Efficacy of Multimodal Psychological Interventions on Pain After Surgery in Breast Cancer Survivors: A Systematic Review
Bibliographic record
Abstract
INTRODUCTION: Postsurgical pain is common among people who undergo breast cancer (BC) surgery and affects health-related quality of life. The aim of this systematic review was to determine the efficacy of multimodal psychologic interventions to reduce pain after BC surgery. METHODS: Nine bibliographic databases and three trial registries were searched from their inception to September 2024. Studies were included if they reported pain outcomes of multimodal psychologic interventions performed after BC surgery. This systematic review was prospectively registered on PROSPERO (CRD42024506835) and followed Preferred Reporting Items for Systematic Reviews and Meta-Analyses and synthesis without meta-analysis guidelines. RESULTS: A total of 2,876 studies were screened, with 18 meeting inclusion criteria including 10 randomized control trials (55.6%). There was a total of 1,712 patients (median sample size was 77). The greatest proportion of studies were conducted in the United States (n = 7, 38.9%). Mindfulness-based stress reduction (MBSR) was the most investigated intervention (4/18, 22.2%), followed by yoga (3/18, 16.7%). The most used pain questionnaires were the Brief Pain Inventory and European Organisation of Research and Treatment of Cancer Quality of Life Questionnaire C30 (5/18, 27.8%). Mindfulness-based cognitive therapy (n = 1), relaxation modification (n = 1), progressive muscular relaxation combined with visualization (n = 1), Qigong mind-body exercise (n = 1), pranic meditation (n = 1), supportive-expressive group therapy (n = 1), diaphragmatic breathing with progressive muscle relaxation (n = 1), and integrated yoga programs (n = 3) demonstrated a significant reduction in pain. CONCLUSION: These findings indicate the potential for multimodal psychologic interventions to reduce pain after BC surgery. However, MBSR was not significantly effective in pain reduction for BC survivors despite being the most frequently investigated intervention. Further randomized controlled trials are necessary to offer conclusive recommendations.
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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 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.008 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".