Healthcare professionals' perspectives on the use of medicinal cannabis to manage chronic pain: A systematic search and narrative review
Bibliographic record
Abstract
RATIONALE, AIMS, AND OBJECTIVES: Chronic pain is a global public health problem that negatively impacts individuals' quality of life and imposes a substantial economic burden on societies. The use of medicinal cannabis (MC) is often considered by patients to help manage chronic pain as an alternative or supplement to more conventional treatments, given enabling legalization in a number of countries. However, healthcare professionals involved in providing guidance for patients related to MC are often doing so in the absence of strong evidence and clinical guidelines. Therefore, it is crucial to understand their perspectives regarding the clinical use and relevance of MC for chronic pain. As little is known about attitudes of HCPs with regard to MC use for chronic pain specifically, the aim of this review was to identify and synthesize the published evidence on this topic. METHODS: A systematic search was conducted across six databases: MEDLINE, EMBASE, CINAHL, Scopus, Web of Science, and PubMed from 2001 to March 26, 2021. Three authors independently performed the study selection and data extraction. Thematic analysis was undertaken to identify key themes. RESULTS: A total of 26 studies were included, involving the United States, Israel, Canada, Australia, Ireland, and Norway, and the perspectives of physicians, nurses, and pharmacists. Seven key themes were identified: MC as a treatment option for chronic pain, and perceived indicated uses; willingness to prescribe MC; legal issues; low perceived knowledge and the need for education; comparative safety of MC versus opioids; addiction and abuse; and perceived adverse effects; CONCLUSION: To support best practice in the use of MC for chronic pain, healthcare professionals require education and training, as well as clinical guidelines that provide evidence-based information about efficacy, safety, and appropriate dosage of products for this indication. Until these gaps are addressed, healthcare professionals will be limited in their capacity to make treatment recommendations about MC for people/patients with chronic pain.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.014 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 source (direct Gemma or distilled Codex), 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".