Sex Differences in the Association Between Cannabis Use and Suicidal Ideation and Attempts, Depression, and Psychological Distress Among Canadians
Bibliographic record
Abstract
BACKGROUND: Depression, anxiety, and substance use disorders are leading causes of morbidity worldwide. The most commonly used illicit substance is cannabis and there is some evidence that the association between cannabis use and poor mental health is more pronounced among females compared with males. This analysis examines sex differences in the association between cannabis use and major depressive episode (MDE), suicidal thoughts and attempts, and psychological distress. METHODS: This study uses data from the 2002 and 2012 Canadian Community Health Survey's Mental Health Component, repeated cross-sectional surveys of nationally representative samples of Canadians 15 years of age and older ( n = 43,466). Linear and binary logistic regressions were performed, applying weighting and bootstrapping. RESULTS: There were significant sex differences in the strength of the association between cannabis use and suicidal thoughts and attempts and psychological distress, but not MDE. Females who reported using cannabis occasionally (defined as 1 to 4 times a month) reported higher levels of psychological distress than their male counterparts. Females who reported using regularly (defined as more than once per week) reported higher levels of psychological distress and were more likely to report suicidal thoughts and attempts. CONCLUSIONS: Future research is needed to further our understanding of the nature of these sex differences. Public health messaging should incorporate being female as a potential risk factor for the co-occurrence of cannabis use and emotional problems, particularly at higher frequencies of use. Clinicians should also be aware of this association to better inform integrated mental health and substance use screening, discussions, and care, particularly for female patients.
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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 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".