Quality of Life Research

, Volume 22, Issue 8, pp 1907–1915 | Cite as

Psychometric properties of a computerized adaptive test for assessing mobility in older adults using novel video-animation technology

  • Edward H. Ip
  • W. Jack Rejeski
  • Anthony P. Marsh
  • Ryan Barnard
  • Shyh-Huei Chen
Article

Abstract

Purpose

This paper reports on the psychometric properties of a computerized adaptive test (CAT) version of the Mobility Assessment Tool (MAT) for older adults (MAT-CAT).

Methods

An item pool of 78 video-animation-based items for mobility was developed, and response data were collected from a sample of 234 participants aged 65–90 years. The video-animation-based instrument was designed to minimize ambiguity in the presentation of task demands. In addition to evaluating traditional psychometric properties including dimensionality, differential item functioning (DIF), and local dependence, we extensively tested the performance of several MAT-CAT measures and compared their performances with a fixed format.

Results

Operationally, the MAT-CAT was sufficiently unidimensional and had acceptable levels of local independence. One DIF item was removed. Most importantly, the CAT measures showed that even starting with a single fixed item at the mean ability, the adaptive version delivered better performance than the fixed format in terms of several criteria including the standard error of estimate.

Conclusion

The MAT-CAT demonstrated satisfactory psychometric properties and superior performance to a fixed format. The video-animation-based adaptive instrument can be used for assessing mobility with specificity and precision.

Keywords

Mobility Assessment Tool Item response theory Health-related quality of life Mobility disability Animation 

Abbreviations

DIF

Differential item functioning

MAT

Mobility Assessment Tool

HRQOL

Health-related quality of life

PRO

Patient-reported outcome

HIPAA

Health Insurance Portability and Accountability Act of 1996

CAT

Computerized adaptive test

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Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  • Edward H. Ip
    • 1
  • W. Jack Rejeski
    • 2
  • Anthony P. Marsh
    • 2
  • Ryan Barnard
    • 1
  • Shyh-Huei Chen
    • 1
  1. 1.Department of Biostatistical SciencesWake Forest School of MedicineWinston-SalemUSA
  2. 2.Department of Health and Exercise ScienceWake Forest UniversityWinston-SalemUSA

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