The Efficacy of Interdisciplinary Rehabilitation for Improving Function in People with Chronic Pain
Bibliographic record
Abstract
Objective. To examine the efficacy of interdisciplinary rehabilitation for improving function in people with chronic pain. Design. Retrospective Chart Review. Setting. The Pain Rehabilitation Center (PRC) at a medical center. Participants. Individuals admitted to the PRC. Interventions. The PRC operates a 3-week outpatient program that utilizes an interdisciplinary approach to treat people with chronic pain. The main treatment elements include physical therapy, occupational therapy, cognitive behavioral therapy (CBT), and medication management. Physical therapy groups focus on moderate exercise despite symptoms. Occupational therapists teach moderation, time management, and activity modification. CBT groups, led by a pain psychologist, address the psychosocial comorbidities of chronic pain. Medical staff oversee the tapering of opiate analgesics and other symptom targeted treatments. This integrated approach is indicated when conventional treatments have been ineffective. Outcome Measures. The objective outcome was the 6-minute walk test (6 mWT) distance. The subjective outcomes were performance (COPM-PER) and satisfaction (COPM-SAT) as measured by the Canadian Occupational Performance Measure (COPM). Results. Average 6 mWT distances improved by 39% from 375 m to 523 m. Average COPM-PER scores increased from 3.4 to 7.5. Average COPM-SAT scores increased from 2.4 to 7.5. Conclusions. Comprehensive interdisciplinary outpatient rehabilitation can significantly improve function in people with chronic pain.
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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 | 0.005 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".