Perceptions and use of electronic cigarettes among young adults in China
Bibliographic record
Abstract
INTRODUCTION: Little is known about the perception and use of e-cigarettes by the Chinese, particularly the young people. This study reveals the awareness, attitudes, and use of e-cigarettes among young adults in China, examines the relationship between smoking behavior and e-cigarette perception and use, and demonstrates the phenomenon of e-cigarette gifting. METHODS: We used results from a mobile app-based survey conducted in November 2015 that included 10477 young Chinese adults aged between 19 and 29 years. Bivariate tests were conducted to analyze perception and use of e-cigarettes by respondents of different smoking status. Multivariate logistic regressions were applied to examine the correlates of e-cigarette use and perception and e-cigarette gifting behavior, particularly the factors of tobacco smoking status and quitting behavior. RESULTS: Among the surveyed young adults, 88.40% were aware of e-cigarettes, and nearly a quarter of all respondents had used e-cigarettes by the time of our survey. Multivariate regression results demonstrated that current smokers with quitting experience were more likely to be aware of and to use e-cigarettes than current smokers with no quitting experience. Smokers with quitting experience also were more inclined to promote e-cigarettes to others by either recommending them or giving them as gifts. CONCLUSIONS: E-cigarettes have gained popularity among young adults in China and smokers, especially those who had tried quitting, were more likely to have known and used e-cigarettes. More empirical research on the relationship between e-cigarette use and smoking cessation is warranted to better inform a potential regulatory framework in China.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".