Mindfulness-Based Stress Reduction in Breast Cancer Survivors with Chronic Neuropathic Pain: A Randomized Controlled Trial
Bibliographic record
Abstract
Context. Many breast cancer survivors live with chronic neuropathic pain (CNP) after breast cancer treatment. Despite pharmacological management of CNP, many women continue to report disabling pain and reduced quality of life. Addressing pain with psychosocial interventions as an adjunct to pharmacological treatment is often recommended for CNP. Objectives. The purpose of this study was to compare the effects of group-delivered mindfulness-based stress reduction as compared to a waitlist control group among breast cancer survivors living with CNP. Methods. A randomized controlled trial design was applied, and outcomes collected included pain, emotional function, quality of life, and global impression of change. Results. A total of 98 women were randomized and included in analyses. The sample included 49 women in the mindfulness-based stress reduction group, and 49 women in the waitlist control group. The intervention group participants (mean age 51.3 years, standard deviation = 11.4) and waitlist participants (mean age 55.1 years, standard deviation = 9.6) reported an average pain duration of approximately three years. No significant differences were found on the primary outcome of the proportions of women with reduced pain interference scores from the time of randomization to 3 months after the intervention was received. No significant changes were found among secondary outcomes. Conclusion. Our randomized clinical trial did not find significant benefits of group-based mindfulness-based stress reduction for the management of CNP. The current study findings should be replicated and are important to consider given ongoing concerns that nonsignificant results of mindfulness-based stress reduction are often unpublished.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".