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TD‐P‐01: MOBILE MONITORING OF COGNITION IN MIDDLE‐AGED AND OLDER ADULTS WITH AND WITHOUT AMNESTIC MILD COGNITIVE IMPAIRMENT: IMPLICATIONS FOR ALZHEIMER'S DISEASE CLINICAL TRIALS
Author(s) -
Campbell Laura M.,
Delgadillo Jeremy D.,
Paolillo Emily W.,
Sundermann Erin E.,
Holden Jason,
Schweitzer Pierre,
Swendsen Joel,
Moore Raeanne C.
Publication year - 2019
Publication title -
alzheimer's and dementia
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.713
H-Index - 118
eISSN - 1552-5279
pISSN - 1552-5260
DOI - 10.1016/j.jalz.2019.06.4312
Subject(s) - neuropsychology , cognition , psychology , clinical trial , neuropsychological assessment , boston naming test , audiology , cognitive impairment , medicine , clinical psychology , psychiatry
for up to eight months in diverse community settings among independent older adults. Methods: Volunteers were participants in the Collaborative Aging Research using Technology (CART) initiative, a study examining the feasibility of unobtrusive remote sensing and monitoring of physical, cognitive, behavioral, physiological, and health-related activities. Participants were older adults living in low income subsidized housing communities and veterans living largely in rural areas of the Pacific Northwest. Data related to sleep (total sleep time) was acquired using a wrist worn device which participants were instructed to wear all the time. Results: 126 participants were monitored with wearable data for a mean of 4.7 Fifty-three percent were women. Cognitive status was assigned according to entry assessmentMoCA score using a reference cutoff of 23/30 which has been suggested as an optimized screening cutoff for MCI on this test. Forty-two participants met the below 23/30 metric. Watch use compliance ([# of days with watch sleep data] / [total days] * 100) overall was high; the lower scoring group had significantly lower watch compliance than the higher scoring MoCA screened group (82% vs 91%, p<0.01). In a multivariate logistic regression model, mean total sleep time (in hours) was significantly related to cognitive status (adjusted for age, gender, and education), OR 0.74 (CI 0.56-0.98), p1⁄40.038; as total sleep time increases, the less likely (or the lower the risk) for meeting the MCI cut score. Conclusions: Continuous longitudinal remote assessment of diverse populations (rural-residing, veterans, low income older adults) using a wearable device is feasible with good compliance. Sleep activity (lower total sleep time) can be detected in those who may be at risk for MCI or dementia. This (and related activity measures) appear useful for detecting salient changes in function and cognition in community-based studies.