Psychometric testing of a French Canadian version of the MacHAND performance assessment short (MPA-SF) for the adult burn survivor population
Bibliographic record
Abstract
Hand burns represent a frequent injury site, often leading to significant functional limitations. However, there is no systematically validated performance-based outcome (PerfO) assessment for burn survivors, making it difficult to plan, implement, and monitor interventions for hand function. The MacHAND performance assessment short (MPA-S) has recently been proposed as a quick, updated, and globally accessible tool for individuals with traumatic hand injuries and could be a suitable PerfO for hand burns, meriting evaluation. This study aimed to 1) translate the MPA-S and Sollerman Hand Function Test (SHFT) into French Canadian (MPA-SF and SHFT-F), and 2) evaluate the psychometric properties of the MPA-SF, including test-retest, inter-rater, and intra-rater reliability, as well as minimal detectable change with 95 % confidence (MDC95 %) and construct validity by examining its correlation with the French Canadian Burnt Hand Outcome Tool (BHOT-F) and SHFT-F. The secondary objective was to explore the relationship between the MPA-SF, SHFT-F, and BHOT-F scores with % total body surface area (TBSA) burned, presence of hand graft, and hand diagnoses. The translation process followed a standardized forwards-backwards method. Psychometric testing was conducted with 31 participants who sustained hand burns (50 hands). The MPA-SF exhibited excellent reliability and strong positive correlations with the SHFT-F; and weak to moderate negative correlations with the BHOT-F. The intra-rater MDC95 % was 0, and the inter-rater MDC95 % was 4.35 %. These findings suggest that the MPA-SF is a reliable tool for assessing hand function after burns, supporting its use in clinical practice and research. All instruction manuals and training videos are open-source.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".