Mode Matters: Investigating the Associations Between Mode of Cannabis Use and Self-Reported Physical and Psychological Effects
Bibliographic record
Abstract
BACKGROUND: The legalization of recreational cannabis in Canada and its subsequent increases in use prevalence have sparked concerns about its potential health effects, particularly for young users. Moreover, the diversification of cannabis product availability and modes of use has greatly outpaced our understanding of how these variations affect user experiences. This study aimed to fill knowledge gaps in the health effects of cannabis across modes of use, with a focus on sex differences. METHODS: A sample of 206 young adult post-secondary students (62% female) primarily above the legal age of purchase, who regularly used cannabis participated in a 14-d ecological momentary assessment. Participants completed two daily surveys on their mobile device, reporting details about their most recent cannabis use occasion. Multilevel modeling was used to analyze the relationship between mode of use and reported health effects among males and females. RESULTS: Self-reported effects varied significantly by mode of use. Bongs predicted significantly more physical and psychological health effects. Joint-use occasions were associated with significantly more physical health effects among males, and significantly more psychological effects among females. The use of edibles among females predicted significantly fewer physical health effects, while females' use of hand pipes predicted significantly more psychological health effects. CONCLUSIONS: The current findings indicate that the mode of cannabis use critically influences the physical and psychological experiences of young adults. Understanding these differences is vital for developing targeted public health interventions and providing evidence-based guidance for decision makers and healthcare providers.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".