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Updated: Sep 26, 2026
Quantified Assessment of Infant's Gross Motor Abilities Using a Multisensor Wearable
Published on: May 17, 2024
Rasch analysis of the Gross Motor Function Measure: validating the assumptions of the Rasch model to create an
Lisa M Avery1, Dianne J Russell, Parminder S Raina
1CanChild Centre for Childhood Disability Research, Institute for Applied Health Sciences, McMaster University, Hamilton, ON, Canada.
Objectives:
To describe the Rasch analysis of the Gross Motor Function Measure (GMFM-88) and to demonstrate how the assumptions of unidimensionality, sample-free measurement, and test-free measurement were validated to create an interval level measure.
Design:
Cross-sectional and longitudinal (12-mo) data from a prospective study of motor development in children with cerebral palsy (CP) were used for the analysis.
Setting:
Motor assessments were completed at 18 children's ambulatory rehabilitation centers in Ontario, Canada, by pediatric physical therapists trained in the use of the GMFM-88.
Participants:
The first 537 of 682 children enrolled into a longitudinal study of motor development in children with CP. Children had a mean age of 6.43+/-2.75 years (range, 11mo-12y) with varying types and severity of CP.
Interventions:
Not applicable.
Main Outcome Measure:
The GMFM-88.
Results:
The Rasch analysis, in conjunction with clinical decisions, identified 66 items from the GMFM-88 that formed a unidimensional measure (GMFM-66). Assumptions of sample-free and test-free measurement were confirmed, and a user-friendly scoring program was developed.
Conclusions:
The GMFM-66 is an interval-level measure of gross motor function for children with CP; it should improve the scoring, interpretation, and overall clinical and research utility over the original GMFM.
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