Differences in smokers’ awareness of the health risks of smoking before and after introducing pictorial tobacco health warnings: findings from the 2012–2017 international tobacco control (ITC) Netherlands surveys
Bibliographic record
Abstract
BACKGROUND: As of May 2016, pictorial health warnings (PHWs) showing the harms of smoking were implemented in the European Union. After one year they had to be fully implemented. We studied changes in awareness of the health risks of smoking after implementation of PHWs among smokers from the Netherlands, whether the trend before the implementation changed after the implementation, and whether there were differences between subgroups. METHODS: We used survey data from six yearly waves of the International Tobacco Control (ITC) Netherlands Survey from 2012 to 2017. The number of participating smokers ranged between 1236 and 1604 per wave. Data were analyzed using Generalized Estimating Equations (GEE) analyses. RESULTS: Indicators of awareness of the health risks of smoking that did not change between 2015 and 2017 were perceived susceptibility (β = 0.043, p = 0.059) and perceived severity (β = - 0.006, p = 0.679) regarding lung problems. Perceived susceptibility, however, was more pronounced between 2015 and 2017 than between 2012 and 2015(p value of interaction: p = 0.044). Noticing information about the dangers of smoking (β = 0.119, p < 0.001) and knowledge about the health risks of smoking (β = 0.184, p < 0.001) increased between 2015 and 2017. These increases were both more pronounced when compared to 2012-2015 (p values of interactions: p = 0.002 and p < 0.001 respectively). Compared to high educated smokers, low educated smokers (β = - 1.137, p < 0.001) and moderate educated smokers (β = - 0.894, p < 0.001) were less knowledgeable about the health risks of smoking in 2016 and 2017. CONCLUSIONS: Introducing PHWs coincided with an increase in smokers' knowledge about the health risks of smoking. Dutch tobacco control policy and campaigns should focus on improving Dutch smokers' awareness of the health risks of smoking even more, especially among low educated 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 | 0.003 | 0.010 |
| 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 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".