Trends in e-cigarette brands, devices and the nicotine profile of products used by youth in England, Canada and the USA: 2017–2019
Bibliographic record
Abstract
Background: The e-cigarette market has rapidly evolved, with a shift towards higher nicotine concentration and salt-based products, such as JUUL; however, the implications for youth vaping remain unclear. Methods: Repeat cross-sectional online surveys were conducted in 2017, 2018 and 2019, with national samples of youth aged 16–19 years recruited from commercial panels in Canada (n=12 018), England (n=11 362) and the USA (n=12 110). Regression models examined differences between countries and over time in the types of e-cigarette products used (design and nicotine content), reasons for using brands and differences in patterns of use, sociodemographics and dependence symptoms by brand/nicotine content. Results: In 2019, the use of pod- or cartridge-style e-cigarettes was greater in Canada and the USA than England, with Smok and JUUL the leading brands in all countries. In 2019, youth vapers in England were less likely to report using e-cigarettes with ≥2% nicotine (12.8%) compared with Canada (40.5%; adjusted OR (AOR)=4.96; 95% CI 3.51 to 7.01) and the USA (37.0%; AOR=3.99, 95% CI 2.79 to 5.71) and less likely to report using nicotine salt-based products (12.3%) compared with Canada (27.1%; AOR=2.77, 95% CI 1.93 to 3.99) and the USA (21.9%; AOR=2.00, 95% CI 1.36 to 2.95). In 2019, self-reported use of products with higher nicotine concentration was associated with significantly greater frequency of vaping, urges to vape and perceived vaping addiction (p<0.05 for all). Conclusions The use of high-nicotine salt-based products is associated with greater symptoms of dependence, including JUUL and other higher-nicotine brands. Greater use of high-nicotine salt-based products may account for recent increases in the frequency of vaping among youth in Canada and the USA.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".