German Medical Students’ Beliefs about How Best to Treat Alcohol Use Disorder
Bibliographic record
Abstract
BACKGROUND/AIMS: A minority of German medical students believe they know how to support smokers willing to quit. This paper examined whether the same would be true for treating alcohol use disorder (AUD), and individual factors associated with incorrect beliefs about the effectiveness of methods to treat AUD. METHODS: In this cross-sectional study, 19,526 undergraduate students from 27 German medical schools completed a survey addressing beliefs about the effectiveness of different methods of overcoming AUD. Beliefs about AUD treatment effectiveness were compared across the 5 years of undergraduate education and predictors identified by means of multiple linear regression. RESULTS: Even in the fifth year, 28.1% (95% CI: 26.5-29.7) of students believed that willpower alone was more effective for overcoming AUD than a comprehensive treatment program. The only significant predictor of this belief was a similar belief for stopping smoking. CONCLUSION: Our results indicate that a considerable proportion of German medical students overestimate the effectiveness of willpower to treat smoking and AUD. The addictive nature of these disorders needs to be stressed during undergraduate medical education to ensure that future physicians will be able and motivated to support patients in their quit attempts.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".