Use of item response theory to develop a return to work measure for acquired brain injury: The employment feasibility checklist
Bibliographic record
Abstract
BACKGROUND: The 2001 Feasibility Evaluation Checklist (FEC) is an assessment of work readiness for individuals with acquired brain injury (ABI). It establishes the integrity of basic safety, productivity, and interpersonal factors in neurorehabilitation and vocational settings. This study represents an effort to further develop the FEC to increase its clinical utility. OBJECTIVE: To redesign the FEC by conducting Item Response Theory (IRT) analyses on the study's results and combining those mathematical calibrations with clinical expert judgement. The result will be a new measure for use in clinical ABI neurorehabilitation and vocational settings: the Employment Feasibility Checklist (EFC). METHODS: Seven participants with ABI were administered a situational assessment on multiple occasions by occupational therapists in a community rehabilitation clinic. The FEC was used to assess the participant's performance across three areas of basic employment feasibility: safety, productivity, and interpersonal factors. Results were analyzed with IRT-Rasch analysis and then subjected to clinical expert judgment, resulting in adjustment recommendations for the FEC. RESULTS: In this scale development study, IRT analysis of results from 89 observation trials was combined with expert clinical judgment resulting in a redesigned tool with increased clinical utility for persons with ABI. The EFC is a 12-item observational rating scale for employment feasibility constructs of Productivity and Interpersonal Relations, with an additional six-item Workplace Safety subsection. CONCLUSION: The EFC is a mathematically calibrated tool designed to gauge feasibility for competitive employment in clients with ABI. The tool may be useful in clinical neurorehabilitation settings and vocational rehabilitation settings.
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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 | 0.061 | 0.136 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".