Pathways of Change Explaining the Effect of Smoke-Free Legislation on Smoking Cessation in the Netherlands. An Application of the International Tobacco Control Conceptual Model
Bibliographic record
Abstract
INTRODUCTION: This study aims to test the pathways of change from individual exposure to smoke-free legislation on smoking cessation, as hypothesized in the International Tobacco Control (ITC) Conceptual Model. METHODS: A nationally representative sample of Dutch smokers aged 15 years and older was surveyed during 4 consecutive annual surveys. Of the 1,820 baseline smokers, 1,012 participated in the fourth survey. Structural Equation Modeling was employed to test a model of the effects of individual exposure to smoke-free legislation through policy-specific variables (support for smoke-free legislation and awareness of the harm of [secondhand] smoking) and psychosocial mediators (attitudes, subjective norm, self-efficacy, and intention to quit) on quit attempts and quit success. RESULTS: The effect of individual exposure to smoke-free legislation on smoking cessation was mediated by 1 pathway via support for smoke-free legislation, attitudes about quitting, and intention to quit smoking. Exposure to smoke-free legislation also influenced awareness of the harm of (secondhand) smoking, which in turn influenced the subjective norm about quitting. However, only attitudes about quitting were significantly associated with intention to quit smoking, whereas subjective norm and self-efficacy for quitting were not. Intention to quit predicted quit attempts and quit success, and self-efficacy for quitting predicted quit success. CONCLUSIONS: Our findings support the ITC Conceptual Model, which hypothesized that policies influence smoking cessation through policy-specific variables and psychosocial mediators. Smoke-free legislation may increase smoking cessation, provided that it succeeds in influencing support for the legislation.
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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 | 0.006 | 0.001 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".