An Interdisciplinary Pain Rehabilitation Programme: Description and Evaluation of Outcomes
Bibliographic record
Abstract
PURPOSE: The purpose of this archival report is to describe the essential elements of an intensive 8-week interdisciplinary pain rehabilitation programme (IPRP) with a cognitive-behavioural emphasis and the results that can be expected in treating patients with chronic pain conditions. METHOD: This report describes a private outpatient program providing treatment services to patients with long-term disabling pain arising from work- or accident-related musculoskeletal injuries. The cohort consists of 338 consecutive patients who completed the program over a 3-year period (patients discharged between January 1, 2005, and December 31, 2007). RESULTS: Improvements in vocational status were noted in 75% of patients with chronic pain. Patients were also able to reduce their pain levels by approximately 16% and to reduce their levels of anxiety and depression by 13% and 17% respectively. At the same time, 61% of patients were able to reduce or eliminate their pain medications. CONCLUSIONS: Outcomes are consistent with evidence-based clinical practice guidelines for the management of chronic pain conditions. The published literature supports the efficacy of this interdisciplinary approach in highly disabled patients for whom effective treatment has been delayed. Early intervention in the subacute phase is recommended for prevention of long-term disability in patients 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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".