Smoking Prevention Counseling Practices of Montreal General Practitioners
Bibliographic record
Abstract
BACKGROUND: Primary care physicians are potentially important sources of interventions aimed at preventing youth smoking. Yet recent surveys suggest that physician smoking prevention practices are less than optimal. OBJECTIVES: To document prevention counseling practices and to identify correlates of these activities in a random sample of general practitioners in Montreal, Quebec. METHODS: A cross-sectional mail survey. RESULTS: Of 440 eligible general practitioners (GPs), 337 (77%) completed the questionnaire. General practitioners were more likely to ascertain the smoking status of adolescents (70.9%) than preadolescents (35.7%). Although about half of the GPs offered advice to prevent smoking onset in young adults (48.6%) and adolescents (48.3%), fewer did so for preadolescents (34.4%); only 12.1% advised parents to discuss smoking onset with their children. Correlates of ascertaining smoking status included female sex (odds ratio [OR], 1.90; 95% confidence interval [CI], 1.07-3.41), lower proportion of walk-in patients (OR, 2.73; 95% CI, 1.31-5.80), awareness of the "stage of behavior change" model (OR, 2.17; 95% CI, 1.18-4.04), and higher self-efficacy (OR, 4.12, 95% CI, 2.00-8.69). Correlates of provision of prevention advice included more hours spent in direct patient care (OR, 1.93; 95% CI, 1.13-3.34), favorable beliefs and attitudes (OR, 1.73; 95% CI, 1.06-2.83), and higher self-efficacy (OR, 4.32; 95% CI, 2.25-8.44). CONCLUSIONS: Our results point to the need for renewed efforts to enhance preventive efforts in primary care settings. Intervention programs for GPs should emphasize overcoming unfavorable beliefs and attitudes and low self-efficacy. Future research should evaluate the effect of brief prevention counseling adapted to increasingly busy practices.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".