Monitoring Health in Older Adults Using mHealth Technology: Framingham Offspring Study

Abstract How to engage and retain older adults in longitudinal mHealth research is virtually unknown. This is of great public health importance as many older adults have barriers to obtaining health care that technology may overcome by permitting in-home monitoring of health including cognitive function. Using mHealth technologies

to obtain data more frequently and in real life settings, vs. research center examinations that occur years apart presents a transformational opportunity for cohort studies and may lead to practical methods for monitoring risk of Alzheimer’s disease and related disorders (ADRD). We previously developed an innovative, scalable digital

cardiovascular health monitoring system, the “electronic Framingham Heart Study” (eFHS)8 for use in middle- aged adults, thus providing foundational experience that will support this proposal. We will extend eFHS to enhance a smartphone app tailored for older participants. The app will capture patient-reported outcomes,

cognition, physical performance, social support, and health events (falls, hospitalizations). We plan to investigate the usefulness of the mHealth system for monitoring health-related behaviors and we will relate the digital data to brain aging including preclinical ADRD using in-person research grade neuropsychological (NP)

testing and brain MRI data. Specific Aims: Aim 1. Enhance engagement strategies and identify factors associated with successful use of the smartphone app and smartwatch among older adults at 3 months and 6 months. Successful use will be defined based on adherence, including: 1) app-based completion of surveys and cognitive and performance

tasks (n=850); 2) wearing the smartwatch daily (n≈500). We will identify participant (e.g., age, sex, cognitive status) and system-related factors (e.g., user-interface, navigation), that affect adherence over 3 and 6 months. Aim 2. Compare the smartphone app-based data to research grade measures of brain health (NP

testing batteries, brain MRIs) collected in the FHS Research Center on the same participants. We will compare the app-based measures with measures of brain health, including NP test measures (global cognition and 4 domains: executive function, memory, language, visuospatial) and brain MRI markers (total brain

volume, hippocampal volume, white matter hyperintensity volume). Sub Aim 2a: Construct a digital frailty phenotype. Aim 3. Examine measures of physical activity and heart rate from the Apple Watch over 90 days with research grade measures of brain health (see Aim 2). Our application will provide critically needed knowledge on how older adults engage with mHealth devices

and will provide insights on the benefit of mHealth data to monitor the health of older adults in clinical and research settings. Digital biomarkers may be powerful tools to monitor risk factors/behaviors for ADRD and to identify older adults at risk for cognitive and physical decline.