Awareness of Marketing of Heated Tobacco Products and Cigarettes and Support for Tobacco Marketing Restrictions in Japan: Findings from the 2018 International Tobacco Control (ITC) Japan Survey
Bibliographic record
Abstract
Japan is one of the world’s largest cigarette markets and the top heated tobacco product (HTP) market. No forms of tobacco advertising, promotion, and sponsorship (TAPS) are banned under national law, although the industry has some voluntary TAPS restrictions. This study examines Japanese tobacco users’ self-reported exposure to cigarette and HTP marketing through eight channels, as well as their support for TAPS bans. Data are from the 2018 ITC Japan Survey, a cohort survey of adult exclusive cigarette smokers (n = 3288), exclusive HTP users (n = 164), HTP-cigarette dual users (n = 549), and non-users (n = 614). Measures of overall average exposure to the eight channels of cigarette and HTP advertising were constructed to examine differences in exposure across user groups and products. Dual users reported the highest exposure to cigarette and HTP advertising. Tobacco users (those who used cigarettes, HTPs, or both) reported higher average exposure to HTP compared to cigarette advertising, however non-users reported higher average exposure to cigarette compared to HTP advertising. Retail stores where tobacco or HTPs are sold were the most prevalent channel for HTP and cigarette advertising, reported by 30–43% of non-users to 66–71% of dual users. Non-users reported similar exposure to cigarette advertising via television and newspapers/magazines as cigarette smokers and dual users; however, advertising via websites/social media was lower among non-users and HTP users than among cigarette smokers and dual users (p < 0.05). Most respondents supported a ban on cigarette (54%) and HTP (60%) product displays in stores, and cigarette advertising in stores (58%).
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".