Adolescents' response to text-only tobacco health warnings: results from the 2008 UK Youth Tobacco Policy Survey
Bibliographic record
Abstract
BACKGROUND: As of June 2009 most (89%) European Union member states continue to use mandated text-only health warnings on tobacco products. This study assessed adolescent (aged 11-16 years) perceptions of and reactions to these text warnings on cigarette packs in the UK. METHODS: Data comes from wave five of the cross-sectional Youth Tobacco Policy Survey in 2008. A total of 1401 adolescents were recruited and health warnings were assessed in terms of salience (noticing, reading), comprehension and credibility, memorability (recall), depth of processing (contemplating, discussing) and persuasiveness (put off smoking, make more likely to stop). Smokers were also asked about behavioural compliance (foregoing cigarettes due to warnings, avoidance of warnings) and perceptions of harm from their smoking (to indirectly assess possible knowledge gained from warnings). RESULTS: Despite moderately high salience of warnings, memorability and, in particular, depth of processing was quite low, with warnings only sometimes thought about and very rarely discussed. Warnings were however considered comprehensible, credible and a reasonable deterrent for occasional and never smokers. Additionally, a third of regular smokers indicated that, in the last month, warnings had stopped them from having a cigarette. However, only 6% of smokers indicated that warnings made them forego cigarettes frequently. CONCLUSION: Text warnings help to communicate the dangers associated with smoking and, resultantly, prompt a small number of smokers to forgo cigarettes and take action to avoid warnings, but depth of processing is low and warnings do not appear to be achieving their full potential among smokers.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".