Identifying changes in e-cigarette use among a longitudinal sample of Canadian youth e-cigarette users in the COMPASS cohort study, 2017/18–2018/19
Bibliographic record
Abstract
Objectives: There are few studies describing longitudinal changes in vaping patterns among current youth e-cigarette users. The objective of this study was to identify-one-year changes in e-cigarette use patterns among a longitudinal sample of Canadian youth e-cigarette users between 2017/18 and 2018/19. Methods: The longitudinal sample included n = 4,071 current (past 30-day) e-cigarette users in grades 9-11 attending schools in four Canadian provinces. Students reported the number of days they used e-cigarettes in the past 30 days in 2017/18 and 2018/19. Based on responses, students could have escalated, reduced, stopped, or maintained their level of vaping. The prevalence of each e-cigarette use pattern was identified across demographic characteristics and regression models identified significant predictors of each use pattern. Results: Over one year, 49.2% of current youth e-cigarette users escalated, 12.8% reduced, 20.2% stopped, and 17.8% maintained their frequency of e-cigarette use. Baseline e-cigarette use frequencies varied according to use pattern. Current youth e-cigarette users with higher baseline vaping frequencies had lower odds of escalating and stopping e-cigarette use and higher odds of reducing e-cigarette use relative to maintaining the same frequency of use. Conclusions: While about half of current youth e-cigarette users increased their frequency of e-cigarette use over a 1-year period, a significant number also decreased or stopped vaping at a time when the prevalence of youth e-cigarette use increased rapidly in Canada. There is a need for longitudinal data to monitor and evaluate changes to e-cigarette use patterns that may be in response to changing public health policies.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| 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".