E-Cigarette Flavors, Devices, and Brands Used by Youths Before and After Partial Flavor Restrictions in the United States: Canada, England, and the United States, 2017‒2020
Bibliographic record
Abstract
Objectives. To examine the impact of US restrictions implemented in February 2020 prohibiting flavors other than menthol and tobacco in cartridge-based e-cigarettes. Methods. We analyzed 5 cross-sectional waves of the International Tobacco Control Policy Evaluation Project Youth Tobacco and Vaping Surveys, conducted online with youths aged 16 to 19 years in the United States, Canada, and England, for differences in usual e-cigarette flavor, device, and brand reported by past-30-day vapers (n = 9512) before (2017, 2018, 2019), during (February 2020), and after (August 2020) implementation of US flavor restrictions. Results. In August 2020, 78.7% of vapers in the United States reported using a flavor prohibited in cartridges or pods, versus 86.3% in Canada (adjusted odds ratio [AOR] = 1.73; 95% CI = 1.25, 1.40) and 79.8% in England (AOR = 1.10; 95% CI = 0.78, 1.55). Disposable e-cigarettes (exempt from flavor restrictions) increased to a greater extent among vapers in the United States (13.2% to 36.8%) versus Canada (7.7% to 14.2%; AOR = 2.01; 95% CI = 1.33, 3.04) and England (10.8% to 16.4%; AOR = 2.33; 95% CI = 1.52, 3.57). Puff Bar (disposable) emerged as the most popular brand in the United States. Conclusions. Usual flavors used by youth vapers in the United States were unchanged after 2020 restrictions on cartridge-based e-cigarettes. Youths used brands and devices exempt from the restrictions. (Am J Public Health. 2022;112(7):1014–1024. https://doi.org/10.2105/AJPH.2022.306780 )
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 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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".