Development of the Gross Motor Function Family Report (GMF-FR) for Children with Cerebral Palsy
Bibliographic record
Abstract
Purpose: To describe the initial steps in the development of a family-completed, modified version of the Gross Motor Function Measure (GMFM-88) to report gross motor function of young people with cerebral palsy in their natural environments. Methods: Development of the Gross Motor Function – Family Report (GMF-FR) was based on expert opinion involving 13 experienced clinicians and researchers, in four steps: (1) item identification to target items that reflect functional gross motor performance; (2) item selection; (3) critical analysis of the items; and (4) item and scoring modification. Results: Several modifications to existing items and scoring were made, including wording changes to optimize ease of families’ understanding, the addition of photographs to illustrate all items, changes to the items to enable use of furniture instead of specialized equipment, and modifications to scoring criteria to ensure a focus on functional motor skills. Ultimately, 30 items were selected, and specific testing/scoring instructions were created for each item. Conclusions: GMF-FR is a new family-report tool, based on the GMFM-88. When validated, it can be used as a telehealth outcome measure to capture family-reported functional motor skill performance in home and community environments.
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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 | 0.009 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".