The association between cannabis use and outcome in pharmacological treatment for opioid use disorder
Bibliographic record
Abstract
BACKGROUND: With the ongoing opioid crisis and policy changes regarding legalization of cannabis occurring around the world, it is necessary to consider cannabis use in the context of opioid use disorder (OUD) and its treatment. We aimed to examine (1) past-month cannabis use in patients with OUD, (2) self-reported cannabis-related side effects and craving, and (3) the association between specific characteristics of cannabis use and opioid use during treatment in cannabis users. METHODS: Participants receiving pharmacological treatment for OUD (n = 2315) were recruited from community-based addiction treatment clinics in Ontario, Canada, and provided information on past-month cannabis use (self-report). Participants were followed for 3 months with routine urine drug screens in order to assess opioid use during treatment. We used logistic regression analysis to explore (1) the association between any cannabis use and opioid use during treatment, and (2) amongst cannabis-users, specific cannabis use characteristics associated with opioid use. Qualitative methods were used to examine responses to the question: "What effect does marijuana have on your treatment?". RESULTS: Past-month cannabis use was reported by 51% of participants (n = 1178). Any cannabis use compared to non-use was not associated with opioid use (OR = 1.03, 95% CI 0.87-1.23, p = 0.703). Amongst cannabis users, nearly 70% reported daily use, and half reported experiencing cannabis-related side effects, with the most common side effects being slower thought process (26.2%) and lack of motivation (17.3%). For cannabis users, daily cannabis use was associated with lower odds of opioid use, when compared with occasional use (OR = 0.61, 95% CI 0.47-0.79, p < 0.001) as was older age of onset of cannabis use (OR = 0.97, 95% CI 0.94, 0.99, p = 0.032), and reporting cannabis-related side effects (OR = 0.67, 95% CI 0.51, 0.85, p = 0.001). Altogether, 75% of cannabis users perceived no impact of cannabis on their OUD treatment. CONCLUSION: Past-month cannabis use was not associated with more or less opioid use during treatment. For patients who use cannabis, we identified specific characteristics of cannabis use associated with differential outcomes. Further examination of characteristics and patterns of cannabis use is warranted and may inform more tailored assessments and treatment recommendations.
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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 | 0.001 |
| 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 | 0.000 |
| 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".