Trends in the Use of Vaping Products and Other Smoking Cessation Methods Among Adults Who Attempt to Stop Smoking: Findings From the International Tobacco Control Four-Country Smoking and Vaping Surveys (2016–2020)
Bibliographic record
Abstract
INTRODUCTION: E-cigarettes are an increasingly popular method of smoking cessation assistance; however, there is little research on whether this has affected the number of smokers who quit using "any" evidence-based cessation aid. This study examined trends in the use of cessation aids, including e-cigarettes and other evidence-based methods. AIMS AND METHODS: Data were cross-sectional surveys in 2016, 2018, and 2020 from the International Tobacco Control Four Country Smoking and Vaping Survey conducted in Canada, United States (US), England, and Australia. Respondents were adults (≥18) recruited by commercial panel firms who currently smoked, and/or quit smoking in the past 12 months. Respondents were asked about use of e-cigarettes, nicotine replacement therapies, prescription medications, quitlines, and counseling services during their last quit attempt (LQA). Generalized estimating equation regression models that were analyzed separately by country examined use of cessation assistance among 14 536 observations (Canada = 4880; US = 2917; England = 4846; and Australia = 1898). RESULTS: E-cigarettes (29.9%) and nicotine replacement therapy (29.8%) were popular methods of cessation assistance at LQA. Using e-cigarettes at LQA increased in Australia (2016 = 11.1%; 2020 = 25.1%; p=.002) and England (2016 = 37.1%; 2018 = 46.7%; p=.002), with no significant change in Canada or the US. Across all countries, there was little change over time in the overall use of evidence-based cessation assistance. Nearly half of respondents used some form of cessation assistance excluding e-cigarettes. Approximately two-thirds used "any" form of evidence-based cessation including e-cigarettes at LQA, which decreased in Canada (2016 = 64.0%, 2020 = 58.9%; p=.010). CONCLUSIONS: While e-cigarettes are a popular cessation aid, use of other evidence-based cessation assistance has remained comparatively stable among adults that tried to quit smoking. IMPLICATIONS: The findings indicated that e-cigarettes are a popular cessation method among adults trying to quit smoking. Despite differences in e-cigarette use and regulatory environments in the four countries, rates of evidence-based cessation assistance were similar across countries and over time. E-cigarettes can be an effective method for stopping smoking; however, the current study suggests few, if any, changes in the proportion of adults who smoke using any evidence-based form of cessation assistance, despite changes in the use of e-cigarettes as a quit aid.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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".