Promoting cessation resources through cigarette package warning labels: a longitudinal survey with adult smokers in Canada, Australia and Mexico
Bibliographic record
Abstract
INTRODUCTION: Health warning labels (HWLs) on tobacco packaging can be used to provide smoking cessation information, but the impact of this information is not well understood. METHODS: Online consumer panels of adult smokers from Canada, Australia and Mexico were surveyed in September 2012, January 2013 and May 2013; replenishment was used to maintain sample sizes of 1000 participants in each country at each wave. Country-stratified logistic Generalised Estimating Equation (GEE) models were estimated to assess correlates of citing HWLs as a source of information on quitlines and cessation websites. GEE models also regressed having called the quitline, and having visited a cessation website, on awareness of these resources because of HWLs. RESULTS: At baseline, citing HWLs as a source of information about quitlines was highest in Canada, followed by Australia and Mexico (33%, 19% and 16%, respectively). Significant increases over time were only evident in Australia and Mexico. In all countries, citing HWLs as a source of quitline information was significantly associated with self-report of having called a quitline. At baseline, citing HWLs as a source of information about cessation websites was higher in Canada than in Australia (14% and 6%, respectively; Mexico was excluded because HWLs do not include website information), but no significant changes over time were found for either country. Citing HWLs as a source of information about cessation websites was significantly associated with having visited a website in both Canada and Australia. CONCLUSIONS: HWLs are an important source of cessation information.
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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".