Perceptions, Experiences, and Patterns of Cannabis Use in Individuals with Mood and Anxiety Disorders in the Context of Cannabis Legalization and Medical Cannabis Program in Canada – A Qualitative Study
Bibliographic record
Abstract
INTRODUCTION: Perceptions of cannabis as a potential medical treatment for mood and anxiety disorders have been increasing in the context of legalizations, availability, and medical cannabis programs, though current evidence predominately indicates risks and negative effects of cannabis use (CU) on mental health outcomes. This study aims to understand motivations, perceptions, effects, and patterns of CU in individuals with mood and anxiety disorders. METHODS: Thirty-six adult patients diagnosed with mood or anxiety disorders, obsessive-compulsive disorder, or posttraumatic stress disorder who were currently using cannabis completed an in-depth qualitative interview on individual motivations, perceptions, experiences, effects, and patterns of their CU. The thematic analysis focused on phases of CU and sources of cannabis products and information. RESULTS: Reported motivations for initiation of CU included curiosity, peer pressure, and dissatisfaction with conventional treatments. Factors such as psychotropic effects and coping with mental health symptoms and insomnia contributed to the continuation of CU. More negative effects, including cognitive dysfunction, worsening of mood, and anxiety symptoms, were acknowledged with ongoing CU. Concerning findings included common initiation of CU before age 18, combined medical and recreational CU, rare consultation of medical professionals on CU, and potential effects and harms. DISCUSSION: Findings indicate individual complexity of motivations, perceptions, and patterns of CU in the study population. The reported potential beneficial effects of specific cannabis products should be further investigated. Findings emphasize patient-provider dialogue on both CU and conventional treatments. Information from this study can contribute to and inform the development of education, prevention, and intervention strategies.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.009 | 0.005 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".