Eating Disorders And Adaptation To Body Image Stressors Among Women Of Arab Descent
Bibliographic record
Abstract
Problem: In the U.S., about 20 million women suffer from clinically significant eating disorders (EDs). New studies show that EDs spare no color; however, there is limited research on EDs among non-White populations. In particular, little is known about EDs and associated risk factors among Arab American college women.\nPurpose: The first aim was to test a middle-range theory (MRT) of adaptation to body image stressors derived from the Roy Adaptation Model (RAM). The MRT describes how different body image stressors (sociocultural pressure to be thin, cultural distance, acculturation, and social media usage) interact with the ideal body shape discrepancy (IBSD), predict emotional regulation, and lead to change in eating behavior and body image. The second aim was to measure the prevalence of ED symptoms.\nMethod: A descriptive, cross-sectional study was conducted with 271 Arab American college women between the ages of 18 and 26. Students completed a background, and a social media usage survey, the Perceived Sociocultural Pressure scale, the Vancouver Index of Acculturation — Arab version, the Contour Drawing Rating scale, the Forms of Self-Criticizing/Reassuring, and the Eating Disorder Examination Questionnaire. The MRT was tested using Structural Equation Modeling.\nResults: First, the MRT achieved a good fit; however, not all theoretical propositions were supported. Specifically, sociocultural pressure to be thin and cultural distance significantly predicted IBSD. Also, emotional regulation mediated the relationship between sociocultural pressure /IBSD and eating behaviors on the one hand and body image on the other. Second, the prevalence of ED symptoms was 17%, while 32.5% of participants engaged in regular objective binge eating and 12.2% in regular compensatory behaviors during the past month.\nDiscussion: The study provides four findings: (1) there was strong support for the RAM major propositions; (2) the MRT achieved a good fit; (3) there was a high prevalence of ED symptoms, binge eating, and the use of compensatory behaviors; and (4) cultural factors such as Arabic thin ideal, within group differences, and high obesity may contribute to this high prevalence.\nConclusion: Health care providers and university health centers need to screen women of color for risk of developing EDs
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".