Feasibility of Remote Administration of the Uniform Data Set-Version 3 for Assessment of Older Adults With Mild Cognitive Impairment and Alzheimer's Disease.
Bonnie C Sachs, Lauren A Latham, James R Bateman, Mary Jo Cleveland, Mark A Espeland, Eric Fischer, Sarah A Gaussoin, Iris Leng, Stephen R Rapp, Samantha Rogers, Heather M Shappell, Benjamin J Williams, Mia Yang, Suzanne Craft
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Abstract
Objective: Assess the feasibility and concurrent validity of a modified Uniform Data Set version 3 (UDSv3) for remote administration for individuals with normal cognition (NC), mild cognitive impairment (MCI), and early dementia.
Method: Participants (N = 93) (age: 72.8 [8.9] years; education: 15.6 [2.5] years; 72% female; 84% White) were enrolled from the Wake Forest ADRC. Portions of the UDSv3 cognitive battery, plus the Rey Auditory Verbal Learning Test, were completed by telephone or video within ~6 months of participant's in-person visit. Adaptations for phone administration (e.g., Oral Trails for Trail Making Test [TMT] and Blind Montreal Cognitive Assessment [MoCA] for MoCA) were made. Participants reported on the pleasantness, difficulty, and preference for each modality. Staff provided validity ratings for assessments. Participants' remote data were adjudicated by cognitive experts blinded to the in person-diagnosis (NC [N = 44], MCI [N = 35], Dementia [N = 11], or other [N = 3]).
Results: Remote assessments were rated as pleasant as in-person assessments by 74% of participants and equally difficult by 75%. Staff validity rating (video = 92%; phone = 87.5%) was good. Concordance between remote/in-person scores was generally moderate to good (r = .3 -.8; p < .05) except for TMT-A/OTMT-A (r = .3; p > .05). Agreement between remote/in-person adjudicated cognitive status was good (k = .61-.64).
Conclusions: We found preliminary evidence that older adults, including those with cognitive impairment, can be assessed remotely using a modified UDSv3 research battery. Adjudication of cognitive status that relies on remotely collected data is comparable to classifications using in-person assessments.