Use of Heated Tobacco Products within Indoor Spaces: Findings from the 2018 ITC Japan Survey
Bibliographic record
Abstract
Although heated tobacco products (HTPs) have become increasingly popular in Japan, little is known about whether these emerging tobacco products are being used within indoor public spaces. Nationally representative data were obtained prior to implementation of a comprehensive smoke-free law in Japan as part of Wave 1 of the International Tobacco Control Japan Survey (February-March 2018). We estimated the weighted prevalence of HTP use within indoor public spaces among tobacco users and compared these to estimates for combustible cigarettes (CCs). Overall, 15.6% of current tobacco users in Japan declared that they used HTPs within indoor public spaces. Any HTP use within indoor public spaces was significantly lower than any CC use (80.1% vs. 96.7%). Dual HTP + CC users reported using CCs more frequently than using HTPs within indoor public spaces (97.7% vs. 76.0%). In conclusion, HTP use is less common than CC use within indoor public spaces. Findings of this study can inform the development of targeted smoke-free policies to benefit public health.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 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".