The effect of MPOWER on smoking prevalence
Bibliographic record
Abstract
OBJECTIVE: To examine the effect of varying levels of comprehensive tobacco control on smoking in a global context. METHODS: Using data from WHO's Reports on the Global Tobacco Epidemic, scatter plots were produced to visualise the relationship between comprehensive tobacco control policy (2008 MPOWER composite score) and change in current tobacco smoking between 2006 and 2009. Fixed-effect regression models assessed the effect of changes in each MPOWER measure on changes in current tobacco smoking between 2006 and 2009. All analyses were stratified by sex. RESULTS: Overall, countries with higher MPOWER composite scores experienced greater decreases in current tobacco smoking between the years 2006 and 2009. Regression analyses revealed that the M and R measures showed a negative association with current tobacco smoking over time. Current tobacco smoking decreased (1.07 percentage points for males, 1.04 percentage points for females) with each increase in score value for monitoring tobacco use (M). Also, current tobacco smoking decreased (0.95 percentage points for males, 0.41 percentage points for females) with each increase in score value for raising taxes on tobacco (R). The effect of the MPOWER measures on current tobacco smoking varied by country income status (P measure in the female analysis; p<0.05) and/or by WHO region (M, P and O measures in the male analysis; p<0.05). CONCLUSIONS: Higher levels of MPOWER combined, as well as continued and frequent monitoring of tobacco use (M) and increasing taxation (R), were associated with a decrease in current tobacco smoking over time.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".