The effect of pack warning labels on quitting and related thoughts and behaviors in a national cohort of Aboriginal and Torres Strait Islander smokers
Bibliographic record
Abstract
Introduction: The high prevalence of smoking among Aboriginal and Torres Strait Islander people in Australia (39%) contributes substantially to health inequalities. This study assesses the impact of warning labels on quitting and related thoughts and behaviors for Aboriginal and Torres Strait Islander smokers. Methods: Participants were recruited from communities served by 34 Aboriginal Community Controlled Health Services and communities in the Torres Strait, Australia, using quota sampling. A cohort of 642 daily/weekly smokers completed relevant questions at baseline (April 2012–October 2013) and follow-up (August 2013–August 2014). Results: We considered three baseline predictor variables: noticing warning labels, forgoing cigarettes due to warning labels (“forgoing”) and perceiving labels to be effective. Forgoing increased significantly between surveys only for those first surveyed prior to the introduction of plain packs (19% vs. 34%); however, there were no significant interactions between forgoing cigarettes and the introduction of new and enlarged graphic warning labels on plain packaging in any model. Forgoing cigarettes predicted attempting to quit (adjusted odds ratio [AOR]: 1.45, 95% confidence interval [CI]: 1.02–2.06) and, among those who did not want to quit at baseline, wanting to quit at follow-up (AOR: 3.19, 95% CI: 1.06–9.63). Among those less worried about future health effects, all three variables predicted being very worried at follow-up. Often noticing warning labels predicted correct responses to questions about health effects that had featured on warning labels (AOR: 1.84, 95% CI: 1.20–2.82) but not for those not featured. Conclusions: Graphic warning labels appear to have a positive impact on the understanding, concerns and motivations of Aboriginal and Torres Strait Islander smokers and, through these, their quit attempts. Implications: Graphic warning labels are likely to be effective for Aboriginal and Torres Strait Islander smokers as they are for the broader Australian population.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".