Are Younger Medical Cannabis Users at Risk? Comparing Patterns of Use and Mental Health in Younger and Older Medical Cannabis Dispensary Users
Bibliographic record
Abstract
While there has been a considerable amount of research on recreational cannabis use in youth to date, much less is known about patterns of medical cannabis use in youth. Adult medical versus recreational cannabis users may differ in how they use the product on important factors such as dose, frequency and route of ingestion, and so it is important to understand whether adolescents and young adults differ in how they use medical cannabis compared to adults, and if this increases risk of impaired mental health. In the present study, one hundred members of a community cannabis dispensary who endorsed cannabis use for medical purposes were assessed for major psychiatric disorders, and completed questionnaires related to stress, depression, sleep and somatic symptoms. Detailed information about cannabis use was collected. In the sample, 35% were aged 19-24 years old, and 24% were aged 25-30 (categorized as youth/young adults). In comparison to the older medical cannabis users, there were unexpectedly few differences, both in mental health status as well as pattern of medical cannabis use. These findings contrast with those of recreational cannabis users, and indicate that medical cannabis in youth may be as effective and well-tolerated as in older adults.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".