Surveying Canadian Pain Physicians’ Attitudes and Beliefs Regarding Medical Cannabis for Chronic Noncancer Pain: A Qualitative Study
Bibliographic record
Abstract
Background: Medical cannabis is commonly and increasingly used by Canadians to manage chronic pain. As of March 2021, Health Canada reported that approximately 300,000 Canadians who were authorized to access medical cannabis, which is more than a 1000% increase from the 24,000 registered in 2015. Physicians, however, receive limited information on therapeutic cannabis during their training, and their perceptions regarding this therapeutic option are uncertain. This study focused on exploring attitudes and beliefs of pain physicians regarding medical cannabis for the management of chronic noncancer pain. Methods: This study utilized a focused ethnography approach. Pain management clinicians within the Greater Toronto and Hamilton Area were recruited through snowball sampling methods, and individually interviewed. We applied thematic analysis to interview transcripts and identified representative quotes. The Hamilton Integrated Research Ethics Board reviewed and approved this project. Results: Thirteen physicians who focused their clinical practice on pain management agreed to be interviewed, and three themes regarding medical cannabis emerged: 1) evidence regarding medical cannabis, 2) medical cannabis as first-line therapy for chronic pain, and 3) barriers to accessing medical cannabis. Subthemes of the last theme included out-of-pocket costs, stigma by society and healthcare providers, and lack of knowledge among physicians. Conclusion: Despite increasing use of medical cannabis for chronic pain among Canadians, pain physicians in our study expressed concerns regarding the evidence to support this therapy and acknowledged important barriers to access.
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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 | 0.175 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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; both teacher heads agree on what is shown here.
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".