People who smoke and formerly smoked do support a smoking ban in open spaces during and after the COVID-19 pandemic in Spain
Bibliographic record
Abstract
BACKGROUND: Spain implemented an extensive outdoor smoking ban during the COVID-19 pandemic in 2020. We examined support for this restriction during and beyond the pandemic among people who currently and formerly smoked. METHODS: Cross-sectional study. The 2021 ITC EUREST-PLUS Spain Survey used a multistage sampling to obtain a representative sample of people who currently or formerly smoked (n=1006). We estimated prevalence ratios (PRs) to examine associations with ban support during and after the pandemic. Analyses accounted for the complex sampling design and were weighted to ensure representativeness. RESULTS: Most people who currently (79.2%) and formerly smoked (94.6%) supported the outdoor smoking ban when a safe interpersonal distance could not be maintained during the pandemic. Support for a permanent ban remained substantial (61.4% and 87.2%, respectively). Those who currently smoke were more likely to support bans during and after the pandemic if they had smoke-free homes (PR=1.11; PR=1.29, respectively), understood secondhand smoke harms to health (PR=1.40; PR=1.65), had tried to quit (PR=1.14; PR=1.30) and self-reported as healthy (PR=1.40; PR=1.47). Those who formerly smoked were more likely to support bans during the pandemic if they had smoke-free homes (PR=1.08) and did not self-report as healthy (PR=0.95); and after the pandemic if they had quit smoking for ≥6 months (PR=1.23) and used alternative tobacco products (PR=1.17). CONCLUSIONS: Most people who currently or formerly smoked in Spain supported the outdoor smoking ban during and after the COVID-19 pandemic. This high acceptance suggests that the pandemic may have created an opportunity to strengthen tobacco control.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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".