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Reliable Change on Neuropsychological Tests in the Uniform Data Set

Published online by Cambridge University Press:  03 August 2015

Brandon E. Gavett*
Affiliation:
University of Colorado, Colorado Springs, Department of Psychology, Colorado Springs, Colorado
Lee Ashendorf
Affiliation:
Boston University School of Medicine, Department of Psychiatry, Boston, Massachusetts
Ashita S. Gurnani
Affiliation:
University of Colorado, Colorado Springs, Department of Psychology, Colorado Springs, Colorado
*
Correspondence and reprint requests to: Brandon E. Gavett, UCCS Department of Psychology, 1420 Austin Bluffs Parkway, Colorado Springs, CO 80918. E-mail: [email protected]

Abstract

Longitudinal normative data obtained from a robust elderly sample (i.e., believed to be free from neurodegenerative disease) are sparse. The purpose of the present study was to develop reliable change indices (RCIs) that can assist with interpretation of test score changes relative to a healthy sample of older adults (ages 50+). Participants were 4217 individuals who completed at least three annual evaluations at one of 34 past and present Alzheimer’s Disease Centers throughout the United States. All participants were diagnosed as cognitively normal at every study visit, which ranged from three to nine approximately annual evaluations. One-year RCIs were calculated for 11 neuropsychological variables in the Uniform Data Set by regressing follow-up test scores onto baseline test scores, age, education, visit number, post-baseline assessment interval, race, and sex in a linear mixed effects regression framework. In addition, the cumulative frequency distributions of raw score changes were examined to describe the base rates of test score changes. Baseline test score, age, education, and race were robust predictors of follow-up test scores across most tests. The effects of maturation (aging) were more pronounced on tests related to attention and executive functioning, whereas practice effects were more pronounced on tests of episodic and semantic memory. Interpretation of longitudinal changes on 11 cognitive test variables can be facilitated through the use of reliable change intervals and base rates of score changes in this robust sample of older adults. A Web-based calculator is provided to assist neuropsychologists with interpretation of longitudinal change. (JINS, 2015, 21, 558–567)

Type
Research Articles
Copyright
Copyright © The International Neuropsychological Society 2015 

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