Mental Health and Cognition in Older Cannabis Users: a Review
Bibliographic record
Abstract
BACKGROUND: The impact of cannabis use on mental health and cognition in older adults remains unclear. With the recent legalization of cannabis in Canada, physicians will need up-to-date information about the mental and cognitive effects of cannabis use in this specific population. METHOD: A narrative review was conducted to summarize the literature on mental health and cognitive effects of cannabis use in older adults using Medline (OvidSP). RESULTS: A total of 16 studies were identified, including nine cross-sectional studies on mental health comorbidities reported by older cannabis users. The self-reported prevalence of mental and substance use disorders is approximately two to three times higher in older adults who report past-year cannabis use, compared to older adults who report using more than one year ago or never using. The remaining seven clinical trials found that short-term, low-dose medical cannabis was generally well-tolerated in older adults without prior serious mental illness. However, mental/cognitive adverse effects were not systematically assessed. CONCLUSION: Although preliminary findings suggests that low-dose, short-term medical cannabis does not carry significant risk of serious mental health and cognitive adverse effects in older adults without prior psychiatric history, epidemiological studies find a correlation between past-year cannabis use and poor mental health outcomes in community-dwelling older adults. These findings may indicate that longer term cannabis use in this population is detrimental to their mental health, although a direct causal link has not been established. Larger, longitudinal studies on the safety of medical cannabis in older adults are needed.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".