Changes in the smoking status of primary care professionals and their association with rates of tobacco treatment delivery: the TiTAN Greece & Cyprus tobacco dependence treatment training programme
Bibliographic record
Abstract
Abstract Aim: This study examines the impact of a continuing medical education (CME) intervention on smoking cessation among primary-care professionals (PCPs) and explores the relationship between PCP smoking status and patient tobacco-treatment delivery. Background: High rates of tobacco use among PCPs have been reported in several European countries. PCPs who smoke are less motivated to provide cessation support to their patients. Methods: A before-after study was conducted with 228 PCPs from Greece and Cyprus. The intervention included a one-day CME training, a 2.5-hour seminar three months later, and practice tools. Expert faculty provided informal support to smoking PCPs. Changes in PCP smoking status and 5As (ask, advise, assess, assist, and arrange) tobacco treatment delivery were assessed before and six months after training. Analysis of variance (ANOVA) and analysis of covariance (ANCOVA) were used to evaluate the association between the training and PCP smoking status and 5As delivery. Findings: At baseline, 18% ( n = 47) of PCPs were current smokers, and 39% ( n = 66) were ex-smokers. At follow-up, 31.9% of current smokers reported quitting ( n = 15/47; p < 0.001). Smoking cessation was higher among female PCPs ( p = 0.02) and those in Cyprus and Thessaloniki ( p < 0.01). PCPs reported increased 5As delivery at follow-up, with the highest rates among ex-smokers (>6 months) and never smokers. PCPs reported significant quitting rates following a comprehensive evidence-based training intervention. The findings suggest that addressing PCPs’ smoking status can improve both health-care provider and patient smoking outcomes.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".