Psychometric Properties of the Wolf Motor Function Test (WMFT) and Its Modified Versions: A Systematic Review With Meta-Analysis
Bibliographic record
Abstract
Background The Wolf Motor Function Test (WMFT) and its modified versions are widely used to assess upper limb (UL) function in stroke survivors. However, comprehensive evaluations of its psychometric properties are lacking. Objective To perform a systematic review with meta-analysis on the psychometric properties (following the COnsensus-based Standards for the selection of health Measurement INstruments [COSMIN] taxonomy) of the WMFT and modified versions in stroke survivors. Methods Six databases were searched until May 2024 for studies examining at least one WMFT measurement property in stroke patients. Two independent reviewers conducted study selection, data extraction, and quality assessment using the COSMIN Risk of Bias checklist and quality of evidence (QoE) with the Grading of Recommendations Assessment, Development, and Evaluation approach. Meta-analyses synthesized psychometric properties reported in at least two studies. Results Twenty-five studies (N = 2044) were included. Regarding the WMFT Functional Ability Scale (FAS) and TIME scales, internal consistency (alpha ≥ .88), intra-rater (intraclass correlation coefficient [ICC] ≥ .97) and inter-rater (ICC ≥ .92) reliability, measurement error for TIME, construct validity (strong correlations [ r ≥| .64|] with Fugl-Meyer Assessment and Action Research Arm Test), and responsiveness (ES ≥ 0.48) were rated sufficiently with QoE from very low to high. Measurement error for FAS was assessed as inconsistent with moderate QoE, and cross-cultural validity was rated as indeterminate with very low QoE. Content validity was not assessed. Few studies investigated the psychometric properties of the modified versions. Conclusions WMFT demonstrates robust psychometric properties in assessing UL function in stroke survivors. While the WMFT-modified versions showed promising properties, further research is needed to use them. Future studies should focus on WMFT measurement error, content, and cross-cultural validity. Trial Review Registration: PROSPERO: CRD42021237425.
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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 | 0.032 | 0.089 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.021 | 0.039 |
| Bibliometrics | 0.010 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".