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Unsupervised high-frequency smartphone-based cognitive assessments are reliable, valid, and feasible in older adults at risk for Alzheimer’s disease

Published online by Cambridge University Press:  05 September 2022

Jessica Nicosia ,
Andrew J. Aschenbrenner Open the ORCID record for Andrew J. Aschenbrenner [Opens in a new window] ,
David A. Balota ,
Martin J. Sliwinski ,
Marisol Tahan ,
Sarah Adams ,
Sarah S. Stout ,
Hannah Wilks ,
Brian A. Gordon  and
Tammie L. S. Benzinger
...Show all authors
Jessica Nicosia
Affiliation:
Charles F. and Joanne Knight Alzheimer Disease Research Center, Department of Neurology, Washington University, School of Medicine, St. Louis, MO, USA
Andrew J. Aschenbrenner
Affiliation:
Charles F. and Joanne Knight Alzheimer Disease Research Center, Department of Neurology, Washington University, School of Medicine, St. Louis, MO, USA
David A. Balota
Affiliation:
Department of Psychological & Brain Sciences, Washington University in St. Louis, St. Louis, MO, USA
Martin J. Sliwinski
Affiliation:
Department of Human Development and Family Studies, The Pennsylvania State University, University Park, PA, USA
Marisol Tahan
Affiliation:
Charles F. and Joanne Knight Alzheimer Disease Research Center, Department of Neurology, Washington University, School of Medicine, St. Louis, MO, USA
Sarah Adams
Affiliation:
Charles F. and Joanne Knight Alzheimer Disease Research Center, Department of Neurology, Washington University, School of Medicine, St. Louis, MO, USA
Sarah S. Stout
Affiliation:
Charles F. and Joanne Knight Alzheimer Disease Research Center, Department of Neurology, Washington University, School of Medicine, St. Louis, MO, USA
Hannah Wilks
Affiliation:
Charles F. and Joanne Knight Alzheimer Disease Research Center, Department of Neurology, Washington University, School of Medicine, St. Louis, MO, USA
Brian A. Gordon
Affiliation:
Department of Psychological & Brain Sciences, Washington University in St. Louis, St. Louis, MO, USA Department of Radiology, Washington University, School of Medicine, St. Louis, MO, USA
Tammie L. S. Benzinger
Affiliation:
Department of Radiology, Washington University, School of Medicine, St. Louis, MO, USA
Anne M. Fagan
Affiliation:
Charles F. and Joanne Knight Alzheimer Disease Research Center, Department of Neurology, Washington University, School of Medicine, St. Louis, MO, USA
Chengjie Xiong
Affiliation:
Charles F. and Joanne Knight Alzheimer Disease Research Center, Department of Neurology, Washington University, School of Medicine, St. Louis, MO, USA Division of Biostatistics, Washington University, School of Medicine, St. Louis, MO, USA
Randall J. Bateman
Affiliation:
Charles F. and Joanne Knight Alzheimer Disease Research Center, Department of Neurology, Washington University, School of Medicine, St. Louis, MO, USA
John C. Morris
Affiliation:
Charles F. and Joanne Knight Alzheimer Disease Research Center, Department of Neurology, Washington University, School of Medicine, St. Louis, MO, USA
Jason Hassenstab*
Affiliation:
Charles F. and Joanne Knight Alzheimer Disease Research Center, Department of Neurology, Washington University, School of Medicine, St. Louis, MO, USA Department of Psychological & Brain Sciences, Washington University in St. Louis, St. Louis, MO, USA
*
Corresponding author: Jason Hassenstab, email: hassenstabj@wustl.edu
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Abstract

Objective:

Smartphones have the potential for capturing subtle changes in cognition that characterize preclinical Alzheimer’s disease (AD) in older adults. The Ambulatory Research in Cognition (ARC) smartphone application is based on principles from ecological momentary assessment (EMA) and administers brief tests of associative memory, processing speed, and working memory up to 4 times per day over 7 consecutive days. ARC was designed to be administered unsupervised using participants’ personal devices in their everyday environments.

Methods:

We evaluated the reliability and validity of ARC in a sample of 268 cognitively normal older adults (ages 65–97 years) and 22 individuals with very mild dementia (ages 61–88 years). Participants completed at least one 7-day cycle of ARC testing and conventional cognitive assessments; most also completed cerebrospinal fluid, amyloid and tau positron emission tomography, and structural magnetic resonance imaging studies.

Results:

First, ARC tasks were reliable as between-person reliability across the 7-day cycle and test-retest reliabilities at 6-month and 1-year follow-ups all exceeded 0.85. Second, ARC demonstrated construct validity as evidenced by correlations with conventional cognitive measures (r = 0.53 between composite scores). Third, ARC measures correlated with AD biomarker burden at baseline to a similar degree as conventional cognitive measures. Finally, the intensive 7-day cycle indicated that ARC was feasible (86.50% approached chose to enroll), well tolerated (80.42% adherence, 4.83% dropout), and was rated favorably by older adult participants.

Conclusions:

Overall, the results suggest that ARC is reliable and valid and represents a feasible tool for assessing cognitive changes associated with the earliest stages of AD.

Keywords

digital biomarkersmobile testingpreclinical Alzheimer’s diseaseecological momentary assessment
Type
Research Article
Information
Journal of the International Neuropsychological Society , Volume 29 , Issue 5 , June 2023 , pp. 459 - 471
Copyright
Copyright © INS. Published by Cambridge University Press, 2022

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