Association of Cannabis With Long-Term Clinical Symptoms in Anxiety and Mood Disorders
Bibliographic record
Abstract
OBJECTIVE: To systematically review studies examining the longitudinal associations between cannabis use and symptomatic outcomes among individuals with an anxiety or mood disorder at baseline. DATA SOURCES: A search of the literature up to May 2017 was conducted using several databases. Search terms related to the exposure (ie, cannabis) and outcome (ie, symptoms) variables of interest. There were no search restrictions. STUDY SELECTION: In total, 10,191 citations were screened. Key inclusion criteria related to (1) cohort-based longitudinal study design using adults who met criteria for a mood or anxiety disorder at baseline, (2) an independent variable focusing on at least baseline cannabis use, and (3) a dependent variable focusing on the symptomatic course and/or outcomes in anxiety and mood disorders (AMD). DATA EXTRACTION: We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Methodological characteristics and key findings were extracted from each study, and quality assessments were conducted for each study. RESULTS: Twelve studies (with a total of 11,959 individuals) met inclusion criteria related to posttraumatic stress disorder (n = 4), panic disorder (n = 1), bipolar disorder (n = 5), and depressive disorder (n = 2). Across 11 studies, "recent" cannabis use (ie, any/greater frequency of use during the last 6 months) was associated with higher symptomatic levels over time relative to comparison groups (ie, no/lesser frequency of use). Ten of these studies further suggested that cannabis use was associated with less symptomatic improvement from treatment (eg, medication, psychotherapy for AMD). CONCLUSIONS: Recent cannabis use was associated with negative long-term symptomatic and treatment outcomes across AMD. The findings should be interpreted with caution, considering the observational designs across studies and the biases associated with the samples (eg, inpatients) and sources of cannabis consumed (ie, unregulated sources). Nonetheless, clinicians can use the insight gained to inform their own and their patients' knowledge concerning potential risks of cannabis with regard to symptoms of AMD.
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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 | 0.012 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| 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".