Prevalence and predictors of return to work following a spinal cord injury using a work disability prevention approach: A systematic review and meta-analysis
Bibliographic record
Abstract
Purpose Worldwide, spinal cord injuries are associated with diminished participation in the labor market. Inconclusive reporting and differences between workplace settings for individuals with spinal cord injury (SCI) make conceptualizing return to work rates among this population inherently challenging. The objectives of this study are to explore factors associated with return to work (RTW) following an SCI. Moreover, the factors were classified according to the work disability prevention framework. Finally, we conducted a meta-analysis of the prevalence of RTW following an SCI. Methods Original articles were identified through a literature search in four health databases. The study followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines for the mapping and identification of records. Included studies contained primary studies that included the nature of the injury, antecedent factors associated with the injury, and study characteristics and RTW outcomes. Exclusion criteria for the studies included if there was no discussion of RTW outcomes, systematic reviews, and meta-analyses. Results A total of 461 full-text articles were assessed for eligibility, and eight studies were included and assessed using the Critical Appraisal Skills Programme checklist, Risk of Bias, and Newcastle–Ottawa Scale. Four studies identified personal system factors, four identified healthcare system factors, two identified compensation system factors, and one identified workplace system factors. Conclusions Attempts to optimize RTW among persons with SCI are inherently difficult due to the diversity of this client population. Findings from the studies included in this systematic review support the utility of interventions for facilitating RTW, such as vocational rehabilitation and workplace accommodations, while simultaneously acknowledging the limitations in identifying specific interventions as facilitatory or inhibitory throughout the process.
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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 | 0.020 | 0.053 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.021 | 0.049 |
| Bibliometrics | 0.013 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".