Reasons for Regularly Using Heated Tobacco Products among Adult Current and Former Smokers in Japan: Finding from 2018 ITC Japan Survey
Bibliographic record
Abstract
The market growth of heated tobacco products (HTPs), such as IQOS, Ploom TECH, and glo, has increased dramatically in Japan since 2016. Little is known about the reasons why current and former smokers are using HTPs. The data for this cross-sectional study were from the 2018 (Wave 1) International Tobacco Control (ITC) Japan Survey, a national web-based survey of 4500 people, including 658 current HTP users, of whom 549 were concurrently smoking cigarettes and 109 were former smokers. The most common reasons for regularly using HTPs were: beliefs that HTP are less harmful than cigarettes to themselves (90.6%) or to others (86.7%), enjoyment (76.5%), and social acceptability (74.4%). About half of current smokers (55.1%) reported using HTPs because these products might help them quit smoking. However, a near-equal percentage (52.0%) of current smokers reported using HTPs to replace some of the cigarettes they smoked so that they did not have to give up smoking altogether. If smokers are using HTPs to complement rather than quit their smoking, then the harm reduction potential of HTPs suggested by the toxicity studies will be diminished.
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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 | 0.001 |
| 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".