Prevalence and characterization of synthetic oral nicotine pouch use in Canadian post-secondary students
Bibliographic record
Abstract
Background: Synthetic oral nicotine pouches (ONP) are a relatively new and increasingly popular means of non-tobacco nicotine consumption. Despite growing understanding of ONP use in Europe, few studies characterize ONP use in Canada. The intersection of ONP use with that of combustible tobacco and non-tobacco nicotine products in this population is also poorly defined. Aims: To quantify current ONP use prevalence and characterize patterns of ONP usage relative to other forms of tobacco and non-tobacco nicotine consumption among Canadian post-secondary students. Methods: A web-based survey of Canadian post-secondary (university/college) students from Sept.–Oct. 2024 collected demographics, self-reported ONP history and recent use, and other nicotine-source use information. The Penn State Nicotine Pouch Dependence Index was also embedded within the survey. Results: Of 452 post-secondary students with valid survey responses (22% male, 78% female; age: 20.2±2.6y), 27.2% reported ever-use of ONPs and 12% reported ONP use in the last 30 days. Mean±SD age at first use was 19.2±3.0 years. 77% and 89% of ONP users reported ever-use of tobacco and e-cigarettes, respectively, versus 24% and 44% of non-ONP users (p<0.001). Among ONP ever-users, 62.3% reported no (Penn State score 0-3), 29.5% reported low (Penn State score 4-8), and 8.2% reported medium (Penn State score 9-12) dependence. Conclusions: These data provide a first glimpse into ONP use in Canadian post-secondary students, against which to assess future use patterns of both oral and inhaled combustible nicotine products, providing a foundation for evaluating the public health impact of these novel nicotine delivery products.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".