Optimizing a technology-based body and mind intervention to prevent falls and reduce health disparities in low-income populations - PROJECT SUMMARY/ABSTRACT Falls and fear of falling (FOF) are the leading cause of injury, disability, and hospitalization in racially diverse low-income older adults (LOA). Lack of motivation, limited resources, low education, and inconvenience remain barriers to participate in fall prevention programs. More than half of older adults have maladaptive fall risk appraisal (FRA), a condition in which there is a discrepancy between perceived fall risk (levels of FOF) and physiological fall risk (balance performance) which may impede physical activity (PA). To help address maladaptive FRA; we developed a fall risk appraisal matrix, a graphical grid categorizing levels of FOF (Mind) and levels of balance (Body) into four quadrants: 1) rational FRA (low FOF and normal balance), 2) incongruent FRA (low FOF despite poor balance), 3) irrational FRA (high FOF despite normal balance), and 4) congruent FRA (high FOF and poor balance). We developed a novel, 8-week technology-based, individualized, in-home Physio-fEedback Exercise pRogram (PEER), which includes a) physio-feedback using a real-time portable innovative technology—the BTrackS Balance System: BBS; b) cognitive reframing based on a novel fall risk appraisal matrix; and c) peer-led exercise by focusing on balance and strength training. Our R03 findings support the feasibility and acceptability of using BBS technology on screening LOA with maladaptive FRA, highlight the importance of reducing sedentary time and increasing moderate to vigorous physical activity (MVPA) time to help shift from maladaptive to adaptive FRA. Critically, we found that none of our LOA had ever had their fall risk and FOF assessed before our study and their data reveal a strong relationship between FOF and negative self-perceptions of aging. In our published pilot study, we found that the technology-based PEER intervention had significant improvements in dynamic balance, reduced fall risk, and facilitated maladaptive to adaptive shifting; however, our limited sample of LOA (40% of total) prevents strong conclusions about effectiveness in this group. We use a clustered randomized controlled trial, and the intervention will be offered at the low-income independent living communities/units in Orlando, FL through our partnership with community-based & public health organizations. We will collect data at baseline (T1) and measure outcomes after program completion (T2), follow up at 3-months (T3), and 6-months (T4). Low-income older adults (n=340) will be enrolled if they are ≥60 years old, cognitive intact, and able to stand without assistance. We aim to 1) examine the effects of the technology-based PEER intervention on fall risk, dynamic balance, and accelerometer-based physical activity; 2) examine the effects of the intervention on fall risk appraisal shifting and negative self-perceptions of aging; and 3) explore participants’ experiences with the intervention and potential barriers to access and adoption of technology-based PEER intervention. This study addresses the public health problem with the optimization of a technology - driven tailored approach that can operate in low-resource environments with unlimited users to prevent falls and reduce health disparities.
