A Personalized Health Behavior System to Promote Well-Being in Older Adults

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Abstract People aged 65+ will represent 21% of the U.S. population and increase to about 80 million by 2040, and the oldest old (age 85+) will number ~ 14.1 million. Population aging presents both opportunities and challenges for our healthcare, the economy, and existing social support systems. Many older adults especially the oldest old, minorities and those of lower Socio-Economic status (SES) are particularly vulnerable to social isolation, poor diet, and decreased levels of physical activity each of which influence morbidity and mortality. Mobile-based, tablet-based, and in-home technologies provide an excellent opportunity for projecting behavior- change interventions and social support into the everyday life of older adults at great economies of scale. The objectives of this study are to examine the usability and efficacy, for diverse older adults, of a new tablet-based dynamic system: the Fittle Senior System (FSS) that will provide: (1) personalized behavior-change programs for improved diet and increased physical activity and (2) online social interaction and support from small teams pursuing similar goals. The system builds on two technology-based systems developed by the investigative team: (1) the computer-based PRISM system, designed for older populations to support social connectivity and well-being, and (2) the Fittle+ mobile platform designed to support positive health behavior change through integrated online social support and personalized coaching based on artificial intelligence (AI). The study will be conducted in two phases. During Phase 1 we will develop and pilot test the FSS with representative samples of older adults. Phase 2 will involve a two group randomized trial where participants will be randomized to the Fittle Senior System (FSS, an adaptive coaching and social support system using mobile technology) or to a paper-based psycho-educational (BPE) control condition following a baseline assessment. The duration of the intervention phase will involve an active 12-week intervention phase followed by a 12-week maintenance phase. We will recruit and randomize 180 community dwelling adults aged 65+ years, who live alone and are at risk for social isolation (90 per condition - 30 White Caucasians, 30 Black/African Americans and 30 Hispanic Americans). We will recruit males and females commensurate to the gender proportions represented in this age group and work to ensure that we have sufficient representation from the “oldest old” cohort. Participants will be assessed at baseline, 3mths post active intervention and 3mths post maintenance (6mths following active intervention) on clinically significant measures of health and health behaviors and indices of social support. We will also gather information on potential moderating (e.g., ethnicity, age) and mediating variables (e.g., health self-efficacy), which will be examined using multilevel modeling techniques guided by current theories of behavior change and technology acceptance and use among older adults.