Trends in vaping and nicotine product use among youth in Canada, England and the USA between 2017 and 2022: evidence to inform policy
Bibliographic record
Abstract
BACKGROUND: Preventing uptake of nicotine products among youth remains a central objective of tobacco control policy. Comparing trends in the use of nicotine across countries provides an opportunity to identify emergent product trends and to evaluate 'natural experiments' in policies. METHODS: Repeat cross-sectional data were analysed from eight waves of the International Tobacco Control Youth Tobacco and Vaping Survey, conducted between 2017 and 2022. Non-probability samples of youth aged 16-19 years in Canada, England and the USA (N=104 473) completed online surveys including measures on vaping, smoking and use of other nicotine products. This paper summarises findings across the 5-year period of the study, as part of a comprehensive report on key indicators of youth vaping in the three countries. RESULTS: The youth nicotine market has rapidly evolved across the three countries, with different patterns of combustible and non-combustible product use in Canada, the USA and England. These changes are primarily attributable to trends in youth vaping: following declines during the initial COVID-19 pandemic period, by 2022, vaping prevalence neared pre-pandemic levels in the USA and Canada, and reached record highs in England. Notable shifts also occurred in the types of vaping products used by youth, including increased use of disposable, nicotine salt-based products. Additional findings are reported on a range of policy-relevant indicators, including for vaping products, promotions and purchasing. CONCLUSIONS: Patterns of nicotine use among youth have rapidly evolved in recent years due to the proliferation of nicotine products, the COVID-19 pandemic and the emerging impact of policy measures.
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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 | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| 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".