Use of disposable e‐cigarettes among youth who vape in Canada, England and the United States: Repeat cross‐sectional surveys, 2017–2023
Bibliographic record
Abstract
AIMS: To measure changes over time (between 2017 and 2023) in disposable e-cigarette use and popular brands among youth in Canada, England and the United States (US) who vaped. DESIGN: Nine waves of repeat cross-sectional data from the International Tobacco Control Policy Evaluation Project (ITC) Youth Tobacco and Vaping Survey. SETTING: Online surveys conducted in Canada, England and the US between 2017 and 2023. PARTICIPANTS: Youth aged 16 to 19 years who had vaped in the past 30 days (n = 19 710). MEASUREMENTS: Usual type (disposable, cartridge/pod, tank) and brand of e-cigarette used; covariates sex at birth, age, race/ethnicity, cigarette smoking status, vaping on ≥20 of the past 30 days. FINDINGS: In 2017, the majority of youth who vaped in the past 30 days reported using refillable tank e-cigarettes, whereas disposable e-cigarettes were the least commonly used product type in Canada (10.0%), England (8.6%) and the US (14.4%). Cartridge/pods overtook tank devices in Canada and the US by 2020; however, by 2023, disposables were the leading type of e-cigarette used by youth who vaped in all three countries (Canada = 58.5%; England = 83.2%; US = 67.3%). The shift to disposables occurred among all socio-demographic groups, with few differences by vaping and smoking status. The percentage of youth who vaped that reported 'no usual' brand also decreased substantially from 2017 (29% to 42%) to 2023 (11% to 17%). The rise of disposable e-cigarettes appeared to be driven primarily by individual brands in the US (Puff Bar in 2020/2021, Elf Bar in 2022/2023) and England (Elf Bar in 2022/2023). CONCLUSIONS: The e-cigarette market has evolved rapidly with notable shifts in the types of e-cigarettes used by youth who vape in Canada, England and the United States. Although the timing differed across countries, major shifts in device types appear to be driven by individual brands and were often accompanied by increases in vaping prevalence among youth.
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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 | 0.001 | 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".