Impact of the Canadian Tobacco and Vaping Products Act on e-cigarette use and perceived risk in adolescents
Bibliographic record
Abstract
Introduction: Canada enacted the Tobacco and Vaping Products Act (TVPA) in 2018, which prohibited the sale of e-cigarettes to individuals under 18. However, this law increased the distribution and sale of e-cigarettes to individuals over 18. Presently, there is limited evidence on the impact of the TVPA on adolescents’ use of e-cigarettes. The aim of this study is to assess adolescents’ prevalence and perception of e-cigarette use before and after enactment of the TVPA. Methods: The Canadian Tobacco, Alcohol and Drugs Survey for 2017 and the Canadian Student Tobacco, Alcohol and Drugs Survey for 2015, 2017, and 2019 were obtained. Using RStudio, we conducted two-way ANOVA with Tukey’s post hoc test. We reported the goodness of fit of each model through its multiple R-squared values and conducted likelihood ratio tests. Results were presented as the mean with 95% confidence intervals. Results: We found that e-cigarette use was more prevalent in adolescents compared to adults prior to enactment of the TVPA. Interestingly, e-cigarette use in adolescents increased even after enactment of the TVPA, and this law did not impact adolescents’ perceived risk of e-cigarette and conventional cigarette use. Furthermore, e-cigarette use in adolescents was highest in Saskatchewan and Newfoundland and lowest in Quebec and Ontario. Conclusion: Although the TVPA aimed to reduce e-cigarette use in adolescents, this study demonstrates that the TVPA generated the opposite effect. These findings highlight the need for improved public education and stricter e-cigarette sale regulations.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".