Case Study: Gender and Feeding and Eating Disorders

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Baring her naked, 60-pound figure, French model Isabella Caro posed for a series of advertisements warning of the dangers of eating disorders. Suffering from Anorexia Nervosa, Caro's photos captured the grim physical and mental effects of the eating disorder. Her gaunt frame and vacant, hopeless stare conveyed the life of many who suffer from the disorder (Grimes, 2010). Typically, eating disorders are categorized by a persistent disturbance in eating and eating-related behaviors.

For this Discussion, consider the eating behaviors of the male client in the attached case study. Think about how an individual's control of eating habits becomes an abnormality in eating behavior.

With these thoughts in mind:

Post a diagnosis for the male client in the case study and explain your rationale for assigning these diagnoses on the basis of the DSM-5. Then explain how gender and culture impact the presentation of an eating disorder. Give at least 2 specific examples.

Be sure to support your postings and responses with specific references to current literature.

3-4 Paragraphs. APA Format. In-text Citations to Support Literature. Minimum of 2 Peer Reviewed References.

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Feeding and Eating Disorders Feeding and Eating Disorders Program Transcript [MUSIC PLAYING] MALE SPEAKER: All things considered, I'm doing pretty well. I own my own consulting firm. I help online businesses identify and build their customer base. The company keeps growing every year, so I'm kept pretty busy. I've got I made, really. I have more free time to play with than most people, a lot more. But to be honest, I'm not happy with my life right now. I wouldn't be otherwise, right? FEMALE SPEAKER: So tell me what's going on for you. MALE SPEAKER: Well, I can't seem to keep a relationship going. I have so much good in my life right now, but just not that. I'll start going out with someone a couple of times, and they stop returning my calls. I used to think that it was just a run of bad luck, but now I know that it's me. I'm just not very attractive. I think that's what happened with my last real boyfriend. We were together for eight months, and never came right out and said it, but I know the reason he ended things-- it was because I was just too fat. No matter what I do, I can't seem to get rid of these right here, my love handles. FEMALE SPEAKER: Well, it sounds as if you exercise some, because you look in shape. MALE SPEAKER: I do. I should. I run five miles a day. I go to the gym a couple times a week and lift weights. I even take a hot yoga class. But it might look like I'm in shape, but trust me, I need to burn more weight. FEMALE SPEAKER: You're what, 6 foot, 5'11''? How much do you weigh? MALE SPEAKER: 155, but 155 pounds of flab. Don't get me wrong. I know you might-- I don't purge or anything. What goes in my belly stays there. FEMALE SPEAKER: Tell me about your diet. What are your eating habits? MALE SPEAKER: I eat two meals a day, breakfast, lunch. That's it, no dinner. I drink a lot of protein mixes. I'll have a smoothie every now and then, but as long as it's low fat. No alcohol, that's fattening. And definitely no pot. If you smoke that, you'll eat the whole grocery store. ©2013 Laureate Education, Inc. 1 Feeding and Eating Disorders FEMALE SPEAKER: When was the last time you had a physical? MALE SPEAKER: Three months ago. Everything was great. Blood pressure, cholesterol,. I've never had sick day in my life. Never seen a shrink, either. You know what my GP said last time I was there, putting my clothes back on? You're too skinny. You know what I said to him? Brother, you can never be too rich or too thin. Feeding and Eating Disorders Additional Content Attribution IMAGES: Images provided by http://www.istockphoto.com/ MUSIC: Creative Support Services Los Angeles, CA Dimension Sound Effects Library Newnan, GA Narrator Tracks Music Library Stevens Point, WI Signature Music, Inc Chesterton, IN Studio Cutz Music Library Carrollton, TX Special Thanks: Fairland Center/Region One Mental Health ©2013 Laureate Education, Inc. 2 Journal of Counseling Psychology 2012, Vol. 59, No. 2, 329 –337 © 2012 American Psychological Association 0022-0167/12/$12.00 DOI: 10.1037/a0026777 BRIEF REPORT Male Body Satisfaction: Factorial and Construct Validity of the Body Parts Satisfaction Scale for Men Michael B. McFarland and Trent A. Petrie This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. University of North Texas Given the centrality of body dissatisfaction in the manifestation of eating, exercise, and affective disturbances in men, measurement of this construct becomes essential. Across 2 studies with male undergraduates (Ns ⫽ 189 and 188), the psychometric properties, including incremental validity and factor structure, of the 25-item Body Parts Satisfaction Scale for Men (BPSS–M) were examined. Three factors—Upper Body, Legs, and Face—that included items measuring both muscularity and leanness were established. The factors were internally consistent and temporally stable (over 6 months), and support was found for their convergent, discriminant, and concurrent validity. Further, we established that, after controlling for social desirability and drive for muscularity, body satisfaction contributes uniquely to men’s experience of disordered eating, negative affect and mood, and psychological well-being. The BPSS–M yielded reliable and valid scores with undergraduate men, suggesting that it may be useful for understanding not only body satisfaction but disordered eating and affective disturbances as well. Keywords: body dysmorphia, body dysmorphic disorder, masculinity, scale development, body objectification perceived pressures from parents, peers, and the media to increase muscles predicted boys’ (aged 8 –11 years) subsequent investment in strategies to build muscles and lose weight and the importance they placed on being muscular, whereas Leit et al. (2002) found exposure to images of muscular men led male participants to experience increased dissatisfaction with their own muscularity. Further, men who defined the ideal body as lean and muscular said the upper (e.g., chest) and lower (e.g., calves) body were areas that affect their satisfaction with their appearance (Ridgeway & Tylka, 2005) and indicated that, in general, they fall far short of these societal body ideals (Tiggemann, Martins, & Churchett, 2008). These studies suggest that boys and men do experience pressures regarding the need to be muscular and that these pressures often are internalized, lead to feelings of dissatisfaction with body size and shape, and promote weight loss and muscle gain strategies such as restrictive dieting, weight lifting, and taking weight-gain supplements. Although there is agreement that muscularity and leanness are central to men’s body satisfaction (e.g., Cafri & Thompson, 2004; Ridgeway & Tylka, 2005), the question remains as to whether men really conceptualize their bodies as suggested by the factor structure of recent measures of men’s body satisfaction (e.g., Tylka, Bergeron, & Schwartz, 2005). That is, do men really perceive themselves in terms of some overall sense of muscularity or body fatness, or is the evaluation more integrated, focusing on the muscularity and leanness of different areas of the body, such as the upper torso and legs? Ridgeway and Tylka (2005) reported that men do identify specific body parts in the upper (e.g., shoulders) and lower (e.g., buttocks) regions as important, but they also elucidated the importance of muscularity with certain body parts Body dissatisfaction, particularly with leanness (or body fat) and muscularity, has been identified as a key factor in men’s psychological health and well-being (e.g., Cafri et al., 2005; McCabe & Ricciardelli, 2004; Ricciardelli & McCabe, 2004; Ridgeway & Tylka, 2005), including the development of muscle dysmorphia, eating disorders, and depression (Olivardia, Pope, Borowiecki, & Cohane, 2004). Developing measures of this construct with evidence of reliability and validity, however, has been more recent and is a necessary step for counseling psychologists to understand, assess, and work effectively with men who may experience such dissatisfaction. In this study, we describe the initial development and validation of a measure of male body satisfaction that is grounded in current body image theory (Cafri & Thompson, 2004). Society’s idealization of a hyper-mesomorphic, hyper-lean male body, in combination with pressures from parents and peers over body size and shape, may adversely influence boys’ and men’s body image and eating behaviors (e.g., Leit, Gray, & Pope, 2002; Smolak, Murnen, & Thompson, 2005). For example, Ricciardelli, McCabe, Lillis, and Thomas (2006) found that initial This article was published Online First January 23, 2012. Michael B. McFarland and Trent A. Petrie, Department of Psychology, University of North Texas. This research was based on the dissertation conducted by Michael B. McFarland under the supervision of Trent A. Petrie. This study was presented at the 2009 annual conference of the American Psychological Association in Toronto, Ontario, Canada. Correspondence concerning this article should be addressed to Trent A. Petrie, Department of Psychology, University of North Texas, 1155 Union Circle, #311280, Denton, TX 76203-5017. E-mail: trent.petrie@unt.edu 329 This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. 330 MCFARLAND AND PETRIE (e.g., arms), leanness with other body parts (e.g., buttocks), and both with a few body parts (e.g., six-pack abdominal muscles). Thus, by focusing primarily on muscularity and leanness, researchers may be overlooking other dimensions that are important in defining men’s satisfaction with their body and appearance (e.g., Tiggemann et al., 2008). Perhaps, like for a woman (Petrie, Tripp, & Harvey, 2002), a man’s perception of his face as attractive (including hair) may influence his overall satisfaction with appearance, psychological well-being, and use of pathogenic eating and weight control behaviors. Recent reviews (e.g., Cafri & Thompson, 2007) and our own examination of current measures (e.g., Ochner, Gray, & Brickner, 2009) indicate that, in addition to the issues raised previously, some measures are limited by insufficient data about their psychometric properties, by items that may not represent the construct of interest, and by a lack of completeness in examining the body parts that men identify as key. Further, in their study of heterosexual men’s body image, Tiggemann et al. (2008) concluded that “appropriate measures of body image for men still require further development and psychometric investigation” (p. 1170). Thus, our purpose was to develop and test a new measure of male body satisfaction that focused on salient body parts (e.g., Ridgeway & Tylka, 2005), incorporated muscularity and leanness (e.g., Cafri & Thompson, 2004), and extended research that has shown hair to be important to men (Tiggemann et al., 2008) by examining the significance of a man’s face. In Study 1, we tested the scale’s initial factor structure and internal consistency reliabilities and examined the factors’ relations with key demographic variables (e.g., age, year in school). In Study 2, we confirmed the factor structure and then found evidence for the scale’s validity, including incremental validity, through relations with measures of disordered eating, drive for muscularity, negative mood, and psychological well-being, constructs that have been shown to be related to body satisfaction (Bergeron & Tylka, 2007; Ochner et al., 2009; Tylka et al., 2005). Study 1: Exploratory Factor Analysis and Initial Reliability Estimates Method Participants. Participants were 189 male undergraduates from a large, public university in the southwestern United States; mean age was 20.3 years (SD ⫽ 2.25); 120 were European American, 25 were Hispanic, 24 were African American, 19 were Asian American/Pacific Islander, and 1 was American Indian. There were 71 freshmen, 49 sophomores, 41 juniors, and 28 seniors. The men’s mean current and desired body mass indices (BMIs) were 25.0 kg/m2 (SD ⫽ 4.71) and 24.4 kg/m2 (SD ⫽ 3.05), respectively; 7 participants could be categorized as underweight, 103 as normal weight, 50 as overweight, and 29 as obese (Centers for Disease Control and Prevention [CDC], 2009). On the demographic questionnaire, 87 men reported being dissatisfied with their current weight; of these, 57 considered themselves overweight and 30 considered themselves underweight. No participant reported having been previously treated for an eating disorder. Measures. Body satisfaction. One counseling psychology faculty member and eight doctoral students (five female and three male), all of whom were knowledgeable about body image concerns, participated in the item generation and review processes. Their purpose was to identify the most salient body parts for men (e.g., Ridgeway & Tylka, 2005), including items related to the face, that addressed issues of muscularity and leanness. The 30 items that resulted from this process composed the Body Parts Satisfaction Scale for Men (BPSS–M) and included (a) 18 items regarding satisfaction with the leanness and the muscularity of each of nine identified body parts (e.g., “leanness of upper legs,” “muscularity of chest”); (b) five items regarding satisfaction with face (e.g., “complexion,” “overall face”); (c) five items regarding satisfaction with overall body size and shape (e.g., “overall body build”); and (d) two items that addressed height and weight. Participants rate each item using a 6-point scale that ranges from 1 (extremely dissatisfied) to 6 (extremely satisfied). Social desirability. The 12-item Marlowe-Crowne Social Desirability Scale Form B (Reynolds, 1982) was used. Items are answered true or false; the total score can range from 0 (low) to 12 (high). In a sample of undergraduates, Reynolds (1982) reported a Kuder-Richardson-20 (KR-20) coefficient of .75 and a .92 correlation with the standard version of the Marlowe-Crowne Social Desirability Scale; KR-20 for the current study was .62. Demographics. We assessed age, race/ethnicity, year in school, height, and current and ideal weight. We asked about (a) satisfaction with current weight and, if participants reported being not satisfied, if they considered themselves to be overweight/ underweight, and (b) if they had been treated for an eating disorder. Procedure. After obtaining approval from the university’s Institutional Review Board for Human Subjects Research, we obtained consent and administered questionnaires through Survey Monkey, a secure website; men were recruited to participate in a study on “the health behaviors of male college students.” They received course extra credit and the chance to win a $50 cash prize. Data analysis. Principal axis factoring, with squared multiple correlations as the communality estimates, was used as the method of factor extraction in the exploratory factor analysis (Worthington & Whittaker, 2006). We conducted a parallel analysis (Hayton, Allen, & Scarpello, 2004) to determine the number of factors. Criteria for item deletion included (a) loadings less than .32, (b) cross-loading differences of less than .15, (c) absolute loadings higher than .32 on two or more factors, and (d) low communalities (i.e., less than .40). Alpha was set at .01 for all analyses. Results Bartlett’s (1950) test of sphericity, ␹2(435) ⫽ 7,766.34, p ⬍ .0001, and the Kaiser–Meyer–Olkin measure of sampling adequacy (.94) both provided evidence that item bivariate correlations were adequate for factorability (Worthington & Whittaker, 2006). Parallel analysis indicated the presence of three factors that explained 75.5% of the variance; we conducted a promax rotation. Height was dropped due to a low communality, as were three other items (i.e., muscularity and leanness of buttocks, leanness of neck) due to high cross-factor loadings. The three factors were Face (five items; ␣ ⫽ .85), Legs (four items; ␣ ⫽ .94), and Upper Body (17 items; ␣ ⫽ .98); factor loadings for Face ranged from .50 to .90 (M ⫽ .71), for Legs from .70 to 1.0 (M ⫽ .86), and for Upper Body MALE BODY SATISFACTION This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. from .50 to 1.0 (M ⫽ .71). Factor intercorrelations ranged from .65 to .79. The factors were unrelated to age (rs ⫽ –.02 to .04) but were related to social desirability (Face: r ⫽ .19, p ⬍ .01; Legs: r ⫽ .09, p ⫽ .21; Upper Body: r ⫽ .14, p ⫽ .03) and current BMI (Face: r ⫽ –.21, p ⬍ .005; Legs: r ⫽ –.23, p ⬍ .005; Upper Body: r ⫽ –.40, p ⬍ .001). The factors were also unrelated to year in school, Wilks’s ␭ ⫽ .954, F(9, 555) ⫽ 0.98, p ⫽ .46, ␩2p ⫽ .016. The factors appeared internally stable and not prone to vary in relation to age and school year. Study 2: Confirmatory Factor Analysis and Construct Validity Method Participants. Participants were 188 male undergraduates drawn from the same university, none of whom had participated in Study 1; mean age was 20.3 years (SD ⫽ 2.29); 123 were European American, 24 were Hispanic, 29 were African American, 11 were Asian American/Pacific Islander, and 1 was American Indian. There were 64 freshmen, 56 sophomores, 38 juniors, and 30 seniors. Mean current and desired BMIs were 24.8 kg/m2 (SD ⫽ 4.11) and 24.4 kg/m2 (SD ⫽ 3.07), respectively; three men were categorized as underweight, 105 as normal weight, 54 as overweight, and 26 as obese (CDC, 2009). On the demographic questionnaire, 89 men reported being dissatisfied with their current weight; of these, 52 considered themselves overweight and 35 considered themselves underweight; two did not specify. One participant reported having previously received treatment for anorexia nervosa. Measures. Body satisfaction. The BPSS–M as described and factor analyzed in Study 1 was used. Drive for muscularity. The 15-item Drive for Muscularity Scale (DMS; McCreary, Sasse, Saucier, & Dorsch, 2004) assesses Muscularity-Oriented Body Image (MBI; seven items; ideation associated with muscularity, e.g., “I wish I were more muscular”) and Muscularity Behavior (MB; seven items; behaviors to increase muscle size and strength, e.g., “I lift weights to build up muscle”). Participants respond on a 6-point scale from 1 (never) to 6 (always). Total scores are the mean; higher scores represent more of those muscularity attitudes or behaviors. In a sample of male high school students and men, McCreary et al. (2004) reported Cronbach’s alphas of .88 (MBI) and .81 (MB); alphas for the current sample were .92 (MBI) and .88 (MB). McCreary and Sasse (2000) provided extensive data regarding the scale’s construct validity. Disordered eating. The 36-item Bulimia Test—Revised (BULIT–R; Thelen, Mintz, & Vander Wal, 1996) assesses bulimic symptomatology. Participants rate items, such as “I am satisfied with my eating patterns,” on a 5-point scale from 1 (absence of disturbance) to 5 (severe disturbance). For the 28 scored items, total scores range from 28 (low) to 140 (high). Cronbach’s alpha was .95 in a community sample of men (Russell & Keel, 2002); alpha for the current sample was .88. Regarding construct validity, Russell and Keel (2002) reported that the scale correlated positively (r ⫽ .67) with the EAT-26 (Garner, Olmstead, Bohr, & Garfinkel, 1982). 331 The 26-item Eating Attitudes Test (EAT-26; Garner et al., 1982) assesses disordered eating in terms of dieting, bulimia and food preoccupation, and oral control. Participants respond to each item, such as “Am terrified of being overweight,” on a 6-point scale; the three responses that represent the lowest levels of disturbance are scored 0, and the subsequent three responses are scored 1, 2, and 3. Total scores range from 0 (low) to 78 (high). Cronbach’s alphas have been found to be .89 in a sample of men (Russell & Keel, 2002); alpha for the current sample was .74. The nine-item Dietary Intent Scale (DIS; Stice, 1998b) assesses behavioral intention to restrict eating. Participants rate items, such as “I limit the amount of food I eat in an effort to control my weight,” on a 5-point scale that ranges from 1 (never) to 5 (always). Total score is the mean; higher scores indicate greater restraint. Stice (1998a) reported a Cronbach’s alpha of .95 in a sample of male and female high school students; alpha for the current sample was .93. The DIS correlated significantly with the Dutch Restrained Eating Scale (r ⫽ .92; Stice, 1998b). Negative affect. The Hostility (six items; e.g., irritable, angry) and Guilt (six items; e.g., blameworthy, guilty) subscales from the Positive and Negative Affect Schedule Expanded Form (PANAS–X; Watson & Clark, 1994) were rated on a 5-point scale from 1 (very slightly or not at all) to 5 (extremely). Each subscale score is the mean; higher scores represent more negative emotions. Watson and Clark (1994) reported Cronbach’s alphas of .86 (Hostility) and .89 (Guilt) among male and female undergraduates; our study’s alphas were .87 (Hostility) and .93 (Guilt). They also reported correlations between the PANAS–X and the Profile of Mood States scales. The 20-item Center for Epidemiologic Studies Depression Scale (CES–D; Radloff, 1977) assesses depressive symptomatology in the general population. Participants rate items, such as “I felt lonely,” on a 4-point scale ranging from 0 (rarely or none of the time [less than 1 day]) to 3 (most or all of the time [5–7 days]), based on the prior week. Total scores can range from 0 (no symptoms) to 60 (high level of symptoms). McCreary and Sasse (2000) reported a Cronbach’s alpha of .87 in a sample of high school boys; alpha for the current study was .88. Shean and Baldwin (2008) found that the CES–D correlated positively (r ⫽ .86) with the Beck Depression Inventory–II. Psychological well-being. The five-item Satisfaction With Life Scale (SWLS; Diener, Emmons, Larsen, & Griffin, 1985) assesses overall life satisfaction. Items, such as “I am satisfied with my life,” are scored using a 7-point Likert scale from 1 (strongly disagree) to 7 (strongly agree). Total scores can range from 5 (low) to 35 (high). Diener et al. (1985) reported a Cronbach’s alpha of .87 among male and female undergraduates; alpha for the current study was .90. Diener et al. have provided extensive information about the scale’s validity. The 12-item General Esteem subscale of the Self Description Questionnaire–III (SDQ; Marsh & O’Neill, 1984) assesses individuals’ effectiveness, pride, and satisfaction in themselves. Items, such as “I have pretty positive feelings about myself,” are scored on an 8-point scale that ranges from 1 (definitely false) to 8 (definitely true). Total score is the mean; higher scores reflect greater self-esteem. Marsh and O’Neill (1984) reported a Cronbach’s alpha of .93 among male and female undergraduates; our alpha was .94. The SDQ correlates with the Affective Perception MCFARLAND AND PETRIE This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. 332 Inventory (r ⫽ .63) and the Rosenberg Self-Esteem Scale (r ⫽ .79; Byrne & Shavelson, 1986). Social desirability. The 12-item Marlowe-Crowne Social Desirability Scale Form B (Reynolds, 1982) was used. KR-20 for the current study was .71. Demographics. Participants provided the same demographic information as in Study 1. Procedure. We used the same procedure described in Study 1. A subset of the men (n ⫽ 59) completed the BPSS–M 6 months following this data collection. Data analysis. Confirmatory factor analysis (CFA) was conducted using the robust maximum-likelihood estimation procedure within EQS Version 6.1 (Bentler, 1995). Internal consistency and test–retest reliabilities were examined as well. We initially examined the factors’ validity (convergent and concurrent) through their correlations with the BULIT–R, EAT-26, DIS, DMS–MB, DMS– MBI, PANAS–Hostility and Guilt, CES–D, SWLS, and SDQ. Then, we tested the factors’ incremental validity, which determined the variance they accounted for in these variables beyond that explained by the men’s muscularity attitudes and behaviors. We followed the procedure outlined by Bergeron and Tylka (2007), though we also controlled for social desirability. Using hierarchical regression, we entered social desirability at Step 1, the two DMS factors at Step 2, and the three BPSS–M factors at Step 3. Significant betas and changes in R2 at Step 3 provide support for their incremental validity. Alpha was set at .01. Results Factor structure and reliability. Based on the two-index strategy recommended by Hu and Bentler (1999), the CFA provided support for the three-factor model, Satorra-Bentler ␹2(257) ⫽ 649.06; comparative fit index ⫽ .93; standardized root-mean-square residual ⫽ .06. Due to high residuals, we dropped one item (“size and shape of head”) from the Face factor. Standardized factor loadings ranged from .66 to .92 (M ⫽ .79; Face), .74 to .92 (M ⫽ .86; Legs), and .69 to .91 (M ⫽ .82; Upper Body). Cronbach’s alphas and 6-month test–retest reliabilities, respectively, were .87 and .58 (Face), .94 and .70 (Legs), and .97 and .72 (Upper Body). Factor intercorrelations ranged from .60 to .81. Convergent and concurrent validity. Correlations with the BPSS–M factors are presented in Table 1. Across the three factors, there were small to moderate correlations with the measures of disordered eating, muscularity attitudes and behaviors, negative affect and mood, and psychological well-being. Further, satisfaction with weight was related significantly to BPSS–M factor scores, Wilks’s ␭ ⫽ .83, F(3, 184) ⫽ 13.02, p ⬍ .0001, ␩2p ⫽ .18. Men who were weight-satisfied had significantly higher BPSS–M factor scores (Upper Body: M ⫽ 4.35, SD ⫽ 0.97; Legs: M ⫽ 4.43, SD ⫽ 1.06; Face: M ⫽ 4.71, SD ⫽ 0.89) than those who were weight-dissatisfied (Upper Body: M ⫽ 3.52, SD ⫽ 0.96; Legs: M ⫽ 3.82, SD ⫽ 1.19; Face: M ⫽ 4.36, SD ⫽ 0.95). Incremental validity. For the BULIT–R, social desirability accounted for 8% of the variance, F(1, 186) ⫽ 17.01, p ⬍ .0001; the inclusion of the DMS factors at Step 2 explained an additional 5% of variance, F(2, 184) ⫽ 5.70, p ⬍ .01. Step 3, which included the BPSS–M factors, also was significant, F(3, 181) ⫽ 8.53, p ⬍ .0001, ⌬R2 ⫽ .11. For the EAT-26, neither Step 1, F(1, 186) ⫽ 0.78, ⌬R2 ⫽ .003, nor Step 2, F(2, 184) ⫽ 1.12, ⌬R2 ⫽ .01, was significant. The BPSS–M factors, however, explained an additional 7% of the variance, F(3, 181) ⫽ 4.38, p ⬍ .01. For the DIS, neither Step 1, F(1, 186) ⫽ 0.87, ⌬R2 ⫽ .005, nor Step 2, F(2, 184) ⫽ 0.62, ⌬R2 ⫽ .007, was significant. Step 3, F(3, 181) ⫽ 14.63, p ⬍ .0001, ⌬R2 ⫽ .19, was significant. For Hostility, social desirability accounted for 22% of the variance, F(1, 186) ⫽ 52.31, p ⬍ .0001; Step 2, though, was not significant, F(2, 184) ⫽ 2.94, ⌬R2 ⫽ .02. The BPSS–M factors added significantly to the model, F(3, 181) ⫽ 5.81, p ⬍ .001, ⌬R2 ⫽ .07. For Guilt, Step 1 was significant, F(1, 186) ⫽ 26.73, p ⬍ .0001, ⌬R2 ⫽ .07, though Step 2 was not, F(2, 184) ⫽ 2.82, ⌬R2 ⫽ .03. Table 1 Study 2 Correlations of the BPSS–M With Selected Variables Variable/measure M SD Face Legs Upper Body Age Current BMI Muscularity-Oriented Body Image Muscularity Behavior BULIT–R EAT-26 Dietary intent PANAS–X Hostility PANAS–X Guilt CES–D Satisfaction With Life Scale SDQ–General Esteem 20.30 24.74 23.28 16.09 43.43 4.32 13.88 1.98 1.93 12.83 23.07 73.09 2.29 4.11 9.16 7.82 11.93 4.69 6.15 0.77 0.91 8.82 6.90 15.38 .05 ⫺.02 ⫺.18 .08 ⫺.27ⴱⴱ ⫺.17 ⫺.25ⴱⴱ ⫺.23ⴱⴱ ⫺.29ⴱⴱ ⫺.34ⴱⴱ .31ⴱⴱ .48ⴱⴱ .03 ⫺.04 ⫺.32ⴱⴱ .03 ⫺.33ⴱⴱ ⫺.12 ⫺.07 ⫺.27ⴱⴱ ⫺.23ⴱⴱ ⫺.28ⴱⴱ .35ⴱⴱ .38ⴱⴱ ⫺.01 ⫺.13 ⫺.29ⴱⴱ .18 ⫺.34ⴱⴱ ⫺.21ⴱ ⫺.26ⴱⴱ ⫺.29ⴱⴱ ⫺.31ⴱⴱ ⫺.35ⴱⴱ .39ⴱⴱ .49ⴱⴱ Note. N ⫽ 188. BPSS–M ⫽ Body Parts Satisfaction Scale for Men; BMI ⫽ body mass index; BULIT–R ⫽ Bulimia Test—Revised; EAT-26 ⫽ Eating Attitudes Test; PANAS–X ⫽ Positive and Negative Affect Schedule Expanded Form; CES–D ⫽ Center for Epidemiologic Studies Depression Scale; SDQ ⫽ Self Description Questionnaire–III. ⴱ p ⬍ .01. ⴱⴱ p ⬍ .001. This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. MALE BODY SATISFACTION The BPSS–M factors were significant, F(3, 181) ⫽ 6.90, p ⬍ .0001, ⌬R2 ⫽ .09. For depressive symptoms, Step 1 was significant, F(1, 186) ⫽ 22.86, p ⬍ .0001, ⌬R2 ⫽ .11, but Step 2 was not, F(2, 184) ⫽ 2.00, ⌬R2 ⫽ .02. The BPSS–M factors accounted for an additional 10% of the variance in CES–D scores, F(3, 181) ⫽ 7.39, p ⬍ .0001. For the men’s overall satisfaction with their lives, Step 1 was significant, F(1, 186) ⫽ 13.39, p ⬍ .0001, ⌬R2 ⫽ .07, but Step 2 was not, F(2, 184) ⫽ 3.92, ⌬R2 ⫽ .04. The inclusion of the BPSS–M factors at Step 3 was significant, F(3, 181) ⫽ 7.24, p ⬍ .0001, ⌬R2 ⫽ .10. For self-esteem, social desirability explained 12% of the variance, F(1, 186) ⫽ 24.09, p ⬍ .0001, DMS factors an additional 5%, F(2, 184) ⫽ 5.80, p ⬍ .01, and BPSS–M factors an extra 20%, F(3, 181) ⫽ 18.67, p ⬍ .0001, ⌬R2 ⫽ .20. See Table 2 for details of the regression analyses. Summary and Concluding Discussion Across the two studies, an internally consistent and temporally stable three-factor model was supported, providing information about men’s satisfaction with their upper body, legs, and face. These findings suggest that, perhaps, men perceive their bodies not in terms of some overall sense of how fat or muscular they are, as has been determined in past research (e.g., Tylka et al., 2005), but rather with respect to an upper torso that is lean, muscular, and V-shaped; legs that are strong and well-defined; and a face that is defined by nice looking hair and an attractive complexion. Our findings are consistent with those of Tiggemann et al. (2008) in that muscularity and leanness, albeit important, are not the only features that define men’s body satisfaction. Although height was dropped from the analyses, past research (e.g., Ridgeway & Tylka, 2005; Tiggemann et al., 2008) has shown it to be salient, so this dimension should be examined further in future studies to test its predictive utility. Regarding evidence of the scale’s convergent and concurrent validity, the BPSS–M factors were related, as expected, with the men’s desire to be more muscular, but not to the extent that they were taking actions to increase their strength and muscle mass (see also Bergeron & Tylka, 2007). Body dissatisfaction, particularly with the upper body and face, also was related to higher levels of bulimic symptomatology, intention to engage in dietary restraint, hostility and guilt, and depressive symptomatology, which is consistent with past research and theoretical models that associate dissatisfaction with negative affect, restricting caloric intake, and bulimic symptoms (e.g., Cafri et al., 2005; Olivardia et al., 2004; Ricciardelli & McCabe, 2004). Finally, in line with the idea that specific forms of self-concept underlie one’s global sense of self (Marsh & O’Neill, 1984) and previous research (Bergeron & Tylka, 2007), we found that being satisfied with one’s body, along all dimensions, was associated with greater psychological wellbeing in terms of the men’s overall satisfaction with their lives and their general self-concept (see also Olivardia et al., 2004). As expected, the BPSS–M was not related significantly to age or year in school and shared only a small amount of variance (⬃4%) with a measure of social desirability. There was some variability, however, regarding the relations between the BPSS–M and BMI across the two studies. Unlike with women, where BMI usually is associated with greater body fat and lower satisfaction, for men, a 333 larger BMI could indicate more lean muscle mass or higher levels of body fat, so variability would be expected (Ricciardelli & McCabe, 2004). Future research may want to examine the relations between satisfaction and more objective measures of body composition, such as percentage body fat or fat-free muscle. Regarding evidence of the scale’s incremental validity, the three factors of the BPSS–M, in particular satisfaction with upper body, uniquely and significantly explained the extent to which men engaged in disordered eating behaviors (i.e., EAT-26), intended to restrict their food intake, felt angry or guilty, and felt positively about themselves, explaining between 7% and 20% of the variance after controlling for social desirability and drive for muscularity. Bergeron and Tylka (2007) also reported associations (after controlling only for drive for muscularity) between men’s body dissatisfaction and self-esteem. Interestingly, the men’s satisfaction with their face also was a significant predictor for their level of self-esteem. Like findings regarding men who have rated their hair as important in their self-evaluation (Tiggemann et al., 2008), our findings support the idea that men’s self-esteem is determined by more than their muscularity, leanness, or how pleased they are with their upper torso. Additional research is needed to determine the relative predictive utility of these factors in explaining disordered eating attitudes and behaviors versus an individual’s general psychological well-being. Across the two studies, we found support for a three-factor model that defined male body satisfaction along the dimensions of upper body, legs, and face. Within each factor, items reflecting the leanness and muscularity of the body parts were present, suggesting that men consider both aspects in determining their level of satisfaction. In addition to individual body parts, two of the factors (i.e., upper body and face) included items reflecting men’s overall satisfaction with body, muscularity, and/or leanness. This finding suggests that our factors were not simply a listing of the body parts that composed each area but include overall evaluations of body as well. In fact, we were somewhat surprised by the final factor structure, as we expected the delineation to occur along the lines of muscularity and leanness as has been found in other studies (e.g., Tylka et al., 2005). We also found evidence that the factors were internally consistent and stable over a 6-month time period and were related (and unrelated) as expected to a wide range of psychosocial, demographic, and eating disorder variables, providing support for their validity. Regarding validity, we found evidence that the factors, in particular Upper Body, but also Face, were unique from social desirability and drive for muscularity in explaining the presence of disordered eating, negative affect, and general self-esteem. Thus, the BPSS–M represents a new, and conceptually distinct, way to measure male body satisfaction. Several clinical implications can be derived from this study. First, given that men do experience body image concerns, counseling psychologists might screen clients for symptoms of body dissatisfaction and, if present, examine whether the men are experiencing eating disturbances, including binge eating, bulimia, and muscle dysmorphia, or are engaging in dangerous bodychanging behaviors, such as excessive exercising or taking steroids (Parent & Moradi, 2011). Men presenting with body dissatisfaction also could be assessed for symptoms of general negative affect, depression, low self-esteem, and anxiety, as body dissatisfaction, eating disturbances, and affective disturbances co-occur frequently. Second, counseling psychologists could use a measure MCFARLAND AND PETRIE 334 Table 2 Incremental Variance in Disordered Eating and Psychological Well-Being as Explained by Three Factors of the BPSS–M Variable This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. ⴱⴱⴱ Bulimic symptomatology (overall adjusted R ⫽ .22, F[6, 181] ⫽ 9.75 Social desirability DMS–MBI DMS–MB BPSS–M Face BPSS–M Legs BPSS–M Upper Body EAT-26 (overall adjusted R2 ⫽ .05, F[6, 181] ⫽ 2.73ⴱ) Social desirability DMS–MBI DMS–MB BPSS–M Face BPSS–M Legs BPSS–M Upper Body Dietary intent (overall adjusted R2 ⫽ .18, F[6, 181] ⫽ 7.74ⴱⴱ) Social desirability DMS–MBI DMS–MB BPSS–M Face BPSS–M Legs BPSS–M Upper Body Hostility (overall adjusted R2 ⫽ .29, F[6, 181] ⫽ 13.56ⴱⴱⴱ) Social desirability DMS–MBI DMS–MB BPSS–M Face BPSS–M Legs BPSS–M Upper Body Guilt (overall adjusted R2 ⫽ .21, F[6, 181] ⫽ 9.46ⴱⴱⴱ) Social desirability DMS–MBI DMS–MB BPSS–M Face BPSS–M Legs BPSS–M Upper Body Depressive symptoms (overall adjusted R2 ⫽ .20, F[6, 181] ⫽ 8.68ⴱⴱⴱ) Social desirability DMS–MBI DMS–MB BPSS–M Face BPSS–M Legs BPSS–M Upper Body Satisfaction with life (overall adjusted R2 ⫽ .18, F[6, 181] ⫽ 7.59ⴱⴱⴱ) Social desirability DMS–MBI DMS–MB BPSS–M Face BPSS–M Legs BPSS–M Upper Body Self-esteem (overall adjusted R2 ⫽ .34, F[6, 181] ⫽ 17.26ⴱⴱⴱ) Social desirability DMS–MBI DMS–MB BPSS–M Face BPSS–M Legs BPSS–M Upper Body 2 ) B SE B ␤ t ⫺0.96 ⫺0.05 0.43 ⫺0.51 ⫺0.34 ⫺3.56 0.28 0.11 0.12 1.11 1.16 1.44 ⫺0.23 ⫺0.04 0.28 ⫺0.04 ⫺0.03 ⫺0.31 ⫺3.42ⴱⴱ ⫺0.46 ⫺3.44ⴱⴱ ⫺0.46 ⫺0.29 ⫺2.47 ⫺0.08 ⫺0.03 0.11 ⫺0.23 0.88 ⫺1.80 0.12 0.05 0.05 0.48 0.51 0.63 ⫺0.05 ⫺0.05 0.18 ⫺0.05 0.22 ⫺0.40 ⫺0.68 ⫺0.55 2.09 ⫺0.48 1.73 ⫺2.87ⴱⴱ ⫺0.21 ⫺0.15 0.23 ⫺0.99 2.66 ⫺3.96 0.15 0.06 0.07 0.59 0.62 0.77 ⫺0.10 ⫺0.23 0.29 ⫺0.15 0.50 ⫺0.67 ⫺1.38 ⫺2.59ⴱ 3.43ⴱⴱ ⫺1.68 4.29ⴱⴱⴱ ⫺5.17ⴱⴱⴱ ⫺0.12 ⫺0.01 0.02 ⫺0.01 0.04 ⫺0.25 0.02 0.01 0.01 0.07 0.07 0.09 ⫺0.44 ⫺0.05 0.22 ⫺0.01 0.06 ⫺0.34 ⫺6.77ⴱⴱⴱ ⫺0.66 2.86ⴱⴱ ⫺0.05 0.55 ⫺2.76ⴱ ⫺0.10 0.01 0.02 ⫺0.12 0.16 ⫺0.33 0.02 0.01 0.01 0.09 0.09 0.11 ⫺0.31 0.03 0.14 ⫺0.13 0.21 ⫺0.38 ⫺4.60ⴱⴱⴱ 0.37 1.73 ⫺1.46 1.86 ⫺2.95ⴱⴱ ⫺0.88 0.02 0.03 ⫺1.60 0.82 ⫺2.42 0.21 0.08 0.09 0.84 0.88 1.09 ⫺0.28 0.02 0.02 ⫺0.17 0.11 ⫺0.29 ⫺4.14ⴱⴱⴱ 0.21 0.28 ⫺1.91 0.93 ⫺2.21 0.47 ⫺0.05 0.01 0.54 0.22 1.74 0.17 0.07 0.07 0.66 0.69 0.86 0.19 ⫺0.06 0.01 0.07 0.04 0.26 2.77ⴱ ⫺0.71 0.14 0.82 0.32 2.02 1.43 ⫺0.11 0.02 4.74 ⫺2.40 5.88 0.33 0.13 0.15 1.32 1.38 1.71 0.27 ⫺0.07 0.01 0.27 ⫺0.18 0.40 4.28ⴱⴱⴱ ⫺0.85 0.12 3.39ⴱⴱ ⫺1.74 3.43ⴱⴱ Note. N ⫽ 188. The values presented in this table are those at Step 3, when all have been entered. BPSS–M ⫽ Body Parts Satisfaction Scale for Men; DMS ⫽ Drive for Muscularity Scale; MBI ⫽ Muscularity-Oriented Body Image; MB ⫽ Muscularity Behavior; EAT-26 ⫽ Eating Attitudes Test. ⴱ p ⬍ .01. ⴱⴱ p ⬍ .005. ⴱⴱⴱ p ⬍ .0005. This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. MALE BODY SATISFACTION of body satisfaction, such as the BPSS–M, to assess this construct and not rely on visual cues, stereotypes, or personal biases about how men “should” look and whether they should be satisfied if they have a certain physique or body type. Further, it provides a way to determine how satisfied men are with not just their body but also their face, which appears to be related to their general feelings of esteem. Finally, counseling psychologists can keep in mind that potent societal factors (e.g., media images) continually reinforce the desirability of the hyper-mesomorphic and lean ideal body image for boys and men. In response, counseling psychologists could work to counter these messages by normalizing an “average” physique, encouraging a healthy lifestyle of moderate exercise and nutritious eating, and modeling body acceptance (see also Greenberg & Schoen, 2008). Limitations existed that deserve mention. First, the participants were obtained from one university, the sample sizes were moderate (⬍200), and we did not specifically assess the participants’ sexual orientation. Thus, the BPSS–M should be tested within other populations (e.g., adolescents, older men, athletes, other races/ ethnicities) to further establish its psychometric properties. In particular, given the discrepancies that exist between heterosexual and homosexual men in terms of body image concerns (e.g., Morrison, Morrison, & Sager, 2004), researchers may want to focus their energies on this population to determine the etiology of such concerns. Second, despite establishing initial concurrent and incremental validity evidence, the study was cross-sectional, and longitudinal designs are needed to determine the directionality of the associations between body satisfaction and the various health outcomes. Researchers also will want to compare the BPSS–M and other measures of male body image to shed more light on just how men conceptualize their body and which dimensions best predict disordered eating and other aspects of men’s psychological wellbeing. Further, given the high intercorrelations amongst the BPSS–M factors, in future studies, using the 25 items to determine a total score could be considered and examined in relation to these outcomes. 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The PANAS–X manual for the Positive and Negative Affect Schedule—Expanded Form. Unpublished manuscript, University of Iowa. Worthington, R. L., & Whittaker, T. A. (2006). Scale development research: A content analysis and recommendations for best practices. The Counseling Psychologist, 34, 806 – 838. doi:10.1177/0011000006288127 MALE BODY SATISFACTION 337 Appendix Body Parts Satisfaction Scale for Men (BPSS–M) Instructions: For each of the body parts listed below, indicate your current level of satisfaction using the scale below. There are no right or wrong answers, so please respond honestly based on how you currently feel. Extremely dissatisfied This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. 1 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. Extremely satisfied 2 Hair Complexion Leanness of face Overall face Weight Leanness of shoulders Muscularity of shoulders Leanness of arms (e.g., biceps/triceps) Muscularity of arms (e.g., biceps/triceps) Leanness of stomach/abdomen Muscularity of stomach/abdomen Leanness of chest/upper torso Muscularity of chest/upper torso Leanness of back Muscularity of back Muscularity of neck Overall body build Overall leanness of body Overall level of body’s muscularity Overall size and shape of body Overall muscle tone/definition of body Leanness of upper legs (e.g., quadriceps) Muscularity of upper legs (e.g., quadriceps) Leanness of lower legs (e.g., calves) Muscularity of lower legs (e.g., calves) 3 4 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 5 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 6 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 Received March 13, 2011 Revision received November 8, 2011 Accepted November 8, 2011 䡲 Journal of Abnormal Psychology 2013, Vol. 122, No. 3, 720 –732 © 2013 American Psychological Association 0021-843X/13/$12.00 DOI: 10.1037/a0034004 This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. DSM–IV–TR and DSM-5 Eating Disorders in Adolescents: Prevalence, Stability, and Psychosocial Correlates in a Population-Based Sample of Male and Female Adolescents Karina L. Allen Susan M. Byrne The University of Western Australia, West Perth and The University of Western Australia, Crawley, Western Australia The University of Western Australia, Crawley, Western Australia Wendy H. Oddy Ross D. Crosby The University of Western Australia, West Perth, Western Australia University of North Dakota School of Medicine and Health Sciences and Neuropsychiatric Research Institute, Fargo, North Dakota The current study aimed to compare the prevalence, stability, and psychosocial correlates of DSM–IV–TR and DSM-5 eating disorders, in a population-based sample of male and female adolescents followed prospectively from 14 to 20 years of age. Participants (N ⫽ 1,383; 49% male) were drawn from the Western Australian Pregnancy Cohort (Raine) Study, a prospective, population-based cohort study that has followed participants from prebirth to young adulthood. Detailed self-report questionnaires were used to assess eating disorder symptoms when participants were aged 14, 17, and 20 years. Comparisons between DSM–IV–TR and DSM-5 were conducted using McNemar chi-square tests and Fisher’s exact tests. Changes in eating disorder prevalence over time were considered using generalized estimating equations. Eating disorder prevalence rates were significantly greater when using DSM-5 than DSM– IV–TR criteria, at all time points for females and at age 17 only for males. “Unspecified”/“other” eating disorder diagnoses were significantly less common when applying DSM-5 than DSM–IV–TR criteria, but still formed 15% to 30% of the DSM-5 cases. Diagnostic stability was low for all disorders, and DSM-5 binge eating disorder or purging disorder in early adolescence predicted DSM-5 bulimia nervosa in later adolescence. Cross-over from binge eating disorder to bulimia nervosa was particularly high. Regardless of the diagnostic classification system used, all eating disorder diagnoses were associated with depressive symptoms and poor mental health quality of life. These results provide further support for the clinical utility of DSM-5 eating disorder criteria, and for the significance of binge eating disorder and purging disorder. Keywords: eating disorders, DSM–IV–TR, DSM-5, prevalence, Raine Study It has been established that eating disorders most commonly develop during adolescence (Steinhausen, Gavez, & Metzke, 2005; Stice, Marti, Shaw, & Jaconis, 2009). Under DSM–IV–TR nomenclature (American Psychiatric Association, 2000), current until May, 2013, between 1% and 4% of this age group could be expected to meet criteria for anorexia nervosa (AN) or bulimia nervosa (BN; Hoek, 2006; Hoek & Van Hoeken, 2003), and at least another 5% to meet criteria for an eating disorder not otherwise specified (EDNOS; Isomaa, Isomaa, Marttunen, KaltialaHeino, & Bjorkqvist, 2009; Kjelsas, Bjornstrom, & Gotestam, Karina L. Allen, Telethon Institute for Child Health Research, Centre for Child Health Research, The University of Western Australia, West Perth, Western Australia and School of Psychology, The University of Western Australia, Crawley, Western Australia; Susan M. Byrne, School of Psychology, The University of Western Australia; Wendy H. Oddy, Telethon Institute for Child Health Research, Centre for Child Health Research, The University of Western Australia; Ross D. Crosby, Department of Clinical Neuroscience, University of North Dakota School of Medicine and Health Sciences and Department of Biostatistics, Neuropsychiatric Research Institute, Fargo, North Dakota. We are extremely grateful to the Raine Study participants and their families who took part in this study and to the Raine Study team for cohort management and data collection. The first author is supported by an early career research fellowship from the National Health and Medical Research Council (NHMRC) of Australia. Core funding for the Western Australian Pregnancy Cohort (Raine) Study is provided by the Raine Medical Research Foundation; The University of Western Australia (UWA); the Faculty of Medicine, Dentistry and Health Sciences at UWA; the Telethon Institute for Child Health Research; the Women’s and Infant’s Research Foundation; and Curtin University. Funding for the 14-year Raine Study follow-up was provided by the Raine Medical Research Foundation and NHMRC project grants. Funding for the 17-year follow-up was provided by NHMRC program Grant 35314. Funding for the 20-year follow-up was provided by the Canadian Institutes of Health Research and NHMRC project grants. Correspondence concerning this article should be addressed to Dr. Karina Allen, Telethon Institute for Child Health Research, P.O. Box 855, West Perth, WA, Australia, 6872. E-mail: karina@ichr.uwa .edu.au 720 This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. DSM-5 EATING DISORDERS 2004). Conceptualizations of EDNOS have varied considerably, with some studies considering atypical AN and subthreshold BN only, and others including binge eating disorder (BED). Relatively few studies have assessed for purging disorder (PD), which was provisionally defined by Keel and colleagues in 2005 as repeated purging in the absence of objective binge eating, accompanied by the overevaluation of eating, weight, or shape (Keel, Haedt, & Edler, 2005). One of the limitations of DSM–IV–TR is the overreliance on EDNOS as a diagnostic category (Fairburn et al., 2007). In clinical settings, approximately 50% of those seen for treatment receive a “not otherwise specified” diagnosis when applying DSM–IV–TR criteria (Fairburn et al., 2007; Turner & Bryant-Waugh, 2004). In the community, this proportion rises to over 70% of eating disorder cases (Kjelsas et al., 2004; Machado, Goncalves, & Hoek, 2013; Wade, Bergin, Tiggemann, Bulik, & Fairburn, 2006). Individuals with EDNOS appear to be broadly comparable with individuals with full AN and BN in terms of symptom severity, symptom persistence, and functional impairment (Grilo et al., 2007; Hay et al., 2010; Thomas, Vartanian, & Brownell, 2009). Thus, it is important that these individuals are appropriately recognized in eating disorder diagnostic systems. Changes to diagnostic criteria in DSM-5 were designed, in part, to reduce the frequency of unspecified eating disorder diagnoses (Walsh, 2009). The fifth edition of the DSM (American Psychiatric Association, 2013) no longer requires amenorrhea for a diagnosis of AN, and AN may be diagnosed if an individual’s behavior indicates fear of weight gain and body image disturbance (e.g., continued self-imposed dietary restriction despite low body weight), even if their self-reported cognitions do not. “Significantly low body weight” has also been more flexibly defined, as “less than minimally normal” for adults, or “less than minimally expected” for children and adolescents (American Psychiatric Association, 2013). For BN, the twice per week frequency requirement for binge eating and purging has been reduced to once per week. Binge eating disorder, an example of EDNOS in DSM–IV– TR, has been recognized as a standalone disorder, and the required frequency of binge eating has also been set at once per week for 3 months, consistent with BN. In DSM–IV–TR, the provisional BED criteria required binge eating 2 days per week for 6 months (American Psychiatric Association, 2000). The “not otherwise specified” category of DSM-5 has been relabeled to give two separate categories. The first category, Other Specified Feeding or Eating Disorder (OSFED), incorporates specific eating disorder examples not captured by AN, BN, or BED. These include atypical AN, subthreshold BN, subthreshold BED, PD, and night eating syndrome (American Psychiatric Association, 2013). The second category, Unspecified Feeding or Eating Disorder, is intended for cases where insufficient information is available to make a specific eating disorder diagnosis, or where symptoms are genuinely unspecified and do not fit other diagnostic examples (American Psychiatric Association, 2013). Several studies have compared the prevalence and distribution of DSM–IV–TR and DSM-5 eating disorder diagnoses, using the proposed DSM-5 criteria released ahead of 2013 publication (Walsh, 2009). Results confirm that DSM-5 decreases the use of “unspecified” or “other” eating disorder diagnoses in treatmentseeking (Birgegard, Norring, & Clinton, 2012; Fairburn & Cooper, 2011) and community (Keel, Brown, Holm-Denoma, & Bodell, 721 2011; Machado et al., 2013; Stice, Marti, & Rohde, 2013) samples. However, research to date has focused almost exclusively on female participants, and only one study (Stice et al., 2013) has used prospective data to compare DSM–IV–TR and DSM-5 prevalence rates over time. Stice, Marti, and Rohde’s (2013) research was conducted with female adolescents (n ⫽ 496), meaning that no data are available regarding developmental changes in the prevalence of DSM-5 eating disorders in males. Stice et al.’s (2013) research is also the only source, to date, of data on the stability of DSM-5 eating disorders over time and on associations between DSM-5 eating disorders and psychological distress. Findings suggest that 1-year remission rates for DSM-5 eating disorders are high (similar to previous reports for DSM– IV–TR eating disorders in the community; Allen, Byrne, Oddy, & Crosby, in press; Stice et al., 2009), that cross-over between DSM-5 BED and BN is relatively common, and that DSM-5 eating disorders are associated with substantial psychosocial impairment (Stice et al., 2013). The current study aimed to compare the prevalence, stability, and psychosocial correlates of DSM–IV–TR and DSM-5 eating disorders in a population-based sample of male and female adolescents, followed prospectively from 14 to 20 years of age. We have previously reported on DSM–IV–TR disorders in this sample, including prevalence and risk factors at age 14 (Allen, Byrne, Forbes, & Oddy, 2009) and disorder stability from 14 to 20 (Allen et al., in press). For this study, it was hypothesized that: Hypothesis 1: The prevalence of DSM-5 eating disorders would be significantly greater than the prevalence of DSM– IV–TR eating disorders, for male and female participants. Hypothesis 2: The proportion of “unspecified” or “other” eating disorder diagnoses would be significantly lower when applying DSM-5 criteria than DSM–IV–TR criteria, for male and female participants. Hypothesis 3: Eating disorder stability would be low, and diagnostic cross-over would be high, for DSM-5 and DSM– IV–TR eating disorders, to a similar degree over 3-year and 6-year periods. Hypothesis 4: DSM-5 and DSM–IV–TR eating disorders would show similar associations with depressive symptoms and quality of life. Method Design and Participants Data were drawn from the Western Australian Pregnancy Cohort (Raine) Study, a population-based cohort study that has followed participants from prebirth to young adulthood. The Raine Study has been described in detail previously (Allen et al., 2009; Newnham, Evans, Michael, Stanley, & Landau, 1993). In brief, 2,900 women were recruited from the antenatal booking clinics at King Edward Memorial Hospital for women (KEMH), the only public maternity hospital in Western Australia, between May, 1989 and November 1991. Of the 2,900 women enrolled, 2,804 delivered live birth babies. Due to 64 multiple births, the initial This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. 722 ALLEN, BYRNE, ODDY, AND CROSBY cohort included 2,868 children. Children were assessed at birth and 1, 2, 3, 5, 8, 10, 14, 17, and 20 years. This study had a primary focus on the 14-, 17-, and 20-year follow-ups, when eating disorder data were collected. Eating disorder data were available for 1,598 participants at age 14, 1,242 participants at age 17, and 1,243 participants at age 20. We focused on participants with data at age 14 and at least one of the subsequent follow-ups, giving an effective sample size of 1,383 (49% male). This represents 76% of the participants who completed at least one of the 14 through 20-year assessments (N ⫽ 1,878) and 59% of the participants who were eligible for participation in the 14- through 20-year assessments (i.e., not deceased or lost to follow-up prior to age 14; N ⫽ 2,344). The mean age of the sample was 14.01 years (SD ⫽ 0.19, range ⫽ 13.00 –15.08) at the 14-year assessment, 16.92 years (SD ⫽ 0.24, range ⫽ 15.0 –18.2) at the 17-year assessment, and 20.01 years (SD ⫽ 0.44, range ⫽ 19.00 – 22.08) at the 20-year assessment. Procedure Questionnaire packages were posted to adolescents at the 14-, 17-, and 20-year assessments, for at-home completion prior to attendance at a face-to-face assessment session. Height and weight were measured during the face-to-face assessment. Body mass index was calculated using the standard formula (weight [kg]/ height [m]2). Data collection occurred in accordance with Australian National Health and Medical Research Council Guidelines for Ethical Conduct and was approved by the ethics committees of KEMH and Princess Margaret Hospital for Children. Measures Eating disorders at 14, 17, and 20 years. Eating disorder symptoms were assessed using 24 self-report items adapted from the Child Eating Disorder Examination (ChEDE; Bryant-Waugh, Cooper, Taylor, & Lask, 1996) and Eating Disorder ExaminationQuestionnaire (EDE-Q; Fairburn & Beglin, 1994). These items were self-report, as per the EDE-Q, but language was simplified or clarified when there was the possibility of confusion for 14-yearold adolescents. Response options were also simplified. The same four response options were used for all items: 0 ⫽ not at all; 1⫽ some of the time (once per week/a few times a month); 2 ⫽ a lot of the time (a few times a week); and 3 ⫽ most of the time (every day or nearly every day). Participants were asked to be conservative in their answers if they were unsure of the frequency of their behaviors. Questions referred to the previous month and the same items were used at all assessment points. The validity of a simplified EDE-Q rating scale for youth has been established (Goldschmidt, Doyle, & Wilfley, 2007) and support exists for the validity of self-report eating disorder assessment more generally (Berg, Peterson, Frazier, & Crow, 2011, 2012; Berg et al., 2012; Keel, Crow, Davis, & Mitchell, 2002; Mond, Hay, Rodgers, Owen, & Beumont, 2004). The 24 self-report items assessed for DSM–IV–TR and DSM-5 diagnostic criteria for AN, BN, BED, and PD, with the exception that items referred to 1 month rather than 3 to 6 months. Others have found good convergence between EDE-Q assessment with a 1 month time frame and interview assessment with a 3 to 6 month time frame, in terms of eating disorder detection and classification (Berg et al., 2012). One limitation of the EDE-Q, however, is that it does not assess criterion B of the diagnostic criteria for BED. Specifically, it does not determine whether three of the following symptoms are present: rapid eating, eating until uncomfortably full, eating large amounts when not hungry, eating alone, or feeling disgusted, depressed or guilty after overeating. When these criteria are omitted from diagnostic decision making, the prevalence of BED is inflated (Berg et al., 2012). To address this, we included the overevaluation of weight and shape as a requirement for BED diagnosis. Others have found overevaluation to be strongly associated with eating disorder psychopathology and distress about binge eating in samples of binge eaters (Hrabosky, Masheb, White, & Grilo, 2007; Mond, Hay, Rodgers, & Owen, 2007), and to reliably distinguish between individuals with BED and those who report binge eating without clinical impairment. Operationalized diagnostic requirements are summarized in Table 1. For DSM–IV– TR, the weight threshold for AN was set at the 3rd BMI percentile for age and sex, which is equivalent to weight at least 85% below that expected (a BMI of 17.5 in adults). An EDNOS diagnosis could be received if participants met our criteria for BED (see Table 1); fell just short of meeting full criteria for AN, either by continuing to menstruate or by losing a significant amount of weight without falling below the 3rd BMI percentile; fell just short of meeting full criteria for BN, by binge eating and purging less than twice per week; or reported recurrent purging (approximately weekly) with overevaluation of weight and shape, but without low weight or objective binge eating (see Table 1). For DSM-5, two sets of criteria (“a” and “b”) are presented for AN. The “a” criteria capture participants who endorsed marked fear of weight gain and body image disturbance, with a BMI below the 10th BMI percentile. This corresponds to a BMI of 18.5 in adults, which is the lower end of the World Health Organization’s healthy weight range (Cole, Flegal, Nicholls, & Jackson, 2007) and may be viewed as a marker of “minimally normal” for DSM-5 purposes (American Psychiatric Association, 2013). The “b” criteria for AN capture participants who did not endorse marked fear of weight gain, but who did demonstrate behaviors suggestive of fear of weight gain. This was defined as very low body weight (retaining the 3rd percentile in use for DSM–IV–TR) combined with some acknowledged fear of weight gain, some acknowledged dietary restriction, and marked body image disturbance (see Table 1). For OSFED, we were in a position to assess PD and atypical AN, but not subthreshold BN or subthreshold BED. We did not assess for Unspecified Feeding or Eating Disorders. For PD, “recurrent purging” was defined as self-induced vomiting or laxative misuse occurring once per week or a few times per month (the same frequency criterion as for DSM-5 BN and BED). For atypical AN, a diagnosis was made if participants had lost considerable weight over the preceding 3 to 4 years, without yet being markedly underweight, and endorsed marked fear of weight gain and body image disturbance. For atypical AN, it was necessary to consider change in weight between assessment points. To facilitate this, percentage ideal body weight (%IBW) was calculated for each participant at each time point, by dividing actual BMI by a BMI equal to DSM-5 EATING DISORDERS 723 Table 1 Diagnostic Requirements for DSM-IV-TR and DSM-5 Eating Disorders in the Current Study DSM-IV-TR This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. Anorexia nervosa (AN) 1. BMI ⬍ 3rd percentile for age/sex (equivalent to BMI ⬍ 17.5 in adults) 2. Fear of weight gain ⱖ 2 3. Body image disturbance: Importance of weight ⱖ 2 OR importance of shape ⱖ 2 OR feelings of fatness ⱖ 2 4. Amenorrhea OR on hormonal contraception. Bulimia nervosa (BN) 1. Objective binge eating: Eating an unusually large amount of food ⱖ 2 ⫹ loss of control over eating ⱖ 2 2. Compensatory behaviors: Self-induced vomiting ⱖ 2 OR laxative/pill use ⱖ 2 OR hard exercise ⱖ 2 3. Over-evaluation of weight/shape: Importance of weight ⱖ 2 OR importance of shape ⱖ 2 4. BMI ⬎ 3rd percentile for age/sex Eating disorder not otherwise specified (EDNOS) Binge eating disorder: 1. Objective binge eating: Eating an unusually large amount of food ⱖ 2 ⫹ loss of control over eating ⱖ 2 2. Distress over binge eating: Concern over loss of control over eating ⱖ 2 3. Over-evaluation of weight/shape: Importance of weight ⱖ 2 OR importance of shape ⱖ 2 4. BMI ⬎ 3rd percentile for age/sex 5. No self-induced vomiting or laxative/pill use 6. Hard exercise for weight control ⱕ 1 Other unspecified cases: 1a. All criteria for DSM-IV AN are met except for amenorrhea OR 1b. All criteria for DSM-IV AN are met except BMI is ⬎ 3rd percentile despite significant weight loss1 OR 1c. All criteria for DSM-IV BN are met except that binge eating and compensatory behavior occur less than 2x week (ratings ⱖ 1) OR 1d. Regular self-induced vomiting or laxative misuse is endorsed (ratings ⱖ 1) in the absence of low weight or objective binge eating, but with over-evaluation of weight/shape (importance of weight ⱖ 2 OR importance of shape ⱖ 2) DSM-5 Anorexia nervosa (AN) 1a. BMI ⬍ 10th percentile for age/sex (equivalent to BMI ⬍ 18.5 in adults) 2a. Fear of weight gain ⱖ 2 3a. Body image disturbance: Importance of weight ⱖ 2 OR importance of shape ⱖ 2 OR feelings of fatness ⱖ 2 OR 1b. BMI ⱕ 3rd percentile for age/sex 2b. Fear of weight gain ⱖ 1 AND trying to restrict food intake ⱖ 1 3b. Body image disturbance: Importance of weight ⱖ 2 OR importance of shape ⱖ 2 OR feelings of fatness ⱖ 2 Bulimia nervosa (BN) 1. Objective binge eating: Eating an unusually large amount of food ⱖ 1 ⫹ loss of control over eating ⱖ 1 2. Compensatory behaviors: Self-induced vomiting ⱖ 1 OR laxative/pill use ⱖ 1 OR hard exercise ⱖ 2 3. Over-evaluation of weight/shape: Importance of weight ⱖ 2 OR importance of shape ⱖ 2 4. BMI ⬎ 10th percentile for age/sex Binge eating disorder (BED) 1. Objective binge eating: Eating an unusually large amount of food ⱖ 1 ⫹ loss of control over eating ⱖ 1 2. Distress over binge eating: Concern over loss of control over eating ⱖ 1 3. Over-evaluation of weight/shape: Importance of weight ⱖ 2 OR importance of shape ⱖ 2 4. BMI ⬎ 10th percentile for age/sex 5. No self-induced vomiting or laxative/pill use 6. Hard exercise for weight control ⱕ 1 Other Specified Feeding or Eating Disorders (OSFED) Purging disorder: 1. Purging behaviour: Self-induced vomiting ⱖ 1 OR laxative/pill use ⱖ 1 2. Over-evaluation of weight/shape: Importance of weight ⱖ 2 OR importance of shape ⱖ 2 3. BMI ⬎ 10th percentile for age/sex 4. No objective binge eating Atypical anorexia nervosa: 1. BMI ⬎ 10th percentile despite significant weight loss1 2. Fear of weight gain ⱖ 2 3. Body image disturbance: Importance of weight ⱖ 2 OR importance of shape ⱖ 2 OR feelings of fatness ⱖ 2 Note. A score of 1 equates to symptoms occurring once per week/a few times a month, and a score of 2 equates to symptoms occurring a few times a week. Over-evaluation of weight and shape is used as a diagnostic criterion for binge eating disorder in lieu of the cognitive-emotional criteria listed in DSM-IV-TR and DSM-5 (which were not assessed in this study). BMI ⫽ Body mass index. 1 Significant weight loss is defined as a reduction in percentage Ideal Body Weight (% IBW) that is ⱖ 2 standard deviations of the cohort mean for change in % IBW, between age 10 and 14, age 14 and 17, or age 17 and 20 years. the 50th percentile for age and sex, and then multiplying by 100. At age 14, we considered change in % IBW from age 10 to age 14, by dividing % IBW at 14 by % IBW at 10. The same process was used to consider changes between ages 14 and 17, and ages 17 and 20. On average across all Raine Study participants, % IBW changed by approximately 2% between assessment points, with a standard deviation of 9%–10% (these changes included a decrease of 2% from age 10 to age 14, an increase of 2% from age 14 to age 17, and an increase of 1% from age 17 to age 20). We defined significant weight loss as a reduction in % IBW that was at least two standard deviations more than the sample mean, equating to a reduction of at least 18%–20% IBW over a 3- to 4-year time period. The mean of items relating to dietary restraint and eating, weight and shape concerns, excluding core diagnostic items (i.e., overevaluation of shape, overevaluation of weight, fear of weight gain, feelings of fatness), was computed as a global index of eating disorder psychopathology. Diagnostic items were excluded so that the index would represent eating disorder psychopathology distinct from diagnostic requirements, facilitating the comparison of dietary restraint and eating, weight and shape concerns across different diagnostic groups. Depressive symptoms. The self-report Beck Depression Inventory for Youth (BDI-Y; Beck, Beck, & Jolly, 2001) was used to assess depressive symptoms at ages 14 and 17. The BDI-Y is an adolescent adaptation of the adult Beck Depression Inventory-2 This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. 724 ALLEN, BYRNE, ODDY, AND CROSBY (BDI-2) and has well-established psychometric properties (Eack, Singer, & Greeno, 2008). Alpha coefficients in this sample were .97 at age 14 and .94 at age 17. The 21-item Depression Anxiety Stress Scale (DASS; Lovibond & Lovibond, 1995) was used to assess depressive symptoms at age 20. The DASS has demonstrated reliability and validity in clinical and nonclinical samples (Henry & Crawford, 2005; Ng et al., 2007), and scores on the Depression subscale correlate highly with those on the adult BDI-2. The alpha coefficient for the Depression subscale in this sample at age 20 was .89. Quality of life. The 12-item Short-Form Health Survey-12 (SF-12) (Ware, Kosinski, & Keller, 1996) was used to assess physical and mental quality of life at age 20. The SF-12 is a reliable, valid, and practical alternative to the longer SF-36 when assessing quality of life (Salyers, Bosworth, Swanson, LambPagone, & Osher, 2000; Ware et al., 1996). It makes use of norm-based scoring with a population mean of 50 (SD ⫽ 10). Quality of life data were not collected at ages 14 or 17. To address Hypothesis 4, nonparametric Kruskal-Wallis and Mann–Whitney U tests were used to compare depressive symptom scores and quality of life scores across DSM–IV–TR and DSM-5 eating disorder diagnoses. Comparisons in global eating disorder symptom scores and BMI were also conducted. These analyses focused on differences within each of the DSM systems (e.g., DSM-5 BN vs. DSM-5 BED vs. no DSM-5 disorder) rather than differences across the DSM systems (e.g., DSM-5 BN vs. DSM– IV–TR BN). This was necessary due to overlap in group membership across DSM–IV–TR and DSM-5 diagnoses. For DSM-5, we distinguish between atypical AN and PD when discussing OSFED diagnoses. All analyses were conducted in SPSS Statistics Version 20. Alpha was set at p ⬍ .05. Statistical Analyses Participant characteristics. Compared with participants included in this study (who completed two or more adolescent assessments), participants who completed no adolescent assessments were significantly more likely to be from single-parent families at 5, 8, and 10 years (p ⬍ .001), were significantly less likely to have employed parents at 5, 8, and 10 years (p ⬍ .001), had significantly lower family incomes at 5, 8, and 10 years (p ⬍ .001), and had significantly higher CBCL Externalizing Problem scores at 5, 8, and 10 years (ps ⫽ .001–.007). Results were similar for participants who completed one adolescent assessment, with the exception that this group was not more likely to be from a single parent family than participants who completed two or more adolescent assessments. These findings are consistent with the tendency for socially disadvantaged families to be lost to follow-up over time (Wolke et al., 2009). When comparing eating disorder data across participants who completed one adolescent assessment (excluded from the current study) and those who completed two or more (included in the study), there were no significant between-groups differences in eating disorder symptom scores, or in the proportion of participants meeting criteria for an eating disorder (ps ⫽ .187–.986). Data imputation. Missing eating disorder data were imputed for participants who completed two of the three adolescent assessments, using EM imputation with maximum likelihood estimation. Data were screened for patterns of missing variables prior to imputation. No evidence was found to suggest that data were not missing at random and Little’s MCAR test was nonsignificant, ␹2(1399) ⫽ 1376, p ⫽ .664. Data were imputed for 281 participants in total (141 participants at age 17 and 140 participants at age 20). The original raw dataset and imputed EM dataset were highly comparable in terms of estimated means and standard deviations for the eating disorder variables, eating disorder prevalence rates, and associations between eating disorder variables, depressive symptoms and quality of life. All subsequent analyses make use of the full, imputed data set. Preliminary analyses. Independent-samples t tests were used to determine if participants included in this study (N ⫽ 1,383) differed in meaningful ways from participants who took part in none (n ⫽ 961) or one (n ⫽ 495) of the adolescent assessments. Participants were compared on family, parent, and psychosocial variables at ages 5, 8, and 10 years. Adolescent eating disorder symptoms were also compared across participants who provided data at two or more adolescent assessment points and those who took part in only one adolescent assessment. After data screening, EM imputation using maximum likelihood estimation was used to impute missing eating disorder data for participants who completed two out of three adolescent assessments. Imputation was conducted using established principles and techniques (Kenward & Carpenter, 2007; Schafer & Graham, 2002) and is described below. Core analyses. All core analyses were conducted for male and female participants separately. To address Hypotheses 1 and 2, McNemar chi-square tests were used to compare the prevalence of DSM–IV–TR and DSM-5 disorders at ages 14, 17, and 20. Analyses were conducted for all disorders combined and, where numbers permitted, separately for different diagnoses. To complement these analyses, generalized estimating equations were used to examine changes in eating disorder prevalence over the 6-year study period, for DSM–IV–TR and DSM-5 separately. Generalized estimating equations account for correlations within individuals over time. Logistic binomial models were specified with a main effect of time, and the independence working correlation model was used (Wang & Carey, 2003). To address Hypothesis 3, two sets of analyses were undertaken. First, logistic regression models were used to determine whether the presence of an eating disorder at one time point (e.g., age 14) predicted the presence of a disorder at a later time point (e.g., age 20). If a disorder was stable over time, early incidence of the disorder should predict later incidence of the disorder. Second, and where numbers permitted, cross-over in eating disorder diagnoses was considered. Fisher’s exact tests were used to compare rates of cross-over for each eating disorder diagnosis. Results Preliminary Analyses Hypotheses 1 and 2: Eating Disorder Prevalence Rates Male participants. Prevalence rates for DSM–IV–TR and DSM-5 eating disorders in males are shown in Figures 1a and 1b, This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. DSM-5 EATING DISORDERS 725 Figure 1. Prevalence rates (%, with 95% confidence intervals) for DSM–IV–TR eating disorders (Figure 1a) and DSM-5 eating disorders (Figure 1b) in males (n ⫽ 680) at ages 14, 17, and 20 years. EDNOS refers to Eating Disorder Not Otherwise Specified, and OSFED refers to Other Specified Feeding or Eating Disorder. Prevalence rates for DSM–IV–TR EDNOS disorders, and for DSM-5 bulimia nervosa, increased significantly from age 14 to age 20. respectively. When comparing total prevalence rates, there were no significant differences between DSM–IV–TR and DSM-5 at age 14 (McNemar ␹2 ⫽ 0.50, p ⫽ .480) or age 20 (McNemar ␹2 ⫽ 1.33, p ⫽ .248). Rates were significantly higher when using DSM-5 than DSM–IV–TR criteria at age 17 (McNemar ␹2 ⫽ 8.10, p ⫽ .004; see Figure 1). Rates for DSM-5 OSFED (“other” eating disorders) were significantly lower than rates for DSM–IV–TR EDNOS (“unspecified” eating disorders) at age 20 (McNemar ␹2 ⫽ 6.67, p ⫽ .010), but not at ages 14 (McNemar ␹2 ⫽ 0.50, p ⫽ .479) or 17 (McNemar ␹2 ⫽ 0.10, p ⫽ .752). Conversely, rates of BN were significantly higher under DSM-5 than DSM–IV–TR at age 20 (McNemar ␹2 ⫽ 7.11, p ⫽ .008), but not at ages 14 (McNemar ␹2 ⫽ 0.50, p ⫽ .480) or 17 (McNemar ␹2 ⫽ 2.25, p ⫽ .134). The prevalence of DSM–IV–TR eating disorders in males increased significantly from age 14 to age 20, Wald ␹2(2) ⫽ 7.54, p ⫽ .023). As no boys met DSM–IV–TR criteria for AN, and very few met criteria for BN, this was largely due to a significant increase in the prevalence of unspecified EDNOS cases, Wald ␹2(2) ⫽ 7.02, p ⫽ .030 (see Figure 1a). The prevalence of DSM-5 eating disorders did not change significantly between age 14 and age 20, overall, Wald ␹2(2) ⫽ 5.42, p ⫽ .066), and there were also no significant changes in the prevalence of OSFED cases, Wald ␹2(2) ⫽ 0.17, p ⫽ .919. The prevalence of BN did increase significantly from age 14 to age 20, Wald ␹2(2) ⫽ 6.55, p ⫽ .038 (see Figure 1b). Group sizes were not sufficient to examine changes in DSM-5 AN, BED, or specific OSFED categories in boys. Within the DSM-5 OSFED category, there were three boys with PD at age 14 (0.4%), four with PD at age 17 (0.6%), and two with PD at age 20 (0.3%). At ages 14 and 20, two boys were classified with Atypical AN (0.3%), with no male participants receiving the diagnosis at age 17. Figure 2. Prevalence rates (%, with 95% confidence intervals) for DSM–IV–TR eating disorders (Figure 1a) and DSM-5 eating disorders (Figure 1b) in females (n ⫽ 703) at ages 14, 17, and 20 years. EDNOS refers to Eating Disorder Not Otherwise Specified, and OSFED refers to Other Specified Feeding or Eating Disorder. Prevalence rates for DSM–IV–TR EDNOS, and for DSM-5 bulimia nervosa and binge eating disorder, increased significantly from age 14 to age 20. ALLEN, BYRNE, ODDY, AND CROSBY 726 Table 2 Univariate Associations (Odds Ratios [With 95% CI]) Between DSM-I-TRV and DSM-5 Eating Disorder Diagnoses at Ages 14 and 17, and Diagnoses at Ages 17 and 20, For Female Participants Age 14 to age 17 DSM-IV Any BN EDNOS Any ⴱⴱ 4.84 [2.53, 9.24] 9.71ⴱ [2.14, 44.16] 3.58ⴱ [1.73, 7.38] BN Age 14 to age 20 EDNOS ⴱ 4.72 [1.47, 15.10] 7.08 [0.80, 42.30] 3.99ⴱ [1.09, 14.51] Any ⴱⴱ 3.64 [1.79, 7.42] 7.04ⴱ [1.54, 32.13] 3.07ⴱ [1.39, 6.79] ⴱ 2.66 [1.32, 5.35] 2.80 [0.53, 14.66] 2.65ⴱ [1.24, 5.66] BN 4.72 [1.47, 15.10] 7.08 [0.80, 62.30] 3.99ⴱ [1.09, 14.52] Age 14 to age 17 This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. DSM-5 Any BN BED PD⫾ Any ⴱⴱ 4.83 [2.74, 8.55] 4.46ⴱ [1.75, 11.36] 9.90ⴱⴱ [3.17, 30.89] 3.53ⴱ [1.36, 9.19] BN ⴱⴱ 5.41 [2.92, 10.00] 5.65ⴱⴱ [2.15, 14.86] 15.92ⴱⴱ [5.06, 50.14] 2.46 [0.79, 7.61] EDNOS ⴱ ⴱ 2.65 [1.24, 5.66] 1.51 [0.18, 12.76] 1.76 [0.71, 4.37] Age 14 to age 20 ⫾ BED PD .02 [.01–.03] .01 [.00–.01] .01 [.00–.01] .01 [.00–.01] 2.82 [0.77, 10.29] 2.66 [0.33, 21.33] .01 [.00–.01] 6.07ⴱ [1.27, 29.03] Any 1.82 [0.96, 3.45] 1.49 [0.48, 4.57] 2.50 [0.76, 8.28] 2.64 [0.98, 7.09] BN ⴱ 2.24 [1.04, 4.82] 2.19 [0.62, 7.74] 2.10 [0.45, 9.71] 3.18ⴱ [1.02, 9.91] Note. Any ⫽ any eating disorder; BED ⫽ binge eating disorder; BN ⫽ bulimia nervosa; EDNOS ⫽ eating disorder not otherwise specified; PD ⫽ purging disorder. Diagnoses in the leftmost column were predictor variables, and diagnoses along the upper rows were dependent variables. Separate models were run to examine associations between 14-year diagnoses and 17-year diagnoses, 14-year diagnoses and 20-year diagnoses, and 17-year diagnoses and 20-year diagnoses. * p ⬍ .05. ** p ⬍ .01. ⫾ PD is an example of the Other Specified Feeding or Eating Disorder category in DSM-5. Female participants. Prevalence rates for DSM–IV–TR and DSM-5 eating disorders in females are summarized in Figures 2a and 2b, respectively. Total prevalence rates were significantly greater when applying DSM-5 than DSM–IV–TR criteria, at ages 14 (McNemar ␹2 ⫽ 11.08, p ⬍ .001), 17 (McNemar ␹2 ⫽ 14.06, p ⬍ .001), and 20 (McNemar ␹2 ⫽ 17.05, p ⬍ .001). In large part, this was due to higher rates of BN when applying DSM-5 criteria, at ages 14 (McNemar ␹2 ⫽ 10.08, p ⫽ .001), 17 (McNemar ␹2 ⫽ 52.02, p ⬍ .001), and 20 (McNemar ␹2 ⫽ 38.02, p ⬍ .001). Rates of “unspecified”/“other” eating disorders were significantly lower when applying DSM-5 than DSM–IV–TR criteria, at ages 14 (McNemar ␹2 ⫽ 8.47, p ⫽ .004), 17 (McNemar ␹2 ⫽ 37.96, p ⬍ .001), and 20 (McNemar ␹2 ⫽ 38.25, p ⬍ .001). The prevalence of DSM–IV–TR eating disorders in females increased significantly from age 14 to ages 17 and 20, Wald ␹2(2) ⫽ 19.33, p ⬍ 001. This shift was largely accounted for by increases in the prevalence of unspecified EDNOS cases, Wald ␹2(2) ⫽ 12.49, p ⫽ 002. The prevalence of AN was low and did not change significantly over time, Wald ␹2(2) ⫽ 0.32, p ⫽ .571, nor did the prevalence of BN, Wald ␹2(2) ⫽ 4.94, p ⫽ .085. The prevalence of DSM-5 eating disorders in females also increased significantly from age 14 to ages 17 and 20, Wald ␹2(2) ⫽ 19.66, p ⬍ .001. There were no significant changes in the prevalence of OSFED cases, Wald ␹2(2) ⫽ 2.36, p ⫽ .307. Instead, the prevalence of BN increased significantly from age 14 to ages 17 and 20, Wald ␹2(2) ⫽ 32.33, p ⬍ .001, and the prevalence of BED increased significantly from age 14 to age 20, Wald ␹2(2) ⫽ 12.09, p ⫽ .002. There were no significant changes in the prevalence of AN, which remained low, Wald ␹2(2) ⫽ 3.52, p ⫽ .172. Within the DSM-5 OSFED category, the prevalence of PD was 2.7% (n ⫽ 19) at age 14, 2.1% (n ⫽ 15) at age 17, and 1.6% (n ⫽ 11) at age 20. These changes over time were not significant, Wald ␹2(2) ⫽ 2.09, p ⫽ .352. The prevalence of atypical AN was low, at 0.9% (n ⫽ 6) at age 14, 0% at age 17, and 0.1% (n ⫽ 1) at age 20. Hypothesis 3: Eating Disorder Stability and Diagnostic Cross-Over Males. Given the small number of male eating disorder cases, diagnosis-specific stability, and rates of diagnostic crossover, were not considered for male participants. At an overall level, there was evidence of eating disorder continuity from age 14 to age 17, and from age 17 to age 20, among males. A DSM–IV–TR eating disorder at 14 significantly predicted a disorder at age 17 (OR 47.00, 95% CIs [10.66, 207.20], p ⬍ .001), and a DSM–IV–TR disorder at age 17 significantly predicted a disorder at age 20 (OR 46.43, 95% CIs [10.53, 204.69], p ⬍ .001). However, 95% confidence intervals for odds ratios were extremely large, suggesting considerable uncertainty in the magnitude of associations. There was no significant association between 14-year eating disorder status and 20-year eating disorder status (p ⫽ .511). The presence of a DSM-5 eating disorder at age 17 was also significant in predicting a DSM-5 disorder at age 20 (OR 39.45, 95% CIs [13.40, 116.12], p ⬍ .001), but there were no significant associations between a DSM-5 eating disorder at age 14 and a disorder at either 17 (p ⫽ .999) or 20 (p ⫽ .999). Females. For females, it was possible to consider the stability of eating disorders overall and by diagnosis. Results are summarized in Table 2. Overall, a DSM–IV–TR eating disorder at age 14 significantly predicted a disorder at ages 17 and 20, and a DSM– IV–TR disorder at age 17 significantly predicted a disorder at age 20 (see Table 2). When considering specific diagnoses, BN at age 14 predicted EDNOS (but not BN) at age 17, and BN at age 17 predicted EDNOS disorder (but not BN) at age 20. There were no significant associations between BN at age 14 and DSM–IV disorders at age 20. An unspecified EDNOS diagnosis at age 14 predicted EDNOS and BN at age 17, and BN only at age 20. An unspecified EDNOS diagnosis at age 17 predicted EDNOS and BN at age 20. DSM-5 EATING DISORDERS 727 Age 17 to age 20 Any BN ⴱⴱ EDNOS ⴱⴱ ⴱⴱ 6.73 [2.53, 17.95] 10.29 [2.65, 39.86] 3.98ⴱ [1.36, 11.65] 10.30 [6.18, 17.20] 8.52ⴱⴱ [3.20, 22.72] 8.51ⴱⴱ [4.94, 14.65] 9.37 [5.44, 16.16] 5.30ⴱ [1.90, 14.81] 8.62ⴱⴱ [4.86, 14.27] Age 14 to age 20 BED This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. Age 17 to age 20 ⫾ Any BN BED PD⫾ 11.56ⴱⴱ [8.18, 18.64] 8.00ⴱⴱ [4.73, 13.54] 5.73ⴱ [1.63, 20.14] 6.72ⴱⴱ [2.38, 18.94] 17.58ⴱⴱ [9.58, 32.24] 12.31ⴱⴱ [6.74, 22.51] 5.07ⴱ [1.28, 20.17] 6.11ⴱ [2.01, 18.56] 1.89 [0.79, 4.55] 1.03 [0.30, 3.49] 2.64 [0.32, 21.56] 1.68 [0.21, 13.26] 7.27ⴱ [2.18, 24.29] 3.44 [0.89, 13.28] 7.59 [0.88, 55.59] 11.61ⴱ [2.28, 49.09] PD 1.27 [0.37, 4.34] 1.30 [0.17, 10.10] 1.97 [0.25, 15.69] 1.30 [0.17, 10.10] 0.01 [0.00, 0.01] 0.01 [0.00, 0.01] 0.01 [0.00, 0.01] 0.01 [0.00, 0.01] For DSM-5, an eating disorder at age 14 significantly predicted a disorder at age 17, but not at age 20, and a disorder at age 17 significantly predicted a disorder at age 20 (see Table 2). The 3-year stability of BN was strong, with significant associations between BN at 14 and BN at 17, and between BN at 17 and BN at 20. A BN diagnosis at 14 did not predict any other eating disorder diagnosis at age 17, and it did not predict BN or other diagnoses at age 20. Although no diagnoses were significant in predicting BED over time, BED at age 14 was a significant predictor of BN at age 17, and BED at age 17 was a significant predictor of BN at age 20. Purging disorder at age 14 predicted PD at age 17 and BN at age 20, and PD at age 17 predicted PD and BN at age 20. Patterns of diagnostic cross-over for female participants are summarized in Table 3. Statistical comparisons were not conducted for AN or atypical AN, due to small group sizes. For DSM–IV–TR, there were no significant differences in diagnostic cross-over rates for BN and those for unspecified disorders (Fisher’s exact test p ⫽ .610). For DSM-5, cross-over rates were significantly lower for participants with an initial diagnosis of BN compared with participants with an initial diagnosis of BED (Fisher’s exact test p ⫽ .009) or PD (Fisher’s exact test p ⫽ .009). Cross-over was comparable for BED and PD (Fisher’s exact test p ⫽ .692), and the likelihood of progressing to BN did not differ significantly across those with an initial diagnosis of BED and those with an initial diagnosis of PD (Fisher’s exact test p ⫽ .086). Nonetheless, it is worth noting that the proportion of BED participants progressing to a BN diagnosis was double the proportion of PD participants making this transition (52% vs. 26%; see Table 3). When comparing DSM–IV–TR and DSM-5 directly, cross-over was significantly more likely for DSM–IV–TR BN than for DSM-5 Table 3 Diagnostic Cross-Over From Initial DSM-IV-TR or DSM-5 Eating Disorder Diagnosis to Later Diagnoses, for Female Participants (N [% of Initial Diagnosis]) Initial diagnosis Subsequent diagnosis DSM-IV Anorexia nervosa Bulimia nervosa Unspecified (EDNOS) No disorder Anorexia nervosa (n ⫽ 1) Bulimia nervosa (n ⫽ 20) Unspecified (EDNOS) (n ⫽ 96) 1 (100%) 0 (0.0%) 1 (1.0%) 0 (0.0%) 2 (10.0%) 6 (6.2%) 0 (0.0%) 8 (40.0%) 32 (33.3%) 0 (0.0%) 10 (50.0%) 57 (59.4%) Other (OSFED) DSM-5 Anorexia nervosa Bulimia nervosa Binge eating disorder Atypical anorexia⫾ Purging disorder⫾ No disorder Anorexia nervosa (n ⫽ 7) Bulimia nervosa (n ⫽ 71) Binge eating disorder (n ⫽ 23) Atypical anorexia ⫾ (n ⫽ 7) Purging disorder ⫾ (n ⫽ 31) 1 (14.3%) 1 (1.4%) 0 (0%) 0 (0%) 1 (3.2%) 2 (28.6%) 28 (39.4%) 12 (52.2%) 0 (0.0%) 8 (25.9%) 1 (14.3%) 2 (2.8%) 2 (8.7%) 0 (0.0%) 2 (6.4%) 1 (14.3%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 4 (5.6%) 1 (4.3%) 0 (0.0%) 4 (12.9%) 2 (28.6%) 36 (50.7%) 8 (34.8%) 7 (100%) 16 (51.6%) Note. EDNOS ⫽ eating disorder not otherwise specified (DSM-IV-TR); OSFED ⫽ Other Specified Feeding or Eating Disorder (DSM-5). ⫾ Atypical anorexia nervosa and purging disorder are examples of OSFED in DSM-5. ALLEN, BYRNE, ODDY, AND CROSBY 728 Table 4 Depressive Symptoms, Quality of Life, Global Eating Disorder Symptoms, and BMI in Males (M(SD)), by DSM-I-TRV and DSM-5 Diagnoses Age 14 This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. DSM-IV Any disorder No disorder DSM-5 Any disorder No disorder Age 17 n BMI Global ED BDI-Y n BMI Global ED BDI-Y 8 635 22.50 (3.99) 20.89 (3.91) 1.47 a (0.66) 0.25 b (0.30) 15.37 (12.05) 4.93 (5.08) 8 672 27.32 a (5.16) 22.70 b (4.13) 1.49 a (0.68) 0.24 b (0.34) 16.00 a (10.75) 5.95 b (7.27) 8 672 22.50 (3.99) 20.89 (3.91) 1.47 a (0.66) 0.25 b (0.30) 15.37 (12.05) 4.93 (5.08) 18 662 26.81 a (4.31) 22.65 b (4.11) 1.30 a (0.53) 0.23 b (0.32) 16.80 a (5.03) 5.01 b (5.33) Note. Within DSM-IV and DSM-5, rows with different subscripts differ significantly at p ⬍ .05, as determined using non-parametric Mann-Whitney U tests. BMI ⫽ Body Mass Index; BDI-Y ⫽ Beck Depression Inventory-Youth; DASS ⫽ Depression Anxiety Stress Scale; Global ED ⫽ Global index of eating disorder symptoms; QoL ⫽ Quality of Life. BN (Fisher’s exact test p ⫽ .015), and movement from BN to an “unspecified” or “other” disorder was also significantly more likely with DSM–IV–TR than with DSM-5 (Fisher’s ...
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Explanation & Answer

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Running head: EATING DISORDERS

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Eating Disorders
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EATING DISORDERS

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According to Piotrowski (2013), eating disorders are illnesses characterized by irregular
eating habits and concerns with one’s body weight. According to DSM-V, eating disorders are
classified as mental illnesses. Anorexia Nervosa, Bulimia Nervosa, and Binge Eating are the
most prevalent eating disorders affecting both sexes across the world with most reported cases in
North America. Anorexia Nervosa is a condition characterized by an urge to cut on weight with
individuals suffering from the condition restricting the number of calories they consume in a day
(Watson et al., 2018). Individuals with the condition also exercise compulsively in an attempt to
maintain a thin body. Bulimia Nervosa, on the other hand, is an eating disorder characterized by
excessive eating within a short period followed by an attempt to vomiting of what has been
consumed ...


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