Cannabis Use Characteristics and Reasons for Product Choices Among Patients Accessing Treatment for Substance Use Disorders: A Mixed-Methods Study
Bibliographic record
Abstract
Objective: The diversity and potency of cannabis products have increased in recent years, underscoring the importance of understanding which products are being used and why. Patients with substance use disorders (SUDs) use have a high prevalence of risky cannabis use, making it especially important to understand use patterns in this group. We aimed to first describe cannabis product characteristics and then explore reasons for choosing products in our sample. Method: In this mixed-methods study, 472 adults who self-reported accessing SUD treatment and lifetime cannabis use completed an online survey. A subset of 22 participants completed in-depth interviews. Quantitative results focused on describing cannabis use characteristics (e.g., product types) among participants reporting past-year cannabis use (current use group) or lifetime cannabis use but no use in past year (past use group), while qualitative descriptive analysis was used to describe reasons for choosing products among participants who were currently using cannabis. Results: Across medical and non-medical use of cannabis, dried flower and smoked cannabis formulations were most used (e.g., 89% of the current use group reported smoking cannabis for non-medical purposes), followed by edibles (e.g., 53% of the current use group used edible formulations of cannabis for non-medical purposes), though there was considerable use of higher-potency products such as concentrates and dabs (e.g., 11% of the current use group had used dabs for non-medical purposes). Our qualitative analysis found that almost all participants were motivated by THC content when purchasing products, yet sometimes perceived medical benefits or harm reduction were reasons for using certain products (especially CBD-dominant products), while sometimes other factors (e.g., convenience, familiarity) were influential. Conclusions: Cannabis use characteristics (including motives for choosing products) are complex and nuanced in patients accessing SUD treatment. More work is needed to understand longitudinal relationships between use of different cannabis products and both harms and potential benefits.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".