The association between MPOWER tobacco control policies and adolescent smoking across 36 countries: An ecological study over time (2006–2014)
Bibliographic record
Abstract
OBJECTIVE: To examine associations over time between national tobacco control policies and adolescent smoking prevalence in Europe and Canada. DESIGN: In this ecological study, national tobacco control policies (MPOWER measures, as derived from WHO data) in 36 countries and their changes over time were related to national-level adolescent smoking rates (as derived from the Health Behaviour in School-aged Children study, 2006-2014). MPOWER measures included were: Protecting people from tobacco smoke (P), offering help to quit tobacco use (O), warning about the dangers of tobacco (W), enforcing bans on advertising, promotion and sponsorship (E) and raising taxes on tobacco (R). RESULTS: Across countries, adolescent weekly smoking decreased from 17.7% in 2006 to 11.6% in 2014. It decreased most strongly between 2010 and 2014. Although baseline MPOWER policies were not directly associated with differences in average rates of adolescent smoking between countries, countries with higher baseline smoke-free policies (P) showed faster rates of change in smoking over the time period. Moreover, countries that adopted increasingly strict policies regarding warning labels (W) over time, faced stronger declines over time in adolescent weekly smoking. CONCLUSION: A decade after the introduction of the WHO MPOWER package, we observed that, in our sample of European countries and Canada, measures targeting social norms around smoking (i.e., smoke-free policies in public places and policies related to warning people about the dangers of tobacco) are most strongly related to declines in adolescent smoking.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".