Predicting change with the RBANS in a community dwelling elderly sample

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...

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Bibliographic Details
Published in:Journal of the International Neuropsychological Society 2004-10, Vol.10 (6), p.828-834
Main Authors: DUFF, KEVIN, SCHOENBERG, MIKE R., PATTON, DOYLE, MOLD, JAMES, SCOTT, JAMES G., ADAMS, RUSSELL L.
Format: Article
Language:English
Subjects:
Adults
Aged - psychology
Aging - psychology
Alzheimer's disease
Attention - physiology
Cognition - physiology
Family physicians
Female
Heart surgery
Humans
Independent sample
Language
Longitudinal Studies
Macular degeneration
Male
Memory - physiology
Neuropsychological Tests
Neuropsychology
Older adults
Older people
Parkinson's disease
Patients
Predicting cognitive change
Predictive Value of Tests
RBANS
Regression Analysis
Reproducibility of Results
Research methodology
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Summary: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.)
ISSN:1355-6177
1469-7661
DOI:10.1017/S1355617704106048