on five levels of foam (0ʺ, ⅛ʺ, ¼ʺ, ½ʺ ,

and 1ʺ) while their COP time series was recorded in both the AP and ML directions. Participants’ visual condition was also varied (eyes open (EO) or eyes closed (EC)). Three 60-second trials were completed for every foam thickness and each visual condition, resulting in thirty trials per subject. Ground reaction forces were collected by an AMTI force plate, and data was sampled at 100 Hz through a Cambridge Electronic Design MkII data acquisition system [11].

Data analysis was completed entirely in MATLAB. All raw data for each subject was graphed so it could be visually checked for errors. An example of the raw data is shown in Figure 3. Upon viewing the data, it was observed that subject 22 showed a large deviation from other subjects. To help create a stronger correlation with the data analysis, this subject’s data was excluded. The data was then filtered and downsampled. The filtering technique was a low pass filter of 10 Hz, and the data was downsampled to 50 Hz (Figure 4).

Figure 3 shows the raw data from a trial. The specifics of the trial are also shown in the figure: “s1001” denotes subject 1, “Foam0” denotes the no foam control, “EC” denotes the EC condition, and “AP” denotes the AP direction. Figure 4 is similarly labeled; however, it contains three different lines labeled in the legend. The light grey line represents the data used for DFA.

DFA was then performed with a minimum partition time of 0.1 seconds and maximum partition time of 15 seconds on the filtered and downsampled data, and the DFA alpha and R-Squared values were extracted for each trial. The mean α across trials and subjects was taken for each set of conditions (visual condition and foam level). Finally, percent change within each subject with respect to no foam was utilized to visualize the impact of the somatosensory deficiency.

RESULTS

The results of the study are shown in the graphs in Figure 5. The lines represent the mean of all subjects’ data. The graphs show the different foam thicknesses and their percent change from the no foam control (F0). The R-Squared value is displayed in the titles of each plot to show the reliability of the α values. The dashed line represents the standard deviation of the α values.

In all four conditions, there was a noticeable increase in percent change between the ⅛ʺ and ¼ʺ foam. The change was around 4% for each condition at this point. Along with this, all conditions besides EC in the ML direction had a nearly 0% change between no foam and ⅛ʺ foam. The EO, AP direction had a difference between the no foam control and the ⅛ʺ foam that was nearly 0%. This condition had the initial jump seen in the other conditions, but then it plateaued and showed almost no additional

changes between foam thicknesses ¼ʺ and 1ʺ. The EO, ML condition also had nearly no change from the no foam control to the ⅛ʺ foam. It also had the initial jump but then continued to show increases in percent change from no foam to the 1ʺ foam. For the EC, ML foam condition the percent change from no foam to 1ʺ about 8%. Again, the EC, AP condition remained near 0% change between the no foam control and the ⅛ʺ foam. It also had the jump between ⅛ʺ and ¼ʺ foam. However, this condition resulted in a decrease in the percent change between ½ʺ and 1ʺ foam. This unique result will be discussed later. Lastly, the EO, ML condition did have a substantial change between the no foam control and the ⅛ʺ foam. It also had the jump between ⅛ʺ and ¼ʺ foam. It then plateaued slightly but showed a subtle increase between the ¼ʺ, ½ʺ and 1ʺ foams. These results with be expanded upon in the discussion.

DISCUSSION

The expectation was that as foam thickness increased, the percent change of α would also increase. A change in the α value denotes a change in the type of noise behavior of the COP time series. Since the COP of a healthy person over time behaves as pink noise when analyzed, it is important to see how the α value changes as that person becomes “diseased” (i.e., has thicker foam placed under their feet). Varying from pink noise to white or brown noise means that the body is no longer behaving healthily. If the α value changes with respect to an increase in foam thickness, it can be expected that the α value would change also with an increase in a somatosensory deficiency in a patient. No statistical significance tests were performed on the results; thus, the discussions below indicate potential trends or conclusions.

Eyes open, anteroposterior direction

The 1/8ʺ foam showed almost no change from the no foam control. This was observed in every other condition except for EC, in the ML direction. The small change either means that 1/8ʺ foam is so small that it did not have an effect on the healthy subjects in the study or small somatosensory deficiencies are not detectable through these methods. The ~5% change between 1/8ʺ and ¼ʺ foam shows that a minor deficiency could be tracked using these methods. The ¼ʺ, ½ʺ, and 1ʺ foam did not show changes between each other. Therefore, for this condition, the increasing foam thickness was not a good approximation of increasing “disease.”

Eyes open, mediolateral direction

The 1/8ʺ foam data point shows the same results as the EO, AP direction. The small change leads to the same conclusions as previously mentioned (foam being too small to make an impact or is not detectable). The ¼ʺ, ½ʺ and 1ʺ foam points create a linear trend that shows that as the foam thickness increases, the percent change of α from

the no foam control increases. These results perhaps show the most potential for somatosensory diagnosis. First, the jump from 1/8ʺ to ¼ʺ foam, shown in other conditions, shows potential for early diagnosis. Secondly, the continual increase shows the potential to diagnose the severity of the deficiency as well. For example, this means that an analysis of the α of a patient could not only show that they have a somatosensory deficiency but also show just how extreme it is.

Eyes closed, anteroposterior direction

The results of the 1/8ʺ, ½ʺ, and ¼ʺ foam points are similar to the corresponding points in the other conditions discussed previously. The 1ʺ foam data point is the most intriguing of all the points. As discussed earlier, a thicker foam is expected to create a greater change in α. However, in this condition, the percent change of α from F0 decreased between ½ʺ and 1ʺ foam. This result is difficult to explain. For now, this data point is inexplicable, so more research is needed to support this finding and eventually find its cause.

Eyes closed, mediolateral direction

The 1/8ʺ foam under this condition was different from all of the other 1/8ʺ foam data points in the other conditions. It had a substantial change from F0. There was also an increase from 1/8ʺ to ¼ʺ foam. This implies that this condition shows the largest potential for early diagnosis. Along with the jumps seen, the magnitude of the percent change was greater than all the other conditions. The ½ʺ and 1ʺ foam points did not show much change from the ¼ʺ point. However, at 1ʺ foam the percent change of α from F0 is ~8%. This means that this condition shows the potential to aid in the diagnosis of more severe somatosensory deficiencies. Thus, testing a patient using a force plate with their EC and analyzing the COP in the ML direction could be used to diagnose a severe somatosensory deficiency.

CONCLUSIONS

Using DFA on the COP of time series shows potential for early somatosensory deficiency. This is supported by multiple conditions showing a larger percent change on smaller foams, specifically the 1/8ʺ foam. In addition, the EO, ML direction condition shows the potential to diagnose not only the existence but the severity of a somatosensory deficiency. Using nonlinear measures on the COP time series shows the feasibility of analyzing this complex data.

Using other nonlinear measures than DFA would provide a further understanding of the data. One study used multiple nonlinear measures to analyze COP in a sitting subject [17]. These measures (Lyapunov Exponent Correlation Dimension and Approximate Entropy) could also be used to analyze the data in this study. Any nonlinear measure to interpret the data could be beneficial to give a bigger picture to understand postural stability.

REFERENCES

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[4] K. S. Rosengren et al., “Changing control strategies during standard assessment using computerized dynamic posturography with older women,” Gait & Posture, vol. 25, no. 2, pp. 215–21, Feb. 2007.

[5] C. Doherty, C. Bleakley, J. Hertel, B. Caulfield, J. Ryan, and E. Delahunt, “Balance failure in single limb stance due to ankle sprain injury: An analysis of center of pressure using the fractal dimension method,” Gait & Posture, vol. 40, no. 1, pp. 172–76, May 2014.

[6] M. Weilert, “The Application of Detrended Fluctuation Analysis and Adaptive Fractal Analysis on Center of Pressure Time Series in Parkinson’s Disease,” Thesis, University of Kansas, 2017. Accessed: Mar. 21, 2022. [Online]. Available: https://kuscholarworks. ku.edu/handle/1808/25868

[7] M. Patel, P. A. Fransson, R. Johansson, and M. Magnusson, “Foam posturography: standing on foam is not equivalent to standing with decreased rapidly adapting mechanoreceptive sensation,” Exp Brain Res, vol. 208, no. 4, pp. 519–27, Feb. 2011.

[8] C. Fujimoto et al., “Power spectral analysis of postural sway during foam posturography in patients with peripheral vestibular dysfunction,” Otol Neurotol, vol. 35, no. 10, pp. e317-23, Dec. 2014.

[9] M. Patel, P. A. Fransson, D. Lush, and S. Gomez, “The effect of foam surface properties on postural stability assessment while standing,” Gait Posture, vol. 28, no. 4, pp. 649–56, Nov. 2008.

[10] G. Wu and J. H. Chiang, “The significance of somatosensory stimulations to the human foot in the control of postural reflexes,” Exp Brain Res, vol. 114, no. 1, pp. 163–69, Mar. 1997.

[11] E. D. Gerber, P. Nichols, C. Giraldo, L. Sidener, C.-K. Huang, and C. W. Luchies, “Rambling-trembling center-of-pressure decomposition reveals distinct sway responses to simulated somatosensory deficit,” Gait & Posture, vol. 91, pp. 276–83, Jan. 2022.

[12] V. Cimolin et al., “Fractal dimension approach in postural control of subjects with Prader-Willi Syndrome,” Journal of NeuroEngineering and Rehabilitation, vol. 8, no. 1, p. 45, Aug. 2011.

[13] M. Duarte and V. M. Zatsiorsky, “On the fractal properties of natural human standing,” Neuroscience Letters, vol. 283, no. 3, pp. 173–76, Apr. 2000.

[14] C.-C. Wang and W.-H. Yang, “Using detrended fluctuation analysis (DFA) to analyze whether vibratory insoles enhance balance stability for elderly fallers,” Arch Gerontol Geriatr, vol. 55, no. 3, pp. 673–76, Dec. 2012.

[15] J. Zhou, D. Liu, X. Li, J. Ma, J. Zhang, and J. Fang, “Pink noise: Effect on complexity synchronization of brain activity and sleep consolidation,” Journal of Theoretical Biology, vol. 306, pp. 68–72, Aug. 2012.

[16] N. Hunt, D. McGrath, and N. Stergiou, “The influence of auditory-motor coupling on fractal dynamics in human gait,” Sci Rep, vol. 4, no. 1, Art. no. 1, Aug. 2014.

[17] R. T. Harbourne and N. Stergiou, “Nonlinear analysis of the development of sitting postural control,” Developmental Psychobiology, vol. 42, no. 4, pp. 368–77, 2003.

The Effect of Adverse Childhood Experiences on the Self-Esteem of College Students

ACKNOWLEDGEMENTS

This endeavor would not have been possible without the oversight and guidance of Dr. Lisa Gassin. Therefore, I would like to thank Dr. Gassin for the opportunity to complete this project with her. I would also like to extend my sincere thanks for Dr. Case and Dr. Stipp. Their feedback was key in shaping the final product of this project. Lastly, I would like to mention Dr. Cole and Prof. Salomone. Their support and excitement for this project was invaluable.

ABSTRACT

Background

Adverse childhood experiences (ACEs) are known to predict negative health and mental health effects later in life. One in two Americans has experienced at least one ACE. This issue is prevalent across class, race, and ethnicity. However, little is known about ACEs and the young adult population.

Methods

A survey was conducted to measure ACEs and self-esteem in fifty college students. The hypothesis was a negative correlation between ACE and self-esteem scores.

Results

A small negative correlation was found between ACEs and self-esteem in college students. The average ACE score was 3.9 and the average self-esteem score was 16.78. A one-tailed Pearson correlation coefficient test was run. A significant correlation was not found between ACE score and self-esteem, r(48) = -0.23, p = 0.06. Therefore, the hypothesis is not supported because not enough evidence was found to do so.

Conclusions

A trend in the data showed a small negative correlation between ACEs and self-esteem in college students. Although the findings in this study were not statistically significant, this does not mean that ACEs do not have an impact on self-esteem. This study lacked the power to detect it.

Keywords: ACEs, ACE Questionnaire, adverse childhood experiences, college students, intervention, Rosenberg Self-Esteem Scale, self-esteem, young adults

INTRODUCTION

There is a mental health crisis in America. Nearly one in five adults in the nation experiences a diagnosable mental health issue each year (Substance Abuse and Mental Health Services Administration, 2018). Though there is no clear cause of mental illness, trauma can contribute to the development of mental health issues (Centers for Disease Control and Prevention [CDC], 2021). Adverse childhood experiences (ACEs) are measurable traumatic incidents endured during childhood, and their link will be explored in depth through this project.

Broadly, ACEs are the experience of an unsafe environment. Specifically, they are instances in which a child is affected or surrounded by violence, abuse, or neglect (CDC, 2020). Defining these experiences as ACEs allows researchers to measure their

prevalence and impact with a questionnaire. Considering their link with mental health outcomes, ACEs are a significant public health issue in the United States with severe consequences (Felitti et al., 1998; Giano et al., 2020). Abuse and neglect in the home are widely prevalent issues in contemporary society and experiencing them can leave a lasting impact. In 1998, a study was published that used the ACE Questionnaire, a tool designed to measure ACE score, for the first time. This study suggested a link between experiencing ACEs and a lasting psychological and physical impact (Felitti et al. 1998).

Defining ACEs

Early traumatic experiences have been correlated with certain outcomes later in life. Research on this topic, however, began relatively recently. Felitti and his colleagues published the initial ACE study in 1998 that established the link between ACEs and physical and psychological health. Because of its importance to child development, this topic has attracted the interest of multiple fields including education, nursing, social work, and psychology. The main question this important first study asked was whether adverse childhood experiences had a positive correlation with greater health risks and earlier mortality in adults. Data collected through the ACE Questionnaire as well as the recent health records of over 8,000 people confirmed a positive correlation between ACEs and greater health risks in adulthood. Additionally, in comparing the newly collected data to recent medical records, the study found that, in general, the more ACEs a participant had, the more likely they were to have one of the leading causes of death in adults (i.e. ischemic heart disease, any cancer, stroke, chronic bronchitis or emphysema, and diabetes) (Felitti et al., 1998). The ACE Questionnaire was designed to measure the number of ACEs people have. However, this tool may have the capacity to help medical professionals understand the leading causes of death and perhaps how to prevent them. Research has shown that one in two people experiences at least one ACE (Giano et al., 2020). The CDC defines ACEs as instances where a child is affected or surrounded by violence, abuse, or neglect (2020). Beyond this, the ACE Questionnaire measures ACEs by the presence of ten specific experiences (e.g., verbal abuse or threats, physical and/or sexual violence, substance use/abuse). As Felitti’s and other studies show, these early traumatic experiences are predictive of certain negative factors in adulthood, including depression, anxiety, substance use, poor health behaviors, suicidal ideation, and suicidal attempt (Karatekin, 2018; Mersky et al., 2013; Thompson et al., 2019; Windle et al., 2018).

Significance

Research on ACEs is important to pursue for multiple reasons. ACEs are prevalent in the U.S., regardless of class, race, or ethnicity (Halfon et al., 2017; Maguire-Jack et a l., 2020). One in six people experiences four or more ACEs, and for these individuals, adulthood is more likely to consist of negative factors (CDC, 2021; Felitti et al., 1998). Based on the minimal research conducted so far on ACEs and young adults, it can be

tentatively concluded that ACEs generally have a negative impact on this population. However, the full extent of this impact is not yet known. Much of the existing research looks exclusively at young adults’ physical health or health risk behaviors of young adults (Espeleta, 2019; Khrapatina & Berman, 2017; Mersky et al., 2013). Research on the mental health of young adults has shown that ACEs predict poorer mental health (Mersky et al., 2013). My research examines how ACEs impact the self-esteem of young adults. The impact of ACEs on the self-esteem of young adults, specifically college students, has not yet been measured.

Purpose and rational

The purpose of this project is to look at the relationship between ACEs and self-esteem in college students. Felitti’s seminal study demonstrated a relationship between ACEs and the leading causes of death in adults. Since then, a multitude of research has investigated ACEs and their connection to various factors later in life (Halfon et al., 2017; Maguire-Jack et al., 2020; Thompson et al., 2019). However, a gap remains when studying how these early experiences affect young adults. Specifically, this project will investigate a possible connection between ACEs and the self-esteem of college students eighteen to twenty-five years old. Participants will be given the ACE questionnaire along with the Rosenberg Self-Esteem Scale (RSES). This survey will be presented to students through MTurk, a survey tool developed by Amazon. After data collection, I analyzed the data using the Person product-moment correlation coefficient and presented my findings. This project is important because there is minimal research that explores ACEs and their effect on college students. Research has shown that ACEs in young adulthood can manifest in harmful ways, but interventions can still be successful (Addie et a l., 2022; Chandler, 2015; Gresham et al., 2022; Khrapatina et al., 2017; Lornec et al., 2020). ACE literature is lacking research gathering information about ACEs and how they affect college students in general. However, research about ACEs and the selfesteem of college students is essentially non-existent. Therefore, this study may provide support for more research to be done on the impact of ACEs on the self-esteem of college students. Real-world implications and recommendations for improving college students’ mental health may emerge based on these findings and conclusions. With a better understanding of the relationship between ACEs and self-esteem, colleges will be equipped to better structure student support services and improve grades.

REVIEW OF LITERATURE

Prevalence of ACEs

The ACE Questionnaire allows traumatic experiences to be quantified. Felitti’s study found that these experiences produce enduring negative effects later in life (1998). Further, that study demonstrated that people who have four or more ACEs are

significantly more likely to experience negative health and mental health effects. In 2021, the CDC reported that one in six people had four or more ACEs. This translates to millions of people being impacted by complications in their health and mental health. Though ACEs may be more heavily connected to certain groups, they have the power to affect anyone in any group. ACEs can affect all economic classes. This was shown in a study that tested children from over 90,000 families for nine different ACEs (Halfon et al., 2017). This study measured the prevalence of ACEs across different economic classes in the U.S. as well as their impact on the health of those children. The information produced by this study is generalizable to the U.S. population because four levels of household income are represented, as well as many different languages, races, and ethnicities. The results of this study revealed the prevalence and impact of nine ACEs on the health of children across the U.S. from birth to seventeen years of age. There was a clear, statistically significant relationship between low income and an increased number of ACEs. However, the results also showed that, though ACEs were less prevalent in children in families with the highest level of income, the ACEs’ negative impact on the health of those children was greater than it was on children in the lower income groups. In other words, though ACEs are statistically less common in certain socioeconomic demographics, this can actually magnify their negative effects (Halfon et al., 2017).

Besides surpassing the barrier of economic status, ACEs have been observed across racial and ethnic groups, albeit unevenly. A study investigating how ACEs are experienced across different racial and ethnic groups in the U.S. analyzed the prevalence of nine different ACEs in Latinx, White, and Black children across the country (Maguire-Jack et al., 2020). The results showed that certain ACEs were more likely within certain races or ethnicities but others had a fairly constant presence between them all. Overall, 59.1% of White children never experienced an ACE, 48.6% of Latinx children never experienced an ACE, and only 36.3% of Black children never experienced an ACE (Maguire-Jack et al., 2020). Although races and ethnicities are shown to experience ACEs at different rates, ACEs remain prevalent in the US.

Another recent study revealed that more than half of the individuals in the study, which included over 200,000 participants, experienced at least one ACE, whereas almost a quarter endured three or more (Giano et al., 2020). The prevalence of ACEs is varied, with females having more than males, ethnic minorities having more than White Americans, and lower socioeconomic groups having more than higher socioeconomic groups (CDC, 2020; Halfon et al., 2017; Maguire-Jack et al., 2020). However, it is important to note that though there are differences in the number of ACEs between these groups, no group is immune to the possibility of ACEs. These experiences are not something that only ‘disadvantaged’ groups endure. Giano’s study had the great advantage of a large and diverse sample size. This allows the results to be

generalized to the greater population of the US. However, this data was acquired from self- assessment, meaning that it is only as true as participants are truthful. This research demonstrates that ACEs continue to be a public health issue in need of widespread action, intervention, and prevention.

Implications of high ACEs

When ACEs are prevalent, certain negative factors are more likely to occur. ACEs have been shown to pose health risks such as heart disease, cancer, and obesity to middle-aged adults affected by such experiences (Felitti et al., 1998). A more recent study explored the impact of ACEs on health and mental health (Mersky et al., 2013). Results of the study reveal that, compared to participants with no ACEs, all participants with multiple ACEs were more likely to report low life satisfaction, frequent depressive symptoms, frequent anxiety, frequent tobacco use, and frequent marijuana use. Long-term physical health consequences may be traced back to mental health issues in early adulthood, which further emphasizes the negative role ACEs have on health (Mersky et al., 2013).

Besides the clear impact ACEs have on health matters, they have also been shown to affect life choices and trajectory. The original ACE study discussed how life choices are impacted by the prevalence of ACEs. Felitti et al. (1998) hypothesized that multiple ACEs would have a negative impact on mental health and speculated that this negative effect would lead to individuals choosing to engage in unhealthy coping mechanisms. This speculation was confirmed in the Mersky et al. (2013) study. These various coping mechanisms were referred to as high-risk behaviors, as they contribute to decreased health in the future of the individual. Therefore, as a result of these high-risk behaviors, Felitti et al. (1998) speculated ACEs would be connected to premature death. This suspicion was explored and tentatively confirmed by Brown et al. (2007).

The stress caused by accumulating ACEs can also impact children as they are experiencing the ACEs. Hinojosa and colleagues eloquently stated this in their study: “Beginning life at a position of structural disadvantage puts children on a trajectory that can differentially influence their social, educational, and health outcomes over time” (2019, p. 402). Children spend most of their time between school and home. Logically, what happens in the home will affect the child’s performance and success at school. The study orchestrated by Hinojosa et al. (2019) considered whether children who experienced ACEs were at a higher risk for poor outcomes at school. This study analyzed data from over 50,000 children between the ages of six and seventeen years of age. Results revealed that a child with two ACEs was slightly over one-third more likely to repeat a grade than a child with no ACEs. Furthermore, a child with three or more ACEs was over two-thirds more likely to repeat a grade than children with no ACEs (Hinojosa et al., 2019). From this data, it is clear

to see that ACEs not only affect various groups of people and their health but other facets of their lives as well.

Prevention of ACEs

Of course, now that the negative effects of ACEs have been quantitatively verified, prevention is a large topic of discussion in the academic literature. Screening children with the ACE Questionnaire as a method of prevention was one of the first suggestions since it was the original method used in the Felitti et al. (1998) study. However, caution toward using the ACE Questionnaire as the primary means for assessment and prevention has been expressed. The ACE Questionnaire alone has not yet been successfully used for the prevention of ACEs. Finkelhor (2018) warns of the potential negative costs wide application of screening for ACEs may produce. The time and effort needed to train physicians, possible false positives, and increased stigma surrounding screening are all examples of potential costs of a wide administration of screening. Essentially, Finkelhor (2018) argues there has not been enough research on the implementation of screening with the ACE Questionnaire for it to be widely distributed just yet. A need for other methods of prevention has been discussed as well as an evaluation of some methods that have already been put into practice.

Besides the ACE Questionnaire, other methods have been utilized in an attempt to assess and prevent ACEs in children. Nurses have commonly used various methods to assess children for things like child abuse and neglect in the past (Waite et a l., 2010). Examples of instruments used by nurses include the Stressful Life Events

Screening Questionnaire and the Life Stressor Checklist. These methods have been evaluated and accepted by the medical community. Since nursing is a holistic practice, mental health is their responsibility as well as physical health. According to this article, the role of nurses includes attention to their patients’ mental health. Although this article described other methods, it also advocated for the additional use of the ACE Questionnaire, viewing it as the link between mental and physical health. While advocating for the use of the ACE Questionnaire as a more general practice, this article lamented the lack of published guidelines for this type of screening (Waite et al., 2010).

Another study attempted to use a different method to identify the prevalence of ACEs for the purpose of prevention (Mersky et al., 2017). This study examined whether a combination of a new questionnaire and in-home observations were a feasible option for assessing children’s risk of future ACEs. Focusing on prevention, a study with over two-thousand families with children from birth to five years of age, attempted to measure the healthiness of the environments in which the children were being raised. The family was assessed using the Family Map Inventories (FMI), which are in-home interviews, and the child’s development was examined using the Ages and Stages Questionnaire. Items on the FMI were chosen to specifically correlate with

ACEs and evaluate the child’s risk of developing ACEs in their environment. This produced an FMI-ACE score. The greater the FMI-ACE score, the more likely the child was to experience ACEs later on. Examples of factors evaluated with the FMI-ACE method include different types of abuse and neglect, as well as substance abuse and household mental illness. Results from this study demonstrate significant relationships between an FMI-ACE score of four or more and the health and development of the child. This method of assessing children and families allows time for intervention to occur before the child accumulates a high ACE score. However, some drawbacks of this method include its dependency on home visits, the extensive time and manpower required, and its intrusive nature (McKelvey et al., 2017).

Other methods of prevention have been proposed. For example, a 2020 study suggested the wide implementation of therapeutic classrooms (Hays-Grudo & Morris). Teachers in U.S. schools must handle children’s emotional and behavioral problems on a daily basis. Problems with emotion and behavior can stem from ACEs (Hays-Grudo & Morris, 2020). Putting therapeutic classrooms into practice, psychologists, child developmental specialists, and social workers would be more involved to help detect ACEs and help the children. Besides therapeutic classrooms, Fortson et al. from the CDC offered potential ways to prevent ACEs (2016). One method that was suggested involved training parents to use positive parenting skills. The second method of prevention offered was public engagement and education campaigns. These methods have been demonstrated as an effective way of reducing childhood abuse and neglect (Fortson et al., 2016).

ACEs and self-esteem

The experiences that shape childhood are correlated with the development of selfesteem. In 2021, research was conducted that measured the effect of positive childhood experiences on self-esteem in college students. Results revealed that positive childhood experiences predict self-esteem and resilience in young adults (Kocatürk & Çiçek, 2021). Logically, then, adverse childhood experiences may be correlated with lower self-esteem in college students.

Kharsah and Latada (2016) revealed a significant positive correlation between self-esteem and grade point average in college students. Academic performance is a crucial factor for college students. According to Kharsah and Latada, self-esteem plays a role in the success of college students. College and young adulthood are formative and pivotal times and interventions designed for this population could help align the trajectory of life to a good path. The current study seeks to explore a possible correlation between ACEs and self-esteem in college students. Perhaps ACEs indirectly impact student grade point averages. Understanding this potential correlation will not only add to the current literature in a new way but also provide a better understanding of what constitutes success in college.

ACEs and college students

There is not much literature that exists on the effects of ACEs on collegiate academic performance. Recently, a longitudinal study was conducted that followed students through all four years of college. Results showed an indirect effect of ACEs on academic performance through psychological distress. More ACEs led to higher psychological distress, which predicted greater academic problems (Gresham & Karatekin, 2022). Another study showed a similar relationship between ACEs and academic achievement in college students. Higher ACE scores were correlated with less resilience in academic achievement and mental health (Addie et al., 2022). Whether directly or indirectly, adverse childhood experiences seem likely to have a negative impact on academic performance.

It has been well established that ACEs correlate with poorer health. A recent study showed that the college student population follows the greater trend of poorer physical and mental health with four or more ACEs (Watt et. al., 2022). College students are not excluded from health complications and often fail to seek help. This study explored a connection between ACEs and the underutilization of resources by college students. Interestingly, students with higher ACE scores were more likely to seek professional and informal help but more often found these resources unhelpful (Karatekin, 2019). The present study will help lay groundwork for future interventions to be more effective for college students and young adults.

Adverse childhood experiences are often correlated with mental health issues. Results from a 2018 study showed that more ACEs were correlated with a greater likelihood of participants also meeting the criteria for depression or anxiety disorders (Karatekin). College students were more likely to report suicidal ideation when they had a higher number of ACEs. Although this study found no direct correlation between stress and ACEs, there was a connection between both ACEs and mental health and stress and mental health (Karatekin, 2018). This preliminary research on connections between ACEs, stress, and mental health in young adults was expanded upon in 2020. Another study showed that college students with higher ACE scores showed greater stress and less social support (Karatekin & Ahluwalia, 2020). Based on these studies, ACEs may seriously affect the mental health of college students, but more research is needed regarding the possible correlation between ACEs and self-esteem.

The young adult/college student population is unique when compared with older adults because there is potential for this population to still be receptive to interventions (Chandler, 2015). Though there is minimal research on early adult interventions for ACEs, one study employed the Empower Resilience Intervention (ERI) on young adults. The ERI uses meetings, in which the participant meditates, hears verbal affirmations, and learns about relevant topics (e.g., ACEs, social support, resilience, etc.). Then the client writes a response to this new information and shares their response in a supportive group setting with their peer participants. The study which utilized ERI

reported that this intervention does not take away any negative side effects of ACEs but could help reduce the likelihood of more symptoms developing (Chandler, 2015). Though more research certainly must be done, there seems to be some potential hope for impactful interventions in the young adult population. My work will help lay the groundwork for more successful interventions to be created in the future.

METHODS

Participants

For this research, sixty participants were accessed through Amazon’s Mechanical Turk (MTurk). However, ten had to be removed because they were outside of the targeted age group for this study (18-25). The average age of participants was 23.9, and all were between 19 and 25 years old. Males made up 78% of participants. As for ethnicity, 84% of participants were White, 10% were Asian, 4% were Hispanic/Latinx, and 2% were Native American/Indigenous. The level of education was also measured. The majority of participants (78%) had completed a bachelor’s degree.

Materials

Data were collected through a survey published on MTurk. This is a website where researchers release surveys and participants are paid small amounts for taking surveys. People who took the survey were paid $5 each. The survey was a combination of the ten-item Adverse Childhood Experiences (ACE) Questionnaire (Felitti et. al., 1998; see Appendix A) and the ten-item Rosenberg Self-Esteem Scale (Rosenberg, 1989; see Appendix B). The ACE Questionnaire measures ACE scores on a scale from 0 to 10. It consists of yes and no questions such as, “Was a household member depressed or mentally ill, or did a household member attempt suicide?” (Felitti et. al., 1998). Every yes counts as one ACE. For example, if participants answer yes to all ten questions, their ACE score would be 10. Having zero to three ACEs tends to have little negative impact on life, whereas ACE scores of four or more tend to have a greater negative impact on life. The Rosenberg Self-Esteem Scale measures self-esteem on a scale of 0 to 30. Questions from this measure are formatted such as, “I feel I do not have much to be proud of” (Rosenberg, 1989). Answers to these questions are on a Likert scale. A score between 15 and 25 is considered normal self-esteem, and below 15 is considered low self-esteem.

Procedures

Participants on MTurk were able to read a brief description of this project (Appendix C). After clicking on the survey, the participants received informed consent and clicked to the next window if they agreed to participate. After completing the survey, participants received $5 through MTurk. No identifying information was collected from participants.

This research was a correlational study. A potential correlation between ACEs and self-esteem was explored. The hypothesis was a negative correlation between ACE score and self-esteem higher ACE scores will correlate with lower self-esteem. After data collection, the Pearson Product Coefficient and Cronbach’s Alpha were used to analyze the data.

RESULTS

General descriptive results showed that the average ACE score was 3.9 with a standard deviation of 3.13. The average Rosenberg Self-Esteem score was 16.78 with a standard deviation of 3.71. Nine out of eleven (81%) females and twelve out of thirty-nine (31%) males had an ACE score above 4. Overall, 42% of participants had ACE scores above 4. The average ACE score of females was 6.27, whereas for males it was 3.23. The average Rosenberg score was 16.64 for females and 16.82 for males. Seven out of thirty-nine (18%) males and one out of eleven females (9%) had a Rosenberg score below 15. Overall, 16% of participants scored below 15.

After running a one-tailed Pearson correlation coefficient in R, no significant relationship was found between ACE score and self-esteem, r(48) = -0.23, p = 0.06. This does not support the hypothesis of a negative correlation between ACE score and self-esteem. The null hypothesis is not rejected since no evidence was found to suggest a correlation between ACE score and self-esteem. Internal consistency for the ACE Questionnaire and the Rosenberg Self-Esteem Scale was tested with Cronbach’s Alpha. Both the ACE Questionnaire (α = 0.87) and the Rosenberg Self-Esteem Scale (α = 0.63) were found to be reliable, meaning they are consistently yielding similar results.

DISCUSSION

Interpretation of results

It is important to distinguish participants who scored above 4 on the ACE Questionnaire and below 15 on the Rosenberg Self-Esteem Scale because these are cut-off points. People with four or more ACEs are much more likely to experience negative effects on their health, and people with less than a 15 on the Rosenberg scale suggests they have low self-esteem (Felitti et al., 1998; Rosenberg, 1989). Forty-two percent of participants reported four or more ACEs. This number is significantly higher than expected, as the CDC reports 1 in 6 people having four or more ACEs (2021). Perhaps this number was too high because MTurk participants chose to take this survey because mental health was a topic that resonated with them.

There was a small negative correlation between ACEs and self-esteem, but because the results were not statistically significant this does not support the hypothesis. The main question this study set out to explore was whether ACEs have an effect on the

self-esteem of college students. The findings in this study did not produce enough evidence to support that hypothesis. However, this does not mean that ACEs do not have an impact on self-esteem. The way that finding significance in correlational studies works is that studies either have enough evidence to support the connection of variables or to support the disconnection of variables. The other option is that studies simply do not have enough evidence to support any connection. This situation is the case for this study. Therefore, the null hypothesis cannot be rejected.

Although this study lacks statistical significance, there are ways it can contribute to research on ACEs. Firstly, a study attempting to correlate ACEs and self-esteem in college students has not been attempted. This study was an important first step in filling this gap and presenting a methodology that others may follow or build upon. A surprisingly large percentage of participants reported ACE scores above 4. Perhaps ACEs are becoming more prevalent despite efforts to reduce them, or the younger generation is more aware of them. This study may act as a call to action for those researching ACEs. Secondly, the probability that the results of this study occurred by chance was only 6%. Though this is technically not statistically significant, it is quite close. This suggests that there may be a correlation between ACEs and self-esteem in college students, this study simply was not powerful enough to detect it.

Limitations

One very clear limitation of this study is its small sample size. With only fifty participants, this study does not have much power and is much more susceptible to a Type I I error, or false negative. There was also a lack of diversity, as most participants were White males. Therefore, this sample was not representative, and the results of this sample may not reflect reality. Further, fifty participants are likely not enough to find a significant correlation. These aspects may have contributed to a false negative.

Though both measures were reliable, meaning they measured what they intended to measure, reliability in the Rosenberg Self-Esteem Scale should have been higher. This scale is the primary measure of self-esteem in the field of psychology. Its reliability and validity have been thoroughly tested over the years. Therefore, the low Cronbach’s alpha established in this study suggests that participants may not have always answered honestly. Perhaps, since the survey was online, participants were distracted, causing this discrepancy in reliability.

The p-value suggested that the results acquired through this research could have occurred by chance. However, a flaw with significance testing is the harsh cut-off point between significant and non-significant results. A p-value with a 0.001 difference can be the defining factor between a significant and non-significant result. This study’s p-value was 0.06, meaning there is a 6% probability these results could have occurred by chance. Studies are only considered statistically significant when the probability of the result occurring by chance is 5% or less. Though this study is not statistically

significant, it still strongly suggests a trend between ACEs and self-esteem in college students.

Future directions

More research must be conducted on the potential effect ACEs may have on the selfesteem of college students. With a more robust research base, a greater understanding of effective interventions for college students who have experienced ACEs will follow. The design and implementation of interventions for this population have the potential to increase the well-being and academic success of college students. There is a clear need for intervention, as participants in this study reported ACE scores of four or more at a higher rate than the general population.

The young adult population is one that is overlooked in ACE research. Results from this study show that researchers miss an opportunity by ignoring this group. Old enough to begin experiencing the complications that are associated with higher ACE scores, but young enough for interventions to be effective, this population allows researchers to identify ways in which ACEs may be counterbalanced. The ACE Questionnaire measures trauma from the past; perhaps with more studies like this, the future can be changed.

REFERENCES

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Bryan, R. (2019). Getting to why: Adverse childhood experiences’ impact on adult health. The Journal for Nurse Practitioners, 15(2), 153–57.

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Centers for Disease Control and Prevention. (2021). About mental health. https://www. cdc.gov/mentalhealth/learn/index.htm

Chandler, G. E., Roberts, S. J., & Chiodo, L. (2015). Resilience intervention for young adults with adverse childhood experiences. Journal of the American Psychiatric Nurses Association, 21(6), 406–16.

Espeleta, H., Sharkey, C., Bakula, D., Gamwell, K., Archer, C., Perez, M., Roberts, C., Chaney, J., & Mullins, L. (2019). Adverse childhood experiences and chronic medical conditions: Emotion dysregulation as a mediator of adjustment. Journal of Clinical Psychology in Medical Settings, 27, 572–81.

Felitti, V. J., Anda, R. F., Nordenberg, D., Williamson, D. F., Spitz, A. M., Edwards, V., Koss, M.P., & Marks, J. S. (1998). Relationship of childhood abuse and household dysfunction to many of the leading causes of death in adults: The adverse childhood experiences (ACE) study. American Journal of Preventive Medicine, 14(4), 245–58.

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Karatekin C. (2019). Adverse childhood experiences (ACEs) and help-seeking for healthrelated interventions in young adults. The Journal of Psychology, 153(1), 6–22.

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APPENDIX A

ACE Questionnaire

Below are the contents of the ACE Questionnaire created by Felitti et al. (1998) that was used to measure ACE scores in this project. This questionnaire is formatted so the participant may calculate their own ACE score, hence the numbering instructions.

While you were growing up, during your first 18 years of life:

1. Did a parent or other adult in the household often … Swear at you, insult you, put you down, or humiliate you?

Or

Act in a way that made you afraid that you might be physically hurt?

Yes No If yes enter 1 ________

2. Did a parent or other adult in the household often … Push, grab, slap, or throw something at you?

Or

Ever hit you so hard that you had marks or were injured?

Yes No If yes enter 1 ________

3. Did an adult or person at least 5 years older than you ever… Touch or fondle you or have you touch their body in a sexual way?

Or

Try to or actually have oral, anal, or vaginal sex with you?

Yes No If yes enter 1 ________

4. Did you often feel that …

No one in your family loved you or thought you were important or special?

Or

Your family didn’t look out for each other, feel close to each other, or support each other?

Yes No If yes enter 1 ________

5. Did you often feel that … You didn’t have enough to eat, had to wear dirty clothes, and had no one to protect you?

Or

Your parents were too drunk or high to take care of you or take you to the doctor if you needed it?

Yes No If yes enter 1 ________

6. Were your parents ever separated or divorced?

Yes No If yes enter 1 ________

7. Was your mother or stepmother: Often pushed, grabbed, slapped, or had something thrown at her? Or

S ometimes or often kicked, bitten, hit with a fist, or hit with something hard? Or Ever repeatedly hit over at least a few minutes or threatened with a gun or knife?

Yes No If yes enter 1 ________

8. Did you live with anyone who was a problem drinker or alcoholic or who used street drugs?

Yes No If yes enter 1 ________

9. Was a household member depressed or mentally ill or did a household member attempt suicide?

Yes No If yes enter 1 ________

10. Did a household member go to prison?

Yes No If yes enter 1 ________

Rosenberg Self-Esteem Scale

Below are the contents of the Rosenberg Self-Esteem Scale created by Rosenberg (1989) that was used to measure self-esteem in this project. This scale comes with instructions for researchers to calculate the self-esteem scores of participants based on their responses to the following statements.

Below is a list of statements dealing with your general feelings about yourself. Please indicate how strongly you agree or disagree with each statement.

1. On the whole, I am satisfied with myself.

Strongly Agree Ag ree Disa gree Strongly Disagree

2. At times I think I am no good at all.

Strongly Agree Ag ree Disa gree Strongly Disagree

3. I feel that I have a number of good qualities.

Strongly Agree Ag ree Disa gree Strongly Disagree

4. I am able to do things as well as most other people.

Strongly Agree Ag ree Disa gree Strongly Disagree

5. I feel I do not have much to be proud of.

Strongly Agree Ag ree Disa gree Strongly Disagree

6. I certainly feel useless at times.

Strongly Agree Ag ree Disa gree Strongly Disagree

7. I feel that I’m a person of worth, at least on an equal plane with others.

Strongly Agree Ag ree Disa gree Strongly Disagree

8. I wish I could have more respect for myself.

Strongly Agree Ag ree Disa gree Strongly Disagree

9. All in all, I am inclined to feel that I am a failure.

Strongly Agree Ag ree Disa gree Strongly Disagree

10. I take a positive attitude toward myself.

Strongly Agree Ag ree Disa gree Strongly Disagree

APPENDIX C

Project Description for Participants

The following is the contents of the information and informed consent given to participants before agreeing to complete this survey. After this explanation, participants were given the option to agree and continue or to disagree and exit the survey.

Introduction

You are invited to take part in a research study (Childhood Experiences and Mental Health). This study is taking place online through Amazon’s Mechanical Turk. The goal of this study is to gather data from college students about childhood experiences and your thoughts about yourself. Taking part in this study is entirely voluntary. If you decide to participate, clicking to the next window and continuing this survey will signify that you have read the information below and wish to voluntarily participate in this study. Some of the essential information you will need to make the decision whether to participate in this research study is outlined below.

Purpose of Research

The purpose of this research study is to collect data exploring a possible connection between two variables in college students. You are being offered the opportunity to take part in this research study because you meet the requirements of being currently enrolled in a college or university and being between the ages of 18 and 25.

Procedures

Should you choose to take part in this study you will fill out a survey. This survey consists of 20 total questions. It is split into two main sections. The first section asks about childhood experiences while the second will ask about what you think about yourself. After you complete the survey, you will receive a code (a short sequence of randomized numbers) to input into MTurk as proof you finished the survey. Shortly after completing the survey, you will receive your compensation.

Time Duration of the Procedures and Study

If you agree to take part in this study, your involvement will last approximately 10-15 minutes. You only have to take the survey once, after this, no other time commitment is required.

Discomforts and Risks

You may choose not to participate in this study due to the potential risks outlined below. This study asks you to think back to your childhood and ponder traumatic experiences you may have had. Therefore, you will have to think about potentially triggering

memories, the following are options for support: National Suicide Prevention Lifeline at 800-273-8255; the Crisis Text Line text HOME to 741741; Substance Abuse and Mental Health Services Administration National Helpline at 800-662-4357.

Potential Benefits

Benefits to the participant could include self-reflection and/or self-appreciation. However, there is no guarantee that you will benefit from this research. The results of this study should be a useful contribution to academic literature on ACEs as there is a gap regarding the influence ACEs may have on self-esteem.

Statement of Confidentiality

A description of this study will be published by Olivet Nazarene University. This article will not include information that can identify you. At most, the article will include a summary of the results. You can request a copy of this article at any time. Your research record that is reviewed, stored, and analyzed at Olivet Nazarene University will be kept in a secured area in a password-protected disc or flash drive, which will then be stored in a locked file in the lab for at least three years. Informed consent forms will also be kept in a locked file in the lab. In the event of any publication or presentation resulting from the research, no personally identifiable information will be shared. Your participation in this research study will be kept confidential to the extent permitted by law. However, it is possible that other people may become aware of your participation in this study. For example, the following people/groups may inspect and copy records pertaining to this research: the Office of Human Research Protection in the U.S. Department of Health and Human Services and the Olivet Nazarene University Institutional Review Board (a committee that reviews and approves research studies).

Compensation for Participation

Each participant will be given $5 for participating in this study. Research Funding disclosure: This investigator is receiving a grant from Olivet Nazarene University to conduct this study. Conflict of interest: The investigator attends the university that is providing funding, it was granted through a class they are enrolled in.

Voluntary Participation

Taking part in this research study is voluntary. If you choose to take part in this research, your major responsibilities will include answering all of the survey questions. You do not have to participate in this research. If you choose to take part, you have the right to stop at any time. If you decide not to participate or if you decide to stop taking part in the research at a later time, there will be no penalty of loss of benefits to which you are otherwise entitled.

Contact Information for Questions or Concerns

You have the right to ask any questions you may have about this research. If you have questions, complaints, or concerns contact (Maggie Van Heemst) at (mjvanheemst@ olivet.edu). You may also contact the faculty advisor of this project (Dr. Lisa Gassin) at lgassin@olivet.edu. If you have questions regarding your rights as a research participant or a complaint regarding the research, you may email the Olivet Nazarene University Institutional Review Board (IRB@olivet.edu). If you need other support, you may contact any of these options recommended by the American Psychological Association: the National Suicide Prevention Lifeline at 800-273-8255; the Crisis Text Line text HOME to 741741; Substance Abuse and Mental Health Services Administration National Helpline at 800-662-4357.

Survey of the Performance of 5 nm Gold Nanoparticles Within an ssDNA-Stabilized Biosensor for the Detection of Hg2+

ACKNOWLEDGEMENTS

This project would not have been possible if not for the opportunity and the funds allowed by the Olivet Honors Program and the Pence-Boyce Research Committee. My undergraduate research process was an unforgettable and invaluable experience thanks to those involved in such programs. I thank my faculty advisor, Dr. Bruce Heyen, for guiding me along the long and winding road, as well as the entire ONU Chemistry Department, for never ceasing to have faith in my abilities. I further extend my thanks to all ONU faculty with whom I have had uplifting conversations, and I want to express my gratitude specifically to Dr. Nichole Vander Schaaf and Dr. Ryan Himes, who were incredible Honors mentors and always went out of their way to assure me I was doing well in navigating my project. Finally, I express my gratitude to my mother, who has always cheered me on from the sidelines in all my academic endeavors and was there for me for all those times I felt like giving up. I am truly grateful for all the support I have received thus far, and I certainly would not have come this far on my own. Thank you all for your unending encouragement.

ABSTRACT

The formation of a fluorescent biosensor complex consisting of 5 nm diameter gold nanoparticles (AuNPs) and single-stranded DNA (ssDNA) was conducted using a low-cost, efficient binding method. The analytical potential for the complex to detect mercuric ions (Hg2+) in an aqueous solution was assessed through the collection of UV-vis and fluorescence spectrometry data for the AuNP-ssDNA complex. The researcher aimed to investigate this potential in case the nanoparticles formed utilizing this method were too small to result in detectable fluorescence. To eliminate this possibility, the complex synthesized from this specific method was qualitatively evaluated to determine if it consistently and reproducibly provides results that would be clearly indicative of the presence of Hg2+. It was discovered that samples of the mercury-bound complex did not yield a consistent quenching for the fluorescence peak observed, as the peak height possessed a high standard deviation for the relatively small mean intensity. In addition, the methods for confirming the formation of the complex itself were not successful in showing a clear result.

Keywords: Gold nanoparticles, AuNPs, ssDNA, mercury, fluorescence spectroscopy, UV-vis spectroscopy, exonuclease I, thymine

INTRODUCTION

With the furtherance of industrialization, mercury (in addition to several other toxic heavy metals) has become a widespread environmental contaminant. Mining, smelting, consumption of fossil fuels, and other man-made processes have resulted in the release of mercury vapor into the atmosphere, where it later accumulates into water sources and sediments by wet and dry deposition (Ali et al., 2019). This contaminates the water as well as the marine life present in such water. Aquatic microorganisms absorb the settled mercury and process it into methylmercury or dimethylmercury, which are forms of mercury even more hazardous to biological systems. Fish and other marine life consume these microorganisms, which causes the mercury to be moved through food chains (Millward et al., 2019, Bernhoft, 2012). This results in the possibility of mercury poisoning from the consumption of contaminated seafood.

Mercury contaminating the environment places humans and animals at higher risk for mercury poisoning, which often causes irreversible damage to the central nervous system due to its effects as a neurotoxin. Acute exposure results in neurological damage, seizures, vomiting, diarrhea, and necrosis of the gut mucosa, whereas chronic exposure may cause fatigue, tremors, personality changes, delirium, and hallucinations in addition to neurological damage (Bernhoft, 2012). Therefore, the accumulation of these metals in our ecosystem presents a health hazard to many forms of life, as is

evident by events that have occurred in the past. The major mercury disaster that took place around Minamata Bay, Japan in the 1960s is such an example. At that time, mercury deposits leaked into the bay from a chemical plant and caused many to fall victim to what was named “Minamata Disease” (2002). In addition, the state of California still struggles with the number of fish contaminated by dangerous levels of mercury in its waters as a result of the large amount of mercury released in mines during the Gold Rush. To minimize poisoning cases, the government must provide guidelines for the consumption of fish for its citizens (Alpers et al., 2005).

In the face of these continuing issues, a proper method for detecting mercury that is low-cost and efficient is being researched in order to find contamination and prevent access to contaminated water or marine life before any mercury poisoning cases result. This is highly important due to the permanence of mercury poisoning symptoms. A method that has been researched for some time is the use of a biosensor, a device that combines a biological molecule with a substance that produces a signal proportional to an analyte in some fashion. The benefits of using these biosensors include that they are selective to a targeted toxic metal (Chen et al., 2016) and they are relatively low-cost (Khoshbin et al., 2018). As a result, there has been much progress in developing them in recent years for common use (Qing et al., 2019). Several types of biosensors have been researched for the detection of heavy metals, including a family of biosensors that utilizes the fluorescent properties of metal nanoparticles. Gold nanoparticles (or AuNPs) are among the researched subjects for this purpose, and they have proven to be majorly useful in biochemical detection methods due to their binding capabilities with many biological molecules and their conductivity (Jiang et al., 2018). Therefore, they are often researched for their abilities as a fluorescence biosensor component.

Gold nanoparticle-based biosensors rely on the fluorescence that the particles emit. However, like any nanoparticle, AuNPs must be stabilized so that they do not form larger lattice structures of gold. Although this is done by the initial chemicals used to synthesize the AuNPs (such as sodium citrate), these chemicals do not provide a means for the AuNPs to fluorescently detect something such as mercuric ions (Hg2+). This is the purpose of the biochemical component of the biosensor: to stabilize the AuNPs while also allowing for interaction with mercuric ions. This may be accomplished by binding a biological molecule of some type to them (Yang et al., 2020). The fluorescence of the AuNPs tends to change if the biological molecule is allowed to interact with an analyte that is a fluorescence quencher, such as mercuric ions. Therefore, this fluorescence change may be an indicator of the presence of mercuric ions (Li et al., 2018).

Because a mercuric ion will spontaneously bind with thymine (one of the four types of nucleotide bases found in DNA) and cause the formation of a T-Hg-T dimer (Park et al., 2010), an effective biological molecule to choose for AuNP stabilization would be a single-stranded DNA (ssDNA) oligonucleotide consisting

only of thymine bases. A problem to overcome using ssDNA, however, is that the charges of AuNPs and DNA are both overall negative, and so they do not spontaneously bind (Liu & Liu, 2017). The most common way to allow for the interaction to take place is to use thiol-modified DNA, although this is a time-consuming process that requires removing a disulfide bond cap through column purification (Liu & Liu, 2017). Fortunately, there have been other potential methods developed that require significantly less time and resources, including a method for attaching ssDNA to AuNPs developed by Yang et al. (2006). This group found that the interaction between AuNPs and ssDNA is size-dependent; if the AuNPs are small enough (around 5 nm or less in diameter), then the DNA may be able to spontaneously attach to the surface of the AuNPs. This only requires the addition of sodium borohydride solution when the researcher synthesizes the gold nanoparticles, so this binding method would be both simple to perform and lower in cost. The concern with this method is that the fluorescence might be too small to detect easily, as the fluorescence of gold nanoparticles appears to increase with size (He et al., 2008). The question, then, is if this method allows for a sufficient signal-to-noise ratio that is both detectable and reproducible.

To address this question, this project focused on the construction of a biosensor for mercuric ion detection based on AuNPs and poly(30)T-ssDNA by use of the method performed by Yang et al. (2005). The indication that the AuNPs have been stabilized by the ssDNA is that the solution experiences a red shift in absorbance of 4-6 nm on a UV-vis spectrum (Yang et al., 2005), and so this was evaluated with a UV-vis spectrometer. Finally, the fluorescence difference between mercury-bound and non-mercury-bound ssDNA-AuNP complexes was qualitatively analyzed to determine if the sensor complex could be used to detect mercury in contaminated water and to determine if the signal produced could be analyzed quantitatively.

METHODS

Materials

Gold (III) chloride (AuCl3) for preparing chloroauric acid solution, Poly(30)T ssDNA oligonucleotides, exonuclease I, sodium citrate dihydrate, sodium borohydride, and mercury (II) chloride were purchased from Sigma-Aldrich. All UV-vis data was taken using a Shimadzu UV-1280 spectrophotometer, and all fluorescence data was taken using a Hitachi F-2500 fluorescence spectrophotometer.

Synthesis of 5 nm gold nanoparticles

Gold nanoparticles of around 5 nm in diameter were synthesized and stabilized in a similar fashion to the traditional sodium citrate method (Agunloye et al., 2018). Initially, 10 mL of 1 mM aqueous HAuCl 4 solution was mixed with 0.8 mL of

38.8 mM aqueous solution of sodium citrate. Under vigorous stirring, 0.3 mL of an aqueous solution of 0.1 M NaBH 4 was added dropwise to the AuNP colloidal solution, which caused the solution to change to a vibrant red, indicating the successful formation of AuNPs of around 5 nm in diameter. The solution was then allowed to age for twenty-four hours before further use, to allow for any residual NaBH 4 to decompose.

Preparation of Hg-bound ssDNA samples

Mercury-bound Poly(30)T ssDNA oligonucleotides were prepared. For each sample, 15 µL of 10 µM solution of the ssDNA was mixed with 15 µL of 10 µM aqueous HgCl2 solution and incubated for thirty minutes at 37 °C. Then, 8 U of exonuclease I was added to each of the solutions, and the incubation was carried out for an additional thirty minutes at the same temperature to allow for enzyme digestion of any unbound ssDNA strands (Li et al., 2019). Only one concentration of HgCl2 was tested due to time constraints.

Spectral analysis

One milliliter aliquots of the AuNP hydrosol were stabilized by either Hg-bound or non-Hg-bound ssDNA and prepared for spectroscopy. The samples were prepared by combining 10 µL AuNP hydrosol, 60 µL of ssDNA (either bound to Hg or not), and 930 µL of N-2-hydroxyethylpiperazine-N’-2-ethanesulfonic acid (HEPES) buffer (0.1 M, pH 7.0). The samples were then aged for at least three hours. An absorbance spectrum for each aliquot was generated using UV-vis spectroscopy in order to locate the red shift and the highest peak of absorbance. Fluorescence data was taken by exciting at the peak absorbance wavelength to investigate any significant fluorescence intensity peaks from 530 nm-800 nm.

RESULTS

UV-vis spectroscopy

As seen in Figure 1, the average maximum absorbance wavelength for the control AuNP samples was found to be around 518 nm. A red shift was observed in only one of the non-Hg-bound ssDNA samples, contrary to what was expected. However, the red shift did appear in all the Hg-bound samples (AuNP-ssDNA complexes with Hg bound to the thymine of the ssDNA). These samples had lower absorbance, with a peak maximum around 524 nm. Samples of the UV-vis spectral data for each type of aliquot are displayed graphically below.

The average absorbance intensity at the maximum wavelength for each of the sample types are given in Table 1. Each sample was run in triplicate, and standard deviations are reported.

Each spectrum represents one of a sample triplicate that remained closest to the average absorbance and wavelength. The spectrum labeled “mercury bound” refers to a sample of AuNP-ssDNA complexes that have had mercury bound to the thymine along the ssDNA. The spectrum labeled “no mercury bound” refers to a sample with no mercury attached. Finally, the control line refers to a sample of AuNPs with no ssDNA complexed with them.

Fluorescence spectroscopy

As seen in Figure 2, the excitation wavelength for fluorescence spectroscopy was 518 nm for the non-Hg samples and 524 for the Hg-bound samples, as these were the maximum wavelengths observed in UV-vis spectroscopy. The fluorescence spectrum of the samples showed one significant emission peak at around 791 nm. The peak was not present in a control sample of DI water, and there was a general quenching of this peak observed in the Hg-bound samples. However, the variation between samples of the same nature was rather large. Therefore, the difference between the peak height for Hg-bound samples and the peak height for non-Hg-bound samples was not consistent. Samples of the fluorescence spectral data that were closest to the average are displayed graphically below.

The average fluorescence intensity and wavelength for each of the sample types is listed in Table 2 below. The standard deviations are reported. The mercury-bound samples were run in triplicate. However, only one sample without mercury was tested due to time constraints, so no standard deviation is included. This is an admitted shortcoming of the current project.

The spectra line labeled “mercury bound” refers to a sample of AuNP-ssDNA complexes that have had mercury bound to the thymine along the ssDNA. This sample was run in triplicate and the spectrum displayed corresponds with the sample closest to the average emission intensity and wavelength. The line labeled “no mercury bound” refers to a sample of unbound AuNP-ssDNA complexes. The control is not pictured, as it was a sample of DI water that did not display any fluorescence.

DISCUSSION

The evaluation of the ability of a gold nanoparticle-single-stranded DNA complex to detect mercuric ions using the binding method by Yang et al. was moderately successful. UV-vis spectra of the complexes were obtained to find the peak absorbance and to identify the presence of a red shift. Fluorescence spectra were measured to determine if the complexes consistently produced a lower level of fluorescence intensity when

mercury was bound to the thymine in the ssDNA. The data have certain implications that were not expected and are discussed below.

Fluorescence of the AuNP-ssDNA samples

The fluorescence intensity was inconsistent for the peak observed at 791 nm and only seemed to loosely follow the trend of being quenched with the addition of mercury (as seen in Table 2). The heights of the peaks seem to be even lower than that of commonly reported peak heights for 5 nm AuNPs, as well (Zuber et al., 2016), though this may be due to differences in instrumentation. The general ratio of the peak heights for both sample types was close to 1, which indicates that the difference in the peak heights is small. This fact, along with the size of the peaks themselves not being very large (only 3-5 counts of emission intensity), presents some difficulty in the determination of mercury in the sample. Therefore, if this level of variation in the peaks were to continue in the preliminary testing of this biosensor, it would be difficult to determine if a lower signal indicates there is mercury present or if it is due to the inconsistency of the peaks. Furthermore, there were no other significant peaks observed in the spectral data. With the evident non-reproducibility of the Hg-bound samples, the biosensor may fail to meet the demands required to accurately detect mercury presence and/or quantify it. It is also not known whether the peak observed is due to the fluorescence of the nanoparticles, or of something else entirely, especially since it was a rather small peak and a considerable distance from the excitation wavelength. Regardless, a sufficient biosensor must be consistent in its analytical properties, which this AuNP-ssDNA complex did not appear to display.

There are a few possible explanations for the ineffectiveness of the biosensor synthesized in this project, the most likely of which being that the gold nanoparticles are simply not large enough to produce a detectable fluorescence signal. The size of the AuNPs is crucial for Yang et al.’s method to be successful, since the method had also been attempted with larger AuNPs (of 17 nm diameter). It was found that the ssDNA did not interact with the AuNPs in that case. Therefore, the interaction is size-dependent, and smaller particles are necessary (Yang et al., 2006). As for using the complexes formed from this exact method as a biosensor component, it is very possible that the signal it produces is so small that it does not readily appear on the fluorescence spectral data. If this is the case, then the peak observed at 791 nm could be due to another component of the mixture, which could explain the reason for the inconsistency of the peak intensity relative to the presence of mercury. However, it is unknown what could be causing the peak to appear other than the AuNPs. Due to these overall fluorescence results, the binding method used for this project may inherently produce insufficient complexes for the purpose of detecting mercuric ions.

Unfortunately, there were time constraints on creating and studying samples of different concentrations in order to observe the fluorescence quenching effect. Thus,

future researchers may find it helpful to perform this procedure with varying concentrations of mercury. If this is performed, a standard curve of concentration versus fluorescence quenching may be generated, and the quantification abilities of the biosensor may be observed. It is apparent from the data, however, that the mercury presence did not alter the fluorescence peak significantly or consistently under the current experimental conditions.

UV-Vis data of the AuNP aliquots

Based on the UV-vis data, there is reason to suspect that the Hg-bound DNA affected the nanoparticles, since the UV-vis spectra showed every sample processed with Hg-bound ssDNA had a significantly lower light absorbance than the samples with no mercury. The red shift also occurred in the Hg-bound samples, suggesting that the AuNP-ssDNA complex had been formed. What is peculiar, however, is that only one of the non-Hg-bound samples produced a red shift. It was even more peculiar to not observe the shift in most of the non-Hg-bound samples, as the procedure performed for these samples was the same as the method for those prepared in Yang et al.’s work, which did produce successful red shifts with their samples at similar wavelengths and intensities. The possibility of an unknown, consistent error in the non-Hg-bound sample preparation is unlikely, as procedures were strictly adhered to, but the possibility of experimental error cannot be discarded based on this data.

The diminished absorbance observed for the Hg-bound samples is an interesting phenomenon that warrants discussion. One possible reason for this observation involves absorbance shadowing. There was more than simply mercury added to the samples, as molecules of exonuclease I were still present. Being a macromolecule, exonuclease is large in comparison to some of the other components in the mixture. This may be more of a problem for this procedure as opposed to procedures that use larger gold nanoparticles, as 5 nm AuNPs are closer in size to the exonuclease. As a result, absorbance shadowing (a phenomenon in which large molecules block the light that a UV-vis spectrometer shines through a sample, keeping the light from striking smaller molecules) may be a possibility in this case, which would explain the lower absorption of the sample. This would be a problem because it is necessary for the AuNP-ssDNA complexes to absorb as much of the radiation as possible so that the fluorescence can be produced. A small fluorescence response can produce an inadequate signal-to-noise ratio for good results. Based on this hypothesis, this method may not be suitable for producing a mercury-indicating biosensor.

In future studies, it may be worth researching the lower absorbance that resulted from the mercury-bound DNA. Unfortunately, there was not enough time to create and evaluate samples without exonuclease I incubation, and this should be investigated. But in that event, the signal may have been even more difficult to interpret since exonuclease I’s purpose was to eliminate background noise from the fluorescence

spectral data. Regardless, if mercury was the cause of the absorbance change, then it would be important to determine if it did so by the nature of the interaction, or if it lowered the absorbance in its unbound state. Tests for the selectivity of the mercury regarding this absorbance change should be conducted as well.

Additional concerns

Finally, it was difficult to determine the correct amounts and concentrations to include in the samples for spectroscopy. The amounts and concentrations of the components of the mixture, especially the buffer, varied between the research projects that were performed with similar methods to this one (Li et al., 2018, Liu et al., 2017, Yang et al., 2006). Therefore, it is unknown whether the optimal concentrations and amounts were used in this research, which could be a source of the uncertainty of the results of the UV-vis spectrometry as well as the fluorescence spectroscopy.

CONCLUSION

In this project, the method suggested by Yang et al. did not produce a biosensor that adequately indicated the presence of mercuric ions; it is possible that the gold nanoparticles were too small to produce a detectable fluorescence signal. In addition, the red shift of absorbance that would indicate the formation of the AuNP-ssDNA complex appeared for the samples containing DNA bound to mercury, but it did not appear for the samples without mercury. This calls the validity and effectiveness of the biosensor into question. However, other methods for confirming the formation of the complex were unable to be performed due to the timeframe for this project, and these methods may be a good starting place for future research. One process to confirm the complex formation would be to conduct a polyacrylamide gel electrophoresis, in which a high molecular weight band would indicate the complex formation, while a lower molecular weight band and other visible bands would indicate no complex formation. This could not be performed within the timeframe of this project. An alternative way to confirm the formation of the complex is with TEM imaging. This type of testing might be available in the future through collaboration with other institutions. Evaluating samples with these methods would allow for a more complete picture on the complexation status of the components.

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