Tobacco-related medical education and physician interventions with parents who smoke: Survey of Canadian family physicians and pediatricians.
Bibliographic record
Abstract
OBJECTIVE: To examine the relationship between physicians' tobacco-related medical training and physicians' confidence in their tobacco-related skills and smoking-related interventions with parents of child patients. DESIGN: Mailed survey. SETTING: Canada. PARTICIPANTS: The survey was mailed to 800 family physicians and 800 pediatricians across Canada, with a corrected response rate of 65% (N = 900). MAIN OUTCOME MEASURES: Physicians' self-reported tobacco-related education, knowledge, and skills, as well as smoking-related interventions with parents of child patients. Cochran-Mantel-Haenszel chi(2) tests were used to examine relationships between variables, controlling for tobacco-control involvement and physician specialty. Data analysis was conducted in 2008. RESULTS: Physicians reporting tobacco-related medical education were more likely to report being "very confident" in advising parents about the effects of smoking and the use of a variety of cessation strategies (P < .05). Furthermore, physicians with tobacco-related training were more likely to help parents of child patients quit smoking whether or not the children had respiratory problems (P < .05). Physicians with continuing medical education in this area were more likely to report confidence in their tobacco-related skills and to practise more smoking-related interventions than physicians with other forms of training. CONCLUSION: There is a strong relationship between medical education and physicians' confidence and practices in protecting children from secondhand smoke. Physicians with continuing medical education training are more confident in their tobacco-related skills and are more likely to practise smoking-related interventions than physicians with other tobacco-related training.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".