The MacHAND performance assessment (MPA): Development and psychometric testing of the short English version (MPA-S) for the traumatic hand injury population
Bibliographic record
Abstract
BACKGROUND: Hand injuries are the most common work-related injuries in Canada, causing significant functional limitations, occupational performance issues, and delaying return to work. Standardized hand function measures are essential for guiding interventions, clinical decisions, and cost-effective care. However, few assessments have been developed for traumatic hand injuries, with even fewer being performance-based outcome (PerfOs) assessments. The MacHAND performance assessment (MPA) is a PerfO developed to evaluate hand function in the traumatic hand injury population. PURPOSE: To revise the MPA instructions and scoring manual (MPA 2.0), produce a shortened version (MPA-S), and evaluate its psychometric properties in adults with traumatic hand injuries. STUDY DESIGN: Mixed method. METHODS: The original MPA instruction's and scoring manual was revised to ensure language consistency, update pictures, and provide identical 3D-printed versions where appropriate (MPA 2.0). To produce the MPA-S, a combined statistical and Delphi approach with rehabilitation experts was used. An existing dataset from the original MPA was then used to determine MPA-S internal consistency, test-retest, and inter-rater reliability for the traumatic hand injury population and agreement with the MPA. Evidence-based dissemination strategies were used to promote clinical and research adoption. RESULTS: For the MPA-S, 10 items were retained for dominant and eight items for nondominant hand testing. The MPA-S showed good internal consistency (Cronbach's alpha and 95% CI: dominant hand: 0.85 [0.78, 0.90], nondominant hand: 0.88 [0.79, 0.92]), excellent test-retest reliability (r = 0.97, 95% CI [0.85, 1]), and inter-rater reliability (ICC 0.98, 95% CI [0.97, 0.99]), and the mixed-effects limits of agreement plots show good agreement with the MPA. CONCLUSIONS: The MPA-S is one of the quickest task-based PerfOs to administer, uses many 3D-printed components, and everyday objects, making it highly accessible and affordable. We believe the MPA 2.0, the creation of the MPA-S, and targeted dissemination strategies will increase clinical and research uptake.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".