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Predicting change with the RBANS in a community dwelling elderly sample

Published online by Cambridge University Press:  01 October 2004

KEVIN DUFF ,
MIKE R. SCHOENBERG ,
DOYLE PATTON ,
JAMES MOLD ,
JAMES G. SCOTT  and
RUSSELL L. ADAMS
KEVIN DUFF
Affiliation:
Department of Psychiatry, University of Iowa, Iowa City
MIKE R. SCHOENBERG
Affiliation:
University Hospitals of Cleveland and Case Western Reserve University School of Medicine, Department of Neurology, Cleveland, Ohio
DOYLE PATTON
Affiliation:
Department of Psychiatry & Behavioral Sciences, University at Oklahoma Health Sciences Center, Oklahoma City
JAMES MOLD
Affiliation:
Department of Family Medicine, University at Oklahoma Health Sciences Center, Oklahoma City
JAMES G. SCOTT
Affiliation:
Department of Psychiatry & Behavioral Sciences, University at Oklahoma Health Sciences Center, Oklahoma City
RUSSELL L. ADAMS
Affiliation:
Department of Psychiatry & Behavioral Sciences, University at Oklahoma Health Sciences Center, Oklahoma City
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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. (JINS, 2004, 10, 828–834.)

Keywords

Predicting cognitive changeRBANSOlder adultsNeuropsychology
Type
Research Article
Information
Journal of the International Neuropsychological Society , Volume 10 , Issue 6 , October 2004 , pp. 828 - 834
Copyright
© 2004 The International Neuropsychological Society

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