SOMATIC SYMPTOM DISORDER AND PERCEIVED SUSCEPTIBILITY TO ILLNESS

Anikó Viktória Varga

A Thesis

Submitted to the Graduate College of Bowling Green State University in partial fulfillment of the requirements for the degree of

MASTER OF ARTS

December 2019

Committee:

William H. O'Brien, Advisor

Abby L. Braden

Dara R. Musher-Eizenman ii

ABSTRACT

William H. O’Brien, Advisor

Somatic Symptom Disorder (SSD) is characterized by persistent somatic symptoms and associated cognitive, affective, and behavioral factors. Perceived susceptibility to illness may contribute to the maintenance of SSD and treatment seeking intent and behavior. There are limited studies examining perceived susceptibility to illness and treatment seeking intent in people with SSD features. The primary aim of the current study was to determine whether individuals with SSD features differ from individuals without SSD features with respect to perceived susceptibility to illness and treatment seeking intent when faced with health-related information. After completing pre-video measures, participants were randomly assigned to watch either a chronic inflammation video or a nature video. Subsequently, participants’ mood, perceived susceptibility to illness, and treatment-seeking intent was assessed using self-report measures. One hundred and thirty (N = 130) participants out of three hundred and fifty-eight (N

= 358) were identified as meeting criteria for SSD. Results indicated that participants with SSD features reported greater perceived susceptibility to illness and treatment seeking intent.

Additionally, the chronic inflammation video was associated with higher perceived susceptibility to illness. However, there was no interaction between video condition and SSD features on perceived susceptibility to illness and treatment seeking intent. The current study provides novel evidence that people with SSD features experience greater perceived susceptibility to illness than people without SSD features, regardless of the type of information (health-related vs non-health related) they are exposed to. iii

Keywords: Somatic Symptom Disorder, perceived susceptibility to illness, treatment seeking intent, health-related information iv

TABLE OF CONTENTS

Page

INTRODUCTION ...... 1

Somatic symptom disorder ...... 2

Epidemiology…………………………… ...... 3

Perceived susceptibility to illness and somatic symptom disorder ...... 5

Summary and hypotheses ...... 8

METHOD……………...... 10

Participants…...... 10

Health-related video ...... 10

Non-health-related video ...... 11

Measures……...... 11

Demographic variables and medical history ...... 11

Patient health questionnaire-15 (PHQ-15) ...... 12

Somatic symptom disorder - B criteria scale (SSD-12) ...... 13

Treatment seeking frequency...... 14

Mood……...... 14

Perceived susceptibility to illness and treatment seeking intent ...... 15

Procedure……...... 16

RESULTS……………...... 18

Comparisons on pre-video measures of the two video conditions……………… .... 18

Comparisons on pre-video measures of participants with and without SSD features 18 v

Manipulation check: Effect of video exposure on perceived susceptibility, treatment

seeking intent, and mood ...... 19

Effects of video condition and SSD features on perceived susceptibility to illness and

treatment seeking intent ...... 20

Effects of video condition and SSD features on mood ...... 22

Relationship between post-video mood, perceived susceptibility to illness, and treatment

seeking intent...... 24

Relationship between perceived susceptibility to illness, treatment seeking intent, and

treatment seeking frequency ...... 24

Correlations between perceived susceptibility, treatment seeking intent, and chronic

inflammation video factors……………...... 25

Summary of results…...... 26

DISCUSSION ...... 27

Limitations...... 32

Future directions and concluding comments ...... 34

REFERENCES ...... 36

APPENDIX A. DEMOGRAPHICS SURVEY ...... 46

APPENDIX B. PATIENT HEALTH QUESTIONNAIRE - 15 (PHQ-15) ...... 56

APPENDIX C. SOMATIC SYMPTOM DISORDER - B CRITERIA SCALE (SSD-12) .. 58

APPENDIX D. TREATMENT SEEKING FREQUENCY ...... 60

APPENDIX E. MOOD SCALE ...... 63

APPENDIX F. ABSOLUTE RISK RATING FORM (ARRF) ...... 64

APPENDIX G. TREATMENT SEEKING INTENT RATING FORM ...... 66 vi

APPENDIX H. HSRB APPROVAL ...... 68

APPENDIX I. TABLES ...... 69

APPENDIX I. FIGURES ...... 93 Running head: SSD AND PERCEIVED SUSCEPTIBILITY TO ILLNESS 1

INTRODUCTION

Somatic symptoms with ambiguous aetiology have been intriguing scholars throughout history. Accordingly, ancient Egyptians, Greeks, and Romans associated somatic symptoms to a dislocated uterus. The 17th-century physician, Thomas Sydenham generalized somatic symptoms to all genders by denoting the psychological origins of such afflictions. Scholars of the 19th century, including Pierre Briquet, Jean-Martin Charcot, and Pierre Janet, maintained the psychological explanation of somatic symptoms, while also introducing new terms such as

“” and “dissociation” to the field (Smith, 1991; Kleinstauber & Rief, 2017;

Heinrich, 2004). Probably the most salient figure in the field of distressing somatic symptoms was Sigmund Freud, who approached the disorder by the exploration of defense mechanisms and the unconscious (Freud, 1964).

The term “”, discussed by Zbigniew Lipowski (1988), was officially introduced in the Diagnostic and Statistical Manual of Mental Disorders-III (DSM-III) within the category of Somatoform Disorders. The category was kept in the subsequent DSM-IV as well.

The current term used to refer to complaints defined by distressing somatic symptoms and associated psychological features is Somatic Symptom Disorder (The American Psychiatric

Association, 1980; 2000; 2013).

When reviewing the literature on somatic symptoms, it becomes apparent that experts have used different terms to describe Somatic Symptom Disorder, including , somatization, medically unexplained symptoms, functional somatic syndromes (, , chronic syndrome, etc.), bodily distress syndrome, etc. The lack of consistency in terminology brings about difficulties with generalizability of findings. SSD AND PERCEIVED SUSCEPTIBILITY TO ILLNESS 2

Additionally, it poses obstacles to the development of a coherent model that addresses the underlying mechanisms of Somatic Symptoms Disorder.

Given that Somatic Symptom Disorder (SSD) is a recent terminology and thus there is limited research in this field, the current paper relies on studies that use former terms (e.g. medically unexplained symptoms, , bodily distress syndrome, etc.).

Nonetheless, in order to preserve uniformity, the term SSD will be used throughout the paper.

Additionally, as explained below, the diagnostic category of SSD has shifted its focus from negative to positive criteria, thus eradicating one of the primary issues with the previous categories: the need to confirm that the symptoms are unexplained from a biomedical perspective. Researchers suggest that measures that are based on positive criteria may be more reliable (Laferton et al., 2017), especially if they are paired with medical morbidity measures

(Barsky, 2016). This further motivates the decision to utilize the term SSD in the present study.

Somatic symptom disorder

SSD is included in the DSM-5 category of Somatic Symptoms and Related Disorders.

The DSM-5 criteria include the following: A) one or more somatic symptoms that cause distress and/or impact a person’s daily functioning; B) disproportionate cognitions, affect, and behaviors associated with the somatic symptoms as evidenced by at least one of the following: 1) excessive and perpetual thoughts concerning the gravity of the symptoms; 2) disproportionate and chronic anxiety regarding health or symptoms; 3) exaggerated time and energy dedicated to health preoccupations or somatic symptoms; C) persistent symptoms – although the specific somatic symptoms may alter – for typically more than 6 months (American Psychiatric Association,

2013). The psychological characteristics of SSD can be affect related (illness worry and fear) and behavioral (e.g. frequent treatment and reassurance seeking, body scanning, medication use, SSD AND PERCEIVED SUSCEPTIBILITY TO ILLNESS 3 avoidance, and social withdrawal, etc.). Cognitive features include catastrophic thoughts about symptoms - even in the presence of contrary medical evidence - and possible future illnesses, low perceived health, attentional biases, and dysfunctional beliefs regarding health (American

Psychiatric Association, 2013).

SSD can be conceptualized as lying on a continuum in terms of the number of symptoms, intensity of discomfort, and persistence (Smith & Dwamena 2007). More specifically, people with SSD can present with a single symptom, multiple ones, as well as specific syndromes, such as fibromyalgia, irritable bowel syndrome, and chronic fatigue syndrome (Steinbrecher & Hiller,

2011; van Dessel, Leone, van der Wouden, Dekker, & van der Horst, 2014). Regarding specific symptoms, people can report a variety of them including dizziness fatigue, pain, gastrointestinal discomfort, and cardiovascular discomfort, etc. (American Psychiatric Association, 2013).

Importantly, SSD is no longer defined by medically unexplained symptoms, a characteristic that had low inter-rater reliability as a diagnostic criterion (Rief & Rojas, 2007), reinforced mind-body dualism, and had pejorative connotation among patients (American

Psychiatric Association, 2013). Instead, SSD is delineated by positive criteria such as the presence of distressing somatic symptoms, along with disproportionate thoughts, feelings, and behaviors related to these somatic symptoms. It is argued that the singular characteristic of SSD is not the somatic symptoms as such, but rather the manner in which they are interpreted and the preoccupation with health (American Psychiatric Association, 2013).

Epidemiology

While currently there is limited prevalence data on SSD specifically, it is likely that prevalence information on previous labels of this symptom cluster are applicable (Allen &

Woolfolk, 2013). Based on preceding categories, the DSM-5 estimates the prevalence of SSD in SSD AND PERCEIVED SUSCEPTIBILITY TO ILLNESS 4 the general adult population to be between 5%-7% (American Psychiatric Association, 2013).

SSD prevalence seems to be somewhat higher in the general adolescent population, namely about 10.5% (van Geelen, Rydelius, & Hagquist, 2015). Although about one third of primary care patients are found to be seeking treatment for somatic symptoms with ambiguous etiology

(Rosendal, Carlsen, Rask, & Moth, 2015), only 8% -17% develop persistent symptoms (Jackson and Kroenke, 2008; Budtz-Lilly, Vestergaard, Fink, Carlsen, & Rosendal, 2015; Toft et al.,

2005).

SSD has been found to predict high treatment-seeking behavior (McAndrew, 2017;

Barsky, Orav, & Bates, 2005) and consequently it has been associated with increased health care costs. In an evaluation of 294 German primary care patients with SSD (conceptualized as medically unexplained symptoms), Konnopka et al. (2013) found the direct costs of SSD to be around $1,200 (€ 1098) while indirect costs $8,500 (€ 7,645) over a 6-month period for one individual. Direct costs were mainly due to medical consultations. Indirect costs originated primarily from work productivity reduction and early retirement. Similarly, Zonneveld,

Sprangers, Kooiman, van’t Spijker, & Busschbach (2013) estimated the costs of health care utilization in individuals with SSD (defined as medically unexplained symptoms) over a one- year period. Researchers found health care utilization to be about $3500 (€ 3,123), while indirect costs (including absenteeism, productivity reduction) were significantly higher ($7,700; € 6,815) for one person. Furthermore, Barsky et al. (2005) examined the costs associated with SSD

(defined as somatization) over a 12-month period in two United States-based primary care practices and found that health care costs associated with SSD patients (inpatient: $3,146; outpatient: $3,208) were approximately twice as much as those without SSD (inpatient: $991; outpatient: $1,771). The authors estimated the overall health care costs associated with SSD to be SSD AND PERCEIVED SUSCEPTIBILITY TO ILLNESS 5 approx. $256 billion/year, which is much higher than the costs associated with other chronic illnesses such as diabetes ($101.4 billion) and hypertension ($ 83.9 billion), or other mental disorders such as ($71.1 billion) or anxiety ($29.7 billion) (Barsky et al., 2005;

Dieleman et al., 2016). Nonetheless, more studies are needed for a more reliable estimate of the financial costs of SSD in the United States.

SSD may affect all areas of the individual’s life. Due to fixation on one’s bodily sensations and their possible consequences, individuals with SSD tend to withdraw from social and professional activities and have an overall low perceived physical quality of life (Allen &

Woolfolk, 2013; Hinz et al, 2017; Deary, Chalder, & Sharpe, 2007; Jackson & Kroenke, 2008).

The causes of withdrawing can be varied and may include fear of discomfort and fear of symptom intensification. Additionally, people with SSD often have to manage co-occurring anxiety (19%) and mood disorders (13%) (van der Sluijs et al., 2015). Finally, anxiety and depression can cause the intensification of somatic symptoms (van der Sluijs et al.).

Perceived susceptibility to illness and somatic symptom disorder

Perceived susceptibility is an important explanatory construct in many psychological theories related to health behavior, including the Health Model (Hochbaum, 1958;

Rosenstock, 1960), Extended Parallel Process Model (Witte, 1992), and Protection Motivation

Theory (Rogers, 1975, 1983). These theories posit that perceived susceptibility, viewed as a cognitive risk appraisal, promotes preventive health behavior (e.g. treatment seeking). For instance, a meta-analysis has found that increased risk appraisals predicted changes in both intent and behavior (Sheeran, Harris, & Epton, 2014). Perceived susceptibility is also thought to have an emotional component. When high susceptibility is coupled with anxiety or worry the likelihood of behavior change, including treatment seeking, is greater (Sheeran et al., 2014). SSD AND PERCEIVED SUSCEPTIBILITY TO ILLNESS 6

The relationship between perceived susceptibility and treatment-seeking behavior can be explained in terms of operant conditioning. Heightened perceived susceptibility combined with health worry leads to treatment seeking. The health care provider then provides an intervention and/or reassurance which reduces anxiety and perceptions of susceptibility. This negative reinforcement may then increase the probability of future susceptibility misjudgments and treatment seeking.

Research indicates that perceived susceptibility may play a significant role in SSD (Rief

& Broadbent, 2007). More specifically, it has been shown that people with SSD tend to overestimate their susceptibility to and seem to have a self-concept of being physically weak (Crane & Martin, 2004; Rief, Hiller, & Margraf, 1998). For instance, Rief, Nanke,

Emmerich, Bender, & Zech (2004) examined a primary care sample of patients with SSD

(conceptualized as medically unexplained symptoms) and found that these patients perceived themselves to be physically weak. Additionally, Steinbrecher & Hiller (2011) examined a primary care sample of 277 patients with SSD (defined as Somatoform Disorders (DSM-IV)) and found that they were more likely to perceive themselves as being susceptible to illness/complaints relative to patients without the diagnosis. Finally, in a validation study of the

Schema Questionnaire-Short Form (SQ-SF), Welburn, Coristine, Dagg, Pontefract, & Jordan

(2002) found that the Vulnerability to Harm subscale of the SQ-SF (which is an index of susceptibility) correlated significantly with the Brief Symptom Inventory (BDI) Somatization

Subscale. Together, these results support the position that people with SSD may have higher levels of perceived susceptibility to illness.

Perceived susceptibility to illness can be based on internal stimuli (symptoms) and external stimuli (e.g. advertisements, articles). Concerning internal stimuli, perceived SSD AND PERCEIVED SUSCEPTIBILITY TO ILLNESS 7 susceptibility to illness may lead to symptom intensification. Specifically, when a person considers herself or himself to be highly susceptible to illness, she or he might carefully monitor bodily sensations in order to detect signs of illness (i.e. symptoms) which in turn could amplify bodily sensations (Deary et al, 2007). Furthermore, Herzog et al. (2015) showed that individuals with SSD reported health worry, rumination about symptoms, catastrophic interpretation of symptoms, as well as perceived susceptibility (defined as perceived bodily ).

Additionally, Rief et al. (1998) conducted a study in which they examined the cognitive styles, attitudes, interpretations of bodily sensations of people with SSD (defined as Somatization

Disorder). In their study, Rief et al. found that SSD was correlated with having a self-concept of being physically weak. Additionally, SSD was associated with catastrophic interpretations and increased detection of autonomic symptoms. These results indicate that individuals with SSD may have higher levels of perceived susceptibility and are more apt to catastrophically interpret physical symptoms.

When people with SSD are exposed to external stimuli (e.g. news, ads, articles) they may be prone to experience an increased level of perceived susceptibility to illness. Crane and Martin

(2002) examined this possibility among patients with Irritable Bowel Syndrome. Their investigation focused on perceived susceptibility to illness subsequent to a media alarm related to

Deep Vein Thrombosis. Crane and Martin exposed participants to news articles about Deep Vein

Thrombosis and then measured perceived susceptibility to Deep Vein Thrombosis and somatic symptoms. Researchers found that individuals with Irritable Bowel Syndrome had a higher perceived susceptibility to Deep Vein Thrombosis when compared to non-Irritable Bowel

Syndrome (healthy or with ) participants. Subsequently, Crane and Martin (2004) examined the perceived susceptibility of individuals with and without Irritable Bowel Syndrome SSD AND PERCEIVED SUSCEPTIBILITY TO ILLNESS 8 to unrelated illnesses (arthritis, bowel cancer). This study confirmed the findings of the former, indicating that people with Irritable Bowel Syndrome had a higher and general perceived susceptibility to illness.

In summary, perceived susceptibility to illness may be an important component of SSD.

Studies suggest that people with SSD tend to consider themselves to be more susceptible to disease. This perceived susceptibility to illness can be based on both internal and external health- related information.

Summary and hypotheses

In summary, SSD is the contemporary term used concerning patients with distressing somatic symptoms and associated psychological features (American Psychiatric Association,

2013). The prevalence, costs, and comorbidities associated with SSD are significant (van Geelen et al., 2015; Jackson & Kroenke, 2008; Budtz-Lilly et al., 2015; Toft et al., 2005; McAndrew,

2017; Barsky et al., 2005, Konnopka et al., 2013; Zonneveld et al., 2013; van der Sluijs et al.,

2015). Perceived susceptibility to illness has been shown to be an important determinant of treatment seeking in the general population (Sheeran et al., 2014). In addition to the cognitive aspect of perceived susceptibility to illness, there is an affective component that can take the form of health anxiety or worry (Sheeran et al., 2014). SSD has been associated with increased perceived susceptibility to illness, health-related worry, as well as heightened treatment-seeking

(Crane & Martin, 2004; Rief et al., 1998; Steinbrecher & Hiller, 2011). Some studies suggest that people with SSD tend to be more reactive to health-related information (Crane & Martin 2002,

2004), however, there are limited studies on these topics. To our knowledge, this is the first study that has examined perceived susceptibility to illness in individuals with SSD. SSD AND PERCEIVED SUSCEPTIBILITY TO ILLNESS 9

The primary aim of this study was to examine the effects of exposure to health-related stimuli on perceived susceptibility to illness and treatment seeking intent among people with and without SSD features. A secondary aim was to examine the relationships between perceived susceptibility, treatment seeking intent, and treatment seeking frequency. It was hypothesized that: (1) participants with SSD features would report higher perceived susceptibility to illness and treatment seeking intent than participants without SSD features and (2) exposure to a health- related video, relative to a non-health related video, would be associated with significantly higher levels of perceived susceptibility and treatment seeking intent among participants with

SSD features compared to participants without SSD features. It was also expected that higher levels of perceived susceptibility to illness and treatment seeking intent would be associated with higher treatment seeking frequency. SSD AND PERCEIVED SUSCEPTIBILITY TO ILLNESS 10

METHOD

Participants

Participants were recruited using Amazon’s Mechanical Turk (MTurk). MTurk is a crowdsourcing platform that allows registered workers to be paid for completing surveys. MTurk workers are demographically, culturally, and clinically diverse (Chandler & Shapiro, 2016;

Shapiro, Chandler, & Mueller, 2013). Participants where compensated with $1.00 for their participation in the study. Participants were included if they were at least 18 years old and were from the United States. Three hundred and eighty-one (N = 381) participants were recruited for the current study. Twenty-three (N=23) participants were removed from the final analyses since they did not correctly complete the three manipulation checks. Participants had to correctly answer the two attention gauge items found in the pre-video measures as well as the video- related question presented after the video. Thus, the final sample consisted of three hundred and fifty-eight (N = 358) participants (chronic inflammation video group N = 178; nature video group N = 180). Power analysis indicated that at least 147 participants are needed for the current study for a 0.3 between-group effect size with a power of 0.8 and alpha level of 0.05 (G*Power,

Faul, Erdfelder, Lang, & Buchner 2007). Also, 130 participants were identified as meeting criteria for SSD (N = 65 in both video conditions). Cut-off scores for SSD criteria are detailed below in the Procedure section. Due to missing data, one participant was excluded from the analyses that involved treatment seeking frequency as a variable. See Table 1 (Appendix I.) for a description of the overall sample.

Health-related video

Participants in the chronic inflammation video group were presented with a health-related video. Namely, participants watched a short film (2:42 minutes) on chronic inflammation. The SSD AND PERCEIVED SUSCEPTIBILITY TO ILLNESS 11 video addressed some of the causes (lack of exercise, unhealthy diet, emotional ) and symptoms/warning signs (leaky gut, acne, psoriasis, belly fat, fatigue, chronic aches and pains) of chronic inflammation. The video also emphasized the possible consequences of chronic inflammation, such as weight gain, cancer, arthritis, cardiovascular disease, asthma, diabetes, allergies, Crohn’s disease, colitis, flus and colds, and Alzheimer’s disease.

Non-health-related video

Participants in the nature video group were presented with a non-illness related, nature video. Accordingly, participants watched a short film (2:20 minutes) showing nature images

(ocean waves).

Measures

Demographic variables and medical history. Information was gathered about the participants’ gender, age, educational level, socioeconomic status, and ethnic background.

Concerning medical history, forty medical conditions were listed, and participants indicated whether they had experienced each one in their lifetime. A total number of diagnosed illnesses was generated by summing across the 40 items (1 = yes, 0 = no). Participants were also asked to indicate any history of psychiatric diagnoses (see Appendix A).

Additionally, given that the health-related video discussed chronic inflammation symptoms (skin problems, fatigue, digestive problems, leaky gut, and body aches), chronic inflammation risk factors (stress, lack of exercise, and being overweight), and chronic inflammation consequences (various illnesses), information was gathered about these factors as well. The chronic inflammation symptoms were combined into one variable by the following method: continuous variables (fatigue and body aches) were counted as a chronic inflammation symptoms if the participant answered “often” and “very often” and they were added together SSD AND PERCEIVED SUSCEPTIBILITY TO ILLNESS 12 with the categorical variables (skin problems, digestive problems, and leaky gut). The final score was the total number of the chronic inflammation symptoms with scores that could range from 0-

5. The chronic inflammation risk factors were treated as separate variables. Namely, stress was measured by the Perceived Stress Scale-4 (Cohen, Kamarck, & Mermelstein, 1983) and lack of exercise was assessed with a single item. Concerning being overweight, each participant’s BMI was calculated using their height and weight information. The chronic inflammation consequences (different illnesses) were all included in the diagnosed illnesses measure described above.

Patient health questionnaire-15 (PHQ-15). The PHQ-15 (Kroenke, Spitzer, &

Williams, 2002) is a self-report measure of distressing somatic symptoms (see Appendix B). The

PHQ-15 addresses the DSM-5 A criterion of SSD (i.e. the presence of distressing somatic symptoms). The PHQ-15 contains 15 items, 14 of which were included in the DSM-IV somatization disorder symptom list. For each item, participants rate how bothered they felt by each symptom in the past 4 weeks on a 3-point Likert scale ranging from 0 “not bothered at all” to 2 “bothered a lot”. Total scores can range from 0-30 with a higher score indicating greater somatic symptom distress. The PHQ-15 has shown good psychometric properties, with an excellent internal consistency (Cronbach α = .80) reported for a primary care population

(Kroenke, 2002) and the general population (Cronbach’s α = .82; Kocalevent, Hinz, & Brähler,

2013). Furthermore, in the general population intercorrelations between the PHQ-15 and measures of depression (PHQ-9 Depression scale, r=.75, p<.001), life satisfaction (SWLS, r=.37, p<.001), and health-related quality of life (SF-12 subscale, r=.64, p<.001) indicate that the PHQ-

15 has adequate convergent validity (Kocalevent et al., 2013). The authors argue that the high correlation between the PHQ-15 and PHQ-9 (r=.75, p<.001) is due to some of the shared items SSD AND PERCEIVED SUSCEPTIBILITY TO ILLNESS 13 between the two scales (i.e. fatigue, problems falling or sleeping too much). After removing these two items, the correlation decreased to r = .65, p < .001 (Kocalevent et al., 2013). In the current study, the PHQ-15 had adequate internal consistency (Cronbach’s α = .86). Additionally, the correlation between the PHQ-9 and PHQ-15 in the current study was r = .64 (p < .01).

In addition to the 15 items, two items were added asking participants whether they had experienced any physical complaints for more than six months and to rate the degree to which they have been symptomatic in the last six months. The aforementioned items were included to address the DSM-5 C criterion of SSD, which states that, in order to receive a diagnosis, a person has to be persistently symptomatic (usually for more than six months).

Somatic symptom disorder - B criteria scale (SSD-12). The SSD-12 (Toussaint et al.,

2016) is a self-report measure of the Somatic Symptom Disorder (DSM-5) B criteria (see

Appendix C). The B criteria refer to cognitions, emotions, and behaviors that are associated with somatic symptoms. The SSD-12 contains 12 items. For each item, participants rate how frequently they experience each cognition, emotion, or behavior on a 5-point Likert scale ranging from 0 “(Never)” to 4 “(Very often)”. Total scores can range from 0-48 with a higher score indicating greater psychological symptom burden. Subscale (cognitive, emotional, behavioral) scores can also be calculated and they range from 0-16 with higher scores indicating more severe psychological symptoms. Using an outpatient sample of 698 individuals, Toussaint et al. (2016), reported that the SSD-12 had strong internal consistency (Cronbach’s α = .95 for the whole scale; α=.71 for the cognitive subscale; α=.91 for the affective subscale; and α=.92 for the behavioral subscale). Additionally, an excellent internal reliability of SSD-12 was also found in the general population (Cronbach’s α=.95; Toussaint, Löwe, Brähler, & Jordan, 2017). Toussaint et al. (2016) also found that the SSD-12 had adequate divergent validity. While anxiety, SSD AND PERCEIVED SUSCEPTIBILITY TO ILLNESS 14 depression, and somatization disorders frequently co-occur, they are different constructs.

Appropriately, Toussaint et al. found moderate associations between SSD-12 and anxiety (GAD-

7; r=.35), as well as depression (PHQ-9; r=.22). Toussaint et al. also reported adequate construct validity because they observed a correlation of r = .47 between the SSD-12 and the PHQ-15, and a correlation of r = .71 between the SSD-12 and health anxiety (Whitely Index-7). In the current study, the SSD-12 had adequate internal consistency for the whole scale (Cronbach’s α = .91), for the cognitive subscale (Cronbach’s α = .56), for the affective subscale (Cronbach’s α = .86), and for the behavioral subscale (Cronbach’s α = .87). After removing item #7 (“Others tell me that my physical problems are not serious”) from the cognitive subscale internal consistency analysis resulted in a Cronbach’s α = .75.

Treatment seeking frequency. To assess for treatment seeking frequency participants were asked about the frequency of medical visits in the past six months (see Appendix D). More specifically, participants were asked how many times they have visited different providers in the past six months. Subsequently, all number of visits from all providers were added up to calculate a final treatment seeking frequency score. Previous research has shown that self-reported outpatient visits, as well as inpatient/nights spent in the hospital, correlate highly with electronic medical records, respectively (r=.70 and r=.83; Lorig et al., 2001).

Mood. Nervousness and Relaxation were assessed using items taken from the Profile of

Mood State (McNair, Lorr, & Droppelman 1971; Heuchert & McNair, 2012). Participants were asked to rate to what degree were they feeling Relaxed and Nervous both before and after the video. Each item was rated on a 5-point Likert scale that ranged from 0 (not at all) to 4

(extremely) (see Appendix E). SSD AND PERCEIVED SUSCEPTIBILITY TO ILLNESS 15

Perceived susceptibility to illness and treatment seeking intent. The Absolute Risk

Rating Form (ARRF) was used to assess perceived susceptibility to illness. The ARRF contains

45 items referring to various illnesses or accidents (Weinstein, 1982). For each item, participants rate the likelihood that the event/illness will happen to them within their lifetime on a 7-point

Likert scale ranging from 1 (no chance) to 7 (certain). Higher scores indicate higher levels of perceived susceptibility. The number and kind of items of the ARRF vary from study to study.

For instance, Weinstein (1984) reported using 6, 8, and 10 item ARRFs in his studies examining perceived susceptibility and perceived risk factors, while O’Brien & VanEgeren (1991) used a

52-item version in their study focused on perceived susceptibility to heart disease and preventive health behaviors. The O’Brien & VanEgeren (1991) version of the ARRF was adapted by retaining only the items (illnesses) that are mentioned in the chronic inflammation video.

Furthermore, items (illnesses) that are mentioned in the chronic inflammation video but are not contained in the original ARRF (Crohn’s disease, infections, gout, Alzheimer’s disease, and stroke) were also added to the measure. Thus, the final scale consisted of 22 items with higher scores indicating higher levels of perceived susceptibility, total scores ranging from 22-154 (see

Appendix F). The ARRF was made of a list of illnesses mentioned in the chronic inflammation video. In the current study, the ARRF had adequate internal consistency (Cronbach’s α = .94).

The treatment seeking intent measure was made up of 22 items listing the illnesses mentioned in the chronic inflammation video (see Appendix G). The items were identical to that of the ARRF. Participants were asked to rate on a 7-point Likert scale (1- “no chance” to 7-

“certain”) the likelihood that they will seek out medical assessment for the listed symptoms/illnesses in their lifetime. Higher scores were indicative of higher levels of intent to SSD AND PERCEIVED SUSCEPTIBILITY TO ILLNESS 16 seek treatment, total scores ranging from 22-154. In the current study, the treatment seeking intent scale had adequate internal consistency (Cronbach’s α = .97).

Procedure

All study procedures were conducted online through MTurk. Interested participants were presented with an Informed Consent form. After agreeing to participate in the study, participants completed demographics, history, number of diagnosed illnesses, chronic inflammation symptoms and risk factors, PHQ-15, SSD-12, treatment seeking frequency, and mood self-report measures. After completing the questionnaires, participants were randomly assigned to either the chronic inflammation video group (chronic inflammation video) or the nature video group (nature video). After exposure to the video, participants were asked to complete the mood, perceived susceptibility to illness, and treatment seeking intent measures.

Chandler & Shapiro’s (2016) guidelines were followed in order to measure participant attentiveness. Therefore, participants were included only if they had a 90% or higher HIT

(Human Intelligence Task) approval rate. HIT approval rates reflect the amount of approved and rejected HITs of an MTurk Worker. If a Worker has a high rejection rate it indicates that he/she is frequently rejected by researchers. HIT approval rate can be used as a participant’s overall work quality indicator. Additionally, two instructional manipulation checks (“Please select

‘Sometimes’ for this item” and “Please select ‘extremely difficult’ for this item”) were employed in the survey.

Furthermore, three methods were employed to ensure that participants watched the videos. First, on a separate page, preceding the video, a message was included informing participants that they are about the view a video and that they will be asked questions about it afterward. They were also asked to have their speakers and sound on and to hit the “Next” page SSD AND PERCEIVED SUSCEPTIBILITY TO ILLNESS 17 whenever they are ready for the video message. Second, after viewing the video, participants were asked one question about the content of the video: What was the video about? (a) waves,

(b) chronic inflammation, (c) trees, (d) hemophilia. Third, the Timing Question feature of

Qualtrics was used to track the time a participant spends on the video page. The Timing Question is a hidden question that can conceal the “Next” button until the participant has had enough time to view the video and it also measures how many seconds a participant spends on the given page.

Finally, after collecting data, participants’ responses were examined, based on the DSM-5 criteria (American Psychiatric Association, 2013), to see if they meet criteria for SSD. In order to establish diagnosis, participants’ PHQ-15 score, persistence of somatic symptoms (6 months or more), and SSD-12 score were combined. The following cut-off scores were employed: a score of 10 or more on the PHQ-15, the presence of all/some of these symptoms for 6 or more months, and a score of 22 on the SSD-12. If a participant met all 3 criteria, they were assigned to the

“with SSD features” group which is consistent with DSM-5 criteria. The cut-off scores for the

PHQ-15 were based on the validity study of the PHQ-15 (Kroenke et al., 2002). The study was conducted with a sample of primary care (N = 3000) and obstetrics-gynecology (N = 3000) clinic patients. The identified categories were minimal (0-4), low (5-9), medium (10-14), and high (15-

30). The cut-off score for the SSD-12 were based on the results of Kamp et al. (2017), who examined the diagnostic validity of the SSD-12 by comparing it to a psychiatric diagnostic assessment. The sample consisted of one hundred and two (N = 102) participants from two outpatient clinics. Researchers found that a cut-off score of 22 results in a 66% of sensitivity and

59% of specificity. SSD AND PERCEIVED SUSCEPTIBILITY TO ILLNESS 18

RESULTS

Comparisons on pre-video measures of the two video conditions

Demographic differences between the chronic inflammation video group and the nature video group were examined with independent t-tests (for continuous variables) and chi square analyses (for dichotomous variables). There were no significant differences between the two video conditions on the following demographic variables: age, sex, race, mental health history, education, relationship status, income, and living area (see Appendix I., Table 1). Pre-video between video group comparisons were also conducted on the PHQ-15, the SSD-12, persistence of somatic symptoms, mood, and treatment seeking frequency. No significant differences were found on these variables (see Appendix I., Table 2).

Pre-video between group comparisons were conducted to examine if there are differences between the two video groups on chronic inflammation risk factors (stress, BMI, lack of exercise), chronic inflammation symptoms (leaky gut, skin problems, digestive problems, fatigue, and body aches) and number of diagnosed illnesses. There were no significant differences observed (see Appendix I., Table 3).

Comparisons on pre-video measures of participants with and without SSD features

Demographic differences between participants with and without SSD features were examined with independent t-tests (for continuous variables) and chi square analyses (for dichotomous variables). There were no significant differences between participants with SSD features and without SSD features on the following demographic variables: age, sex, race, education, relationship status, income, and living area (see Appendix I., Table 4). There were significant differences between the participants with and without SSD features on history of depression, anxiety disorders, Post-Traumatic Stress Disorder (PTSD), and other mental health SSD AND PERCEIVED SUSCEPTIBILITY TO ILLNESS 19 conditions. Participants with SSD features, relative to people without SSD features, also reported significantly higher levels of stress, chronic inflammation symptoms, number of diagnosed illnesses, and treatment seeking frequency (see Appendix I., Table 5).

Manipulation check: Effect of video exposure on perceived susceptibility, treatment seeking intent, and mood

A one-way ANOVA was conducted with video condition (chronic inflammation video/nature video) as the independent variable and perceived susceptibility to illness as the dependent variable. There was a significant effect of video condition on perceived susceptibility to illness (F (1, 356) = 5.34, p = .02; ηp² = .02). Participants in the chronic inflammation video group (M= 87.28; SD = 22.60) had significantly higher perceived susceptibility to illness scores relative to participants in the nature video group (M= 81.62; SD= 23.70).

A one-way ANOVA was conducted with video condition (chronic inflammation video/nature video) as the independent variable and treatment seeking intent as the dependent variable. There was no significant effect of video condition on treatment seeking intent (F (1,

356) = 1.57, p = .21, ηp² = .004).

To assess changes in mood, two 2 x 2 ANOVAs were conducted with video condition

(chronic inflammation video/nature video) as the between-subject independent variable, time

(pre-video, post-video) as the within-subject independent variable, and mood as the dependent variable.

For the Nervousness item the main effects of video condition (F (1, 356) = 1.77, p = .18,

ηp² = .01) and time (F (1, 356) = 1.76, p = .19, ηp² = .01) were nonsignificant (see Appendix I.,

Table 6). There was a significant interaction between video condition and time (F (1, 356) =

42.59, p < .001, ηp² = .11). Planned pairwise comparisons were conducted for each video SSD AND PERCEIVED SUSCEPTIBILITY TO ILLNESS 20 condition. Results showed that participants in the chronic inflammation video group had a significant pre- to post-video increase in Nervousness while participants in the nature video group had a significant pre- to post-video decrease in Nervousness (see Appendix I., Table 7).

For the Relaxation item, there was a significant effect of video condition (F (1, 356) =

7.88, p = .005, ηp² = .02). Participants in the chronic inflammation video group (M = 3.14; Std.

Error = 0.9) had lower Relaxation scores relative to participants in the nature video group (M =

3.47; Std. Error = .09). There also was a significant effect of time (F (1, 356) = 6.09, p = .01, ηp²

= .02) with an overall increase in Relaxation from pre-video (M = 3.25; Std. Error = .06) to post- video (M = 3.36; Std. Error = .06). There was a significant interaction between video condition and time (F (1, 356) = 115.77, p < .001, ηp² = .25). Planned pairwise comparisons were conducted for each video condition. The results indicated that participants in the chronic inflammation video group had a significant decrease in Relaxation scores from pre-video to post- video, while participants in the nature video group had a significant increase in Relaxation scale scores from pre-video to post-video (see Appendix I., Table 8).

Effects of video condition and SSD features on perceived susceptibility to illness and treatment seeking intent

Two 2 x 2 (chronic inflammation video/nature video x with SSD/without SSD features)

ANOVAs were conducted using perceived susceptibility to illness and treatment seeking intent as dependent variables.

Concerning perceived susceptibility to illness there was a significant main effect of SSD features (F (1,354) = 44.79, p < .001, ηp² = .11). Participants with SSD features (M = 94.69; SD

= 18.72) had significantly higher perceived susceptibility to illness scores relative to participants without SSD features (M = 78.58; SD = 23.66) across conditions. As noted earlier, there also was SSD AND PERCEIVED SUSCEPTIBILITY TO ILLNESS 21 a significant main effect of video condition (F (1,354) = 5.98, p = .02, ηp² = .02) with participants in the chronic inflammation video group having higher perceived susceptibility to illness scores relative to participants in the nature video group. There was no significant interaction between SSD features and video condition (F (1,354) = .19, p = .66, ηp² = .001) (see

Appendix J., Figure 1).

Given that history of depression, anxiety disorders, PTSD, other mental health conditions, stress, chronic inflammation symptoms, number of diagnosed illnesses, and treatment seeking frequency were significantly different between participants with SSD and without SSD features, these eight variables were included as covariates in a two-way ANCOVA. After controlling for the aforementioned variables, the main effects of SSD features (F (1, 345) = 5.77, p = .02, ηp² = .02) and video condition (F (1, 345) = 7.20, p = .01; ηp² = .02) remained significant. The main effects of stress (F (1, 345) = 4.63, p = .03; ηp² = .01), chronic inflammation symptoms (F (1, 345) = 4.82, p = .03; ηp² = .01), and number of diagnosed illnesses (F (1, 345) = 21.67, p < .001; ηp² = .06) were also significant. The main effects of history of depression (F (1, 345) = .42, p = .52; ηp² = .001), history of anxiety disorders (F (1,

345) = 3.38, p = .07; ηp² = .01), history of PTSD (F (1, 345) = 1.42, p = .23; ηp² = .004), history of other mental health conditions (F (1, 345) = .37, p = .55; ηp² = .001), and treatment seeking frequency (F (1, 345) = .05, p = .83; ηp² < .001) were nonsignificant. Finally, as noted above, there was no significant interaction between video condition and SSD features (F (1, 345) = .15, p = .70; ηp² < .001).

Concerning treatment seeking intent, there was a significant main effect of SSD features

(F (1, 354) = 5.20, p = .02, ηp² = .01) on treatment seeking intent. Participants with SSD features

(M = 105.53; SD = 27.02) had higher treatment seeking intent scores relative to participants SSD AND PERCEIVED SUSCEPTIBILITY TO ILLNESS 22 without SSD features (M = 97.20; SD = 36.12). Again, as noted above, there was no significant main effect of video condition (F (1, 354) = 1.23, p = .27, ηp² = .00). There was no significant interaction between SSD features and video condition (F (1,354) = .11, p = .74, ηp² < .001) (see

Appendix J., Figure 2).

Given that history of depression, anxiety disorders, PTSD, other mental health conditions, stress, stress, chronic inflammation symptoms, number of diagnosed illnesses, and treatment seeking frequency were significantly different between participants with SSD and without SSD features, these eight variables were included as covariates in a two-way ANCOVA.

After controlling for the aforementioned variables, the main effects of SSD features (F (1, 345) =

.26, p = .61, ηp² = .001) and video condition (F (1, 345) = 1.65, p = .20, ηp² = .005) were nonsignificant. The main effects of history of depression (F (1, 345) = .14, p = .71, ηp² < .001), history of anxiety disorders (F (1, 345) = 1.22, p = .27, ηp² = .004), history of PTSD (F (1, 345)

= .07, p = .79, ηp² < .001), history of other mental health conditions (F (1, 345) = .03, p = .88,

ηp² < .001), stress (F (1, 345) = .72, p = .40, ηp² = .002), chronic inflammation symptoms (F (1,

345) = 1.82, p = .18, ηp² = .005), number of diagnosed illnesses (F (1, 345) = 3.05, p = .08, ηp² =

.009), and treatment seeking frequency (F (1, 345) = 1.34, p = .25, ηp² = .004) were also nonsignificant. Finally, as noted above, there was no significant interaction between video condition and SSD features (F (1, 345) = .001, p = .98; ηp² < .001).

Effects of video condition and SSD features on mood

Two three-way (chronic inflammation video/nature video x with SSD/without SSD features x pre/post mood) mixed ANOVAs were conducted using mood as dependent variable.

Concerning the Nervousness scale, there was a significant main effect of SSD features on

Nervousness (F (1, 354) = 15.71, p < .001, ηp² = .04) scale. Participants with SSD features (M = SSD AND PERCEIVED SUSCEPTIBILITY TO ILLNESS 23

1.86; Std. Error = .08) had higher Nervousness scores than participants without SSD features (M

= 1.48; Std. Error = .06). As noted above, there was a nonsignificant main effect of video condition (F (1, 354) = 2.32, p < .13, ηp² = .01). There was a significant main effect of time (F

(1, 354) = 4.80, p < .03, ηp² = .01). There was an overall decrease in Nervousness from pre- (M

= 1.71, Std. Error = .05) to post-video (M = 1.63, Std. Error = .05).

There was a significant three-way interaction between video condition, SSD features, and time on the Nervousness scale (F (1, 354) = 3.85, p = .05, ηp² = .01) (see Appendix I., Table 9).

Planned pairwise comparisons were conducted for participants with SSD features and without

SSD features and the two video conditions (see Appendix I., Table 10 and Appendix J., Figure

3). The results indicated that participants with SSD features who were in the chronic inflammation video group did not show a significant difference in Nervousness scores from pre- to post-video, while participants without SSD features in the chronic inflammation video group had a significant increase in Nervousness scores from pre- to post-video. On the other hand, in the nature video group participants with SSD features had a significantly greater decrease in

Nervousness scores from pre- to post-video than participants without SSD features.

Concerning the Relaxation scale, there was a significant main effect of SSD features on the Relaxation item (F (1, 354) = 18.02, p < .001, ηp² = .05) scale. Participants with SSD features (M = 2.97; Std. Error = .10) had lower Relaxation scale score than participants without

SSD features (M = 3.49; Std. Error = .07). As noted above, there was a significant main effect of video condition (F (1, 354) = 7.48, p = .01, ηp² = .02) and time (F (1, 354) = 10.72, p = .001, ηp²

= .03).

There was a significant three-way interaction between video condition, SSD features, and time on the Relaxation scale (F (1, 354) = 9.86, p = .002, ηp² = .03) (see Appendix I., Table 9). SSD AND PERCEIVED SUSCEPTIBILITY TO ILLNESS 24

Planned pairwise comparisons were conducted (see Appendix I., Table 11 and Appendix J.,

Figure 4). The results indicated that participants with SSD features who were in the chronic inflammation video group had a significant decrease in Relaxation scores from pre- to post- video, as did participants without SSD features in the chronic inflammation video group. On the other hand, in the nature video group participants with SSD features had a significantly greater increase in Relaxation scale score from pre- to post-video than participants without SSD features.

Relationship between post-video mood, perceived susceptibility to illness, and treatment seeking intent

There was a significant but small positive correlation between perceived susceptibility to illness and Nervousness (r = .19, p < .01) and a small negative correlation between perceived susceptibility to illness and Relaxation (r = -.20, p < .01). There was no significant correlation between treatment seeking intent and Nervousness and treatment seeking intent and Relaxation.

Relationship between perceived susceptibility to illness, treatment seeking intent, and treatment seeking frequency

Because perceived susceptibility to illness and treatment seeking intent were collected after the video while treatment seeking frequency was collected prior to the video, separate correlations were conducted for each video condition. Concerning the nature video group there was a significant but small correlation between perceived susceptibility to illness and treatment seeking frequency (r = .23, p < .01). There was also a significant but small positive correlation between treatment seeking intent and treatment seeking frequency (r = .20, p < .01). Regarding the chronic inflammation video group, there was no significant correlation between treatment seeking frequency and perceived susceptibility to illness (r = .02, p = .80) or treatment seeking intent (r = .01, p = .93). SSD AND PERCEIVED SUSCEPTIBILITY TO ILLNESS 25

Also, correlations were conducted for participants with and without SSD features in both video conditions. There was a significant but small correlation between treatment seeking frequency and perceived susceptibility to illness (r = .22, p < .05) as well as treatment seeking frequency and treatment seeking intent (r = .19, p < .05) in people without SSD features who were in the nature video group. There were no significant correlations between treatment seeking frequency and perceived susceptibility to illness as well as treatment seeking frequency and treatment seeking intent in participants with SSD features in the nature video group (r = .13, p =

.30; r = .19, p = .13, respectively), participants without SSD features in the chronic inflammation video group (r = -.03, p = .72; r = -.04, p = .68, respectively), and participants with SSD features in the chronic inflammation video group (r = .08, p = .51; r = .10, p = .43, respectively).

Correlations between perceived susceptibility, treatment seeking intent, and chronic inflammation video factors

To examine whether chronic inflammation risk factors (stress, being overweight – BMI -, lack of exercise), chronic inflammation symptoms (leaky gut, skin problems, digestive problems, fatigue, and body aches) and number of diagnosed illnesses were related to perceived susceptibility to illness and treatment seeking intent, correlations between these variables were conducted separately for the two video conditions. Among participants in the chronic inflammation video group, perceived susceptibility to illness was significantly positively correlated with stress, chronic inflammation symptoms, and number of diagnosed illnesses.

Treatment seeking intent was significantly positively correlated with chronic inflammation symptoms (see Appendix I., Table 12). Among participants in the nature video group, perceived susceptibility to illness was significantly positively correlated with stress, chronic inflammation SSD AND PERCEIVED SUSCEPTIBILITY TO ILLNESS 26 symptoms, and number of diagnosed illnesses. Treatment seeking intent was significantly positively correlated with number of diagnosed illnesses (see Appendix I., Table 13).

Summary of results

Overall, a suitable number of participants met criteria for SSD so that two groups (with SSD features and without SSD features) were formed. SSD was associated with higher reporting of mental health conditions (e.g. history of depression, anxiety disorders, PTSD, and other), higher treatment seeking frequency, and higher number of diagnosed illnesses. The chronic inflammation video elicited expected increases in perceived susceptibility to illness and in one of the mood scales (Relaxation) but not in treatment seeking intent and the second mood scale

(Nervousness). The first hypothesis was confirmed, participants with SSD features reported higher perceived susceptibility to illness and treatment seeking intent overall. Results did not confirm the second hypothesis, there was no significant interaction between video condition and

SSD features. While treatment seeking frequency was related to perceived susceptibility to illness and treatment seeking intent, these correlations were only significant regarding participants without SSD features in the nature video group. Participants with SSD features did report significantly higher Nervousness and lower Relaxation scores. Participants with SSD features reported significantly greater increase in Relaxation and decrease in Nervousness than participants without SSD features after viewing the nature video. Only participants without SSD features showed a significant increase in Nervousness after watching the chronic inflammation video. Both participants with SSD features and without SSD features showed a similar decrease in Relaxation after watching the chronic inflammation video. SSD AND PERCEIVED SUSCEPTIBILITY TO ILLNESS 27

DISCUSSION

The current study relied on MTurk to recruit participants. Given that one hundred and thirty (N=130) participants out of three hundred and fifty-eight (N = 358) were identified as meeting criteria for SSD, MTurk proved to be a valuable platform to identify people with this disorder. While previous studies have not examined SSD in the MTurk population, research suggests that MTurk workers experience more elevated clinical symptoms (e.g. anxiety, difficulties in social functioning, psychological distress) than community or college student samples (Chandler & Shapiro, 2016). Additionally, MTurk can provide people with SSD the ability to work from home and adapt work schedules to fit personal demands. Specifically, some people with SSD tend to socially withdraw (Dirkzwager & Verhaak, 2007), be on disability programs (Carson et al., 2011), or take multiple sick leaves (Bakker et al., 2007; Rask et al.,

2015). This likely makes MTurk an attractive work opportunity for people with SSD. Indeed, it has been reported that MTurk workers have higher unemployment rates than the general population (Ross, Zaldivar, Irani, & Tomlinson, 2010).

The present paper examined whether individuals with SSD features differed from those without SSD features with respect to perceived susceptibility to illness and treatment seeking intent after being exposed to health-related information. Concerning perceived susceptibility to illness, the results of the current study indicate that individuals with SSD features tended to perceive themselves to be more susceptible to illness when compared to individuals without SSD features. Even after controlling for history of mental health conditions, stress, chronic inflammation symptoms, number of diagnosed illnesses, and treatment seeking frequency the effects of SSD features remained significant. These findings are noteworthy given the predictive value of perceived susceptibility to illness in treatment seeking (Sheeran et al., 2014) and the SSD AND PERCEIVED SUSCEPTIBILITY TO ILLNESS 28 perpetuating feature of treatment seeking frequency in SSD (Rief & Broadbent, 2007).

Furthermore, results indicate that overall, the video type had a significant effect on perceived susceptibility to illness. Specifically, participants in the chronic inflammation video group reported higher perceived susceptibility to illness than participants in the nature video group, even after controlling for history of mental health conditions, stress, chronic inflammation symptoms, number of diagnosed illnesses, and treatment seeking frequency. Nonetheless, there was no significant interaction between video condition and SSD features, indicating that participants with SSD features did not react more to the health-related information (chronic inflammation video) than to the non-health related information (nature video).

These results are in part consistent with the literature. For instance, Rief et al. (1998) also examined the cognitive features of people with SSD (conceptualized as somatization). Although the authors did not measure perceived susceptibility to illness directly, they did report that participants with SSD tended to have a self-perception of being physically weak. Furthermore,

Rief et al. (2004), while studying the causal illness attributions of people with SSD

(conceptualized as Somatoform disorder), found that participants with SSD scored higher on the

“vulnerability to infection and environmental factors” scale than participants without SSD. With regards to the interaction between video type and SSD features, our results are not entirely consistent with the literature. Namely, Crane & Martin (2002; 2004) found that when exposed to health-related information participants with Irritable Bowel Syndrome (IBS) reported greater perceived susceptibility to illness than those without IBS. Nonetheless, Crane & Martin’s studies did not include a control condition and the group of participants was made up of a more specific disorder (Irritable Bowel Syndrome). Consequently, it could be that people with IBS respond differently to health-related information than those with general SSD. Furthermore, Crane & SSD AND PERCEIVED SUSCEPTIBILITY TO ILLNESS 29

Martin’s studies also differ from the current study with respect to the health-related information they used (previous DVT media scare), the smaller number of participants (total N = 124, IBS =

19, 2002; total N = 200; IBS = 19, 2004), and sample type (university clerical staff, 2002; college students, 2004 ). The divergence between the studies warrants further examination of the relationship between health-related information, SSD, and perceived susceptibility to illness.

The nonsignificant interaction between video type and SSD features could be a function of a ceiling effect. The results suggest that participants with SSD features already had a higher perceived susceptibility to illness then participants without SSD features, and thus they did not experience a significant increase in their susceptibility after watching the chronic inflammation video. The results regarding mood provide support for this interpretation. Participants with SSD features who watched the chronic inflammation video had a nonsignificant change from pre- to post-video in Nervousness and decrease in Relaxation that was similar to participants without

SSD features. It is likely that participants with SSD features already experienced high

Nervousness and low Relaxation such that the chronic inflammation video was not able to elicit additional changes in mood. Another possible explanation for the lack of interaction between

SSD features and video type on perceived susceptibility could be that the people with SSD features have had more experience with health-related information and were therefore more habituated to it. Additionally, it is also possible that participants with SSD features may be more reactive to internal health-related information (e.g. somatic symptoms) relative to external health-related stimuli. Finally, it could be that the chronic inflammation video was not perceived as more threatening or relevant by participants with SSD features than by those without SSD features. SSD AND PERCEIVED SUSCEPTIBILITY TO ILLNESS 30

Regarding treatment seeking intent, SSD features had a significant but smaller effect on treatment seeking intent than on perceived susceptibility to illness. However, SSD features was no longer a significant predictor of treatment seeking intent after controlling for history of mental health conditions, stress, chronic inflammation symptoms, number of diagnosed illnesses, and treatment seeking frequency. Of the covariates, only chronic inflammation symptoms and number of diagnoses illnesses were significantly correlated with treatment seeking intent.

Finally, the video condition did not have a significant effect on treatment seeking intent and the interaction between SSD features and video condition was also nonsignificant.

Similar to the perceived susceptibility to illness findings, there might have been a ceiling effect with people with SSD features already having a very high level of treatment seeking intent and consequently they did not experience any significant changes in their treatment seeking intent level after watching the chronic inflammation video. The smaller effect on treatment seeking intent could also be attributed to the lack of sensitivity of the treatment seeking intent measure. The instructions of the measure asked participants to consider whether they will seek out medical care for the illnesses listed in their lifetime. Given the broad time frame (lifetime) and possibly the high likelihood of actually developing such illnesses in one’s lifetime, it is likely that the treatment seeking intent measure did not capture the effects of the video and SSD features on treatment seeking intent.

Also, results suggest that increased treatment seeking frequency was associated with perceived susceptibility to illness and treatment seeking intent among participants without SSD features in the nature video group. Previous studies reported that susceptibility judgements are predictors of treatment seeking. For instance, Sheeran et al. (2014) indicated that increased risk appraisals are associated with changes in intention and behavior. Additionally, in another meta- SSD AND PERCEIVED SUSCEPTIBILITY TO ILLNESS 31 analysis researchers found that perceived susceptibility was a significant predictor of vaccination

(Brewer et al., 2007). A possible explanation for the small correlation is that the treatment seeking frequency measure was collected prior to the video and the perceived susceptibility to illness/treatment seeking intent was completed after the video. Previous studies typically examined the effects of perceived susceptibility to illness prior to the assessment of treatment seeking frequency, thus providing a more accurate picture of the predictive effects of risk perceptions. Additionally, the current study did not measure general perceived susceptibility to illness but focused in the illnesses mentioned in the chronic inflammation video. Also, the difference in sample size between participants with SSD features (N = 65/video condition) and without SSD features (N = 115 nature video group; N= 113 chronic inflammation video group) might have also contributed to the small and nonsignificant correlations between treatment seeking frequency and perceived susceptibility to illness/treatment seeking intent.

Although not included in the hypotheses, exploratory analyses were conducted examining the effect of video condition and SSD features on mood (Nervousness and Relaxation). The results suggest that being exposed to health-related information (chronic inflammation video) increased Nervousness and decreased Relaxation from pre- to post-video. Interestingly, participants who viewed the nature video experienced a decrease in Nervousness and increase in

Relaxation over time. While initially intended as a neutral video, it is likely that the type of the nature video (i.e. waves) could have had relaxation properties and thus might have induced a sense of relaxation in participants. Participants with SSD features reported higher Nervousness and lower Relaxations than participants without SSD features. These results are in line with the literature (Han et al., 2004; Lipsitz et al., 2004; Rief & Broadbent, 2007) which indicates that people with SSD features experience higher anxiety and worry, especially related to health. SSD AND PERCEIVED SUSCEPTIBILITY TO ILLNESS 32

Results showed a significant three-way interaction between video condition, SSD features, and time on both the Nervousness and Relaxation scales. Overall, results indicate that participants with SSD features reported a significantly greater decrease in Nervousness and increase in Relaxation after watching the nature video than participants without SSD features.

Additionally, in the chronic inflammation video group participants with SSD features did not report significant changes from pre- to post-video while participants without SSD features reported a significant increase in Nervousness. Similar to the findings concerning perceived susceptibility to illness and treatment seeking intent, these results could suggest a ceiling effect such that participants with SSD features, given their higher levels of Nervousness, were not able to increase in Nervousness after watching the chronic inflammation video. An alternative explanation may be that participants without SSD features were presented with novel information and thus reacted more to it while those with SSD features were already habituated to the health-related information presented in the chronic inflammation video. It is likely that individuals with SSD features tend to seek out health-related information more frequently than those without SSD features.

Limitations

There are several limitations in the current study. One limitation is that the SSD diagnosis was based on self-report measures. Future studies should replicate the current design by also including participants with SSD identified based on structural clinical interview and medical examination. Such studies could provide more confidence that the selected individuals are indeed suffering from SSD. Additionally, all study variables were based on self-report which increases the likelihood of common-method bias. SSD AND PERCEIVED SUSCEPTIBILITY TO ILLNESS 33

A second limitation of the current study is that it relied on an MTurk sample and consequently it limits the generalizability of findings to the overall population. As mentioned above, MTurk provides a useful platform to conduct research on clinical symptoms and it is also considered a more diverse sample than other convenience samples (e.g. college students).

Nonetheless, MTurk workers differ from the general population in that they are reportedly more attentive when completing surveys and experiments (Boas, Christenson, & Glick, 2018), are younger, have higher education level, and lower income (Levay, Freese, & Druckman, 2016;

Berinsky, Huber, & Lenz, 2012). Additionally, it has been reported that there is a small number of workers who complete most tasks posted on MTurk. It is thus suggested that these workers have likely completed the same surveys multiple times and are also highly experienced. This may alter their performance and the treatment effects (Chandler, Mueller, & Paolacci, 2014). It has also been suggested that MTurk workers endorse clinical symptoms not usually reported in the general population. According to researchers this could be a sign of trying to please the investigator by inferring demands and conforming to those demands (Shapiro et al., 2013).

Future studies should replicate the current study with individuals with and without SSD from different settings (primary care or the general population).

A third limitation is that participants of the study were self-selected. It is possible that after reading the title of the survey (“Individual differences in perceived susceptibility to illness”) participants with somatic symptoms and chronic illnesses might have been more likely to participate in the study. One concern with self-selection is the possibility of restriction of range concerning the SSD measures as well as the medical history and perceived susceptibility measures. For example, while 228 participants did not meet all three criteria for SSD, multiple participants met at least two of the criteria. Consequently, the effect sizes found in the current SSD AND PERCEIVED SUSCEPTIBILITY TO ILLNESS 34 study may have been diminished if indeed mainly participants with somatic symptoms and/or chronic illnesses participated in the study.

A fourth limitation is that this study did not include a pre-video assessment of perceived susceptibility to illness. This limits our insight into the extent to which people with and without

SSD features may have reacted differently to the two video conditions. Future studies should extend this research by including both pre- and post-measures of perceived susceptibility to illness and treatment seeking intent.

A fifth limitation of the current study is that because the study was conducted online it cannot be known whether the participants actually watched the video or simply waited until enough time elapsed so that they could proceed with the completion of the survey.

Future directions and concluding comments

It would be important to determine whether heightened perceived susceptibility to illness develops prior to SSD or after acquiring SSD. Additionally, given that in the current sample participants with SSD features also had higher occurrence of medical illnesses in the past compared to participants without SSD features, it would be important to see if perceived susceptibility to illness develops as a result of having experienced multiple illnesses in the past.

Moreover, future research should focus on assessing objective risk factors of developing various conditions in SSD populations and their levels of perceived susceptibility to illness. For instance, some individuals might actually be more susceptible to certain illnesses (e.g. due to genetic history) and this objective risk could be compared against their perceived risk. Also, combining self-report, other-report, and psychophysiological measures in replicating these findings would likely contribute to the validity and reliability of the results. Finally, given that the SSD-12 and SSD AND PERCEIVED SUSCEPTIBILITY TO ILLNESS 35 its cut-off score were developed using European (German and Dutch) samples, future studies should aim to validate these on US-based samples.

In sum, the current study provides evidence that people with SSD features report higher perceived susceptibility to illness and, to a certain degree, treatment seeking intent. The heightened perceived susceptibility may be associated with increased health care utilization.

Future studies should replicate the current findings within the general and health care (e.g. primary care) population and by implementing multiple diagnostic methods (e.g. self-report, medical examination). Future research could implement pre- and post-measures of perceived susceptibility to illness with the utilization of internal or external health-related information. SSD AND PERCEIVED SUSCEPTIBILITY TO ILLNESS 36

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APPENDIX A. DEMOGRAPHICS SURVEY

1. ID: ______

2. What is the highest level of education you have?

o Did not finish High School

o High School Diploma or GED

o Associates Degree (2-year degree)

o Vocational Degree

o Some College

o Bachelor’s Degree (4-year degree)

o Graduate Degree (Masters, Ph.D., JD, MD, etc.)

o Other (Please Specify): ______

3. Age: ______

4. Gender:

o Male

o Female

o Other (please specify): ______

5. Racial or ethnic group(s) you most identify with (check all that apply):

o Black or African American

o Asian or Asian American or Pacific Islander

o White, Anglo, European American

o Native American or American Indian

o Hispanic or Latino SSD AND PERCEIVED SUSCEPTIBILITY TO ILLNESS 47

o Other (please specify): ______

6. What is your relationship status?

o Single

o Married

o Divorced

o Widowed

o Other (please specify): ______

7. What area do you live in?

o Rural area

o Suburban area

o Urban area

o Other (please specify): ______

8. What is your households estimated yearly income?

o Less than $10,000

o $10,000 to $14,999

o $15,000 to $24,999

o $25,000 to $34,999

o $35,000 to $49,999

o $50,000 to $74,999

o $75,000 to $99,999

o $100,000 to $149,999

o $150,000 to $199,999

o $200,000 or more SSD AND PERCEIVED SUSCEPTIBILITY TO ILLNESS 48

9. Have you ever been diagnosed with any psychological disorders (e.g. , major depressive disorder, , etc.)

o No

o Yes (Please specify disorder(s)) ______

10. Please list any medication that you are currently taking. Include prescribed, non-prescribed, vitamins, and supplements.

11. Medical History

Have you ever been WHEN (year) were Do you CURRENTLY diagnosed with… you diagnosed with… suffer from…

1.Diabetes o YES o YES

o NO o NO

2.High blood pressure o YES o YES

o NO o NO

3.High cholesterol o YES o YES

o NO o NO

4.Hypothyroidism o YES o YES

o NO o NO

5.Goiter o YES o YES

o NO o NO

6.Cancer (type) ______o YES o YES

o NO o NO SSD AND PERCEIVED SUSCEPTIBILITY TO ILLNESS 49

7.Leukemia o YES o YES

o NO o NO

8.Psoriasis o YES o YES

o NO o NO

9.Angina o YES o YES

o NO o NO

10.Heart problems o YES o YES

(specify): ______o NO o NO

11.Heart murmur o YES o YES

o NO o NO

12.Asthma o YES o YES

o NO o NO

13.Emphysema o YES o YES

o NO o NO

14.Stroke o YES o YES

o NO o NO

15.Epilepsy o YES o YES

o NO o NO

16.Kidney disease o YES o YES

o NO o NO

17.Kidney stones o YES o YES

o NO o NO

18.Crohn’s disease o YES o YES SSD AND PERCEIVED SUSCEPTIBILITY TO ILLNESS 50

o NO o NO

19.Colitis o YES o YES

o NO o NO

20.Anemia o YES o YES

o NO o NO

21.Jaundice o YES o YES

o NO o NO

22.Hepatitis o YES o YES

o NO o NO

23.Stomach or peptic ulcer o YES o YES

o NO o NO

24.Rheumatic fever o YES o YES

o NO o NO

25.Tuberculosis o YES o YES

o NO o NO

26.HIV/AIDS o YES o YES

o NO o NO

27.Chronic Inflammation o YES o YES

o NO o NO

28.Obesity o YES o YES

o NO o NO

29.Cardiovascular disease o YES o YES

o NO o NO SSD AND PERCEIVED SUSCEPTIBILITY TO ILLNESS 51

30.Arthritis o YES o YES

o NO o NO

31.Eye disorders o YES o YES

o NO o NO

32.Infections o YES o YES

o NO o NO

33. Migraine o YES o YES

o NO o NO

34.Common cold and flu o YES o YES

o NO o NO

35.Gout o YES o YES

o NO o NO

36.Alzheimer’s disease o YES o YES

o NO o NO

37.Stroke o YES o YES

o NO o NO

38.Heart Attack o YES o YES

o NO o NO

39. Allergies o YES o YES

o NO o NO

40.Other o YES o YES

o NO o NO SSD AND PERCEIVED SUSCEPTIBILITY TO ILLNESS 52

12. Have you ever been diagnosed with any mental disorders? a) Yes

i) Please list diagnoses: ______b) No

13. Chronic Inflammation Symptoms

i. Do you suffer from leaky gut syndrome?

a. Yes

b. No

ii. In the past month, how often have you felt fatigued?

a. Never

b. Rarely

c. Sometimes

d. Often

e. Very often iii. In the past month, how often have you experienced body aches?

a. Never

b. Rarely

c. Sometimes

d. Often

e. Very often iv. In the past month, have you suffered from any skin problems (e.g. acne, psoriasis,

eczema, etc.)?

a. Yes SSD AND PERCEIVED SUSCEPTIBILITY TO ILLNESS 53

i. Please specify skin problem(s): ______

b. No

v. In the past month, have you suffered from any digestive problems (e,g, bloating, gas,

diarrhea, constipation, etc.)

a. Yes

i. Please specify digestive problem(s): ______

b. No

14. Chronic Inflammation Risk Factors

i. Stress (Perceived Stress Scale – 4)

a. The questions in this scale ask you about your feelings and thoughts during THE

LAST MONTH. In each case, please indicate your response by selecting the

answer representing HOW OFTEN you felt or thought a certain way.

i. In the last month, how often have you felt that you were unable to control

the important things in your life?

1. Never

2. Almost never

3. Sometimes

4. Fairly often

5. Very often

ii. In the last month, how often have you felt confident about your ability to

handle your personal problems?

1. Never

2. Almost never SSD AND PERCEIVED SUSCEPTIBILITY TO ILLNESS 54

3. Sometimes

4. Fairly often

5. Often

iii. In the last month, how often have you felt that things were going your

way?

1. Never

2. Almost never

3. Sometimes

4. Fairly often

5. Often

iv. In the last month, how often have you felt difficulties were piling up so

high that you could not overcome them?

1. Never

2. Almost never

3. Sometimes

4. Fairly often

5. Often

ii. What is your current weight? ______iii. What is your current height? ______iv. On average, how many times a week do you exercise?

a. 0

b. 1-2

c. 3-4 SSD AND PERCEIVED SUSCEPTIBILITY TO ILLNESS 55

d. 5-6

e. 7 or more SSD AND PERCEIVED SUSCEPTIBILITY TO ILLNESS 56

APPENDIX B. PATIENT HEALTH QUESTIONNAIRE - 15 (PHQ-15)

During the past four weeks, how much have you Not bothered Bothered a Bothered a been bothered by any of the following problems? at all little lot

1. Stomach pain

2. Back pain

3. Pain in your arms or legs or other joints

4. Menstrual cramps or other problems with your periods (women only)

5. Headaches

6. Chest Pain

7. Dizziness

8. Fainting spells

9. Feeling your heart pound or race

10. Shortness of breath

11. Pain or problems during sexual intercourse

12. Constipation, loose bowels, or diarrhea

13. Nausea, gas, or indigestion

14. Feeling tired, or having low energy

15. Trouble sleeping SSD AND PERCEIVED SUSCEPTIBILITY TO ILLNESS 57

16. Have you experienced one (or o Yes more) of the above-mentioned physical o No complaints for more than SIX

MONTHS?

17. During the last SIX MONTHS (or Never Very Rarely Often Very Always more), how often have you experienced Rarely Often these physical complaints?

o o o o o o SSD AND PERCEIVED SUSCEPTIBILITY TO ILLNESS 58

APPENDIX C. SOMATIC SYMPTOM DISORDER - B CRITERIA SCALE (SSD-12)

Almost everyone suffers from physical complaints such as headaches, back pain, nausea, or palpitations. The following statements are about your thoughts and feelings about these physical complaints and how you deal with these types of complaints. For each of these statements please select the answer that most applies to you. There are no right or wrong answers.

Items Never Rarely Sometimes Often Very

often

1. I think that my physical symptoms are      signs of a serious illness

2. I am very worried about my health.     

3. My health concerns hinder me in everyday      life

4. I am convinced that my symptoms are      serious

5. My symptoms scare me     

6. My physical complaints occupy me for      most of the day

7. Others tell me that my physical problems      are not serious

8. I'm worried that my physical complaints      will never stop SSD AND PERCEIVED SUSCEPTIBILITY TO ILLNESS 59

9. My worries about my health take my      energy

10. I think that doctors do not take my      physical complaints seriously

11. I am worried that my physical symptoms      will continue into the future

12. Due to my physical complaints, I have      poor concentration on other things SSD AND PERCEIVED SUSCEPTIBILITY TO ILLNESS 60

APPENDIX D. TREATMENT SEEKING FREQUENCY

The following questionnaire asks about your utilization of different health care services in the past SIX MONTHS. Please indicate if you have utilized any of the health care services mentioned below in the past SIX MONTHS.

In the past SIX MONTHS, have you visited a … How many times have

you visited a …

Primary care physician/GP  YES

 NO

Nurse practitioner  YES

 NO

Dermatologist  YES

 NO

Psychiatrist  YES

 NO

Cardiologist  YES

 NO

Physiotherapist  YES

 NO

Occupational medical physician  YES

 NO

Psychotherapist/Psychologist  YES SSD AND PERCEIVED SUSCEPTIBILITY TO ILLNESS 61

 NO

Osteopath  YES

 NO

Allergist/Immunologist  YES

 NO

Endocrinologist  YES

 NO

Gastroenterologist  YES

 NO

Gynecologist  YES

 NO

Urologist  YES

 NO

Surgeon  YES

 NO

Rheumatologist  YES

 NO

Radiologist  YES

 NO

Pulmonologist  YES

 NO

Otolaryngologist  YES SSD AND PERCEIVED SUSCEPTIBILITY TO ILLNESS 62

 NO

Orthopedist  YES

 NO

Ophthalmologist  YES

 NO

Oncologist  YES

 NO

Neurologist  YES

 NO

Other medical providers  YES

 NO SSD AND PERCEIVED SUSCEPTIBILITY TO ILLNESS 63

APPENDIX E. MOOD SCALE

Below is a list of words that describe feelings people have. Please CIRCLE THE NUMBER

THAT BEST DESCRIBES HOW YOU FEEL RIGHT NOW.

Not at all A little Moderately Quite a lot Extremely

Nervous 0 1 2 3 4

Relaxed 0 1 2 3 4 SSD AND PERCEIVED SUSCEPTIBILITY TO ILLNESS 64

APPENDIX F. ABSOLUTE RISK RATING FORM (ARRF)

The following questionnaire asks you to rate the probability of a number of illnesses happening to you IN YOUR LIFETIME. That is, estimate how likely it is that each of these illnesses will happen to you, yourself, at some point in the future. Base your estimates on the following rating scale.

0. No Chance

1. Very Unlikely

2. Unlikely

3. About Equally Likely to Happen or Not Happen

4. Likely

5. Very Likely

6. Certain

Place a number from 0-6 in the blank next to the following items. This number represents your idea of how likely it is that each of these illnesses will happen to you at some point in your life.

Illness Rating

1. Chronic Inflammation

2. Weight gain

3. Cardiovascular disease

4. Heart attack

5. Heart disease SSD AND PERCEIVED SUSCEPTIBILITY TO ILLNESS 65

6. High blood pressure

7. Lung Cancer

8. Cancer

9. Arthritis

10. Joint Pain

11.Allergies

12. Eye disorders

13. Asthma

14. Diabetes

15. Colitis

16. Crohn’s disease

17. Infections

18. Migraine headaches

19. Common cold and flu

20. Gout

21. Alzheimer’s disease

22. Stroke SSD AND PERCEIVED SUSCEPTIBILITY TO ILLNESS 66

APPENDIX G. TREATMENT SEEKING INTENT RATING FORM

The following questionnaire asks you to rate the likelihood the you will seek out medical assessment and/or treatment for a number of illnesses. Base your estimates on the following rating scale.

0. No Chance

1. Very Unlikely

2. Unlikely

3. About Equally Likely to Seek Out Treatment/Assessment or Not to Seek Out

Treatment/Assessment

4. Likely

5. Very Likely

6. Certain

Place a number from 0-6 in the blank next to the following items. This number represents your idea of how likely it is that you will seek out medical assessment and/or treatment for these conditions:

Illness Rating

1. Chronic Inflammation

2. Weight gain

3. Cardiovascular disease

4. Heart attack SSD AND PERCEIVED SUSCEPTIBILITY TO ILLNESS 67

5. Heart disease

6. High blood pressure

7. Lung Cancer

8. Cancer

9. Arthritis

10. Joint Pain

11.Allergies

12. Eye disorders

13. Asthma

14. Diabetes

15. Colitis

16. Crohn’s disease

17. Infections

18. Migraine headaches

19. Common cold and flu

20. Gout

21. Alzheimer’s disease

22. Stroke SSD AND PERCEIVED SUSCEPTIBILITY TO ILLNESS 68

APPENDIX H. HSRB APPROVAL SSD AND PERCEIVED SUSCEPTIBILITY TO ILLNESS 69

APPENDIX I. TABLES

Table 1. Demographic characteristics of overall sample and of video condition

Overall Nature video Chronic inflammation Pearson Chi-Square

Sample group video group Test

(N = 358) (N = 180) (N = 178)

N % N % N % χ² df p

Sex Female 221 61.7 116 64.4 105 59 2.27 2 .32

Race 6.10 5 .30

Black or 28 7.8 16 8.9 12 6.7

African

American

Asian or 19 5.3 7 3.9 12 6.7

Asian

American or

Pacific

Islander

White, 285 79.6 146 81.1 139 78.1

Anglo,

European

American SSD AND PERCEIVED SUSCEPTIBILITY TO ILLNESS 70

Native 3 .8 n/a n/a 3 1.7

American

Hispanic or 19 5.3 10 5.6 9 5.1

Latina

Mixed 4 1.1 1 .6 3 1.7

Education 7.99 6 .24

Did not 4 1.1 1 .6 3 1.7

finish high

school

High school 52 14.5 27 15.0 25 14.0

diploma or

GED

Associates 45 12.6 30 16.7 15 8.4

Degree (2-

year degree)

Vocational 16 4.5 7 3.9 9 5.1

Degree

Some 62 17.3 30 26.7 32 18.0

College

Bachelor’s 133 37.2 60 33.3 73 41.0

Degree (4-

year degree) SSD AND PERCEIVED SUSCEPTIBILITY TO ILLNESS 71

Graduate 46 12.8 25 13.9 21 11.8

Degree

Relationship 1.34 4 .67

Status

Single 137 38.3 71 39.4 66 37.1

Married 163 45.5 85 47.2 78 43.8

Divorced 42 11.7 18 10.0 24 13.5

Widowed 5 1.4 2 1.1 3 1.7

Other 11 3.1 4 2.2 7 3.9

Living Area 2.32 3 .51

Rural 90 25.1 42 23.3 48 27.0

Urban 95 26.5 46 25.6 49 27.5

Suburban 172 48.0 92 51.1 80 44.9

Other 1 .3 n/a n/a 1 .6

Income 7.06 9 .63

Less than 19 5.3 9 5.0 10 5.6

$10,000

$10,000 to 33 9.2 10 5.6 23 12.9

$19,999 SSD AND PERCEIVED SUSCEPTIBILITY TO ILLNESS 72

$20,000 to 49 13.7 23 12.8 26 14.6

$29,999

$30,000 to 52 14.5 29 16.1 23 12.9

$39,999

$40,000 to 51 14.2 28 15.6 23 12.9

$54,999

$55,000 to 48 13.4 26 14.4 22 12.4

$69,999

$70,000 to 33 9.2 17 9.4 16 9.0

$84,999

$85,000 to 23 6.4 12 6.7 11 6.2

$99,999

$100,000 to 32 8.9 17 9.4 15 8.4

$149,999

More than 18 5.0 9 5.0 9 5.1

$150,000 SSD AND PERCEIVED SUSCEPTIBILITY TO ILLNESS 73

History of 117 32.6 61 33.8 56 31.4 .24 1 .65

Mental

Health

Conditions

Types of

Mental

Health

Conditions

(history)

Depression 78 21.8 38 21.1 40 22.5 .10 1 .76

Anxiety 72 20.1 39 21.7 33 18.5 .55 1 .46

disorder

ADHD 7 2.0 3 1.7 4 2.2 .16 1 .69

PTSD 23 6.4 11 6.1 12 6.7 .06 1 .81

Bipolar 10 2.8 4 2.2 6 3.4 .44 1 .51

Other 8 2.2 2 1.1 6 3.3 2.09 1 .15

Independent t-

test SSD AND PERCEIVED SUSCEPTIBILITY TO ILLNESS 74

M SD M SD M SD t df p

Age 41.12 13.24 40.86 12.85 41.39 13.65 .376 356 .71

Note. ADHD = Attention Deficit/Hyperactivity Disorder; PTSD = Post Traumatic Stress

Disorder; Bipolar = Bipolar Disorder (Type I and II) SSD AND PERCEIVED SUSCEPTIBILITY TO ILLNESS 75

Table 2. Video condition differences on pre-video study variables

Chronic

inflammation video

Nature video group group

(N = 180) (N = 178) Independent t-test

M SD M SD t (356) p

Somatic symptom 21.25 5.18 22.24 5.66 - 1.73 .09 distress (PHQ-15)

Psychological aspects 25.00 9.57 25.99 9.48 - .99 .32 of SSD (SSD-12)

Mood-Nervous (pre) 1.71 1.07 1.58 . 91 1.20 .23

Mood-Relaxed (pre) 3.19 1.23 3.31 1.19 - .89 .37

Treatment seeking 3.70 5.82 3.10 5.22 1.03 .30 frequency

Pearson

Chi Square

N % N % Test

χ² (1) p

Persistence of 84 46.6% 81 45.5% .05 .83 somatic symptoms

SSD features 65 36.1% 65 36.5% .01 1

Note. PHQ-15 = Patient Health Questionnaire – 15; SSD-12 = Somatic Symptom Disorder B

Criteria Scale -12; SSD = Somatic Symptom Disorder SSD AND PERCEIVED SUSCEPTIBILITY TO ILLNESS 76

Table 3. Video condition differences on number of diagnosed illnesses, chronic inflammation symptoms and risk factors

Chronic

Nature video inflammation Independent t-

group video group test

M SD M SD t (356) p

1. BMI 27.95 6.85 26.96 6.88 -1.37 .17

2. Exercise (times/per week) 2.67 1.02 2.68 1.04 .07 .95

3. Stress 9.98 3.71 9.92 3.63 -.17 .86

4. Chronic Inflammation 1.12 1.17 1.08 1.16 -.31 .76

Symptoms

5. Number of diagnosed illnesses 2.77 2.45 2.82 2.38 .21 .83

Note. BMI = Body Mass Index SSD AND PERCEIVED SUSCEPTIBILITY TO ILLNESS 77

Table 4. Demographic characteristics of participants with and without SSD features

with SSD features without features Pearson Chi-Square

group SSD group Test

(N = 130) (N = 228)

N % N % χ² df p

Sex Female 86 66.9 134 58.8 2.76 2 .25

Race 8.37 5 .14

Black or 9 6.9 19 8.3

African

American

Asian or 4 3.1 15 6.6

Asian

American or

Pacific

Islander

White, Anglo, 111 85.4 174 76.3

European

American

Native 2 1.5 1 .4

American

Hispanic or 4 3.1 15 6.6

Latina SSD AND PERCEIVED SUSCEPTIBILITY TO ILLNESS 78

Mixed n/a n/a 4 1.8

Education 6.10 6 .41

Did not finish 1 .8 3 1.3

high school

High school 18 13.8 34 14.9

diploma or

GED

Associates 19 14.6 26 11.4

Degree (2-

year degree)

Vocational 9 6.9 7 3.1

Degree

Some College 19 14.6 43 18.9

Bachelor’s 51 39.2 82 36.0

Degree (4-

year degree)

Graduate 13 10 33 14.5

Degree

Relationship 4.14 4 .39

Status

Single 46 35.4 91 39.9

Married 63 48.5 100 43.9

Divorced 16 12.3 26 11.4 SSD AND PERCEIVED SUSCEPTIBILITY TO ILLNESS 79

Widowed n/a n/a 5 2.2

Other 5 3.8 6 2.6

Living Area 3.09 3 .38

Rural 39 30 51 22.4

Urban 33 25.4 62 27.2

Suburban 58 44.6 114 50.0

Other n/a n/a 1 .4

Income 15.07 9 .09

Less than 12 9.2 7 3.1

$10,000

$10,000 to 13 10.0 20 8.8

$19,999

$20,000 to 13 10.0 36 15.8

$29,999

$30,000 to 24 18.5 28 12.3

$39,999

$40,000 to 22 16.9 29 12.7

$54,999 SSD AND PERCEIVED SUSCEPTIBILITY TO ILLNESS 80

$55,000 to 15 11.5 33 14.5

$69,999

$70,000 to 10 7.7 23 10.1

$84,999

$85,000 to 5 3.8 18 7.9

$99,999

$100,000 to 11 8.5 21 9.2

$149,999

More than 5 3.8 13 5.7

$150,000

History of 62 48.5 54 23.7 23.10 1 < .001

Mental

Health

Conditions

Types of

Mental

Health SSD AND PERCEIVED SUSCEPTIBILITY TO ILLNESS 81

Conditions

(history)

Depression 43 33.1 35 15.4 15.27 1 < .001

Anxiety 39 30.0 33 14.5 12.42 1 < .001

disorder

ADHD 3 2.3 4 1.8 .13 1 .72

PTSD 13 10.0 10 4.4 4.34 1 .04

Bipolar 3 2.3 7 3.1 .18 1 .67

Other 6 4.6 2 .88 5.30 1 .02

Independent t-test

M SD M SD t df p

Age 40.68 13.51 41.38 13.11 .48 356 .63

Note. ADHD = Attention Deficit/Hyperactivity Disorder; PTSD = Post Traumatic Stress

Disorder; Bipolar = Bipolar Disorder (Type I and II) SSD AND PERCEIVED SUSCEPTIBILITY TO ILLNESS 82

Table 5. Differences in number of diagnosed illnesses, chronic inflammation symptoms and risk factors between participants with SSD and without SSD features

with SSD features without features SSD

group group

(n = 130) (n = 228) Independent t-test

M SD M SD t (356) p

1. BMI 27.78 7.01 27.34 6.82 -.44 .66

2. Exercise (times/per 2.58 1.06 2.73 1.02 1.37 .17 week)

3. Stress 11.48 3.62 9.08 3.41 -6.26 < .001

4. Chronic 1.88 1.15 .65 .92 -11.01 < .001

Inflammation

Symptoms

5. Number of diagnosed 3.80 2.73 2.22 2.00 -6.27 < .001 illnesses

6. Treatment seeking 4.44 6.24 2.81 5.00 -2.70 .007 frequency

Note. BMI = Body Mass Index SSD AND PERCEIVED SUSCEPTIBILITY TO ILLNESS 83

Table 6. Descriptive statistics for pre- and post-video mood based on video condition

Chronic inflammation video group Nature video group

pre-video post-video pre-video post-video

Mood M SD M SD M SD M SD

Nervous 1.58 .91 1.78 1.04 1.71 1.07 1.40 .84

Relaxed 3.31 1.19 2.96 1.23 3.19 1.23 3.75 1.14 SSD AND PERCEIVED SUSCEPTIBILITY TO ILLNESS 84

Table 7. Post-hoc comparisons for the interaction between video condition and time on the

Nervousness scale

Independent t-test for pre-video differences Independent t-test for post-video between video conditions differences between video conditions t df p t df p

1.20 356 .23 -3.79 356 <.001

Paired t-test for pre-post differences within groups

Chronic inflammation video group Nature video group t df p t df p

3.58 177 <.001 5.71 179 <.001 SSD AND PERCEIVED SUSCEPTIBILITY TO ILLNESS 85

Table 8. Post-hoc comparisons for the interaction between video condition and time on the

Relaxation scale

Independent t-test for pre-video differences Independent t-test for post-video between video groups differences between video groups t df p t df p

-.89 356 .37 6.27 356 <.001

Paired t-test for pre-post differences within groups

Chronic inflammation video group Nature video group t df p t df p

5.63 177 . <.001 9.76 179 <.001 SSD AND PERCEIVED SUSCEPTIBILITY TO ILLNESS 86

Table 9. Descriptive statistics for mood based on video condition and SSD features

Chronic inflammation video group

with SSD features without SSD features

pre-video post-video pre-video post-video

Mood M SD M SD M SD M SD

Nervous 1.91 1.07 2.05 1.19 1.39 .76 1.63 .92

Relaxed 2.98 1.13 2.63 1.18 3.50 1.19 3.15 1.23

Nature video group

with SSD features without SSD features

pre-video post-video pre-video post-video

Mood M SD M SD M SD M SD

Nervous 2.03 1.18 1.46 .92 1.52 .95 1.37 .79

Relaxed 2.69 1.26 3.58 1.19 3.48 1.13 3.84 1.10 SSD AND PERCEIVED SUSCEPTIBILITY TO ILLNESS 87

Table 10. Post-hoc comparisons for the interaction between video condition, SSD features, and time on the Nervousness scale with SSD features

Independent t-test for pre-video Independent t-test for post-video differences between video groups differences between video groups t df p t df p

.62 128 .54 -3.13 128 .002

Paired t-test for pre-post differences within groups

Chronic inflammation video group Nature video group t df p t df p

-1.32 64 .19 5.54 64 <.001

without SSD features

Independent t-test for pre-video Independent t-test for post-video differences between video groups differences between video groups t df p t df p

1.15 226 .25 2.30 226 .02

Paired t-test for pre-post differences within groups SSD AND PERCEIVED SUSCEPTIBILITY TO ILLNESS 88

Chronic inflammation video group Nature video group t df p t df p

-3.64 112 <.001 2.79 114 .006 SSD AND PERCEIVED SUSCEPTIBILITY TO ILLNESS 89

Table 11. Post-hoc comparisons for the interaction between video condition, SSD features, and time on the Relaxation scale

with SSD features

Independent t-test for pre-video Independent t-test for post-video differences differences t df p t df p

-1.39 128 .17 4.57 128 <.001

Paired t-test for pre-post differences within groups

Chronic inflammation video group Nature video group t df p t df p

3.49 64 .001 -8.65 64 <.001

without SSD features

Independent t-test for pre-video Independent t-test for post-video differences differences t df p t df p

-.11 226 .91 4.47 226 <.001

Paired t-test for pre-post differences within groups SSD AND PERCEIVED SUSCEPTIBILITY TO ILLNESS 90

Chronic inflammation video group Nature video group t df p t df p

4.41 112 <.001 -6.00 114 <.001 SSD AND PERCEIVED SUSCEPTIBILITY TO ILLNESS 91

Table 12. Correlations between chronic inflammation risk factors and symptoms, number of diagnosed illnesses, perceived susceptibility to illness, and treatment seeking intent (chronic inflammation video group)

1 2 3 4 5 6 7

1. Stress -

2. BMI .07 -

3. Exercise -.28** -.15* -

4. Chronic inflammation .45** .13 -.13 - symptoms

5. Number of diagnosed .22** .21** -.03 .42** - illnesses

6. Perceived susceptibility .22** .14 -.08 .37** .42** - to illness

7. Treatment seeking intent -.03 .07 -.004 .17* .13 .44** -

Note. BMI = Body Mass Index

* p < .05, ** p < .01 SSD AND PERCEIVED SUSCEPTIBILITY TO ILLNESS 92

Table 13. Correlations between chronic inflammation risk factors and symptoms, number of diagnosed illnesses, perceived susceptibility to illness, and treatment seeking intent (nature video group)

1 2 3 4 5 6 7

1. Stress -

2. BMI .03 -

3. Exercise .01 -.26** -

4. Chronic inflammation .41** .13 .19* - symptoms

5. Number of diagnosed .06 .27** -.17* .36** - illnesses

6. Perceived susceptibility .37** .12 -.13 .36** .34** - to illness

7. Treatment seeking intent .13 .05 -.05 .14 .21** .49** -

Note. BMI = Body Mass Index

* p < .05, ** p < .01 SSD AND PERCEIVED SUSCEPTIBILITY TO ILLNESS 93

APPENDIX J. FIGURES

154

132

110

88

66

44

22 Chronic Inflammation Video Group Nature Video Group

with SSD without SSD

Figure 1. Nonsignificant interaction between video condition and SSD features on perceived

susceptibility to illness SSD AND PERCEIVED SUSCEPTIBILITY TO ILLNESS 94

154

132

110

88

66

44

22 Chronic Inflammation Video Group Nature Video Group

with SSD without SSD

Figure 2. Nonsignificant interaction between video condition and SSD features on treatment

seeking intent SSD AND PERCEIVED SUSCEPTIBILITY TO ILLNESS 95

with SSD features without SSD features 4 4

3 3

2 2

1 1

0 0 Nervousness Pre-Test Nervousness Post-Test Nervousness Pre-Test Nervousness Post-Test

Chronic Inflammation Video Group Chronic Inflammation Video Group Nature Video Group Nature Video Group

Figure 3. Significant interaction between video condition, SSD features, and time on the

Nervousness scale SSD AND PERCEIVED SUSCEPTIBILITY TO ILLNESS 96

with SSD without SSD 4 4

3 3

2 2

1 1

0 0 Relaxation Pre-Test Relaxation Post-Test Relaxation Pre-Test Relaxation Post-Test

Chronic Inflammation Video Group Chronic Inflammation Video Group Nature Video Group Nature Video Group

Figure 4. Significant interaction between video condition, SSD features, and time on the

Relaxation scale