The role of cannabis in pain management among people living with <scp>HIV</scp> who use drugs: A qualitative study
Bibliographic record
Abstract
INTRODUCTION: People living with HIV who use drugs commonly experience chronic pain and often use illicit opioids to manage pain. Recent research suggests people living with HIV use cannabis for pain relief, including as an adjunct to opioids. This underscores the need to better understand how people living with HIV who use drugs use cannabis for pain management, particularly as cannabis markets are undergoing changes due to cannabis legalisation. METHODS: From September 2018 to April 2019, we conducted in-depth interviews with 25 people living with HIV who use drugs in Vancouver, Canada to examine experiences using cannabis to manage pain. Interviews were audio-recorded, transcribed and coded. Themes were identified using inductive and deductive approaches. RESULTS: Most participants reported that using cannabis for pain management helped improve daily functioning. Some participants turned to cannabis as a supplement or periodic alternative to prescription and illicit drugs (e.g. benzodiazepines, opioids) used to manage pain and related symptoms. Nonetheless, participants' access to legal cannabis was limited and most continued to obtain cannabis from illicit sources, which provided access to cannabis that was free or deemed to be affordable. DISCUSSION AND CONCLUSIONS: Cannabis use may lead to reduced use of prescription and illicit drugs for pain management among some people living with HIV who use drugs. Our findings add to growing calls for additional research on the role of cannabis in pain management and harm reduction, and suggest the need for concrete efforts to ensure equitable access to cannabis.
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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 | 0.004 | 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 | 0.000 |
| 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".