Smoking habits among healthcare professionals in family medicine in Republic of Srpska
Bibliographic record
Abstract
Introduction. Smoking prevalence among healthcare professionals is high in European countries and the surveys conducted in the past decade have confirmed the existence of this public health problem in the Republic of Srpska (RS) as well. The aim of this study is to investigate smoking habits, as well as the readiness for smoking cessation in family medicine services in RS. Methods. The study was conducted on randomly selected two-stage stratified sample in seven health centers in RS. Results. In family medicine services belonging to seven healthcare centers of RS, there were 22.7% of daily and 8% of occasional smokers. There were significantly higher percentage of smokers among nurses, compared to medical doctors. There were 10.5% of former smokers, mostly found among medical doctors. Approximately a quarter of smokers (25.3%) lit their first cigarette half an hour after waking up. The highest percent of health professionals (61.5%) intended to quit smoking, while more than a quarter (27.1%) were ready to quit smoking in the following 30 days, without any significant difference according to the healthcare professional profile. A small percentage of respondents used professional assistance (3.11%), as well as pharmacotherapeutic approach to the smoking cessation process (3.9%). Approximately one quarter of healthcare professionals (24.6%) were willing to participate in smoking cessation programs, but more than two-thirds of respondents needed additional motivation for it. Conclusion. This study has shown that more than a fifth of healthcare professionals in family medicine are daily smokers, and every one in ten individuals is a former smoker. Although half of healthcare professionals intend to quit smoking, it is a source of concern that the majority of respondents are reluctant to start the process of smoking cessation.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.003 | 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".