Randomized Controlled Trial on the Effects of a Skills–Based Workshop on Medical Students’ Management of Problem Drinking and Alcohol Dependence
Bibliographic record
Abstract
The purpose of this study was to determine whether a skills-based workshop will improve medical students' management of problem drinking and alcohol dependence in simulated patients. Seventy-six 3rd and 4th year Ontario medical students were randomized to receive a 3-h workshop on either problem drinking and alcohol dependence or depression (control condition). Students then completed eight simulated office visits (OSCE stations) with simulated patients presenting with depression, problem drinking or alcohol dependence. Examiners completed a checklist of the questions asked and advice given by the student, and simulated patients and examiners completed a global rating scale. Four months later, students were sent a survey on their knowledge, attitudes, and behavior towards patients with alcohol problems. The alcohol group received significantly higher assessment and management checklist scores and global rating scores than did the depression group (p < 0.01) and performed better on almost all aspects of clinical management of both problem drinking and alcohol dependence. On the follow-up survey (n = 55) the alcohol group showed a significant increase in beliefs about self-efficacy in managing alcohol problems (p < 0.05) and had greater knowledge of reduced drinking strategies, but the two groups did not differ on other measures. A skills-based workshop causes marked short-term improvements in medical students' management of problem drinking and alcohol dependence, an increase from baseline to postworkshop in self-efficacy beliefs that was sustained through to follow-up, and greater knowledge of reduced drinking strategies. Repeated reinforcement of clinical skills may be required for a long-term impact on clinical behavior.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.016 | 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".