Changes in Attitudes toward Tobacco Smoking and Factors Associated with Quitting in 9-Year Observation of PURE Poland Cohort Study
Bibliographic record
Abstract
(1) Background: This study aims to examine changes in tobacco smoking prevalence in the PURE Poland cohort study over the 9-year follow-up period. Moreover, it attempts to identify socio-demographic factors that affect changes in attitudes towards tobacco smoking. (2) Methods: The PURE Poland cohort study-baseline was performed in 2007-2010 and covered 2036 participants, including urban (59.4%) and rural (40.6%) residents of Lower Silesia, Poland. The following study reports the results of 1690 participants who took part in both the baseline (2007-2010) study and 9-year follow-up (2016-2019). (3) Results: There was a 3.5% decrease in current smokers during the analyzed period (from 20.2% at the baseline study to 16.7% in the 9-year follow-up). Living in rural area increased the likelihood of being a current smoker by more than 1.5-fold (OR = 1.65 CI = 1.26-2.14) and decreased the likelihood of being a former smoker (OR = 0.70 CI = 0.57-0.86). In the 9-year follow-up period, more women were current smokers than men (17.2% vs. 16.0%) and women had lower chances of being former smokers than men (OR = 0.77 CI = 0.62-0.95). People with a primary education had 1.5-fold higher likelihood of being a current smoker (OR = 1.45 CI = 1.03-2.05). Nearly 11% significant increase in the percentage of current smokers was observed in the oldest age group (1.9% in the baseline study vs. 12.6% in the follow-up period). (4) Conclusions: The results obtained during 9 years of observation indicate the necessity of intensifying anti-tobacco programs especially targeting women, elderly population, people with lower level of education, rural residents, and the unemployed.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".