Oncologists' and Naturopaths' Nutrition Beliefs and Practices
Bibliographic record
Abstract
PURPOSE: Despite the widespread use of complementary and alternative therapies by persons with cancer, little is known about how the understandings of complementary and alternative practitioners of these therapies compare with those of conventional physicians. The broad purpose of this research was, thus, to explore the beliefs of physicians and complementary and alternative health practitioners, their use of scientific and other types of evidence, and their counseling practices. The specific issue addressed was the beliefs and practices of oncologists and naturopaths regarding the role of diet in breast cancer prevention and treatment. DESCRIPTION OF STUDY: A qualitative research design was used, involving in-depth semistructured interviews with 10 oncologists and 11 naturopaths. Interviews were tape-recorded, transcribed verbatim, and analyzed using qualitative methods. RESULTS: The oncologists believed that there is little evidence of a role for diet in breast cancer prevention and treatment, citing the lack of evidence from randomized controlled trials. They reported that they provide only general advice on healthy eating to patients. The naturopaths believed that diet is strongly implicated in breast cancer development, prevention, and treatment. They justified this belief by using scientific evidence from a variety of types of studies, logic or common sense, and their clinical experiences. Naturopaths reported that they provide patients with specific suggestions for foods to avoid or to emphasize in diets. CLINICAL IMPLICATIONS: The differences in the advice provided by oncologists and naturopaths are associated with different decision-making or knowledge construction systems. Educating patients about these differences will help patients to make more informed healthcare choices.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".