The impact of the 2009/2010 enhancement of cigarette health warning labels in Uruguay: longitudinal findings from the International Tobacco Control (ITC) Uruguay Survey
Bibliographic record
Abstract
BACKGROUND: Framework Convention on Tobacco Control (FCTC) Article 11 Guidelines recommend that health warning labels (HWLs) should occupy at least 50% of the package, but the tobacco industry claims that increasing the size would not lead to further benefits. This article reports the first population study to examine the impact of increasing HWL size above 50%. We tested the hypothesis that the 2009/2010 enhancement of the HWLs in Uruguay would be associated with higher levels of effectiveness. METHODS: Data were drawn from a cohort of adult smokers (≥18 years) participating in the International Tobacco Control (ITC) Uruguay Survey. The probability sample cohort was representative of adult smokers in five cities. The surveys included key indicators of HWL effectiveness. Data were collected in 2008/09 (prepolicy: wave 2) and 2010/11 (postpolicy: wave 3). RESULTS: Overall, 1746 smokers participated in the study at wave 2 (n=1379) and wave 3 (n=1411). Following the 2009/2010 HWL changes in Uruguay (from 50% to 80% in size), all indicators of HWL effectiveness increased significantly (noticing HWLs: OR=1.44, p=0.015; reading HWLs: OR=1.42, p=0.002; impact of HWLs on thinking about risks of smoking: OR=1.66, p<0.001; HWLs increasing thinking about quitting: OR=1.76, p<0.001; avoiding looking at the HWLs: OR=2.35, p<0.001; and reports that HWLs stopped smokers from having a cigarette 'many times': OR=3.42, p<0.001). CONCLUSIONS: The 2009/2010 changes to HWLs in Uruguay, including a substantial increment in size, led to increases of key HWL indicators, thus supporting the conclusion that enhancing HWLs beyond minimum guideline recommendations can lead to even higher levels of effectiveness.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".