Public support for tobacco endgame policies in South Korea: Findings from the 2020 International Tobacco Control Korea Survey
Bibliographic record
Abstract
BACKGROUND: Strong public support can increase the likelihood of adopting tobacco control policies. We assessed support for six commercial tobacco endgame policies in South Korea: limiting the nicotine in cigarettes, banning all additives in cigarettes, restricting the number of places where cigarettes are sold, and banning the manufacture and sales of cigarettes (unconditionally, with the provision of cessation support and with alternative tobacco products available). METHODS: Data were obtained from 4740 adults who completed the 2020 International Tobacco Control Korea Survey. Participants were categorised based on their nicotine use: (1) did not use any products, (2) vaped and/or used heated tobacco products (HTPs) but did not smoke cigarettes, (3) smoked cigarettes only and (4) smoked cigarettes and vaped and/or used HTPs. Attitudes towards the policies were classified as supportive, undecided or opposed. Weighted multinomial logistic regression models assessed support levels according to nicotine use. RESULTS: Support was highest for limiting the nicotine content in cigarettes (68.4%; 95% CI 64.6% to 72.3%) and restricting the number of retailers (68.1%; 95% CI 64.5% to 71.7%), and lowest for banning cigarette sales if alternative products are made available (45.0%; 95% CI 40.9% to 49.1%). People who did not use any products were most likely to support endgame policies, except for banning cigarette sales with alternatives available. The proportion of undecided participants exceeded 10% (range 13%-25%) for all policies. CONCLUSION: There is a strong public support for tobacco endgame policies in South Korea. Further research should prioritise the development of strategies to ensure the effective implementation of highly supported policies.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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 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".