Prescription weight loss medication use and eating disorder psychopathology among adolescent boys and young men from Canada and the United States
Bibliographic record
Abstract
This study aimed to identify the prevalence of prescription weight loss medication use among boys and men, describe the sociodemographic differences between those who did and did not report use, and explore differences in eating disorder attitudes and behaviors between those who did and did not report use. Data from 1543 boys and men from Canada and the United States aged 15 to 35 were analyzed. The prevalence of prescription weight loss medication use in the past 12 months was estimated. Fisher's exact tests and independent samples t-tests were used to determine the differences in sociodemographic identifiers and eating disorder attitudes and behaviors between those who did and did not use prescription weight loss medication. Among the sample, 1.2 % (n = 19) reported use of prescription weight loss medication in the past 12 months. Those who reported use of prescription weight loss medication were significantly older and had significantly higher body mass index compared to those who did not report use. Any loss of control while eating, binge eating, and purging via vomiting in the past 28 days were all more common among those who reported the use of prescription weight loss medication. Eating disorder psychopathology was also significantly higher among those who reported the use of prescription weight loss medication. These preliminary findings underscore that eating disorder attitudes and behaviors may be more prevalent among boys and men who use prescription weight loss medication, emphasizing the need for more research to understand these novel findings.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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 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".