Depression and anxiety: predictors of eating disorder symptoms and substance addiction severity
Bibliographic record
Abstract
Depression, anxiety, and low self-esteem are frequently associated with eating and substance use disorders (SUD). Given the high prevalence of concurrent disorders in individuals with eating and substance use problems, it is critical to identify other psychological factors important for consideration in treatment of this population. Individuals (N = 314) seeking treatment for eating disorder (ED) and problematic substance use were administered a self-report questionnaire battery. Regression analyses indicated that depressive (p < 0.001) and anxiety (p = 0.03) symptoms significantly predicted ED symptom severity. Anxiety (p = 0.01) and self-esteem (p = 0.06; trend) predicted whether or not participants used substances. Greater substance addiction severity was associated with higher anxiety (p = 0.01) and lower self-esteem (p = 0.04). These findings suggest the importance of assessing other mental health problems in individuals with concurrent eating and SUD, and offering strategies to help these individuals cope with depressive and anxiety symptoms, and low self-esteem. Integrated treatment issues are discussed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".