Risk factors associated with smoking behaviour in recreational venues: findings from the International Tobacco Control (ITC) China Survey
Bibliographic record
Abstract
OBJECTIVE: To explore the determinants of smoking behaviour in recreational venues and to provide scientific bases for establishing smoke-free measures applying to these locations. METHODS: The International Tobacco Control (ITC) China Survey--a face-to-face cross-sectional survey of representative adult smokers from six cities (Shenyang, Beijing, Shanghai, Guangzhou, Changsha and Yinchuan)--was conducted between April and August 2006. A total of 4815 smokers were selected using multistage sampling methods, and final analyses were conducted on 2875 smokers who reported patronising recreational venues at least once in the last six months. Multivariate logistic regression models were used to identify factors influencing the smoking behaviour within recreational settings. Outcome measure Whether a smoker reported smoking in recreational venues during the last 6 months. RESULTS: 84% subjects reported smoking in recreational venues. Analyses showed that smoke-free laws had been exempted, 32.0% of the patrons reporting bans on smoking in these locations. The following factors were significant predictors of smoking in recreational venues: absence of bans on smoking, support for non-bans, being aged 18-24 years, positive smoking-related attitudes, low number of health effects reported and not living in Beijing. CONCLUSIONS: The findings point to the importance of informing Chinese smokers about the active smoking and passive smoking harmfulness in both building support for smoke-free laws and in reducing smokers' desire to smoke within recreational venues. They also point to the importance of good enforcement of smoke-free laws when implemented. Such strategies could also serve to de-normalise smoking in China, a key strategy for reducing smoking in general.
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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 | 0.001 |
| 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 | 0.001 |
| 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".