Screening for<i>DSM-5</i>Other Specified Feeding or Eating Disorder in a Weight-Loss Treatment–Seeking Obese Sample
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Bibliographic record
Abstract
OBJECTIVE: To evaluate the effectiveness of specific self-report questionnaires in detecting DSM-5 eating disorders identified via structured clinical interview in a weight-loss treatment-seeking obese sample, to improve eating disorder recognition in general clinical settings. METHOD: Individuals were recruited over a 3-month period (November 2, 2011, to January 10, 2012) when initially presenting to a hospital-based weight-management center in the northeastern United States, which offers evaluation and treatment for outpatients who are overweight or obese. Participants (N = 100) completed the Structured Clinical Interview for DSM-IV eating disorder module, a DSM-5 feeding and eating disorders interview, and a battery of self-report questionnaires. RESULTS: Self-reports and interviews agreed substantially in the identification of bulimia nervosa (DSM-IV and DSM-5: tau-b = 0.71, P < .001) and binge-eating disorder (DSM-IV and DSM-5: tau-b = 0.60, P < .001), modestly for subthreshold binge-eating disorder (tau-b = 0.44, P < .001), and poorly for other subthreshold conditions (night-eating syndrome: tau-b = -0.04, P = .72, r = 0.06 [DSM-5]). DISCUSSION: Current self-report assessments are likely to identify full syndrome DSM-5 eating disorders in treatment-seeking obese samples, but unlikely to detect DSM-5 other specified feeding or eating disorders. We propose specific content changes that might enhance clinical utility as suggestions for future evaluation.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it