Population-based age standards for interpreting results on the test of motor infant performance

Pediatr Phys Ther. 2006 Summer;18(2):119-25. doi: 10.1097/01.pep.0000223108.03305.5d.


Purpose: The goals of this study were establishment of age standards for the Test of Infant Motor Performance (TIMP) and evaluation of possible group differences based on sex, medical risk for poor developmental outcome, and race/ethnicity.

Subjects: Subjects were 990 infants with a range of risk for poor outcome from 11 geographic locations across the United States that were recruited to reflect the distribution of race/ethnicity in the US population of low birth weight infants.

Methods: Between 67 and 97 infants were tested in each two-week age range from 34-35 weeks' postconceptional age through 16-17 weeks after term. Boys made up 52% of the subjects. Fifty-eight percent of the sample was white, 25% black, and the remainder were of other ethnicities. Scores for all infants in each age group were averaged to form age expectations for each two-week period. Multiple regression was used to explore the effect on TIMP scores of sex, risk, and race/ethnicity.

Results: Means ranged from 49 (standard deviation = 15) at 34-35 weeks' postconceptional age through 120 (standard deviation = 16) at 16-17 weeks after term. High-risk infants scored significantly lower than other infants (beta = -0.133, P < 0.0001). Latino infants scored lower than infants of all other ethnicities (beta = -0.052, p < 0.006). Performance did not differ by sex. CONCLUSIONS/CLINICAL IMPLICATIONS: These standards for performance on the TIMP can be used to identify infants with delayed motor development.

Publication types

  • Comparative Study
  • Multicenter Study

MeSH terms

  • Age Distribution
  • Age Factors
  • Data Interpretation, Statistical
  • Diagnosis, Differential
  • Female
  • Humans
  • Infant
  • Infant, Low Birth Weight / physiology*
  • Infant, Newborn
  • Male
  • Motor Skills / physiology*
  • Movement Disorders / diagnosis*
  • Movement Disorders / epidemiology
  • Population Surveillance*
  • Regression Analysis
  • United States / epidemiology