JMIR Publications

ABSTRACT

Background:

Frontotemporal lobar degeneration (FTLD) is a leading cause of dementia in individuals under age 65. Several challenges to conducting in-person evaluations in FTLD illustrate an urgent need to develop remote, accessible, and low-burden assessment techniques. Studies of unobtrusive monitoring of at-home computer use in older adults with mild cognitive impairment have shown that declining function is reflected in reduced computer use. This study aimed to extend these findings by examining smartphone usage.

Objective:

We characterized daily trajectories in smartphone battery usage, a proxy of smartphone use, and examined relationships with clinical indicators of disease severity in FTLD.

Methods:

Participants were 231 adults (mean age=52.5 years [SD=14.9]; 41% men; 97% non-Hispanic White) enrolled in the ALLFTD Mobile App study, including 49 with mild neurobehavioral changes and no functional impairment (i.e., prodromal FTLD), 43 with neurobehavioral changes and functional impairment (i.e., symptomatic FTLD), and 139 clinically normal adults, 40% of whom harbored heterozygous pathogenic or likely pathogenic variants in an autosomal dominant FTLD gene. Participants completed the FTLD Clinical Dementia Rating scale (CDR®+NACC FTLD), a neuropsychological battery, the Neuropsychiatric Inventory (NPI), and brain MRI. The ALLFTD Mobile App was installed on participants’ smartphones for remote, passive, and continuous monitoring of smartphone use. Battery percentage was collected every 15 minutes over an average of 28 days (range=14-30). To determine whether temporal patterns of battery percentage varied as a function of disease severity, linear mixed effects models examined linear, quadratic, and cubic effects of time of day and their interactions with each measure of disease severity on battery percentage. Models covaried for age, sex, and smartphone type.

Results:

CDR®+NACC FTLD Global score interacted with time on battery percentage, such that prodromal and symptomatic participants demonstrated less change in battery percentage throughout the day (a proxy of less smartphone use) than clinically normal participants (P<.001 in both cases). Worse cognitive performance, more neuropsychiatric symptoms, and smaller MRI gray matter volumes also associated with less battery usage throughout the day (P<.001 in all cases).

Conclusions:

Findings support a proof of concept that passively collected data about smartphone use behaviors have potential to detect clinical impairment in FTLD. This work underscores the need for ongoing studies to develop passive digital markers sensitive to longitudinal clinical decline across neurodegenerative diseases, with potential to enhance real-world monitoring for early detection and use in clinical trials.