Legal Performance-Enhancing Substances and Substance Use Problems Among Young Adults
Bibliographic record
Abstract
BACKGROUND: Legal performance-enhancing substance(s) (PES) (eg, creatine) are widely used among adolescent boys and young men; however, little is known about their temporal associations with substance use behaviors. METHODS: We analyzed prospective cohort data from the National Longitudinal Study of Adolescent to Adult Health, Waves I to IV (1994-2008). Logistic regressions were used to first assess adolescent substance use (Wave I) and use of legal PES (Wave III) and second to assess use of legal PES (Wave III) and subsequent substance use-associated risk behaviors (Wave IV), adjusting for potential confounders. RESULTS: Among the sample of 12 133 young adults aged 18 to 26 years, 16.1% of young men and 1.2% of young women reported using legal PES in the past year. Adolescent alcohol use was prospectively associated with legal PES use in young men (odds ratio 1.39; 95% confidence interval [CI] 1.13-1.70). Among young men, legal PES use was prospectively associated with higher odds of problematic alcohol use and drinking-related risk behaviors, including binge drinking (adjusted odds ratio [aOR] 1.35; 95% CI 1.07-1.71), injurious and risky behaviors (aOR 1.78; 95% CI 1.43-2.21), legal problems (aOR 1.52; 95% CI 1.08-2.13), cutting down on activities and socialization (aOR 1.91; 95% CI 1.36-2.78), and emotional or physical health problems (aOR 1.44; 95% CI 1.04-1.99). Among young women, legal PES use was prospectively associated with higher odds of emotional or physical health problems (aOR 3.00; 95% CI 1.20-7.44). CONCLUSIONS: Use of legal PES should be considered a gateway to future problematic alcohol use and drinking-related risk behaviors, particularly among young men.
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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 | 0.001 | 0.001 |
| 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".