Eating disorder symptom profiles and physical activity cognitions and motivations among emerging adults with physical activity intentions.

Eating Disorder Symptom Profiles and Physical Activity Cognitions and Motivations among Emerging Adults with Physical Activity Intentions - PMC Skip to main content An official website of the United States government Here's how you know Here's how you know Search Log in Primary site navigation Search Log in Search PMC Full-Text Archive Search in PMC Journal List User Guide As a library, NLM provides access to scientific literature. Inclusion in an NLM database does not imply endorsement of, or agreement with, the contents by NLM or the National Institutes of Health. Learn more: PMC Disclaimer | PMC Copyright Notice Eat Behav . Author manuscript; available in PMC: 2026 Jun 1. Published in final edited form as: Eat Behav. 2026 Jan 5;60:102068. doi: 10.1016/j.eatbeh.2026.102068 Eating Disorder Symptom Profiles and Physical Activity Cognitions and Motivations among Emerging Adults with Physical Activity Intentions Tyler B Mason 1, * , Wei-Lin Wang 1 , Shirlene D Wang 2 , Stephen S Intille 3 , Alexander J Rothman 4 , Donald Hedeker 5 , Genevieve F Dunton 1, 6 Author information Article notes Copyright and License information 1 Department of Population and Public Health Sciences, University of Southern California Keck School of Medicine, Los Angeles, CA 2 Department of Preventive Medicine, Northwestern University, Chicago, IL 3 Khoury College of Computer Sciences and Bouvé College of Health Sciences, Northeastern University, Boston, MA 4 Department of Psychology, University of Minnesota, Minneapolis, MN 5 Department of Public Health Sciences, University of Chicago, Chicago, IL 6 Department of Psychology, University of Southern California, Los Angeles, CA * Corresponding author: Tyler B. Mason, University of Southern California Keck School of Medicine, 2001 N Soto Street, Los Angeles, CA 90032; tylermas@usc.edu . Issue date 2026 Jan. PMC Copyright notice PMCID: PMC13222661  NIHMSID: NIHMS2135240  PMID: 41505839 The publisher's version of this article is available at Eat Behav Abstract Eating disorders (EDs) encompass maladaptive eating behaviors and body image concerns and often include unhealthy physical activity behaviors (e.g., driven and compulsive exercise). Despite exercise’s potential health benefits, its driven pursuit may exacerbate ED symptoms. This study used latent profile analysis in a non-clinical sample of emerging adults to identify classes of ED symptoms and their associations with physical activity cognitions and motivations (e.g., self-efficacy, identity, self-regulatory efforts). Emerging adults completed a baseline questionnaire of ED symptoms and measures of physical activity cognitions and motivations. Latent profile analysis was run with ED symptoms as indicators, including body dissatisfaction, overvaluation, dietary restraint, binge-eating frequency, and driven exercise frequency. Extracted groups were then compared on physical activity cognitions and motivations. Four distinct groups were identified: recurrent binge-eating symptoms (RBE), cognitive ED symptoms (COG), driven exercise symptoms (DE), and low ED symptoms (LED). These groups exhibited varying patterns of physical activity cognitions and motivations, with the DE group showing elevated adaptive cognitions and motivations (e.g., self-efficacy, self-regulation) and strong physical activity identity. Both the DE and COG groups reported higher guilt and shame regarding not exercising and reinforcing self-regulatory efforts. The RBE group displayed lower amotivation and less self-regulation for physical activity, suggesting challenges in incorporating exercise into their routines. These findings highlight similar and different physical activity cognitions and motivations that may underlie varying ED presentations and highlight the need for tailored interventions to promote healthy physical activity behaviors among individuals with EDs. Keywords: eating disorders, exercise, binge eating, physical activity, emerging adults Introduction Given the role of exercise in body image, weight, and energy balance, many individuals with eating disorders (EDs) engage in high levels of exercise, and this exercise is sometimes excessive, compulsive, and driven. Therefore, driven exercise has been outlined as a core ED behavior ( Meyer & Taranis, 2011 ). Exercise is a planned and structured movement behavior that falls under the broader umbrella of physical activity (PA), which involves any bodily movements. Although exercise is a well-documented health-promoting behavior ( Fletcher et al., 2018 ), there is a complex association between exercise and EDs. Individuals with anorexia nervosa and bulimia nervosa often report driven exercise behaviors ( Schlegl et al., 2018 ), which are associated with negative psychiatric and behavioral indices and poor treatment outcomes ( Dalle Grave et al., 2008 ; Lichtenstein et al., 2017 ). However, not all EDs are characterized by elevated exercise. For instance, binge-eating disorder is characterized by little PA and exercise ( Vancampfort et al., 2014 ), and lower PA and exercise may be a maintenance factor for the disorder ( Mason et al., 2020 ; 2021 ). Therefore, depending on the ED symptom presentation, exercise could be a possible treatment for symptoms, but exercise could also maintain or worsen symptoms. EDs have been associated with both adaptive and maladaptive PA cognitions and motivations and may be characterized by cognitive exercise obsessive thoughts (e.g., “I need to exercise”) in the absence of actual excessive exercise behaviors ( Bratland-Sanda et al., 2019 ). In a study of women with and without EDs, Schlegl and colleagues (2018) found that women with EDs reported greater exercise enjoyment, challenge, and recognition but lower exercise ill-health avoidance (i.e., motivations to engage in exercise for its health benefits) and affiliation (i.e., motivations to engage in exercise as a social activity) motives compared to healthy controls. Women with EDs also reported greater exercising for weight management and appearance motives than controls, which are often maladaptive in the context of EDs ( Schlegl et al., 2018 ). Relatedly, EDs and compulsive exercise are positively related to feeling guilt and shame when missing or avoiding exercise ( Bratland-Sanda et al., 2022 ; Mond et al., 2008 ). Finally, stronger exercise identity (i.e., believing being someone who exercises is an important part of one’s identity) has been shown to be related to both compulsive and adaptive exercise, suggesting exercise identity may not differentiate between healthy vs. unhealthy types of exercise ( Palermo & Rancourt, 2023 ). In sum, cognitions and motivations toward PA are altered in EDs, but much of the research focuses specifically on clinical EDs. Due to emerging adulthood being a social, educational, and developmental transition period, emerging adulthood is a critical window for ED onset ( El-Jor et al., 2025 ). ED symptoms, including driven exercise, have increased in emerging adults over the past few decades, and significant variability in cognitive and behavioral ED symptoms is often seen in non-clinical samples ( Romano et al., 2022 ). Data from 5,848 college students in the Healthy Minds Study found that approximately 30% and 40% of students reported moderate-to-high weight concerns and past-month binge eating, respectively ( Lipson & Sonneville, 2020 ). Additionally, a separate analysis of 8,251 students from the Healthy Minds Study showed that 11% of men and 17% of women reported past-month compulsive exercise ( Ganson et al., 2022 ). Furthermore, vulnerability for ED symptoms may be particularly increased among emerging adults who exercise/intend to exercise ( Lechner et al., 2019 ). Given the heterogeneity of symptoms that may be present in a non-clinical sample of emerging adults who exercise, it is important to study both bivariate associations between ED symptoms and PA cognitions and motivations as well as associations between clusters of ED symptoms and PA cognitions and motivations. In the current secondary data analysis, we examined bivariate correlations between ED symptoms and PA cognitions and motivations. Then, we used latent profile analysis (LPA) to empirically classify emerging adults based on ED symptoms and to examine how the identified groups differed on PA cognitions and motivations. We generally expected positive correlations between ED symptoms and maladaptive cognitions and motivations and negative associations with adaptive cognitions and motivations. Given the data-driven nature of LPA, no specific hypotheses were developed. This data can increase our understanding of potential PA-specific factors to focus on in interventions seeking to limit unhealthy exercise behaviors and promote healthy PA in non-clinical samples of emerging adults; however, the cross-sectional nature of the study does not allow for understanding of processes as antecedent or consequences of ED symptoms. Results of the LPA will allow us to delineate specific PA cognitions and motivations that are associated with specific ED symptom profiles, which may provide insight into early detection and prevention of EDs and unhealthy exercise behaviors. Method Participants and Procedure Participants were emerging adults from across the United States who enrolled in the Temporal Influences on Movement & Exercise (TIME) study, which focused on understanding long-term PA patterns in emerging adults ( Wang et al., 2022 ). Recruitment occurred from March 2020-August 2021, with data collection ending in August 2022. There were detailed inclusion and exclusion criteria, assessed by self-report during the screening process (see Table S1 ). The study was approved by the Institutional Review Boards of the University of Southern California and Northeastern University. All participants provided informed consent to participate in the study. The current study only examined the baseline self-report questionnaire data, which were collected remotely. The study involved other measures not being used in the current analyses (see Wang et al., 2022 ). The sample size for the current study was slightly lower than the recommended LPA sample size of 300 ( Sinha et al., 2021 ) but is consistent with other LPA analyses in ED research that have been successful at delineating classes ( Abber et al., 2024 ; Jackson et al., 2022 ; Wildes et al., 2013 ). Measures ED symptoms. The Eating Disorder Examination Questionnaire (EDEQ; Fairburn & Beglin, 1994 ) was used to measure ED symptoms. Consistent with factor analyses of the EDEQ ( Grilo et al., 2015 ), we calculated three cognitive subscales: Overvaluation (two items), Body Dissatisfaction (two items), and Dietary Restraint (three items). In addition, behavioral frequencies of ED symptoms from the EDEQ were used, including binge-eating frequency and driven exercise (i.e., number of episodes of exercising in either a “driven” or “compulsive” way to control weight, shape or to burn off calories) in the past 28 days. Cronbach’s alpha for dietary restraint was .83, and the Spearman-Brown coefficients (appropriate for 2-item measures) for overvaluation and body dissatisfaction were .93 and .88. PA intention strength. Strength of intention to engage in PA most days of the week was assessed with a single item ( Rhodes & Rebar, 2017 ). Participants indicated their commitment to intentions on a scale from 0 ( not committed at all ) to 5 ( very committed ). Exercise motivation. The Behavioral Regulation in Exercise Questionnaire-3 (BREQ-3; Markland & Tobin, 2010 ) measured intrinsic and extrinsic motivations for exercise. The BREQ-3 included 24 items, which comprised six subscales with four items each. The subscales included Amotivation (i.e., low attitudes about the importance of PA), External Regulation (i.e., engaging in exercise for external rewards or appeasement of others), Introjected Regulation (i.e., regulating exercise through feelings of guilt and shame), Identified Regulation (i.e., valuing benefits of exercise), Integrated Regulation (i.e., congruence of exercise with one’s life goals; ), and Intrinsic Regulation (i.e., engaging in exercise for pleasure). Items were rated on a five-point scale from 0 ( not true for me ) to 4 ( very true for me ). Cronbach’s alphas for the subscales ranged from .72-.89. PA habits. The Self-Report Habit Index ( Verplanken & Orbell, 2003 ) was used to measure PA habits. The scale asked participants how often they do moderate and vigorous PA automatically, without thinking, without having to consciously remember, and without realizing. Items were answered on a scale ranging from 1 ( disagree completely ) to 7 ( agree completely ). Cronbach’s alpha was .93. PA identity. A four-item PA identity scale was used to assess PA identity, which describes the extent to which someone sees their identity aligning with being someone who engages in PA ( Wilson & Muon, 2008 ). Participants responded to each item on a scale from 1 ( strongly disagree ) to 5 ( strongly agree ). Cronbach’s alpha was .83. PA enjoyment. The Physical Activity Enjoyment Scale ( Kendzierski & DeCarlo, 1991 ) was used to measure PA enjoyment. Respondents rated 18 items about how they feel while doing moderate or vigorous PA (including walking, exercise, sports) using a 7-point bipolar rating scale. For example, one item used a rating scale from 1 ( I enjoy it ) to 7 ( I hate it ). A composite score was created with eleven items reverse scored. Higher PACES scores reflect greater levels of enjoyment. Cronbach’s alpha was .93. Exercise preference and tolerance. The Preference for and Tolerance of the Intensity of Exercise Questionnaire ( Ekkekakis et al., 2005 ) was used to assess exercise intensity preference (e.g., tendency to choose a level of exercise intensity) and tolerance (i.e., extent someone can tolerate uncomfortable and unpleasant exercise intensities). Eight tolerance and eight preference items were rated on a scale from 1 ( I totally disagree ) to 5 ( I totally agree ). Cronbach’s alphas were .89 and .87 for preference and tolerance, respectively. Exercise self-efficacy. The Physical Exercise Self-efficacy Scale ( Schwarzer, & Renner, 2009 ) measured physical exercise self-efficacy, which is the degree to which someone can carry out exercise intentions even when experiencing barriers. Five items were rated on a scale from 1 ( very uncertain ) to 4 ( very certain ). Cronbach’s alpha was .88. PA regulatory effort. The 12-item Physical Activity Self-Regulation scale (PASR-12; Umstattd et al., 2009 ) regulatory effort for moderate and vigorous PA. The PASR-12 was comprised of six two-item subscales, including Self-monitoring, Goal-setting, Eliciting social support, Reinforcement, Time management, and Relapse prevention. Items were rated on a five-point scale from 1 ( never ) to 5 ( very often ). Spearman-Brown coefficients ranged from .67-.80. Demographics. Participants were asked to self-report sex at birth, gender identity, sexual identity, race, ethnicity, age, college education, height, and weight. Self-reported height and weight were used to calculate body mass index (BMI). Statistical Analyses Bivariate correlations were calculated among study variables in SPSS v29.0. To generate profiles of ED symptoms, a LPA was calculated with Mplus software v8.3. LPA is a person-centered statistical approach that derives profiles based on multiple continuous indicators. Indicators used to generate ED symptom profiles in the current LPA included body dissatisfaction, overvaluation of shape and weight, dietary restraint, binge-eating frequency, and driven-exercise frequency. The LPA was conducted using the three-step procedure ( Asparouhov & Muthén, 2014 ). In the first step, model fit statistics were used to decide on the number of groups/classes. Models were estimated with the number of classes added iteratively (starting with a one-class solution). The best-fitting model was determined using model fit statistics including log likelihood (LL), Akaike information criterion (AIC), Bayesian information criterion (BIC), sample-size-adjusted BIC (aBIC), and entropy. Lower AIC, BIC, and aBIC values indicated better fit, and larger entropy values indicated better classification accuracy. In evaluating the number of classes, we accounted for the proportion of the sample in each class because solutions with only a small proportion of the sample in some classes may not be meaningful or generalizable. In the second step, most-likely class membership was obtained; this accounted for the estimated probability that an individual can belong to each of the possible classes. Third, chi-square analyses were conducted to compare groups on demographics and PA cognitions and motivations. Full-information maximum likelihood estimation was used to account for missing outcomes data. Results There were 283 participants with complete data on the indicators. The sample was relatively racially diverse, predominantly non-Hispanic, mostly cisgender, and most had some or more college education (see Table 1 ). Missing data was low, with only the intention strength and BREQ-3 having missing data (<2%). Bivariate correlations among study variables are reported in Table 2 . Dietary restraint was positively correlated with PA intention strength, self-efficacy, preference, and tolerance; introjected, identified, integrated, and intrinsic motivation; and all self-regulatory constructs. Overvaluation and body dissatisfaction were positively correlated with greater external and introjected motivations and reinforcement; body dissatisfaction was also related to lower PA identity. Binge-eating frequency was not correlated with any PA variables. Driven exercise frequency was positively correlated with PA intention strength, self-efficacy, habit, tolerance, and identity; introjected, identified, and integrated motivation; and all self-regulatory constructs except eliciting social support. Table 1. Demographic Characteristics of the Sample, N=283 Characteristic M(SD) Age, years 23.69 ± 3.14 Body mass index, kg/m 2 22.64 ± 3.15 N (%) Sex at birth Female 124 (43.8%) Male 158 (55.8%) Missing 1 (0.4%) Race (select all that apply) White 130 (45.9%) Black 3 (12.7%) American Indian 13 (4.6%) Asian 20 (10.2%) Chinese 37 (13.1%) Filipino 18 (6.4%) Japanese 5 (1.8%) Korean 12 (4.2%) Vietnamese 11 (3.9%) Other Asian 14 (4.9%) Guamani 1 (0.4%) Other Pacific Islander 4 (1.4%) Ethnicity Hispanic 205 (72.4%) Non-Hispanic 78 (27.6%) Highest Education Some high school 1 (0.4%) High school graduate or equivalent 34 (12.0%) Some college or technical school 107 (37.8%) College graduate 141 (49.8%) Sexual Identity Straight 195 (68.9%) Gay 13 (4.6%) Bisexual 49 (17.3%) Something else 20 (7.1%) Unsure 5 (1.8%) Missing 1 (0.4%) Gender identity Cisgender 24 (93.3%) Transgender, male-to-female 1 (0.4%) Transgender, female-to-male 3 (1.1%) Transgender, gender non-conforming 12 (4.2%) Unsure 3 (1.1%) Open in a new tab Table 2. Bivariate Correlations among Study Variables, N=283 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 1. Restraint 1 .44 .50 .19 .32 .22 .20 .04 −.06 .03 .30 .16 .17 .15 −.04 .14 .20 .08 .24 .19 .14 .26 .20 .16 2. Overvaluation - 1 .62 .30 .26 .07 −.07 −.09 −.04 .15 .39 .09 .02 −.03 −.03 .10 .03 −.06 .11 .12 −.00 .19 .06 −.04 3. BD - - 1 .29 .22 .01 −.06 −.11 .02 .19 .33 .04 −.09 −.09 .06 .05 .03 −.14 .06 .06 .03 .19 .02 .01 4. Binge eating - - - 1 .14 −.01 .02 −.01 −.07 .08 .12 −.05 −.03 −.03 .04 .02 −.02 −.07 −.05 −.02 .09 .03 −.03 −.08 5. Driven exercise - - - - 1 .23 .19 .13 −.09 .01 .20 .16 .22 .06 −.05 .11 .24 .20 .13 .23 .07 .14 .18 .24 6. PA intention strength - - - - - 1 .34 −.03 −.10 −.18 .27 .43 .44 .45 .10 .13 .30 .50 .42 .33 .06 .37 .34 .39 7. PA self-efficacy - - - - - - 1 .48 −.19 −.10 .03 .21 .33 .36 −.28 .22 .38 .47 .36 .30 .18 .24 .49 .46 8. PA habit - - - - - - - 1 .13 −.09 −.17 −.19 .19 .18 −.68 .07 .14 .35 .14 .10 .28 −.01 .27 .35 9. Amotivation - - - - - - - - 1 .28 −.20 −.45 −.19 −.23 .04 −.19 −.20 −.23 −.20 −.26 .12 −.36 −.15 −.04 10. External - - - - - - - - - 1 .06 −.22 −.19 −.26 .05 −.05 −.04 −.13 −.13 −.13 .13 −.14 −.08 −.08 11. Introjected - - - - - - - - - - 1 .48 .38 .25 .10 .12 .26 .22 .32 .25 −.02 .43 .32 .18 12. Identified - - - - - - - - - - - 1 .72 .50 .13 .25 .33 .54 .43 .34 −.00 .54 .40 .26 13. Integrated - - - - - - - - - - - - 1 .65 −.11 .30 .45 .72 .41 .32 .12 .39 .50 .42 14. Intrinsic - - - - - - - - - - - - - 1 −.12 .30 .39 .63 .41 .24 .17 .45 .43 .28 15. PA enjoyment - - - - - - - - - - - - - - 1 −.15 −.14 −.18 −.12 −.06 −.17 −.06 −.18 −.14 16. PA Preference - - - - - - - - - - - - - - - 1 .62 .31 .20 .24 .16 .25 .31 .16 17. PA Tolerance - - - - - - - - - - - - - - - - 1 .45 .32 .31 .21 .37 .43 .39 18. PA identity - - - - - - - - - - - - - - - - - 1 .41 .34 .23 .41 .48 .46 19. Self-monitoring - - - - - - - - - - - - - - - - - - 1 .52 .14 .57 .53 .38 20. Goal-setting - - - - - - - - - - - - - - - - - - - 1 .21 .52 .55 .47 21. Elicit SS - - - - - - - - - - - - - - - - - - - - 1 .14 .31 .26 22. Reinforcement - - - - - - - - - - - - - - - - - - - - - 1 .50 .28 23. Time management - - - - - - - - - - - - - - - - - - - - - - 1 .51 24. Relapse prevention - - - - - - - - - - - - - - - - - - - - - - - 1 Open in a new tab Note. SS=social support. Correlations greater than .13 are significant at p<.05 The model fit statistics for solutions from 1-class to 5-classes are shown in Table S2 . Model fit continued to improve across all class solutions; however, class sizes decreased substantially at the 5-class solution, with one class having three participants. Thus, we settled on a 4-class solution to have more stable results and to examine group differences. The 4-class solution included the following groups, which were defined based on mean values on the set of ED symptom indictors: (1) recurrent binge eating symptoms (RBE; 3.2%; n =9), (2) cognitive ED symptoms (i.e., primarily overvaluation and body dissatisfaction) (COG; 25.0%; n =71), (3) driven exercise symptoms (DE; 6.4%; n =18), and (4) low ED symptoms (LED; 65.4%; n =185). Two classes had relatively low numbers of participants, yet this is consistent with the fact that this is a non-clinical sample. These classes were retained as they represent important ED-relevant classes. Figure 1 depicts class values on the profile indicators and Table 3 displays each classes’ value on indicators. Figure 1. Open in a new tab Bar graph of class values on indicators Note . Sx=symptoms Table 3. Mean values of groups on indicator variables, N=283 Recurrent binge eating (RBE) ( n =9) Cognitive ED (COG) ( n =71) Driven exercise (DE) ( n =18) Low ED (LED) (n=185) Dietary restraint 2.14 2.99 3.49 0.83 Overvaluation 5.63 5.13 3.88 2.09 Body dissatisfaction 3.77 5.17 4.37 2.45 Binge eating 12.74 1.44 1.31 0.32 Driven exercise 2.86 1.52 17.14 0.18 Open in a new tab The comparisons of classes by demographic characteristics are displayed in Table 4 . Detailed inferential statistics, p -values, and Cohen’s d effect size values are in Table S3 . The LED class had a significantly lower mean BMI than the DE and COG groups. Participants in the DE group were less likely to be female compared to the LED group and less likely to be White compared to the LED and COG groups. Compared to the COG group, sexual minority participants were less likely to be in the LED and RBE groups. Hispanic participants were more likely to be in the COG group compared to the LED group. Table 4. Comparisons between Latent Classes on Demographics, N=283 Recurrent binge eating sx (BE) Cognitive ED sx (COG) Driven exercise sx (DE) Low ED sx (LED) Differences ( p <.05) Age 23.11 23.34 22.93 23.85 ns BMI 30.51 29.12 25.75 23.18 LED<COG,DE; COG>DE Female sex a 0.56 0.55 0.33 0.59 DE<LED Sexual minority a 0.11 0.43 0.28 0.28 COG>RBE,LED White a 0.45 0.40 0.16 0.51 DE<COG,LED Hispanic a 0.45 0.42 0.34 0.21 COG>LED Open in a new tab Note. Sx=symptoms a Values are proportions. The comparisons of groups on PA cognitions and motivations are displayed in Table 5 . See Table S4 for detailed inferential statistics, p -values, and Cohen’s d effect size values. Compared to other groups, the DE group was marked by elevated PA-specific intention strength, self-efficacy, integrated regulation, introjected regulation, preference for high intensity, tolerance of high intensity, goal setting, reinforcement, time management, and relapse prevention. The COG group showed PA cognitions and motivations characterized by lower habits, greater amotivation, higher external regulation, higher introjected regulation, and greater reinforcement. The RBE group was marked by lower PA-specific amotivation, time management, and relapse prevention. There were no significant group differences in identified motivation, intrinsic motivation, PA enjoyment, self-monitoring, or eliciting social support. Table 5. Mean Comparisons between Latent Classes on Validators, N=283 Recurrent binge eating sx (RBE) Cognitive ED sx (COG) Driven exercise sx (DE) Low ED sx (LED) Differences ( p <.05) M M M M PA intention strength 3.66 3.94 4.24 3.61 DE>LED Exercise self-efficacy 2.36 2.40 3.19 2.59 DE>RBE,COG PA habit 4.15 3.08 5.94 4.10 COG<DE,LED Amotivation 0.66 1.88 0.99 1.29 COG>RBE External 2.65 4.56 3.22 2.87 COG>LED Introjected 9.43 11.51 10.62 7.03 LED<COG,DE Identified 10.88 12.08 12.64 11.49 ns Integrated 7.33 7.44 11.32 7.78 DE>RBE,COG,LED Intrinsic 9.33 9.61 10.29 9.80 ns Enjoyment 3.14 2.98 2.83 2.91 ns Preference 3.07 2.87 3.13 2.83 DE>LED Tolerance 2.78 2.99 3.59 2.86 DE>RBE,COG,LED PA identity 2.90 3.15 3.85 3.13 DE>RBE,COG,LED Self-monitoring 3.16 3.52 3.71 3.22 ns Goal setting 2.83 3.14 4.03 2.98 DE>RBE,COG,LED Elicit Social Support 2.00 1.89 2.26 1.90 ns Reinforcement 3.44 3.95 3.87 3.38 LED<COG,DE Time management 2.10 2.87 3.64 2.67 DE>RBE,COG,LED; RBE<COG Relapse prevention 1.38 2.03 3.33 2.10 RBE<COG,DE,LED; DE>COG,LED Open in a new tab Note. Sx=symptoms; PA=physical activity Discussion In general, we found that dietary restraint and driven-exercise frequency were positively correlated with a range of adaptive and maladaptive PA cognitions and motivations, yet binge-eating frequency was not associated with any PA cognitions and motivations in bivariate analyses. Overvaluation and body dissatisfaction were positively correlated with greater external and introjected motivations and reinforcement, which suggests that individuals with higher body image concerns may regulate PA through shame and external reward and are reinforced by positive effects (possibly changes in appearance). The LPA identified four groups—three groups with ED symptoms and one with low ED symptoms. Each group was characterized by a unique set of PA cognitions and motivations. Higher weight, sexual minority, and Hispanic participants were more likely to report elevated cognitive ED symptoms compared to low ED symptoms, which is consistent with prior research showing higher ED pathology in these groups ( Alegria et al., 2007 ; Parker & Harriger, 2020 ; Rø et al., 2012 ). The DE group had higher BMI than the LED group. This could be due to higher muscularity or use of driven exercise for weight loss, but this cannot be differentiated from our analyses. The DE group was also more likely to be male and non-White, which aligns with other research finding higher muscle dysmorphia symptoms in South Asian and Middle Eastern young adults ( Ganson et al., 2023 ). Consistently, a meta-analysis found higher problematic exercise in males, including time spent in exercise and exercising with greater volume/intensity than planned ( Alcaraz-Ibanez et al., 2022 ). Little research has examined race-ethnicity differences in driven exercise, but one study found higher compulsive exercise in Asian-American men ( Kelly et al., 2015 ). Individuals in the DE group had elevated levels of cognitions and motivations (e.g., self-efficacy, self-regulatory capacity) that typically support higher PA engagement. They also reported PA being an important part of their identity. Therefore, while for most individuals it is beneficial to focus on improving PA cognition and motivations, there may be a point in which elevated levels suggest engaging in recurrent driven-exercise episodes. Moreover, this collection of PA cognitions and motivations, along with driven exercise behaviors, may be a sign of addiction toward exercise, which is often seen in restrictive EDs and muscle dysmorphia ( Klein et al., 2004 ; Olave et al., 2021 ). Oppositely, the COG group showed a pattern of controlled motivations and non-habitual activity. These individuals did not have a clear internal desire to engage in PA and may be motivated by external rewards, which is consistent with broader research on elevated controlled motivations and poorer eating and body image ( Panão & Carraça, 2020 ). While the DE and the COG groups showed mostly different patterns of PA cognitions and motivations from one another, both groups had higher guilt and shame regarding not exercising (i.e., introjected regulation), which is a key factor associated with compulsive and addictive exercise and EDs ( Mond et al., 2008 ). Therefore, the introjected regulation trait may be a defining transdiagnostic feature of EDs across symptom presentations. Perhaps guilt and shame regarding not exercising are due to the high level of body image concerns that were present in the DE and COG groups. That is, by not exercising, individuals with body image concerns may fear weight gain or muscle loss, leading to guilt and shame. In addition, guilt and shame may be associated with disappointing others, being embarrassed socially about not exercising, or social appearance anxiety. Also, reinforcement self-regulation was higher in the DE and COG groups. Reinforcement self-regulatory motivations are defined as focusing on improving positive feelings after PA--similar to the concept of affective response (i.e., changes in mood and emotions after an event). Several conceptual papers outline the role of elevated rewarding affective response to exercise as a maintenance factor of EDs, possibly due to the use of exercise as a compensatory behavior for eating ( Coniglio et al., 2022 ; Kolar & Gorrell, 2021 ). The RBE group was the smallest group and thus there was limited power to detect differences. However, the RBE group was marked by low amotivation, suggesting that there was a desire to be physically active. Moreover, the group showed low time management and low relapse prevention and thus may have difficulty fitting PA into their schedules and continuing activity when experiencing barriers. Similarly, Crandall and colleagues (2011) found that individuals with binge-eating disorder reported elevated barriers to engaging in exercise compared to matched controls, including inconvenient scheduling, taking time away from family, and having few places to exercise ( Crandall et al., 2011 ). Persistent binge eating may be associated with poor executive functioning abilities, which could manifest as difficulty planning and shifting between multiple priorities ( Smith et al., 2018 ). Yet, more research is needed to determine why these barriers exist among individuals who engage in binge eating. These findings have clinical implications and underscore areas for future research. Our findings suggest that guilt and shame over not exercising and over-focusing on reinforcing aspects of PA may be defining features across different ED symptom presentations. Reducing these types of PA cognitions and motivations may be helpful in preventing EDs or may be a warning sign of a possible ED. While targeting the reinforcing aspects of PA may be helpful for individuals without EDs, people with ED symptoms may be overly focused on body- and weight-related feelings after PA (e.g., less feeling fat), which in turn may increase ED symptoms and unhealthy exercise. Self-compassion treatments may be one therapeutic approach that could reduce exercise-related guilt and shame ( Röthlin et al., 2023 ). Additionally, individuals with RBE appear to be interested in PA but perhaps have less self-regulatory resources to engage and continue PA. Given the benefits of PA in treating binge eating ( Mason et al., 2020 ; 2021 ), intervention strategies that focus on increasing self-regulatory capacity to engage in activity are needed for individuals with RBE symptoms. Although this study increases knowledge of PA traits underlying ED symptoms in a non-clinical sample of emerging adults, there are several limitations. First, this was a cross-sectional analysis and thus no causal inferences about the associations between PA cognitions and motivations and ED symptoms can be made. Second, this study used self-report retrospective survey questionnaires of ED symptoms. Retrospective recall biases may lead to misreporting of symptoms. Third, there were low levels of other types of compensatory ED behaviors (e.g., vomiting, laxatives), so these variables could not be included in the LPA. Fourth, while transgender young adults were represented in our study, focus on transgender adults is needed in future research given their risk for EDs and muscle dysmorphia ( Nagata et al., 2024 ). Fifth, the aims of the parent study required specific inclusion/exclusion criteria that may have led to a less representative sample. Finally, the RBE and DE groups were small, limiting ability to detect significant associations. While a similar sample size has been used in prior research ( Abber et al., 2024 ; Jackson et al., 2022 ; Wildes et al., 2013 ), the modest sample size is a limitation. Cohen’s d effect size estimates for group comparisons showed that there was generally only power to detect medium and large mean differences between groups. Suggestions to improve future research include using multiple assessment points, clinical interviews, and larger samples to capture more symptom variability. In conclusion, distinct groups were identified based on ED symptomatology, with varying patterns of PA cognitions and motivations. Experiencing guilt and shame over not exercising and overemphasis on reinforcing aspects of PA emerged as potential features across ED presentations. These findings underscore the importance of addressing maladaptive PA cognitions and motivations in for ED prevention, highlighting the need for interventions aimed at reducing exercise-related guilt and shame while enhancing self-regulatory capacities for healthy PA engagement. Supplementary Material 1 NIHMS2135240-supplement-1.docx (37KB, docx) Highlights. Latent profile analysis was run with eating disorder (ED) symptoms as indicators. Extracted groups were compared on physical activity (PA) cognitions and motivations. There were four groups-binge-eating, cognitive ED, driven exercise, and low ED. Findings highlight PA cognitions and motivations that may underlie ED presentations. Role of Funding Sources: This project was supported in part by grants K01DK124435 from the National Institute of Diabetes and Digestive and Kidney Diseases Award Number (NIDDK) and U01HL146327 from National Heart, Lung, and Blood Institute (NHLBI). The content is solely the responsibility of the authors and does not necessarily represent the official views of NIDDK or NHLBI. Footnotes Conflicts of Interest: The authors have no conflicts of interest. Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. Data availability statement. 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