“If I knew I could get that every hour instead of alcohol, I would take the cannabis”: need and feasibility of cannabis substitution implementation in Canadian managed alcohol programs
Bibliographic record
Abstract
BACKGROUND: While there is robust evidence for strategies to reduce harms of illicit drug use, less attention has been paid to alcohol harm reduction for people experiencing severe alcohol use disorder (AUD), homelessness, and street-based illicit drinking. Managed Alcohol Programs (MAPs) provide safer and regulated sources of alcohol and other supports within a harm reduction framework. To reduce the impacts of heavy long-term alcohol use among MAP participants, cannabis substitution has been identified as a potential therapeutic tool. METHODS: To determine the feasibility of cannabis substitution, we conducted a pre-implementation mixed-methods study utilizing structured surveys and open-ended interviews. Data were collected from MAP organizational leaders (n = 7), program participants (n = 19), staff and managers (n = 17) across 6 MAPs in Canada. We used the Consolidated Framework for Implementation Research (CFIR) to inform and organize our analysis. RESULTS: Five themes describing feasibility of CSP implementation in MAPs were identified. The first theme describes the characteristics of potential CSP participants. Among MAP participants, 63% (n = 12) were already substituting cannabis for alcohol, most often on a weekly basis (n = 8, 42.1%), for alcohol cravings (n = 15, 78.9%,) and withdrawal (n = 10, 52.6%). Most MAP participants expressed willingness to participate in a CSP (n = 16, 84.2%). The second theme describes the characteristics of a feasible and preferred CSP model according to participants and staff. Participants preferred staff administration of dry, smoked cannabis, followed by edibles and capsules with replacement of some doses of alcohol through a partial substitution model. Themes three and four highlight organizational and contextual factors related to feasibility of implementing CSPs. MAP participants requested peer, social, and counselling supports. Staff requested education resources and enhanced clinical staffing. Critically, program staff and leaders identified that sustainable funding and inexpensive, legal, and reliable sourcing of cannabis are needed to support CSP implementation. CONCLUSION: Cannabis substitution was considered feasible by all three groups and in some MAPs residents are already using cannabis. Partial substitution of cannabis for doses of alcohol was preferred. All three groups identified a need for additional supports for implementation including peer support, staff education, and counselling. Sourcing and funding cannabis were identified as primary challenges to successful CSP implementation in MAPs.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".