Mindfulness-based stress reduction (MBSR) as sole intervention for non-somatisation chronic non-cancer pain (CNCP): protocol for a systematic review and meta-analysis of randomised controlled trials
Bibliographic record
Abstract
INTRODUCTION: Chronic non-cancer pain (CNCP) affects up to 50% of the world's population. It impacts negatively on quality of life; entailing high costs on our medical systems, and translates to economic burden due to work loss. Aetiology of CNCP is complex and multifactorial, embracing the somatosensory, cognitive and affective domains. Opioid analgesia and other invasive interventions are often inadequate for clinical management of CNCP. Recently, mindfulness-based stress reduction (MBSR) has become a popular therapy for various medical conditions, including CNCP. However, studies reported varying efficacies, and relevant systematic reviews have included clinical trials with inherent heterogeneity either in study conditions or types of interventions used. Our study aims to provide an updated and more critical evaluation of the efficacy of MBSR as the intervention for non-somatisation CNCP. METHODS AND ANALYSIS: A systematic review with meta-analysis of randomised controlled trials published in English will be performed in accordance with the Preferred Reporting Items for Systematic reviews and Meta-analyses (PRISMA) guidelines and the Cochrane Collaboration format. MEDLINE, EMBASE, PsychINFO, and the Cochrane Central Register of Controlled Trials Intervention, will be searched independently by reviewers using defined MeSH terms. Studies with full texts using MBSR as the main intervention on patients with non-somatising CNCP will be included. Outcome measures include pain scores and disability assessment scales. Continuous data will be meta-analysed using the RevMan 5 Review Manager programme. Primary analysis will adopt the random effects model in view of heterogeneity between trials. The standardised mean difference will be expressed as the effect size with 95% CIs. Forest plots, funnel plots, the I(2) statistic and the Cochrane Risks of Bias Assessment table will be included. ETHICS AND DISSEMINATION: No ethics approval is deemed necessary. Results of this study will be disseminated via peer-reviewed publications and scientific meetings. TRIALS REGISTRATION NUMBER: PROSPERO CRD42014015568.
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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 | 0.065 | 0.080 |
| Meta-epidemiology (narrow) | 0.009 | 0.006 |
| Meta-epidemiology (broad) | 0.029 | 0.031 |
| Bibliometrics | 0.011 | 0.011 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.006 | 0.005 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.054 | 0.007 |
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".