Cannabis use among youth in Canada: a scoping review protocol
Bibliographic record
Abstract
Introduction Canadian youth (aged 15–24) have the highest rates of cannabis use globally. There are increasing concerns about the adverse effects of cannabis use on youth physical and mental health. However, there are gaps in our understanding of risks and harms to youth. This scoping review will synthesise the literature related to youth cannabis use in Canada. We will examine the relationship between youth cannabis use and physical and mental health, and the relationship with use of other substances. We will also examine prevention strategies for youth cannabis use in Canada and how the literature addresses social determinants of health. Methods and analysis Using a scoping review framework developed by Arksey and O’Malley, we will conduct our search in five academic databases: MEDLINE, Embase, APA PsycInfo, CINAHL and Web of Science’s Core Collection. We will include articles published between 2000 and 2021, and articles meeting the inclusion criteria will be charted to extract relevant themes and analysed using a qualitative thematic analysis approach. Ethics and dissemination This review will provide relevant information about youth cannabis use and generate recommendations and gaps in the literature. Updated research will inform policies, public education strategies and evidence-based programming. Results will be disseminated through an infographic, peer-reviewed publication and presentation at a mental health and addiction conference. Ethics approval is not required for this scoping review.
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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 | 0.085 | 0.071 |
| Meta-epidemiology (narrow) | 0.004 | 0.005 |
| Meta-epidemiology (broad) | 0.011 | 0.009 |
| Bibliometrics | 0.026 | 0.024 |
| Science and technology studies | 0.009 | 0.005 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.007 | 0.007 |
| Research integrity | 0.007 | 0.005 |
| Insufficient payload (model declined to judge) | 0.054 | 0.008 |
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".