Efficacy of Mindfulness-Based Cognitive Therapy on Late Post-Treatment Pain in Women Treated for Primary Breast Cancer: A Randomized Controlled Trial
Bibliographic record
Abstract
PURPOSE: To assess the efficacy of mindfulness-based cognitive therapy (MBCT) for late post-treatment pain in women treated for primary breast cancer. METHODS: A randomized wait list-controlled trial was conducted with 129 women treated for breast cancer reporting post-treatment pain (score ≥ 3 on pain intensity or pain burden assessed with 10-point numeric rating scales). Participants were randomly assigned to a manualized 8-week MBCT program or a wait-list control group. Pain was the primary outcome and was assessed with the Short Form McGill Pain Questionnaire 2 (SF-MPQ-2), the Present Pain Intensity subscale (the McGill Pain Questionnaire), and perceived pain intensity and pain burden (numeric rating scales). Secondary outcomes were quality of life (World Health Organization-5 Well-Being Index), psychological distress (the Hospital Depression and Anxiety Scale), and self-reported use of pain medication. All outcome measures were assessed at baseline, postintervention, and 3-month and 6-month follow-up. Treatment effects were evaluated with mixed linear models. RESULTS: Statistically significant time × group interactions were found for pain intensity (d = 0.61; P = .002), the Present Pain Intensity subscale (d = 0.26; P = .026), the SF-MPQ-2 neuropathic pain subscale (d = 0.24; P = .036), and SF-MPQ-2 total scores (d = 0.23; P = .036). Only pain intensity remained statistically significant after correction for multiple comparisons. Statistically significant effects were also observed for quality of life (d = 0.42; P = .028) and nonprescription pain medication use (d = 0.40; P = .038). None of the remaining outcomes reached statistical significance. CONCLUSION: MBCT showed a statistically significant, robust, and durable effect on pain intensity, indicating that MBCT may be an efficacious pain rehabilitation strategy for women treated for breast cancer. In addition, the effect on neuropathic pain, a pain type reported by women treated for breast cancer, further suggests the potential of MBCT but should be considered preliminary.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| 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".