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Examining Recruitment Methods for College Women At-Risk for Eating Disorders and the Relationship between Exercise and E...


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EXAMINING RECRUITMENT METHODS FOR COLLEGE WOMEN AT-RISK FOR EATING DISORDERS AND THE RELATI ONSHIP BETWEEN EXERCISE AND EATING PATHOLOGY By BRIAN COOK A THESIS PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLOR IDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE UNIVERSITY OF FLORIDA 2006

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Copyright 2006 by Brian Cook

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This thesis is dedicated to all who have helped me succeed in my academic career.

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iv ACKNOWLEDGMENTS I thank my committee for their direction, wi sdom, and help with this thesis and guiding me through this master’s program. All of our interactions during these past three years have made an impact on me as a student a researcher, and a pe rson. All of them are excellent role models both professionally and personally. Dr. Heather Hausenblas, my committee chair, has been especially importa nt in providing assistance with my academic work and research, as well as offering timely words of encouragement that are so very much needed and appreciated. I also thank everyone at ProC hange Behaviors Systems, Inc., for providing me with the foundation to pursue my career goals. The opportunities and experi ences that I have gained while working at ProChange have b een invaluable to my development as a researcher. Most of all, I thank them for believing in my ability to succeed. Finally, I thank all of my friends and fa mily that have guided me throughout my education. I thank them all for their love and suppor t that have enabled me to pursue my education.

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v TABLE OF CONTENTS page ACKNOWLEDGMENTS.................................................................................................iv LIST OF TABLES............................................................................................................vii LIST OF FIGURES.........................................................................................................viii ABSTRACT....................................................................................................................... ix CHAPTER 1 INTRODUCTION........................................................................................................1 2 LITERATURE REVIEW.............................................................................................7 General Overview.........................................................................................................7 Etiology....................................................................................................................... 11 Stage One.............................................................................................................11 Stage Two............................................................................................................12 Stage Three..........................................................................................................12 Prevalence...................................................................................................................14 Prevention...................................................................................................................17 Recruitment.................................................................................................................20 Exercise and Eating Disorders....................................................................................24 3 METHODS.................................................................................................................28 Participants.................................................................................................................28 Measures.....................................................................................................................28 Demographic Questionnaire................................................................................28 Drive for Thinness Subscale................................................................................28 Exercise Dependence Scale ................................................................................29 Body composition................................................................................................29 Leisure-time Exercise Questionnaire .................................................................29 Procedure....................................................................................................................30 Primary Purpose..........................................................................................................32 Eligibility Criteria................................................................................................32 Data Analysis.......................................................................................................32 Secondary Purpose......................................................................................................33

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vi 4 RESULTS...................................................................................................................35 Response Rate.............................................................................................................35 Primary Purpose..........................................................................................................35 Secondary Purpose......................................................................................................37 5 DISCUSSION.............................................................................................................40 Overview.....................................................................................................................40 Study Findings............................................................................................................40 Recruitment.........................................................................................................40 Mediator Effect....................................................................................................43 Limitations..................................................................................................................46 Future Directions........................................................................................................49 Conclusions.................................................................................................................51 APPENDIX A DEMOGRAPHIC QUESTIONS................................................................................52 B DRIVE FOR THINNESS QUESTIONNAIRE .........................................................53 C EXERCISE DEPENDENCE QUESTIONNAIRE.....................................................54 D LEISURE TIME EXERCISE QUESTIONNAIRE....................................................55 E STUDY ANNOUNCEMENT....................................................................................56 F REPLY WITH PIN AND INFORMED CONSENT..................................................57 G ELIGIBLE RESPONSE.............................................................................................59 H INELIGIBLE RESPONSE.........................................................................................60 LIST OF REFERENCES...................................................................................................61 BIOGRAPHICAL SKETCH.............................................................................................68

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vii LIST OF TABLES Table page 2-1 One-Year-Period Prevalence Rates per 100,000 Young Females...............................16 3-1 Thesis Timeline...........................................................................................................3 1 4-1 Means, Standard Devi ations, and Alpha Values.........................................................36 4-2 Frequency of Recruitment Method..............................................................................36

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viii LIST OF FIGURES Figure page 2-1 Etiological Model of Eating Diso rder Development and Maintenance......................14 3-1 Study Flow................................................................................................................. ..31 3-2 Relationship of Mediator Variables ............................................................................34 3-3 Relationship of Moderator Variables .........................................................................34 5-1 Moderator Model.........................................................................................................44 5-2 Mediator Model...........................................................................................................44 5-3 Conceptual Model of Mediation..................................................................................45 5-4 Conceptual Model of Medi ation with Study Variables...............................................45

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ix Abstract of Thesis Presen ted to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Master of Science EXAMINING RECRUITMENT METHODS FOR COLLEGE WOMEN AT-RISK FOR EATING DISORDERS AND THE RELATI ONSHIP BETWEEN EXERCISE AND EATING PATHOLOGY By Brian Cook May 2006 Chair: Heather Hausenblas Major Department: Applied Physiology and Kinesiology Between 10-30% of college age women are at -risk for eating disorders. This at-risk population will also be experienci ng some of the negative consequences associated with eating disorders. Prevention interventions are th erefore needed to halt development on to full blown eating pathology. Despite the fact th at prevention interventions targeting atrisk populations, such as college women, are more effective in reducing eating disorder symptoms than universal program, little res earch has examined the best methods to recruit at-risk individuals. The primary purpose of my thesis was to examine the efficaciousness of recruitment methods for i ndividuals at-risk for developing bulimia nervosa. Specifically, I examined the fo llowing two recruitment pathways: college campus announcements and announcements made via alternative delivery systems. I hypothesized that recruitment through the altern ative methods, such as the Internet and email, would produce a larger number of both total respondents and e ligible respondents.

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x Recruiting at-risk individuals allowed for the examination of behaviors believed to aid the development of eating disorders. Exercise has long been observed in this population and thought to exacerbate the progression and maintenance of eating disorders. However, little attention has been given to examining the psychological motivation for exercise in this population, t hus allowing the possibi lity of a separate variable mediating or moderating the relations hip of exercise and eating disorders. The secondary purpose of my thesis was to examine the associations among exercise behavior, drive for thinness scores, and ex ercise dependence scores. Specifically, I examined the relationship of exercise behavi or and exercise depe ndence scores on drive for thinness scores. I hypothesized that drive for thinness scor es would be more strongly influenced by exercise dependence scores than by total amount of exercise alone. The results of my study indi cated that the hypothesis of my primary purpose was not statistically supported. The results were approaching significance and may have been improved with a larger sample size. The data also indicated that alternative methods cover a substantial breadth of potential participants. The results also indicated that the hypothesis of my secondary purpose was fully supported. These results indicate that the effect of exercise on eating disorder sympto ms is mediated by exercise dependence. Future research can build upon these result s by continuing to use the advantages of new and evolving alternative technologies in the recruitment of difficult to reach populations. Through this, future research may also expand on the results of my secondary purpose by recruiting larger and more diverse samples. Because of the negative physical and psychological consequenc es of eating disorder, prevention efforts are a high research priority.

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1 CHAPTER 1 INTRODUCTION The most common psychiatric disord ers afflicting young women are eating disorders (i.e., anorexia nervosa, bulimia nervosa, & eating disorder not otherwise specified; Pritts & Susman, 2003). They are ca tegorized by a persistent and distorted view of ones own body and subsequent behavior s performed in an attempt to relieve the psychological turmoil resulting from this fa ulty self-perception. Although the morbidity rate of eating disorders in college age wo men is low (1 – 3%; Franko et al., 2005), the mortality rate is high (20% 40%; Harri s & Barraclough, 1994, 1998; Keel et al., 2003; Mehlenbeck, 2002). More alarming is that 10-3 0% of college age women are at risk for eating disorders (Cassell, 1994; Franko et al., 2005). Furthermore, serious consequences of the behaviors associated with eating diso rders may not be limited to only those with the full-syndrome disorders. Some consequences contribute to impaired health even when they are exclusive of a full-syndrome eating disorder (Pearson, Goldklang, & StriegelMoore, 2002). In other words, being at risk for these disorders may not preclude a person from experiencing their negative health impact. Treating these individuals is also difficult due to their secretive nature, which allo ws for many cases to not be recognized immediately (Fairburn, 1995; Fairburn & Cooper, 1982; Hoek, 1995; Hoek & van Hoeken, 2003). The large number of individua ls at risk for eating disord ers, and the serious health consequences experienced throughout the enti re spectrum of development, offers an opportunity and necessity to apply preventi on interventions. Eating disorder prevention

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2 has recently made great strides While early programs tended to be didactic and psychoeducational in nature, and generally did not produce much effectiveness, the latest prevention programs are interactive and have shown promising results (Stice & Shaw, 2004). Overall, the most effective prevention programs are delivered to women over the age of 15 and are interactive, multisession programs not presented as eating disorder prevention (Stice & Shaw, 2004). Following the tr aditional modes of universal education programs as prevention are not effective when applied to this health problem. Perhaps effects are lost by not selecti ng those individuals whom are at -risk and therefore the most in need. In other words, a better understandi ng and targeting of at risk populations may be a logical next step in the progression of eating disorder prevention (Stice & Shaw, 2004). Examining recruitment methods for prev ention efforts offers an opportunity to increase the impact of such interventi ons by providing the knowledge of how to efficaciously select those most in need. Recruitment is an immediate concern wh en preparing to implement an eating disorder prevention program with women. Ir onically, this should not be much of a challenge considering the pr eviously mentioned large numbers at-risk for eating disorders. For example, normal to overweight college age women are all at a higher risk for the development of eating disorder than men (Jacobi et al., 2004; Woodside et al., 2001). Recruitment efforts need to focus on finding new and more effective ways of reaching these at-risk people in need of intervention. Examining how efficaciously a recruitment strategy can contact potential par ticipants can be guide d by applying certain factors of the RE-AIM fr amework. The RE-AIM framework is a framework that addresses issues of internal and external validity of health behavior programs (Glasgow,

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3 Vogt, & Boles, 1999; Glasgow et al., 2004). For example, an effective recruitment strategy must be able to sample large nu mbers of potentially eligible and willing participants, while still being implemented in a standard and consistent fashion. Such a strategy would demonstrate the RE-AIM dimensions of R each, E ffectiveness, A doption, and I mplementation (Glasgow, Vogt, & Boles, 1999; Glasgow et al., 2004). Specifically, sampling a large number of potentially eligible participants is a recruitment strategy’s reach. Examining the number of eligible and willing participants a strategy can deliver represents its effectiveness. A strategy’s adoption would be evident by its ability to be consistently delivered through a variety of settings. Simila rly, consistently delivering a recruitment strategy in each setting is th e implementation dimension of the RE-AIM framework (Glasgow, Vogt, & Bole s, 1999; Glasgow et al., 2004). A review of the literature reveals limi ted research addressing efficacious methods of recruiting this population (Lovato et al., 1997; McDermott et al., 2003). New technologies, such as computers and the intern et, enable researchers and practitioners to reach and recruit populations that were previ ously difficult to help (Kraut et al., 2004), and offer both the researcher and particip ant numerous advantages; such as costeffectiveness, accessibility, portability, ease of use, accessibility, and convenience (Kraut et al., 2004; Myers et al., 2004). Using these advantages may be one way to increase the effectiveness of recruitment e fforts of at-risk individuals. Both risk factor and prevention research have made substantial advances in their understanding and effectiveness of intervening on this difficult population. Synthesizing relevant information from both lines of re search with new alternative technologies clarifies an opportunity to examine new methods of isolating and reaching at-risk

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4 populations. Given this collective understa nding, identifying the most efficacious methods of recruiting this population is the next logical step in the progression of better prevention efforts. Thus, the primary purpose of my thesis was to examine the efficaciousness of recruitment methods for individuals at risk for developing bulimia nervosa. Specifically, I examined two recruitment pathways: college campus announcements (in classroom settings and advertisements posted on a college campus) and announcements made via alternative delivery systems (placed on an in ternet website and a mass email sent to college students). The primary outcome meas ures of this purpose were the total number of responses to each advertisement and the to tal number of respondents who met criteria indicating being at risk for the developmen t of bulimia nervosa. I hypothesized that recruitment through the alternative methods, such as th e internet and email, would produce both a larger number of total respondents and a la rger number of eligible respondents (Kraut et al., 2004; McDerm ott et al., 2003; Myers et al., 2004). Examining recruitment methods also provi des an opportunity to collect data for other purposes because responding participants will need to complete assessments once they have inquired about a program. Adding measures of self-reported exercise and exercise dependence to risk screening assessm ents allows the possibility of questioning the role of exercise and its relationship to we ight control in terms of the development of eating pathology. The view traditionally held is that exercise may exacerbate the effects of eating pathology based on the observation th at eating disordered individuals also excessively exercising (Brewerton, Stellefs on, Hibbs, Hodges, & Cochrane, 1995; Davis, Katzman, Kaptein et al., 1997; Hglund, & Normn, 2002; Katz, 1996). More recent

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5 research reveals that exercise may not be excl usively to blame; rather there may be other moderating variables at play in this relationship (Davis et al., 1997, 1998, 1999a). Examining the relationship of exercise a nd eating pathology, a nd looking at other possible factors that may or may not be contribu ting to this relationship, is needed to help clarify these two very divergent schools of thought that currently exist. Furthermore, comparing exercise dependence data, total amoun t of exercise data, and drive for thinness data may offer insight into the distinction of primary versus secondary dependence of exercise in the context of eating disorders. In other words, examining the difference between those whom are exercising as an end in itself (primary dependence) and those whom are exercising for some other end (s econdary dependence; Hausenblas & Fallon, 2002; Hausenblas & Symons Downs, 2002). Previous research has begun to examine these relationships between exercise dependence and eating pathology. Hausenblas and Fallon (2002) found that primary exercise dependence played a marginal role in predicting body image in a sample of female undergraduate college students. Th ey recommended for future research to examine mediator and/or moderator eff ects of body image and exercise behavior. Similarly, Zmijewski and Howard (2003) f ound that exercise dependence scores in female undergraduate students were positively correlated with the Bulimia subscale of the EAT-26 (Garner & Garfinkel, 1979) and th at this subscale was also an important predictor of exercise dependence scores. Thes e results indicate that many college women may be exercising in association with a formal or subclinical eating disorder (Zmijewski & Howard, 2003). Unfortunately, these analyses stopped short of examining a potential mediating or moderating effect.

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6 Thus, the secondary purpose of my thesis was to examine the associations between exercise behavior, drive for thinness scores, and exercise dependen ce scores. Specifically, I examined the relationship of exercise beha vior and exercise depe ndence scores on drive for thinness scores. I hypothesized that drive for thinness scores (i.e. cardinal features of an eating disorder) would be more strongly influenced by exercise dependence scores than by total amount of exercise alone (Hausenblas & Fallon, 2002; Hausenblas & Symons Downs, 2002; Zm ijewski & Howard, 2003).

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7 CHAPTER 2 LITERATURE REVIEW The purposes of this chapter are to pr esent a general understanding of eating disorders and to examine the research that is relevant to this thesis. I will begin by describing eating disorders and their e tiology of acquisition, development, and maintenance. This will be followed by a brief review of the most widely accepted prevalence rates for these disorders. I will then provide a basic overview of prevention and how it is applicable to this thesis, follo wed by a review of the literature on recruiting eating disordered individuals. Finally, I will pr esent research relevant to the role of exercise and eating disorders. The research pres ented in this literatu re review will provide a sound rational for this thesis research. General Overview Anorexia nervosa and bulimia nervosa are si milar, yet distinct disorders which are the two most common eating disorders; acc ounting for two thirds of the individuals seeking treatment for eating disorders (Fai rburn & Walsh, 1995). Each is characterized by cognitive distortions regarding body image resulting in behaviors in an attempt to modify the body. The criterion for anorexia nervosa is explicitly outlined in the DSM-IV (APA, 1994) and can be generally stated as an in tense and unrealistic fear of becoming fat, engaging in behaviors intended to produce distinct weight lo ss, and amenorrhea resulting from the refusal to maintain a health weight (Garfinkel, 1995). The specific criterions are as follows. The intense fear of becoming fat experienced by anorexic s does not cause an

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8 overestimation of body part size ; rather the excessive concer n with weight and shape of the body predicates the self-esteem and affect of the person. Furthermore, simply overestimating the size of ones body or a body part is not exclusive to eati ng disorders. It is the relation of the body or body parts to the individuals’ affect which distinguishes anorexia from other disorders (Garfinkel, 1995) This disturbance of self-evaluation and consequential denial of the brevity of one’s low weight are defined in the DSM-IV (APA, 1994) as maintaining a weight that is less than 85% of what is considered an ideal body weight for the individual. This denial is phys ically evident by a physiological criterion of amenorrhea. Simply stated, this is when at least three consecutively absent menstrual cycles occur in women. Two specific types, restricting type a nd binge-eating/purging type, based on how the extreme low weight is reached and maintained, also define anorexia. The restricting type is only de fined as the absence of binging and purging behaviors. The binge-eating/ purging type states that dur ing the current episode of anorexia, the individual also engages in binges (i.e., eating ina ppropriately massive amounts of food in one set period of time) or purging behavior (i.e., self-induced vomiting, misuse of laxatives, diuretics, or enemas). The DSM-IV (APA, 1994) criteria for bu limia nervosa are similar to that of anorexia in that it too outlines an intense f ear of becoming fat, but differentiates itself by including the requirements of powerful urges to overeat and subsequent binges that are followed by engaging in some sort of purging or compensatory behavior in an attempt to avoid the fattening effects of excessive calor ic intake. Similar to anorexics, the fear experienced by bulimics is in regards to self -evaluation, thus resulting in compensatory behaviors to evade weight gain. The paradox is the presence of the uncontrollable urges

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9 to overeat. These binges are defined as occu rring within 2 hours and including an amount of food that is definitely larger than mo st people would consume in a similar time and setting and a sense of lack of control duri ng the binge (APA, 1994). Similar to anorexia, these behaviors are separated into purging t ype (self-induced vom iting, use of laxative, diuretics, enemas, or medication abuse.) and non-purging type (other compensatory behaviors such as fasting or excessively exercising). These two eating disorders present a vari ety of serious physical and psychological health consequence throughout their duration. This is extr emely relevant when one considers that up to half of the mortality rate of eating disordered persons can be attributed to cardiac complica tions and failure (Mehlenbeck, 2002) due to the weakening of the individual’s heart muscles and subs equent cardiac irregularities (Sobel, 2004). Perhaps equally as troublesome is that the c onsequences of fasting and/or starvation as a compensatory behavior in either anorexia or bulimia can result in structural abnormalities in the brain that are nonreversible; even w ith proper refeeding and nutrition. In other words, the individual experien ces malnutrition and its physio logical repercussions. Other physical symptoms attributed to improper nutrition are kidney dys function, electrolyte disturbances, dehydration, bone mineral and mass loss, and amenorrhea in anorexic women. Other compensatory behaviors in both a norexia and bulimia can also manifest themselves physically. Specifically, vomiti ng can result in enlarged parotid and submandibular glands, abdominal pain, dent al deterioration and gum disease, and gastrointestinal problems such as rupture. It is also ironic that some consequences of the attempts to control one’s bodily appearance such as scaring of the hands due to acid burn

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10 marks from self-induced vomiting, easy bruisi ng, a compromised ability to heal wounds, breast atrophy, dry and crack ing skin, lanugo, and yellowing of the skin due to hypercartotenemia are generally related to idea ls of beauty. All of the resulting physical deficits for all forms of compensatory beha viors listed above are the body’s attempt to shut down nonessential systems in an a ttempt for survival (Sobel, 2004). The physical consequences of eating disord ers are severe, and in some cases life threatening, but the psychological consequen ces present equal grav ity. Converse to the previously mentioned cardiac complications bei ng responsible for up to half of all deaths, suicide resulting from negative psychologica l consequences may be responsible for the other half of the mortality rate (Meh lenbeck, 2002). Specifically, depression and irrational and labile moods may contribute to th is aspect of mortality. Other less extreme but still serious psychological consequences are anxiety, obsessive thoughts concerning food and weight, increased isolation, impaired judgment, low self-esteem, guilt, shame, feelings of imperfection, diminished con centration, and feelings of loss of control (Mehlenbeck, 2002; Sobel, 2004). A body-image distortion is also a psychological characteristic that is necessary for an ea ting disorder diagnosis. Suicide is the most serious implication, yet self-i njurious behaviors such as cutting, hitting, and scratching may also result from the psychological distre ss of eating disorders (Paul, Schroeter, Dahme, & Nutzinger, 2002). It should be noted that other eating diso rders, such as binge eating disorder, do exist and are categorized in the DSM-IV (A PA, 1994) as Eating Disorders Not Otherwise Specified. This literature review and the inte ntions of this thesis will only focus on the

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11 two more common and previously described di sorders of anorexia and bulimia and there spectrums of risk, development, and prevention. Etiology The examination of the etiology and preval ence of eating disorders is multifaceted and points out the methodological difficulties in identifying the development and breadth of this problem. Cooper (1995) offers an etiol ogical paradigm to consider the course of eating pathology (Figure 2-1). This etiolo gical model breaks down the process of development, progression, and maintenance of eating disorders into three distinct stages. Stage one examines the period from con ception to the emergence of behavioral precursors of the disorder, followed by stage two covering the period from the development of behavioral precursors through any precipitating factor s that may lead to the onset of the full disorder, and ending with a description of how various maintaining factors interact with protective factors and determine whether the disorder will take a transient course or become esta blished or chronic during stage three. Each of the stages is described in detail below. Stage One Stage one primarily examines risk factors that lead to the behavioral precursors of a disorder. During this time, the individual may be exposed to predisposing factors for the disorder that occur prior to onset of the diso rder and in turn increas e the person’s risk for development of the disorder. Stice (2002) conc isely organized the risk literature into a comprehensive meta-analysis and identified which risk factors are relevant to eating disorders. His meta-analysis found that several factors believed to pl ace an individual at risk were not empirically supported, while othe r lesser know factors did received support. For example, childhood sexual abuse, the role of stress, control issues, dysfunctional

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12 family systems, and deficits in parental a ffection are theorized as risk factors, yet received no empirical support in this meta-ana lysis. These findings suggest that there is not an individual, univariate relationshi p between a single ri sk factor and the development of eating disorders, but rather several factors interact to spark the development and others may be present to move a person further along the spectrum of development of pathology to diso rder. Interestingly, i ndividuals at risk in the presence of pathological behaviors and their perception of these messages may encourage further progression of eating disorders. Stice explains this by pr oposing a Perfectionism X Body Dissatisfaction X Low Self-Esteem model of development of eating disorders. This relates to Cooper’s model by explaining that individuals possessing the set of factors identified by Stice would then represen t the initial stage of eating pathology. Stage Two Most people will exhibit some known eati ng disordered risk behavior, such as fasting or restrictively dieting, and never de velop an eating disorder (Tylka, 2004; Tylka & Subich, 2002). This behavior alone does not qualify someone as having an eating disorder. The primary goal of stage two is to examine what other factors combine and interact with various known eating disorder risk factor s, which in turn, trigger progression into an eating disord er. Little research has examin ed this line of questioning. The sparse amount of existing research is lim ited in that any possibl e contributing factors have not been clearly documented. Furthermor e, it is difficult to separate those with eating disorder symptoms and those who will go on to develop the actual eating disorder. Stage Three The third stage of this model explains the course and maintenance of eating disorders by offering three views. The cogni tive view suggests th at characteristic

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13 cognitive distortions of the extreme importan ce of weight and shape explain most of the features of eating disorders. Therefore treatment efforts, such as cognitive behavioral therapy, are targeted at changing these mistak en attitudes. The second view stating that interpersonal events shape the course of an eating disorder is based on the observation that anorexics experiencing relationship and so cial changes during the course of family therapy and bulimics experiencing the same events while engaged in interpersonal therapy appear to have beneficial effects. These interpersonal events may enhance or weaken self-esteem, which then lead to c ognitive distortions being changed. The third view is physiologically based and mainly pe rtains to anorexia. It is support by the physiological changes that occur as a result of starvation. Some of these changes may then perpetuate the anorexic cycle. Cooper’s etiological view offers a ge neral understanding of how risk factors introduce, progressively facilitate the behavi oral components leading to an actual eating disorder, and maintain the course of a disorder but fails to consider that protective factors may be at work in stopping this progression in the majority of indi viduals exhibiting risk behaviors. Furthermore, much of the research examining this has used clinical samples of eating disorder patients. This type of selection bias may offer insights into a subpopulation of eating disordered individuals but not necessarily capture the true nature of eating disorders. This bias is even more of a shortcoming in the literature given that many eating disordered individuals do not seek treatment (Fairburn, 1995; Hoek, 1995) and therefore are not cap turing a sizable sub-popul ation. Other methodological considerations are that many studies do not include control groups and very few studies have attempted to examine the o ccurrence of etiological factors.

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14 Figure 2-1. Etiological Model of Eating Disorder Development and Maintenance Prevalence Most people will face socio-cultural pressures concerning weight and exhibit some risk factors over the course of a lifetime (Tylka, 2004; Tylka & Subich, 2002). Separating those who experience such f actors from those who go on to develop an actual eating disorder can be difficult. Stringent criteria fo r diagnosis have yielde d the clearest picture of how many people are suffering from actual eating disorders. Hoek (1995; Hoek & van Hoeken, 2003) offers a two-stage approach in determining the preval ence rates of eating disorders. Currently, this twostage approach is the most widely accepted approach in determining eating disorder prevalence (H oek & van Hoeken, 2003). Other approaches, such as survey methods, have yiel ded drastically different results. The first stage of Hoek's screening m odel involves administering a screening survey to large populations of those who are co nsidered to be at risk to determine the number of individuals who c ould have an eating disorder. The second stage consists of semi-structured interviews with those individua ls who are determined to potentially have an eating disorder. This type of rigorous screening and evaluation has shown the point prevalence rate for anorexia nervosa is 280 per 100,000 young females (0.28%) and the point prevalence of bulimia nervosa is 1,000 per 100,000 young females (1%; Hoek, 1995). Recent reexaminations of prevalence rates have reported similar results; 0.30% anorexia in young females and 1% bulimia in young females (Hoek & van Hoeken,

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15 2003). Results for males with eating disorders were reported as 5 -10% of clinical samples of eating disordered patients thus supporting women being at higher risk than men. The surveys used in stage one of this m odel also indicate that bulimic symptoms are present in 19% of female students. This is supported by previous research reports indicating that medical experts estimate that 16 to 30 percent of all women have practiced bulimic behaviors (Cassell, 1994). Closer examination of prevalence rates over a one-year period yields a more comprehensive view of the overall prevalence of eating disorders. Table 2-1 presents Hoek's (1995) findings. Level 0 represents the number of eati ng disordered individuals in the community. Level 1 represen ts the number of individual s considered to have an eating disorder by their primary health care physician. Level 2 represents the number of eating disordered individuals receiving outpatient or inpatient treatment. In regards to the claim that eating disorders, part icularly bulimia nervosa, are secretive in nature, (Fairburn & Cooper, 1982; Hoek, 1995) examination of the prevalence rates listed in Table 2-1 shows that only 43% of the cases of anorex ia nervosa in the co mmunity are recognized by primary care physicians and of those, 79% are referred for treatment. The secretiveness of eating disord ers becomes more apparent when you consider that only 11% of bulimics in the community were r ecognized by their primary care physician and of those, only half (51%) are referred for treatment. In other words, most eating disordered individuals do not receive ade quate treatment (Hoek & van Hoeken, 2003). Less stringent methods of prevalence eval uation yield drastically different results. For example, Kjels s, Bjrnstrm, and Gunnar Gtestam (2004) administered self-report surveys to 1987, 14 15 year old Norwegian students (1034 girls and 953 boys) in class.

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16 Prevalence rates reported from this study were 17.9% for anorexia nervosa and 0.7% for bulimia nervosa in girls and 0.2% for anorex ia nervosa and 0.4% for bulimia nervosa in boys. Interestingly, a 14.6% prev alence rate of eating disorder not other wise specified was reported for the girls. This may be consis tent with previously discussed results of 16 30 % rates of bulimic behaviors report ed in the same age group (Cassell, 1994). However, the drastic difference in anorexia nervosa prevalence rates illustrates the importance of using strict criteria such as Hoek’s two-stage model. Table 2-1. One-Year-Period Prevalence Rates per 100,000 Young Females Level of health care Anorexia Nervosa Bulimia Nervosa 0. Community 370 1,500 1. Primary Care 160 170 2. Mental Health Care 127 87 A major concern is that these prevalence rates and examination of prevalence of treatment only account for those individuals whom have developed a diagnosable eating disorder. Many others may be on their way to developing an eating di sorder, thus placing them at risk for at least some of the physic al and psychological risks stated above. Tylka and Subich (2002) found that high school and college women reported frequently skipping meals (59%), ate fewer than 1200 calories per day (36.7%), eliminated fat (30.1%) or carbohydrates from th eir diet (26.5%), fasted for more than 24 hours (25.9%), used laxatives (7.2%), used diuretics (6.6%), and vomited after meals (4.8%). Tylka and Subich concluded that these behaviors are sim ilar to clinical eating disorders but without the frequency required to be considered seriou s. This is similar to Thomsen, Weber, and Brown’s (2001, 2002) findings in a sample of high school girls who read women’s health and fitness magazines. They found a posit ive association betw een reading such

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17 magazines and frequency of unhealthy weight c ontrol behaviors; specifically taking diet pills and restricting ca loric intake. The authors also found that frequent readers of such magazines scored significantly higher on s cales of eating disordered cognition. While these results do not specifically show a relatio nship to diagnosable eating disorders, they do show a relationship to the behavior al precursors to eating disorders. Eating disorders are a serious threat to many young people’s lives that, as suggested by the differences in Hoek’s three level prevalence rates, will go unnoticed and otherwise ignored until it is much too la te. The negative physical and psychological consequences of these disorders begin to impact the individual from the onset of development. By the time an individual is diagnosed with an eati ng disorder, they are experiencing at least some of these consequences. Simply stated, the quality of these person’s lives is compromised by thoughts and behaviors that must be intervened upon. Understanding that most of individuals de veloping an eating di sorder will not be recognized or seek or be referred to trea tment raises an immediate need for improved recruiting practices in this population as well as improved prevention efforts. Furthermore, prevention of eating disorder s becomes increasingly important given the knowledge of negative behaviors such as t hose reported by Tylka and Subich (2002) and their potential for development in to more serious pathologies. Prevention If something, such as an eating disorder, can quietly affect the h ealth and lives of so many individuals, then the most prudent course of action would be to stop the problem before it begins. Perhaps then the most logical approach to dealing with eating disorders is to address the issues of primary, seconda ry, and tertiary preven tion efforts (Caplan, 1964). Several eating disorder prevention inte rventions have been conducted, mostly at

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18 the primary prevention level, producing va rying degrees of success. Many early interventions have yielded more cautious re sults, while recently reported interventions have shown the most promising effects. Iden tifying areas in need of improvement, and then continuing this progression of more e ffective prevention programs is needed to advance the efforts of previous research. Primary prevention efforts attempt to in tervene on the population as a whole and stop negative health behaviors before any signs of an illness are present. This goal is accomplished in two varying methods: reactive and proactive efforts (Catalano & Dooley, 1980). Reactive primary prevention or selective prevention (Levine & Piran, 2004) is defined as strategies that improve c oping responses and augm ent the individual’s resistances to any potentially harmful stressors It is selecting those who have not shown signs of an illness or condition, but are consid ered to be at a higher risk. For example, administering a vaccine for the measles to ch ildren would be considered reactive primary prevention. On the other hand, proactive primary prevention is defined as strategies that eliminate causal agents. Proactive primary ea ting disorder interventions typically target populations that generally have not yet begun to exhibit any behavi oral precursors to eating pathology, such as elementary school a nd middle school students. This type of prevention is also called universal or pub lic health prevention because it is often accomplished in the form of public policy or community change (Levine & Piran, 2004). Secondary, or indicated, prevention target s those individuals whom have begun to show signs of a problem but are not quite experiencing the full-blown problem or illness (Levine & Piran, 2004). Secondary prevention eating disorder inte rventions focus on known precursors, such as negative body imag e (Stice, 2002), to reduce the risk of

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19 experiencing the full-blown disorder. The tert iary level of prevention is an attempt to improve the course of a disease or minimize th e harmful effects of an illness once it has been diagnosed. In other words, it is basically a course of therapy or treatment for an illness or disorder. Cognitive behavioral therapy for diagnosed eating disordered patients is the most widely employed tertiary appro ach and has been extensively supported for use in bulimia nervosa (Fairburn, 1995; Herzog et al., 1992; Vitousek, 1995). Several studies have addressed preventing ea ting disorders at each of the previously described levels. Austin’s (2000) literature review and Stice and Shaw’s (2004) metaanalysis summarize a wide range of these studies and offer insight into the future of eating disorder prevention. Austin (2000) found that of 20 eating diso rder prevention interventions, only four reported positive behavioral changes, while 14 showed improvements in knowledge and/or attitudes towards eating disorders and concerns about weight and shape. The main reason these interventions have, for the most pa rt, failed to elicit behavioral changes is “a fundamental disjunction in the transition from theories of aetiology to theories of prevention” (Austin, 2000; p.1256) Specifically, many of the interventions focused on sociocultural risk factors of eating disorders, yet attempted to intervene by focusing at the individual level. Therefore, implementing proactive primary prevention programs similar to those commonly used in other areas of public health is the logical next step in eating disorder prevention. Interestingly, recommenda tions for the prevention of public health issues such as coronary heart disease, di abetes, osteoporosis, obe sity, and cancer (CDC, 1996; USDHHS, 1990, 1996; Seidell, 1999) overlap with recommendations in the eating disorder prevention literature (Battle & Brownell, 1996; Killen et al.,1993; Neumark-

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20 Sztainer, 1996; Smolak & Schermer, 1998) in that they all call for programs focusing on nutrition and exercise. Since Austin’s (2000) literature review of eating disorder prevention programs, there has been encouraging progress in the ev olution of eating diso rder prevention. Stice and Shaw’s (2004) meta-analysis of 51 eating disorder preventions found that preventions have undergone three generations of development. The preliminary research attempted to intervene by delivering did actic psycho-educational materials which informed general populations a bout the adverse health conseq uences of eating disorders. The second generation of inte rventions was similar in th at they were universally distributed and didactic but also included socio-cultural education. The most recent prevention programs have moved away from uni versal didactic approaches and focused on delivering interactive materi als and exercises to population that are at risk. Overall, the most effective programs reduced attitudina l risk factors and promoted healthy weight control behaviors. This is similar to Au stin’s (2000) recommendations as discussed above. In contrast to Austin’s proposed pub lic health model, Stice and Shaw (2004) recommend that programs target selected popula tions rather than universally intervene on general populations. Sp ecifically, prevention programs that were targeted, interactive, and multi-session programs all out performed universal, didactic, and single-session programs (Stice & Shaw, 2004). Recruitment Implementing a prevention program presents a unique obstacle of combining the recommendation to target sp ecific populations (Stice & Shaw, 2004) with the knowledge of which risk factors constitute these populatio ns (Stice, 2002). A general search of the literature identified articles concerned with re cruitment for a variety of other behavioral

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21 health problems. The most relevant of wh ich were included in a literature summary (Lovato et al., 1997). A much broader search of the topic of recruitment shows that the internet is a viable means of reaching large populations. A review of the eating disorder literature found that despite a sizable body of intervention and prevention research, amazingly, only one study has specifically addr essed recruiting as its primary objective. Recruitment is a basic and important issue for any study involving human participants. Lovato et al. (1997) f ound over 4000 citations between 1987 and 1995 related to recruiting individuals for a number of studies. Most provi ded anecdotal reports of recruitment efforts and little or no data to support a ny conclusions (Lovato et al., 1997). The most common strategies of recruitment reported we re: using patient registries, occupational screening, direct mail, and using the media. A more broad view of poten tial recruitment pathways leads one to question if interactive technologies could be useful in reaching problem populations. The American Psychological Association’s Board of Scientific Affairs has established an advisory group that has released a report outlining several issu es related to internet research and in doing so have provided encouraging preliminary a ccounts of the widespread reach of this technology. In the section of th is document pertaining only to recruitment, Kraut et al. (2004) identify several benefits of using the internet for recruitment including low cost, the ability to attract a large and diverse sample, and the ability for undergraduates, graduate students, and researchers at smalle r institutions to al l contribute original research. In essence, the internet has democr atized data collection (Kraut et al., 2004). Examples given include a sample of over 1.5 million completed responses collected in a four year span (Nosek, Banaji, & Gr eenwald, 2002b in Kraut et al., 2004), 40,000

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22 respondents from a link on the National Geogr aphic website (Wellman, Quan Haase, Witte, & Hampton, 2001 in Kraut et al., 2004), and over 18,500 responses from 3,300 participants recruited from an online video game over the course of 7 months (Kraut et al., 2004). Clearly the internet provides a wide r breadth over a shorter time period than previously available. Recruiting special populations, such as individuals at a ny point on the continuum of pathological eating, presents its own sp ecific challenges and therefore the common recruitment methods listed above may or may not be entirely applicable. McDermott et al. (2003) examined recruitment as part of a larger study involving anorexia nervosa relapse prevention and two similar studies treating bulimic women. Advertisements in newspapers, on radio stations, a nd posting flyers in various locations at a site in New York, Minnesota, and California were the main reported methods of recruitment. This study found that using multiple sites to recru it during shorter periods is a preferable method of recruiting versus using fewer sites and larger windows of time. While no studies report on this question sp ecifically in terms of eating disorders, several recent studies have examined interactive technologi es with eating disordered individuals. Myers et al. ( 2004) summarized the state of several altern ative delivery systems and new technologies employed in this population, including em ail, the internet, CD-ROMS, computer software, portable co mputers, and virtual reality. Possible advantages listed specifically for computer based delivery systems (email, internet, CDROM, software, etc.) were: cost-effectiveness, accessibility, portability, the possibility that they may elicit less resistance compared to face to face contact, and the ability for simply structured programs. Em ail and internet delivered programs also were found to be

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23 easier to use, have widespread and pragmatic applications, are rela tively accessible, and are very convenient for the participant. The general consensus in the literature is that these alternative methods hold a great deal of promise when applied to eating disordered populations (Myers et al., 2004) .These conclusions are supported by a meta-analysis of similar research finding that web-based inte rventions are more effective than non-webbased interventions in producing attitudinal and behavioral cha nges in a variety of health behaviors (Wantland et al, 2004). Continuing to apply new computer based technologies to the issue of recruiting pathologically eating populations may be a logical step based on the reported preliminary success (Myers et al., 2004; Wantland et al., 2004). These technologies could very easily be applied to the McDermott et al. (2003) conclusion that recruitment should focus on many sites over a short period rather than fewer sites over a long period. Commonly listed methods of recruitment such as advertisements, flyers, and announcements (Lovato et al., 1997) are only seen or h eard by individuals whom freque nt the specific location, or site, of the advertisement. Sampling captive audiences in this way is the traditional method of recruiting on college campuses for a variety of studies just as sampling inpatients is the traditi on for eating disorder research (Cooper, 1995). Both the undergraduates and the inpatients will refr esh their respective population pools at the beginning of a new semester or at new patie nt intakes. Therefore, recruiting enough of either group would require l onger windows of possible recrui tment. Alternatively, a one time only, web based or email announcement c ould be sent out to entire populations would turn each email into its own site of recruitment. In other words, it is not limited to only those who will be in class or pass by an advertisement or in inpatient care and thus

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24 would not require longer amounts of time for the eligible pool to refresh itself. In essence, this is analogous to the McDermo tt et al. (2003) recommendation of multiple sites over a short period because emails or web-based announcements can reach anyone anywhere, while the announcements and/or flyers over several semesters or the recruitment of patients at inta ke are all analogous to fewer sites over longer periods of time. Therefore, the next step in improvi ng the recruitment of pathologically eating populations is to examine the possibility of using new and alternative technologies to sample populations that are larger than were traditionally accessible. Exercise and Eating Disorders A review of the literature reveals that the relationship between exercise and eating disorders began with the observation of high levels of exercise in clinical samples, questioned if exercise somehow exacerbate s eating pathology, and has progressed to understand that there are other moderating variables involved in this relationship. Relevant research and a furthe r explanation of each of thes e views are presented below. The traditional view of the relationship between exercise and eating disorders has primarily been based on clin ical observations from th e 1960s’ and 1970’s that 65% to 75% of anorexic patients were excessively physically active at so me point during the course of their disorder (Katz, 1996). This observation has seemed to carry over to a more universal view of all eating disorders as opposed to staying exclusively aligned with anorexia. Research has followed this clinical observation and has shown that there may be some validity to this relationship. The be st evidence of this comes from research finding that strenuous exercise can suppress appetite (Riv est & Richard, 1990). Rivest and Richard conditioned rats to become accu stom to eating 3 meals per day in 8 hour intervals. Some rats were then injected with a corticotropin-releasing factor antagonist

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25 and other with saline. All of the rats were th en forced to exercise on motorized wheels for 40 mins prior to feeding. The ra ts that did not receive the co rticotropin-rele asing factor antagonist then began restricting the amount of food pellets they ate, while the other groups of rats did not. It was concluded that the physiological effects of exercise were what was suppressing the food intake of thes e rats. Research such as this is the physiological basis to show the a norectic effects of exercise. Replicating these findings in humans is difficult because forcing humans to excessively exercise would raise ethical con cerns. Still, research has focused on showing similar effects of exercise and arrived at the same conclusion that excessive exercise may contribute to eating disordered and pathological weight control behavior. For example, studies such as Hglund and No rmn (2002) examined total amount of exercise in female aerobic instructors, a group known to have high levels of total exercise. They hypothesized that high amounts of exercise, simply defined by total hours per week, would be associated with a strong focus on weight control and body shape. They also hypothesized that previous experiences of anor exia or bulimia would be more common in the high exercising group when compared to the general public of similar age and demographic characteristics. The findings of this study suggest that the first hypothesis concerning total amount of exercise was s upported by participants reporting exercise levels 1.5 – 3 times higher than that of th e same population in the general public. The high exercising group also exhibited more pat hological weight contro l behaviors and less body satisfaction compared to the low exerci sing group. The second hypothesis was also supported by 35% of participants reporting cu rrently or previously having an eating disorder.

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26 Findings such as Hglund and Normn (2002) can only make inferences based on two variables (exercise and pr esence of eating pathology). Ot her studies have examined the possibility that the high amounts of exer cise commonly seen in eating disordered individuals may be a function of some other moderating infl uence. Davis and colleagues have published several articles concluding that th is moderating effect is likely to play a role in exercise and pathologi cal weight control. In a study examining the prevalence of high exercise in an eating disordered population, Davis et al. (1997, 1999b) found that anorexia was linked to childhood physical activ ity levels that were higher compared to other children of the same age. While this alone is similar to Hglund and Normn (2002), these results indicated th at excessive exercisers also maintained more obligatory and pathological attitudes to ex ercise. This is an important result because it allows for the possibility of some other fact or interacting with the more simplistic idea of high exercise being directly related to more pathology. Subs equent studies have indeed shown this to be a likely possibility. Davis et al. (1998, 1999a) compared m easures of high exercising and moderately or not exercising inpatient s on obsessive-compulsive symptomatology. The reported results showed that the high exercising group exhibited greater obsessivecompulsive symptomatology and obsessive-com pulsive personality characteristics than the group of moderate or non-exercising i ndividuals, and that this underscores a moderating influence of physical activity. Ho wever, it was not concluded that over exercising is uniquely associated with greater obsessionality (Davis et al., 1999a). While these findings do show that there is a re lationship between obse ssionality and eating pathology, they failed to concl ude that it was the amount of exercise that influenced obsessionality. Future resear ch will advance these findings by further examining the

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27 relationship between exercise and eating pathology. Specifical ly, further examination of the mediating and/or moderating influen ce of exercise on eating pathology is recommended (Hausenblas & Fallon, 2002).

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28 CHAPTER 3 METHODS Participants Participants were 330 female college students (age 17-36, M age = 19.97, SD = 2.14). Women in this age group were chosen be cause this cohort is at greater risk for eating disorders compared to men of the same age, and incidences of eating disorders typically peak during adolescen ce to early adulthood (Jacobi et al., 2004; S tice, 2002). Most of this sample was Caucasian (67.3 %), followed by Hispanic (13.3%), African American (10.9%), and Asian (4.5%). About 29% of the participants we re in their junior year of school (28.8%), followed by freshm an (25.2%), seniors (23.0%), and sophomores (20.9%). Measures Demographic Questionnaire Participants reported their age, year in school, course of stud y, ethnicity, family income level, major in school, height, curren t weight, ideal weight, contact information, eating disorder history, weekly exercise level, and where th ey saw the advertisement for this study. (see Appendix A) Drive for Thinness Subscale The Drive for Thinness subscale of the Eating Disorder Inventory-2 (EDI-2) measures excessive concerns with dieti ng and weight preoccupa tion. This scale are measured by rating items on a 6-point Likert scale ranging from 1 (never) to 6 (always). Ratings totaling a higher score indicate gr eater endorsement of the attitudinal and

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29 behavioral correlates of eating disorders. Extensive research s upports the validity and reliability of the Drive for Thinness subscale (Garner, 1991). (see Appendix B) Exercise Dependence Scale (EDS) The EDS is a 21-item measure of exercise dependence symptoms on the following seven subscales based on the criteria for substance dependence (American Psychiatric Association [APA], 1994): To lerance (e.g., I conti nually increase my exercise frequency to achieve the desired effects/benefits), W ithdrawal Effects (e.g., I exercise to avoid feeling tense), Continuance (e.g., I exercise despite persistent physical problems), Lack of Control (e.g., I am unable to reduce how intense I exerci se), Reductions in Other Activities (e.g., I think about ex ercise when I should be concentrating on school/work), Time (e.g., I spend a lot of time exercising), and Intention (e .g., I exercise longer than I expect; Hausenblas & Symons Downs, 2002). Responses to the items are on a 6-point Likert scale ranging from 1 (never) to 6 (a lways). A lower score reveals less exercise dependence symptoms. The psychometric propert ies of this scale ar e good (Hausenblas & Symons Downs, 2002; Symons Downs, Hausenblas, & Ni gg, 2004). (see Appendix C) Body composition Body mass index (BMI) was calculated from self-reported height and weight by dividing weight (kg) by hei ght (m) squared. A BMI score of 18.5-24.9 is normal weight, 25.0 – 29.9 is overweight, and a BMI score of 30.0 or greater is obese (ACSM, 2000). There is however, a 5% error rate associated with BMI when used to estimate body fat percentage compared to 3.5% error rate of skin fold calipers (ACSM, 2000). Leisure-time Exercise Questionnaire (LTEQ) The LTEQ is a self-report of the frequency that an individual engages in strenuous, moderate, and mild bouts of exercise during a typical w eek (Godin & Shephard, 1985).

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30 Each of the subscale scores are converted in to metabolic equivalents (METS; [Mild x 3] + [Moderate x 5] + [Strenuous x 9]) and summed to provide an estimate of total METS expenditure from exercise for an average week. The LTEQ has adequate reliability and validity (Jacobs, Ainsworth, Hartman, & Leon,1993). (see Appendix D) Procedure Data Collection Participants were recruited by respondi ng to an advertisement for larger study examining an exercise program designed to improve physical appearance and body image (see appendix E). This advertisement was pos ted throughout the month of September and was identical regardless of wh ere or when it was announced in the following four ways: 1. The campus announcements were 45 announcements posted on campus bulletin boards available for posting such informa tion for students in Turlington Plaza, on the Reitz Union lawn, and on telephone poles adjacent to bus shelte rs near sorority houses. 2. The classroom announcements were made in 12 sport and fitness classes and 4 psychology classes. 3. The website announcement was placed on my.ufl.edu, which is a secure website, accessible only to university students. 4. The email announcement was sent once as part of a weekly list serve email which delivers information only to undergraduate students. Interested persons were directed to ema il a request for access to a secure website containing screening questions for inclusion in this st udy. A standard email response containing a unique personal identification num ber (PIN) and informed consent form was sent as a reply to email requests for th is study (see appendix F). At their own convenience, participants then accessed a we bsite containing the Leisure-time Exercise Questionnaire (Godin & Shephard, 1985), Driv e for Thinness subscale of the EDI-2 (Garner, 1991), the Exercise Dependence S cale (Hausenblas & Symons Downs, 2002),

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31 and demographic questions. A follow-up email repl y was sent to all participants after the data were analyzed. Individuals who met eligib ility criteria for the exercise intervention were then invited to join the program (see ap pendix G), while all others were thanked for their time and participation (see appendix H). St udy flow is presented in Figure 3-1. This study was completed over the course of one academic semester. The timeline for this study is presented in Table 3-1. Study Announcement Email Inquiry Email reply Website survey Data Analysis Follow-up Reply Figure 3-1. Study Flow Table 3-1. Thesis Timeline. September Month 1 October Month 2 November Month 3 Study Announcement X Participant Inquiry X Email Reply X Web Based Assessment X Data Analysis X Follow-up Reply X X Preparing and Reporting Results X X

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32 Primary Purpose Eligibility Criteria To obtain a targeted population of women at -risk for an eating disorder, I used the following eligibility criteria. 1. Low Active Only those participants w ho were exercising 4 or fewer times per week were selected. The total amount of exercise per week was measured by the Leisure-time Exercise Questionnaire, as well as an open ended question in the demographic section of the survey simply asking, “How many times a week do you exercise?”. The screening website allowe d for alphanumeric data entry on LTEQ questions. Through this it was found that 52 participants (15.75%) included qualitative data stating that they were reporting inappropria te physical activity, rather than exercise behavior, in the LTEQ and therefore were over reporting total weekly exercise amount. Examples of these responses are: depends, varies, walking to class, ideally once or twice, sometimes sporadically, whenever I a in the mood, and the days that I am late to class. The single exercise be havior question was chosen to determine eligibility because it was apparent that LTEQ questions were not accurately capturing the nature of exerci se in this sample. (see chapter 4 results section for statistical justif ications) The total weekly amount of exercising 4 times or less was chosen because it reflected that these indi viduals were not meeting ACSM (2000) criteria for total weekly ex ercise. Research has shown that single item measures of exercise behavior have reasonable validity (Schectman et al., 1991; Prochaska et al., 2 001; Weiss et al., 1990). 2. Drive for Thinness – Drive for Thinness scor e cutoffs of 8 or greater were chosen because this reflects the 75th percentile and theref ore indicates a risk for developing eating disorders (Garner, 1991). A score of 14 or greater, or the 91st percentile, on the Drive for Thinness w ould typically be used to indicate the potential of more serious risk of eating pathology (Garner, 1991). 3. Body Mass – Body Mass Index (BMI) scores between 18.5 and 29.9 were used as an eligibility criterion. Th is range is considered the normal to overweight range (ACSM, 2000) and was chosen because normal to overweight women are at a higher risk for the development of eating disorder (Jacobi et al., 2004). Data Analysis Measures of internal consistency were performed on the Exercise Dependence scale and the Drive for Thinness subscale. Descript ive statistics and frequencies were also performed on all relevant variables.

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33 A 4 (recruitment levels – campus an nouncements, classroom announcements, website announcement, email announcement) x 2 (eligible or ineligible) ANOVA was performed to determine if individuals meeti ng eligibility criteria were more prevalent from any of the four methods of recruitm ent examined. A one-way ANOVA was used to determine differences in self-reported exer cise from the two previously discussed questions measuring exercise behavior. Similarly, a one-way ANOVA was used to examine how responses to these questions w ould affect eligibility rates. Finally, an independent sample t test was performed to determin e if new alternative methods of recruitment gathered significantly more eligib le individuals than traditional methods of recruitment. Secondary Purpose The procedure for the secondary purpose of this thesis, examin ing the hypothesized relationship of Leisure-time Exercise scores (LTEQ), Exercise Dependence scores (EDS) and Drive for Thinness (DT) scores, wa s followed as detailed by Baron and Kenny (1986). My independent variables were LTEQ scores and EDS scores and my dependent variable was DT scores. Firs t, correlations were used to determine the relationship between the independent and dependent variab les. A significant correlation indicates a mediator effect, while a nonsignificant correl ation indicates a mode rator effect (Baron & Kenny, 1986). See figures 3-2 and 3-3.

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34 Figure 3-2 Relationship of Mediator Variables Figure 3-3 Relationship of Moderator Variables Independent Variable Moderator Variable Independent Variable X Moderator Variable Dependent Variable

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35 CHAPTER 4 RESULTS Response Rate Four hundred forty eight individuals re sponded to the announcement and sent emails indicating interest in the study. A ll 448 were sent an email reply including a personal identification number (PIN) to access the website (see appendix F). Twenty participants (4.5%) lost or misused there PI N when logging in and emailed a request for a new PIN. Eight participants (1.8%) wrote back explicitly saying they would not like to continue with the study. A total of 330 part icipants (73.7%) accesse d and completed the website questionnaires. Primary Purpose First, descriptive statistics such as mean s, standard deviations, frequencies, and alpha values, were conducted for the primar y purpose study variables. (See Tables 4-1 – 4-2.) The eligibility criterion was then calculated resulting in 87 eligible and 241 ineligible individuals. A 4 (recruitment leve ls) x 2 (eligible or ineligible) ANOVA was performed to determine if individuals meeti ng eligibility criteria were more prevalent from any of the six methods of recruitm ent examined. Two recruitment groups (“found out from a friend” and “other”) were not included in this analysis because only 2 individuals were recruited from each. No si gnificant influence of method of recruitment on eligibility was found, F (3, 319) = 1.04, p = .38. A Pearson chi-square test also revealed that the recruitment groups did not differ significantly for eligibility [ x2 (3) = 3.12, p = .37].

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36 Table 4-1 Means, Standard Deviations, and Alpha Values Variable MSD Exercise per week (single question) 2.211.71 LTEQ 36.8123.02 EDS 40.6313.09 .93 DT 6.686.00 .88 BMI 25.164.77 Age 19.972.14 Table 4-2 Frequency of Recruitment Method Announcement FrequencyPercent Ad posted on campus 123.6 Ad posted on my.ufl.edu 175.2 Classroom announcement 6720.3 From a friend 20.6 Wednesday Update email 22969.4 Other (unspecified) 20.6 Missing 10.3 Total 330100.0 A one-way ANOVA was used to determine differences in self-reported exercise from the two questions measuring exercise be havior (LTEQ and a single question). This ANOVA compared the amount of exercise re ported in the Leisure-Time Exercise Questionnaire (LTEQ) and the single que stion, “How many times a week do you exercise”. The dependent variable was frequency of exerci se reported and the independent variable was whic h question the frequency was measured by. I found that the self-reported total amount of exercise per week was signi ficantly lower when reported through a single question than by the total of strenuous and m oderate exercise measured by the LTEQ [ F (1, 647) = 207.96, p = .001]. These results al so indicated that a significant positive correlation existed between these two variables [ r = 621, p =.001]. This self-report of exercise was important in the determination of eligibility. A one way ANOVA was used to examine how responses to these questions would affect eligibility

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37 rates. The dependent variable was eligibil ity and the independent variable was which question the exercise frequency was used to determine eligibility. I found that using the single question to measure weekly exercise be havior yielded more e ligible persons than by using the LTEQ [ F (1, 647) = 207.96, p = .001]. In other words, the lower amounts of exercise reported by the singl e question indicated more inac tive, and therefore eligible, persons than did the LTEQ. Finally, an independent sample t test was performed to determine if new alternative methods of recruitment gathered significantly more eligible individuals than traditional methods of recruitment. A lternative methods were defi ned as announcements posted on the internet website and the email announcemen t. Traditional methods were defined as announcements posted on campus and announcem ents made in classrooms. The two other levels of the recruitment variable (“fr om a friend” and “other”) were excluded due to the uncertainty of where the announcem ent was originally seen. The independent variable was method of recruitment (trad itional or alternative), and the dependent variable was eligibility. The Levene’s test for equality of variance was significant [ F = 14.344, p = .01], therefore the equal va riances not assumed statisti c was used to interpret the t test. Traditional and a lternative methods of recruitm ent were not significantly different in their ability to reach eligible participants [ t (146.761) = -1.823, p = .07]. Secondary Purpose Correlations were performed between exerci se dependence scores (EDS), drive for thinness scores (DT), and Leisure-Time Exer cise Questionnaire scores (LTEQ). I found that all of the vari ables were significantly correlate d. That is LTEQ was significantly correlated with EDS scores [ r = .440, p =.001], followed by EDS and DT being significantly correlated [ r = .207, p =.001], and LTEQ being signi ficantly correlated with

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38 DT [ r = .149, p =.008]. Because LTEQ and DT score were significantly correlated and LTEQ and EDS scores were also significantl y correlated, mediation was assumed and a three-step mediation model was followed (Baron & Kenny, 1986). Furthermore, exercise and exercise dependence exhibit a temporal re lationship with exercise preceding exercise dependence (Hausenblas & Symons Downs, 2002; Symons Downs, Hausenblas, & Nigg, 2004). This is also an indication that the re lationship may potentially be that of a mediator and not a moderator (Baron & Kenny, 1986; Kreamer et al., 2001). This model outlines that three forced entry regressions must be performed. First, a simple linear regression with forced entry was performed with EDS (dependent variable) regressed on LTEQ (independent variable). Re sults of this regression show ed that higher LTEQ scores ( = .440, p = .001) resulted in higher ex ercise dependence scores [ F (1,306) = 73.38, p = .001]; with 19.3% of the variance in exercise dependence explained by LTEQ. Next, DT (dependent variable) was re gressed on LTEQ (Independent va riable). Results of this regression showed that higher LTEQ scores ( = .149, p = .008) resulted in higher drive for thinness scores [ F (1,312) = 7.12, p = .008]; with 2.2% of the variance in exercise dependence explained by LTEQ. Finally, a forced entry multiple regression was performed with DT (dependent variable ) regressed on LTEQ and EDS (independent variables). This regression found that EDS and LTEQ explai ned 4.6% of the variance in drive for thinness scores [ F (2,296) = 7.06, p = .001], with only EDS scores being a significant predictor of DT ( = .180, p = .005). For mediation to be found, the independent variable in the first regression (LTEQ) must affect the mediator (EDS). The second regression must show that the independent variable (LTEQ) must affect the dependent, or outcome, variable (D T). Finally, the third

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39 regression must show that mediator (EDS) a ffects the dependent variable (DT). If the beta of the independent variable become s non significant, then there is complete mediation (Baron & Kenny, 1986). Based on these criteria and the resu lts of these three regressions, a full mediator effect for ED S on the relationship of LTEQ and DT was found.

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40 CHAPTER 5 DISCUSSION Overview The purpose of this thesis was twofold. Firs t, the ability to effectively recruit a population of college age women dissatisfied with their body was examined. Specifically, traditional modes of recruitment, such as verbal announcements and campus postings were compared to announcements, made on newer, alternative mediums such as the internet and email. I hypothesized that these alternative channels of recruitment would produce both more interest and more indivi duals indicating potential risk for the development of eating pathology. While this hypothesis was not st atistically supported, the raw data did show that th e alternative channels of recr uitment do cover a substantial breadth of potential participants. Second, the relationship between exercise, exercise dependence, and drive for thinness was examined. I hypothesized that exercise dependence would affect the re lationship between exercise and drive for thinness. This hypothesis was fully supported. A more detail ed description of my study findings, limitations, and future research di rections are discussed below. Study Findings Recruitment The results of this study i ndicated that there is no si gnificant difference of how or where participants are recruite d on the amount of potentially at risk individuals that are reachable by each recruitment pathway. While these results are not significant statistically, they are of note practically because these results were approaching

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41 significance [ p = .07]. The relatively small sample size of this study may have contributed to these results by lowe ring the power of these analyses. Researchers concluded that recruitment e fforts should be short in duration and widespread (McDermott et al., 2003); and that alternative technologies may be a viable means of achieving these recommendations (Kraut et al., 2004; Myers et al., 2004; Nosek, Banaji, & Greenwald, 2002). This study supports both of these conclusions. The announcement of this study was short in its duration (one month) and focused on reaching a vast number of individuals. McDermo tt et al. (2003) similarly concluded that recruitment advertisements should be posted at more sites over shorter lengths of time. Each email acted as its own site, just as th e more usual sites of campus billboards and classroom announcements were there own site s. Specifically, the advertisement posted on a website acted similar to an ad posted on a campus billboard. Take for example each advertisement posted on an internet webpage (i.e. my.ufl.edu) or on campus billboards, both may have the potential for many to be in the presence of the announcement. In other words, they are more passively there for anyone to see. Accordingly, each produced a similar number of respondents (12 from ad s posted on campus, 17 from ads posted on my.ufl.edu). The difference is that the we bsite based posting was one ad, whereas the campus based postings were about 50 ads. Conversely, an in class announcement or email is proactively forced upon an individual. The differenc e to consider is the total population available to be actively advertised to. Classes are limite d to the number of students enrolled or the number of students in as many classe s that announcements can be made in. Emails, however, are limited to only the number of people a email is sent to. Each classroom, regardless of the number of students in it b ecomes one singular site with

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42 x number of potential participants. Each em ail becomes one site with one potentially potential participant (possibly more if he or she talks to others about the opportunity). This closely follows McDermott’s (2003) sugge stion of increasing the number of places that each advertisement is made. The re cruitment data from this study, while not statistically significant, does practically support Mc Dermott by the number of participants recruited via ema ils (n = 229) being almost 3.5 times larger than the number returned from in-class announcements (n = 67). A more contemporary view of social evol ution is also evident by comparing the recommendations of the literature to the findi ngs of this study (Kraut et al., 2004; Myers et al., 2004). In 1985 only 8.2% of the US population had a computer. By 2001 that number increased to 66% of the US populati on having access to a computer and 56% of Americans having access to the internet (Kraut et al., 2004) Clearly this technology is expanding exponentially and simultaneously ch anging the delivery of information to most Americans. As evident by the results of the breadth of al ternative methods of recruitment in this study, this increase in computer and internet usage is a growing resource to contact and intervene on populati ons. Simply, remaining with the status quo of sampling convenient populations such as coll ege classes, may not be keeping with the changing times. Much attention has been given to the fact that eating disorders generally develop very quietly (Fairburn & Cooper, 1982; Ho ek, 1995) and at a young age (Jacobi et al., 2004; Stice, 2002), thus making intervention difficult. Cooper (1995) outlined this by elucidating the stages of development, beginning with beha vioral precursors, transitioning into risk fact ors, and finally progressing onto full syndrome disorder.

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43 Examining new methods of effectively recr uiting potentially at -risk populations is analogous to finding new ways of interven ing at Cooper’s (1995) first stage of development. In other words, sampling a population, such as college women, that is known to show behavioral precursors (C assell, 1994; Franko et al., 2005; Tylka & Subich, 2002; Tylka, 2004) allows the opportuni ty to access and halt the development of precursors of risk that the individual ma y or may not be aware of. Alternative technologies, such as the internet, offer the possibility of reaching far more people than previously available, yet little attention has focused on exploiting the advantages of them (Kraut et al., 2004; Myers et al., 2004). Mediator Effect The secondary purpose of my thesis wa s to examine the relationship between exercise, exercise dependence, and drive for thinness. Researchers have recommended that a mediating and/or moderating relati onship of such variables be examined (Hausenblas & Fallon, 2002). Both mediators a nd moderators are type s of variables that may affect the association between two othe r variables. Both variables have been confused, mistakenly referred to, an d wrongly identified (Baron & Kenny, 1986; Kraemer et al., 2001). To help clarify, I will fi rst describe both mediators and moderators, then continue by using the variables of interest in this thesis as examples to discuss the difference of the two and why a mediator effect, but not a moderator effect, was examined. A mediator is any variable that explains the how or w hy a relationship exists, while a moderator is any variable that specifie s on whom or under whic h conditions (when) a relationship exists (Baron & Kenny, 1986; Bennet, 2000; Kraemer et al., 2001). A potentially mediating variable (exercise dependence) must be correlated to the

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44 independent variable (exerc ise) and a potentially mode rating variable (exercise dependence) must not be correlated to an i ndependent (exercise) or dependent variable (drive for thinness; See figures 5-1 and 5-2.). Put another way, a mediator is a variable that is present and correlated to the indepe ndent variable, which he lps to explain how or why the independent variable affects the depe ndent variable. A moderator is a different variable, uncorrelated to the independent or dependent variable, that when present explains to whom or when a relationship occurs. Figure 5-1 Moderator Model Figure 5-2 Mediator Model In my study, the relationship between ex ercise, as an independent variable, and drive for thinness, as an outcome or depende nt variable, was in question. The relationship between exercise and exercise dependence in this thesis was correlated. This correlation is similar to previous research (Zmijewski & Howard, 2003). Because of the correlation between these two variables, examining a possible mediator effect of exercise dependence on the relationship between ex ercise and drive for thinness was the appropriate analysis. This method specifies that three regressions must meet the following conditions to show a medi ator effect (Baron & Kenny, 1986): 4. Variations in the independent variable si gnificantly account fo r variations in the mediator variable (f igure 5-3, path a),

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45 5. Variations in the mediator variable signi ficantly account for the dependent variable (figure5-3, path b), 6. When both path a and b are controlled, the significant relationship observed in independent and dependent variables disappears. (figure 5-3, path c). Figure 5-3 illustrates this conceptually, while fi gure 5-4 illustrates this with my thesis’s variables and results. Figure 5-3 Conceptual Model of Mediation. Figure 5-4 Conceptual Model of Mediation with Study Variables These results build upon the recommendations of previous research by examining a potential mediating or moderating effect of exercise dependence on eating pathology (Hausenblas & Fallon, 2002). Furthermore, they improve upon research examining the relationship of the same vari ables (Zmijewski & Howard, 2003). These results may also help clarify the confused rela tionship of exercise with eati ng disorders by demonstrating evidence of a mediating affect of exercise dependence as a means in which exercise becomes problematic for eating disordered in dividuals. Specifically, a mediator is a variable that explains how or why another variable aff ects the outcome (Baron & Kenny, 1986; Kraemer et al., 2001). The basic question in my thesis then is, how does exercise affect eating pathology? The poten tial mediator, exercise depe ndence, is examined to see if its presence will affect the outcome of exercise on eating pathology. This is shown

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46 statistically by the three path s described above. Simply stat ed, there are two causal paths on the dependent variable (Baron & Kenny, 1986). Pa th c represents the direct impact of the exercise on driver for th inness, and path b represents the impact of the exercise dependence also on drive for thinness. Separate ly, both of these paths show that exercise and exercise dependence affect drive for thi nness. When the mediati ng variable paths are controlled, the significant rela tionship between exercise and drive for thinness is no longer significant. Therefore, answer to th e question, how does exercise affect eating pathology?, is answered by these analyses show ing that the affect of exercise on drive for thinness is mediated by exercise dependence. Limitations Several limitations were present in my study. The most obvious limitation is the capabilities of alterna tive technologies. For example, ma ny participants took the liberty of reporting qualitative data in inappropriate areas, specifi cally when reporting exercise amounts. While this data was useful in a llowing for a better inference of what the participants were reporting, it poi nts out that computer based technologies are very exact. In other words, they will only perform in the very specific manner as programmed. Future research involving the use of webs ites or computer based interactions with participants should be very careful to program places for participants to enter data in a way that does not allow for confused reporti ng. For example, amount of exercise should only been allowed to be entered as nu meric data, not as alphanumeric data. A similar limitation of alternative tec hnologies is how many people are actually using them. In other words, does recruiting via alternative methods, such as email and internet websites, accurately capture the targeted populat ion? The most recent U.S. Census report on computer and internet usage (Cheeseman Day, Janus, & Davis, 2005)

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47 states that in 2003, 47.1% of all 15-24 year ol d Americans had internet access in their home. Furthermore, 89.4% of all 18-24 year olds enrolled in school were using computers, while 70.6% of all 18-24 year olds enrolled in school we re using the internet. These data support that most of the 10-30% of college age women whom are at risk of developing eating disorders (Cassell, 1994; Franko et al., 2005) can be reached by alternative technologies. Several researchers have reported that women overestimate the amount of total exercise duration (Buchowski et al.,1999; Irwin et al., 2001; & Jakicic et al., 1998). Specifically, this overestimation has been found in women with higher percentage of body fat. The BMI of the sample in my th esis was in the overweight range (ACSM, 2000). Therefore, using self-report measures of exercise behavi or is another limitation of my thesis. Similarly, using other self-report m easures for eating disordered behavior was also a limitation of my thesis. A limitation that was potentially present and somewhat related to the first limitation is the look and feel of a website. While it was not reported back to me that the drab gray color and simplistic design and layout of th e questions was a problem for participants, some participants did have trouble initia lly accessing the website via the PIN login screen. This may or may not have been because of the onscreen layout. What was a noticeable limitation of this website’s layout wa s the inability to form at instructions and questions correctly. For exampl e, the instructions for the LTEQ and the first question in this scale were run together. These instructi ons are rather lengthy and can be hard on the eyes when viewed onscreen. Moreover, the length of the website may have been a problem. Allowing for screen breaks, font changes, deliberate spacing, or even just

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48 placing pictures or changing background colors may have helped with the website’s usability. A fourth limitation was time to respond to the large number of interested individuals contacting me for access to this study. The announcement made via email to all University of Florida students resulte d in a deluge of inquiries in my inbox immediately following the transmission of th e email announcement. Several interested individuals even email multiple times a day until they received a PIN. This perhaps speaks to the previously disc ussed changing nature of our society and the role of the internet in it. People are in creasingly becoming accustomed to instant responses and interactions. Allowing a day or two to re spond to an email may have been acceptable etiquette in the past, but th e increasingly fast paced and quick response nature of interactive technologies, such as the internet, is slowly conditioning people to expect more sooner. Potential solutions to this problem will be discussed in the future directions section of this thesis. A fifth limitation pertains to the findings of the mediator effect of exercise dependence. These data came from participants whom were recruited via advertisements for an exercise program for women dissatisf ied with their bodies. This population of college females may not be truly representati ve of a general population in regards to exercise behavior, exercise dependence, and/ or drive for thinness scores. Specifically, past research has identified the onset of development of eating disorder pathology at earlier ages than of this sample (Jacobi et al., 2004; Stice, 200 2; Thomsen, Weber & Brown, 2001; 2002). Any interpretation of these data should be mindful and considerate of the population from which this data was collected.

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49 Future Directions Several adjustments are need ed in any future resear ch continuing to build upon these data. First, any future research using a website based method of data collection should be more aesthetically pleasing and user friendly than the one used in this thesis. Future studies measuring participants on more scales or questionnaires than the ones use in this thesis must be particularly co ncerned with this a nd consider how such improvements in usability may ease the burden of participation. Sta ndards for protecting and securely storing computeri zed data must be kept, but no t at the expense of usability and convenience for the participant. Time was also discussed as a limitation of this study. Any future directions of similar research should use expert systems to help ease the management of data collection and standardized responses sent to participants. An expert system is defined as any software based program that can mimi c the deductive or inductive reasoning of a human expert (Negotia, 1985). These system s can use algorithms to make decisions based on entered data and be qu ite sophisticated. Something as simple as the ability to review data and send and automated reply to participants would be of extreme convenience to both the researcher and the partic ipant. For example, in this thesis having a simple expert system that could have re viewed data collected from the website and made a decision as to which email to send a pa rticipant (either informing them of there potential eligible status for future studies or not) would have been paramount in time and data management. A third future direction involves th e email method of announcing the study. Everyday our email inboxes are bombarded with unsolicited advertisements and junk mail commonly referred to as spam. Not only are these unwanted emails annoying, but

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50 many may carry the risk of inf ecting and crippling your comput er from attached viruses. The email for this study was sent through a listserve, or list of email addresses encompassing all University of Florida underg raduates, designed to inform the student body of a variety of events on campus. The resp onse rate was substantially greater than any other method of recruitment measure, but wa s still low considering that it was sent to thousands of students. Emails such as these, even though they are sent from familiar and reputable sources, may be discarded along with any other junk mail of the day. A future direction to help alleviate this problem is to examine what f actors would lead to students taking better advantage of emails, such as the one announcing this study, that inform them of opportunities at the university rather than deleting them without reading them. Creating a listserve solely a nnouncing research opportunities ma y be a way to reach only those students whom are willing to participate in future studies. Future research is also needed to furthe r examine the mediator relationship that was found in this thesis. Efforts should focus on re cruiting a more representative cross section of the population. Future research should also examine these relationships in samples of men. Similarly, announcements should not focu s solely on recruiting those whom are currently dissatisfied with their body. While this was acceptable for the purposes of this thesis, future research should focus on recruiting a sample that is more representative of the general population. Finally, a limitation discussed above was th at this study used se lf-report measures of exercise behavior and ea ting disorder risk. Future studies should use more objective methods of collecting similar data. For exampl e, accelerometers could be used to collect

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51 more accurate data on exercise behavior and c linical interviews could be used to more accurately determine eating disorder risk status. Conclusions This study illustrated the importance of using new technologies and alternative methods to recruit a large number of indi viduals in a short time, thus supporting recommendations researchers (McDermont et al., 2003) and emphasi zing advantages of computer based research (Kraut et al., 2004; Myers et al., 2004). Using such methods was not shown to be statistically different th an more traditional methods of announcing research, but did show that there is potent ial for reaching large numbers of people while being convenient for both the researcher and the participant. This study also improved upon previous research finding that exercise dependence is corre lated with bulimia subscale scores in female undergraduate co llege students (Zmijewski & Howard, 2003) by further examining the relationship between exercise and eating pathology based on the recommendation to examine moderator and mediator effects of these variables (Hausenblas & Fallon, 2002). Eating disorders are serious and secre tive both in their development and their course, (Cassell, 1994; Fairburn, 1995; Hoek, 1995; & Hoek & van Hoeken, 2003) thus necessitating the need fo r further research to identify better ways of recruiting this special population.

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52 APPENDIX A DEMOGRAPHIC QUESTIONS What is your age? Please type how many feet tall you are. Inches? What is your current weight? What is your ideal weight? (The weight you would like to be at right now.) What year in school are you? What is your major? What is your family's annual income? What is your ethnic background? If you selected "other" ethnic background, please type your ethnic background here. What is your first name? What is your email address? (Please type an email account that you check regularly.) What is your phone number? How many times a week do you exercise? Have you ever been diagnosed with an eating disorder? Do you currently have an eating disorder? What is your gender? Where did you hear about this study?

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53 APPENDIX B DRIVE FOR THINNESS QUESTIONNAIRE Instructions : This is a scale which measures a variety of attitudes, feelings, and behaviors. Read each question carefully a nd circle the number to the right of the question which applied best to you. Please use the following scale: 1 2 3 4 5 6 Never Rarely Sometimes Often Usually Always 1. I eat sweets and carbohydrates without feeling nervous. 1 2 3 4 5 6 2. If I gain a pound, I worry that I will keep gaining. 1 2 3 4 5 6 3. I think about dieting. 1 2 3 4 5 6 4. I am terrified of gaining weight. 1 2 3 4 5 6 5. I exaggerate or magnify the importan ce of weight. 1 2 3 4 5 6 6. I am preoccupied with the desire to be thinner. 1 2 3 4 5 6 7. I feel extremely guilty after overeating. 1 2 3 4 5 6

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54 APPENDIX C EXERCISE DEPENDENCE QUESTIONNAIRE Instructions Using the scale provided below, please complete the following questions as honestly as possible. The questi ons refer to current exercise beliefs and behaviors that have occu rred in the past 3 months Please place your answers in the blank space provided after each statement. 1. I exercise to avoid f eeling irritable. ____ 2. I exercise despite recu rring physical problems. _____ 3. I continually increase my exercise intensity to achieve the desi red effects/benefits._ 4. I am unable to reduce how long I exercise. _____ 5. I would rather exercise than spe nd time with my family/friends. _____ 6. I spend a lot of time exercising. ______ 7. I exercise longer than I intend. ______ 8. I exercise to avoi d feeling anxious.______ 9. I exercise when injured. ______ 10. I continually increase my exercise frequency to achieve the desired effects/benefits.__ 11. I am unable to reduce how often I exercise. _____ 12. I think about exercise when I shoul d be concentrating on school/work._____ 13. I spend most of my free time exercising. _____ 14. I exercise longer th an I expect. _____ 15. I exercise to avoi d feeling tense._____ 16. I exercise despite persistent physical problems._____ 17. I continually increase my exercise duration to achieve the desired effects/benefits.___ 18. I am unable to reduce how intense I exercise. _____ 19. I choose to exercise so I can get out of spending time with family/friends._____ 20. A great deal of my time is spent exercising. _____ 21. I exercise longer than I plan. _____ 1 2 3 4 5 6 Always Never

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55 APPENDIX D LEISURE TIME EXERCISE QUESTIONNAIRE Instructions This is a scale which measures your leisure-time exercise (i.e., exercise that was done during your free tim e such as intramural sports–NOT your physical education class). Considering a typical week, please indicate how often (on average) you have engaged in strenuous, moderate, and mild exercise more that 20 minutes during your free time? 1. Strenuous exercise: heart beats rapidly (running, basketba ll, jogging, hockey, squash, judo, roller skating, vigorous swimming, vi gorous long distance bicycling, vigorous aerobic dance classes, heavy weight training) How many times per typical week do you perf orm strenuous exercise for 20 minutes or longer? ______ 2. Moderate exercise: not exhausting, light sweating (fast walking, baseball, tennis, easy bicycling, volleyball, badminton, easy swimming, popular and folk dancing) How many times per typical week do you perf orm moderate exercise for 20 minutes or longer? _______ 3. Mild exercise: minimal effort, no sw eating (easy walking, yoga, archery, fishing, bowling, lawn bowling, shuffleboard, horseshoes, golf) How many times per typical week do you pe rform mild exercise for 20 minutes or longer? _______

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56 APPENDIX E STUDY ANNOUNCEMENT Are you dissatisfied with your body? Would you like to get into better shape? Are you dissatisfied with your body? Would you like to ge t into better shape? The exercise psychology lab in the Department of Applied Physiology and Kinesiology is looking for female students who are inte rested in participating in an exercise program designed to improve your physic al appearance and body image. Please contact the exercise psych lab at exer.psych.lab@hhp.ufl.edu to complete a short web based questionnaire to de termine your study eligibility.

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57 APPENDIX F REPLY WITH PIN AND INFORMED CONSENT Thank you very much for your interest in this study! Please visit the following website to complete our eligibility questionnaire, http://survey.hhp.uf l.edu/index.php?id=65 Your PIN login in for this study is XXXXXX. Enter this PIN w hen prompted and click on the “Begin the Survey” box. Simply pressing enter after entering your PIN may not work. Please complete all of the survey questions. This survey is only accessible through the unique password that has been emailed to you and cannot be used more than once. Do not give your PIN to anyone else to use. Please complete the entire survey in one session. If you need to stop or are di sconnected before you have completed the survey, email the exercise psychology lab at exer.psych.lab@hhp.ufl.edu and we will respond with a new PIN for you to use. A consent form explaining this study and whom to contact if you have any questions is provided below. Please review th is form. Please reply to this email if you decide not to participate after reading this form. Thank you again for your interest in this study, The exercise psychology lab. INFORMED CONSENT PLEASE READ THIS ENTIRE DOCUMENT CAREFULLY BEFORE YOU DECIDE TO PARTICIPATE IN THIS STUDY. TO: All Research Participants FROM: Brian Cook RE: Informed Consent PURPOSE OF THIS STATEMENT: The purpose of this statement is to summarize the study I am conducting, explain what I am asking you to do, and to assure you that the information you and other participants share will be kept confiden tial to the extent permitted by law. Specifically, nobody besides the principal investigator and the research assistants will be able to identify you in this study and your name will not be used in any research repor ts that result from this project. WHAT YOU WILL BE ASKED TO DO: If you agree to participate in this study, you will be asked to complete a few questionnaires via the web. Based on your responses to these measures, you may be contacted by a research assistant to participate in an exercise intervention. TIME RQUIRED: Completion of the measures will take no more than 10 minutes.

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58 RISKS AND BENEFITS: There are no risks expected from participating in this study. There are no direct benefits to you for participating in this study. COMPENSATION: You will not be compensated monetar ily for your participation in this study. You may be given extra credit by your instructor for completing this study. CONFIDENTIALITY: Your identity will be kept confiden tial to the extent provided by law. Your information will be assigned a code number. The list connecting your name to this number will be kept in my laboratory (Room 145 Florida Gym) in a locked file cabin et. When the study is complete and the data have been analyzed all ma terials will be destroyed. Your name will not be used in any report. VOLUNTARY PARTICIPATION: Your participation in this st udy is completely voluntary. There is no penalty for not participating. RIGHT TO WITHDRAW: You have the right to withdraw from the study at anytime without consequence. WHOM TO CONTACT IF YOU HAVE QUESTIONS ABOUT THIS STUDY: Brian Cook, Department of Applied Physiology and Kinesiology. Email: bcook@hhp.ufl.edu Heather Hausenblas, Department of Applied Physiology and Kinesiology. Email: heatherh@hhp.ufl.edu WHOM TO CONTACT ABOUT YOUR RIGHTS AS A RESEARCH PARTICIPANT IN THE STUDY: UFIRB Office, Box 112250, University of Florida, Gainesville, FL 32611-2250; phone 352-392-0433. AGREEMENT: I have read the procedure described above I voluntarily agree to participate in the procedure. By clicking here I am giving my consent to participate in this study.

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59 APPENDIX G ELIGIBLE RESPONSE Dear (insert first name here) Recently you completed a web-based screening questionnaire for an upcoming exercise program designed to improve your physical appearance and body image. Based on your responses, you have met the preliminary criteria for inclusion in this program. The program is scheduled to begin at the start of the spring 2006 semester Please reply to this email and let us know: 1.) If you are still interested in this program. 2.) If you will be able to complete the 6 m onth exercise program, as well as a 6 month follow up. 3.) What time(s) will be the best for you to participate in this exercise program? Specify if mornings, days, and/or ev enings will work best for you. Please consider your class and academic res ponsibilities, work responsibilities, family obligations, and any other time restraints that you will have next semester. Prior to the beginning of this program, ev eryone will be randomized into either the intervention or the control group. Everyone has an equal chance of being in either group. You will receive notificati on of which group you are a part of. Thank you for your interest and participation in this study. The Exercise Psychology Laboratory

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60 APPENDIX H INELIGIBLE RESPONSE Dear (insert first name here) Recently you completed a web-based screening questionnaire for an upcoming exercise program designed to improve your physical appearance and body image. Unfortunately, based on your responses, you ha ve not met the preliminary criteria for inclusion in this program. We may contact you in the futu re if other similar programs begin that may be better suited for you. Please reply to this email if you would not like to be contacted for any future studies. Thank you for your interest and participation in this study. The Exercise Psychology Laboratory

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61 LIST OF REFERENCES American College of Sports Medicine. (2000). ACSM’s guidelines for exercise testing and prescription (6th ed.) Baltimore: Williams & Wilkins. American Psychological Association. (1994). Diagnostic and statistica l manual of mental disorders (4th ed.). Washington, DC.: Author Austin, S.B. (2000). Prevention research in eat ing disorders: Theory and new directions. Psychological Medicine, 30, 1249-1262. Baron, R.M., & Kenny, D.A. (1986). The moderator-mediator variable distinction in social psychology research: Conceptual, st rategic, and statistical considerations. Journal of Personality and Social Psychology, 51(6), 1173-1182. Battle, E.K., & Brownell, K.D. (1996). Confr onting a rising tide of eating disorders and obesity: treatment versus prevention and policy. Addictive Behaviors, 21, 755-765. Bennett, J.A. (2000). Mediator and moderator variables in nursing re search: Conceptual and statistical differences. Research in Nursing and Health, 23, 415-420. Brewerton, T., Stellefson, E., Hibbs, N., H odges, E., & Cochrane, C. (1995). Comparison of eating disorder patients with and without compulsive exercising. International Journal of Eating Disorders, 17(4), 413-416. Buchowski, M.S., Townsend, K.Y., Che n., Acra, S.A., & Sun, M. (1999). Energy expenditure determined by self -reported physical activity is related to body fatness. Obesity Research, 7, 23-33. Caplan, G. (1964). Principles of preventive psychiatry. New York : Basic Books Cassell, Dana K. (1994). Encyclopedia of obesity and eating disorders New York New York: Facts on File, Inc. Catalano, J.A. & Dooley, D. (1980). Economic change in primary prevention. In R.H. Price, R.F. Ketter, B.C. Ba der, and J. Monahan (Eds.), Prevention in mental health: Research, policy, and practice. (pp. 21-40). Beverly Hills, CA : Sage Publications Center for Disease Control, (1996). Guidelin es for school health programs to promote lifelong healthy eating. Morbidity and Mortality Weekly Report, 45(rr9), 1-41.

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62 Cheeseman Day, Janus, & Davis, (2005). Computer and internet use in the United States: 2003. Current Population Reports, U.S. Department of Co mmerce, U.S. Census Bureau, October 2005. Cooper, Z. (1995). The development and maintenance of eating disorders. In K.D. Brownell & C.G. Fairburn (Eds.), Eating disorders and obesity: A comprehensive handbook (pp. 199-206). New York, New York: Guilford Publications, Inc. Davis, C., Kaptein, S., Allan, M., Olmsted, M., Woodside, D. (1998). Obsessionality in anorexia nervosa: The moderating influence of exercise. Psychosomatic Medicine, 60, 192-197. Davis, C., Katzman, D., & Kirsh, C. (1999b). Co mpulsive physical activity in adolescents with anorexia nervosa. A psychobe havioral spiral of pathology. Journal of Nervous and Mental Disorders, 187, 336-342. Davis, C., Katzman, D., Kaptein, S., Brewer H., Kalmbach, K., Olmsted, M., Woodside, D., & Kaplan, A. (1997). The prevalence of high-level exercise in the eating disorders: Etiological implications. Comprehensive Psychiatry, 38(6), 321-326. Davis, C., Woodside, D.B., Olmsted, M.P., & Kaptein, S. (1999a). Psychopathology in the eating disorders: the influence of physical activity. Journal of Applied Biobehavioral Research, 4(2), 139-156. Fairburn, C.G. (1995). The prevention of eati ng disorders. In K.D. Brownell & C.G. Fairburn (Eds.), Eating disorders and obesity: A comprehensive handbook (pp. 289-293). New York, New York: Guilford Publications, Inc. Fairburn, C.G. & Cooper, P.J. (1982). Self-induced vomiting and bulimia nervosa: An undetected problem. British Medical Journal, 284, 1153-1155. Fairburn, C.G., & Walsh, B.T. (1995). Atypica l eating disorders. In K.D. Brownell & C.G. Fairburn (Eds.), Eating disorders and obesity: A comprehensive handbook (pp. 135-140). New York, New York : Guilford Publications, Inc. Franko, D.L., Mintz, L.B., Villapiano, M., Gr een, T.C., Mainelli, D., Folensbee, L., Butler, S., Davidson, M.M., Hamilton, E., Little, D., Kearns, M., & Budman, S. (2005). Food, mood, and attitude: Reducing risk for eating disorders in college women. Health Psychology, 24(6), 567-578. Garfinkel, P.E. (1995). Classifi cation and diagnosis of eating disorders. In K.D. Brownell & C.G. Fairburn (Eds.), Eating disorders and obesity: A comprehensive handbook (pp. 125-134). New York, New York : Guilford Publications, Inc. Garner, D.M. (1991). The Eating Disorder Inventory-2 professional manual. Odessa, FL: Psychological Assessment Resources.

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66 Stice, E. (2002). Risk and maintenance factors for eati ng pathology: A meta-analytic review. Psychological Bulletin, 128(5), 825-848. Stice, E., & Shaw, H. (2004). Eating Disord er Prevention Programs: A Meta-Analytic Review. Psychological Bulletin, 130(2), 206-227. Symons Downs, D., Hausenblas, H., & Nigg, C. (2004). Factorial validity and psychometric examination of the exercise dependence scalerevised. Measurement in Physical Education and Exercise Science, 84(4), 183-201. Thomsen, S.R., Weber, M.M., & Brown, L.B. (2001). The relationship between health and fitness magazine reading and eati ng-disordered weight-loss methods among high school girls. American Journal of Health Education, 32(3), 133-38. Thomsen, S.R., Weber, M.M., & Brown, L.B. (2002). The relationship between reading beauty and fashion magazines and the use of pathogenic dieting methods among adolescent females. Adolescence, 37(145), 1-18. Tylka, T.L. (2004). The relationship between body dissatisfaction and eating disorder symptomatology: an analysis of moderating variables. Journal of Counseling Psychology, 51(2), 178-191. Tylka, T.L., & Subich, L.M. (2002). Expl oring young womens perceptions of the effectiveness and safety of malada ptive weight control techniques. Journal of Counseling and Development, 80(1), 101-111. US Department of Health and Human Services (1990). Healthy people 2000: National health promotion and disease prevention objectives. Washington, D.C.: USDHHS US Department of Health and Human Services (1996). Physical activity and health: A report of the surgeon general. Atlanta, Georgia: USD HHS Center for Chronic Disease Prevention and Health Promotion Vitousek, K.B., 1995 Cognitive-behavioral th erapy for anorexia nervosa. In K.D. Brownell & C.G. Fairburn (Eds.), Eating disorders and obesity: A comprehensive handbook (pp. 324-329). New York, New York: Guilford Publications, Inc. Wantland, D., Portillo, C., Holzemer, W., Slaughter, R., & McGhee, E. (2004). The effectiveness of web-based vs. non-web-ba sed interventions: A meta-analysis of behavioral change outcomes. Journal of Medical Internet Research, 6(4), e40. January 2006. Weiss, T.W., Slater, C.H., Green, L.W., Ke nnedy, V.C., Albright, D.L., & Wun, C.C. (1990). The validity of singleitem self-assessment questions as measures of adult physical activity. Journal of Clinical Epidemiology,43 1123-1129.

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67 Wellman, B., Quan Haase, A., Witte, J., & Hampton, K. (2001). Does the Internet increase, decrease, or supplement social cap ital? Social networks participation, and community commitment. American Behavioral Scientist, 45(3), 436-455. Woodside, D.B., Garfinkel, P.E., Lin, E., Go ering, P., Kaplan, A.S., Goldbloom, D.S., & Kennedy, S.H. (2001). Comparison of men w ith full or partial eating disorders, men with out eating disorders, and women with eating disorders in the community. American Journal of Psychiatry, 158, 570-574. Zmijewski, C.F. & Howard, M.O. (2003). Ex ercise dependence and attitudes toward eating among young adults. Eating Behaviors, 4, 181-195.

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68 BIOGRAPHICAL SKETCH Brian was raised in Cumberland, Rhode Is land, and attended hi gh school at Mount Saint Charles Academy in Woonsocket, Rhode Island. He began his undergraduate education at Johnson State College in Johnson, Vermont, where he majored in psychology and competed on the men’s varsity cross country and tennis teams. At the conclusion of his freshman year, he transferre d to the University of Rhode Island to focus on his psychology major. After graduating from the University of Rhode Island, he worked as a project assistant at ProChange Behavior Systems, Inc., in West Kingston, Rhode Island. Brian enrolled at the University of Florida in the fall semester of 2003.


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Physical Description: Mixed Material
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EXAMINING RECRUITMENT METHODS FOR COLLEGE WOMEN AT-RISK FOR
EATING DISORDERS AND THE RELATIONSHIP BETWEEN EXERCISE AND
EATING PATHOLOGY















By

BRIAN COOK


A THESIS PRESENTED TO THE GRADUATE SCHOOL
OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT
OF THE REQUIREMENTS FOR THE DEGREE OF
MASTER OF SCIENCE

UNIVERSITY OF FLORIDA


2006

































Copyright 2006

by

Brian Cook

































This thesis is dedicated to all who have helped me succeed in my academic career.















ACKNOWLEDGMENTS

I thank my committee for their direction, wisdom, and help with this thesis and

guiding me through this master's program. All of our interactions during these past three

years have made an impact on me as a student, a researcher, and a person. All of them are

excellent role models both professionally and personally. Dr. Heather Hausenblas, my

committee chair, has been especially important in providing assistance with my academic

work and research, as well as offering timely words of encouragement that are so very

much needed and appreciated.

I also thank everyone at ProChange Behaviors Systems, Inc., for providing me with

the foundation to pursue my career goals. The opportunities and experiences that I have

gained while working at ProChange have been invaluable to my development as a

researcher. Most of all, I thank them for believing in my ability to succeed.

Finally, I thank all of my friends and family that have guided me throughout my

education. I thank them all for their love and support that have enabled me to pursue my

education.
















TABLE OF CONTENTS



A C K N O W L E D G M E N T S ................................................................................................. iv

LIST OF TABLES ............. ........... ...... ........ .......... vii

LIST OF FIGURES ........................ ........................ viii

ABSTRACT .............. .......................................... ix

CHAPTER

1 IN TR O D U C TIO N ......................................................................... .... .. ........

2 LITER A TU R E R EV IEW ............................................................... ...................... 7

G en eral O v erv iew ............ .................... .............................................. ....... ....... .. ..
E tiology .............................................................................. ...............11
Stage O ne ...................................................................................... ..... .. .......11
S ta g e T w o ......................................................................................12
S ta g e T h re e .....................................................................................12
P re v a le n c e .............................................................................................................. 1 4
P re v e n tio n .............................................................................................................. 1 7
R ecru itm ent ............................................................................... 2 0
Exercise and Eating Disorders ................................. .......................... ....24

3 M E T H O D S ............................................................................................................ 2 8

P a rtic ip a n ts ............................................................................................................ 2 8
M e a su re s ................................................................................................................ 2 8
Demographic Questionnaire ................................................... 28
D rive for Thinness Subscale................................ ................... 28
Exercise D ependence Scale .......................................... ............... 29
Body composition....................................... 29
Leisure-tim e Exercise Questionnaire ........................................ ............... 29
P ro c e d u re ................................................................ 3 0
Prim ary Purpose................................................. 32
E eligibility C riteria.................................................. 32
D ata A n a ly sis .................................................................................................. 3 2
Secondary Purpose................................................... 33


v









4 R E SU L T S ....................................................... 3 5

R espon se R ate.......................................................35
Prim ary Purpose...................... ......... .. ..... ..... .. ............35
S econ dary P u rp o se........... ...... ........................................ .................. .......... ....... 37

5 D ISC U S SIO N ............................................................................... 40

O v e rv iew .........................................................................................4 0
Stu dy F in din g s ................................................................................ 4 0
R e c ru itm e n t ................................................................................................... 4 0
M e d iato r E ffe ct ....................................................................................................4 3
Lim stations .................................. .......................... ..... ..... ........ 46
F utu re D direction s ................................................................4 9
C o n c lu sio n s ........................................................................................................... 5 1

APPENDIX

A DEMOGRAPHIC QUESTIONS .............................................. ..................52

B DRIVE FOR THINNESS QUESTIONNAIRE ........................................ ...53

C EXERCISE DEPENDENCE QUESTIONNAIRE ................................ ............. 54

D LEISURE TIME EXERCISE QUESTIONNAIRE ........................55

E STUDY ANNOUNCEMENT ................................................56

F REPLY WITH PIN AND INFORMED CONSENT ................................................57

G E L IG IB L E R E SP O N SE ....................................................................................... 59

H INELIGIBLE RESPONSE ................ ......... ...... ........60

LIST OF REFERENCES ............ .. .......... ................................................ 61

BIOGRAPHICAL SKETCH ................................ ........................................68
















LIST OF TABLES

Table p

2-1 One-Year-Period Prevalence Rates per 100,000 Young Females............................16

3-1 T hesis T im line. ........................................................................31

4-1 M eans, Standard Deviations, and Alpha Values ............................... ............... .36

4-2 Frequency of Recruitm ent M ethod.................................... ........................... ......... 36
















LIST OF FIGURES

Figure page

2-1 Etiological Model of Eating Disorder Development and Maintenance ...................14

3-1 Study Flow ........................................................................ ... ......... ..... 31

3-2 Relationship of M editor V ariables .................................... ............. ...................34

3-3 Relationship of M oderator Variables .............................................. ............... 34

5-1 M operator M odel ............... ................. ............ ............ ............ 44

5-2 M editor M odel .................................. ... ........ .... .......... 44

5-3 C onceptual M odel of M edition ..................................................................... .. .....45

5-4 Conceptual Model of Mediation with Study Variables.............................................45















Abstract of Thesis Presented to the Graduate School
of the University of Florida in Partial Fulfillment of the
Requirements for the Degree of Master of Science

EXAMINING RECRUITMENT METHODS FOR COLLEGE WOMEN AT-RISK FOR
EATING DISORDERS AND THE RELATIONSHIP BETWEEN EXERCISE AND
EATING PATHOLOGY

By

Brian Cook

May 2006

Chair: Heather Hausenblas
Major Department: Applied Physiology and Kinesiology

Between 10-30% of college age women are at-risk for eating disorders. This at-risk

population will also be experiencing some of the negative consequences associated with

eating disorders. Prevention interventions are therefore needed to halt development on to

full blown eating pathology. Despite the fact that prevention interventions targeting at-

risk populations, such as college women, are more effective in reducing eating disorder

symptoms than universal program, little research has examined the best methods to

recruit at-risk individuals. The primary purpose of my thesis was to examine the

efficaciousness of recruitment methods for individuals at-risk for developing bulimia

nervosa. Specifically, I examined the following two recruitment pathways: college

campus announcements and announcements made via alternative delivery systems. I

hypothesized that recruitment through the alternative methods, such as the Internet and

email, would produce a larger number of both total respondents and eligible respondents.









Recruiting at-risk individuals allowed for the examination of behaviors believed to

aid the development of eating disorders. Exercise has long been observed in this

population and thought to exacerbate the progression and maintenance of eating

disorders. However, little attention has been given to examining the psychological

motivation for exercise in this population, thus allowing the possibility of a separate

variable mediating or moderating the relationship of exercise and eating disorders. The

secondary purpose of my thesis was to examine the associations among exercise

behavior, drive for thinness scores, and exercise dependence scores. Specifically, I

examined the relationship of exercise behavior and exercise dependence scores on drive

for thinness scores. I hypothesized that drive for thinness scores would be more strongly

influenced by exercise dependence scores than by total amount of exercise alone.

The results of my study indicated that the hypothesis of my primary purpose was

not statistically supported. The results were approaching significance and may have been

improved with a larger sample size. The data also indicated that alternative methods

cover a substantial breadth of potential participants. The results also indicated that the

hypothesis of my secondary purpose was fully supported. These results indicate that the

effect of exercise on eating disorder symptoms is mediated by exercise dependence.

Future research can build upon these results by continuing to use the advantages of

new and evolving alternative technologies in the recruitment of difficult to reach

populations. Through this, future research may also expand on the results of my

secondary purpose by recruiting larger and more diverse samples. Because of the

negative physical and psychological consequences of eating disorder, prevention efforts

are a high research priority.














CHAPTER 1
INTRODUCTION

The most common psychiatric disorders afflicting young women are eating

disorders (i.e., anorexia nervosa, bulimia nervosa, & eating disorder not otherwise

specified; Pritts & Susman, 2003). They are categorized by a persistent and distorted

view of ones own body and subsequent behaviors performed in an attempt to relieve the

psychological turmoil resulting from this faulty self-perception. Although the morbidity

rate of eating disorders in college age women is low (1 3%; Franko et al., 2005), the

mortality rate is high (20% 40%; Harris & Barraclough, 1994, 1998; Keel et al., 2003;

Mehlenbeck, 2002). More alarming is that 10-30% of college age women are at risk for

eating disorders (Cassell, 1994; Franko et al., 2005). Furthermore, serious consequences

of the behaviors associated with eating disorders may not be limited to only those with

the full-syndrome disorders. Some consequences contribute to impaired health even when

they are exclusive of a full-syndrome eating disorder (Pearson, Goldklang, & Striegel-

Moore, 2002). In other words, being at risk for these disorders may not preclude a person

from experiencing their negative health impact. Treating these individuals is also difficult

due to their secretive nature, which allows for many cases to not be recognized

immediately (Fairburn, 1995; Fairburn & Cooper, 1982; Hoek, 1995; Hoek & van

Hoeken, 2003).

The large number of individuals at risk for eating disorders, and the serious health

consequences experienced throughout the entire spectrum of development, offers an

opportunity and necessity to apply prevention interventions. Eating disorder prevention









has recently made great strides. While early programs tended to be didactic and

psychoeducational in nature, and generally did not produce much effectiveness, the latest

prevention programs are interactive and have shown promising results (Stice & Shaw,

2004). Overall, the most effective prevention programs are delivered to women over the

age of 15 and are interactive, multisession programs not presented as eating disorder

prevention (Stice & Shaw, 2004). Following the traditional modes of universal education

programs as prevention are not effective when applied to this health problem. Perhaps

effects are lost by not selecting those individuals whom are at-risk and therefore the most

in need. In other words, a better understanding and targeting of at risk populations may

be a logical next step in the progression of eating disorder prevention (Stice & Shaw,

2004). Examining recruitment methods for prevention efforts offers an opportunity to

increase the impact of such interventions by providing the knowledge of how to

efficaciously select those most in need.

Recruitment is an immediate concern when preparing to implement an eating

disorder prevention program with women. Ironically, this should not be much of a

challenge considering the previously mentioned large numbers at-risk for eating

disorders. For example, normal to overweight college age women are all at a higher risk

for the development of eating disorder than men (Jacobi et al., 2004; Woodside et al.,

2001). Recruitment efforts need to focus on finding new and more effective ways of

reaching these at-risk people in need of intervention. Examining how efficaciously a

recruitment strategy can contact potential participants can be guided by applying certain

factors of the RE-AIM framework. The RE-AIM framework is a framework that

addresses issues of internal and external validity of health behavior programs (Glasgow,









Vogt, & Boles, 1999; Glasgow et al., 2004). For example, an effective recruitment

strategy must be able to sample large numbers of potentially eligible and willing

participants, while still being implemented in a standard and consistent fashion. Such a

strategy would demonstrate the RE-AIM dimensions of Reach, Effectiveness, Adoption,

and Implementation (Glasgow, Vogt, & Boles, 1999; Glasgow et al., 2004). Specifically,

sampling a large number of potentially eligible participants is a recruitment strategy's

reach. Examining the number of eligible and willing participants a strategy can deliver

represents its effectiveness. A strategy's adoption would be evident by its ability to be

consistently delivered through a variety of settings. Similarly, consistently delivering a

recruitment strategy in each setting is the implementation dimension of the RE-AIM

framework (Glasgow, Vogt, & Boles, 1999; Glasgow et al., 2004).

A review of the literature reveals limited research addressing efficacious methods

of recruiting this population (Lovato et al., 1997; McDermott et al., 2003). New

technologies, such as computers and the internet, enable researchers and practitioners to

reach and recruit populations that were previously difficult to help (Kraut et al., 2004),

and offer both the researcher and participant numerous advantages; such as cost-

effectiveness, accessibility, portability, ease of use, accessibility, and convenience (Kraut

et al., 2004; Myers et al., 2004). Using these advantages may be one way to increase the

effectiveness of recruitment efforts of at-risk individuals.

Both risk factor and prevention research have made substantial advances in their

understanding and effectiveness of intervening on this difficult population. Synthesizing

relevant information from both lines of research with new alternative technologies

clarifies an opportunity to examine new methods of isolating and reaching at-risk









populations. Given this collective understanding, identifying the most efficacious

methods of recruiting this population is the next logical step in the progression of better

prevention efforts.

Thus, the primary purpose of my thesis was to examine the efficaciousness of

recruitment methods for individuals at risk for developing bulimia nervosa. Specifically, I

examined two recruitment pathways: college campus announcements (in classroom

settings and advertisements posted on a college campus) and announcements made via

alternative delivery systems (placed on an internet website and a mass email sent to

college students). The primary outcome measures of this purpose were the total number

of responses to each advertisement and the total number of respondents who met criteria

indicating being at risk for the development of bulimia nervosa. I hypothesized that

recruitment through the alternative methods, such as the internet and email, would

produce both a larger number of total respondents and a larger number of eligible

respondents (Kraut et al., 2004; McDermott et al., 2003; Myers et al., 2004).

Examining recruitment methods also provides an opportunity to collect data for

other purposes because responding participants will need to complete assessments once

they have inquired about a program. Adding measures of self-reported exercise and

exercise dependence to risk screening assessments allows the possibility of questioning

the role of exercise and its relationship to weight control in terms of the development of

eating pathology. The view traditionally held is that exercise may exacerbate the effects

of eating pathology based on the observation that eating disordered individuals also

excessively exercising (Brewerton, Stellefson, Hibbs, Hodges, & Cochrane, 1995; Davis,

Katzman, Kaptein et al., 1997; Hoglund, & Normen, 2002; Katz, 1996). More recent









research reveals that exercise may not be exclusively to blame; rather there may be other

moderating variables at play in this relationship (Davis et al., 1997, 1998, 1999a).

Examining the relationship of exercise and eating pathology, and looking at other

possible factors that may or may not be contributing to this relationship, is needed to help

clarify these two very divergent schools of thought that currently exist. Furthermore,

comparing exercise dependence data, total amount of exercise data, and drive for thinness

data may offer insight into the distinction of primary versus secondary dependence of

exercise in the context of eating disorders. In other words, examining the difference

between those whom are exercising as an end in itself (primary dependence) and those

whom are exercising for some other end (secondary dependence; Hausenblas & Fallon,

2002; Hausenblas & Symons Downs, 2002).

Previous research has begun to examine these relationships between exercise

dependence and eating pathology. Hausenblas and Fallon (2002) found that primary

exercise dependence played a marginal role in predicting body image in a sample of

female undergraduate college students. They recommended for future research to

examine mediator and/or moderator effects of body image and exercise behavior.

Similarly, Zmijewski and Howard (2003) found that exercise dependence scores in

female undergraduate students were positively correlated with the Bulimia subscale of

the EAT-26 (Garner & Garfinkel, 1979) and that this subscale was also an important

predictor of exercise dependence scores. These results indicate that many college women

may be exercising in association with a formal or subclinical eating disorder (Zmijewski

& Howard, 2003). Unfortunately, these analyses stopped short of examining a potential

mediating or moderating effect.






6


Thus, the secondary purpose of my thesis was to examine the associations between

exercise behavior, drive for thinness scores, and exercise dependence scores. Specifically,

I examined the relationship of exercise behavior and exercise dependence scores on drive

for thinness scores. I hypothesized that drive for thinness scores (i.e. cardinal features of

an eating disorder) would be more strongly influenced by exercise dependence scores

than by total amount of exercise alone (Hausenblas & Fallon, 2002; Hausenblas &

Symons Downs, 2002; Zmijewski & Howard, 2003).














CHAPTER 2
LITERATURE REVIEW

The purposes of this chapter are to present a general understanding of eating

disorders and to examine the research that is relevant to this thesis. I will begin by

describing eating disorders and their etiology of acquisition, development, and

maintenance. This will be followed by a brief review of the most widely accepted

prevalence rates for these disorders. I will then provide a basic overview of prevention

and how it is applicable to this thesis, followed by a review of the literature on recruiting

eating disordered individuals. Finally, I will present research relevant to the role of

exercise and eating disorders. The research presented in this literature review will provide

a sound rational for this thesis research.

General Overview

Anorexia nervosa and bulimia nervosa are similar, yet distinct disorders which are

the two most common eating disorders; accounting for two thirds of the individuals

seeking treatment for eating disorders (Fairburn & Walsh, 1995). Each is characterized

by cognitive distortions regarding body image resulting in behaviors in an attempt to

modify the body.

The criterion for anorexia nervosa is explicitly outlined in the DSM-IV (APA,

1994) and can be generally stated as an intense and unrealistic fear of becoming fat,

engaging in behaviors intended to produce distinct weight loss, and amenorrhea resulting

from the refusal to maintain a health weight (Garfinkel, 1995). The specific criterions are

as follows. The intense fear of becoming fat experienced by anorexics does not cause an









overestimation of body part size; rather the excessive concern with weight and shape of

the body predicates the self-esteem and affect of the person. Furthermore, simply over-

estimating the size of ones body or a body part is not exclusive to eating disorders. It is

the relation of the body or body parts to the individuals' affect which distinguishes

anorexia from other disorders (Garfinkel, 1995). This disturbance of self-evaluation and

consequential denial of the brevity of one's low weight are defined in the DSM-IV (APA,

1994) as maintaining a weight that is less than 85% of what is considered an ideal body

weight for the individual. This denial is physically evident by a physiological criterion of

amenorrhea. Simply stated, this is when at least three consecutively absent menstrual

cycles occur in women. Two specific types, restricting type and binge-eating/purging

type, based on how the extreme low weight is reached and maintained, also define

anorexia. The restricting type is only defined as the absence ofbinging and purging

behaviors. The binge-eating/purging type states that during the current episode of

anorexia, the individual also engages in binges (i.e., eating inappropriately massive

amounts of food in one set period of time) or purging behavior (i.e., self-induced

vomiting, misuse of laxatives, diuretics, or enemas).

The DSM-IV (APA, 1994) criteria for bulimia nervosa are similar to that of

anorexia in that it too outlines an intense fear of becoming fat, but differentiates itself by

including the requirements of powerful urges to overeat and subsequent binges that are

followed by engaging in some sort of purging or compensatory behavior in an attempt to

avoid the fattening effects of excessive caloric intake. Similar to anorexics, the fear

experienced by bulimics is in regards to self-evaluation, thus resulting in compensatory

behaviors to evade weight gain. The paradox is the presence of the uncontrollable urges









to overeat. These binges are defined as occurring within 2 hours and including an amount

of food that is definitely larger than most people would consume in a similar time and

setting and a sense of lack of control during the binge (APA, 1994). Similar to anorexia,

these behaviors are separated into purging type (self-induced vomiting, use of laxative,

diuretics, enemas, or medication abuse.) and non-purging type (other compensatory

behaviors such as fasting or excessively exercising).

These two eating disorders present a variety of serious physical and psychological

health consequence throughout their duration. This is extremely relevant when one

considers that up to half of the mortality rate of eating disordered persons can be

attributed to cardiac complications and failure (Mehlenbeck, 2002) due to the weakening

of the individual's heart muscles and subsequent cardiac irregularities (Sobel, 2004).

Perhaps equally as troublesome is that the consequences of fasting and/or starvation as a

compensatory behavior in either anorexia or bulimia can result in structural abnormalities

in the brain that are nonreversible; even with proper refeeding and nutrition. In other

words, the individual experiences malnutrition and its physiological repercussions. Other

physical symptoms attributed to improper nutrition are kidney dysfunction, electrolyte

disturbances, dehydration, bone mineral and mass loss, and amenorrhea in anorexic

women.

Other compensatory behaviors in both anorexia and bulimia can also manifest

themselves physically. Specifically, vomiting can result in enlarged parotid and

submandibular glands, abdominal pain, dental deterioration and gum disease, and

gastrointestinal problems such as rupture. It is also ironic that some consequences of the

attempts to control one's bodily appearance such as scaring of the hands due to acid burn









marks from self-induced vomiting, easy bruising, a compromised ability to heal wounds,

breast atrophy, dry and cracking skin, lanugo, and yellowing of the skin due to

hypercartotenemia are generally related to ideals of beauty. All of the resulting physical

deficits for all forms of compensatory behaviors listed above are the body's attempt to

shut down nonessential systems in an attempt for survival (Sobel, 2004).

The physical consequences of eating disorders are severe, and in some cases life

threatening, but the psychological consequences present equal gravity. Converse to the

previously mentioned cardiac complications being responsible for up to half of all deaths,

suicide resulting from negative psychological consequences may be responsible for the

other half of the mortality rate (Mehlenbeck, 2002). Specifically, depression and

irrational and labile moods may contribute to this aspect of mortality. Other less extreme

but still serious psychological consequences are anxiety, obsessive thoughts concerning

food and weight, increased isolation, impaired judgment, low self-esteem, guilt, shame,

feelings of imperfection, diminished concentration, and feelings of loss of control

(Mehlenbeck, 2002; Sobel, 2004). A body-image distortion is also a psychological

characteristic that is necessary for an eating disorder diagnosis. Suicide is the most

serious implication, yet self-injurious behaviors such as cutting, hitting, and scratching

may also result from the psychological distress of eating disorders (Paul, Schroeter,

Dahme, & Nutzinger, 2002).

It should be noted that other eating disorders, such as binge eating disorder, do

exist and are categorized in the DSM-IV (APA, 1994) as Eating Disorders Not Otherwise

Specified. This literature review and the intentions of this thesis will only focus on the









two more common and previously described disorders of anorexia and bulimia and there

spectrums of risk, development, and prevention.

Etiology

The examination of the etiology and prevalence of eating disorders is multifaceted

and points out the methodological difficulties in identifying the development and breadth

of this problem. Cooper (1995) offers an etiological paradigm to consider the course of

eating pathology (Figure 2-1). This etiological model breaks down the process of

development, progression, and maintenance of eating disorders into three distinct stages.

Stage one examines the period from conception to the emergence of behavioral

precursors of the disorder, followed by stage two covering the period from the

development of behavioral precursors through any precipitating factors that may lead to

the onset of the full disorder, and ending with a description of how various maintaining

factors interact with protective factors and determine whether the disorder will take a

transient course or become established or chronic during stage three. Each of the stages is

described in detail below.

Stage One

Stage one primarily examines risk factors that lead to the behavioral precursors of a

disorder. During this time, the individual may be exposed to predisposing factors for the

disorder that occur prior to onset of the disorder and in turn increase the person's risk for

development of the disorder. Stice (2002) concisely organized the risk literature into a

comprehensive meta-analysis and identified which risk factors are relevant to eating

disorders. His meta-analysis found that several factors believed to place an individual at

risk were not empirically supported, while other lesser know factors did received support.

For example, childhood sexual abuse, the role of stress, control issues, dysfunctional









family systems, and deficits in parental affection are theorized as risk factors, yet

received no empirical support in this meta-analysis. These findings suggest that there is

not an individual, univariate relationship between a single risk factor and the

development of eating disorders, but rather, several factors interact to spark the

development and others may be present to move a person further along the spectrum of

development of pathology to disorder. Interestingly, individuals at risk in the presence of

pathological behaviors and their perception of these messages may encourage further

progression of eating disorders. Stice explains this by proposing a Perfectionism X Body

Dissatisfaction X Low Self-Esteem model of development of eating disorders. This

relates to Cooper's model by explaining that individuals possessing the set of factors

identified by Stice would then represent the initial stage of eating pathology.

Stage Two

Most people will exhibit some known eating disordered risk behavior, such as

fasting or restrictively dieting, and never develop an eating disorder (Tylka, 2004; Tylka

& Subich, 2002). This behavior alone does not qualify someone as having an eating

disorder. The primary goal of stage two is to examine what other factors combine and

interact with various known eating disorder risk factors, which in turn, trigger

progression into an eating disorder. Little research has examined this line of questioning.

The sparse amount of existing research is limited in that any possible contributing factors

have not been clearly documented. Furthermore, it is difficult to separate those with

eating disorder symptoms and those who will go on to develop the actual eating disorder.

Stage Three

The third stage of this model explains the course and maintenance of eating

disorders by offering three views. The cognitive view suggests that characteristic









cognitive distortions of the extreme importance of weight and shape explain most of the

features of eating disorders. Therefore treatment efforts, such as cognitive behavioral

therapy, are targeted at changing these mistaken attitudes. The second view stating that

interpersonal events shape the course of an eating disorder is based on the observation

that anorexics experiencing relationship and social changes during the course of family

therapy and bulimics experiencing the same events while engaged in interpersonal

therapy appear to have beneficial effects. These interpersonal events may enhance or

weaken self-esteem, which then lead to cognitive distortions being changed. The third

view is physiologically based and mainly pertains to anorexia. It is support by the

physiological changes that occur as a result of starvation. Some of these changes may

then perpetuate the anorexic cycle.

Cooper's etiological view offers a general understanding of how risk factors

introduce, progressively facilitate the behavioral components leading to an actual eating

disorder, and maintain the course of a disorder, but fails to consider that protective factors

may be at work in stopping this progression in the majority of individuals exhibiting risk

behaviors. Furthermore, much of the research examining this has used clinical samples of

eating disorder patients. This type of selection bias may offer insights into a

subpopulation of eating disordered individuals but not necessarily capture the true nature

of eating disorders. This bias is even more of a shortcoming in the literature given that

many eating disordered individuals do not seek treatment (Fairburn, 1995; Hoek, 1995)

and therefore are not capturing a sizable sub-population. Other methodological

considerations are that many studies do not include control groups and very few studies

have attempted to examine the occurrence of etiological factors.











SDevelopment f Establishedf
BI b Be hav Preeuro Onset Chronic
B ws-D[Lsorder


Predisposing Precipitating Maintaining
Factors Factors Factors
Stage 1 Stage2 S tage3
Figure 2-1. Etiological Model of Eating Disorder Development and Maintenance

Prevalence

Most people will face socio-cultural pressures concerning weight and exhibit some

risk factors over the course of a lifetime (Tylka, 2004; Tylka & Subich, 2002). Separating

those who experience such factors from those who go on to develop an actual eating

disorder can be difficult. Stringent criteria for diagnosis have yielded the clearest picture

of how many people are suffering from actual eating disorders. Hoek (1995; Hoek & van

Hoeken, 2003) offers a two-stage approach in determining the prevalence rates of eating

disorders. Currently, this two-stage approach is the most widely accepted approach in

determining eating disorder prevalence (Hoek & van Hoeken, 2003). Other approaches,

such as survey methods, have yielded drastically different results.

The first stage of Hoek's screening model involves administering a screening

survey to large populations of those who are considered to be at risk to determine the

number of individuals who could have an eating disorder. The second stage consists of

semi-structured interviews with those individuals who are determined to potentially have

an eating disorder. This type of rigorous screening and evaluation has shown the point

prevalence rate for anorexia nervosa is 280 per 100,000 young females (0.28%) and the

point prevalence of bulimia nervosa is 1,000 per 100,000 young females (1%; Hoek,

1995). Recent reexaminations of prevalence rates have reported similar results; 0.30%

anorexia in young females and 1% bulimia in young females (Hoek & van Hoeken,









2003). Results for males with eating disorders were reported as 5 -10% of clinical

samples of eating disordered patients thus supporting women being at higher risk than

men. The surveys used in stage one of this model also indicate that bulimic symptoms are

present in 19% of female students. This is supported by previous research reports

indicating that medical experts estimate that 16 to 30 percent of all women have practiced

bulimic behaviors (Cassell, 1994).

Closer examination of prevalence rates over a one-year period yields a more

comprehensive view of the overall prevalence of eating disorders. Table 2-1 presents

Hoek's (1995) findings. Level 0 represents the number of eating disordered individuals in

the community. Level 1 represents the number of individuals considered to have an

eating disorder by their primary health care physician. Level 2 represents the number of

eating disordered individuals receiving outpatient or inpatient treatment. In regards to the

claim that eating disorders, particularly bulimia nervosa, are secretive in nature, (Fairburn

& Cooper, 1982; Hoek, 1995) examination of the prevalence rates listed in Table 2-1

shows that only 43% of the cases of anorexia nervosa in the community are recognized

by primary care physicians and of those, 79% are referred for treatment. The

secretiveness of eating disorders becomes more apparent when you consider that only

11% of bulimics in the community were recognized by their primary care physician and

of those, only half (51%) are referred for treatment. In other words, most eating

disordered individuals do not receive adequate treatment (Hoek & van Hoeken, 2003).

Less stringent methods of prevalence evaluation yield drastically different results.

For example, Kjelsas, Bjnmstrom, and Gunnar Gdtestam (2004) administered self-report

surveys to 1987, 14 15 year old Norwegian students (1034 girls and 953 boys) in class.









Prevalence rates reported from this study were 17.9% for anorexia nervosa and 0.7% for

bulimia nervosa in girls and 0.2% for anorexia nervosa and 0.4% for bulimia nervosa in

boys. Interestingly, a 14.6% prevalence rate of eating disorder not other wise specified

was reported for the girls. This may be consistent with previously discussed results of 16

- 30 % rates of bulimic behaviors reported in the same age group (Cassell, 1994).

However, the drastic difference in anorexia nervosa prevalence rates illustrates the

importance of using strict criteria such as Hoek's two-stage model.

Table 2-1. One-Year-Period Prevalence Rates per 100,000 Young Females
Level of health care Anorexia Nervosa Bulimia Nervosa
0. Community 370 1,500
1. Primary Care 160 170
2. Mental Health Care 127 87


A major concern is that these prevalence rates and examination of prevalence of

treatment only account for those individuals whom have developed a diagnosable eating

disorder. Many others may be on their way to developing an eating disorder, thus placing

them at risk for at least some of the physical and psychological risks stated above. Tylka

and Subich (2002) found that high school and college women reported frequently

skipping meals (59%), ate fewer than 1200 calories per day (36.7%), eliminated fat

(30.1%) or carbohydrates from their diet (26.5%), fasted for more than 24 hours (25.9%),

used laxatives (7.2%), used diuretics (6.6%), and vomited after meals (4.8%). Tylka and

Subich concluded that these behaviors are similar to clinical eating disorders but without

the frequency required to be considered serious. This is similar to Thomsen, Weber, and

Brown's (2001, 2002) findings in a sample of high school girls who read women's health

and fitness magazines. They found a positive association between reading such









magazines and frequency of unhealthy weight control behaviors; specifically taking diet

pills and restricting caloric intake. The authors also found that frequent readers of such

magazines scored significantly higher on scales of eating disordered cognition. While

these results do not specifically show a relationship to diagnosable eating disorders, they

do show a relationship to the behavioral precursors to eating disorders.

Eating disorders are a serious threat to many young people's lives that, as

suggested by the differences in Hoek's three level prevalence rates, will go unnoticed and

otherwise ignored until it is much too late. The negative physical and psychological

consequences of these disorders begin to impact the individual from the onset of

development. By the time an individual is diagnosed with an eating disorder, they are

experiencing at least some of these consequences. Simply stated, the quality of these

person's lives is compromised by thoughts and behaviors that must be intervened upon.

Understanding that most of individuals developing an eating disorder will not be

recognized or seek or be referred to treatment raises an immediate need for improved

recruiting practices in this population as well as improved prevention efforts.

Furthermore, prevention of eating disorders becomes increasingly important given the

knowledge of negative behaviors such as those reported by Tylka and Subich (2002) and

their potential for development into more serious pathologies.

Prevention

If something, such as an eating disorder, can quietly affect the health and lives of so

many individuals, then the most prudent course of action would be to stop the problem

before it begins. Perhaps then the most logical approach to dealing with eating disorders

is to address the issues of primary, secondary, and tertiary prevention efforts (Caplan,

1964). Several eating disorder prevention interventions have been conducted, mostly at









the primary prevention level, producing varying degrees of success. Many early

interventions have yielded more cautious results, while recently reported interventions

have shown the most promising effects. Identifying areas in need of improvement, and

then continuing this progression of more effective prevention programs is needed to

advance the efforts of previous research.

Primary prevention efforts attempt to intervene on the population as a whole and

stop negative health behaviors before any signs of an illness are present. This goal is

accomplished in two varying methods: reactive and proactive efforts (Catalano &

Dooley, 1980). Reactive primary prevention or selective prevention (Levine & Piran,

2004) is defined as strategies that improve coping responses and augment the individual's

resistances to any potentially harmful stressors. It is selecting those who have not shown

signs of an illness or condition, but are considered to be at a higher risk. For example,

administering a vaccine for the measles to children would be considered reactive primary

prevention. On the other hand, proactive primary prevention is defined as strategies that

eliminate causal agents. Proactive primary eating disorder interventions typically target

populations that generally have not yet begun to exhibit any behavioral precursors to

eating pathology, such as elementary school and middle school students. This type of

prevention is also called universal or public health prevention because it is often

accomplished in the form of public policy or community change (Levine & Piran, 2004).

Secondary, or indicated, prevention targets those individuals whom have begun to

show signs of a problem but are not quite experiencing the full-blown problem or illness

(Levine & Piran, 2004). Secondary prevention eating disorder interventions focus on

known precursors, such as negative body image (Stice, 2002), to reduce the risk of









experiencing the full-blown disorder. The tertiary level of prevention is an attempt to

improve the course of a disease or minimize the harmful effects of an illness once it has

been diagnosed. In other words, it is basically a course of therapy or treatment for an

illness or disorder. Cognitive behavioral therapy for diagnosed eating disordered patients

is the most widely employed tertiary approach and has been extensively supported for use

in bulimia nervosa (Fairburn, 1995; Herzog et al., 1992; Vitousek, 1995).

Several studies have addressed preventing eating disorders at each of the previously

described levels. Austin's (2000) literature review and Stice and Shaw's (2004) meta-

analysis summarize a wide range of these studies and offer insight into the future of

eating disorder prevention.

Austin (2000) found that of 20 eating disorder prevention interventions, only four

reported positive behavioral changes, while 14 showed improvements in knowledge

and/or attitudes towards eating disorders and concerns about weight and shape. The main

reason these interventions have, for the most part, failed to elicit behavioral changes is "a

fundamental disjunction in the transition from theories of aetiology to theories of

prevention" (Austin, 2000; p.1256). Specifically, many of the interventions focused on

sociocultural risk factors of eating disorders, yet attempted to intervene by focusing at the

individual level. Therefore, implementing proactive primary prevention programs similar

to those commonly used in other areas of public health is the logical next step in eating

disorder prevention. Interestingly, recommendations for the prevention of public health

issues such as coronary heart disease, diabetes, osteoporosis, obesity, and cancer (CDC,

1996; USDHHS, 1990, 1996; Seidell, 1999) overlap with recommendations in the eating

disorder prevention literature (Battle & Brownell, 1996; Killen et al.,1993; Neumark-









Sztainer, 1996; Smolak & Schermer, 1998) in that they all call for programs focusing on

nutrition and exercise.

Since Austin's (2000) literature review of eating disorder prevention programs,

there has been encouraging progress in the evolution of eating disorder prevention. Stice

and Shaw's (2004) meta-analysis of 51 eating disorder prevention found that

prevention have undergone three generations of development. The preliminary research

attempted to intervene by delivering didactic psycho-educational materials which

informed general populations about the adverse health consequences of eating disorders.

The second generation of interventions was similar in that they were universally

distributed and didactic but also included socio-cultural education. The most recent

prevention programs have moved away from universal didactic approaches and focused

on delivering interactive materials and exercises to population that are at risk. Overall,

the most effective programs reduced attitudinal risk factors and promoted healthy weight

control behaviors. This is similar to Austin's (2000) recommendations as discussed

above. In contrast to Austin's proposed public health model, Stice and Shaw (2004)

recommend that programs target selected populations rather than universally intervene on

general populations. Specifically, prevention programs that were targeted, interactive,

and multi-session programs all out performed universal, didactic, and single-session

programs (Stice & Shaw, 2004).

Recruitment

Implementing a prevention program presents a unique obstacle of combining the

recommendation to target specific populations (Stice & Shaw, 2004) with the knowledge

of which risk factors constitute these populations (Stice, 2002). A general search of the

literature identified articles concerned with recruitment for a variety of other behavioral









health problems. The most relevant of which were included in a literature summary

(Lovato et al., 1997). A much broader search of the topic of recruitment shows that the

internet is a viable means of reaching large populations. A review of the eating disorder

literature found that despite a sizable body of intervention and prevention research,

amazingly, only one study has specifically addressed recruiting as its primary objective.

Recruitment is a basic and important issue for any study involving human

participants. Lovato et al. (1997) found over 4000 citations between 1987 and 1995

related to recruiting individuals for a number of studies. Most provided anecdotal reports

of recruitment efforts and little or no data to support any conclusions (Lovato et al.,

1997). The most common strategies of recruitment reported were: using patient registries,

occupational screening, direct mail, and using the media.

A more broad view of potential recruitment pathways leads one to question if

interactive technologies could be useful in reaching problem populations. The American

Psychological Association's Board of Scientific Affairs has established an advisory group

that has released a report outlining several issues related to internet research and in doing

so have provided encouraging preliminary accounts of the widespread reach of this

technology. In the section of this document pertaining only to recruitment, Kraut et al.

(2004) identify several benefits of using the internet for recruitment including low cost,

the ability to attract a large and diverse sample, and the ability for undergraduates,

graduate students, and researchers at smaller institutions to all contribute original

research. In essence, the internet has democratized data collection (Kraut et al., 2004).

Examples given include a sample of over 1.5 million completed responses collected in a

four year span (Nosek, Banaji, & Greenwald, 2002b in Kraut et al., 2004), 40,000









respondents from a link on the National Geographic website (Wellman, Quan Haase,

Witte, & Hampton, 2001 in Kraut et al., 2004), and over 18,500 responses from 3,300

participants recruited from an online video game over the course of 7 months (Kraut et

al., 2004). Clearly the internet provides a wider breadth over a shorter time period than

previously available.

Recruiting special populations, such as individuals at any point on the continuum of

pathological eating, presents its own specific challenges and therefore the common

recruitment methods listed above may or may not be entirely applicable. McDermott et

al. (2003) examined recruitment as part of a larger study involving anorexia nervosa

relapse prevention and two similar studies treating bulimic women. Advertisements in

newspapers, on radio stations, and posting flyers in various locations at a site in New

York, Minnesota, and California were the main reported methods of recruitment. This

study found that using multiple sites to recruit during shorter periods is a preferable

method of recruiting versus using fewer sites and larger windows of time.

While no studies report on this question specifically in terms of eating disorders,

several recent studies have examined interactive technologies with eating disordered

individuals. Myers et al. (2004) summarized the state of several alternative delivery

systems and new technologies employed in this population, including email, the internet,

CD-ROMS, computer software, portable computers, and virtual reality. Possible

advantages listed specifically for computer based delivery systems (email, internet, CD-

ROM, software, etc.) were: cost-effectiveness, accessibility, portability, the possibility

that they may elicit less resistance compared to face to face contact, and the ability for

simply structured programs. Email and internet delivered programs also were found to be









easier to use, have widespread and pragmatic applications, are relatively accessible, and

are very convenient for the participant. The general consensus in the literature is that

these alternative methods hold a great deal of promise when applied to eating disordered

populations (Myers et al., 2004).These conclusions are supported by a meta-analysis of

similar research finding that web-based interventions are more effective than non-web-

based interventions in producing attitudinal and behavioral changes in a variety of health

behaviors (Wantland et al, 2004).

Continuing to apply new computer based technologies to the issue of recruiting

pathologically eating populations may be a logical step based on the reported preliminary

success (Myers et al., 2004; Wantland et al., 2004). These technologies could very easily

be applied to the McDermott et al. (2003) conclusion that recruitment should focus on

many sites over a short period rather than fewer sites over a long period. Commonly

listed methods of recruitment such as advertisements, flyers, and announcements (Lovato

et al., 1997) are only seen or heard by individuals whom frequent the specific location, or

site, of the advertisement. Sampling captive audiences in this way is the traditional

method of recruiting on college campuses for a variety of studies just as sampling

inpatients is the tradition for eating disorder research (Cooper, 1995). Both the

undergraduates and the inpatients will refresh their respective population pools at the

beginning of a new semester or at new patient intakes. Therefore, recruiting enough of

either group would require longer windows of possible recruitment. Alternatively, a one

time only, web based or email announcement could be sent out to entire populations

would turn each email into its own site of recruitment. In other words, it is not limited to

only those who will be in class or pass by an advertisement or in inpatient care and thus









would not require longer amounts of time for the eligible pool to refresh itself. In

essence, this is analogous to the McDermott et al. (2003) recommendation of multiple

sites over a short period because emails or web-based announcements can reach anyone

anywhere, while the announcements and/or flyers over several semesters or the

recruitment of patients at intake are all analogous to fewer sites over longer periods of

time. Therefore, the next step in improving the recruitment of pathologically eating

populations is to examine the possibility of using new and alternative technologies to

sample populations that are larger than were traditionally accessible.

Exercise and Eating Disorders

A review of the literature reveals that the relationship between exercise and eating

disorders began with the observation of high levels of exercise in clinical samples,

questioned if exercise somehow exacerbates eating pathology, and has progressed to

understand that there are other moderating variables involved in this relationship.

Relevant research and a further explanation of each of these views are presented below.

The traditional view of the relationship between exercise and eating disorders has

primarily been based on clinical observations from the 1960s' and 1970's that 65% to

75% of anorexic patients were excessively physically active at some point during the

course of their disorder (Katz, 1996). This observation has seemed to carry over to a

more universal view of all eating disorders as opposed to staying exclusively aligned with

anorexia. Research has followed this clinical observation and has shown that there may

be some validity to this relationship. The best evidence of this comes from research

finding that strenuous exercise can suppress appetite (Rivest & Richard, 1990). Rivest

and Richard conditioned rats to become accustom to eating 3 meals per day in 8 hour

intervals. Some rats were then injected with a corticotropin-releasing factor antagonist









and other with saline. All of the rats were then forced to exercise on motorized wheels for

40 mins prior to feeding. The rats that did not receive the corticotropin-releasing factor

antagonist then began restricting the amount of food pellets they ate, while the other

groups of rats did not. It was concluded that the physiological effects of exercise were

what was suppressing the food intake of these rats. Research such as this is the

physiological basis to show the anorectic effects of exercise.

Replicating these findings in humans is difficult because forcing humans to

excessively exercise would raise ethical concerns. Still, research has focused on showing

similar effects of exercise and arrived at the same conclusion that excessive exercise may

contribute to eating disordered and pathological weight control behavior. For example,

studies such as Hoglund and Normen (2002) examined total amount of exercise in female

aerobic instructors, a group known to have high levels of total exercise. They

hypothesized that high amounts of exercise, simply defined by total hours per week,

would be associated with a strong focus on weight control and body shape. They also

hypothesized that previous experiences of anorexia or bulimia would be more common in

the high exercising group when compared to the general public of similar age and

demographic characteristics. The findings of this study suggest that the first hypothesis

concerning total amount of exercise was supported by participants reporting exercise

levels 1.5 3 times higher than that of the same population in the general public. The

high exercising group also exhibited more pathological weight control behaviors and less

body satisfaction compared to the low exercising group. The second hypothesis was also

supported by 35% of participants reporting currently or previously having an eating

disorder.









Findings such as Hoglund and Normen (2002) can only make inferences based on

two variables (exercise and presence of eating pathology). Other studies have examined

the possibility that the high amounts of exercise commonly seen in eating disordered

individuals may be a function of some other moderating influence. Davis and colleagues

have published several articles concluding that this moderating effect is likely to play a

role in exercise and pathological weight control. In a study examining the prevalence of

high exercise in an eating disordered population, Davis et al. (1997, 1999b) found that

anorexia was linked to childhood physical activity levels that were higher compared to

other children of the same age. While this alone is similar to Hoglund and Normen

(2002), these results indicated that excessive exercisers also maintained more obligatory

and pathological attitudes to exercise. This is an important result because it allows for the

possibility of some other factor interacting with the more simplistic idea of high exercise

being directly related to more pathology. Subsequent studies have indeed shown this to

be a likely possibility. Davis et al. (1998, 1999a) compared measures of high exercising

and moderately or not exercising inpatients on obsessive-compulsive symptomatology.

The reported results showed that the high exercising group exhibited greater obsessive-

compulsive symptomatology and obsessive-compulsive personality characteristics than

the group of moderate or non-exercising individuals, and that this underscores a

moderating influence of physical activity. However, it was not concluded that over

exercising is uniquely associated with greater obsessionality (Davis et al., 1999a). While

these findings do show that there is a relationship between obsessionality and eating

pathology, they failed to conclude that it was the amount of exercise that influenced

obsessionality. Future research will advance these findings by further examining the






27


relationship between exercise and eating pathology. Specifically, further examination of

the mediating and/or moderating influence of exercise on eating pathology is

recommended (Hausenblas & Fallon, 2002).














CHAPTER 3
METHODS

Participants

Participants were 330 female college students (age 17-36, M age = 19.97, SD =

2.14). Women in this age group were chosen because this cohort is at greater risk for

eating disorders compared to men of the same age, and incidences of eating disorders

typically peak during adolescence to early adulthood (Jacobi et al., 2004; Stice, 2002).

Most of this sample was Caucasian (67.3%), followed by Hispanic (13.3%), African

American (10.9%), and Asian (4.5%). About 29% of the participants were in their junior

year of school (28.8%), followed by freshman (25.2%), seniors (23.0%), and sophomores

(20.9%).

Measures

Demographic Questionnaire

Participants reported their age, year in school, course of study, ethnicity, family

income level, major in school, height, current weight, ideal weight, contact information,

eating disorder history, weekly exercise level, and where they saw the advertisement for

this study. (see Appendix A)

Drive for Thinness Subscale

The Drive for Thinness subscale of the Eating Disorder Inventory-2 (EDI-2)

measures excessive concerns with dieting and weight preoccupation. This scale are

measured by rating items on a 6-point Likert scale ranging from 1 (never) to 6 (always).

Ratings totaling a higher score indicate greater endorsement of the attitudinal and









behavioral correlates of eating disorders. Extensive research supports the validity and

reliability of the Drive for Thinness subscale (Garner, 1991). (see Appendix B)

Exercise Dependence Scale (EDS)

The EDS is a 21-item measure of exercise dependence symptoms on the following

seven subscales based on the criteria for substance dependence (American Psychiatric

Association [APA], 1994): Tolerance (e.g., I continually increase my exercise frequency

to achieve the desired effects/benefits), Withdrawal Effects (e.g., I exercise to avoid

feeling tense), Continuance (e.g., I exercise despite persistent physical problems), Lack of

Control (e.g., I am unable to reduce how intense I exercise), Reductions in Other

Activities (e.g., I think about exercise when I should be concentrating on school/work),

Time (e.g., I spend a lot of time exercising), and Intention (e.g., I exercise longer than I

expect; Hausenblas & Symons Downs, 2002). Responses to the items are on a 6-point

Likert scale ranging from 1 (never) to 6 (always). A lower score reveals less exercise

dependence symptoms. The psychometric properties of this scale are good (Hausenblas &

Symons Downs, 2002; Symons Downs, Hausenblas, & Nigg, 2004). (see Appendix C)

Body composition

Body mass index (BMI) was calculated from self-reported height and weight by

dividing weight (kg) by height (m) squared. A BMI score of 18.5-24.9 is normal weight,

25.0 29.9 is overweight, and a BMI score of 30.0 or greater is obese (ACSM, 2000).

There is however, a 5% error rate associated with BMI when used to estimate body fat

percentage compared to 3.5% error rate of skin fold calipers (ACSM, 2000).

Leisure-time Exercise Questionnaire (LTEQ)

The LTEQ is a self-report of the frequency that an individual engages in strenuous,

moderate, and mild bouts of exercise during a typical week (Godin & Shephard, 1985).









Each of the subscale scores are converted into metabolic equivalents (METS; [Mild x 3]

+ [Moderate x 5] + [Strenuous x 9]) and summed to provide an estimate of total METS

expenditure from exercise for an average week. The LTEQ has adequate reliability and

validity (Jacobs, Ainsworth, Hartman, & Leon, 1993). (see Appendix D)

Procedure

Data Collection

Participants were recruited by responding to an advertisement for larger study

examining an exercise program designed to improve physical appearance and body image

(see appendix E). This advertisement was posted throughout the month of September and

was identical regardless of where or when it was announced in the following four ways:

1. The campus announcements were 45 announcements posted on campus bulletin
boards available for posting such information for students in Turlington Plaza, on
the Reitz Union lawn, and on telephone poles adjacent to bus shelters near sorority
houses.

2. The classroom announcements were made in 12 sport and fitness classes and 4
psychology classes.

3. The website announcement was placed on my.ufl.edu, which is a secure website,
accessible only to university students.

4. The email announcement was sent once as part of a weekly list serve email which
delivers information only to undergraduate students.

Interested persons were directed to email a request for access to a secure website

containing screening questions for inclusion in this study. A standard email response

containing a unique personal identification number (PIN) and informed consent form was

sent as a reply to email requests for this study (see appendix F). At their own

convenience, participants then accessed a website containing the Leisure-time Exercise

Questionnaire (Godin & Shephard, 1985), Drive for Thinness subscale of the EDI-2

(Garner, 1991), the Exercise Dependence Scale (Hausenblas & Symons Downs, 2002),









and demographic questions. A follow-up email reply was sent to all participants after the

data were analyzed. Individuals who met eligibility criteria for the exercise intervention

were then invited to join the program (see appendix G), while all others were thanked for

their time and participation (see appendix H). Study flow is presented in Figure 3-1. This

study was completed over the course of one academic semester. The timeline for this

study is presented in Table 3-1.

Study
Announcement

Email Inquiry

Email reply

Website survey

Data Analysis

SFollow-up Reply
Figure 3-1. Study Flow


Table 3-1. Thesis Timeline.
September October November
Month 1 Month 2 Month 3

Study Announcement X

Participant Inquiry X

Email Reply X

Web Based Assessment X

Data Analysis X

Follow-up Reply X X

Preparing and Reporting Results X X










Primary Purpose

Eligibility Criteria

To obtain a targeted population of women at-risk for an eating disorder, I used the

following eligibility criteria.

1. Low Active Only those participants who were exercising 4 or fewer times per
week were selected. The total amount of exercise per week was measured by the
Leisure-time Exercise Questionnaire, as well as an open ended question in the
demographic section of the survey simply asking, "How many times a week do you
exercise?". The screening website allowed for alphanumeric data entry on LTEQ
questions. Through this it was found that 52 participants (15.75%) included
qualitative data stating that they were reporting inappropriate physical activity,
rather than exercise behavior, in the LTEQ and therefore were over reporting total
weekly exercise amount. Examples of these responses are: depends, varies, walking
to class, ideally once or twice, sometimes, sporadically, whenever I a in the mood,
and the days that I am late to class. The single exercise behavior question was
chosen to determine eligibility because it was apparent that LTEQ questions were
not accurately capturing the nature of exercise in this sample. (see chapter 4 results
section for statistical justifications) The total weekly amount of exercising 4 times
or less was chosen because it reflected that these individuals were not meeting
ACSM (2000) criteria for total weekly exercise. Research has shown that single
item measures of exercise behavior have reasonable validity (Schectman et al.,
1991; Prochaska et al., 2001; Weiss et al., 1990).

2. Drive for Thinness Drive for Thinness score cutoffs of 8 or greater were chosen
because this reflects the 75th percentile and therefore indicates a risk for
developing eating disorders (Garner, 1991). A score of 14 or greater, or the 91st
percentile, on the Drive for Thinness would typically be used to indicate the
potential of more serious risk of eating pathology (Garner, 1991).

3. Body Mass Body Mass Index (BMI) scores between 18.5 and 29.9 were used as
an eligibility criterion. This range is considered the normal to overweight range
(ACSM, 2000) and was chosen because normal to overweight women are at a
higher risk for the development of eating disorder (Jacobi et al., 2004).

Data Analysis

Measures of internal consistency were performed on the Exercise Dependence scale

and the Drive for Thinness subscale. Descriptive statistics and frequencies were also


performed on all relevant variables.









A 4 (recruitment levels campus announcements, classroom announcements,

website announcement, email announcement) x 2 (eligible or ineligible) ANOVA was

performed to determine if individuals meeting eligibility criteria were more prevalent

from any of the four methods of recruitment examined. A one-way ANOVA was used to

determine differences in self-reported exercise from the two previously discussed

questions measuring exercise behavior. Similarly, a one-way ANOVA was used to

examine how responses to these questions would affect eligibility rates. Finally, an

independent sample t test was performed to determine if new alternative methods of

recruitment gathered significantly more eligible individuals than traditional methods of

recruitment.

Secondary Purpose

The procedure for the secondary purpose of this thesis, examining the hypothesized

relationship of Leisure-time Exercise scores (LTEQ), Exercise Dependence scores (EDS)

and Drive for Thinness (DT) scores, was followed as detailed by Baron and Kenny

(1986). My independent variables were LTEQ scores and EDS scores and my dependent

variable was DT scores. First, correlations were used to determine the relationship

between the independent and dependent variables. A significant correlation indicates a

mediator effect, while a nonsignificant correlation indicates a moderator effect (Baron &

Kenny, 1986). See figures 3-2 and 3-3.












flrs nation


Figue 32 R ad o qufiato ri
Figure 3-2 Relationship of Mediator Variables


Independent
Variable
X
Moderator
Variable


Figure 3-3 Relationship of Moderator Variables














CHAPTER 4
RESULTS

Response Rate

Four hundred forty eight individuals responded to the announcement and sent

emails indicating interest in the study. All 448 were sent an email reply including a

personal identification number (PIN) to access the website (see appendix F). Twenty

participants (4.5%) lost or misused there PIN when logging in and emailed a request for a

new PIN. Eight participants (1.8%) wrote back explicitly saying they would not like to

continue with the study. A total of 330 participants (73.7%) accessed and completed the

website questionnaires.

Primary Purpose

First, descriptive statistics such as means, standard deviations, frequencies, and

alpha values, were conducted for the primary purpose study variables. (See Tables 4-1 -

4-2.) The eligibility criterion was then calculated resulting in 87 eligible and 241

ineligible individuals. A 4 (recruitment levels) x 2 (eligible or ineligible) ANOVA was

performed to determine if individuals meeting eligibility criteria were more prevalent

from any of the six methods of recruitment examined. Two recruitment groups ("found

out from a friend" and "other") were not included in this analysis because only 2

individuals were recruited from each. No significant influence of method of recruitment

on eligibility was found, F (3, 319) = 1.04, p = .38. A Pearson chi-square test also

revealed that the recruitment groups did not differ significantly for eligibility [x2 (3) =

3.12, p = .37].









Table 4-1 Means, Standard Deviations, and Alpha Values
Variable M SD a
Exercise per week (single question) 2.21 1.71
LTEQ 36.81 23.02
EDS 40.63 13.09 .93
DT 6.68 6.00 .88
BMI 25.16 4.77
Age 19.97 2.14


Table 4-2 Frequency of Recruitment Method
Announcement Frequency Percent
Ad posted on campus 12 3.6
Ad posted on my.ufl.edu 17 5.2
Classroom announcement 67 20.3
From a friend 2 0.6
Wednesday Update email 229 69.4
Other (unspecified) 2 0.6
Missing 1 0.3
Total 330 100.0


A one-way ANOVA was used to determine differences in self-reported exercise

from the two questions measuring exercise behavior (LTEQ and a single question). This

ANOVA compared the amount of exercise reported in the Leisure-Time Exercise

Questionnaire (LTEQ) and the single question, "How many times a week do you

exercise". The dependent variable was frequency of exercise reported and the

independent variable was which question the frequency was measured by. I found that the

self-reported total amount of exercise per week was significantly lower when reported

through a single question than by the total of strenuous and moderate exercise measured

by the LTEQ [F (1, 647) = 207.96, p = .001]. These results also indicated that a

significant positive correlation existed between these two variables [r = 621, p =.001].

This self-report of exercise was important in the determination of eligibility. A one way

ANOVA was used to examine how responses to these questions would affect eligibility









rates. The dependent variable was eligibility and the independent variable was which

question the exercise frequency was used to determine eligibility. I found that using the

single question to measure weekly exercise behavior yielded more eligible persons than

by using the LTEQ [F (1, 647) = 207.96, p = .001]. In other words, the lower amounts of

exercise reported by the single question indicated more inactive, and therefore eligible,

persons than did the LTEQ.

Finally, an independent sample t test was performed to determine if new alternative

methods of recruitment gathered significantly more eligible individuals than traditional

methods of recruitment. Alternative methods were defined as announcements posted on

the internet website and the email announcement. Traditional methods were defined as

announcements posted on campus and announcements made in classrooms. The two

other levels of the recruitment variable ("from a friend" and "other") were excluded due

to the uncertainty of where the announcement was originally seen. The independent

variable was method of recruitment (traditional or alternative), and the dependent

variable was eligibility. The Levene's test for equality of variance was significant [F=

14.344, p = .01], therefore the equal variances not assumed statistic was used to interpret

the t test. Traditional and alternative methods of recruitment were not significantly

different in their ability to reach eligible participants [t (146.761) = -1.823, p = .07].

Secondary Purpose

Correlations were performed between exercise dependence scores (EDS), drive for

thinness scores (DT), and Leisure-Time Exercise Questionnaire scores (LTEQ). I found

that all of the variables were significantly correlated. That is LTEQ was significantly

correlated with EDS scores [r = .440, p =.001], followed by EDS and DT being

significantly correlated [r = .207, p =.001], and LTEQ being significantly correlated with









DT [r = .149, p =.008]. Because LTEQ and DT score were significantly correlated and

LTEQ and EDS scores were also significantly correlated, mediation was assumed and a

three-step mediation model was followed (Baron & Kenny, 1986). Furthermore, exercise

and exercise dependence exhibit a temporal relationship with exercise preceding exercise

dependence (Hausenblas & Symons Downs, 2002; Symons Downs, Hausenblas, & Nigg,

2004). This is also an indication that the relationship may potentially be that of a

mediator and not a moderator (Baron & Kenny, 1986; Kreamer et al., 2001). This model

outlines that three forced entry regressions must be performed. First, a simple linear

regression with forced entry was performed with EDS (dependent variable) regressed on

LTEQ (independent variable). Results of this regression showed that higher LTEQ scores

(P = .440, p = .001) resulted in higher exercise dependence scores [F (1,306) = 73.38, p =

.001]; with 19.3% of the variance in exercise dependence explained by LTEQ. Next, DT

(dependent variable) was regressed on LTEQ (Independent variable). Results of this

regression showed that higher LTEQ scores (P = .149, p = .008) resulted in higher drive

for thinness scores [F (1,312) = 7.12, p = .008]; with 2.2% of the variance in exercise

dependence explained by LTEQ. Finally, a forced entry multiple regression was

performed with DT (dependent variable) regressed on LTEQ and EDS (independent

variables). This regression found that EDS and LTEQ explained 4.6% of the variance in

drive for thinness scores [F (2,296) = 7.06, p = .001], with only EDS scores being a

significant predictor of DT (P = .180, p = .005).

For mediation to be found, the independent variable in the first regression (LTEQ)

must affect the mediator (EDS). The second regression must show that the independent

variable (LTEQ) must affect the dependent, or outcome, variable (DT). Finally, the third






39


regression must show that mediator (EDS) affects the dependent variable (DT). If the

beta of the independent variable becomes non significant, then there is complete

mediation (Baron & Kenny, 1986). Based on these criteria and the results of these three

regressions, a full mediator effect for EDS on the relationship of LTEQ and DT was

found.














CHAPTER 5
DISCUSSION

Overview

The purpose of this thesis was twofold. First, the ability to effectively recruit a

population of college age women dissatisfied with their body was examined. Specifically,

traditional modes of recruitment, such as verbal announcements and campus postings

were compared to announcements, made on newer, alternative mediums such as the

internet and email. I hypothesized that these alternative channels of recruitment would

produce both more interest and more individuals indicating potential risk for the

development of eating pathology. While this hypothesis was not statistically supported,

the raw data did show that the alternative channels of recruitment do cover a substantial

breadth of potential participants. Second, the relationship between exercise, exercise

dependence, and drive for thinness was examined. I hypothesized that exercise

dependence would affect the relationship between exercise and drive for thinness. This

hypothesis was fully supported. A more detailed description of my study findings,

limitations, and future research directions are discussed below.

Study Findings

Recruitment

The results of this study indicated that there is no significant difference of how or

where participants are recruited on the amount of potentially at risk individuals that are

reachable by each recruitment pathway. While these results are not significant

statistically, they are of note practically because these results were approaching









significance [p = .07]. The relatively small sample size of this study may have

contributed to these results by lowering the power of these analyses.

Researchers concluded that recruitment efforts should be short in duration and

widespread (McDermott et al., 2003); and that alternative technologies may be a viable

means of achieving these recommendations (Kraut et al., 2004; Myers et al., 2004;

Nosek, Banaji, & Greenwald, 2002). This study supports both of these conclusions. The

announcement of this study was short in its duration (one month) and focused on

reaching a vast number of individuals. McDermott et al. (2003) similarly concluded that

recruitment advertisements should be posted at more sites over shorter lengths of time.

Each email acted as its own site, just as the more usual sites of campus billboards and

classroom announcements were there own sites. Specifically, the advertisement posted on

a website acted similar to an ad posted on a campus billboard. Take for example each

advertisement posted on an internet webpage (i.e. my.ufl.edu) or on campus billboards,

both may have the potential for many to be in the presence of the announcement. In other

words, they are more passively there for anyone to see. Accordingly, each produced a

similar number of respondents (12 from ads posted on campus, 17 from ads posted on

my.ufl.edu). The difference is that the website based posting was one ad, whereas the

campus based postings were about 50 ads. Conversely, an in class announcement or

email is proactively forced upon an individual. The difference to consider is the total

population available to be actively advertised to. Classes are limited to the number of

students enrolled or the number of students in as many classes that announcements can be

made in. Emails, however, are limited to only the number of people a email is sent to.

Each classroom, regardless of the number of students in it becomes one singular site with









x number of potential participants. Each email becomes one site with one potentially

potential participant (possibly more if he or she talks to others about the opportunity).

This closely follows McDermott's (2003) suggestion of increasing the number of places

that each advertisement is made. The recruitment data from this study, while not

statistically significant, does practically support McDermott by the number of

participants recruited via emails (n = 229) being almost 3.5 times larger than the number

returned from in-class announcements (n = 67).

A more contemporary view of social evolution is also evident by comparing the

recommendations of the literature to the findings of this study (Kraut et al., 2004; Myers

et al., 2004). In 1985 only 8.2% of the US population had a computer. By 2001 that

number increased to 66% of the US population having access to a computer and 56% of

Americans having access to the internet (Kraut et al., 2004). Clearly this technology is

expanding exponentially and simultaneously changing the delivery of information to

most Americans. As evident by the results of the breadth of alternative methods of

recruitment in this study, this increase in computer and internet usage is a growing

resource to contact and intervene on populations. Simply, remaining with the status quo

of sampling convenient populations such as college classes, may not be keeping with the

changing times.

Much attention has been given to the fact that eating disorders generally develop

very quietly (Fairburn & Cooper, 1982; Hoek, 1995) and at a young age (Jacobi et al.,

2004; Stice, 2002), thus making intervention difficult. Cooper (1995) outlined this by

elucidating the stages of development, beginning with behavioral precursors,

transitioning into risk factors, and finally progressing onto full syndrome disorder.









Examining new methods of effectively recruiting potentially at-risk populations is

analogous to finding new ways of intervening at Cooper's (1995) first stage of

development. In other words, sampling a population, such as college women, that is

known to show behavioral precursors (Cassell, 1994; Franko et al., 2005; Tylka &

Subich, 2002; Tylka, 2004) allows the opportunity to access and halt the development of

precursors of risk that the individual may or may not be aware of. Alternative

technologies, such as the internet, offer the possibility of reaching far more people than

previously available, yet little attention has focused on exploiting the advantages of them

(Kraut et al., 2004; Myers et al., 2004).

Mediator Effect

The secondary purpose of my thesis was to examine the relationship between

exercise, exercise dependence, and drive for thinness. Researchers have recommended

that a mediating and/or moderating relationship of such variables be examined

(Hausenblas & Fallon, 2002). Both mediators and moderators are types of variables that

may affect the association between two other variables. Both variables have been

confused, mistakenly referred to, and wrongly identified (Baron & Kenny, 1986;

Kraemer et al., 2001). To help clarify, I will first describe both mediators and moderators,

then continue by using the variables of interest in this thesis as examples to discuss the

difference of the two and why a mediator effect, but not a moderator effect, was

examined.

A mediator is any variable that explains the how or why a relationship exists, while

a moderator is any variable that specifies on whom or under which conditions (when) a

relationship exists (Baron & Kenny, 1986; Bennet, 2000; Kraemer et al., 2001). A

potentially mediating variable (exercise dependence) must be correlated to the









independent variable (exercise) and a potentially moderating variable (exercise

dependence) must not be correlated to an independent (exercise) or dependent variable

(drive for thinness; See figures 5-1 and 5-2.). Put another way, a mediator is a variable

that is present and correlated to the independent variable, which helps to explain how or

why the independent variable affects the dependent variable. A moderator is a different

variable, uncorrelated to the independent or dependent variable, that when present

explains to whom or when a relationship occurs.


Independent Outcome
Variable I Variable


Moderator
Variable
Figure 5-1 Moderator Model


independent -. Mediator .. Outcome
Variable Variable Variable
Figure 5-2 Mediator Model

In my study, the relationship between exercise, as an independent variable, and

drive for thinness, as an outcome or dependent variable, was in question. The relationship

between exercise and exercise dependence in this thesis was correlated. This correlation

is similar to previous research (Zmijewski & Howard, 2003). Because of the correlation

between these two variables, examining a possible mediator effect of exercise

dependence on the relationship between exercise and drive for thinness was the

appropriate analysis. This method specifies that three regressions must meet the

following conditions to show a mediator effect (Baron & Kenny, 1986):

4. Variations in the independent variable significantly account for variations in the
mediator variable (figure 5-3, path a),










5. Variations in the mediator variable significantly account for the dependent variable
(figure5-3, path b),

6. When both path a and b are controlled, the significant relationship observed in
independent and dependent variables disappears. (figure 5-3, path c).

Figure 5-3 illustrates this conceptually, while figure 5-4 illustrates this with my thesis's

variables and results.

^a diator Variable b

Indepndene c________ __ Dependent (Outcome)
Variable Variable

Figure 5-3 Conceptual Model of Mediation.

Firstreg ssion irdrel ssian
P = .440 = .001 EDS P= .180,P=.005


LTEQ _DT
Secoil re ge ssion
S= .149,p =.008
Third re re sin
= J59,p= .354
Figure 5-4 Conceptual Model of Mediation with Study Variables

These results build upon the recommendations of previous research by examining a

potential mediating or moderating effect of exercise dependence on eating pathology

(Hausenblas & Fallon, 2002). Furthermore, they improve upon research examining the

relationship of the same variables (Zmijewski & Howard, 2003). These results may also

help clarify the confused relationship of exercise with eating disorders by demonstrating

evidence of a mediating affect of exercise dependence as a means in which exercise

becomes problematic for eating disordered individuals. Specifically, a mediator is a

variable that explains how or why another variable affects the outcome (Baron & Kenny,

1986; Kraemer et al., 2001). The basic question in my thesis then is, how does exercise

affect eating pathology? The potential mediator, exercise dependence, is examined to see

if its presence will affect the outcome of exercise on eating pathology. This is shown









statistically by the three paths described above. Simply stated, there are two causal paths

on the dependent variable (Baron & Kenny, 1986). Path c represents the direct impact of

the exercise on driver for thinness, and path b represents the impact of the exercise

dependence also on drive for thinness. Separately, both of these paths show that exercise

and exercise dependence affect drive for thinness. When the mediating variable paths are

controlled, the significant relationship between exercise and drive for thinness is no

longer significant. Therefore, answer to the question, how does exercise affect eating

pathology?, is answered by these analyses showing that the affect of exercise on drive for

thinness is mediated by exercise dependence.

Limitations

Several limitations were present in my study. The most obvious limitation is the

capabilities of alternative technologies. For example, many participants took the liberty

of reporting qualitative data in inappropriate areas, specifically when reporting exercise

amounts. While this data was useful in allowing for a better inference of what the

participants were reporting, it points out that computer based technologies are very exact.

In other words, they will only perform in the very specific manner as programmed.

Future research involving the use of websites or computer based interactions with

participants should be very careful to program places for participants to enter data in a

way that does not allow for confused reporting. For example, amount of exercise should

only been allowed to be entered as numeric data, not as alphanumeric data.

A similar limitation of alternative technologies is how many people are actually

using them. In other words, does recruiting via alternative methods, such as email and

internet websites, accurately capture the targeted population? The most recent U.S.

Census report on computer and internet usage (Cheeseman Day, Janus, & Davis, 2005)









states that in 2003, 47.1% of all 15-24 year old Americans had internet access in their

home. Furthermore, 89.4% of all 18-24 year olds enrolled in school were using

computers, while 70.6% of all 18-24 year olds enrolled in school were using the internet.

These data support that most of the 10-30% of college age women whom are at risk of

developing eating disorders (Cassell, 1994; Franko et al., 2005) can be reached by

alternative technologies.

Several researchers have reported that women overestimate the amount of total

exercise duration (Buchowski et al.,1999; Irwin et al., 2001; & Jakicic et al., 1998).

Specifically, this overestimation has been found in women with higher percentage of

body fat. The BMI of the sample in my thesis was in the overweight range (ACSM,

2000). Therefore, using self-report measures of exercise behavior is another limitation of

my thesis. Similarly, using other self-report measures for eating disordered behavior was

also a limitation of my thesis.

A limitation that was potentially present and somewhat related to the first limitation

is the look and feel of a website. While it was not reported back to me that the drab gray

color and simplistic design and layout of the questions was a problem for participants,

some participants did have trouble initially accessing the website via the PIN login

screen. This may or may not have been because of the onscreen layout. What was a

noticeable limitation of this website's layout was the inability to format instructions and

questions correctly. For example, the instructions for the LTEQ and the first question in

this scale were run together. These instructions are rather lengthy and can be hard on the

eyes when viewed onscreen. Moreover, the length of the website may have been a

problem. Allowing for screen breaks, font changes, deliberate spacing, or even just









placing pictures or changing background colors may have helped with the website's

usability.

A fourth limitation was time to respond to the large number of interested

individuals contacting me for access to this study. The announcement made via email to

all University of Florida students resulted in a deluge of inquiries in my inbox

immediately following the transmission of the email announcement. Several interested

individuals even email multiple times a day until they received a PIN. This perhaps

speaks to the previously discussed changing nature of our society and the role of the

internet in it. People are increasingly becoming accustomed to instant responses and

interactions. Allowing a day or two to respond to an email may have been acceptable

etiquette in the past, but the increasingly fast paced and quick response nature of

interactive technologies, such as the internet, is slowly conditioning people to expect

more sooner. Potential solutions to this problem will be discussed in the future directions

section of this thesis.

A fifth limitation pertains to the findings of the mediator effect of exercise

dependence. These data came from participants whom were recruited via advertisements

for an exercise program for women dissatisfied with their bodies. This population of

college females may not be truly representative of a general population in regards to

exercise behavior, exercise dependence, and/or drive for thinness scores. Specifically,

past research has identified the onset of development of eating disorder pathology at

earlier ages than of this sample (Jacobi et al., 2004; Stice, 2002; Thomsen, Weber &

Brown, 2001; 2002). Any interpretation of these data should be mindful and considerate

of the population from which this data was collected.









Future Directions

Several adjustments are needed in any future research continuing to build upon

these data. First, any future research using a website based method of data collection

should be more aesthetically pleasing and user friendly than the one used in this thesis.

Future studies measuring participants on more scales or questionnaires than the ones use

in this thesis must be particularly concerned with this and consider how such

improvements in usability may ease the burden of participation. Standards for protecting

and securely storing computerized data must be kept, but not at the expense of usability

and convenience for the participant.

Time was also discussed as a limitation of this study. Any future directions of

similar research should use expert systems to help ease the management of data

collection and standardized responses sent to participants. An expert system is defined as

any software based program that can mimic the deductive or inductive reasoning of a

human expert (Negotia, 1985). These systems can use algorithms to make decisions

based on entered data and be quite sophisticated. Something as simple as the ability to

review data and send and automated reply to participants would be of extreme

convenience to both the researcher and the participant. For example, in this thesis having

a simple expert system that could have reviewed data collected from the website and

made a decision as to which email to send a participant (either informing them of there

potential eligible status for future studies or not) would have been paramount in time and

data management.

A third future direction involves the email method of announcing the study.

Everyday our email inboxes are bombarded with unsolicited advertisements and junk

mail commonly referred to as spam. Not only are these unwanted emails annoying, but









many may carry the risk of infecting and crippling your computer from attached viruses.

The email for this study was sent through a listserve, or list of email addresses

encompassing all University of Florida undergraduates, designed to inform the student

body of a variety of events on campus. The response rate was substantially greater than

any other method of recruitment measure, but was still low considering that it was sent to

thousands of students. Emails such as these, even though they are sent from familiar and

reputable sources, may be discarded along with any other junk mail of the day. A future

direction to help alleviate this problem is to examine what factors would lead to students

taking better advantage of emails, such as the one announcing this study, that inform

them of opportunities at the university rather than deleting them without reading them.

Creating a listserve solely announcing research opportunities may be a way to reach only

those students whom are willing to participate in future studies.

Future research is also needed to further examine the mediator relationship that was

found in this thesis. Efforts should focus on recruiting a more representative cross section

of the population. Future research should also examine these relationships in samples of

men. Similarly, announcements should not focus solely on recruiting those whom are

currently dissatisfied with their body. While this was acceptable for the purposes of this

thesis, future research should focus on recruiting a sample that is more representative of

the general population.

Finally, a limitation discussed above was that this study used self-report measures

of exercise behavior and eating disorder risk. Future studies should use more objective

methods of collecting similar data. For example, accelerometers could be used to collect









more accurate data on exercise behavior and clinical interviews could be used to more

accurately determine eating disorder risk status.

Conclusions

This study illustrated the importance of using new technologies and alternative

methods to recruit a large number of individuals in a short time, thus supporting

recommendations researchers (McDermont et al., 2003) and emphasizing advantages of

computer based research (Kraut et al., 2004; Myers et al., 2004). Using such methods was

not shown to be statistically different than more traditional methods of announcing

research, but did show that there is potential for reaching large numbers of people while

being convenient for both the researcher and the participant. This study also improved

upon previous research finding that exercise dependence is correlated with bulimia

subscale scores in female undergraduate college students (Zmijewski & Howard, 2003)

by further examining the relationship between exercise and eating pathology based on the

recommendation to examine moderator and mediator effects of these variables

(Hausenblas & Fallon, 2002). Eating disorders are serious and secretive both in their

development and their course, (Cassell, 1994; Fairburn, 1995; Hoek, 1995; & Hoek &

van Hoeken, 2003) thus necessitating the need for further research to identify better ways

of recruiting this special population.














APPENDIX A
DEMOGRAPHIC QUESTIONS

What is your age?

Please type how many feet tall you are.

Inches?

What is your current weight?

What is your ideal weight? (The weight you would like to be at right now.)

What year in school are you?

What is your major?

What is your family's annual income?

What is your ethnic background?

If you selected "other" ethnic background, please type your ethnic background here.

What is your first name?

What is your email address? (Please type an email account that you check regularly.)

What is your phone number?

How many times a week do you exercise?

Have you ever been diagnosed with an eating disorder?

Do you currently have an eating disorder?

What is your gender?

Where did you hear about this study?














APPENDIX B
DRIVE FOR THINNESS QUESTIONNAIRE

Instructions: This is a scale which measures a variety of attitudes, feelings, and
behaviors. Read each question carefully and circle the number to the right of the
question which applied best to you.

Please use the following scale:







1. I eat sweets and carbohydrates without feeling nervous. 1 2 3 4 5 6

2. If I gain a pound, I worry that I will keep gaining. 1 2 3 4 5 6

3. I think about dieting. 1 2 3 4 5 6

4. I am terrified of gaining weight. 1 2 3 4 5 6

5. I exaggerate or magnify the importance of weight. 1 2 3 4 5 6

6. I am preoccupied with the desire to be thinner. 1 2 3 4 5 6

7. I feel extremely guilty after overeating. 1 2 3 4 5 6














APPENDIX C
EXERCISE DEPENDENCE QUESTIONNAIRE

Instructions. Using the scale provided below, please complete the following
questions as honestly as possible. The questions refer to current exercise beliefs and
behaviors that have occurred in the past 3 months. Please place your answers in the
blank space provided after each statement.


1 2 3 4 5 6
Always Never


1. I exercise to avoid feeling irritable.
2. I exercise despite recurring physical problems.
3. I continually increase my exercise intensity to achieve the desired effects/benefits.
4. I am unable to reduce how long I exercise.
5. I would rather exercise than spend time with my family/friends.
6. I spend a lot of time exercising.
7. I exercise longer than I intend.
8. I exercise to avoid feeling anxious.
9. I exercise when injured.
10. I continually increase my exercise frequency to achieve the desired
effects/benefits.
11. I am unable to reduce how often I exercise.
12. I think about exercise when I should be concentrating on school/work.
13. I spend most of my free time exercising.
14. I exercise longer than I expect.
15. I exercise to avoid feeling tense.
16. I exercise despite persistent physical problems.
17. I continually increase my exercise duration to achieve the desired
effects/benefits.
18. I am unable to reduce how intense I exercise.
19. I choose to exercise so I can get out of spending time with family/friends.
20. A great deal of my time is spent exercising.
21. I exercise longer than I plan.














APPENDIX D
LEISURE TIME EXERCISE QUESTIONNAIRE

Instructions. This is a scale which measures your leisure-time exercise (i.e.,
exercise that was done during your free time such as intramural sports-NOT your
physical education class). Considering a typical week, please indicate how often
(on average) you have engaged in strenuous, moderate, and mild exercise more that
20 minutes during your free time?

1. Strenuous exercise: heart beats rapidly (running, basketball, jogging, hockey, squash,
judo, roller skating, vigorous swimming, vigorous long distance bicycling, vigorous
aerobic dance classes, heavy weight training)

How many times per typical week do you perform strenuous exercise for 20 minutes or
longer?

2. Moderate exercise: not exhausting, light sweating (fast walking, baseball, tennis, easy
bicycling, volleyball, badminton, easy swimming, popular and folk dancing)

How many times per typical week do you perform moderate exercise for 20 minutes or
longer?

3. Mild exercise: minimal effort, no sweating (easy walking, yoga, archery, fishing,
bowling, lawn bowling, shuffleboard, horseshoes, golf)

How many times per typical week do you perform mild exercise for 20 minutes or
longer?











APPENDIX E
STUDY ANNOUNCEMENT

Are you dissatisfied with your

body? Would you like to get into

better shape?

Are you dissatisfied with your body? Would you like to get into better shape? The
exercise psychology lab in the Department of Applied Physiology and Kinesiology
is looking for female students who are interested in participating in an exercise
program designed to improve your physical appearance and body image. Please
contact the exercise psych lab at exer.psych.lab@hhp.ufl.edu to complete a short
web based questionnaire to determine your study eligibility.















APPENDIX F
REPLY WITH PIN AND INFORMED CONSENT

Thank you very much for your interest in this study! Please visit the following
website to complete our eligibility questionnaire,
http://survey.hhp.ufl.edu/index.php?id=65 Your PIN login in for this study is
XXXXXX. Enter this PIN when prompted and click on the "Begin the Survey" box.
Simply pressing enter after entering your PIN may not work. Please complete all
of the survey questions. This survey is only accessible through the unique
password that has been emailed to you and cannot be used more than once. Do
not give your PIN to anyone else to use. Please complete the entire survey in
one session. If you need to stop or are disconnected before you have completed
the survey, email the exercise psychology lab at exer.psych.lab@hhp.ufl.edu and
we will respond with a new PIN for you to use.

A consent form explaining this study and whom to contact if you have any
questions is provided below. Please review this form. Please reply to this email if
you decide not to participate after reading this form.

Thank you again for your interest in this study,

The exercise psychology lab.

INFORMED CONSENT

PLEASE READ THIS ENTIRE DOCUMENT CAREFULLY BEFORE YOU DECIDE TO
PARTICIPATE IN THIS STUDY.

TO: All Research Participants
FROM: Brian Cook
RE: Informed Consent

PURPOSE OF THIS STATEMENT: The purpose of this statement is to summarize the study I
am conducting, explain what I am asking you to do, and to assure you that the information you
and other participants share will be kept confidential to the extent permitted by law. Specifically,
nobody besides the principal investigator and the research assistants will be able to identify you
in this study and your name will not be used in any research reports that result from this project.

WHAT YOU WILL BE ASKED TO DO: If you agree to participate in this study, you will be
asked to complete a few questionnaires via the web. Based on your responses to these measures,
you may be contacted by a research assistant to participate in an exercise intervention.

TIME RQUIRED: Completion of the measures will take no more than 10 minutes.










RISKS AND BENEFITS: There are no risks expected from participating in this study. There are
no direct benefits to you for participating in this study.

COMPENSATION: You will not be compensated monetarily for your participation in this
study. You may be given extra credit by your instructor for completing this study.

CONFIDENTIALITY: Your identity will be kept confidential to the extent provided by law.
Your information will be assigned a code number. The list connecting your name to this number
will be kept in my laboratory (Room 145 Florida Gym) in a locked file cabinet. When the study is
complete and the data have been analyzed all materials will be destroyed. Your name will not be
used in any report.

VOLUNTARY PARTICIPATION: Your participation in this study is completely voluntary.
There is no penalty for not participating.

RIGHT TO WITHDRAW: You have the right to withdraw from the study at anytime without
consequence.

WHOM TO CONTACT IF YOU HAVE QUESTIONS ABOUT THIS STUDY: Brian Cook,
Department of Applied Physiology and Kinesiology. Email: bcook@hhp.ufl.edu. Heather
Hausenblas, Department of Applied Physiology and Kinesiology. Email: heatherh@hhp.ufl.edu.

WHOM TO CONTACT ABOUT YOUR RIGHTS AS A RESEARCH PARTICIPANT IN
THE STUDY: UFIRB Office, Box 112250, University of Florida, Gainesville, FL 32611-2250;
phone 352-392-0433.

AGREEMENT: I have read the procedure described above. I voluntarily agree to participate in
the procedure. By clicking here I am giving my consent to participate in this study.














APPENDIX G
ELIGIBLE RESPONSE

Dear (insert first name here) ,

Recently you completed a web-based screening questionnaire for an upcoming
exercise program designed to improve your physical appearance and body image. Based
on your responses, you have met the preliminary criteria for inclusion in this program.
The program is scheduled to begin at the start of the spring 2006 semester. Please
reply to this email and let us know:
1.) If you are still interested in this program.
2.) If you will be able to complete the 6 month exercise program, as well as a 6
month follow up.
3.) What times) will be the best for you to participate in this exercise program?
Specify if mornings, days, and/or evenings will work best for you. Please
consider your class and academic responsibilities, work responsibilities,
family obligations, and any other time restraints that you will have next
semester.

Prior to the beginning of this program, everyone will be randomized into either the
intervention or the control group. Everyone has an equal chance of being in either group.
You will receive notification of which group you are a part of. Thank you for your
interest and participation in this study.

The Exercise Psychology Laboratory














APPENDIX H
INELIGIBLE RESPONSE

Dear (insert first name here) ,

Recently you completed a web-based screening questionnaire for an upcoming
exercise program designed to improve your physical appearance and body image.
Unfortunately, based on your responses, you have not met the preliminary criteria for
inclusion in this program. We may contact you in the future if other similar programs
begin that may be better suited for you. Please reply to this email if you would not like to
be contacted for any future studies. Thank you for your interest and participation in this
study.

The Exercise Psychology Laboratory















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BIOGRAPHICAL SKETCH

Brian was raised in Cumberland, Rhode Island, and attended high school at Mount

Saint Charles Academy in Woonsocket, Rhode Island. He began his undergraduate

education at Johnson State College in Johnson, Vermont, where he majored in

psychology and competed on the men's varsity cross country and tennis teams. At the

conclusion of his freshman year, he transferred to the University of Rhode Island to focus

on his psychology major. After graduating from the University of Rhode Island, he

worked as a project assistant at ProChange Behavior Systems, Inc., in West Kingston,

Rhode Island. Brian enrolled at the University of Florida in the fall semester of 2003.