Associations between eating disorders and illicit drug use among college students
Bibliographic record
Abstract
OBJECTIVE: To estimate the associations between a positive eating disorder screen and any lifetime eating disorder diagnosis and illicit drug use among a large, diverse sample of college students. METHOD: We analyzed data from the national (United States), cross-sectional 2018-2019 Healthy Minds Study (HMS; n = 42,618; response rate: 16%). HMS collects information on the physical, mental, and social health of college students. Multiple logistic regression analyses were used to estimate the association between a positive eating disorder screen (measured using the SCOFF) and any self-reported lifetime eating disorder diagnosis and self-reported illicit drug use in the past 30 days (any illicit drug use and use of marijuana, cocaine, heroin, methamphetamines, stimulants, ecstasy, opioids, benzodiazepines), while adjusting for potential confounders. RESULTS: Among the sample, 54.34% (n = 28,608) were female and the mean age of participants was 23.30 (SE ± 0.05) years. Logistic regression analyses revealed unique associations between a positive eating disorder screen and any lifetime eating disorder diagnosis and illicit drug use among the sample of college student participants. A positive eating disorder screen was most strongly associated with methamphetamine use (adjusted odds ratio [AOR] 3.93, 95% confidence interval [CI] 1.43-10.78), and any lifetime eating disorder diagnosis was most strongly associated with benzodiazepine use (AOR 3.42, 95% CI 2.28-5.13). DISCUSSION: Illicit drug use is common among college students who screen positive for an eating disorder and report any lifetime eating disorder diagnosis. The co-occurring nature of eating disorders and illicit drug use may complicate treatment and lead to compounded adverse health outcomes.
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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 | 0.001 | 0.001 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".