Educational differences in the impact of pictorial cigarette warning labels on smokers: findings from the International Tobacco Control (ITC) Europe surveys
Bibliographic record
Abstract
OBJECTIVE: To examine (1) the impact of pictorial cigarette warning labels on changes in self-reported warning label responses: warning salience, cognitive responses, forgoing cigarettes and avoiding warnings, and (2) whether these changes differed by smokers' educational level. METHODS: Longitudinal data of smokers from two survey waves of the International Tobacco Control (ITC) Europe Surveys were used. In France and the UK, pictorial warning labels were implemented on the back of cigarette packages between the two survey waves. In Germany and the Netherlands, the text warning labels did not change. FINDINGS: Warning salience decreased between the surveys in France (OR=0.81, p=0.046) and showed a non-significant increase in the UK (OR=1.30, p=0.058), cognitive responses increased in the UK (OR=1.34, p<0.001) and decreased in France (OR=0.70, p=0.002), forgoing cigarettes increased in the UK (OR=1.65, p<0.001) and decreased in France (OR=0.83, p=0.047), and avoiding warnings increased in France (OR=2.93, p<0.001) and the UK (OR=2.19, p<0.001). Warning salience and cognitive responses decreased in Germany and the Netherlands, forgoing did not change in these countries and avoidance increased in Germany. In general, these changes in warning label responses did not differ by education. However, in the UK, avoidance increased especially among low (OR=2.25, p=0.001) and moderate educated smokers (OR=3.21, p<0.001). CONCLUSIONS: The warning labels implemented in France in 2010 and in the UK in 2008 with pictures on one side of the cigarette package did not succeed in increasing warning salience, but did increase avoidance. The labels did not increase educational inequalities among continuing smokers.
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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 | 0.002 | 0.002 |
| 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".