The perceptions and beliefs of cannabis use among Canadian genitourinary cancer patients
Bibliographic record
Abstract
INTRODUCTION: The legalization of recreational cannabis in Canada in 2018 has led to many patients being curious about the benefits of taking cannabis in conjunction with their cancer treatment. We investigated the perceptions among genitourinary (GU) cancer patients regarding cannabis use as part of their care plans. METHODS: A survey was created to explore current cannabis use behaviors, reasons for cannabis use, and the beliefs of cannabis usefulness towards cancer-related care, including cancer treatment, among GU cancer patients. The survey was distributed across Canada online via RedCAP through social media platforms, email, and patient advocacy groups. The survey was active from August to December 2020. RESULTS: Of eighty-five responses, 52 met inclusion for analysis. Participants included 11 bladder, 26 kidney, and 15 prostate cancer patients. Many (48.1%) participants used cannabis daily and 75% had been using it for more than one year. Cannabis was consumed through oil-based products, edibles, and smoking. The most common reasons for using cannabis were cancer-related anxiety, to prevent cancer progression, cancer-related pain, recreational use, and other, non-cancer-related illness or symptoms. Participants believed cannabis improved their sleep (70.2%), anxiety (65.9%), and overall mood (72.3%). Most participants were either unsure (38.3%) or neutral (31.9%) in the belief that cannabis might decrease their cancer progression. CONCLUSIONS: GU cancer patients use cannabis for a variety of cancer- and non-cancer-related symptoms. Many patients believe cannabis has benefited their cancer-related symptoms. These findings highlight the importance of healthcare providers remaining familiar with current evidence on cannabis to support patient conversations about cannabis use.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".