Quality of Life Research

, Volume 18, Issue 3, pp 359–370

Measuring global physical health in children with cerebral palsy: illustration of a multidimensional bi-factor model and computerized adaptive testing

Authors

    • Health and Disability Research InstituteBoston University School of Public Health
  • Pengsheng Ni
    • Health and Disability Research InstituteBoston University School of Public Health
  • Helene M. Dumas
    • Research Center for Children with Special Health Care NeedsFranciscan Hospital for Children
  • Maria A. Fragala-Pinkham
    • Research Center for Children with Special Health Care NeedsFranciscan Hospital for Children
  • Ronald K. Hambleton
    • Department of Educational Policy, Research and Administration, Center for Educational AssessmentUniversity of Massachusetts
  • Kathleen Montpetit
    • Department of Occupational TherapyShriners Hospital for Children
  • Nathalie Bilodeau
    • Department of Occupational TherapyShriners Hospital for Children
  • George E. Gorton
    • Motion LabShriners Hospital for Children
  • Kyle Watson
    • Motion Analysis LabShriners Hospital for Children
  • Carole A. Tucker
    • Physical Therapy Department, College of Health ProfessionsTemple University
Article

DOI: 10.1007/s11136-009-9447-5

Cite this article as:
Haley, S.M., Ni, P., Dumas, H.M. et al. Qual Life Res (2009) 18: 359. doi:10.1007/s11136-009-9447-5

Abstract

Purpose

The purposes of this study were to apply a bi-factor model for the determination of test dimensionality and a multidimensional CAT using computer simulations of real data for the assessment of a new global physical health measure for children with cerebral palsy (CP).

Methods

Parent respondents of 306 children with cerebral palsy were recruited from four pediatric rehabilitation hospitals and outpatient clinics. We compared confirmatory factor analysis results across four models: (1) one-factor unidimensional; (2) two-factor multidimensional (MIRT); (3) bi-factor MIRT with fixed slopes; and (4) bi-factor MIRT with varied slopes. We tested whether the general and content (fatigue and pain) person score estimates could discriminate across severity and types of CP, and whether score estimates from a simulated CAT were similar to estimates based on the total item bank, and whether they correlated as expected with external measures.

Results

Confirmatory factor analysis suggested separate pain and fatigue sub-factors; all 37 items were retained in the analyses. From the bi-factor MIRT model with fixed slopes, the full item bank scores discriminated across levels of severity and types of CP, and compared favorably to external instruments. CAT scores based on 10- and 15-item versions accurately captured the global physical health scores.

Conclusions

The bi-factor MIRT CAT application, especially the 10- and 15-item versions, yielded accurate global physical health scores that discriminated across known severity groups and types of CP, and correlated as expected with concurrent measures. The CATs have potential for collecting complex data on the physical health of children with CP in an efficient manner.

Keywords

Bi-factor modelComputerized adaptive testingItem response theory

Copyright information

© Springer Science+Business Media B.V. 2009