Mindfulness-Based Stress Reduction for Breast Cancer—A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
OBJECTIVE: The aim of this systematic review and meta-analysis was to assess the effectiveness of mindfulness-based stress reduction (mbsr) and mindfulness-based cognitive therapy (mbct) in patients with breast cancer. METHODS: The medline, Cochrane Library, embase, cambase, and PsycInfo databases were screened through November 2011. The search strategy combined keywords for mbsr and mbct with keywords for breast cancer. Randomized controlled trials (rcts) comparing mbsr or mbct with control conditions in patients with breast cancer were included. Two authors independently used the Cochrane risk of bias tool to assess risk of bias in the selected studies. Study characteristics and outcomes were extracted by two authors independently. Primary outcome measures were health-related quality of life and psychological health. If at least two studies assessing an outcome were available, standardized mean differences (smds) and 95% confidence intervals (cis) were calculated for that outcome. As a measure of heterogeneity, I(2) was calculated. RESULTS: Three rcts with a total of 327 subjects were included. One rct compared mbsr with usual care, one rct compared mbsr with free-choice stress management, and a three-arm rct compared mbsr with usual care and with nutrition education. Compared with usual care, mbsr was superior in decreasing depression (smd: -0.37; 95% ci: -0.65 to -0.08; p = 0.01; I(2) = 0%) and anxiety (smd: -0.51; 95% ci: -0.80 to -0.21; p = 0.0009; I(2) = 0%), but not in increasing spirituality (smd: 0.27; 95% ci: -0.37 to 0.91; p = 0.41; I(2) = 79%). CONCLUSIONS: There is some evidence for the effectiveness of mbsr in improving psychological health in breast cancer patients, but more rcts are needed to underpin those results.
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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 | 0.014 | 0.030 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.035 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".