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Record W4281675156 · doi:10.1093/pm/pnac085

Benefits and Concerns regarding Use of Cannabis for Therapeutic Purposes Among People Living with Chronic Pain: A Qualitative Research Study

2022· article· en· W4281675156 on OpenAlexaffabout
Mahmood AminiLari, Natasha Kithulegoda, Patricia H. Strachan, James MacKillop, Li Wang, Sushmitha Pallapothu, Samuel Neumark, Sangita Sharma, Jagmeet Sethi, Ramesh Zacharias, Allison Blain, Lisa Patterson, Jason W. Busse

Bibliographic record

VenuePain Medicine · 2022
Typearticle
Languageen
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsSt. Joseph’s Healthcare HamiltonMcMaster UniversityImpact
Fundersnot available
KeywordsCannabisChronic painMedicineThematic analysisQualitative researchPsychiatryFamily medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: Although there is growing interest in medically authorized cannabis for chronic pain, little is known about patients' perspectives. We explored perceptions of people living with chronic pain regarding benefits and concerns surrounding their use of cannabis for therapeutic purposes. SETTING: A hospital-based clinic in Hamilton and two community-based interdisciplinary pain clinics in Burlington, Ontario, Canada. METHODS: In this qualitative descriptive study, we conducted semi-structured interviews with 13 people living with chronic pain who used cannabis therapeutically, living in Ontario, Canada. We used thematic analysis, with data collection, coding, and analysis occurring concurrently. RESULTS: People living with chronic pain reported important benefits associated with use of cannabis for therapeutic purposes, including reduced pain, improved functionality, and less risk of harms compared to prescription opioids. Most patients also acknowledged harms, such as grogginess and coughing, and there was considerable variability in patient experiences. Financial costs and stigma were identified as important barriers to use of cannabis. CONCLUSION: Evidence-based guidance that incorporates patients' values and preferences may be helpful to inform the role of cannabis in the management of chronic pain.

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 imitation

Not 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.

metaresearch head score (Codex)0.024
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.306
Threshold uncertainty score0.978

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0240.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.121
GPT teacher head0.417
Teacher spread0.296 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations13
Published2022
Admission routes2
Has abstractyes

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