Associations Between Risk Perceptions and Cigarette, E-cigarette, and Dual-Product Use Among Canadian Adolescents
Bibliographic record
Abstract
INTRODUCTION: The popularity of e-cigarettes has increased significantly in recent years. E-cigarettes are perceived as less harmful than cigarettes, and both dual-use of cigarette and e-cigarette use is common among adolescents. This study assessed cigarette and e-cigarette risk perception and associations with dual-product use among Canadian adolescents. METHODS: We used data from the 2016-2017 Canadian Student Tobacco, Alcohol, and Drugs Survey. Perceived risks of cigarette and e-cigarette use were classified into 4 categories: "high-risk perception," "high-e-cigarette-risk and low-cigarette-risk perception," "low-e-cigarette-risk and high-cigarette-risk perception," and "low-risk perception." Adjusted odds ratios (aOR) were estimated from multinomial logistic regression. RESULTS: Of the population, 92% perceived high risk from cigarettes, and 65% from e-cigarettes. Compared to students with low-risk perception, those with high-risk perception of both products had lower odds of dual-use (aOR: 0.21; 95% confidence interval [CI]: 0.15, 0.28), cigarette-only use (aOR: 0.33; 95% CI: 0.25, 0.45), and e-cigarette-only use (aOR: 0.64; 95% CI: 0.51, 0.79) relative to nonusers. Adolescents with high-e-cigarette and low-cigarette-risk perception had higher odds of e-cigarette-only use, relative to nonusers. Those with high-risk perception were more likely to be e-cigarette-only users relative to cigarette-only users. CONCLUSION: Results highlight that high perceived risk is associated with lower odds of use. However, those with a high-risk perception of both products had higher odds of e-cigarette use relative to cigarette-only users; as did those with high-e-cigarette and low-cigarette-risk perception, relative to nonusers. Future research should assess ways of communicating the risks of adolescent tobacco use.
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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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".