Biopsychosocial Approaches to the Treatment of Chronic Pain
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Biopsychosocial treatments address the range of physical, psychological, and social components of chronic pain. OBJECTIVE: This review sought to determine how effective unimodal and multimodal biopsychosocial approaches are in the treatment of chronic pain. METHODOLOGY: The literature search identified three systematic reviews of the literature and 21 randomized controlled trials to provide the evidence for this review. RESULTS: The systematic reviews and 12 randomized controlled trials reported on chronic low back pain. Other randomized controlled trials studied fibromyalgia (three trials) and back or other musculoskeletal disorders (five trials). Biopsychosocial components reviewed were electromyogram feedback and hypnosis as unimodal approaches, and behavioral and cognitive-behavioral treatments and back school, or group education, as multimodal approaches for chronic low back pain. For other chronic pain disorders, cognitive-behavioral treatments were reviewed. Comparisons were hindered by studies with heterogeneous subjects, varied comparison groups, different cointerventions and follow-up times, variable outcomes, and a range of analytic methods. CONCLUSIONS: Multimodal biopsychosocial treatments that include cognitive-behavioral and/or behavioral components are effective for chronic low back pain and other musculoskeletal pain for up to 12 months (level 2). There is limited evidence (level 3) that electromyogram feedback is effective for chronic low back pain for up to 3 months. The remaining evidence of longer-term effectiveness and of effectiveness of other interventions was inadequate (level 4a) or contradictory (level 4b). Future studies of cognitive-behavioral treatments should be condition specific, rather than include patients with different pain conditions.
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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 | 0.014 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it