The impact of smokefree legislation in Scotland: results from the Scottish ITC Scotland/UK longitudinal surveys
Bibliographic record
Abstract
BACKGROUND: To evaluate how Scotland's smokefree law impacted self-reported secondhand smoke (SHS) exposure in hospitality venues, workplaces and in people's homes. In addition, we examine changes in support for the law, pub and restaurant patronage, smoking cessation indicators and whether any observed changes varied by socioeconomic status. METHODS: A quasi-experimental longitudinal telephone survey of nationally representative samples of smokers and non-smokers interviewed before the Scottish law (February to March 2006) and 1 year later after the law (March 2007) in Scotland (n = 705 smokers and n = 417 non-smokers) and the rest of the UK (n = 1027 smokers and n = 447 non-smokers) where smoking in public places was not regulated at the time. RESULTS: Dramatic declines in the observance of smoking in pubs, restaurants and workplaces were found in Scotland relative to the rest of the UK. The change in the percent of smokers reporting a smokefree home and number of cigarettes smoked inside the home in the evening was comparable in Scotland and the rest of the UK. Support for smokefree policies increased to a greater extent in Scotland than in the rest of the UK. Self-reported frequency of going to pubs and restaurants was generally comparable between Scotland and the rest of the UK; however, non-smokers in Scotland were more likely to frequent pubs more often. No differences in smoking cessation indicators were observed between countries. CONCLUSION: The Scottish smokefree law has been successful in decreasing secondhand smoke exposure while causing none of the hypothesized negative outcomes.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".