| Autor: |
Louisa I. Thompson, Zachary J. Kunicki, Sheina Emrani, Jennifer Strenger, Alyssa N. De Vito, Karysa J. Britton, Catherine Dion, Karra D. Harrington, Nelson Roque, Stephen Salloway, Martin J. Sliwinski, Stephen Correia, Richard N. Jones |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
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| Zdroj: |
Alzheimer’s & Dementia: Diagnosis, Assessment & Disease Monitoring, Vol 15, Iss 4, Pp n/a-n/a (2023) |
| Druh dokumentu: |
article |
| ISSN: |
2352-8729 |
| DOI: |
10.1002/dad2.12500 |
| Popis: |
Abstract 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. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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