Work capacity assessment and return to work: A scoping review
Bibliographic record
Abstract
OBJECTIVE: This review sought to synthesize existing evidence on work capacity assessments and to identify the knowledge supporting their use in return to work practice and future research. METHODS: A scoping review was conducted identifying studies examining assessments used in return to work. Studies published before 1986 and studies not written in English were excluded. A five point relevancy criteria was used to establish the fit of articles with the research question. Articles were thematically analyzed into components of the PEO Model, proposed future research, and areas of vested interest. RESULTS: Forty four articles met the criteria for inclusion. For over twenty five years, work capacity assessment literature has remained focused on the individual's physical work performance capacities. Gaps were identified in the lack of qualitative research and incorporation of person, occupation, and environmental dimensions in evaluation of work capacity. Future research recommendations emphasize the need for knowledge generation on work modification and investigation of psychosocial factors that impact work capacity and return to work yet only minimal progression is evident in these areas in the literature reviewed. CONCLUSION: The limited consideration of the occupation and environmental dimensions in returning to work and the global interest in work capacity assessment highlight the need for the development of contextually based assessment tools. Assessment needs to move toward the incorporation of environmental and occupational aspects in addition to the person dimension in a culturally transcendent manner.
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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 | 0.009 | 0.041 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.019 | 0.018 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".