Impact of the removal of misleading terms on cigarette pack on smokers' beliefs about ‘light/mild’ cigarettes: cross‐country comparisons
Bibliographic record
Abstract
AIM: This paper examines how smokers' beliefs about 'light/mild' cigarettes in Australia, Canada and the United Kingdom were affected by the removal of misleading 'light/mild' terms from packs. DESIGN, SETTING AND PARTICIPANTS: The data come from the first seven waves (2002-09) of the International Tobacco Control Policy Evaluation (ITC) Four-Country Survey, an annual cohort telephone survey of adult smokers in Canada, the United States, the United Kingdom and Australia (21 613 individual cases). 'Light' and 'mild' descriptors were removed in 2003 in the United Kingdom, in 2006 in Australia and in 2007 in Canada. We compare beliefs about 'light' cigarettes both before and after the bans, with those of smokers in the United States serving as the control condition. MEASURES: Smokers' beliefs about 'light' cigarettes were assessed using a set of statements rated on a five-point 'agree'-'disagree' scale. FINDINGS: The proportions of respondents reporting misperceptions about light cigarettes declined between 2002 and 2009 in all four countries. There were marked temporary reductions in reported misperceptions in the United Kingdom and Australia, but not in Canada, following the removal of 'light/mild' descriptors. CONCLUSIONS: Removal of 'light/mild' descriptors and tar, nicotine and carbon monoxide yield information from cigarette packs is insufficient to effectively eliminate false beliefs. The combination of alternative descriptors and design features that produce differences in taste strength and harshness, independent of actual intakes, are sufficient to produce or sustain the same misbeliefs.
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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 | 0.005 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".