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98 Remote App-Based Assessment of Memory and Executive Functioning in Aging and Pre-Clinical Alzheimer’s Disease

Published online by Cambridge University Press:  21 December 2023

Dawn Mechanic-Hamilton*
Affiliation:
University of Pennsylvani, Philadelphia, PA, USA.
Kimberly Halberstadter
Affiliation:
University of Pennsylvani, Philadelphia, PA, USA.
MIchael Dicalogero
Affiliation:
University of Pennsylvani, Philadelphia, PA, USA.
Rachel Rovere
Affiliation:
University of Pennsylvani, Philadelphia, PA, USA.
La’cendria Pulley
Affiliation:
Drexel University, Philadelphia, PA, USA
David Wolk
Affiliation:
University of Pennsylvani, Philadelphia, PA, USA.
*
Correspondence: Dawn Mechanic-Hamilton, University of Pennsylvania, Perelman School of Medicine, dawn.mechanic@pennmedicine.upenn.edu
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Abstract

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Objective:

Mobile, valid, and engaging cognitive assessments are essential for detecting and tracking change in research participants and patients at risk for Alzheimer’s Disease and Related Dementias (ADRDs). This pilot study aims to determine the feasibility and performance of app-based memory and executive functioning tasks included in the mobile cognitive app performance platform (mCAPP), to remotely detect cognitive changes associated with aging and preclinical Alzheimer’s Disease (AD).

Participants and Methods:

The mCAPP includes three gamified tasks: (1) a memory task that includes learning and matching hidden card pairs and incorporates increasing memory load, pattern separation features (lure vs. non-lure), and spatial memory (2) a stroop-like task (“brick drop”) with speeded word and color identification and response inhibition components and (3) a digit-symbol coding-like task (“space imposters”) with increasing pairs and incidental learning components. The cohort completed the NACC UDS3 neuropsychological battery, selected NIH Toolbox tasks, and additional cognitive testing sensitive to pre-clinical AD, within six months of the mCAPP testing. Participants included thirty-seven older adults (60% female; age=72±4.4, years of education=17±2.5; 67% Caucasian, 30% Black/AA, 3% Multiracial) with normal cognition who are enrolled in the Penn Alzheimer’s Disease Research Center (ADRC) cohort. Participants completed one in-person session and two weeks of at-home testing, with eight scheduled sessions, four in the morning and four in the afternoon. Participants also completed questionnaires and an interview about technology use and wore activity trackers to collect daily step and sleep data and answered questions about mood, anxiety, and fatigue throughout the two weeks of at-home data collection.

Results:

The participants completed an average of 11 at-home sessions, with the majority choosing to play extra sessions. Participants reported high usability ratings for all tasks and the majority rated the task difficulty as acceptable. On all mCAPP tasks, participant performance declined in accuracy and speed with increasing memory load and task complexity. mCAPP tasks correlated significantly with paper and pencil measures and several NIH Toolbox tasks (p<0.05). Examination of performance trends over multiple sessions indicates stabilization of performance within 4-6 sessions on memory mCAPP measures and 5-7 sessions on executive functioning mCAPP measures. Preliminary analyses indicate differences in mCAPP measures and imaging biomarkers.

Conclusions:

Participants were willing and able to complete at-home cognitive testing and most chose to complete more than the assigned sessions. Remote data collection is feasible and well-tolerated. We show preliminary construct validity with the UDS3 and NIH Toolbox and test-retest reliability following a period of task learning and performance improvement and stabilization. This work will help to advance remote detection and monitoring of early cognitive changes associated with preclinical AD. Future directions will include further evaluation of the relationships between mCAPP performance, behavioral states, and neuroimaging biomarkers as well as the utility of detection of practice effects in identifying longitudinal change and risk for ADRD-related cognitive decline.

Type
Poster Session 08: Assessment | Psychometrics | Noncredible Presentations | Forensic
Copyright
Copyright © INS. Published by Cambridge University Press, 2023