Reasons for Initiation and Regular Use of Heated Tobacco Products among Current and Former Smokers in South Korea: Findings from the 2020 ITC Korea Survey
Bibliographic record
Abstract
South Korea is the world's second-largest heated tobacco product (HTP) market after Japan. HTP sales in South Korea have increased rapidly since May 2017, accounting for 10.6% of the total tobacco market in 2020. Despite this, little is known as to why HTP consumers who were current and former smokers started using HTPs and used them regularly. We analyzed cross-sectional data for 1815 adults (aged 19+) who participated in the 2020 International Tobacco Control (ITC) Korea Survey, of whom 1650 were HTP-cigarette consumers (those who reported smoking cigarettes and using HTPs ≥ weekly) and 165 were exclusive HTP consumers (using HTPs ≥ weekly) who were former or occasional smokers (smoking cigarette < weekly). Respondents were asked to report the reason(s) they used HTPs, with 25 possible reasons for HTP-cigarette consumers and 22 for exclusive HTP consumers. The most common reasons for initiating HTP use among all HTP consumers were out of curiosity (58.9%), family and friends use HTPs (45.5%), and they like the HTP technology (35.9%). The most common reasons for regularly using HTPs among all HTP consumers were that they were less smelly than cigarettes (71.3%), HTPs are less harmful to own health than cigarettes (48.6%), and stress reduction (47.4%). Overall, 35.4% of HTP-cigarette consumers reported using HTPs to quit smoking, 14.7% to reduce smoking but not to quit, and 49.7% for other reasons besides quitting or reducing smoking. In conclusion, several common reasons for initiating and regularly using HTPs were endorsed by all HTP consumers who were smoking, had quit smoking completely, or occasionally smoked. Notably, only about one-third of HTP-cigarette consumers said they were using HTPs to quit smoking, suggesting that most had no intention of using HTPs as an aid to quit smoking in South Korea.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".