Investigating the Effectiveness of Pictorial Health Warnings in Mauritius: Findings From the ITC Mauritius Survey
Bibliographic record
Abstract
INTRODUCTION: Health warnings on tobacco packages are an effective strategy for informing the public about the harms associated with tobacco use. Most studies investigating the effectiveness of pictorial health warnings (PHWs) on cigarette packages are from high-income countries. This study evaluated the impact of PHWs on smokers' perceptions and behavior in Mauritius, the first country in the World Health Organization African region to implement PHWs. METHODS: Data were drawn from 3 waves of a nationally representative cohort of adult smokers from the International Tobacco Control (ITC) Mauritius Survey (n = 668). Wave 1 was conducted in 2009, 6 months prior to the implementation of PHWs. Waves 2 and 3 were conducted 10-12 months and 20-21 months, respectively, postimplementation. Six established indicators of warning effectiveness were used to evaluate the effect of PHWs on smokers' perceptions and behavior. RESULTS: All indicators of warning effectiveness (salience, cognitive, and behavioral reactions) and the Label Impact Index, a weighted combination of 4 indicators, increased significantly between Waves 1 and 2. However, between Waves 2 and 3, there was a significant decline in the proportion of smokers who reported "avoiding looking" at labels. CONCLUSIONS: This study found that implementation of PHWs in Mauritius significantly enhanced the effectiveness of warnings, illustrating their value for other countries, particularly in Africa, at an early stage in tobacco control. The study also demonstrates the importance of revising PHWs to counteract wearout. The introduction of PHWs in Mauritius clearly demonstrates the benefits of employing an evidence-based approach to strengthen tobacco control policies.
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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 | 0.025 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".