Comparative evaluation of group-based mindfulness-based stress reduction and cognitive behavioral therapy for the treatment and management of chronic pain disorders: protocol for a systematic review and meta-analysis with indirect comparisons
Bibliographic record
Abstract
BACKGROUND: Chronic pain disorders impact the physical, psychological, social, and financial well-being of between 10%-30% of Canadians. The primary aims of psychological interventions targeting chronic pain disorders are to reduce patients' pain-related disability and to improve their quality of life. Cognitive behavioral therapy (CBT) is the prevailing treatment for chronic pain, however mindfulness-based stress reduction (MBSR) has displayed promise as an alternative treatment option. The objective of this systematic review and meta-analysis is to compare MBSR to CBT in their relative ability to reduce pain-related disability and intensity, to alleviate emotional distress, and to improve global functioning in chronic pain patients. METHODS/DESIGN: We will conduct a systematic review with meta-analyses to compare MBSR to CBT in the treatment of chronic pain disorders in adults. We will report our review according to the recommendations provided by the PRISMA statement. Randomized studies will be included and the literature search will comprise Ovid MEDLINE®, Ovid MEDLINE® In-Process & Other Non-Indexed Citations, Embase Classic+Embase, PsycINFO, the Cochrane Library on Wiley, including CENTRAL, Cochrane Database of Systematic Reviews, DARE, and HTA. Study selection and data extraction will be conducted by independent investigators and in duplicate. Outcomes of interest will include pain interference, pain intensity, emotional functioning, and patient global impression of change. The Cochrane risk of bias tool will be used to assess risk of bias of included studies. As we anticipate that scales used to measure participant responses will be related but varied from study to study, standardized mean differences will be used to compare effect sizes between treatment modalities. Given the possibility of little or no head-to-head evidence comparing MBSR with CBT, we will use indirect treatment comparison methodology to assess the relative effectiveness of these interventions. DISCUSSION: The findings from this study will assist patients and treatment providers to make informed decisions regarding evidence-based treatment selection for chronic pain disorders. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42014009356.
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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 | 0.055 | 0.068 |
| Meta-epidemiology (narrow) | 0.007 | 0.004 |
| Meta-epidemiology (broad) | 0.029 | 0.042 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.034 | 0.003 |
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".