Evaluation of the Behaviors of Physicians Working in Primary Healthcare Institutions About Secondhand Smoke
Bibliographic record
Abstract
The aim of this study was to evaluate the behaviors of physicians working in primary healthcare institutions in Elazığ province about secondhand smoke. This cross-sectional study was conducted on 250 physicians working in primary healthcare institutions in Elazığ. For data collection, a questionnaire was used. Obtained data were evaluated with frequency, percentage, mean ± standard deviation, chi-square, Mann– Whitney U-test, and binary logistic regression analysis. The mean age of the physicians was 40.86 ± 10.58 years and 68.0% of them were male. Of the physicians, 12% received training on secondhand smoke, 13.2% asked patients about secondhand smoke exposure, and 34.8% advised that patients be protected from secondhand smoke exposure. Male physicians (odds ratio: 3.00, 95% Confidence Interval: 1.10–8.18) and physicians trained in secondhand smoke (odds ratio: 3.55, 95% Confidence Interval: 1.44–8.78) stated that they asked patients more frequently about their exposure to secondhand smoke. As a result, very few of the primary care physicians ask about the exposure of their patients to secondhand smoke and very few of them have received training on secondhand smoke. The number of trained physicians should be increased in order for physicians to ask patients about secondhand smoke exposure and to provide counseling on this issue.
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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 | 0.000 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".