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Related Experiment Video

Updated: Jan 3, 2026

Measurements of Motor Function and Other Clinical Outcome Parameters in Ambulant Children with Duchenne Muscular Dystrophy

Measurements of Motor Function and Other Clinical Outcome Parameters in Ambulant Children with Duchenne Muscular Dystrophy

Published on: January 12, 2019

High-Level Mobility Assessment Tool Normative Values for Children.

Beverly J Eldridge¹, Mary P Galea², Anne L Kissane³

¹Department of Allied Health, La Trobe University, Level 4, The Alfred Centre, Melbourne, Victoria, Australia.

Physical Therapy

|November 20, 2019

Summary

This summary is machine-generated.

The High-Level Mobility Assessment Tool (HiMAT) shows scores increase with age, height, weight, and BMI in Australian children. Age is the best predictor for developing normative HiMAT scores for primary schoolers.

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Last Updated: Jan 3, 2026

Measurements of Motor Function and Other Clinical Outcome Parameters in Ambulant Children with Duchenne Muscular Dystrophy

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Published on: January 12, 2019

An Objective and Child-friendly Assessment of Arm Function by Using a 3-D Sensor

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Published on: February 12, 2018

Measuring the Functional Abilities of Children Aged 3-6 Years Old with Observational Methods and Computer Tools

Measuring the Functional Abilities of Children Aged 3-6 Years Old with Observational Methods and Computer Tools

Published on: June 20, 2020

Area of Science:

Pediatric physical therapy
Gross motor skill assessment
Childhood mobility evaluation

Background:

Physical therapists require tools to assess high-level gross motor skills in children.
The High-Level Mobility Assessment Tool (HiMAT) demonstrates strong reliability and is less prone to ceiling effects in children aged 6-17 with traumatic brain injury.

Purpose of the Study:

To establish normative HiMAT score ranges for Australian children.
To examine the correlation between HiMAT scores and children's age, height, weight, and BMI.

Main Methods:

Cross-sectional study design involving 1091 Australian children aged 5-12.
Data collection included height, weight, and HiMAT scores at local schools.
Statistical analysis utilized Spearman correlations and truncated regression models.

Main Results:

A positive correlation was observed between HiMAT scores and age, height, weight, and BMI.
Childhood age was identified as the primary factor explaining variability in HiMAT scores for both sexes.

Conclusions:

HiMAT scores in children correlate positively with age, height, weight, and BMI.
Age is the most suitable predictor for creating normative HiMAT score datasets for primary school-aged children.