Recovery expectations can be assessed with single-item measures: findings of a systematic review and meta-analysis on the role of recovery expectations on return-to-work outcomes after musculoskeletal pain conditions
Bibliographic record
Abstract
ABSTRACT: The objective of this systematic review is to quantify the association between recovery expectations and return-to-work outcomes in adults with musculoskeletal pain conditions. In addition, this review has the second objective to compare the predictive utility of single-item and multi-item recovery expectation scales on return-to-work outcomes. Relevant articles were selected from Embase, PsycINFO, PubMed, Cochrane, and manual searches. Studies that assessed recovery expectations as predictors of return-to-work outcomes in adults with musculoskeletal pain conditions were eligible. Data were extracted on study characteristics, recovery expectations, return-to-work outcomes, and the quantitative association between recovery expectations and return-to-work outcomes. Risk of bias was assessed using the Effective Public Health Practice Project. Odds ratios were pooled to examine the effects of recovery expectations on return-to-work outcomes. Chi-square analyses compared the predictive utility of single-item and multi-item recovery expectation scales on return-to-work outcomes. Thirty studies on a total of 28,741 individuals with musculoskeletal pain conditions were included in this review. The odds of being work disabled at follow-up were twice as high in individuals with low recovery expectations (OR = 2.06 [95% CI 1.20-2.92] P < 0.001). Analyses also revealed no significant differences in the predictive value of validated and nonvalidated single-item measures of recovery expectations on work disability (χ 2 = 1.68, P = 0.19). There is strong evidence that recovery expectations are associated with return-to-work outcomes. The results suggest that single-item measures of recovery expectations can validly be used to predict return-to-work outcomes in individuals with musculoskeletal pain conditions.
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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 | 0.007 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.001 | 0.003 |
| 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) | 0.001 | 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 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".