Related Experiment Video
Updated: Feb 10, 2026

Quantified Assessment of Infant's Gross Motor Abilities Using a Multisensor Wearable
Published on: May 17, 2024
The Validity of Two Neuromotor Assessments for Predicting Motor Performance at 12 Months in Preterm Infants
You Hong Song1, Hyun Jung Chang1, Yong Beom Shin2
1Department of Physical Medicine and Rehabilitation, Samsung Changwon Hospital, Sungkyunkwan University School of Medicine, Changwon, Korea.
Insights
General movements (GMs) and the Test of Infant Motor Performance (TIMP) at 3 months corrected age predict motor outcomes in preterm infants. Early neuromotor assessment aids in identifying infants who may benefit from intervention.
Area of Science:
- Neonatal neurology
- Developmental pediatrics
- Motor development research
Background:
- Preterm infants are at higher risk for neuromotor impairments.
- Early identification of motor delays is crucial for timely intervention.
- Predictive validity of early motor assessments in preterm populations requires further investigation.
Purpose of the Study:
- To assess the predictive validity of the Test of Infant Motor Performance (TIMP) and general movements (GMs) assessments.
- To determine their ability to predict Alberta Infant Motor Scale (AIMS) scores at 12 months corrected age in preterm infants.
Main Methods:
- 44 preterm infants were assessed using GMs and TIMP at 1 and 3 months corrected age (CA).
- Motor performance was evaluated using AIMS at 12 months CA.
- GMs and TIMP scores were correlated with AIMS classification.
Main Results:
- TIMP scores at 3 months CA and GMs at 1 and 3 months CA significantly correlated with 12-month motor performance.
- TIMP scores at 1 month CA did not correlate with 12-month AIMS classification.
- In infants with normal GMs at 3 months CA, TIMP scores at 3 months CA showed significant correlation with 12-month AIMS classification.
Conclusions:
- Neuromotor assessments, including GMs and TIMP, are valuable tools for identifying preterm infants.
- These assessments can help identify infants likely to benefit from early intervention strategies.
- Combined use of GMs and TIMP may enhance prediction of motor outcomes in preterm infants.
Objective:
To evaluate the validity of the Test of Infant Motor Performance (TIMP) and general movements (GMs) assessment for predicting Alberta Infant Motor Scale (AIMS) score at 12 months in preterm infants.
Methods:
A total of 44 preterm infants who underwent the GMs and TIMP at 1 month and 3 months of corrected age (CA) and whose motor performance was evaluated using AIMS at 12 months CA were included. GMs were judged as abnormal on basis of poor repertoire or cramped-synchronized movements at 1 month CA and abnormal or absent fidgety movement at 3 months CA. TIMP and AIMS scores were categorized as normal (average and low average and >5th percentile, respectively) or abnormal (below average and far below average or <5th percentile, respectively). Correlations between GMs and TIMP scores at 1 month and 3 months CA and the AIMS classification at 12 months CA were examined.
Results:
The TIMP score at 3 months CA and GMs at 1 month and 3 months CA were significantly correlated with the motor performance at 12 months CA. However, the TIMP score at 1 month CA did not correlate with the AIMS classification at 12 months CA. For infants with normal GMs at 3 months CA, the TIMP score at 3 months CA correlated significantly with the AIMS classification at 12 months CA.
Conclusion:
Our findings suggest that neuromotor assessment using GMs and TIMP could be useful to identify preterm infants who are likely to benefit from intervention.
More Related Videos
08:58Development of a Neonatal Piglet Acute Lung Injury Model Recreating the Early Environment of Preterm Infant Lungs
Published on: October 31, 2025
05:35Experience is Instrumental in Tuning a Link Between Language and Cognition: Evidence from 6- to 7- Month-Old Infants' Object Categorization
Published on: April 19, 2017
Related Concept Videos
Reliability and Validity
Predicting Molecular Geometry
Prediction Intervals
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.
Data Validation
Key parameters for method validation include:
Data Validation
Nursing assessment guides are generally based on holistic models rather than medical...
Drug Dosing: Infants and Children