Family Medicine Residents’ Beliefs, Attitudes and Performance with Problem Drinkers
Bibliographic record
Abstract
Fifty-six second-year family medicine residents completed a survey on their knowledge and beliefs about problem drinkers. Most residents felt responsible for screening and counseling, were confident in their clinical skills in these areas, and scored well on related knowledge questions. However, only 18% felt that problem drinkers would often respond to brief counseling sessions with physicians while 36% felt that moderate drinking was a reasonable goal for patients with severe alcohol dependence. Residents were then visited by unannounced simulated patients (SPs) presenting with alcohol-induced hypertension or insomnia. Residents detected the SP in 45 out of 104 visits. In the 59 undetected SP visits, residents asked about alcohol consumption in 47 visits (80%), discussed the relationship between alcohol use and the presenting complaint in 37 visits (63%), and recommended a specific weekly consumption in 35 visits (59%). Only 31% offered reduced drinking strategies, and most did not ask about features of alcohol dependence. These results suggest that residents have the fundamental clinical skills required to manage the problem drinker who gives a clear history and is receptive to advice. Educational efforts with residents should focus on the importance of systematic screening, taking an alcohol history under more challenging conditions, identifying the subtler presentations of alcohol problems, counselling the less receptive patient at an earlier stage of change, distinguishing the problem drinker from the alcohol-dependent patient, and offering specific behavioral strategies for the problem drinker.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".