Predicting change with the RBANS in community dwelling elderly sample

Abstract

Repeated neuropsychological assessments are common with older adults, and the determination of clinically significant change across time is an important issue. Regression-based prediction formulas have been utilized with other patient and healthy control samples to predict follow-up test performance based on initial performance and demographic variables. Comparisons between predicted and observed follow-up performances can assist clinicians in determining the significance of change in the individual patient. In the current study, multiple regression-based prediction equations for the 5 Indexes and Total Score of the RBANS were developed for a sample of 223 community dwelling older adults. These algorithms were then validated on a separate elderly sample (N = 222). Minimal differences were present between observed and predicted follow-up scores in the validation sample, suggesting that the prediction formulas are clinically useful for practitioners who assess older adults. A case example is presented that illustrates how the algorithms can be used clinically. Copyright © 2004 INS. Published by Cambridge University Press.