Passively monitored smartphone battery percentage relates to disease severity in frontotemporal dementia: A proof‐of‐concept study
Year: 2023
Type: article
Study design: Observational Study
Abstract: 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<0.001). Additional models showed that worse memory (hour3 x memory score: 𝛃 = 0.59, p<0.001) and executive functioning (hour3 x executive score: 𝛃 = 0.64, p<0.001), more neuropsychiatric symptoms (hour3 x NPI‐Q: 𝛃 = ‐0.22, p = 0.004), and smaller gray matter volumes (controlling for intracranial volume; hour3 x volume: 𝛃 = 0.49, p<0.001) were also statistically significantly related to less battery usage throughout the day. Conclusion These findings are proof‐of‐concept that passively acquired smartphone data, specifically battery usage, can provide insights about disease progression in FTD. Results support future research focusing on the development of passively collected digital metrics sensitive to clinical declines in neurodegenerative disease.
Source: Alzheimer s & Dementia
DOI: 10.1002/alz.079178
Institutions: University of California, San Francisco, Mayo Clinic
Language: English
Subfield: Psychiatry and Mental health
Field: Medicine
Domain: Health Sciences
Open Access status: bronze
OpenAlex ID: W4390200022