INS NYC 2024 Program

Custom Content	Poster Session 04 Program Schedule 02/15/2024 12:00 pm - 01:15 pm Room: Shubert Complex (Posters 1-60) Poster Session 04: Neuroimaging \| Neurostimulation/Neuromodulation \| Teleneuropsychology/Technology Final Abstract #3 Poster Symposium: Novel Technology-Based Approaches for Cognitive Assessment — Abstract 2 Longitudinal decline in smartphone usage relates to disease severity and clinical progression in frontotemporal lobar degeneration Emily Paolillo, UCSF Memory and Aging Center, San Francisco, United States Kaitlin Casaletto, UCSF Memory and Aging Center, San Francisco, United States Annie Clark, UCSF Memory and Aging Center, San Francisco, United States Jack Taylor, UCSF Memory and Aging Center, San Francisco, United States Amy Wise, UCSF Memory and Aging Center, San Francisco, United States Sreya Dhanam, UCSF Memory and Aging Center, San Francisco, United States Mark Sanderson-Cimino, UCSF Memory and Aging Center, San Francisco, United States Brandon Palacios, UCSF Memory and Aging Center, San Francisco, United States Rowan Saloner, UCSF Memory and Aging Center, San Francisco, United States Shubir Dutt, UCSF Memory and Aging Center, San Francisco, United States Adam Boxer, UCSF Memory and Aging Center, San Francisco, United States Adam Staffaroni, UCSF Memory and Aging Center, San Francisco, United States Category: Teleneuropsychology/ Technology Keyword 1: aging disorders Keyword 2: dementia - other cortical Keyword 3: technology Objective: Frontotemporal lobar degeneration (FTLD) is a common cause of early-onset dementia. There are several challenges to conducting in-person evaluations in FTLD (e.g., behavioral and/or motor symptoms, low base rates), creating an urgent need to examine remote and accessible assessment techniques. Passive digital monitoring methods are low burden and provide unique opportunities to capture naturalistic behavioral data reflecting cognitive decline in real time. This study utilized passively collected smartphone battery percentage data to characterize linear trajectories of smartphone usage over time and examined relationships with clinical indicators of disease severity and progression in FTLD. Participants and Methods: Participants included 172 adults enrolled in the ALLFTD Mobile App study (mean age=53.1 [SD=15.3]; 58% women; 96% White; 56% unimpaired; 20% prodromal FTLD; 24% symptomatic FTLD) who completed at least 3 months of passive smartphone monitoring via the ALLFTD Mobile App (mean monitoring period = 6.9 months, range = 3-18). Battery percentage was collected frequently (median collection interval = 46 min [IQR = 15-62]), and daily battery usage was calculated by summing consecutive declines in battery percentage throughout each day (a proxy for daily smartphone use; higher battery usage = more smartphone use). To assess different aspects of clinical disease severity at baseline, participants completed: the modified Clinical Dementia Rating plus FTLD behavior and language domains (CDR®+NACC FTLD); a neuropsychological battery measuring executive function, memory, and language (z-scored); the Neuropsychiatric Inventory (NPI); and structural brain MRI. Linear mixed effects models examined each index of baseline disease severity as a predictor of linear smartphone usage trajectories over time. In a subset of 36 participants who completed a follow-up CDR®+NACC FTLD at 12 or 18 months, additional linear effects models examined smartphone usage trajectories as a function of CDR®+NACC FTLD Sum of Boxes change score (negative values = decline). All models covaried for baseline age, sex, education, and each of their interactions with time. Person-specific random intercepts and time slopes were modeled. Results: Greater declines in smartphone usage over time were associated with worse baseline functional severity (CDR®+NACC FTLD Sum of Boxes x time: b=-0.412, p=0.001), executive functioning (z-score x time: b=0.892, p=0.014), memory (z-score x time: b=0.888, p=0.021), language (z-score x time: b=2.41, p<0.001), anxiety symptoms (NPI anxiety x time: b=-1.462, p=0.034), and smaller brain volumes (intracranial volume-corrected total gray matter x time: b=0.212, p<0.001). In the subset of 36 participants with longitudinal clinical data, greater declines in smartphone usage over time reflected more severe clinical progression over the same 12-18 month follow-up period (Sum of Boxes change score x time: b=0.482, p=0.028). Conclusions: These novel results provide support that changes in smartphone usage may reflect disease progression in FTLD. Smartphone usage trajectories were not specific to changes in particular cognitive domains, suggesting that these data may represent a more global marker of functioning. Future work is needed to develop passively collected smartphone metrics that may be more specific to neurobehavioral domains (e.g., keystroke data). With continued validation, these passive, digital, remote monitoring methodologies have potential to increase access to care among underserved populations at risk for dementia.

Custom Content

02/15/2024
12:00 pm - 01:15 pm
Room: Shubert Complex (Posters 1-60)

Poster Session 04: Neuroimaging | Neurostimulation/Neuromodulation | Teleneuropsychology/Technology

Final Abstract #3

Poster Symposium: Novel Technology-Based Approaches for Cognitive Assessment — Abstract 2

Longitudinal decline in smartphone usage relates to disease severity and clinical progression in frontotemporal lobar degeneration

Emily Paolillo, UCSF Memory and Aging Center, San Francisco, United States
Kaitlin Casaletto, UCSF Memory and Aging Center, San Francisco, United States
Annie Clark, UCSF Memory and Aging Center, San Francisco, United States
Jack Taylor, UCSF Memory and Aging Center, San Francisco, United States
Amy Wise, UCSF Memory and Aging Center, San Francisco, United States
Sreya Dhanam, UCSF Memory and Aging Center, San Francisco, United States
Mark Sanderson-Cimino, UCSF Memory and Aging Center, San Francisco, United States
Brandon Palacios, UCSF Memory and Aging Center, San Francisco, United States
Rowan Saloner, UCSF Memory and Aging Center, San Francisco, United States
Shubir Dutt, UCSF Memory and Aging Center, San Francisco, United States
Adam Boxer, UCSF Memory and Aging Center, San Francisco, United States
Adam Staffaroni, UCSF Memory and Aging Center, San Francisco, United States

Category: Teleneuropsychology/ Technology

Keyword 1: aging disorders
Keyword 2: dementia - other cortical
Keyword 3: technology

Objective:

Frontotemporal lobar degeneration (FTLD) is a common cause of early-onset dementia. There are several challenges to conducting in-person evaluations in FTLD (e.g., behavioral and/or motor symptoms, low base rates), creating an urgent need to examine remote and accessible assessment techniques. Passive digital monitoring methods are low burden and provide unique opportunities to capture naturalistic behavioral data reflecting cognitive decline in real time. This study utilized passively collected smartphone battery percentage data to characterize linear trajectories of smartphone usage over time and examined relationships with clinical indicators of disease severity and progression in FTLD.

Participants and Methods:

Participants included 172 adults enrolled in the ALLFTD Mobile App study (mean age=53.1 [SD=15.3]; 58% women; 96% White; 56% unimpaired; 20% prodromal FTLD; 24% symptomatic FTLD) who completed at least 3 months of passive smartphone monitoring via the ALLFTD Mobile App (mean monitoring period = 6.9 months, range = 3-18). Battery percentage was collected frequently (median collection interval = 46 min [IQR = 15-62]), and daily battery usage was calculated by summing consecutive declines in battery percentage throughout each day (a proxy for daily smartphone use; higher battery usage = more smartphone use). To assess different aspects of clinical disease severity at baseline, participants completed: the modified Clinical Dementia Rating plus FTLD behavior and language domains (CDR®+NACC FTLD); a neuropsychological battery measuring executive function, memory, and language (z-scored); the Neuropsychiatric Inventory (NPI); and structural brain MRI. Linear mixed effects models examined each index of baseline disease severity as a predictor of linear smartphone usage trajectories over time. In a subset of 36 participants who completed a follow-up CDR®+NACC FTLD at 12 or 18 months, additional linear effects models examined smartphone usage trajectories as a function of CDR®+NACC FTLD Sum of Boxes change score (negative values = decline). All models covaried for baseline age, sex, education, and each of their interactions with time. Person-specific random intercepts and time slopes were modeled.

Results:

Greater declines in smartphone usage over time were associated with worse baseline functional severity (CDR®+NACC FTLD Sum of Boxes x time: b=-0.412, p=0.001), executive functioning (z-score x time: b=0.892, p=0.014), memory (z-score x time: b=0.888, p=0.021), language (z-score x time: b=2.41, p<0.001), anxiety symptoms (NPI anxiety x time: b=-1.462, p=0.034), and smaller brain volumes (intracranial volume-corrected total gray matter x time: b=0.212, p<0.001). In the subset of 36 participants with longitudinal clinical data, greater declines in smartphone usage over time reflected more severe clinical progression over the same 12-18 month follow-up period (Sum of Boxes change score x time: b=0.482, p=0.028).

Conclusions:

These novel results provide support that changes in smartphone usage may reflect disease progression in FTLD. Smartphone usage trajectories were not specific to changes in particular cognitive domains, suggesting that these data may represent a more global marker of functioning. Future work is needed to develop passively collected smartphone metrics that may be more specific to neurobehavioral domains (e.g., keystroke data). With continued validation, these passive, digital, remote monitoring methodologies have potential to increase access to care among underserved populations at risk for dementia.