Anxiety and Mood Disorders and Cannabis Use
Bibliographic record
Abstract
BACKGROUND: Cannabis use has been linked to anxiety and mood disorders (AMD) in clinical cases, but little research on this relationship has been reported at the epidemiological level. OBJECTIVES: We examined the relationship between self-reported frequency of cannabis use and risk for AMD in the general Ontario adult population. METHODS: Data were based on the CAMH Monitor survey of Ontario adults from 2001 to 2006 (n = 14,531). AMD was assessed with the 12-item version of the General Health Questionnaire (GHQ12). Frequency of cannabis use within the past year was grouped into five categories: No use (abstainer), less than once a month but at least once a year, less than once a week but at least once a month, less than daily but at least once a week, almost every day to more than once a day. Logistic regression analysis of AMD and cannabis use was implemented while controlling for demographics and alcohol problems. RESULTS: AMD was most common among heavy cannabis users (used almost every day or more) (18.1%) and lowest for abstainers (8.7%). Compared to abstainers, the risk of AMD was significantly greater for infrequent cannabis users (OR = 1.43) and heavy cannabis users (OR = 2.04) but not for those in between. CONCLUSION: These data provide epidemiological evidence for a link between both light and heavy cannabis use and AMD. SCIENTIFIC SIGNIFICANCE: Recognizing the comorbidity of heavy cannabis use and AMD should facilitate improved treatment efforts. Our results also suggest the possibility that, for some individuals, AMD may occur at relatively low levels of cannabis use.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".