The impact of the ‘CATCH My Breath’ vaping prevention curriculum among high school students in Ontario, Canada: Results of a pilot test
Bibliographic record
Abstract
Background: Youth vaping is a public health concern in Canada. However, there is a dearth of evaluation data for school-based vaping prevention programs in Canada. This pilot study assessed short-term changes in knowledge, subjective norms, and intentions to vape among a sample of high school students in Ontario, Canada exposed to the 'CATCH My Breath' (CMB) vaping prevention curriculum. Methods: A convenience sample of 10 high schools across Ontario delivered CMB lessons between October 2022 and April 2023. Students completed an online survey before being exposed to CMB and 4-weeks after the lessons. McNemar's Chi-square exact tests of paired proportions assessed significant changes in knowledge, subjective norms, and intentions to vape before/after exposure to the curriculum among n = 116 students who could be linked over time. Results: After exposure to CMB, students exhibited a significant increase in their knowledge: pre-test scores averaged 5.5 and post-test scores averaged 7.5. At post-test, significantly fewer students thought that most people in high school vape. There were no significant changes in intentions to vape and pre/post changes were similar for boys and girls. Discussion: After exposure to CMB, high school students in Ontario demonstrated significant increases in knowledge of the risks of vaping and modest reductions in perceptions of subjective norms of vaping. CMB has been adapted for use in high schools in Canada, and implementing this program could help to reduce youth vaping.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".