PROJECT SUMMARY/ABSTRACT
At present, one in 10 Americans age 65 and older has Alzheimer's dementia. Further, the global prevalence of
dementia is expected to triple from 50 million to over 150 million by 2050. Given this trend, there is a need for
increasingly efficient, objective, and sensitive methods to characterize cognition, assess risk, and discriminate
individuals at various stages of the disease spectrum. Traditional neuropsychological assessments have been
extensively validated for these purposes, yet present several methodological drawbacks such as limited
ecological validity, practice effects, and burdensome testing and scoring procedures that are prone to human
error. On the other hand, smartphones are ubiquitous, are owned by older adults at increasing rates, and
present a unique method to capture subtle cognitive and behavioral profiles in everyday life, outside of the
laboratory or clinic. In the proposed observational study, we aim to explore the validity of a digital phenotyping
protocol as a novel method for characterizing cognition and function among a heterogeneous group of older
adults. Specifically, we will investigate the relations between passively captured smartphone-based digital
features and gold-standard neuropsychological measures. We also will explore optimal sampling rates for
collection of digital data along with clinically-useful digital phenotypes to inform future studies. A total of 90
participants age 65 and older with normal cognition, mild cognitive impairment, and mild Alzheimer's dementia
will be recruited from the Philadelphia region and from a pool of eligible participants who have completed
recent aging studies. Participants will use their own personal smartphones naturally during a four-week study
period while a secure software application unobtrusively and continuously obtains de-identified raw sensor-
based data spanning domains including device activity and usage, spatial trajectories and mobility, and social
interactions. Daily surveys delivered via the study software will be used to complement the passively collected
data. Participants also will complete traditional neuropsychological measures at a baseline visit to examine
construct validity. This study will explore whether digital phenotyping may provide a valid, highly efficient, and
naturalistic method for tracking cognition, function and disease burden both cross-sectionally and, eventually,
over time. If successful, this tool can be applied in several clinical and research contexts to yield improved
assessment efficiency, enhanced diagnostic accuracy, and personalized treatment interventions, which
together will generate tremendous cost savings and improved health outcomes. A training plan has been
designed in consultation with experts in the fields of digital phenotyping, everyday cognition and function in
aging populations, and secure computer systems to develop the applicant's expertise in designing and
adapting digital phenotyping platforms for use in aging populations, longitudinal data analysis for continuous
multivariate data, and security protections related to personal digital data.