The Effects of the Bali Yoga Program for Breast Cancer Patients on Cancer Related Fatigue: Results of a Randomized Partially Blinded Controlled Trial
Bibliographic record
Abstract
Background: A few complementary and alternative medicine methods have been reported to reduce cancer related fatigue (CRF). The purpose of this study was to evaluate the effects of a yoga intervention in reducing CRF among women receiving chemotherapy. Materials and Methods: This was a randomized partially blinded controlled trial comparing a standardized yoga intervention to standard care. It was conducted at three medical centers in Montreal, Canada. Eligible patients were women diagnosed with stage I–III breast cancer receiving chemotherapy. Participants were randomly assigned to receive the yoga intervention immediately or after a waiting period. The Bali Yoga Program for Breast Cancer patients (BYP-BC) consisted of 24 gentle poses, 2 breathing techniques, relaxation periods, and psychoeducational themes. Participants attended eight weekly sessions lasting 90 minutes and a DVD for home practice with 20- and 40-minute sessions. Participants in the waitlist (WL) control group received standard care. Results: Forty-eight participants were included in the study. The repeated measure analyses revealed no significant increase in general fatigue in the BYP-BC group (P = 0.66) while it significantly worsened in the WL group (P = 0.000). Motivation improved in the BYP-BC group (P = 0.01) and worsened in the WL group (P = 0.01). Conclusions: These preliminary results suggest BYP-BC could be beneficial in preventing worsening of CRF during chemotherapy.
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".