Passively monitored smartphone battery percentage relates to disease severity in frontotemporal dementia: A proof‐of‐concept study

Background Frontotemporal dementia (FTD) is a leading cause of dementia in individuals under age 65. Due to limitations in access to in‐person evaluations, there is an urgent need to examine remote, accessible, and low‐burden assessment techniques for FTD. Unobtrusive monitoring of at‐home computer...

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Veröffentlicht in:Alzheimer's & dementia 2023-12, Vol.19 (S18), p.n/a
Hauptverfasser: Paolillo, Emily W., Casaletto, Kaitlin B., Clark, Annie L, Taylor, Jack C, Heuer, Hilary W., Wise, Amy B., Dhanam, Sreya, Sanderson‐Cimino, Mark E., Saloner, Rowan, Kramer, Joel H., Kornak, John, Kremers, Walter K., Forsberg, Leah K., Boeve, Brad F., Rosen, Howard J., Boxer, Adam L., Staffaroni, Adam M.
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Sprache:eng
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Zusammenfassung:Background Frontotemporal dementia (FTD) is a leading cause of dementia in individuals under age 65. Due to limitations in access to in‐person evaluations, there is an urgent need to examine remote, accessible, and low‐burden assessment techniques for FTD. Unobtrusive monitoring of at‐home computer use in older adults has shown that those with mild cognitive impairment (MCI) have significant declines in computer use over time. To extend these findings, we characterized daily trajectories in smartphone battery percentage, a proxy of smartphone use, and examined relationships with clinical indicators of disease severity in FTD. Method Participants included 250 adults enrolled in the ALLFTD Mobile App study (mean age = 53.9 [SD = 14.9]; 59% women; 94% White). To assess clinical disease severity, all participants completed the FTLD Clinical Dementia Rating scale (CDR®+NACC FTLD), a brief neuropsychological battery, the Neuropsychiatric Inventory Questionnaire (NPI‐Q), and brain MRI. The ALLFTD Mobile App was installed onto participants’ smartphones for remote, passive, continuous monitoring of smartphone use (average days of monitoring = 82 [range = 7‐541]). Battery percentage was collected every 15 minutes. Linear mixed effects models examined linear, quadratic, and cubic effects of time of day (i.e., hour; modeled as person‐specific random effects) and their interactions with each measure of disease severity on battery percentage. Models covaried for age. Result 57% of participants were clinically normal, 21% had MCI, and 22% had dementia. CDR®+NACC FTLD Global score interacted with hour such that participants with MCI and dementia had flatter battery curves (i.e., less change in battery percentage throughout the day – a proxy of less smartphone use) than clinically normal participants (ps
ISSN:1552-5260
1552-5279
DOI:10.1002/alz.079178