Levels and correlates of awareness of tobacco promotional activities among adult smokers in Malaysia and Thailand: findings from the International Tobacco Control Southeast Asia (ITC-SEA) Survey
Bibliographic record
Abstract
AIM: To examine the impact of tobacco advertising policy on adult smokers' awareness of tobacco promotion in two developing countries--Malaysia and Thailand. METHODS: Data from 2004 Malaysian and 2000 Thai adult smokers who participated in the baseline wave of the International Tobacco Control Southeast Asia survey (ITC-SEA). Respondents were asked in a face-to-face interview conducted between January and March 2005 to indicate their levels of awareness of tobacco advertising and promotional activities in the last six months. RESULTS: Unprompted awareness of any tobacco marketing activities was very low in Thailand (20%) but significantly higher in Malaysia (53%; OR = 5.6, 95% CI: 3.5 to 8.9, p<0.001). When prompted about specific locations, Thai adult smokers reported very low recall of tobacco advertising where it was banned, being highest around point of sale, particularly street vendors (7.5%). In contrast, Malaysian adult smokers reported significantly higher levels of awareness of tobacco advertising in all locations (range = 17.7% noticing in disco lounges to 59.3% on posters) including where they are notionally banned (for example, billboards). CONCLUSIONS: These findings demonstrate that comprehensive tobacco advertising legislation when well implemented can lead to dramatic decline in awareness of tobacco promotion, thus supporting strong implementation of Article 13 of the Framework Convention on Tobacco Control.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".