Seeking Mind, Body and Spirit Healing–-Why Some Men with Prostate Cancer Choose CAM (Complementary and Alternative Medicine) over Conventional Cancer Treatments
Bibliographic record
Abstract
UNLABELLED: Little is known about men with prostate cancer who decline conventional treatment and use only complementary and alternative medicine (CAM). OBJECTIVES: To 1) explore why men decline conventional prostate cancer treatment and use CAM 2) understand the role of holistic healing in their care, and 3) document their recommendations for health care providers. METHODS: Semi-structured interviews and follow-up focus groups. SAMPLE: Twenty-nine men diagnosed with prostate cancer who declined all recommended conventional treatments and used CAM. RESULTS: Based on strong beliefs about healing, study participants took control by researching the risks of delaying or declining conventional treatment while using CAM as a first option. Most perceived conventional treatment to have a negative impact on quality of life. Participants sought healing in a broader mind, body, spirit context, developing individualized CAM approaches consistent with their beliefs about the causes of cancer. Most made significant lifestyle changes to improve their health. Spirituality was central to healing for one-third of the sample. Participants recommended a larger role for integrated cancer care. CONCLUSION: Men who decline conventional prostate cancer treatment and use CAM only may benefit from a whole person approach to care where physicians support them to play an active role in healing while carefully monitoring their disease status.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".