A systematic review of multidisciplinary outcomes in the management of chronic low back pain
Bibliographic record
Abstract
OBJECTIVE: Previous research has provided an inconsistent message as to the effectiveness of multidisciplinary programs to improve employment outcomes in clients with Chronic Low Back Pain (CLBP). The primary aims of this review were to: 1) update the evidence for the multidisciplinary treatment of CLBP to improve employment outcomes 2) assess what knowledge supports occupational therapy as contributing to a multidisciplinary approach in the treatment of CLBP. PARTICIPANTS: Working-age adults experiencing CLBP who took part in controlled trials evaluating multidisciplinary programs between July 1998 and July 2009. METHODS: Updated guidelines provided by the Cochrane Collaboration Back Review Group (BRG) were used to perform a systematic review to identify, appraise, and synthesize research evidence relevant to our research questions. RESULTS: Twelve unique articles were found, after a database search and citation tracking, only two of which were high quality. Our findings suggest that there is still conflicting evidence for the effectiveness of multidisciplinary programs to improve employment outcomes in CLBP. CONCLUSIONS: The results are discussed with reference to current methodological limitations found in the literature. Furthermore, occupational therapists were found to be underutilized in the included studies and future multidisciplinary programs should take advantage of the wide range of skills that occupational therapists can contribute in this practice area.
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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 | 0.012 | 0.057 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.007 |
| Bibliometrics | 0.011 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".