Interactions between analgesic drug therapy and mindfulness-based interventions for chronic pain in adults: protocol for a systematic scoping review
Bibliographic record
Abstract
INTRODUCTION: Most current chronic pain treatment strategies have limitations in effectiveness and tolerability, and accumulating evidence points to the added benefits of rational combinations of different therapies. However, most published clinical trials of treatment combinations have involved combinations of 2 drugs, whereas very little research has been performed to characterize interactions between drug and nondrug interventions. Mindfulness-based interventions (MBIs) have been emerging as a safe and potentially effective treatment option in the management of chronic pain, but it is unclear how MBIs can and should be integrated with various other pain treatment interventions. Thus, we seek to review available clinical trials of MBIs for chronic pain to evaluate available evidence on the interactions between MBIs and various pharmacological treatments. METHODS: A detailed search of trials of MBIs for the treatment of chronic pain in adults will be conducted on the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, EMBASE, and PsycINFO from their inception until the date the searches are run to identify relevant randomized controlled trials. Primary outcomes will include the following: (1) what concomitant analgesic drug therapies (CADTs) were allowed; (2) if and how trials controlled for CADTs and analyzed their interaction; and (3) results of available analyses of interactions between the MBI and CADT. PERSPECTIVE: This review is expected to synthesize available evidence describing the interactions between MBIs and various studied drug therapies for chronic pain. Available evidence may help inform the rational integration of MBIs with drug therapy for chronic pain.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".