Perspectives of pediatric oncologists and palliative care physicians on the therapeutic use of cannabis in children with cancer
Bibliographic record
Abstract
BACKGROUND: Children with cancer are increasingly using cannabis therapeutically. AIM: The purpose of this study was to determine the perspectives and practices of pediatric oncologists and palliative care physicians regarding the use of cannabis for medical purposes among children with cancer. METHODS: A self-administered, voluntary, cross-sectional, deidentified online survey was sent to all pediatric oncologists and palliative care physicians in Canada between June and August 2020. Survey domains included education, knowledge, and concerns about cannabis, views on its effectiveness, and the importance of cannabis-related research. Data were analyzed using descriptive statistics. RESULTS: In total, 122/259 (47.1%) physicians completed the survey. Although 62.2% of the physicians completed some form of training about medical cannabis, nearly all (95.8%) desired to know more about the dosing, side effects, and safety of cannabis. Physicians identified a potential role of cannabis in the management of nausea and vomiting (85.7%), chronic pain (72.3%), cachexia/poor appetite (67.2%), and anxiety or depression (42.9%). Only four (0.3%) physicians recognized cannabis to be potentially useful as an anticancer agent. Nearly all physicians reported that cannabis-related research for symptom relief is essential (91.5%) in pediatric oncology, whereas 51.7% expressed that future studies are necessary to determine the anticancer effects of cannabis. CONCLUSIONS: Our findings indicate that most pediatric oncologists and palliative care physicians recognize a potential role for cannabis in symptom control in children with cancer. Well-conducted studies are required to create evidence for cannabis use and promote shared decision making with pediatric oncology patients and their caregivers.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".