Heavy Drinking in University Students With and Without Attention-Deficit/Hyperactivity Disorder: Contributions of Drinking Motives and Protective Behavioral Strategies
Bibliographic record
Abstract
This study examined rates of heavy drinking and alcohol problems in relation to drinking motives and protective behavioral strategies in university students with a documented current diagnosis of attention-deficit/hyperactivity disorder (ADHD; n = 31) compared with students with no history of ADHD (n = 146). Participants completed a Web-based questionnaire, and logistic regression models tested interactions between ADHD/comparison group membership and motives and protective strategies. Group differences in rates of heavy drinking and alcohol problems were not statistically significant, but medium-sized risk ratios showed that students without ADHD reported heavy drinking at a rate 1.44 times higher than students with ADHD and met screening criteria for problematic alcohol use at a rate of 1.54 times higher than students with ADHD. Other key findings were, first, that drinking to enhance positive affect (e.g., drinking because it is exciting), but not to cope with negative affect (e.g., drinking to forget your worries), predicted both heavy drinking and alcohol problems. Second, only protective behavioral strategies that emphasize alcohol avoidance predicted both heavy drinking and alcohol problems. Contrary to expectations, we found no ADHD-related moderation of effects of motives or protective strategies on our alcohol outcomes. Results of this study are limited by the small sample of students with ADHD but highlight tentative similarities and differences in effects of motives and strategies on drinking behaviors and alcohol problems reported by students with and without ADHD.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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 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".