Systematic review and meta-analyses of nonpharmacological interventions for co-occurring chronic pain and posttraumatic stress disorder
Bibliographic record
Abstract
ABSTRACT: Chronic pain and posttraumatic stress disorder (PTSD) frequently co-occur; however, evidence for effective nonpharmacological treatments is limited, resulting in a guidance gap for clinicians. The aim of this systematic review with meta-analysis was to synthesize and analyze the evidence base for nonpharmacological interventions for chronic pain and posttraumatic stress symptoms. MEDLINE, Embase, PsycINFO, and the PTSD Repository were searched for randomized controlled trials of noninvasive, nonpharmacological interventions in adults with chronic pain, PTSD, or both published from January 1, 1988 to August 31, 2024. Studies reporting assessments of both pain intensity and PTSD symptoms were included, and the primary outcomes were change in pain intensity and PTSD symptom severity. Meta-analyses calculated standardized mean differences (SMDs) in change scores for PTSD symptom severity and pain intensity from pre- to posttreatment. Confidence in the evidence was assessed using Grading of Recommendations, Assessment, Development and Evaluation (GRADE). The study is registered with PROSPERO, CRD42024507881. We identified 30 eligible trials (N = 3245 participants). We found evidence (low quality) that trauma-focused treatments may improve both PTSD symptom severity (a medium effect; SMD -0·75, 95% CI -1·37 to -0·12) and pain intensity (a small effect; SMD -0·34, 95% CI -0·56 to -0·11). We found no significant effects for cognitive-behavioral therapies, mind-body therapies, or peripheral modulation interventions for either outcome. Most studies were methodologically weak. Our findings suggest that treatments targeting chronic pain and PTSD should, at minimum, include a trauma-focused therapy component. However, further research is required to develop effective treatments for co-occurring chronic pain and PTSD.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.033 | 0.089 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.024 | 0.044 |
| Bibliometrics | 0.011 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".