Predicting cognitive change across 3 years in community-dwelling elders.
The determination of clinically significant cognitive change across time is an important issue in neuropsychology, and repeated assessments are common with older adults. Regression-based prediction formulas, which use initial test performance and demographic variables to predict follow-up test performance, have been utilized with patient and healthy control samples. 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 five Indexes and Total Score of the RBANS were developed for a sample of 146 community-dwelling older adults across a 2-year interval. These algorithms were then validated on a separate elderly sample (n = 145). 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.
Duff
Kevin
K
Department of Psychiatry, University of Iowa, Iowa City, IA 52242-1000, USA. kevin-duff@uiowa.edu
Schoenberg
Mike R
MR
Patton
Doyle E
DE
Mold
James W
JW
Scott
James G
JG
Adams
Russell L
RL
D000368:Aged; D000369:Aged, 80 and over; D003071:Cognition / Q000502:physiology*; D005260:Female; D015577:Geriatric Assessment; D006801:Humans; D008137:Longitudinal Studies; D008297:Male; D009483:Neuropsychological Tests / Q000706:statistics & numerical data*; D011237:Predictive Value of Tests; D012044:Regression Analysis; D012111:Residence Characteristics