Prospective predictors of quitting behaviours among adult smokers in six cities in China: findings from the International Tobacco Control (ITC) China Survey
Bibliographic record
Abstract
AIMS: To examine predictors of quitting behaviours among adult smokers in China, in light of existing knowledge from previous research in four western countries and two southeast Asian countries. DESIGN: Face-to-face interviews were carried out with smokers in 2006 using the International Tobacco Control (ITC) China Survey, with follow-up about 16 months later. A stratified multi-stage cluster sampling design was employed. SETTING: Beijing and five other cities in China. PARTICIPANTS: A total of 4732 smokers were first surveyed in 2006. Of these, 3863 were re-contacted in 2007, with a retention rate of 81.6%. MEASUREMENTS: Baseline measures of socio-demographics, dependence and interest in quitting were used prospectively to predict both making quit attempts and staying quit among those who attempted. FINDINGS: Overall, 25.3% Chinese smokers reported having made at least one quit attempt between waves 1 and 2; of these, 21.7% were still stopped at wave 2. Independent predictors of making quit attempts included having higher quitting self-efficacy, previous quit attempts, more immediate intentions to quit, longer time to first cigarette upon waking, negative opinion of smoking and having smoking restrictions at home. Independent predictors of staying quit were being older, having longer previous abstinence from smoking and having more immediate quitting intentions. CONCLUSIONS: Predictors of Chinese smokers' quitting behaviours are somewhat different to those found in previous research from other countries. Nicotine dependence and self-efficacy seem to be more important for attempts than for staying quit in China, and quitting intentions are related to both attempts and staying quit.
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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".