The Prevalence of Vaping and Smoking as Modes of Delivery for Nicotine and Cannabis among Youth in Canada, England and the United States
Bibliographic record
Abstract
Background: Vaping has become an increasingly common mode of administration for both nicotine and cannabis, with overlap among users, devices, as well as nicotine and cannabis companies. There is a need to understand patterns of use among youth, including the way nicotine and cannabis are administered. Methods: Data are from Wave 2 of the ITC Youth Tobacco and Vaping survey, an online survey conducted in 2018 among 16–19 year-olds recruited from commercial panels in Canada (n = 3757), England (n = 3819), and the U.S. (n = 3961). The prevalence of past 30-day vaping nicotine, non-nicotine and cannabis substances, as well as cannabis modes of use was examined. Logistic regression models examined between country differences in prevalence. Results: Past 30-day cannabis use was highest among Canadian youth (16.6%), followed by youth in the U.S. (13.8%) and England (9.0%). Vaping e-cigarettes was substantially more prevalent than vaping cannabis in all three countries. All forms of cannabis use were higher among Canadian and U.S. youth compared to England (p < 0.001 for all). Past 30-day cannabis users in the U.S. were more likely to report vaping cannabis oil (30.1%), and consuming solid concentrates such as wax and shatter (30.2%), compared to cannabis users in Canada (18.6% and 22.9%) and England (14.3% and 11.0%; p < 0.001 for all). Conclusions: Youth are administering cannabis and nicotine using a wide diversity of modes. Cannabis users in the U.S.—where an increasing number of states have legalized medical and non-medical cannabis—reported notably higher use of more potent cannabis products, including cannabis oils and extracts.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".