Emerging adult perceptions of higher-risk cannabis consumption behaviours
Bibliographic record
Abstract
BACKGROUND: Emerging adults have the highest cannabis consumption rates in Canada and are among the most vulnerable to cannabis-related harms. Since certain cannabis consumption behaviours carry greater risks of harm, the Lower-Risk Cannabis Use Guidelines (LRCUG) provide harm reduction strategies. To address a critical gap in the literature, the current study examined emerging adults' awareness of the guidelines and perceptions of higher-risk cannabis consumption behaviours identified within the LRCUG. METHODS: Emerging adults (N = 653) between the ages of 18-25 years were recruited from across Canada. Participants were presented with five vignettes depicting a character's cannabis consumption behaviours. Each vignette focused on a unique aspect of the character's consumption (frequency, polysubstance use, family history of mental illness, method of consumption, and potency). Participants were randomly assigned to one of three conditions within each of the five vignettes that were altered to capture varying levels of risk (e.g. weekly, almost daily, or daily consumption). Following each vignette, participants were asked to respond to four items relating to overall risk of harm, cognitive health, physical health, and mental health. RESULTS: Participants perceived: (1) frequent consumption to be associated with greater risks than less frequent consumption; (2) simultaneous consumption of cannabis and tobacco as being associated with higher risk of harm, yet no difference between simultaneous consumption of cannabis and alcohol or cannabis consumption alone; (3) consuming cannabis with a family history of psychosis or substance use disorder as being associated with greater overall risk than consumption with no family history; (4) smoking and vaping cannabis as associated with more risk than ingesting edibles; and (5) higher-potency THC-dominant strains as being associated with more risk than lower-potency CBD-dominant strains, yet no difference between the two higher-potency THC-dominant strains. CONCLUSIONS: While emerging adults seemed to appreciate the risks associated with some cannabis consumption behaviours, they had difficulty identifying appropriate levels of harm of other higher-risk behaviours. Through an improved understanding of emerging adult perceptions, effective education campaigns should be designed to improve the awareness of cannabis risks and encourage the uptake of harm reduction awareness and strategies.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".