Cannabis Use Among Mental Health Professionals: A Qualitative Study of Cannabis-Related Risk Perceptions
Bibliographic record
Abstract
BACKGROUND: Perceptions of cannabis-related risk are changing, and many are viewing cannabis as harmless despite the biopsychosocial risks. Perceptions of risk have an impact on behavior as individuals who are less likely to view cannabis as risky are more likely to use it problematically. PURPOSE: This study examined how mental health professionals who use cannabis perceive the risks related to use. METHODS: Interpretative phenomenological analysis was utilized to understand how participants made sense of the harm related to personal and client use. Interviews were conducted with a sample of social workers, nurses, and psychotherapists who work with cannabis-consuming clients. RESULTS: Participants reported cannabis use is related to anxiety, relational challenges, impaired driving, psychosis, cognitive impairment, educational/employment dysfunction, and addiction in some users. CONCLUSION: Assessing risk perceptions among cannabis users can reveal subtle psychosocial problems the user may be experiencing. Mental health workers may benefit from further education regarding cannabis-related physical health harm.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".