Measurement properties of the Gross Motor Function Classification System, Gross Motor Function Classification System‐Expanded & Revised, Manual Ability Classification System, and Communication Function Classification System in cerebral palsy: a systematic review with meta‐analysis
Bibliographic record
Abstract
AIM: To systematically review and meta-analyse the measurement properties of the Gross Motor Function Classification System (GMFCS), Gross Motor Function Classification System-Expanded & Revised (GMFCS-E&R), Manual Ability Classification System (MACS), and Communication Function Classification System (CFCS) in children with cerebral palsy (CP). METHOD: Six databases were searched. Articles on the measurement properties of the GMFCS, GMFCS-E&R, MACS, and CFCS administered to children with CP were included. Quality was assessed by means of the COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) Risk of Bias checklist. The level and grading of evidence were defined for each measurement property. RESULTS: Forty-four articles were included in the systematic review and 37 articles were included in the meta-analysis. The level (grading) of evidence was strong (positive) for reliability and construct validity. Content validity displayed an unknown level of evidence for the GMFCS, limited evidence (positive) for the MACS, and moderate evidence (positive) for the CFCS. There was moderate (positive) evidence for measurement error in the GMFCS and MACS. The level of evidence for responsiveness was unknown. No studies investigated cross-cultural validity. INTERPRETATION: These instruments can be used by health care professionals and caregivers to quantify the constructs needed to measure ability in children with CP. Current high-quality evidence supports the use of these tools to classify ability in children with CP. Adopting the COSMIN guidelines, content, and cross-cultural validity should be investigated further. What this paper adds Strong evidence supports the reliability and construct validity of the GMFCS, GMFCS-E&R, MACS, and CFCS as functional classification systems in children with cerebral palsy. The GMFCS, GMFCS-E&R, MACS, and CFCS can be used by both health care professionals and caregivers. The GMFCS, GMFCS-E&R, MACS, and CFCS should not be used to detect change.
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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 | 0.029 | 0.082 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.021 | 0.032 |
| Bibliometrics | 0.008 | 0.010 |
| 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) | 0.003 | 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".