Preventing and addressing youth vaping in British Columbia, Canada: Evidence from triangulation of a scoping review of vaping policy and qualitative interviews with school-aged youth
Bibliographic record
Abstract
Vaping remains a widespread and ongoing epidemic among youth, with research demonstrating that well-designed policies can play a critical role in curbing this growing issue. The present study provides a Canadian case-study examination of vaping policy by triangulating a scoping review of federal (Canada, n = 3), provincial (British Columbia, n = 4), and regional (Okanagan, n = 26) policies ( N = 33) from 2000 to 2024 with qualitative interviews with secondary school students aged 12 to 18 ( N = 25). The scoping review, conducted in 2020 and updated in 2024, followed the Arksey and O'Malley framework and incorporated guidelines from PRISMA to ensure comprehensive identification of relevant policies across government, health, and educational domains. The interviews, conducted in 2020 and 2021 in the Okanagan region of British Columbia, were analyzed using NVivo software through conventional content analysis, an inductive approach where two coders collaboratively identified categories and sub-categories from participant responses using a finalized codebook. The policy review identified gaps in comprehensiveness, public accessibility, and enforcement, particularly at regional levels, where policies often lack comprehensiveness and fail to address vaping-specific challenges. Interview findings revealed youth perceptions of school policies as poorly implemented, reactive, and overly punitive, highlighting the need for proactive, educational approaches to address vaping behaviors. Findings emphasize the importance of clear, accessible, and targeted policies that address possession, distribution, and marketing while involving youth, educators, and parents in awareness and prevention efforts. This case study provides insights applicable to other jurisdictions, offering a framework for designing dynamic, equitable, and effective vaping policies internationally. • Triangulating vaping policies with youth accounts offers a novel evaluation modality. • Many vaping policies lack vaping-specific measures, relying on outdated smoking frameworks. • Youth perceive school policies as reactive, punitive, and ineffective at curbing vaping. • School policies fail to address possession, distribution, marketing, and accessibility issues. • Youth call for proactive measures, including education and targeted health campaigns.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 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".