A Systematic Investigation of Interventions Preventing Vaping Among Adolescents: A Multiple Method Study
Bibliographic record
Abstract
Background: E-cigarettes, also known as vaping devices, are the most commonly used nicotine product among Ontario adolescents, with past year prevalence doubling from 11% to 23% between 2017 and 2019. Since vaping has the potential to lead to future nicotine dependence this escalating prevalence is deeply concerning. The overall aim of this thesis was to examine public health interventions targeting the prevention of adolescent vaping and to identify characteristics associated with vaping among Ontario adolescents. Objectives: 1) To identify existing public health interventions targeting the prevention of adolescent vaping; 2) to determine and compare regional (Greater Toronto Area (GTA), north, west, east) variations in adolescent vaping rates and associated characteristics among a population-based sample of Ontario students; 3) to examine Ontario public health professionals’ perceptions of adolescent vaping. Methods: A multiple method study was used for this thesis. To address Objective 1, a scoping review was conducted using Joanna Briggs Institute methodology. Objective 2, a case-control analysis using cross-sectional Ontario Student Drug Use and Health Survey data was performed. A qualitative collective case study was conducted to address Objective 3. Results: Vaping prevention interventions found in the literature and real-world practice included: school-based, community-based, media/web-based, and policies/regulations. Factors enabling prevention efforts included partnerships and collaborations, and funding. Characteristics associated with vaping included: identifying as male (OR=1.36, 95% CI=1.11, 1.67), being a high school student (OR=2.61, 95% CI=1.95, 3.49); engaging in three hours or more of daily social media (OR=5.57, 95% CI=3.54, 8.76), alcohol use (OR=3.54, 95% CI=2.85, 4.37), smoking (OR=4.76, 95% CI=3.10, 7.30), cannabis use (OR=10.66, 95% CI=8.11, 14.0), having Canadian born parents (OR=1.37, 95% CI=1.06, 1.77); and feeling a part of the school community (OR=1.35, 95% CI=1.08,1.70). Of regional significance, students in northern, western, or eastern Ontario had increased odds of past year vaping compared to those in the GTA. Conclusions: Urgent action is needed to prevent adolescent vaping and protect this generation from associated risks. Public health interventions tailored to local characteristics and contexts are essential for maximizing impact. Study findings offer valuable insights for shaping and implementing effective vaping prevention strategies, contributing to improved population health outcomes for adolescents.
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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 | 0.068 | 0.135 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.008 | 0.009 |
| Bibliometrics | 0.011 | 0.009 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".