Biopsychosocial predictors of prognosis in musculoskeletal disorders: a systematic review of the literature (corrected and republished)
Bibliographic record
Abstract
Purpose: To review the prognostic factors of musculoskeletal disorders while adopting a multidimensional perspective and including studies on various pertinent outcomes to the adjustment process. We also aimed to highlight the overall and phase-specific evidence. Method: We searched the Psychinfo and Ovid Medline(R) databases as well as pertinent periodicals and reviews and retained prospective studies of subjects suffering from specific or non-specific musculoskeletal pain that adopted multivariate statistical analysis. Results: We selected 105 studies, of which 68 included biopsychosocial and sociodemographic variables. For those studies using a biopsychosocial framework, we determined the level of evidence for every prognostic factor with each outcome. Strong evidence was found for recovery expectations and disability management with work participation outcomes. With disability outcomes, strong evidence was also found for recovery expectations, coping and somatization. Comorbidity and duration of episode strongly predicted pain outcomes. Some differences coinciding with phases of chronicity were also identified. Conclusion: Although uncertainty remains about the role of many prognostic factors, we found strong evidence to support the predictive value of clinically significant variables. There is, however, a need for additional research and replication, adopting more homogenous models and measurement methods.Implications for RehabilitationDespite numerous studies, it remains difficult to identify a clear set of prognostic factors in musculoskeletal disorders.Outcomes in musculoskeletal disorders are determined by biopsychosocial prognostic variables although psychosocial factors appear predominant, as early as in the acute phase.There appears to be negligible differences between prognostic factors in acute, subacute and chronic phases and a biopsychosocial approach should be considered from the acute phase in rehabilitation practice.Outcomes in rehabilitation practice should also be evaluated from a biopsychosocial perspective.
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How this classification was reachedexpand
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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".