Psychological Responses and Behaviors During the Initial Stages of COVID-19 Among General US Population By Connor Tripp, M.A., M.S. July, 2022 Director of Dissertation: Samuel F. Sears, PhD Major Department: Psychology ABSTRACT Background: The novel coronavirus, COVID-19, has posed a major public health risk across the world. The threat of the virus and the resulting quarantine or “stay-home-orders,” likely impacted physical and mental health across the US population. The purpose of this study was to examine the psychological responses and behaviors during the initial stages of the COVID-19 epidemic in a US sample, applying the Common-Sense Model of illness to encourage a more comprehensive conceptualization of psychological and behavioral response to COVID-19. Methods: This study used Amazon Mechanical Turk (MTurk), a widely used data-sourcing tool, to assess the psychological impact of COVID-19 and quarantine for a large sample (N = 584) of US citizens, applying the Common-Sense Model of Illness as a way of predicting cognitive and emotional representations of the virus, engagement in precautionary and self-care behaviors, and appraisals of control. Conclusions: These results suggested that US citizens felt knowledgeable about COVID-19 and confident in precautionary behaviors to control the spread of COVID-19. However, while most US citizens reported normative levels of emotional distress in response to COVID-19, about 19- 30% reported scores that indicated moderate to severe distress. Greater distress predicted decreased engagement in self-care behaviors and certain precautionary behaviors. People who engaged in both precautionary and self-care behaviors felt that they were helpful. While the results of this study are preliminary and further study is needed, these results suggest that Leventhal’s Common-Sense Model of Illness may be applicable to understanding the US citizen experience of COVID-19. Psychological Responses and Behaviors During the Initial Stages of COVID-19 Among General US Population A Dissertation Defense Presented to The Faculty of the Department of Psychology East Carolina University In Partial Fulfillment of the Requirement for the Degree PhD in Health Psychology by Connor Tripp July 2022 © Connor Tripp, M.A., M.S., 2021 TABLE OF CONTENTS LIST OF TABLES ............................................................................................................ vii LIST OF FIGURES ............................................................................................................ ix CHAPTER 1: SYNOPSIS .................................................................................................... 1 CHAPTER 2: INTRODUCTION …………………………………………………………. 3 COVID-19 ............................................................................................................ 3 Origin ............................................................................................................ 4 Prevalence in the United States...................................................................... 4 Clinical Presentation and Transmission ......................................................... 4 High Risk Groups .......................................................................................... 5 Public Health Recommendations ................................................................... 6 Psychological Impact of COVID-19……………………………………………….. 7 Psychological Impact of a Pandemic………………………………………. 7 Psychological Impact of a Quarantine……………………………………… 7 Early Psychological Impact of COVID-19…………………………………. 8 Healthcare Workers and COVID-19……………………………………….. 9 General Public and COVID-19……………………………………………. . 10 Leventhal’s Common-Sense Model of Illness ……………………………………. . 13 The Common-Sense Model Applied to COVID-19………………………. . 15 Specific Aims………………………………………………………………. 17 Hypotheses…………………………………………………………………………. 18 CHAPTER 3: Methods and Materials ................................................................................... 19 Method………. .......................................................................................................... 19 Measures…………. ................................................................................................... 19 Statistical Analyses………………………………………………………………… 21 CHAPTER 4: RESULTS…………………………………………………………………… 24 Aim 1: Demographic Information and USA-Revised NUSQC Responses………… 24 Sample………………………………………………………………............ 24 COVID-19 Symptoms, Health Literacy, and Perceptions………………….. 26 Engagement in Precautionary Behaviors…………………………………... 28 COVID-19 Knowledge…………………………………………………….. 31 Aim 2: IES-R………………………………………………………………………. 33 Aim 3: DASS-21…………………………………………………………………… 35 Aim 4: SCBI-RQ and other Reported Self-Care Behaviors……………………….. 40 Aim 5: Common Sense Model of COVID-19……………………………………... 44 Cognitive Representation…………………………………………………... 44 Emotional Representation………………………………………………….. 50 Engagement in Self-Care Behaviors……………………………………….. 50 Engagement in Precautionary Behaviors…………………………………... 52 Appraisals of Helpfulness………………………………………………….. 52 Analysis of the Model ................................................................................................ 52 Predictability of Cognitive Representation and Emotional Representation .. 52 Cognitive Representation and Precautionary Behaviors ................................ 53 Emotional Representation and Precautionary Behaviors ............................... 55 Cognitive Representation and Self-Care Behaviors ...................................... 57 Emotional Representation and Self-Care Behaviors ...................................... 57 Precautionary Behaviors and Perceived Helpfulness .................................... 57 Self-Care Behaviors and Helpfulness ............................................................ 58 Helpfulness and Precautionary Behaviors and Helpfulness of Self-Care ...... 59 Multiple Regression Analyses ................................................................................... 59 Covering mouth when coughing and sneezing .............................................. 59 Avoiding sharing of utensils .......................................................................... 60 Washing hands with soap and water .............................................................. 60 Washing hands after coughing, rubbing nose, or sneezing ............................ 60 Wearing mask regardless of presence or absence of symptoms .................... 60 Washing hands after touching contaminated objects ..................................... 61 Cleaning and disinfecting surfaces in your home .......................................... 61 Using hand sanitizer, with 60% alcohol ........................................................ 62 Social distancing, as able ............................................................................... 62 Staying home, aside from essential purposes ................................................ 62 Avoid rubbing eyes, nose, and mouth ............................................................ 62 Self-Care Behavior......................................................................................... 63 CHAPTER V: CONCLUSIONS ........................................................................................... 64 Discussion…... ........................................................................................................... 64 Common-Sense Model................................................................................... 67 Clinical and Policy Implications ................................................................................ 70 Strengths…… ............................................................................................................ 71 Limitations…. ............................................................................................................ 72 Future Directions ....................................................................................................... 72 Conclusions… ............................................................................................................ 73 REFERENCES ...................................................................................................................... 75 APPENDIX A: NUSCQ-USA .............................................................................................. 79 APPENDIX B: SCBI-RQ ..................................................................................................... 88 APPENDIX C: IRB ............................................................................................................ 89 LIST OF TABLES 1. Table 1. Major Findings of Wang and Colleagues (2020).........................................11 2. Table 2. Sociodemographic Information ...................................................................24 3. Table 3. Health Information .......................................................................................25 4. Table 4. Physical Symptom Experience ....................................................................26 5. Table 5. Risk Perception ............................................................................................27 6. Table 6. Engagement in Precautionary Behaviors .....................................................29 7. Table 7. COVID-19 Knowledge and Desires for Additional Information ................32 8. Table 8. IES-R ...........................................................................................................33 9. Table 9. DASS-21 Scores ..........................................................................................35 10. Table 10. DASS-21 Depression Subscale by Demographics ....................................36 11. Table 11. DASS-21 Anxiety Subscale by Demographics .........................................37 12. Table 12. DASS-21 Stress Subscale by Demographics .............................................38 13. Table 13. Engagement in Self-Care Behaviors over the Past Month ........................40 14. Table 14. Other Self-Care Behaviors Reported During Quarantine ..........................42 15. Table 15. Initial CFA of Cognitive Representation Scales ........................................45 16. Table 16. Second CFA of Cognitive Representation Scales......................................46 17. Table 17. Preliminary PCA of Cognitive Representation Items ................................47 18. Table 18. Cognitive Representation Components and Variable Correlations ...........48 19. Table 19. SCBI-RQ Factor Structure .........................................................................51 20. Table 20. Cognitive Representation and Emotional Representation .........................52 21. Table 21. Cognitive Representation and Precautionary Behaviors ...........................53 22. Table 22. Emotional Representation and Precautionary Behaviors ...........................55 23. Table 23. Cognitive Representation and Self-Care Behaviors ..................................57 24. Table 24. Emotional Representation and Self-Care Behavior Engagement ..............57 25. Table 25. Precautionary Behaviors and Helpfulness .................................................58 LIST OF FIGURES 1. Figure 1. Common-Sense Model ...............................................................................16 Psychological Responses and Behaviors During the Initial Stages of COVID-19 Among General US Population I. Synopsis In December 2019, Chinese health officials noticed a string of cases of an atypical pneumonia, unresponsive to antibiotics. The virus was eventually recognized as a beta-strain of the coronavirus, similar to that of SARS-CoV in 2002-2003, and it was named COVID-19. Public health authorities in China declared COVID-19 a public health crisis on January 20, 2020 (Li, Wang, Xue, Zhao, & Zhu, 2020). The first case of COVID-19 in the United States was diagnosed January 21, 2020 (Center for Disease Control and Prevention (CDC), 2020). Around this time, most states adopted “stay-at-home” orders, forcing many businesses to close and schools to adopt virtual course administration methods. Guidelines for social distancing and regular hand washing to reduce the spread of the virus had also been put in place (CDC, 2020). By April 2020, the literature on the psychological impacts of COVID-19 and “stay-at-home,” or quarantine, orders was largely studied in Chinese samples. The Chinese literature suggested high levels of anxiety and psychological impact in the general public, but particularly for women, healthcare workers, and individuals living in areas with high rates of infection (Li et al., 2020; Lai et al., 2020; Wang et al., 2020). However, the Chinese literature also suggested protective factors, including perceptions of specific, accurate, and up-to-date health information related to the virus, as well certain precautionary behaviors such as avoiding the sharing of utensils and washing hands after coughing, sneezing or nose rubbing (Wang et al., 2020). At this time, there were an abundance of editorials and commentaries in the US literature related to possible mechanisms for psychological care during the COVID-19 outbreak, however, the psychological impacts of COVID-19 and quarantine for US citizens was unknown. This 2 study explored the psychological impact of COVID-19 and quarantine in a large US sample, applying Leventhal’s Common-Sense Model of Illness in order to understand the relationships between cognitive and emotional representations of the health threat and self-care behaviors in quarantine. II. Introduction COVID-19 Origin. In December of 2019, health officials in Wuhan, China became aware of an atypical pneumonia with unknown etiology (Lake, 2020). Patients were experiencing a range of symptoms, primarily including respiratory distress and fever, that was not resolved with 3-5 days of treatment with antibiotics. The illness was eventually identified as a beta strain of coronavirus. Coronaviruses are common strains of ribonucleic acid (RNA) viruses that infect a wide range of animals and less commonly humans; there are alpha, beta, gamma and delta strains of coronavirus (Velavan & Meyer, 2020). Similar to the severe acute respiratory syndrome (SARS- CoV) in 2002-2003, the current coronavirus has been identified as a beta strain and has been officially named SARS-CoV2, better known as COVID-19. COVID-19 is believed to infect the lung alveolar epithelial cells via receptor mediated endocytosis. While early in the pandemic it was theorized that an antiretroviral regimen may help to stop the progression of the virus, there is still no identified cure to date (Velavan & Meyer, 2020). The introduction of vaccines that were rapidly formulated has been the primary advance in the management of COVID-19 internationally. Initial cases of the virus have been linked to a possible source, a South China Seafood Market, also known as a “wet” market, where a range of different animals were sold including chickens, rats, and snakes (Lake, 2020; Velavan & Meyer, 2020). Similar to SARS-CoV, COVID-19 is believed to have been transmitted to humans from common mammalian hosts, specifically bats (Velavan & Meyer, 2020). It is possible that the transmission occurred directly via exposure to bats or by transmission from bats to other animals that humans are more commonly exposed to, such as raccoon dogs, which were also sold at the “wet” market (Lake, 2020). 4 Prevalence in the United States. Since its initial presentation in Wuhan, China, COVID- 19 has been identified by the World Health Organization (WHO) as a global health emergency, spreading quickly across the continents, with numbers of infections and associated deaths increasing exponentially by the day (Velevan & Meyer, 2020). At the time of this study, according to the CDC, since the first confirmed US case on January 21, 2020, there had been over 200,000 confirmed cases of COVID-19 in the United States, with over 4,500 deaths and cases in every state (CDC, April 4, 2020). This number has continued to increase exponentially with increased testing capabilities and continued transmission. More recent reports indicate at total of 30, 492, 334 confirmed cases in the United States with over 553, 681 deaths in the United States alone (CDC, April 5, 2021). While experts are now hopeful these numbers will start to decrease with the roll-out of several vaccines, at the time of this study, there were no vaccines and no indication of when the pandemic would end. Clinical Presentation and Transmission. The clinical presentation of COVID-19 is complex and highly variable, with patients ranging from asymptomatic to severely symptomatic. For patients who are symptomatic, symptoms typically include fever, nasal congestion, fatigue, and respiratory symptoms (e.g. chest tightness; dyspnea) (Velavan & Meyer, 2020). Less commonly, patients experience gastrointestinal symptoms, such as diarrhea (Lake, 2020). While most patients recover, some patients progress to severe respiratory distress, some experience secondary infection, and some sustain virus-associated myocardial injury, all leading to possible death. The virus is transmitted human-to-human via respiratory transmission or contact with infected secretion (e.g. sneeze); contact with fomites, or surfaces with traces of the virus is also a concern (Lake, 2020). The WHO has estimated that the rate of transmission is 1.4-2.5, meaning 5 each person who has the virus transmits the virus to 1.4-2.5 others; comparatively, the rate of transmission for the seasonal flu is 1.28 and for the measles is 12-18 (Lake, 2020). Once the virus has been contracted, the median incubation period has been estimated at 5.2 days with a range of 0-24 days, meaning symptoms will present within 5 days for most people, however, there is variability (Velavan & Meyer, 2020). In February 2020, the estimated fatality rate of COVID-19 was 2.2%, compared to 9.6% during the SARS-CoV pandemic in 2002-2003 (Velavan & Meyer, 2020). However, it was difficult to make accurate estimations at the time of this study due to likely biases in identification and lack of testing accessibility; there was likely a bias toward individuals with the most severe cases, as individuals who were asymptomatic or only mildly symptomatic likely went unidentified (Lake, 2020). Current estimates of fatality rates are closer to 1%, likely due to improvements in access to testing, guidelines around getting tested and treatment (CDC, 2020). High Risk Groups. While all persons are susceptible to the viruses, there are trends with regards to symptomology and progression. For example, children are susceptible to the virus but most commonly are asymptomatic and pose greater risk to others as carriers (Lake, 2020). The CDC has announced that groups at highest risk for serious illness with COVID-19 are individuals 65 years of age and older and individuals with chronic lung disease, moderate to severe asthma, cardiovascular conditions, immunocompromising conditions (e.g. HIV), severe obesity (i.e. BMI ? 40), diabetes, chronic kidney disease, and liver disease (CDC, 2020). Individuals who are pregnant or homeless have also been identified as members of high-risk groups (CDC, 2020). Public Health Recommendations. The CDC made several recommendations to minimize the spread of COVID-19 in the United States. Recommendations include cleaning 6 hands often by washing them or using hand sanitizer with 60% alcohol, avoid touching eyes, nose, and mouth, avoiding close contact with individuals who are sick, staying home, maintaining a 6-foot distance from people in public, covering mouth and sneezes with a tissue rather than hand or elbow, and cleaning household surfaces with disinfectants frequently (CDC, 2020). At the time of this study, it was recommended that individuals avoid gatherings of 10 or more people when possible (CDC, 2020) and universities had asked that students return home and finish their semester courses virtually (e.g. WebEx, Zoom, other online forums). Restaurants and other businesses were temporarily closed, posing financial concerns for individuals working hourly-wage jobs, as well as the global economy. In order to ensure individuals were following guidelines to minimize the spread of the virus, most states put “stay-at-home” orders in place, instructing individuals to not leave home except to go to the grocery store, pharmacy, vet, or doctor. Individuals under “stay-at-home” orders were advised that if they go outside to exercise or walk dogs, they maintain 6-feet of distance from others; CDC guidelines even suggested wearing masks when around other people, regardless of whether or not one was experiencing symptoms (CDC, 2020). Similar practices, referred to as “quarantines,” or separation from others to prevent the possible spread of infectious disease, can be traced back to Italy in 1127 during leprosy outbreaks (Brooks et al., 2020). While rare, quarantines have been used in many countries to prevent spread of infectious disease such as the plague, Ebola, H1N1, and SARS-CoV (Brooks et al., 2020). While effective for reducing transmission of disease, there are likely psychological impacts to living in quarantine. Psychological Impact of COVID-19 7 Psychological well-being is undoubtedly affected during viral outbreaks and should be explored and considered, due to associated behavioral changes and their effects on the success of public health strategies to manage pandemics (Brooks et al., 2020; Asmundson & Taylor, 2020). Psychological Impact of a Pandemic. Based on research during previous pandemics, psychological function prior to outbreak is likely to impact function during and following outbreaks. For example, health anxiety, or hypervigilance to bodily sensations and perceived illness, is believed to exist on a continuum from low to high; within the context of a viral outbreak, some normative health anxiety is likely adaptive, however, there are negative consequences to existence on both ends of the health anxiety spectrum (Asmundson & Taylor, 2020). Based on research during the H1N1 epidemic, we know that individuals with low perceived risk and low health anxiety were less likely to follow public health recommendations for safety – such as washing hands frequently (Asmundson & Taylor, 2020). However, for people who are high risk or have higher levels of health anxiety, individuals may be hypervigilant to bodily sensations, causing overutilization and subsequent increased risk for exposures. Additionally, individuals with high health anxiety may engage in excessive handwashing (i.e. raw; risk for infection), avoidance of medical care for fear of contagion, and “panic purchasing” of essential items (e.g. hand sanitizer; toilet paper) that may have communal consequences. Psychological Impact of Quarantine. With the novel and extreme “stay-at-home” guidelines in the majority of the states at the time of this study, enforcing business closures and quarantine for the general public, it was important to also consider the psychological impacts of quarantine. A review of historical quarantine literature identified 24-studies, assessing the psychological impacts quarantine during various infectious disease outbreaks including SARS- 8 CoV, Ebola, and H1N1 (Brooks et al., 2020). Results of this meta-analysis indicated some common psychological symptoms in response to living in quarantine and adjustment to life after quarantine. Stressors during quarantine periods include separation from loved ones, boredom, inadequate supplies, and inadequate information from public health authorities (Brooks et al., 2020). Common psychological symptoms include anxiety, anger, fear, loneliness, annoyance, post-traumatic stress symptoms, avoidance, guilt, and sadness. After a quarantine period, financial loss and stigma towards certain groups, particularly healthcare workers and minority populations (e.g. Asian Americans), are stressors that likely influence the persistence of consequential psychological symptoms such as anger, anxiety, and avoidance, that may persist months after quarantine is lifted (Brooks et al., 2020). Results of this review also suggest that length of quarantine may predict greater psychological impacts, specifically 10 days or more (Brooks et al., 2020). Potential high-risk groups identified included younger age, individuals with pre-existing mental health problems, healthcare workers, and parents with 1-2 children; however, results related to high-risk groups were often noted to be inconsistent between studies (Brooks et al., 2020). It is possible that inconsistencies between studies reflect different disease states and associated risks; for example, H1N1 was known to affect children to a greater extent than other viruses, which may have increased the psychological impact for parents. Early Psychological Impact of COVID-19. At the time of this study, literature regarding the psychological impacts of COVID-19 had investigated impacts on the Chinese general public and healthcare workers. Li and colleagues (2020) investigated the psychological impacts of COVID-19 on the general public in China, analyzing social media data from the week prior to declaration of a public health crisis in China, January 13-19, to the week after, January 20-26. 9 Data from 17,865 users of a social media site, Weibo, was collected and analyzed with linguistic categorization software. The sample included members of the general public, 25% male, ranging in age from 8-56 years, with a median of 33 years. Analysis of the data indicated significant differences in the emotional valence of social media posts, between the two weeks. Specifically, in the week following declaration of a public health crisis, there was an increase in negative emotional terms (e.g. anxiety, worry, depression) and a decrease in positive emotional terms (e.g. happy). Additionally, analysis of the data indicated significant increases in terms that express concern for health and family and decreases in terms of concern for leisure and friends (Li et al., 2020). The authors suggested that uncertainty and low predictability surrounding COVID-19 and perceived risk led to the increase in negative emotions, sensitivity to social risk, and a decrease in positive emotions and life satisfaction (Li et al., 2020). Healthcare workers and COVID-19. Based on research from the 2003 SARS-CoV outbreak of 2002-2003, Lai and colleagues (2020) hypothesized that healthcare workers may be at heightened risk for psychological distress in response to COVID-19 due to exposure, overwhelming workload, limited personal protection equipment, media coverage, lack of specific treatments, and feelings of inadequate support that were present in the early stages of the COVID-19 outbreak (Lai et al., 2020). In order to assess the psychological impacts of COVID- 19 on healthcare workers in China at this time, researchers administered a survey battery to 1,257 healthcare professionals at 34 hospitals in China between January 29 and February 3, 2020 (Lai et al., 2020). Participants included 764 nurses and 593 physicians, 522 (42%) of which were identified as frontline healthcare workers, working in fever clinics or wards for COVID-19. The survey battery included the Patient Health Questionnaire (PHQ-9) as a measure of depression, Generalized Anxiety Disorder – 7 (GAD-7) as a measure of anxiety, Insomnia 10 Severity Index (ISI) as a measure of insomnia, and the Impact of Events Scale – Revised (IES – R) as a measure of COVID-19 specific distress. Results suggested that a high number of participants endorsed psychological symptoms; 634 (50%) endorsed symptoms of depression, 560 (44%) endorsed symptoms of anxiety, 427 (34%) endorsed symptoms of insomnia, and 899 (72%) endorsed distress (Lai et al., 2020). Median scores were 5 (2-8) on the PHQ-9, indicating mild depressive symptoms, 4 (1-7) on the GAD-7, indicating mild to moderate anxious symptoms, 5 (2-9) on the ISI, suggesting normative sleep, and 20 (7-31) on the IES – R, indicating normative to partial concern for PTSD. Results also indicated that groups with the most severe psychological symptoms on all scales were women, nurses, frontline healthcare workers, and those working in Wuhan hospitals (Lae et al., 2020). These numbers suggest groups that may be at particular risk in the US include women, healthcare workers, and those working in high-risk regions (e.g. New York). General Public and COVID-19. Prior to the current study, the only one that assessed psychological impact on the general public was based in China (Wang et al., 2019). Wang and colleagues (2020) explored that psychological impact of COVID-19 outbreak in the general public of China, between January 31 and February 2, 2020. This study administered anonymous online surveys via a “snowballing” technique; specifically, they sent the survey to university students in China and encouraged them to send the survey to others. The final sample consisted of 1,120 participants (67.3% female, 53.1% aged 21.4-30.8, 53% married, 67.4% with children, 88% educated) living on mainland China during the outbreak (Wang et al., 2020). The anonymous survey battery included the National University of Singapore Questionnaire on COVID-19, IES-R, and Depression, Anxiety, and Stress Scale -21 (DASS-21). The National University of Singapore Questionnaire on COVID-19 consists of items assessing demographic 11 information (gender, age, education, marital status, etc.), as well as specific information regarding knowledge of COVID-19, perceived contact with COVID-19, perceived risk of contracting COVID-19, engagement in specific precautionary measures (e.g. handwashing, not sharing utensils), and specific physical symptoms over the past 14 days (e.g. fever, cough, difficulty breathing); it also includes a qualitative component, inquiring participant specific desires for knowledge on COVID-19 (Wang et al., 2020). The DASS-21 is a measure of psychological symptoms on three subscales of stress, anxiety, and depression. Major findings from this study are presented in Table 1. Table 1. Major Findings of Wang and Colleagues (2020) Measure Average Minimal Mild Moderate to Severe Score (SD) Psychological Psychological Psychological Impact Impact Impact n (%) n (%) n (%) Impact of 32.98 (15.42) 296 (24.5%) 263 (21.7%) 651 (53.8%) Events (Score ?23) (Score 24-32) (Score ?33) Scale Revised Normal Mild Symptoms Moderate Severe or Extremely Score n (%) Symptoms Severe Symptoms n (%) n (%) n (%) DASS-21 843 (69.7%) 167 (13.8%) 148 (12.2%) 52 (4.3%) Depression (Score 0-9) (Score 10-12) (Score 13-20) (Score 21-42) Subscale DASS-21 770 (63.6%) 91 (7.5%) 247 (20.5%) 102 (8.4%) Anxiety (Score 0-6) (Score 7-9) (Score 10-14) (Score 15-42) Subscale DASS-21 821 (67.9%) 292 (24.1%) 66 (5.5.%) 102 (8.4%) Stress (Score 0-10) (Score 11-18) (Score 19-26) Score (27-42) Subscale Overall, correlational analyses indicated that women, students, and individuals who experienced specific physical symptoms over the prior 14-days (i.e. chills, myalgia, cough, dizziness, coryza, and sore through) experienced greater psychological impact related to the outbreak, as well as higher levels of stress, anxiety, and depression (Wang et al., 2020). 12 Interestingly, participants who indicated that they felt they had up-to-date, specific, and accurate health information indicated lower psychological impact, as well as lower levels of stress, anxiety, and depression (Wang et al., 2020). Additionally, lower psychological impact, stress, anxiety, and depression was associated with engagement in specific precautionary behaviors including avoiding the sharing of utensils with others and washing hands immediately after coughing sneezing, and rubbing nose (Wang et al., 2020). The Chinese literature suggested the psychological impacts of COVID-19 and associated public health measures may be vast. Groups identified as those that may be particularly at risk for psychological distress include those with existing mental health conditions, healthcare workers, women, students, and those with physical symptoms (Li et al., 2020; Lai et al., 2020; Wang et al., 2020). Protective factors included accurate and specific health information, as well as engagement in specific precautionary behaviors (Wang et al., 2020). While there were a vast number of editorials and commentaries suggesting the utility of Telehealth and remote psychotherapy, protocol for psychological treatment during a quarantine and pandemic had not been established at the time of this study. While studies have since investigated psychologic impact on the general public, at this time, the specific psychological impacts of COVID-19 on citizens of the United States were not well-known, nor was there a model for understanding the specific psychological impacts and associated behavioral consequences, or self-care coping behaviors, related to threat of illness and living in quarantine. The current study proposed that the psychologic and behavioral impacts might be explained by Leventhal’s Common-Sense Model of Illness. To our knowledge, this has still not been explored in the literature. Leventhal’s Common-Sense Model of Illness 13 Leventhal’s Common-Sense Model of Illness Representation was developed after a series of studies indicating that health behavior change (e.g. smoking cessation) was best predicted by fear messages presented in combination with an action plan for change, only when the two occurred together, regardless of the salience of the “fear” message (Leventhal, Meyer, Norenz, 1980). Leventhal and colleagues (1980) interpreted this as being reflective of a change in thinking with regards to health threat. In other words, health threat, in combination with an action plan for change, determined coping behaviors and led to the development of the Common- Sense Model of Illness Representation (Diefenbach & Leventhal, 1996). The Common-Sense Model of Illness Representation posits that there are two parallel processes involved in the development of perceptions related to health threat, a cognitive process and an emotional process. The model posits that internal or external cues for illness, such as mass media or physician discussions of illness or somatic sensations, evoke cognitive representation of the illness based on prior illness and treatment experiences (Diefenbach & Leventhal, 1996; Leventhal, Phillips, & Burns, 2016). Cognitive representation of illness influences the emotional representation of the illness, further influencing “action” in terms of treatment seeking or adherence to treatment regimens, and subsequent perceptions of the helpfulness of those actions. The cognitive perception of health threat is determined by five core attributions: identity, timeline, causality, controllability, and consequences (Diefenbach & Leventhal, 1996; Leventhal et al., 2016). Illness identity refers to the label of the illness and associated symptoms; for example, when an individual experiences physical symptoms such as runny nose and a cough, “prototypes” or past experiences are activated, and the individual identifies the symptoms as a reflection of having contracted the “common cold” (Leventhal et al., 2016). Timeline refers to an 14 individual’s perceptions and experiences of rates of onset, duration, and decline; causality refers to an individual’s perception or awareness of contributors to contraction or diagnosis; consequences refer to an individual’s perceptions, experiences, or awareness of possible or likely physical, cognitive, and even social disruptions resulting from the diagnosis or illness; and control refers to an individual’s perception of the ability to treat or be treated for the diagnosis or illness (Leventhal et al., 2016. Emotionally, internal and external cues for illness, paired with cognitive perceptions of risk, evoke emotional reactions to health threat. According to the model, these cognitive and emotional representations of health threat influence an individual’s degree of engagement in preventative or treatment seeking and coping behaviors (Diefenbach & Leventhal, 1996). For example, if a person is exposed to material on the importance of regular mammograms for early detection of breast cancer and perceive themselves to be at risk, provoking a level of anxiety, they will likely start scheduling regular mammograms. The final step in the model is appraisal of the helpfulness of these behaviors (e.g. seeking regular mammograms allowed for early detection and treatment of breast cancer) (Diefenbach & Leventhal, 1996; Leventhal et al., 2016). In order to evaluate illness perception and apply Leventhal’s Common-Sense Model of Illness to various disease states, the Illness Perception Questionnaire (IPQ) was developed (Weinman et al., 1996). This measure was later revised, and a briefer measure was created, the Brief Illness Perception Questionnaire (BIPQ), with since established validity and reliability in various samples across many disease states (Broadbent et al., 2006). Leventhal’s Common-Sense Model of Illness has been applied to both acute and chronic health threats including but not limited to the flu, tetanus, asthma, cardiovascular disease (i.e., 15 myocardial infarction and heart failure), diabetes, and traumatic brain injury (Leventhal et al., 2016; Snell et al., 2013). Overall, studies suggests that “action” or health behavior is dependent upon a person’s representations of both the diagnosis/illness and treatments, as well as their past experiences. For example, while most professionals and laypersons recognize common symptoms of cardiovascular disease, many people who present with myocardial infarction or heart failure are delayed in seeking treatment due to the experience of atypical symptoms, such as fatigue, swelling, and shortness of breath, versus the more typical symptoms of chest and shoulder pain (Leventhal et al., 2016). Further research examining the role of health threat messages has supported preliminary work in this area, highlighting that threat messages, regardless or salience, predict health behaviors, but only when accompanied by a concrete and specific action plan, requiring perception of personal health threat (e.g., proximity to environmental origin of infection) in the absence of somatic symptoms (Leventhal et al., 2016). The Common-Sense Model Applied to COVID-19. The current study proposed that Leventhal’s Common-Sense Model of illness can be applied to COVID-19, explaining individual cognitive and emotional representations of COVID-19, as well engagement in precautionary and self-care behaviors, and the perceived helpfulness of these behaviors. The results of Wang and colleagues (2020) provided preliminary support, suggesting that perceptions of adequate health information and knowledge about the virus (e.g. identity; cause) and engagement in precautionary behavior (e.g. controllability) were associated with decreased psychological symptoms in response to the virus. Other important factors to consider in exploring this model include the incongruence between symptom experience for individuals diagnosed with COVID- 19, with some being extremely symptomatic, mildly symptomatic, or asymptomatic, as well as 16 perceptions related to threat messages from the media and inconsistencies in action plans created by the CDC due to the novelty of the virus and perceived uncertainty around best modes of prevention. Figure 1. Common-Sense Model Cognitive Representation: Membership in high risk group Beliefs about likelihood of contracting Understanding of the virus Expectations of timeline for risk Engagement in In the past 14 days: Precautionary Appraisal: Is this Contact with virus Behaviors helping? Proximity to high risk areas COVID19 Physical Symptoms Emotional Representation: Psychologic Impact of Engagement in Appraisal: Is this Threat Self-Care Depression Behaviors helping? Anxiety Stress This model proposed that individual cognitive representations of COVID-19 would be influenced by knowledge and understanding of the virus, membership in a CDC prescribed high- risk group (e.g. 65+ years of age, asthma, lung disease), beliefs about likelihood of contracting the virus, possible contact with COVID-19 in the past 14 days, the experience of physical symptoms (e.g. fever, coughing) in the past 14 days, and beliefs about how long the virus will pose a threat to health. Emotional representations of COVID-19 could be influenced by psychologic impact of the outbreak, perceived risk, and “stay-at-home” orders, and may include symptoms of anxiety, 17 depression, and stress. This model also suggested that cognitive and emotional representations of COVID-19 likely influence an individual’s engagement in CDC suggested precautionary measures (e.g. cleaning surfaces frequently, staying home), as well as self-care behaviors (e.g. maintaining contact with close friends, physical activity), and consequential appraisals of the helpfulness of these behaviors. Specific Aims: 1. This study aimed to describe attitudes related to COVID-19 and engagement in precautionary behaviors in response to COVID-19 for US citizens [i.e., USA Revised-National University of Singapore COVID-19 Questionnaire (NUSCQ)]. 2. This study aimed to describe the psychological impact of COVID-19 and quarantine on US citizens (i.e., IES-R). 3. This study aimed to describe psychological symptoms in response to COVID-19 and quarantine for US citizens (i.e., DASS-21). 4. This study aimed to describe engagement self-care behaviors within the context of COVID-19 and quarantine, and develop a measure of self-care behaviors, specific to quarantine situations in response to pandemic [i.e., Self-Care Behavior Inventory - Revised for Quarantine (SCBI-RQ)]. 5. This study aimed to provide evidence for a Common-Sense Model of COVID-19 (i.e., USAR-NUSQ; questions from BIPQ, revised for COVID-19 and added to USAR-NUSQ; IES-R; DASS-21; SCBI-RQ). Hypotheses: Aims 1-3 represent descriptive analyses designed to describe the reported impact across psychological functioning indices. Aim 4 described specific self-care behaviors. Qualitative 18 information provided with this measure was coded and analyzed, descriptively to form a more comprehensive measure of self-care behaviors within the context of quarantine. No specific hypotheses were offered for these analyses. Aim 5 assessed the utility of the Common-Sense Model for predicting engagement in precautionary and self-care behaviors, within the context of COVID-19 and quarantine. It was hypothesized that cognitive and emotional representations of COVID-19 and quarantine would predict engagement in precautionary and self-care behaviors. It was further hypothesized that engagement in precautionary and self-care behaviors will predict appraisals of helpfulness of these behaviors for reducing threat. III. Methods and Materials Method This study used a well-established data sourcing program, Amazon Mechanical Turk (MTurk), to examine the psychological and behavioral impacts of the COVID-19 virus and quarantine on the general US population. Four measures were entered into Qualtrics and administered to 1,200 US participants enrolled in the MTurk system as survey takers. Sample size estimates were approximated using multiple considerations. First, we sought a sample that would be comparable to what was at the time the most recent, similar study of the psychological impact of COVID-19 on the general population in China (Wang et al., 2020). Second, we considered a sample large enough to complete the factor analysis of the new COVID behavioral scales. Third, we completed a statistical power analysis for linear bivariate regression analyses, which indicated a necessary sample size of 472 to reach 95% power for aim 5. Participants were paid $.50 for their participation in this project. Surveys took about 20 minutes to complete. Measures USA -Revised – National University of Singapore Questionnaire of COVID-19 (Appendix 1): This is a 56-item assessment of demographic information, knowledge about COVID-19, engagement in precautionary behaviors, amount of concern related to COVID-19, and perceived risk of contracting COVID-19. It was developed for use in similar projects (Wang et al., 2020), but has been revised for this project for US citizens and to include more recently established information related to COVID-19, including assessment of membership in CDC identified high-risk groups and engagement in more recently prescribed CDC precautionary behaviors. 20 The measure was also revised to include questions that were adapted for COVID- 19 from the Brief Illness Perception Questionnaire (BIPQ), related to perceptions of control and perceptions of the timeline of risk (i.e. “How much control do you feel you have over contraction of COVID-19?,” “If you have been diagnosed, how much control do you feel you have in managing COVID-19?,” “How long do you feel COVID-19 will pose a risk to you?,” and “If you have been diagnosed with COVID-19, how long do you think the virus will last?.” Impact of Events Scale – Revised: This is a 22-item, reliable and well-validated (? = 0.96) measure of traumatic reactions to stressful life events (Creamer, Bell, & Failla, 2003), also used in similar studies assessing the impact of COVID-19 (Wang et al., 2020). DASS-21: This is a 21-item assessment of psychological function, with reliable and well- validated measures of general psychological distress (? = 0.93), as well as three subscales of depression (? = 0.88), anxiety (? = 0.82) and stress (? = 0.90) (Henry, & Crawford, 2005), also used in similar studies assessing the impact of COVID-19 (Wang et al., 2020). Self-Care Behavior Inventory – Revised for Quarantine (Appendix 2): This is a 19-item, researcher-revised assessment of current self-care behaviors, within the context of a quarantine. This measure was revised from a brief measure of self-care behaviors for doctoral students in psychology (Santana & Fouad, 2017), that was based off of a 60- item, comprehensive worksheet of self-care behaviors developed for clinician reflection when working with patients with extensive trauma histories (Saakvitne, Pearlman, & Abrahamson, 1996). The original 19-item SCBI has demonstrated good preliminary 21 reliability and validity (Santana & Fouad, 2017). However, due to the novelty of the COVID-19 virus and quarantine recommendations in the United States this assessment was revised, removing items that are not possible during quarantine (e.g. “take vacations”), adding items that are possible during quarantine (e.g. “virtually connect with others you enjoy”), separating “pray” and “meditate,” and adding a qualitative component to allow individuals to describe their own self-care behaviors during quarantine. The qualitative component will hopefully aid in the development of a more valid tool and better understanding of how people are coping with the novel experience of living in quarantine within the context of a pandemic. Due to the possibility that participants may have been experiencing significant psychological distress at the time of the survey, the following information was provided to each participant at the end of the survey: Thank you for your participation in this study. We understand that this is a difficult time, and some may be experiencing significant distress. If you find yourself in crisis, here are some 24-hour hotlines available for support. For Crisis Text Line, text HOME to 741741. For the National Suicide Prevention Lifeline, call 1-800-273-8255. For LGBTQ Support, visit the Trevor Project website at www.thetrevorproject.org or call 1-866- 488-7386. Statistical Analyses Aim 1: Descriptive statistics were used to describe the sample (i.e. demographic information) and attitudes related to risk for contracting COVID-19, experience of specific, symptoms over the past 14-days, healthcare utilization over the past 14-days, COVID-19 testing status, self-rated 22 health status, related self-reported comorbidities, and engagement in precautionary behaviors during COVID-19 and “stay-at-home” orders, using USAR-NUSCQ self-report. Aim 2: Descriptive statistics were used to describe the psychological impact of COVID-19, using averages and percentiles of scores of the IES-R. Categorical frequencies were provided to describe psychological impact with regards to specific demographic variables (e.g. gender, age, educational attainment, marital status, parental status, occupational status, etc.). Aim 3: Descriptive statistics were used to describe psychological symptomology during COVID- 19 and “stay-at-home” orders, using averages and cut off scores across subscales of the DASS- 21. Categorial frequencies were provided to describe psychological symptomologies (i.e. depressive, anxious, and stress-related) with regards to specific demographic variables. Aim 4: Descriptive statistics were used to describe engagement in self-care behaviors during COVID-19 and “stay-at-home” orders, using self-reported averages on the SCBI-RQ. Additionally, qualitative information provided by participants was coded, analyzed, and provided descriptively in order to inform the development of a more comprehensive measure of self-care behaviors within the context of quarantine. Aim 5: Principal Components analysis were used to establish a measure of the cognitive representation of COVID-19, using specific questions from the US-NUSCQ related to identity, timeline, causality, controllability, and consequences of the virus per the Common-Sense Model of Illness. Items from this measure were used to represent the cognitive representation of COVID-19 in the final model. Questions for this analysis included those related to membership in a high-risk group, experience of symptoms in the last 14-days, self-rated health status, contact with the virus, knowledge of transmission, perceived likelihood of contracting the virus, perceptions of control, and timeline of risk. 23 Principal Components analysis was used to further develop the SCBI-RQ to represent engagement in self-care behaviors in the final model. A factor structure was developed and to use in subsequent analyses. Regression analyses were used to examine the proposed Common-Sense Model of Illness as it relates to COVID-19, specifically assessing fit of the model as it relates to the predictability between cognitive and emotional representations of the virus (i.e. IES-R; DASS-21), engagement in self-care behaviors and specific precautionary behaviors, and appraisals of helpfulness. Appraisals of helpfulness will be represented by responses to the Likert-scale question on the US-NUSCQ: “How confident do you feel the precautionary measures you are taking will help prevent you from contracting or spreading COVID -19?” IV. Results Aim 1. Demographic Information and USA – Revised NUSQC Responses Sample. Data was collected between April 21 to April 29, 2020. A total of 1,159 participants completed the survey. Upon examining survey responses, several participant surveys were removed from the study for various reasons. Participant responses were disregarded if the participant provided an answer other than “Never” on any of the three validity questions. Additionally, one case was removed for indicating age under 18, one case was removed for suspicious answers on demographic questions (i.e. reported no children, pregnant, child under 16 and child over 16), twelve cases were removed for not providing responses on the IES-R, DASS- 21, and SCBI, and 114 were removed for indicating they were from countries other than the United States [e.g. China (n = 6, .9%), Brazil (n = 20, 2.7%), and India (n = 33, 3.6%)]. After removing questionable responses, the final sample size was N = 584, with a 50.39% rate of exclusion. Gender was approximately evenly distributed (n = 309, 52.9% female). The mean age of the sample was 41.14 years (SD ± 13.49), with a median of 38. The youngest participant was 18 years of age and the oldest was 78 years of age. Participants were categorized by age group to describe the experience of young adults aged 18-44 (n = 378, 65.7%), middle- aged adults aged 45-64 (n = 164, 28.1%), and older adults aged 65 and older (n = 42, 7.2%). Other sociodemographic information for the sample is provided in Table 2. Table 2. Sociodemographic Information Variable n (%) Employment Status Employed 443 (75.9) Homemaker 18 (3.1) Retired 42 (7.2) 25 Student 31 (5.3) Unemployed 50 (8.6) Marital Status Divorced/Separated 43 (7.4) Married 287 (49.1) Single 243 (41.6) Widowed 11 (1.9) Parental Status No children 215 (36.8) Has child 16 years or younger 147 (25.2) Has child older than 16 years 99 (17) Has child 16 years or under and has child 31 (5.3) older than 16 years Pregnant and has child 16 years or under 5 (.9) Pregnant 3 (.5) Self-reported health information, including membership in one or more of the CDC identified high-risk groups for serious illness with COVID-19, is provided in Table 3. Of note, most of the participants reported that they had medical insurance (n = 501, 85.8%). Table 3. Health Information Variable n (%) Current Health Status Poor 8 (1.4) Fair 107 (18.3) Good 309 (52.9%) Very Good 160 (27.4) Chronic Medical Conditions/CDC High- Risk Groups Suffer from chronic illness 118 (20.2) 65 years or older 46 (7.9) Moderate to Severe Asthma 42 (7.2) Chronic Lung Disease, other than Asthma 10 (1.7) Cardiovascular Disease 21 (3.6) Currently Pregnant 9 (1.5) Human Immunodeficiency Virus (HIV) 3 (.5) COVID-19 Symptoms, Healthcare Utilization, and Perceptions. Participants were asked to indicate specific physical symptoms they had experienced over the past 14-days. Most 26 participants reported that they had not experienced symptoms (n = 443, 75.9%), however, some experienced one or a range of symptoms (n = 141, 24.1%) (Table 4). Table 4. Physical Symptom Experience Symptom(s) n (%) One symptom endorsed 69 (11.82%) Two symptoms endorsed 31 (5.31%) Three or more symptoms endorsed 41 (7.02%) Despite frequencies of chronic illness and symptom endorsement, only 45 (7.7%) participants reported that they had seen a doctor in the previous 14-days and only 5 (.9%) reported having been admitted to the hospital in the previous 14-days. Interestingly, 58 (9.9%) of participants reported that avoided seeking acute or emergency health care when they thought they might need it, due to fear of COVID-19, and 170 (29.1%) reported that they avoided attendance of regularly scheduled healthcare appointments, due to fear of COVID-19. However, 16 (2.7%) participants reported that they had been tested for COVID-19 over the previous 14- days, 2 (3%) reported that they had been diagnosed with COVID-19, and 54 (9.2%) participants reported that they had been under quarantine by a “health authority” in the previous 14-days. Interestingly, 43 (7.4%) participants reported that they felt discrimination by other countries due to the virus while over half reported feeling like too much “fuss” had been made about COVID- 19 at some point (Table 5). Related to risk perception, individuals were asked about known contact with COVID-19, confidence in their doctor’s ability to diagnose COVID-19, perceptions of individual risk, and beliefs about how long the virus will pose a threat (Table 5). Overall, 25 (4.3%) participants indicated that they had either directly or indirectly had contact with patients suffering from 27 COVID-19. Participants mostly reported indirect contact with a confirmed case (n = 20, 3.4%) or contact with a suspected case (n = 12, 2.1%). Table 5. Risk Perception Variables n (%) Contact with COVID-19 No known contact 535 (91.6) Close contact with a confirmed case 4 (.7) Contact with a suspected case 12 (2.1) Contact with infected materials 1 (.2) Indirect contact with a confirmed case (‘contact of a direct contact) 20 (3.4) Close contact with a confirmed case, contact with a suspected care 1 (.2) Close contact with a confirmed case, no known contact 1 (.2) Close contact with a confirmed case, contact with infected materials 1 (.2) Close contact with confirmed case, indirect contact with a confirmed case 1 (.2) (‘contact of a direct contact’) Indirect contact with a confirmed case (‘contact of a direct contact), contact 2 (.3) with a suspected case Indirect contact with a confirmed case (‘contact of a direct contact), contact 2 (.3) with infected materials Close contact with a confirmed case, contact with a suspected case, and close 2 (.3) contact with infected materials Close contact with a confirmed case, indirect contact with a confirmed case 1 (.2) (‘contact of a direct contact’), contact with a suspected case Close contact with a confirmed case, indirect contact with a confirmed case, 1 (.2) contact with a suspected case, contact with infected materials Confidence in doctor’s ability to diagnose COVID-19 Not at all confident 19 (3.3) Not very confident 46 (7.9) Somewhat confident 309 (52.9) Very confident 161 (27.6) Likelihood of contracting the virus Don’t know 27 (4.6) Not likely at all 139 (23.8) Not very likely 202 (34.6) Somewhat likely 190 (32.5) Very likely 26 (4.5) Likelihood of surviving COVID-19 if infected Don’t know 25 (4.3) Not likely at all 29 (5.0) Not very likely 44 (7.5) Somewhat likely 220 (37.7) Very likely 266 (45.5) 28 Concerns of family members contracting the virus Don’t have family member 9 (1.5) Not worried at all 45 (7.7) Not very worried 76 (13.0) Somewhat worried 120 (20.5) Very worried 92 (15.8) Felt that too much “fuss” had been made about COVID-19 Never 256 (43) Occasionally 108 (18.5) Sometimes 124 (21.2) Most of the time 55 (9.4) Always 41 (7.0) How long do you feel COVID-19 will pose a risk to you? Days 27 (4.6) Weeks 39 (6.7) Months 273 (46.7) 1-3 years 195 (33.4) 3+ years 22 (3.8) Forever 28 (4.8) If you have been diagnosed, how long do you think the virus will last? Days 31 (5.3) Weeks 163 (27.9) Months 60 (10.3) 1-3 years 18 (3.1) Forever 4 (.7) I have not been diagnosed 308 (52.7) Engagement in Precautionary Behaviors. Participants were asked about the frequency of their engagement in CDC recommended precautionary behaviors over the previous 14-days and their perceptions of control over the virus, as a result of engagement in these behaviors and in general (Table 6). Overall, most participants reported engaging in precautionary behaviors “always” or “most of the time,” with the exception of wearing a mask regardless of symptom presence or absence. With regards to mask wearing, 86 (14.7%) reported never wearing a mask, 46 (7.9%) reported occasionally wearing a mask, 70 (12.0%) reported sometimes wearing a mask, 98 (16.8) reported wearing a mask most of the time, and 284 (48.6%) reported always 29 wearing a mask. Additionally, most felt somewhat confident or very confident that engagement in these precautionary behaviors would help prevent them from contracting COVID-19. Table 6. Engagement in Precautionary Behaviors Variables n (%) Covering mouth when coughing and sneezing Never 12 (2.1) Occasionally 15 (2.6) Sometimes 21 (3.6) Most of the time 86 (14.7) Always 450 (77.1) Avoid sharing utensils Never 22 (3.8) Occasionally 19 (3.3.) Sometimes 25 (4.3) Most of the time 84 (14.4) Always 434 (74.3) Washing hands with soap and water Never 5 (.9) Occasionally 17 (2.9) Sometimes 24 (4.1) Most of the time 72 (12.3) Always 466 (79.8) Washing hands immediately after coughing, rubbing rose, or sneezing Never 19 (3.3) Occasionally 26 (4.5) Sometimes 71 (12.2) Most of the time 127 (21.7) Always 341 (58.4) Wearing mask, regardless of presence or absence of symptoms Never 86 (14.7) Occasionally 46 (7.9) Sometimes 70 (12.0) Most of the time 98 (16.8) Always 284 (48.6) Washing hand after touching contaminated objects Never 9 (1.5) Occasionally 18 (3.1) Sometimes 34 (5.8) 30 Most of the time 95 (16.3) Always 428 (73.3) Cleaning and disinfecting surfaces in your home Never 14 (2.4) Occasionally 35 (6.0) Sometimes 74 (12.7) Most of the time 159 (27.2) Always 302 (51.7) Using hand sanitizer, with 60% alcohol Never 48 (8.2) Occasionally 36 (6.2) Sometimes 82 (14.0) Most of the time 106 (18.2) Always 312 (53.4) Social distancing, as able Never 7 (1.2) Occasionally 21 (3.6) Sometimes 21 (3.6) Most of the time 111 (19.0) Always 424 (72.6) Staying home, aside from essential purposes (i.e. grocery store, pharmacy, medical appointments, caregiving) Never 8 (1.4) Occasionally 19 (3.3) Sometimes 21 (3.6) Most of the time 104 (17.8) Always 432 (74.0) Avoid touching eyes, nose, and mouth Never 14 (2.4) Occasionally 41 (7) Sometimes 93 (15.9) Most of the time 190 (32.5) Always 246 (42.1) Extra hours per day at home to avoid COVID-19 I don’t leave home 168 (28.8) 0-5 hours 76 (13) 5-10 hours 119 (20.4) 10-15 hours 71 (12.2) 15-20 hours 42 (7.2) 20+ hours 119 (20.4) 31 Confidence that engagement in precautionary measures will prevent contraction of COVID-19 Not confident at all 9 (1.5) Not very confident 20 (3.4) Neutral 78 (13.4) Somewhat confident 326 (55.8) Very confident 151 (25.9) Control felt over the contraction of COVID-19 (generally) No control at all 25 (4.3) Very little control 93 (15.9) Neutral 60 (10.3) Some control 242 (41.4) A lot control 135 (23.1) Total Control 24 (4.1) I have already been diagnosed 5 (.9) If you have been diagnosed, how much control do you feel you have in managing COVID-19? Days 31 (5.3) Weeks 163 (27.9) Months 60 (10.3) 1-3 years 18 (3.1) Forever 4 (.7) I have not been diagnosed 308 (52.7) COVID-19 Knowledge. Finally, as part of Aim 1, participants were asked about their knowledge of COVID-19, where they get information on the virus, satisfaction with information available, and desires for additional information (Table 7). Overall, participants appeared to be very knowledgeable about COVID-19, however, slightly less than half (n = 250, 42.8%) indicated that they would like to have additional information on COVID-19. While about 93% of people agreed that the virus was transmitted via droplets and contact with contaminated objects, only 71% agreed that airborne transmission was possible; it is notable to point out that the CDC was unsure of airborne transmission at the time of this survey. Most reported that their 32 main sources of information were the internet (53.6%), television (28.4%), or social media (9.6%). Table 7. COVID-19 Knowledge and Desires for Additional Information Variables n (%) Does COVID-19 transmit through droplets? Agree 547 (93.7) Disagree 17 (2.9) Does COVID-19 transmit through contact via contaminated objects? Agree 542 (92.8) Disagree 22 (3.8) Does COVID-19 transmit through airborne? Agree 414 (70.9) Disagree 82 (14.0) Heard information on the following: Number of infected cases 572 (97.9) Number related deaths 574 (98.3) Number of recovered cases 485 (83) Main source of health information Family members 10 (1.7) Internet 313 (53.6) Newspaper 16 (2.7) Radio 13 (2.2) Social media 56 (9.6) Television 166 (28.4) How satisfied are you with the amount of health information available? Very dissatisfied 21 (3.6) Dissatisfied 84 (14.4) Satisfied 363 (62.2) Very satisfied 103 (17.6) Hours spent on social media to obtain COVID-19 health information per day 0-5 hours 531 (90.9) 5-10 hours 40 (6.8) 10-15 hours 11 (1.9) 15-20 hours 2 (.3) Desires for Additional Information Details on symptoms 211 (36.1) Advice on prevention 200 (34.2) Advice on treatment 241 (41.3) Regular updates for latest information 282 (48.3) Regular updates for the outbreaks 274 (46.9) 33 Advice for people who might need more tailored information, such as those 213 (36.5) with pre-existing illness Availability and effectiveness of medicine/vaccines 306 (52.4) How many people are affected and where it is affected 275 (47.1) Travel advice 194 (33.2) How COVID-19 is spread 208 (35.6) What other countries are doing 230 (39.4) Aim 2. IES-R Participants scores on the IES-R, related to COVID-19 and quarantine, indicated an average score of 22.19 (SD = 18.49) with a median of 19. The lowest score on the measure was 0 and the highest was 88. Overall clinical categorizations of scores are presented in Table 8. It is notable that 156 (26.7%) of scores indicated moderate to severe psychological impact. Additionally, of participants who reported that they had avoided acute or emergency care due to fear of COVID-19, 17 (29.3%) indicated minimal psychological impact, 8 (13.8%) indicated mild psychologic impact, and 33 (56.9%) indicated moderate to severe psychological impact; of participants who reported that they had avoided regularly scheduled healthcare appointments due to fear of COVID-19, 81 (47.6%) indicated minimal psychological impact, 32 (18.8%) indicated mild psychologic impact, and 57 (33.5%) indicated moderate to severe psychological impact. Table 8. IES-R Scores Average Minimal Mild Moderate to Score Psychological Psychological Severe (SD) Impact Impact Psychological n (%) n (%) Impact n (%) Total Sample 22.19 335 (57.4) 93 (15.9) 156 (26.7) (18.49) (Score ?23) (Score 24-32) (Score ?33) Gender Female gender 166 (53.7) 59 (19.1) 84 (27.2) Male gender 168 (61.3) 34 (12.4) 72 (26.3) Age Young Adults (18-44) 195 (51.6) 59 (15.6) 124 (32.8) Middle Age (45-64) 106 (64.6) 28 (17.1) 30 (18.3) 34 Older Adults (65+) 34 (81.0) 6 (14.3) 2 (4.8) Marital Status Single 132 (54.3) 41 (16.9) 70 (28.8) Married 169 (58.9) 44 (15.3) 74 (25.8) Divorced/Separated 26 (60.4) 6 (14.0) 11 (25.6) Widowed 8 (72.7) 2 (18.2) 1 (9.1) Parental Status No Children 116 (54.0) 40 (18.6) 59 (27.4) Pregnant 1 (33.3) 1 (33.3) 1 (33.3) Has child 16 years or 82 (55.8) 20 (13.6) 45 (30.6) under Pregnant, has child 16 1 (20.0) 2 (40.0) 2 (40.0) years or under Has child older than 16 69 (69.7) 16 (16.2) 14 (14.1) years Has child 16 years or 21 (67.7) 2 (6.5) 8 (25.8) under, has child older than 16 years Educational Status None/Kindergarten 1 (100.0) 0 (0.0) 0 (0.0) Primary School 0 (0.0) 0 (0.0) 1 (100.0) (Grades 1-6) Lower Secondary 3 (75.0) 0 (0.0) 1 (25.0) School (Grades 7-9) Upper Secondary 38 (58.5) 10 (15.4) 17 (26.2) School (Grades 10-12) College 111 (61.0) 30 (16.5) 41 (22.5) University/Bachelor 116 (52.7) 34 (15.5) 70 (31.8) University/Master or 66 (59.5) 19 (17.1) 26 (23.4) PhD Occupational Status Unemployed 21 (42.0) 12 (24.0) 17 (34.0) Student 10 (32.3) 10 (32.3) 11 (35.5) Employed 261 (58.9) 62 (14.0) 120 (27.1) Homemaker 10 (55.6) 3 (16.7) 5 (27.8) Retired 33 (78.6) 6 (14.3) 3 (7.1) Chronic Illness General (Any) 64 (54.2) 26 (22.0) 28 (23.7) Moderate to severe 15 (35.7) 10 (23.8) 17 (40.5) asthma Other lung disease 4 (40.0) 2 (20.0) 4 (40.0) Cardiovascular disease 10 (47.6) 5 (23.8) 6 (28.6) HIV 0 (0.0) 2 (66.7) 1 (33.3) 35 Aim 3. DASS-21 Participant scores on the DASS-21 indicated a mean depression subscale score of 8.33 (SD = 10.19) and median of 4; scores indicated a mean anxiety subscale score of 5.7 (SD = 8.54) and median of 2; scores indicated a mean stress subscale score of 9.28 (SD = 9.7) and median of 6. Frequencies of scores by categorization for the total sample on the DASS-21 subscales are presented in Table 9. Frequencies of scores by demographic variables for the DASS-21 depression, anxiety, and stress subscales are presented in Table 10, 11, and 12, respectively. Of participants who reported that they had avoided seeking acute or emergency care for COVID-19, 16 (27.6%) reported depressive symptoms in the severe to extremely severe range 18 (31%) reported anxiety symptoms in the severe to extremely severe range, and 17 (29.3%) reported stress in the severe to extremely severe range; of participants who reported they had avoided attendance of regularly scheduled appointments, 35 (20.6%) reported depressive symptoms in the severe to extremely severe range, 30 (17.6%) reported anxiety symptoms in the severe to extremely severe range, and 19 (11.2%) reported stress in the severe to extremely severe range. Table 9. DASS-21 Scores Normal Mild Moderate Severe or Extremely Score Symptoms Symptoms Severe Symptoms n (%) n (%) n (%) n (%) DASS-21 376 (64.4) 50 (8.6) 75 (12.8) 83 (14.2) Depression (Score 0-9) (Score 10-12) (Score 13-20) (Score 21-42) Subscale DASS-21 426 (72.9) 22 (3.8) 42 (7.2) 94 (16.1) Anxiety (Score 0-6) (Score 7-9) (Score 10-14) (Score 15-42) Subscale DASS-21 438 (75.0) 37 (6.3) 60 (10.3) 49 (8.4) Stress (Score 0-10) (Score 11-18) (Score 19-26) Score (27-42) Subscale Table 10. DASS-21 Depression Subscale by Demographics 36 Normal Score Mild Moderate Severe or (Score 0-9) Symptoms Symptoms (Score Extremely Severe n (%) (Score 10-12) 13-20) (Score 21-42) n (%) n (%) n (%) Gender Female gender 202 (65.4) 28 (9.1) 36 (11.7) 43 (13.9) Male gender 174 (63.5) 22 (8.0) 39 (14.2) 39 (14.2) Age Young Adults (18- 218 (57.7) 32 (8.5) 60 (15.9) 68 (18.0) 44) Middle Age (45-64) 122 (74.4) 15 (9.1) 13 (7.9) 14 (8.5) Older Adults (65+) 36 (85.7) 3 (7.1) 2 (4.8) 1 (2.4) Marital Status Single 144 (59.3) 21 (8.6) 33 (13.6) 45 (18.5) Married 191 (66.6) 23 (8.0) 40 (13.9) 33 (11.5) Divorced/Separated 33 (76.7) 4 (9.3) 2 (4.7) 4 (9.3) Widowed 8 (72.7) 2 (18.2) 0 (0.0) 1 (9.1) Parental Status No Children 128 (59.5) 24 (11.2) 28 (13.0) 35 (16.3) Pregnant 2 (66.7) 0 (0.0) 0 (0.0) 1 (33.3) Has child 16 years 95 (64.6) 11 (7.5) 21 (14.3) 20 (13.6) or under Pregnant, has child 3 (60.0) 0 (0.0) 2 (40%) 0 (0.0) 16 years or under Has child older than 76 (76.8) 9 (9.1) 8 (8.1) 6 (6.1) 16 years Has child 16 years 25 (80.6) 2 (6.5) 1 (3.2) 3 (9.7) or under, has child older than 16 years Educational Status None/Kindergarten 1 (100.0) 0 (0.0) 0 (0.0) 0 (0.0) Primary School 0 (0.0) 0 (0.0) 1 (100.0) 0 (0.0) (Grades 1-6) Lower Secondary 3 (75.0) 0 (0.0) 0 (0.0) 1 (25.0) School (Grades 7-9) Upper Secondary 42 (64.6) 2 (3.1) 9 (13.8) 12 (18.5) School (Grades 10- 12) College 120 (65.9) 16 (8.8) 17 (9.3) 29 (15.9) University/Bachelor 137 (62.3) 19 (8.6) 33 (15.0) 31 (14.1) University/Master 73 (65.8) 13 (11.7) 11 (13.5) 10 (9.0) or PhD Occupational Status Unemployed 25 (50.0) 8 (16.0) 5 (10.0) 12 (24.0) 37 Student 15 (48.4) 5 (16.1) 4 (12.9) 7 (22.6) Employed 289 (65.2) 32 (7.2) 61 (13.8) 61 (13.8) Homemaker 13 (72.2) 0 (0.0) 3 (16.7) 2 (11.1) Retired 34 (81.0) 5 (11.9) 2 (4.8) 1 (2.4) Chronic Illness General (Any) 66 (55.9) 15 (12.7) 18 (15.3) 19 (16.1) Moderate to severe 19 (45.2) 7 (16.7) 8 (19.0) 8 (19.0) asthma Other lung disease 6 (60.0) 2 (20.0) 0 (0.0) 2 (20.0) Cardiovascular 11 (52.4) 2 (9.5) 2 (9.5) 6 (28.6) disease HIV 2 (66.7) 0 (0.0) 1 (33.3) 0 (0.0) Table 11. DASS-21 Anxiety Subscale by Demographics Normal Score Mild Symptoms Moderate Symptoms Sever or Extremely (Score 0-6) (Score 7-9) (Score 10-14) Severe Symptoms n (%) n (%) n (%) (Score 15-42) n (%) Gender Female gender 225 (72.8) 12 (3.9) 21 (6.8) 51 (16.5) Male gender 201 (73.4) 10 (3.6) 20 (7.3) 43 (15.7) Age Young Adults (18- 250 (66.1) 18 (4.8) 29 (7.7) 81 (21.4) 44) Middle Age (45-64) 138 (84.1) 3 (1.8) 12 (7.3) 11 (6.7) Older Adults (65+) 38 (90.5) 1 (2.4) 1 (2.4) 2 (4.8) Marital Status Single 166 (68.3) 9 (3.7) 18 (7.4) 50 (20.6) Married 218 (76.0) 10 (3.5) 18 (6.3) 41 (14.3) Divorced/Separated 34 (79.1) 3 (7.0) 4 (9.3) 2 (4.7) Widowed 8 (72.7) 0 (0.0) 2 (18.2) 1 (9.1) Parental Status No Children 151 (70.2) 11 (5.1) 15 (7.0) 38 (17.7) Pregnant 2 (66.7) 0 (0.0) 1 (33.3) 0 (0.0) Has child 16 years 106 (72.1) 4 (2.7) 13 (8.8) 24 (16.3) or under Pregnant, has child 4 (80.0) 1 (20.0) 0 (0.0) 0 (0.0) 16 years or under Has child older than 84 (84.8) 2 (2.0) 5 (5.1) 8 (8.1) 16 years Has child 16 years 27 (87.1) 1 (3.2) 1 (3.2) 2 (6.5) or under, has child older than 16 years 38 Educational Status None/Kindergarten 1 (100.0) 0 (0.0) 0 (0.0) 0 (0.0) Primary School 0 (0.0) 0 (0.0) 1 (100.0) 0 (0.0) (Grades 1-6) Lower Secondary 2 (50.0) 1 (25.0) 0 (0.0) 1 (25.0) School (Grades 7-9) Upper Secondary 50 (76.9) 3 (4.6) 6 (9.2) 6 (9.2) School (Grades 10- 12) College 128 (70.3) 8 (4.4) 18 (9.9) 28 (15.4) University/Bachelor 153 (69.5) 8 (3.6) 15 (6.8) 44 (20.0) University/Master 92 (82.9) 2 (1.8) 2 (1.8) 15 (13.5) or PhD Occupational Status Unemployed 31 (62.0) 6 (12.0) 3 (6.0) 10 (20.0) Student 17 (54.8) 2 (6.5) 4 (12.9) 8 (25.8) Employed 325 (73.4) 13 (2.9) 31 (7.0) 74 (16.7) Homemaker 13 (72.2) 0 (0.0) 4 (22.2) 1 (5.6) Retired 40 (95.2) 1 (2.4) 0 (0.0) 1 (2.4) Chronic Illness General (Any) 84 (71.2) 7 (5.9) 11 (9.3) 16 (13.6) Moderate to severe 22 (52.4) 5 (11.9) 3 (7.1) 12 (28.6) asthma Other lung disease 4 (40.0) 0 (0.0) 3 (30.0) 3 (30.0) Cardiovascular 12 (57.1) 2 (9.5) 3 (14.3) 4 (19.0) disease HIV 2 (66.7) 1 (33.3) 0 (0.0) 0 (0.0) Table 12. DASS-21 Stress Subscale by Demographics Normal Score Mild Moderate Severe or (Score 0-10) Symptoms Symptoms Extremely Severe n (%) (Score 11-18) (Score 19-26) Symptoms n (%) n (%) (Score 27-42) n (%) Gender Female gender 229 (74.1) 22 (7.1) 30 (9.7) 28 (9.1) Male gender 209 (76.3) 15 (5.5) 30 (10.9) 20 (7.3) Age Young Adults (18- 262 (69.3) 27 (7.1) 48 (12.7) 41 (10.8) 44) Middle Age (45-64) 139 (84.8) 9 (5.5) 10 (6.1) 6 (3.7) Older Adults (65+) 37 (88.1) 1 (2.4) 2 (4.8) 2 (4.8) 39 Marital Status Single 169 (69.5) 21 (8.6) 30 (12.3) 23 (9.5) Married 224 (78.0) 13 (4.5) 27 (9.4) 23 (8.0) Divorced/Separated 36 (83.7) 3 (7.0) 2 (4.7) 2 (4.7) Widowed 9 (81.8) 0 (0.0) 1 (9.1) 1 (9.1) Parental Status No Children 151 (70.2) 20 (9.3) 26 (12.1) 18 (8.4) Pregnant 2 (66.7) 0 (0.0) 1 (33.3) 0 (0.0) Has child 16 years 112 (76.2) 7 (4.8) 14 (9.5) 14 (9.5) or under Pregnant, has child 3 (60.0) 0 (0.0) 2 (40.0) 0 (0.0) 16 years or under Has child older than 84 (84.8) 7 (7.1) 3 (3.0) 5 (5.1) 16 years Has child 16 years 27 (87.1) 0 (0.0) 2 (6.5) 2 (6.5) or under, has child older than 16 years Educational Status None/Kindergarten 1 (100.0) 0 (0.0) 0 (0.0) 0 (0.0) Primary School 0 (0.0) 0 (0.0) 0 (0.0) 1 (100.0) (Grades 1-6) Lower Secondary 3 (75.0) 0 (0.0) 0 (0.0) 1 (25.0) School (Grades 7-9) Upper Secondary 49 (75.4) 4 (6.2) 5 (7.7) 7 (10.8) School (Grades 10- 12) College 140 (76.9) 11 (6.0) 16 (8.8) 15 (8.2) University/Bachelor 157 (71.4) 15 (6.8) 28 (12.7) 20 (9.1) University/Master 88 (79.3) 7 (6.3) 11 (9.9) 5 (4.5) or PhD Occupational Status Unemployed 32 (64) 1 (2.0) 7 (14.0) 10 (20.0) Student 22 (71.0) 2 (6.5) 2 (6.5) 5 (16.1) Employed 331 (74.7) 33 (7.4) 48 (10.8) 31 (7.0) Homemaker 14 (77.8) 0 (0.0) 2 (11.1) 2 (11.1) Retired 39 (92.9) 1 (2.4) 1 (2.4) 1 (2.4) Chronic Illness General (Any) 84 (71.2) 12 (10.2) 11 (9.3) 11 (9.3) Moderate to severe 26 (61.9) 5 (11.9) 2 (4.8) 9 (21.4) asthma Other lung disease 7 (70.0) 1 (10.0) 1 (10.0) 1 (10.0) Cardiovascular 12 (57.1) 1 (4.8) 4 (19.0) 4 (19.0) disease HIV 2 (66.7) 1 (33.3) 0 (0.0) 0 (0.0) 40 Aim 4: SCBI-RQ and other reported Self-Care Behaviors Frequencies of engagement in self-care behaviors are presented in Table 13. Mean score on the SCBI-RQ was 30.8 (± 10), with the highest possible score being 57. When asked how helpful engagement in self-care behaviors had been, 134 (22.9%) indicated they were “Very helpful,” 280 (47.9%) indicated they were “Somewhat helpful,” 131 (22.4%) were “Neutral,” 28 (4.8%) indicated they were “Not very helpful,” and 11 (1.9%) indicated they were “Not helpful at all.” Table 13. Engagement in Self-Care Behaviors Over the Past Month Self-Care Behavior n (%) Virtually connect with others you enjoy Never 49 (8.4) Rarely 112 (19.2) Occasionally 283 (48.5) Frequently 140 (24.0) Maintain deep interpersonal relationships Never 40 (6.8) Rarely 122 (20.9) Occasionally 247 (42.3) Frequently 175 (30.0) Stay in contact with important people Never 28 (4.8) Rarely 85 (14.6) Occasionally 248 (42.5) Frequently 223 (38.2) Seek out projects that are exciting or rewarding Never 67 (11.5) Rarely 166 (28.4) Occasionally 248 (42.5) Frequently 103 (17.6) Take time to chat with peers Never 44 (7.5) Rarely 140 (24.0) Occasionally 276 (47.3) Frequently 124 (21.2) Allow yourself to laugh Never 20 (3.4) 41 Rarely 70 (12.0) Occasionally 251 (43.0) Frequently 243 (41.6) Quiet time to complete tasks Never 22 (3.8) Rarely 83 (14.2) Occasionally 269 (46.1) Frequently 210 (36.0) Seek out comforting activities Never 23 (3.9) Rarely 92 (15.8) Occasionally 269 (46.1) Frequently 200 (34.2) Be open to not knowing Never 90 (15.4) Rarely 163 (27.9) Occasionally 212 (36.3) Frequently 119 (20.4) Eat healthy Never 31 (5.3) Rarely 133 (22.8) Occasionally 254 (43.5) Frequently 166 (28.4) Exercise Never 59 (10.1) Rarely 139 (23.8) Occasionally 205 (35.1) Frequently 181 (31.0) Spend time in nature Never 91 (15.6) Rarely 162 (27.7) Occasionally 206 (35.3) Frequently 125 (21.4) Medical care Never 236 (40.4) Rarely 184 (31.5) Occasionally 115 (19.7) Frequently 49 (8.4) Take breaks from virtual work, class, or similar obligations Never 71 (12.2) Rarely 157 (26.9) Occasionally 255 (43.7) Frequently 101 (17.3) Pray 42 Never 238 (40.8) Rarely 105 (18.0) Occasionally 116 (19.9) Frequently 125 (21.4) Meditate Never 255 (43.7) Rarely 128 (21.9) Occasionally 122 (20.9) Frequently 79 (13.5) Connect with spirituality Never 230 (39.4) Rarely 115 (19.7) Occasionally 141 (24.1) Frequently 98 (16.8) Contribute to causes Never 247 (42.3) Rarely 182 (31.2) Occasionally 115 (19.7) Frequently 40 (6.8) Advocate Never 297 (50.9) Rarely 149 (25.5) Occasionally 105 (18.0) Frequently 33 (5.7) Qualitative data was collected related to other self-care activities. A brief review of the data elicited 52 variables or other self-care behaviors. Two researchers independently coded the data. Initial comparisons indicated that researchers were in agreement on 546/581 (94%) responses. After these initial comparisons, researchers reviewed and discussed items on which they disagreed to ensure appropriate coding. The final list of variables and frequencies are provided in Table 14. Table 14. Other Self Care Behaviors Reported During Quarantine Self-Care Behavior Frequency Nothing (e.g. blank; none; n/a) 180 (30.8%) Walking 48 (8.2%) Home Spa Day (e.g. nails, facials) 12 (2.1%) Watch news 2 (.3%) Learning about COVID 2 (.3%) Work/Studying 33 (5.7%) Keeping mind busy 9 (1.5%) Exercise (e.g. running; fitness training) 53 (9.1%) 43 Pets (e.g. dogs; cats; chickens) 27 (4.6%) Cleaning 16 (2.7%) Writing (e.g. journaling; music) 14 (2.4%) Yard work/Gardening 40 (6.8%) Precautionary Behaviors (e.g. washing hands; sanitizing; avoiding people; 43 (7.4%) staying home) Video games 23 (3.9%) Arts and Crafts 19 (3.3%) Reading 51 (8.7%) Solitary Activities (e.g. puzzles; LEGO; sewing/knitting; model trains) 24 (4.1%) Watching TV/Streaming (e.g. Netflix; Hulu) 40 (6.8%) Relaxing 13 (2.2%) Learning new skills/hobbies/language 7 (1.2%) Hot baths/showers 8 (1.4%) Eating well/healthier 25 (4.3%) Cooking 29 (5%) Sleep (e.g. sleeping in; sleeping more) 19 (3.3%) Self-Soothing/Positive Thoughts (e.g. singing/telling everything is okay) 22 (3.8%) Listening to music 12 (2.1%) Dancing 3 (.5%) Being Productive 2 (.3%) Family/Spouse/Friend Time (in person) 37 (6.3%) Alcohol 4 (.7%) Read bible/pray 4 (.7%) Time outdoors 33 (5.7%) Meditation 7 (1.2%) Yoga/Stretching 12 (2.1%) Exploring (e.g. short trips; travel) 5 (.9%) New ways to make money 1 (.2%) Routine/Keep normal schedule 12 (2.1%) Sex (e.g. hooking up; sex; masturbation) 3 (.5%) Marijuana 5 (.9%) Tobacco 1 (.2%) Home Repairs/Projects 12 (2.1%) Online Shopping 1 (.2%) Me-Time 7 (1.2%) Avoiding News 7 (1.2%) Teaching (e.g. children; grandchildren) 2 (.3%) Caring for others 9 (1.5%) Planning future activities (e.g. road trips) 1 (.2%) Recovering from surgery 1 (.2%) Avoiding thoughts of COVID (e.g. worry about family becoming sick) 6 (1.0%) Social Media Events 1 (.2%) Virtually Connecting with loved ones/friends 14 (2.4%) Miscellaneous/Nonsensical Responses 8 (1.4%) 44 Aim 5. A Common-Sense Model of COVID-19 Measures In order to efficiently test the applicability of the Common-Sense Model in understanding responses to COVID-19, different measures were used to represent Cognitive Representation, Emotional Representation, precautionary and self-care behavioral engagement, and perceived helpfulness of behavioral changes. Cognitive Representation. In order to establish a measure of cognitive representation of COVID-19, items from the NUSQC-Revised USA (Appendix 1) were entered into a CFA. Items included in this analysis were hypothesized to represent the five core components of cognitive representation including identity, timeline, causes, consequences, control. The analysis included 37 items in total. Specifically, it included all items from Part B: Symptoms and physical health status excluding 5 and 17-21, as these items were discarded due to invalid responses or were related to behavior; in order to categorize item 1 from this section, responses were coded as either “no symptoms” or experiencing one or more symptoms over the past 14 days. Item 1 from Part C: Contact history, all items from Part D: Knowledge and beliefs about COVID-19, and items 13-18 from Part E: Precautionary measures in past 14 days were also included in this CFA. Hypothesized factors and associated items are presented in Table 15. Initially, in order to establish a measurement scale for each of the latent variables, a regression weight of 1 was set between each latent variable and one its indicator variables (Table 15). Results from the initial CFA are also provided in Table 15. In order to determine “fit” of the model, the comparative fit index (CFI) was considered. In this initial CFA, the CFI was calculated to be .484, suggesting poor fit. Table 15. Initial CFA of Cognitive Representation Scales 45 Cognitive Representation Unstandardized Standardized regression weight regression weight Identity Symptom experience in the past 14 days** 1.00 .360 Doctor visit in the past 14 days .713 .413 Hospital visit in the past 14 days .121 .202 Tested for COVID-19 in the past 14 days .436 .412 Diagnosed with COVID-19 .154 .407 Quarantined by a Public Health Authority .274 .146 Self-reported Health Status 2.100 .455 Chronic Illness 1.066 .409 Age over 65 .221 .126 Asthma .576 .344 Lung Disease .343 .408 CVD .452 .374 Pregnant .030 .038 HIV .018 .038 Contact Specific (e.g., surface) 2.407 .299 Perceived likelihood of contracting -1.908 -.307 Social Media Hours per day .065 .025 Discrimination -.231 -.137 Too much fuss .936 .113 Causality Transmission via droplets** 1.00 .658 Transmission via contact with contaminated objects 1.107 .649 Airborne Transmission 1.072 .328 Satisfied with Information Available -.039 -.006 Sources of Information -.897 -.110 Controllability Medical Insurance .000 .001 Confidence in doctor to diagnose .000 -.002 Extra hours at home to avoid virus .000 .000 Perceived control over contraction** 1.00 94.531 If diagnosed, perceived control to manage .000 .001 Consequences Heard number of cases 1.613 .895 Heard number of deaths 1.506 .914 Heard number of recovered cases 1.519 .319 Perceived likelihood of surviving** 1.00 .075 Concern for family members contracting .854 .080 Concern for children contracting .770 .045 Timeline Timeline virus will pose a risk** 1.00 .030 If diagnosed, perception of how long virus will last -4.415 -.104 ** regression weight set to 1.00 46 A second CFA was conducted, using only indicator variables with AMOS calculated standardized regression loadings above .300 on each latent variable. These items are presented in Table 16. Notably, no items theorized to represent Timeline were retained in the model. Results of this new CFA are presented in Table 16. In this model, the CFI was calculated to be .814; while improved, it is slightly below the standard .95of acceptability, suggesting a misfit. Table 16. Second CFA of Cognitive Representation Scales Identity Standardized Standardized Regression Regression Weight in Weight in New Model Initial Model Symptom experience in the past .360 14 days Doctor visit in the past 14 days .413 Tested for COVID-19 in the past .412 14 days Diagnosed with COVID-19 .407 Self-reported Health Status .455 Chronic Illness .409 Asthma .344 Lung Disease .408 CVD .374 Perceived likelihood of -.307 contracting Causality Transmission via droplets .658 Transmission via Contact with .649 contaminated Objects Airborne Transmission .328 Controllability Control over Contraction 94.531 Consequences Heard Number of Cases .895 Heard Number of Deaths .914 Heard Number Recovered Cases .319 Due to CFA results indicating a misfit of model based on theory, an exploratory factor analysis (EFA) was used to determine the number of components and items to be retained from this measure. The initial 37 items were entered into a principal components analysis with 47 varimax rotation. Preliminary analysis was set to identify components with an Eigenvalue greater than one. Results of this initial analysis yielded 13 components (Table 17). Table 17. Preliminary PCA of Cognitive Representation Items Components Correlations Component 1 Doctor in the last 14 days .513 Tested for COVID-19 .730 Diagnosed with COVID-19 .578 Quarantined by a public health authority .508 Any Contact or Suspected Contact with Virus .603 Timeline of Risk -.359 Component 2 Symptom experience in the last 14 days .455 Self-Rated Health Status .612 Chronic Illness .715 Asthma .594 Lung Disease .443 Cardiovascular Disease .392 Component 3 Heard of Number of Cases .879 Heard Number of Recovered Cases .514 Heard Number of Deaths .870 Component 4 Perceived Likelihood of Contracting .398 Concern for family members contracting .775 Concerns for children contracting .634 Too much “fuss” has been made -.625 Component 5 Confidence in Precautionary Measures to .628 Prevent Contraction Perceived Control over Contraction -.718 Component 6 Transmission via Droplets .760 Transmission via Contact with Contaminated .755 Objects Airborne Transmission .568 Component 7 If diagnosed, control to manage .714 If diagnosed, perceived time virus will last .742 Component 8 Hospital admission in the last 14 days .599 Pregnant .668 48 Component 9 Satisfied with Available Information .782 Confidence in Doctor to Diagnose COVID-19 .645 Component 10 Perceived Discrimination due to the Virus -.564 Extra hours spent at home to prevent spread .660 Component 11 Age over 65 .722 Source of Information .439 Component 12 HIV .808 Component 13 Medical Insurance .636 Perceived Likelihood of Surviving -.469 A second PCA was employed, with a specified extraction of 5 components, consistent with the core components of Cognitive Representation within the Common-Sense Model. After reviewing the results of this analysis, it was decided that variables with correlations of less than .300 would be excluded; excluded items included those related to age, pregnancy status, HIV status, perceived discrimination, and sources of information. The PCA was conducted again with these items removed to more clearly define the measure. Results of this final analysis are provided in Table 18. Table 18. Cognitive Representation Components and Variable Correlations Component or Variable Correlations Component 1: Identity Component Symptom experience in the last 14 days .388 Doctor in the last 14 days .594 Hospital in the last 14 days .402 Tested for COVID-19 .685 Diagnosed with COVID-19 .563 Quarantined by a public health authority .355 Asthma .329 Lung Disease .511 Cardiovascular Disease .345 Any Contact or Suspected Contact with Virus .539 Component 2: Causes 49 Transmitted via droplets .444 Transmitted via contact with contaminated .484 objects Transmitted via airborne .460 Self-rated Health Status -.422 Chronic Illness -.515 Social media hours per day seeking .500 information If diagnosed, perceived control to manage .538 If diagnosed, perceived time virus will last .481 Component 3: Consequences Heard number of cases .793 Heard number of deaths .778 Heard number of recovered cases .486 Perceived likelihood of surviving .375 Component 4: Control Medical Insurance -.327 Satisfaction with available information .561 Confidence in doctor to diagnose .681 Confidence in precautionary behaviors to .593 prevent Perceived control over contraction -.567 Perceived likelihood contracting -.407 Component 5: Timeline Timeline think COVID presents risk for you .431 Concern for family members contracting -.719 Concerns for children contracting -.534 Too much fuss has been made about risk .640 Scores for each of the five components were calculated. The mean score on the Identity scale was .618 (SD = .982, min = 0, max = 9), with higher scores indicating symptom experience, medical care in the past 14 days, confirmed or suspected contact with the virus, and presence of a high-risk condition such as asthma, lung disease, or CVD. The mean score on the Causes scale was 4.319 (SD = 2.963, min = 0, max = 13), with higher scores indicating less knowledge related to transmission and course of virus, as well as worse self-rated health status and presence of chronic illness. The mean score on the Consequences scale was 3.640 (SD = 1.130, min = 0, max = 7), with higher scores indicating greater awareness of prevalence and 50 outcomes, as well as uncertainty or greater perceived likelihood of surviving. The mean score on the Control scale was 16.417 (SD = 2.918, min = 8, max = 23), with higher scores indicating presence of medical insurance, satisfaction with information available about the virus, greater confidence in the doctor to diagnose COVID, greater control over contraction, and uncertainty or lower perceived likelihood of contracting. The mean score on the Timeline scale was 9.926 (SD = 2.882, min = 1, max = 17), with higher scores indicating increased worry about family members and children contracting the virus before it is managed, belief that the virus will pose risk for greater amounts of time, and belief that there has not been “too much fuss” made about the virus. Emotional Representation. Emotional representation of COVID-19 was assessed via scores on the IES-R and the DASS-21, previously established and validated measures. Engagement in Self-Care Behaviors. Engagement in self-care behaviors was assessed via score on the SCBI-RQ, excluding qualitative data due to lack of ability to quantify frequency of engagement in these behaviors. In order interpret the revised measure, PCA with varimax rotation was employed to assess the validity of the measure, assessing the number of components with Eigenvalue equal to or greater than 1. Results of this analysis indicated five principal components (Table 19); in order to establish reliability of each component, Cronbach’s alpha was employed: maintaining connection (? = .854), maintaining efficiency (? = .759), maintaining mindfulness/spirituality (? = .854), outreach (? = .787), and maintaining physical health (? = .789). In order to assess the utility of a total score from the SCBI-RQ, a second PCA was run, specifying extraction of one component. Results of the second PCA supported the validity of using a total score, as all variable correlations were greater than .448 (Table 19). Cronbach’s alpha results supported the reliability 51 of a total score on this measure (? = .881). The highest possible total score on this measure is 57. In this sample, the mean score on this measure was 30.759 (SD ± 10.03), with the lowest score being 0.00 and the highest score being 57.00. Table 19. SCBI-RQ Factor Structure Initial PCA (Eigenvalue ?1) Correlations Component 1: Maintaining Connection Virtually connect with others you enjoy .760 Maintain deep interpersonal relationships .800 Stay in contact with important people .800 Take time to chat with peers .683 Component 2: Maintaining Efficiency Seek out projects that are exciting or rewarding .542 Allow yourself to laugh .520 Quiet time to complete tasks .721 Seek out comforting activities .696 Be open to not knowing .635 Take breaks from virtual work, class, or similar obligations .475 Component 3: Maintaining Mindfulness/Spirituality Pray .872 Meditate .698 Connect with spirituality .870 Component 4: Maintaining Sense of Community Medical care .716 Contribute to causes .654 Advocate .742 Component 5: Maintaining Physical Health Eat Healthy .792 Exercise .841 Spend time in nature .713 Final PCA Extracting 1 Component for Total Score Correlations Virtually connect with others you enjoy .551 Maintain deep interpersonal relationships .561 Stay in contact with important people .588 Seek out projects that are exciting or rewarding .651 Take time to chat with peers .659 Allow yourself to laugh .569 Quiet time to complete tasks .548 Seek out comforting activities .574 Be open to not knowing .448 Eat healthy .594 Exercise .602 52 Spend time in nature .612 Medical care .536 Take breaks from virtual work, class, or similar obligations .495 Pray .475 Meditate .595 Connect with spirituality .599 Contribute to causes .571 Advocate .552 Engagement in Precautionary Behaviors. Precautionary behavior engagement was assessed using individual items from the NUSCQ-Revised USA, 1-11 from Part E: Precautionary measures in past 14 days. Appraisals of Helpfulness. Appraisals of helpfulness were assessed using individual items including item 12 from the NUSCQ Part E: Precautionary measures in the past 14 days, and item 21 from the SCBI-RQ. Analysis of The Model Predictability of Cognitive Representation and Emotional Representation. Simple linear regression analyses were run to determine if Cognitive Representation scales predicted Emotional Representation (IES-R, DASS-21 Stress, Anxiety, Depression, and Total Scores). Results of these analyses are provided in Table 20. Notably, all Cognitive Representation scales significantly predicted Emotional Representation scales, with the exception on Timeline which only significantly predicted IES-R scores. Table 20. Cognitive Representation and Emotional Representation Regression Equation R p value Identity Scale IES-R 19.120 + 4.971 (IES-R) .264 ? .001** DASS-21 Stress 7.673 + 2.601 (DASS-21 Stress) .263 ? .001** DASS-21 Anxiety 4.036 + 2.689 (DASS-21 Anxiety) .309 ? .001** DASS-21 Depression 6.800 + 2.473 (DASS-21 Depression) .238 ? .001** DASS-21 Total Score 9.255 + 3.882 (DASS-21 Total Score) .288 ? .001** Cause Scale 53 IES-R 13.841 + 1.639 (IES-R) .266 ? .001** DASS-21 Stress 5.719 + .730 (DASS-21 Stress) .226 ? .001** DASS-21 Anxiety 1.631 + .869 (DASS-21 Anxiety) .311 ? .001** DASS-21 Depression 3.968 + .905 (DASS-21 Depression) .267 ? .001** DASS-21 Total 5.659 + 1.253 (DASS-21 Total Score) .286 ? .001** Consequences Scale IES-R 13.927 + 2.271 (IES-R) .139 .001* DASS-21 Stress 5.912 + .925 (DASS-21 Stress) .108 .009* DASS-21 Anxiety 2.351 + .920 (DASS-21 Anxiety) .122 .003* DASS-21 Depression 5.106 + .885 (DASS-21 Depression) .098 .018* DASS-21 Total 6.684 + 1.365 (DASS-21 Total) .117 .005* Control Scale IES-R 47.573 – 1.546 (IES-R) .241 ? .001** DASS-21 Stress 26.890 – 1.065 (DASS-21 Stress) .315 ? .001** DASS-21 Anxiety 19.847 - .857 (DASS-21 Anxiety) .288 ? .001** DASS-21 Depression 25.577 – 1.059 (DASS-21 Depression) .304 ? .001** DASS-21 Total 36.156 – 1.490 (DASS-21 Total) .324 ? .001** Timeline Scale IES-R 16.002 + .624 (IES-R) .097 .019* DASS-21 Stress 7.176 + .212 (DASS-21 Stress) .063 .129 DASS-21 Anxiety 5.377 + .032 (DASS-21 Anxiety) .011 .792 DASS-21 Depression 6.726 + .161 (DASS-21 Depression) .046 .270 DASS-21 Total 9.639 + .203 (DASS-21 Total) .203 .286 Cognitive Representation and Precautionary Behaviors. Simple linear regression analyses were run to determine if Cognitive Representation scales predicted engagement in precautionary behaviors. Results are presented in Table 21. Notably, the Identity scale did not significantly predict frequency of engagement in any precautionary behaviors. The Cause scale predicted frequency of engagement in only two precautionary behaviors, the Consequences and Control scales predicted frequency of engagement in almost all precautionary behaviors, and the Timeline scale predicted frequency of engagement in all precautionary behaviors. Table 21. Cognitive Representation and Precautionary Behaviors. Cognitive Regression Equation R p value Scale Identity Covering mouth when coughing and sneezing = 3.607 + .024 (Identity) .028 .496 Scale Avoid sharing utensils = 3.517 + .008 (Identity) .008 .850 Washing hands with soap and water = 3.666 + .011 (Identity) .014 .737 54 Washing hands after coughing, rubbing nose or sneezing = 3.289 - .022 .021 .615 (Identity) Wearing mask regardless of presence or absence of symptoms = 2.694 + .118 .078 .060 (Identity) Washing hands after touching contaminated objects = 3.537 + .049 (Identity) .056 .177 Cleaning and disinfecting surfaces in your home = 3.175 + .038 (Identity) .036 .384 Using hand sanitizer, with 60% alcohol = 3.037 - .021 (Identity) .016 .703 Social Distancing = 3.580 + .003 (Identity) .004 .925 Staying home, aside from essential purposes = 3.567 + .050 (Identity) .060 .146 Avoid touching eyes, nose, and mouth = 3.063 - .021 (Identity) .020 .628 Cause Covering mouth when coughing and sneezing = 3.832 - .047 (Cause) .170 ?.001** Scale Avoid sharing utensils = 3.748 - .043 (Cause) .137 .003* Washing hands with soap and water = 3.745 - .016 (Cause) .065 .154 Washing hands after coughing, rubbing nose or sneezing = 3.330 - .012 .033 .477 (Cause) Wearing mask regardless of presence or absence of symptoms = 2.619 + .029 .058 .207 (Cause) Washing hands after touching contaminated objects = 3.603 - ,014 (Cause) .047 .305 Cleaning and disinfecting surfaces in your home = 3.176 + .002 (Cause) .006 .897 Using hand sanitizer, with 60% alcohol = 2.938 + .027 (Cause) .061 .180 Social Distancing = 3.649 - .018 (Cause) .064 .166 Staying home, aside from essential purposes = 3.613 - .004 (Cause) .015 .746 Avoid touching eyes, nose, and mouth = 3.059 + .000 (Cause) .001 .979 Consequences Covering mouth when coughing and sneezing = 3.526 + .026 (Consequence) .035 .396 Scale Avoid sharing utensils = 3.724 - .056 (Consequence) .063 .127 Washing hands with soap and water = 3.339 + .092 (Consequence) .136 .001* Washing hands after coughing, rubbing nose or sneezing = 2.880 + .109 .117 .005* (Consequence) Wearing mask regardless of presence or absence of symptoms = 1.872 + .246 .188 ? .001** (Consequence) Washing hands after touching contaminated objects = 3.146 + .116 .153 ? .001** (Consequence) Cleaning and disinfecting surfaces in your home = 2.618 + .159 .175 ? .001 (Consequence) Using hand sanitizer, with 60% alcohol = 2.461 + .155 (Consequence) .135 .001* Social Distancing = 3.278 + .084 (Consequence) .115 .005* Staying home, aside from essential purposes = 3.346 + .069 (Consequence) .095 .021* Avoid touching eyes, nose, and mouth = 2.568 + .132 .144 ? .001** Control Covering mouth when coughing and sneezing = 3.172 + .032 (Control) .124 .005* Scale Avoid sharing utensils = 2.861 + .041 (Control) .123 .005* Washing hands with soap and water = 3.338 + .023 (Control) .099 .023* Washing hands after coughing, rubbing nose or sneezing = 2.533 + .049 .146 .001* (Control) Wearing mask regardless of presence or absence of symptoms = 2.181 + .039 .078 .075 (Control) Washing hands after touching contaminated objects = 3.143 + .029 (Control) .110 .012* Cleaning and disinfecting surfaces in your home = 2.987 + .016 (Control) .048 .275 Using hand sanitizer, with 60% alcohol = 2.283 + .049 (Control) .116 .008* Social Distancing = 2.807 + .049 (Control) .187 ? .001** Staying home, aside from essential purposes = 3.026 + .037 (Control) .147 .001* Avoid touching eyes, nose, and mouth = 2.574 + .033 (Control) .097 .026* Timeline Covering mouth when coughing and sneezing = 3.120 + .051 (Timeline) .173 ? .001** Scale Avoid sharing utensils = 3.013 + .051 (Timeline) .149 ? .001** Washing hands with soap and water = 3.056 + .062 (Timeline) .235 ? .001** Washing hands after coughing, rubbing nose or sneezing = 2.270 + .101 .278 ? .001** (Timeline) 55 Wearing mask regardless of presence or absence of symptoms = 1.349 + .143 .278 ? .001** (Timeline) Washing hands after touching contaminated objects = 2.875 + .070 .234 ? .001** (Timeline) Cleaning and disinfecting surfaces in your home = 2.306 + .090 (Timeline) .252 ? .001** Using hand sanitizer, with 60% alcohol = 2.003 + .103 (Timeline) .230 ? .001** Social Distancing = 2.658 + .093 (Timeline) .326 ? .001** Staying home, aside from essential purposes = 2.799 + .080 (Timeline) .283 ? .001** Avoid touching eyes, nose, and mouth = 1.992 + .107 (Timeline) .296 ? .001** Emotional Representation and Precautionary Behaviors. Initial linear regression analyses were run to determine if Emotional Representation (IES-R, DASS-21 Stress, Anxiety, Depression, and Total Scores) predicted engagement in precautionary behaviors. Results are detailed in Table 22. Table 22. Emotional Representation and Precautionary Behaviors. Emotional Frequency Precautionary Behavior = a + b (x) R p Representation Covering mouth when coughing and sneezing = IES-R 3.744 - .006 (IES-R) .121 .003* DASS-21 Stress 3.742 - .013 (DASS-21 Stress) .149 ? .001** DASS-21Anxiety 3.720 - .017 (DASS-21 Anxiety) .176 ? .001** DASS-21 Depression 3.719 - .012 (DASS-21 Depression) .141 .001* DASS-21 Total 3.745 - .011 (DASS-21 Total) .166 ? .001** Avoid sharing utensils = IES-R 3.660 - .006 (IES-R) .116 .005* DASS-21 Stress 3.629 – .012 (DASS-21 Stress) .113 .006* DASS-21 Anxiety 3.657 - .024 (DASS-21 Anxiety) .203 ? .001** DASS-21 Depression 3.643 - .014 (DASS-21 Depression) .149 ? .001** DASS-21 Total 3.66 - .012 (DASS-21 Total) .164 ? .001** Washing hands with soap and water = IES-R 3.698 - .001 (IES-R) .028 .505 DASS-21 Stress 3.713 - .004 (DASS-21 Stress) .055 .188 DASS-21 Anxiety 3.715 - .007 (DASS-21 Anxiety) .082 .047* DASS-21 Depression 3.714 - .005 (DASS-21 Depression) .065 .115 DASS-21 Total 3.721 - .004 (DASS-21 Total) .072 .084 Washing hands immediately after coughing, rubbing nose or sneezing = IES-R 3.234 + .002 (IES-R) .033 .429 DASS-21 Stress 3.330 - .006 (DASS-21 Stress) .055 .188 DASS-21 Anxiety 3.295 - .003 (DASS-21 Anxiety) .027 .508 DASS-21 Depression 3.350 - .009 (DASS-21 Depression) .086 .038* DASS-21 Total 3.333 - .005 (DASS-21 Total) .062 .134 56 Wearing mask regardless of presence or absence of symptoms = IES-R 2.534 + .011 (IES-R) .131 .001* DASS-21 Stress 2.751 + .002 (DASS-21 Stress) .012 .778 DASS-21 Anxiety 2.710 + .010 (DASS-21 Anxiety) .057 .167 DASS-21 Depression 2.765 + .000 (DASS-21 Depression) .002 .959 DASS-21 Total 2.736 + .003 (DASS-21 Total) .024 .569 Washing hands after touching contaminated objects = IES-R 3.597 - .001 (IES-R) .029 .484 DASS-21 Stress 3.628 - .006 (DASS-21 Stress) .063 .128 DASS-21 Anxiety 3.620 - .008 (DASS-21 Anxiety) .076 .066 DASS-21 Depression 3.638 - .009 (DASS-21 Depression) .102 .014* DASS-21 Total 3.632 - .006 (DASS-21 Total) .087 .036* Cleaning and disinfecting surfaces in your home = IES-R 3.095 + .005 (IES-R) .083 .044* DASS-21 Stress 3.191 + .001 (DASS-21 Stress) .007 .864 DASS-21 Anxiety 3.184 + .003 (DASS-21 Anxiety) .021 .609 DASS-21 Depression 3.242 - .005 (DASS-21 Depression) .052 .210 DASS-21 Total 3.208 - .001 (DASS-21 Total) .011 .799 Using hand sanitizer, with 60% alcohol = IES-R 2.916 + .005 (IES-R) .070 .093 DASS-21 Stress 3.017 + .001 (DASS-21 Stress) .006 .884 DASS-21 Anxiety 2.996 + .005 (DASS-21 Anxiety) .032 .439 DASS-21 Depression 3.082 - .007 (DASS-21 Depression) .055 .185 DASS-21 Total 3.034 - .001 (DASS-21 Total) .009 .836 Social distancing = IES-R 3.672 - .004 (IES-R) .091 .028* DASS-21 Stress 3.657 - .008 (DASS-21 Stress) .095 .021* DASS-21 Anxiety 3.649 - .012 (DASS-21 Anxiety) .122 .003* DASS-21 Depression 3.668 - .010 (DASS-21 Depression) .127 .002* DASS-21 Total 3.672 - .008 (DASS-21 Total) .123 .003* Staying home, aside from essential purposes = IES-R 3.672 - .003 (IES-R) .075 .070 DASS-21 Stress 3.641 - .005 (DASS-21 Stress) .055 .185 DASS-21 Anxiety 3.641 – .008 (DASS-21 Anxiety) .079 .055 DASS-21 Depression 3.646 - .006 (DASS-21 Depression) .072 .082 DASS-21 Total 3.651 - .005 (DASS-21 Total) .074 .076 Avoid touching eyes, nose, and mouth = IES-R 2.979 + .003 (IES-R) .057 .172 DASS-21 Stress 3.077 - .003 (DASS-21 Stress) .028 .503 DASS-21 Anxiety 3.003 + .003 (DASS-21 Anxiety) .024 .567 DASS-21 Depression 3.135 - .010 (DASS-21 Depression) .101 .015* DASS-21 Total 3.807 - .003 (DASS-21 Total) .041 .320 57 Cognitive Representation and Self-Care Behaviors. Initial linear regression analyses were run to determine if Cognitive Representation variables predicted self-care behavior engagement (SCBI-RQ Total Scores). Results are detailed in Table 23. All Cognitive Representation scales significantly predicted self-care behavior engagement except Cause and Timeline scales. Table 23. Cognitive Representation and Self-Care Behavior Cognitive Regression Equation R p value Representations Identity Scale SCBI-RQ = 30.161 + .967 (Identity) .095 .022* Cause Scale SCBI-RQ = 31.307 - .177 (Cause) .051 .263 Consequences Scale SCBI-RQ = 27.652 + .853 (Consequence) .096 .020* Control Scale SCBI-RQ = 18.952 + .753 (Control) .224 ? .001** Timeline Scale SCBI-RQ = 28.360 + .242 (Timeline) .069 .094 Emotional Representation and Self-Care Behaviors. Regression analyses between Emotional Representation measures (IES-R, DASS-21) and self-care behavior engagement (SCBI-RQ) are detailed in Table 24. DASS-21 Stress, DASS-21 Depression, and DASS-21 Total Scores significantly predicted SCBI-RQ total scores. Participants who scored higher on these measures reported decreased self-care behavior engagement. Table 24. Emotional Representation and Self-Care Behavior Engagement. Emotional Representation SCBI-RQ Score = a + b (x) R p IES-R Score 30.251 + .023 (IES-R Score) .042 .309 DASS-21 Stress 31.768 - .099 (DASS-21 Stress) .096 .020* DASS-21 Anxiety 30.765 - .001 (DASS-21 Anxiety) .001 .981 DASS-21 Depression 32.081 - .159 (DASS-21 Depression) .161 ? .001** DASS-21 Total 32.621 - .074 (DASS-21 Total) .098 .018* Precautionary Behavior Engagement and Perceived Helpfulness. Regression analyses between precautionary behavior engagement and perceived helpfulness of engagement in these behaviors are detailed in Table 25. Many of the independent variables were dichotomous or 58 ordinal, so dummy variables were used to create regression equations and t coefficients to determine significance of the regressions. Table 25. Precautionary Behaviors and Helpfulness. Precautionary Mean engagement Increase in mean Coefficient t p Behavior with perceived if perceived helpfulness a + b (x) helpful Covering mouth when 2.009 + .286 (0/1) .286 7.163 ?.001** coughing and sneezing Avoid sharing utensils 2.569 + .125 (0/1) .125 3.709 ?.001** Washing hands after 2.110 + .245 (0/1) .245 5.658 ?.001** touching contaminated objects Washing hands 2.336 + .206 (0/1) .206 6.614 ?.001** immediately after coughing, rubbing nose or sneezing Wearing mask 2.785 + .082 (0/1) .082 3.604 ?.001** regardless of presence or absence of symptoms Washing hands after 2.137 + .245 (0/1) .245 6.395 ?.001** touching contaminated objects Cleaning and 2.438 + .179 (0/1) .179 5.585 ?.001** disinfecting surfaces in your home Using hand sanitizer, 2.583 + .141 (0/1) .141 5.507 ?.001** with 60% alcohol Social Distancing 1.824 + .331 (0/1) .331 8.518 ?.001** Staying home, aside 1.989 + .284 (0/1) .284 7.168 ?.001** from essential purposes Avoid touching eyes, 2.424 + .192 (0/1) .192 6.070 ?.001** nose, and mouth Self-Care Behaviors and Helpfulness. Simple regression analysis was run to assess the predictability of perceived helpfulness of self-care from self-care engagement. Results of this analysis indicated that greater engagement in self-care per the SCBI significantly predicted 59 perceived helpfulness [Perceived helpfulness self-care = 1.573 + .042(0/1), t = 12.775, p ? .001, R2 = .219]. Helpfulness of Precautionary Behaviors and Helpfulness of Self-Care Behaviors. Simple regression analysis was run to assess the predictability between perceived helpfulness of precautionary behaviors and perceived helpfulness of self-care engagement. Results of this analysis indicated that perceived helpfulness of engagement in precautionary behaviors significantly predicted perceived helpfulness of self-care engagement [Perceived helpfulness self-care = 1.696 + .384 (0/1), t = 9.091, p ? 001, R2 = .124]. Multiple Regression Analyses After reviewing initial analyses of the relationships between individual cognitive representation scales, emotional representation scales, and precautionary and self-care behaviors, multiple regression analyses were conducted to more accurately describe the model. Each precautionary behavior was entered into multiple regression analyses, first with just Cognitive Representation Scales, then with Emotional Representation Scales, and finally with the full model including both Cognitive Representation and Emotional Representation Scales. Covering mouth when coughing and sneezing. 8% of variance in frequency of engagement in this precautionary behavior was explained by the cognitive representation model, F(4, 471) = 10.269, p ? .001, R2 = .080, with only Cause and Timeline significantly contributing. 2.8% of variance in frequency of engagement in this precautionary behavior was explained by the emotional representation model, F(2, 583) = 8.227, p ? .001, R2 = .028, with only DASS Total score contributing significantly. Finally, 8% of variance in frequency of engagement in this precautionary behavior was explained by the full model, F(7, 425) = 5.221, p ? .001, R2 = .080, with only Cause, Timeline, and DASS- Total contributing significantly. 60 Avoiding the sharing of utensils. 4% of variance in frequency of engagement in this precautionary behavior was explained by the cognitive representation model, F(5, 425) = 3.484, p = .004, R2 = .040, with only Cause and Timeline contributing significantly. 2.7% of variance was explained by the emotional representation model, F(2, 583) = 8.103, p ? .001, R2 = .027, with only DASS-Total contributing significantly. Finally, 5.4% of variance was explained by the full model, F(7, 425) = 3.441, p = .001, R2 = .054, with only Cause, Timeline, and DASS-Total contributing significantly. Washing hands with soap and water. 6.7% of variance in frequency of engagement in this precautionary behavior was explained by the cognitive representation model, F(5, 425) = 6.603, p ? .001, R2 = .067, with only Consequence and Timeline contributing significantly. The emotional representation model was not significantly associated with washing hands with soap and water. However, interestingly, 7.5% of variance was explained by the full model, F(5, 425) = 4.830, p ? .001, R2 = .075, with only Consequence and Timeline contributing significantly and DASS-Total contributing at p = .087. Washing hands immediately after coughing, rubbing nose, or sneezing. 9.9% of variance in frequency of engagement in this behavior was explained by the cognitive representation model, F(5, 425) = 9.272, p ? .001, R2 = .099, with Consequence, Control, and Timeline contributing significantly. Only 1.8% of variance was explained by the emotional representation model, F(2, 583) = 5.371, p = .005, R2 = .018, with both IES-R and DASS-Total contributing significantly. Finally, 11.2% of variance was explained by the full model, F(7, 425) = 7.503, p ? .001, R2 = .112, with Control, Timeline, DASS-21 Total, and IES-R contributing significantly. Wearing a mask, regardless of presence or absence of symptoms. 10.7% of variance in frequency of engagement in this precautionary behavior was explained by the cognitive 61 representation model, F(5,425) = 10.062, p ? .001, R2 = .107, with Consequence, Control and Timeline Contributing significantly. 3% of variance was explained by the emotional representation model, F(2, 583) = 8.977, p ? .001, R2 = .030, with both IES-R and DASS-21 Total contributing significantly. 12.1% of variance was explained by the full model, F(7, 425) = 8.252, p ? .001, R2 = .121, with Consequence, Control, Timeline, IES-R, and DASS-21 Total contributing significantly. Washing hands after touching contaminated objects. 7.7% of variance in frequency of engagement in this precautionary behavior was explained by the cognitive representation model, F(5, 425) = 6.970, p ? .001, R2 = .077, with Consequence, Control, and Timeline Scales contributing significantly.1.1% of variance was explained by the emotional representation model, F(2, 583) = 3.094, p = .046, R2 = .011, with only DASS-21 Total score contributing significantly. 8.5% of variance was explained by the full model, F(7,425) = 5.581, p ? .001, R2 = .085, with Consequence, Control, and Timeline contributing significantly. Notably, this is an increase in variance from cognitive representation model alone, suggesting some contribution from emotional representation, however neither emotional representation scale contributing significantly (i.e., DASS-21 Total score p = .060). Cleaning and disinfecting surfaces in your home. 9.4% of variance in frequency of engagement in this precautionary behavior was explained by the cognitive model, F(5, 425) = 8.736, p ? .001, R2 = .094, with only Consequence and Timeline contributing significantly. 1.9% of variance was explained by the emotional representation, F(2, 583) = 5.664, p = .004, R2 = .019, with both IES-R and DASS-21 total contributing significantly. 10.8% of variance was explained by the full model, F(7, 425) = 7.216, p ? .001, R2 = .108, with Consequence, Timeline, IES-R, and DASS-21 Total scores contributing significantly. 62 Using hand sanitizer, with 60% alcohol. 10% of variance in frequency of engagement in this precautionary behavior was explained by the cognitive representation model, F(5,425) = 9.364, p ? .001, R2 = .100, with Consequence, Control, and Timeline contributing significantly. 1.3% of variance was explained by the emotional representation model, F(2, 583) = 3.904, p = .021, R2 = .013, with both IES-R and DASS-21 Total. 11.2% of variance was explained by the full model, F(7, 425), p ? .001, R2 = .112, with Control, Timeline, IES-R, and DASS-21 Total. Social distancing, as able. 19.7% of variance in frequency of engagement in this behavior is explained by the Cognitive representation model, F (5, 425) = 20.547, p ? .001, R2 = .197, with Consequence, Control, and Timeline contributing significantly. 1.5% of variance was explained by the emotional representation model, F (2, 583) = 4.412, p = .012, R2 = .015, with only DASS-21 Total contributing significantly. 20.6% of variance was explained by the full model, F(7, 425) = 15.526, p ? .001, R2 = .206, with Consequence, Control, and Timeline contributing significantly. Staying home, aside from essential purposes. 14% of variance in frequency of engagement in this precautionary behavior was explained by the cognitive representation model, F(5, 425) = 13.693, p ? .001, R2 = .140, with Consequence, Control, and Timeline contributing significantly. 0.6% of variance was explained by the emotional representation model, however, the results were not significant. 14.9% of variance was explained by the full model, F(7, 425) = 10.415, p ? .001, R2 = .149, with Consequence, Control, and Timeline contributing significantly. Avoid rubbing eyes, nose, and mouth. 10.6% of variance in frequency of engagement in this precautionary behavior was explained by the cognitive representation model, F(5, 425) = 9.993, p ? .001, R2 = .106, with Consequence, Control, and Timeline contributing significantly. 1.9% of variance was explained by the emotional representation model, F(2, 583) = 5.674, p = 63 .004, R2 = .019, with both IES-R and DASS-21 Total contributing significantly. 12.2% of variance was explained by the full model, F(7, 425) = 8.271, p ? .001, R2 = .122, with Consequence, Timeline, IES-R, and DASS-21 Total contributing significantly. Self-care behavior. Related to self-care behavior engagement, 7.1% of variance was explained by the cognitive representation model, F(5, 425) = 6.443, p ? .001, R2 = .071, with Identity, Consequence, and Control contributing significantly. 4.0% of variance was explained by the emotional representation model, F(2, 583) = 12.055, p ? .001, R2 = .040, with IES-R and DASS-21 Total contributing significantly. 10.1% of variance was explained by the full model, F (7, 425) = 6.729, p ? .001, R2 = .101, with Identity, Consequence, Control, IES-R, and DASS-21 Total contributing significantly. These results suggest that a full model, including both Cognitive and Emotional Representation components, best explains the variance in frequency of precautionary behavior engagement in most instances. Related to self-care behavior engagement, a full model, including both cognitive representation and emotional representation, was also best for explaining the most variance in behavior. V. Conclusions Discussion The current study aimed to describe the early US citizen response to COVID-19, with particular attention to cognitive and emotional perceptions of the virus, and how these perceptions contribute to psychological function and engagement in precautionary and self-care behaviors. Leventhal’s Common-Sense Model of Illness was applied, and preliminary support was found for using this model to describe the US citizen response to COVID-19. This information may be useful to control the current pandemic (i.e., vaccines) and adjustment to life post-pandemic, considering potential challenges including financial loss and stigma toward healthcare providers and Asian American citizens. Overall, this data, collected in the very early stages of the pandemic (April 21-29, 2020), suggested normative cognitive, psychologic, and behavioral adjustment to COVID-19 for the majority of respondents. The majority of this sample was mostly female (52.9%), employed (75.9%), married (49.1%) or single (41.6%), American citizens reported being in good (52.9%) or very good health (27.4%), with no known contact with COVID-19 (91.6%). Interestingly, the majority of respondents reported feeling somewhat confident (52.9%) or very confident (27.6%) in their doctor’s ability to diagnose COVID-19. The majority of respondents indicated that they “always” or “most of the time” engage in all CDC recommended precautionary behaviors, with the exception of mask wearing, which had the lowest rates of adherence. While inconsistencies in mask wearing are concerning and may reflect negative attitudes about masks, it is possible that mask wearing was influenced by inconsistent guidance from the CDC with regards to mask wearing at the onset of the pandemic. Most felt somewhat confident (55.8%) or very confident (25.9%) in precautionary behaviors to prevent the spread of COVID-19 and most reported 65 accurate knowledge of ways the virus can be spread, getting their information from the internet or TV and feeling satisfied overall with the information available to them. Related to psychological function in response to COVID-19 and “stay-at-home” orders, most obtained scores in the normative range on the IES-R and DASS-21 subscales; 75.9% of IES-R scores were in the normative or mild psychological impact range, 64.4% of scores on the DASS-21 Depression range were in the normative range, 72.9% of DASS-21 Anxiety scores were in the normative range, and 75% of DASS-21 Stress scores were in the normative range. However, it is notable that 27.6% of individuals obtained scores in the moderate to severe range on the IES-R, suggesting high psychological impact of COVID-19 for these individuals. Additionally, 27% of participants obtained moderate to severe scores on the DASS-21 Depression scale, 23.3% obtained moderate to severe scores on the DASS-21 Anxiety scale, and 18.7% obtained moderate to severe scores on the DASS-21 Stress scale, suggesting that about 19-30% of individuals in the US may have been experiencing significant psychological distress during the early stages of the pandemic. Fortunately, results on the SCBI-RQ indicated that the majority of participants “occasionally” or “frequently” engage in some sort of self-care behaviors designed to decrease stress and distress. Other commonly reported self-care behaviors identified in the qualitative portion of this study, to be included in future development and assessment of the SCBI-RQ, included going to walks, home-spa days, reading, watching TV/streaming shows/movies, and spending time outdoors. Overall, these results are consistent with more recent research on COVID-19 psychological and behavioral responses (Prati and Macini, 2021; Xiong et al., 2020). While most research to date on the psychological response to COVID-19 suggests psychological resiliency, there have been small but significant increases in anxiety and depression with COVID-19 66 outbreak and quarantine measures (Prati and Macini, 2021). Normative DASS-21 data for a nonclinical U.S. sample, in a pre-COVID-19 context, indicated average scores of 5.70, 3.99, 8.12, and 17.80 on the DASS-21 Depression, Anxiety, Stress, and Total scales, respectively (Sinclair, Siefert, Slavin-Mulford, Stein, Renna, & Blais, 2011). Normative DASS-21 data for an outpatient clinical U.S. sample, in a pre-COVID context, indicated average pre-treatment scores of 13.32, 9.09, and 15.01 on the DASS-21 Depression, Anxiety, and Stress scales, respectively. In the current study assessing psychological function within the context of early COVID-19 and quarantine, average scores were 8.3, 5.7, and 9.8 on the DASS-21 Depression, Anxiety, and Stress scales respectively, consistent with existing research suggesting slightly elevated psychological distress (Prati and Macini, 2021; Xiong et al., 2020). While Wang and colleagues (2020) only reported an average total score on the DASS-21 (m = 20.16), this is similar but also slightly higher than normative pre-COVID U.S. data. Interestingly, considering categorical scores on these measures, this study suggests higher levels of depression and stress in the U.S. sample compared to the Chinese sample, but higher levels of anxiety in the Chinese sample compared to the U.S. sample. Frequencies of scores in the moderate to severe or extremely severe range were 16.5% (Wang et., 2020) versus 27.0% (current study) on the DASS-21 Depression Scale, 28.9% (Wang et al., 2020) versus 23.3% (current study) on the DASS-21 Anxiety Scale, and 13.9% (Wang et al., 2020) versus 18.7% (current study) on the DASS-21 Stress Scale. While researchers are still working to describe differences in psychological response between groups, it is hypothesized that differences may be observed overtime between social groups, due to disparities in healthcare access and health outcomes (Prati and Macini, 2021; Xiong et al., 2020). One recent systematic review of the literature on responses to COVID-19 67 suggested relatively high levels of anxiety, depression, and psychological impact, with contributing factors including female gender, younger age, presence of chronic illness, and increased frequency of exposure to news and social media (Xiong et al., 2020). Other groups that have been identified as high risk for psychological distress and burnout are healthcare workers, with number of work hours, perceptions of support, and fear of infection predicting significantly predicting burnout (Giusti et al., 2020). Specific demographics of healthcare workers at higher risk for psychological distress and depersonalization were also identified and included female gender, being in contact with COVID-19 patients, working in the hospital, and being a nurse (Giusti et al., 2020). Another review paper discussing psychological impacts for the general public identified perceptions of inaccurate information from public health authorities as a risk factor for psychological distress, while also identifying a sense of community and social support as protective factors promoting psychological resilience (Serafini, Parmigiani, Amerio, Aguglia, & Amore, 2020). Our study adds to the current literature by further describing factors that may contribute to psychological distress or well-being in response to COVID-19 and quarantine measures. We also gained some information about perceptions of risk, perceptions of control with regards to contraction and management if contracted, confidence in medical providers, concern for loved ones, and beliefs about timeline of risk. Common-Sense Model. Preliminary support for applying Leventhal’s Common-Sense Model of Illness was obtained. When considered independently, all Cognitive Representation scales significantly predicted scores on all emotional representation scales, with the exception of the Timeline scale that only predicted traumatic stress. Specifically, persons who had higher scores on the Identity, Cause, and Consequences scales had higher scores on measures of trauma response, stress, anxiety, depression, and overall distress. This suggests individuals who 68 experienced physical symptoms characteristic of COVID-19, perceived themselves to be at higher risk, and were more attentive to information on prevalence and outcomes, had greater psychological distress. Interestingly, scores on the Control scale predicted lower scores on all emotional representation measures, suggesting that presence of medical insurance, satisfaction with available information, confidence in doctors, and greater perceived control over contraction were less distressed. Higher scores on the Timeline scale were predicted by greater scores on the IES-R scale, suggesting that people who believed the virus would persist for longer amounts of time and had greater worry about family and children, also had greater trauma responses. Again, at the time of the survey, the timeline of the pandemic was completely unknown and vaccines were not available. Analysis of the role of Cognitive Representation in predicting precautionary behavior engagement yielded some interesting results as well. Notably, people with higher scores on the Cause, Consequences, and Timeline scales had greater frequency of engagement in all or most precautionary behaviors when cognitive representation scales were considered independently. Interestingly, when considered independently, only the Consequences scale and Timeline Scale predicted mask wearing, suggesting that people with more knowledge of outcomes and prevalence, higher perceived timeline of risk, and more concern for family members were more likely to wear their masks regularly. Analysis of the role of Emotional Representation scales independently in predicting precautionary behavior engagement indicated that higher scores on all emotional distress measures predicted less frequent engagement in three behaviors – covering mouth when coughing and sneezing, avoidance of sharing utensils, and social distancing. While emotional representation did not seem to play a large role in predicting precautionary behavior engagement, 69 the trend was that people with higher emotional distress reported less frequent engagement in most precautionary behaviors. Analysis of the role of Cognitive Representation and Emotional Representation scales independently in predicting self-care behavior engagement suggested that higher Identity scores, Consequence scores, and Control scores predicted greater engagement in self-care; higher scores on stress, depression, and overall psychological distress scales predicted less frequent engagement in self-care behaviors. This likely suggests that individuals with greater knowledge of the virus, their own risk, and perceived control, were those that had less distress and therefore, engaged in more self-care. After considering scales independently, multiple regression analyses were conducted to evaluate the Common-Sense Model of COVID-19 as it applies to precautionary and self-care behavior engagement. Related to frequency of engagement in precautionary behaviors, the cognitive representation model was significant in explaining variance across all behaviors, with Control, Consequence, and Timeline most frequently providing significant contributions to the model. The emotional representation (IES-R and DASS-21 Total) model was also independently significant in explaining some, though less, variance in frequency of precautionary behavior engagement, for all but two precautionary behaviors. When entered into the full model, including both Cognitive and Emotional Representation components, variance explained increased for all but two precautionary behaviors. Interestingly, the DASS-21 was the Emotional Representation component that most frequently contributed significantly to the model. While IES-R contributed to some as well, it did not contribute to variance when DASS-21 Total did not also contribute. This suggests that a full model, including both Cognitive and Emotional Representation components, best explains the variance in frequency of precautionary behavior engagement. 70 However, most variance can be explained considering only Cognitive Representation Scales. Perceptions of control, knowledge of COVID-19 outcomes, perceived timeline of risk, and concern for others, are aspects of cognitive representation that seem particularly important when considering precautionary behavior engagement. General psychologic distress in the past two weeks is also an important aspect to consider. Interestingly, related to self-care behavior engagement, a full model, including both cognitive representation and emotional representation, was also best for explaining the most variance in behavior. However, Identity also contributed significantly, in addition to Consequences, Control, IES-R, and DASS-21 Total scores. Analysis of perceived helpfulness of precautionary and self-care behavior engagement indicated that people who reported frequent engagement in precautionary behaviors perceived them to be helpful and people who reported frequent engagement in self-care behaviors perceived them to be helpful. Interestingly, perceived helpfulness of precautionary behaviors also predicted perceived helpfulness of self-care behaviors, suggesting that those who perceived precautionary behaviors to be helpful also perceived self-care behaviors to be helpful. Clinical and Policy Implications Clinical implications of these results suggest that psychologists working with distressed patients should consider pre-existing patient knowledge and perceptions of COVID-19, as well as engagement in self-care behaviors and perceptions of helpfulness in order to promote positive psychologic adjustment and engagement in precautionary behaviors to prevent the spread of COVID-19. These results may be additionally useful in helping patients navigating the decision to pursue vaccination. A recent study of 7,429 participants indicated that vaccine hesitancy is directly correlated with trust in the vaccine development and government approval processes 71 (Daly, Jones, and Robinson, 2021); while hesitancy has decreased over the past year, rates of hesitancy are still high, particularly among high-risk groups including Black and low SES groups, suggesting a need for more public outreach and education to increase trust. Policy makers might consider using the Common-Sense Model to drive education, planning, and reporting when delivering information to the public, considering that while “Timeline” may be uncertain, perceived control predicts a more adaptive response. For example, messaging focused on providing accurate, specific, and easily interpretable education on the virus, as well as messaging focused increasing perceptions of control related to the virus, may encourage a more adaptive emotional and behavioral response to COVID-19. Special attention may also be paid to ensuring that this type of messaging reaches communities that are typically considered to have low trust in the healthcare system. More tailored communication can ensure that they are receiving clear and accurate information with regard to the virus, methods to control the virus, and resources to aid in establishing a sense of control (e.g., where to obtain low cost or free masks if one is not yet vaccinated). Strengths The major strength of this study is that it is the first national study, to our knowledge, to consider the psychological and behavioral adjustment to COVID-19 in the United States, providing information on adjustment in the acute stages of the pandemic when “stay at home” orders and other restrictions were novel and vast. This study not only considered the impacts of knowledge and beliefs on behavior in terms of engagement in precautionary behaviors, but also considered self-care behavior, supporting a more comprehensive understanding of psychological adjustment to COVID-19 using the Common-Sense Model of Illness. It is believed that this 72 information will be important to consider as we continue to adjust to the ever-changing environment within the context of this pandemic. Limitations While this study has its strengths, it is not without limitations. The first is that the data sourcing software did not provide geographic information of respondents, as originally projected. This limited our ability to consider location as a factor in predicting psychological and behavioral adjustment. For example, living closer to New York and other “hot spots” may have predicted increased psychological distress, further influencing behavior. The second is the frequency of “invalid” responders, reducing our sample size by approximately 50% of what we originally expected. While this was unfortunate, we still had more than needed for statistical power. Third, our sample largely consisted of people with who were employed at the time of the survey, potentially limiting the generalizability of our data, considering high rates of job loss during COVID-19 and quarantine. Other limitations include that our study was only a one-time assessment of psychological and behavioral response to COVID-19, limiting us to a “snap-shot” at one early time point during the pandemic; another limitation is a lack of comprehensive medical history on each participant to more accurately assess a person’s actual risk versus their perceptions of risk. Lastly, due to the nature of the questions and differences in response items (e.g., Likert and yes/no), test-retest data is needed to establish the reliability of the Cognition Representation Measure described in this study. However, analyses in this study used single-item responses to establish preliminary support for the model. Future Directions 73 Future directions include retesting the model on specific samples to better develop the model, such as heart and lung disease patients who experience greater risk from COVID-19 infection. This may be helpful in predicting likelihood of getting the vaccine, continuing to adhere to mask mandates and other restrictions, and adjustment to future pandemics or other quarantine situations. Another future step will be to create the SBCI-RQ measure, incorporating items from the qualitative analysis, in order to readminister the measure, establishing its validity and reliability to be used in future pandemic or other quarantine contexts. Our results may help to develop “pandemic profiles” of people or information to be included in public health communications. Conclusions Results of this study indicated that during the early stages of the pandemic, US citizens felt knowledgeable about COVID-19 and confident in precautionary behaviors to control the spread of COVID-19. While most US citizens reported normative levels of emotional distress in response to COVID-19, about 19-30% had scores that indicated moderate to severe levels of psychological impact, depression, anxiety, or stress. Psychological distress is important to consider, as greater distress did predict decreased engagement in self-care behaviors and certain precautionary behaviors. People who engaged in both precautionary and self-care behaviors felt that they were helpful. This study built on the work of Wang and colleagues (2020), applying a model to the data to encourage a more comprehensive understanding of the psychological and behavioral response to COVID-19. While the results of this study are preliminary and further study is needed, these results suggest that Leventhal’s Common-Sense Model of Illness may be applicable to understanding the US citizen experience of COVID-19. 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M., Gill, H., Phan, L., Chen-Li, D., Iacobucci, M., Ho, R., Majeed, A., & McIntyre, R. S. (2020). Impact of COVID-19 pandemic on mental health in the general population: A systematic review. Journal of Affective Disorders, 277, 55-64. doi: 10.1016/j.jad.2020.08.001 Appendix 1. National University of Singapore Questionnaire on COVID-19 – Revised USA Thank you very much for your willingness to participate in a study on the effects of COVID-19. The entire survey will take about 20 minutes to complete. No personally identifiable information will be collected. Part A: Demographics 1. Gender: ? Male ? Female ? Other: 2. Age: ___________ 3. Education attainment ? None/kindergarten ? Primary school (Grades 1 – 6) ? Lower secondary school (Grades 7 – 9) ? Upper secondary school (Grades 10 – 12) ? College ? University: Bachelor ? University: Master or PhD 4. Residential country during the COVID-19 outbreak ? Cambodia ? China ? Philippines ? Malaysia ? Vietnam ? United States ? Other, please specify 5. Marital status ? Single ? Married ? Divorced/separated ? Widowed 6. Employment status ? Student, ? Employed ? Unemployed ? Housewife ? Farmers ? Retired 7. Parental status? ? Not applicable ? No children 80 ? Pregnant ? Has child 16 years or under ? Has child older than 16 years 8. Household size: ? 1 person ? 2 persons ? 3-5 persons ? 6 persons or more 9. Have you traveled outside of your residential country in the past 14 days? ? No ? Yes, please specify visited countries Part B: Symptoms and physical health status 1. Symptoms of body discomfort in the past 14 days (please check all that apply) ? Persistent fever (>38°C for at least 1 day) ? Chills ? Headaches ? Myalgia ? Cough ? Difficulty breathing ? Dizziness ? Coryza ? Sore throat ? Persistent fever and cough or difficulty breathing ? Nausea, vomiting, diarrhoea 2. Did you see a doctor in the clinic in the past 14 days? ? No ? Yes 3. Were you admitted to the hospital in the past 14 days? ? No ? Yes 4. Were you tested for COVID-19 / 2019-novel coronavirus in the past 14 days? ? No ? Yes 5. In the past 14 days, did you request a test or want a test but were unable to receive a test for COVID-19? ? No ? Yes 6. Were you diagnosed with COVID-19? ? No ? Yes 7. Were you under quarantine by health authority in the past 14 days? ? No ? Yes 8. Please self-rate your current health status 81 ? Very good ? Good ? Fair ? Poor ? Very poor 9. Do you have medical insurance? ? Yes ? No 10. Do you suffer from a chronic illness? ? Yes ? No 11. Are you 65 years or older? ? Yes ? No 12. Do you have moderate to severe asthma? ?Yes ?No 13. Do you have chronic lung disease, aside from asthma? ? Yes ? No 14. Do you have cardiovascular disease? ? Yes ? No 15. Are you currently pregnant? ? Yes ? No 16. Do you have HIV? ? Yes ? No 17. What is your estimated height? 18. What is your estimated weight? 19. Have you avoided seeking acute or emergency healthcare when you felt you needed it for fear of COVID-19? ? Yes ? No 20. Have you avoided attendance of regularly scheduled healthcare appointments (e.g. for pre-existing healthcare conditions) for fear of COVID-19? ?Yes ? No 21. Do you like to go surfing while eating scones? ? Never 82 ? Rarely ? Sometimes ? Frequently ? Never Part C: Contact history 1. Have you directly or indirectly contacted patients suffering from COVID-19? ? No (skip to Part D) ? Yes 2. Extent of direct and indirect contact history of COVID-19 patients (please check all that apply) ? Close contact with a confirmed case ? Indirect contact with a confirmed case (‘‘contact of direct contact’’) ? Contact with a suspected case ? Contact with infected materials Part D: Knowledge and belief about COVID-19 1. Does the COVID-19 transmit through… Agree Disagree Don’t know a. Droplets ? ? ? b. Contact via contaminated objects ? ? ? c. Airborne ? ? ? 2. How satisfy you are with the amount of health information available about COVID-19? ? Very satisfied ? Satisfied ? Dissatisfied ? Very dissatisfied ? Don’t know 3. Have you heard of the following… Heard Not heard a. Number of cases infected by COVID-19 ? ? b. Number of deaths infected by COVID-19 ? ? c. Number of recovered cases infected by COVID-19 ? ? 4. How do you mainly obtain health information? ? Social media (go to 4a) ? Internet ? Television ? Radio ? Newspaper ? Family members 83 ? Other, please specify 4a. How many hours per day do you spend on social media to obtain information about the 2019 coronavirus outbreak? ? 0-5 ? 5-10 ? 10-15 ? 15-20 ? 20+ 5. How confident are you in your own doctor’s ability to diagnose or recognize COVID-19? ? Very confident ? Somewhat confident ? Not very confident ? Not at all confident ? Don’t know Very Somewh- Not very Not likely Don’t 6. Please rate your likelihood of … likely at likely likely at all know a. Contracting COVID-19 ? ? ? ? ? during the current outbreak b. Surviving COVID-19 if ? ? ? ? ? infected 7. Please rate your concerns about other family members getting COVID-19. ? Don’t have family member ? Very worried ? Somewhat worried ? Not very worried ? Not worried at all 7. Please rate your concerns about child younger than 16 years getting COVID-19. ? Don’t have child ? Very worried ? Somewhat worried ? Not very worried ? Not worried at all 8. Do you feel that you are being discriminated by other countries due to the outbreak of COVID-19? ? Yes ? No Part E: Pre-cautionary measures in past 14 days 84 Do you do the following in the most of the past 14 days… Always time sometime occasional Never 1.Covering mouth when coughing and sneezing ? ? ? ? ? 2.Avoid sharing utensils ? ? ? ? ? 3. Washing hands with soap and water ? ? ? ? ? 4. Washing hands immediately after coughing, rubbing nose or ? ? ? ? ? sneezing 5. Wearing mask regardless the presence or absence of ? ? ? ? ? symptoms 6. Washing hands after touching contaminated objects ? ? ? ? ? 7. Cleaning and disinfecting surfaces in your home ? Always ? Most of the time ? Sometimes ? Occasional ? Never 8. Using hand sanitizer, with 60% alcohol ? Always ? Most of the time ? Sometimes ? Occasional ? Never 9. Social Distancing, as able (i.e. maintaining 6-foot distance from others) ? Always ? Most of the time ? Sometimes ? Occasional ? Never 85 10. Staying home, aside from essential purposes (i.e. grocery store, pharmacy, medical appointments, caregiving) ? Always ? Most of the time ? Sometimes ? Occasional ? Never 11. Avoid touching eyes, nose, and mouth ? Always ? Most of the time ? Sometimes ? Occasional ? Never 12. How confident do you feel the precautionary measures you are taking will help prevent you from contracting or spreading COVID -19? ? Not confident at all ? Not very confident ? Neutral ? Somewhat confident ? Very confident 13. Do you feel that too much fuss has been made about COVID-19? ? Always ? Most of the time ? Sometime ? Occasional ? Never 14. How many extra hours per day do you stay at home to avoid COVID-19? ? 0-5 ? 5-10 ? 10-15 ? 15-20 2? 0+ ? I don’t leave home. 86 22. How much control do you feel you have over contraction of COVID-19? ? I have already been diagnosed ? No control at all ? Very little control ? Neutral ? Some control ? A lot of control ? Total control 23. If you have been diagnosed, how much control do you feel you have in managing COVID-19? ? No control at all ? Very little control ? Neutral ? Some control ? A lot of control ? Total control 24. How long do you feel COVID-19 will pose a risk to you? ? Days ? Weeks ? Months ?1-3 years ? 3+ years ? Forever 18 If you have been diagnosed with COVID-19, how long do you think the virus will last? ? Days ? Weeks ? Months 1? -3 years ? 3+ years ? Forever 19. How often do you travel to Neptune for lunch? ? Never ? Rarely ? Sometimes ? Frequently ? Always Part F Additional information about COVID-19 1. Would you like to receive additional information about COVID-19? ? Yes ? No 87 2. I would like to receive additional information about Yes No COVID-19 on … a. Details on symptoms ? ? b. Advice on prevention ? ? c. Advice on treatment ? ? d. Regular updates for latest information ? ? e. Regular updates for the Outbreaks ? ? f. Advice for people who might need more tailored ? ? information, such as those with pre-existing illness g. Availability and effectiveness of medicine/vaccine ? ? h. How many people are affected/where it is affected ? ? i. Travel advice ? ? j. How COVID-19 is spread ? ? k. What other countries are doing ? ? 3. Please specify other information you would like to receive about COVID-19 Appendix 2. Self-Care Behavior Inventory – Revised for Quarantine Over the past month, how often have you engaged in the following self-care behaviors: 0- Never 1- Rarely 2- Occasionally 3- Frequently 1. Virtually connect with others you enjoy 2. Maintain deep interpersonal relationships 3. Stay in contact with important people 4. Seek out projects that are exciting or rewarding 5. Take time to chat with peers 6. Allow yourself to laugh 7. Quiet time to complete tasks 8. Seek out comforting activities 9. Be open to not knowing 10. Eat healthy 11. Exercise 12. Spend time in nature 13. Medical care 14. Take breaks from virtual work, class, or similar obligations 15. Pray 16. Meditate 17. Connect with spirituality 18. Contribute to causes 19. Advocate Other activities you have been doing to take care of yourself: How helpful do you feel engaging in self-care behaviors has been for reducing emotional stress in response to COVID-19 and quarantine? ?Not helpful at all ? Not very helpful ? Neutral ? Somewhat helpful ? Very helpful How often do you visit Mars? ? Never ? Somewhat often ? Often ?Frequently ?Very often 89 Appendix 3. 90