Comparative evaluation of group-based mindfulness-based stress reduction and cognitive behavioural therapy for the treatment and management of chronic pain: A systematic review and network meta-analysis
Bibliographic record
Abstract
QUESTION: This review compares mindfulness-based stress reduction (MBSR) to cognitive-behavioural therapy (CBT) in its ability to improve physical functioning and reduce pain intensity and distress in patients with chronic pain (CP), when evaluated against control conditions. STUDY SELECTION AND ANALYSIS: Ovid MEDLINE, EmbaseClassic+Embase, PsycINFO and the Cochrane Library were searched to identify randomised controlled trials. The primary outcome measure was physical functioning. Secondary outcomes were pain intensity and depression symptoms. We used random and fixed effects (RE and FE) network meta-analyses (NMA) to compare MBSR, CBT and control interventions on the standardised mean difference scale. FINDINGS: Twenty-one studies were included: 13 CBT vs control (n=1095), 7 MBSR vs control (n=545) and 1 MBSR vs CBT vs control (n=341). Of the 21 articles, 12 were determined to be of fair or good quality. Findings from RE NMA for change in physical functioning, pain intensity and depression revealed clinically important advantages relative to control for MBSR and CBT, but no evidence of an important difference between MBSR and CBT was found. CONCLUSIONS: This review suggests that MBSR offers another potentially helpful intervention for CP management. Additional research using consistent measures is required to guide decisions about providing CBT or MBSR.
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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 | 0.019 | 0.045 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.019 | 0.028 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".