Support for a point-of-sale cigarette display ban among smokers: findings from the international tobacco control (ITC) Netherlands survey
Bibliographic record
Abstract
BACKGROUND: Displaying tobacco products at point-of-sale (PoS) has become an important marketing strategy for the tobacco industry. This study was designed to (1) examine how support for a PoS cigarette display ban changed among Dutch smokers between 2010 and 2015 and (2) identify the variables that predict support among smokers for a PoS cigarette display ban. METHODS: Longitudinal data from six annual survey waves (2010-2015) from the International Tobacco Control (ITC) Netherlands Survey were analyzed. The sample consisted of between 1279 and 1800 smokers per year. Smokers were asked whether they supported a complete ban on displays of cigarettes inside shops and stores. RESULTS: Support for a PoS cigarette display ban increased from 28.9% in 2010 to 42.5% in 2015 (OR = 1.40, p < 0.001). A multiple logistic regression analysis revealed that support for a PoS display ban of cigarettes was more likely among smokers who had more knowledge about the health risks of smoking (OR = 3.97, p < 0.001), believed smoking-related health risks to be severe (OR = 1.39, p < 0.001), had a more positive attitude towards quitting smoking (OR = 1.44, p = 0.006), reported stronger social norms to quit smoking (OR = 1.29, p = 0.035), had a higher self-efficacy for quitting smoking (OR = 1.31, p = 0.001), and had stronger intentions to quit smoking (OR = 1.23, p = 0.006). CONCLUSIONS: This paper showed that support for a PoS display ban of cigarettes increased among smokers in the Netherlands over the years. To further increase support, educational campaigns about the dangers of smoking, and campaigns that encourage quitting may be needed.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".