Attention deficit hyperactivity disorder and future alcohol outcomes: Examining the roles of coping and enhancement drinking motives among young men
Bibliographic record
Abstract
OBJECTIVE: Although there is evidence that Attention Deficit Hyperactivity Disorder (ADHD) symptoms are positively related to alcohol use and related problems among young adults, little research has examined the mechanisms that might explain this association. In response, this study examined the mediating effects of coping and enhancement drinking motives on the prospective associations between ADHD symptoms and alcohol outcomes. METHOD: Participants (N = 4,536) were young men from the Cohort Study on Substance Use Risk Factors. Measures of ADHD symptoms and those of drinking motives, heavy episodic drinking (HED) and alcohol use disorder symptoms were used from the baseline and 15-month follow-up assessments. RESULTS: Findings indicated that the associations of ADHD-inattention symptoms with alcohol use disorder (AUD) symptoms and with HED were partially and completely mediated through drinking motives, respectively, whereas drinking motives did not mediate the ADHD-hyperactivity/impulsivity-symptoms-alcohol outcomes associations. CONCLUSION: Results indicated that coping and enhancement motives partially explained the ADHD-inattention symptoms-subsequent alcohol outcomes association. These findings suggest that interventions targeting enhancement and coping motives may help prevent problematic drinking among young men with elevated ADHD-inattention symptoms.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".