Introduction: We evaluated the accuracy of remote and in-person digital tests to distinguish between older adults with and without AD pathological change and used the Montreal Cognitive Assessment (MoCA) as a comparison test.
Methods: Participants were 69 cognitively normal older adults with known beta-amyloid (Aβ) PET status. Participants completed smartphone-based assessments 3×/day for 8 days, followed by TabCAT tasks, DCTclock™, and MoCA at an in-person study visit. We calculated the area under the curve (AUC) to compare task accuracies to distinguish Aβ status.
Results: Average performance on the episodic memory (Prices) smartphone task showed the highest accuracy (AUC = 0.77) to distinguish Aβ status. On in-person measures, accuracy to distinguish Aβ status was greatest for the TabCAT Favorites task (AUC = 0.76), relative to the DCTclockTM (AUC = 0.73) and MoCA (AUC = 0.74).
Discussion: Although further validation is needed, our results suggest that several digital assessments may be suitable for more widespread cognitive screening application.
Keywords: cognitive screening; digital technology; early diagnosis; preclinical Alzheimer's disease.
© 2023 The Authors. Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring published by Wiley Periodicals LLC on behalf of Alzheimer's Association.