Integrative Practices of Canadian Oncology Health Professionals
Bibliographic record
Abstract
OBJECTIVE: Cancer patients are increasingly known to use complementary medicine (CAM) during conventional treatment, but data are limited on how Canadian oncology health professionals attempt to assist patients with their use of cam in the context of conventional cancer care. As part of a larger qualitative study assessing the perceptions of Canadian oncology health professionals regarding integrated breast cancer care, we undertook an exploration of current integrative practices of oncology health professionals. DESIGN: Using an interpretive description research design and a purposive sampling, we conducted a series of in-depth qualitative interviews with various oncology health professionals recruited from provincial cancer agencies, hospitals, integrative clinics, and private practice settings in four Canadian cities: Vancouver, Winnipeg, Montreal, and Halifax. A total of 16 oncology health professionals participated, including medical and radiation oncologists, nurses, and pharmacists. RESULTS: Findings highlighted two main strategies used by oncology health professionals to create a more integrative approach for cancer patients: acting as an integrative care guide, and collaborating with other health professionals. CONCLUSIONS: Although few clear standards of practice or guidance material were in place within their organizational settings, health professionals discussed some integrative roles that they had adopted, depending on interest, knowledge, and skills, in supporting patients with cam decisions. Given that cancer patients report that they want to be able to confer with their conventional health professionals, particularly their oncologists, about their cam use, health professionals who elect to adopt integrative practices are likely offering patients much-welcomed support.
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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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.010 | 0.004 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 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".