Internet-Based Brief Intervention to Prevent Unhealthy Alcohol Use among Young Men: A Randomized Controlled Trial
Bibliographic record
Abstract
INTRODUCTION: Alcohol use is one of the leading modifiable morbidity and mortality risk factors among young adults. STUDY DESIGN: 2 parallel-group randomized controlled trial with follow-up at 1 and 6 months. SETTING/PARTICIPANTS: Internet based study in a general population sample of young men with low-risk drinking, recruited between June 2012 and February 2013. Intervention: Internet-based brief alcohol primary prevention intervention (IBI). The IBI aims at preventing an increase in alcohol use: it consists of normative feedback, feedback on consequences, calorific value alcohol, computed blood alcohol concentration, indication that the reported alcohol use is associated with no or limited risks for health. Intervention group participants received the IBI. Control group (CG) participants completed only an assessment. MAIN OUTCOME MEASURES: Alcohol use (number of drinks per week), binge drinking prevalence. Analyses were conducted in 2014-2015. RESULTS: Of 4365 men invited to participate, 1633 did so; 896 reported low-risk drinking and were randomized (IBI: n = 451; CG: n = 445). At baseline, 1 and 6 months, the mean (SD) number of drinks/week was 2.4(2.2), 2.3(2.6), 2.5(3.0) for IBI, and 2.4(2.3), 2.8(3.7), 2.7(3.9) for CG. Binge drinking, absent at baseline, was reported by 14.4% (IBI) and 19.0% (CG) at 1 month and by 13.3% (IBI) and 13.0% (CG) at 6 months. At 1 month, beneficial intervention effects were observed on the number of drinks/week (p = 0.05). No significant differences were observed at 6 months. CONCLUSION: We found protective short term effects of a primary prevention IBI. TRIAL REGISTRATION: Controlled-Trials.com ISRCTN55991918.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".