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Identification of Mild Cognitive Impairment in ACTIVE: Algorithmic Classification and Stability

Published online by Cambridge University Press:  25 October 2012

Sarah E. Cook ,
Michael Marsiske ,
Kelsey R. Thomas ,
Frederick W. Unverzagt ,
Virginia G. Wadley ,
Jessica B.S. Langbaum  and
Michael Crowe
Sarah E. Cook
Affiliation:
Department of Psychiatry, Duke University, Durham, North Carolina Department of Clinical and Health Psychology, University of Florida, Gainesville, Florida
Michael Marsiske*
Affiliation:
Department of Clinical and Health Psychology, University of Florida, Gainesville, Florida
Kelsey R. Thomas
Affiliation:
Department of Clinical and Health Psychology, University of Florida, Gainesville, Florida
Frederick W. Unverzagt
Affiliation:
Department of Psychiatry, Indiana University School of Medicine, Indianapolis, Indiana
Virginia G. Wadley
Affiliation:
Department of Psychology, University of Alabama-Birmingham, Birmingham, Alabama
Jessica B.S. Langbaum
Affiliation:
Banner Alzheimer's Institute, Banner Health, Phoenix, Arizona
Michael Crowe
Affiliation:
Department of Psychology, University of Alabama-Birmingham, Birmingham, Alabama
*
Correspondence and reprint requests to: Michael Marsiske, Department of Clinical and Health Psychology, University of Florida, Gainesville, Florida, 32610-0165. E-mail: marsiske@ufl.edu
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Abstract

Rates of mild cognitive impairment (MCI) have varied substantially, depending on the criteria used and the samples surveyed. The present investigation used a psychometric algorithm for identifying MCI and its stability to determine if low cognitive functioning was related to poorer longitudinal outcomes. The Advanced Cognitive Training of Independent and Vital Elders (ACTIVE) study is a multi-site longitudinal investigation of long-term effects of cognitive training with older adults. ACTIVE exclusion criteria eliminated participants at highest risk for dementia (i.e., Mini-Mental State Examination < 23). Using composite normative for sample- and training-corrected psychometric data, 8.07% of the sample had amnestic impairment, while 25.09% had a non-amnestic impairment at baseline. Poorer baseline functional scores were observed in those with impairment at the first visit, including a higher rate of attrition, depressive symptoms, and self-reported physical functioning. Participants were then classified based upon the stability of their classification. Those who were stably impaired over the 5-year interval had the worst functional outcomes (e.g., Instrumental Activities of Daily Living performance), and inconsistency in classification over time also appeared to be associated increased risk. These findings suggest that there is prognostic value in assessing and tracking cognition to assist in identifying the critical baseline features associated with poorer outcomes. (JINS, 2012, 18, 1–15)

Keywords

Cognitive impairmentResearch classificationCognitive agingLongitudinal follow-up
Type
Research Articles
Information
Journal of the International Neuropsychological Society , Volume 19 , Issue 1 , January 2013 , pp. 73 - 87
Copyright
Copyright © The International Neuropsychological Society 2012

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