Validity and Reliability of Two Abbreviated Versions of the Gross Motor Function Measure
Bibliographic record
Abstract
BACKGROUND: The "gold standard" for measuring gross motor function in children with cerebral palsy is the 66-item Gross Motor Function Measure (GMFM-66). OBJECTIVE: The purpose of this study was to estimate the validity and reliability of 2 abbreviated versions of the GMFM-66; one version involves an item set approach, and the other version involves a basal and ceiling approach. DESIGN: This was a measurement study comprising concurrent validity, comparability, and test-retest reliability components. METHODS: The study participants were 26 children who were 2 to 6 years of age and had cerebral palsy across all Gross Motor Function Classification System levels. In the first session, both abbreviated versions were administered by 2 independent raters; next, the full GMFM-66 was administered. In the second session, only the abbreviated versions were administered by the same raters. Concurrent validity, comparability of versions, and test-retest reliability were determined with intraclass correlation coefficients [ICC (2,1)]. RESULTS: Both versions demonstrated high levels of validity, with an ICC of .99 (95% confidence interval=0.972-0.997), reflecting associations with the GMFM-66. Both versions also were shown to be highly reliable, with ICCs of greater than .98 (95% confidence interval=0.965-0.994). LIMITATIONS: A smaller-than-expected sample was recruited for this study and may be a potential limitation of the study. CONCLUSION: Both versions of the GMFM-66 can be used in clinical practice or research. However, the GMFM-66 with the basal and ceiling approach is recommended as the preferred abbreviated version.
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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 | 0.014 | 0.049 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".