Future physicians and tobacco: an online survey of the habits, beliefs and knowledge base of medical students at a Canadian University
Bibliographic record
Abstract
BACKGROUND: Little is known about the knowledge and attitudes towards tobacco use among medical students in Canada. Our objectives were to estimate the prevalence of tobacco use among medical students, assess their perceived level of education about tobacco addiction management and their preparedness to address tobacco use with their future patients. METHODS: A cross-sectional online survey was administered to University of Alberta undergraduate medical school trainees. The 32-question survey addressed student demographics, tobacco use, knowledge and attitudes around tobacco and waterpipe smoking, tobacco education received in medical school, as well as knowledge and competency regarding tobacco cessation interventions. RESULTS: Of 681 polled students, 301 completed the survey. Current (defined as "use within the last 30 days") cigarette, cigar/cigarillo and waterpipe smoking prevalence was 3.3%, 6% and 6%, respectively. One third of the respondents had ever smoked a cigarette, but 41% had tried cigars/cigarillos and 40% had smoked a waterpipe at some time in the past. Students reported moderate levels of education on a variety of tobacco-related subjects but were well-informed on the role of tobacco in disease causation. The majority of students in their final two years of training felt competent to provide tobacco cessation interventions, but only 10% definitively agreed that they had received enough training in this area. CONCLUSIONS: Waterpipe exposure/current use was surprisingly high among this sample of medical students, a population well educated about the role of tobacco in disease causation. The majority of respondents appeared to be adequately prepared to manage tobacco addiction but education could be improved, particularly training in behavioral modification techniques used in tobacco use cessation.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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".