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Hierarchical cognitive and psychosocial predictors of amnestic mild cognitive impairment

  • S. DUKE HAN (a1), HIDEO SUZUKI (a2), AMY J. JAK (a3) (a4), YU-LING CHANG (a3), DAVID P. SALMON (a5) and MARK W. BONDI (a3) (a4)...

To identify neuropsychological and psychosocial factors predictive of amnestic Mild Cognitive Impairment (aMCI) among a group of 94 nondemented older adults, we employed a novel nonlinear multivariate classification statistical method called Optimal Data Analysis (ODA) in a dataset collected annually for 3 years. Performance on measures of memory and visuomotor processing speed or symptoms of depression in year 1 predicted aMCI status by year 2. Performance on a measure of learning at year 1 predicted aMCI status at year 3. No other measures significantly predicted incidence of aMCI at years 2 and 3. Results support the utility of multiple neuropsychological and psychosocial measures in the diagnosis of aMCI, and the present model may serve as a testable hypothesis for prospective investigations of the development of aMCI. (JINS, 2010, 16, 721–729.)

Corresponding author
*Correspondence and reprint requests to: S. Duke Han, Ph.D., Department of Behavioral Sciences, Rush University Medical Center, 1653 West Congress Parkway, Chicago, IL 60612-3833. E-mail:
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Journal of the International Neuropsychological Society
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