Regret and rationalization among smokers in Thailand and Malaysia: Findings from the International Tobacco Control Southeast Asia Survey.
Bibliographic record
Abstract
OBJECTIVE: To test whether differences of history and strength in tobacco control policies will influence social norms, which, in turn, will influence quit intentions, by influencing smokers' regret and rationalization. DESIGN: The data were from the International Tobacco Control (ITC) Policy Evaluation Southeast Asia Survey, a cohort survey of representative samples of adult smokers in Thailand (N = 2,000) and Malaysia (N = 2,006). The survey used a stratified multistage sampling design. MAIN OUTCOME MEASURES: Measures included regret, rationalization, social norms, and quit intention. RESULTS: Thai smokers were more likely to have quit intentions than Malaysian smokers. This difference in quit intentions was, in part, explained by the country differences in social norms, regret, and rationalization. Reflecting Thailand's history of stronger tobacco control policies, Thai smokers, compared with Malaysian smokers, perceived more negative social norms toward smoking, were more likely to regret, and less likely to rationalize smoking. Mediational analyses revealed that these differences in social norms, accounted, in part, for the country-quit intention relation and that regret and rationalization accounted, in part, for the social norm-quit intention relation. CONCLUSION: The results suggest that social norms toward smoking, which are shaped by tobacco control policies, and smokers' regret and rationalization influence quit intentions.
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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".