Brief Physician Advice for Heavy Drinking College Students: A Randomized Controlled Trial in College Health Clinics
Bibliographic record
Abstract
OBJECTIVE: The aim of this study was to test the efficacy of brief physician advice in reducing alcohol use and related harm in college students. METHOD: The College Health Intervention Projects (CHIPs) is a randomized, controlled clinical trial with 12-month follow-up conducted in five college health clinics in Wisconsin; Washington state; and Vancouver, Canada. Of the 12,900 students screened for high-risk drinking, 484 men and 502 women met inclusion criteria and were randomized into a control (n = 493) or intervention (n = 493) group. Ninety-six percent of students participated in the follow-up procedures. The intervention consisted of two 15-minute counseling visits and two follow-up phone calls, and used motivational interviewing, contracting, diary cards, and take-home exercises. RESULTS: No significant differences were found between groups at baseline on alcohol use, age, socioeconomic or smoking status, rates of depression, or measures of alcohol-related harm. At 12 months, the experimental subjects reduced their 28-day drinking totals by 27.2%, and the control group reduced their totals by 21%. A mixed effects repeated measures model found a statistical difference in favor of the brief-intervention group (beta = 4.7, SE = 2.0, p = .018) in 28-day drinking totals. The total Rutgers Alcohol Problem Index score was also significantly different during the 12-month follow-up period (beta = 0.8, SE = 0.4, p = .033). There was no difference on the other outcome measures of interest, such as frequency of excessive heavy drinking, health care utilization, injuries, drunk driving, depression, or tobacco use. CONCLUSIONS: The study supports resource allocation and implementation of alcohol screening and brief physician advice in primary care-based college health clinics.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".