Correlates of the support for smoke-free policies amongsmokers: A cross-sectional study in six European countriesof the EUREST-PLUS ITC EUROPE SURVEYS
Bibliographic record
Abstract
INTRODUCTION: This report describes the support for smoke-free policies in different settings among smokers in six European countries and the relationship between their opinions about the places where smoking should be banned and their beliefs about the harms of secondhand smoke to non-smokers. METHODS: A cross-sectional survey (the ITC 6 European Country Survey, part of the EUREST-PLUS Project) was conducted using nationally representative samples of adult smokers in Germany, Greece, Hungary, Poland, Romania and Spain (n=6011). We describe the prevalence of agreement and support for smoke-free policies in different settings according to sociodemographics, smoking characteristics and beliefs about the danger of secondhand smoke to non-smokers. RESULTS: There was high agreement with smoking regulations in cars with preschool children and in schoolyards of primary/secondary schools (>90% overall) and low agreement with banning smoking in outdoor terraces of bars/pubs (8.6%; 95%CI: 7.5%-9.8%) and restaurants (10.1%; 95%CI: 8.9%-11.4%). The highest support for complete smoking bans inside public places came from smokers in Poland, among women, people aged ≥25 years, who had low nicotine dependence, and who tried to quit smoking in the last 12 months. About 78% of participants agreed that tobacco smoke is dangerous to non-smokers, ranging from 63.1% in Hungary to 88.3% in Romania; the highest agreement was noted among women, the 25-54 age groups, those with higher education, low cigarette dependence, and those who tried to quit in the last 12 months. The support for complete smoking bans in public places was consistently higher among smokers who agreed that secondhand smoke is dangerous to non-smokers. CONCLUSIONS: Smokers in six European countries declared strong support for smoke-free policies in indoor settings and in settings with minors but low support in outdoor settings, particularly leisure facilities. More education is needed to increase the awareness about the potential exposure to secondhand smoke in specific outdoor areas.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".