Developing a sensor-based mobile application for in-home frailty assessment: a qualitative study

Background Frailty syndrome disproportionately affects older people, including 15% of non-nursing home population, and is known to be a strong predictor of poor health outcomes. There is a growing interest in incorporating frailty assessment into research and clinical practice, which may provide an opportunity to improve in home frailty assessment and improve doctor patient communication. Methods We conducted focus groups discussions to solicit input from older adult care recipients (non-frail, pre-frail, and frail), their informal caregivers, and medical providers about their preferences to tailor a mobile app to measure frailty in the home using sensor based technologies. Focus groups were recorded, transcribed, and analyzed thematically. Results We identified three major themes: 1) perspectives of frailty; 2) perceptions of home based sensors; and 3) data management concerns. These relate to the participants’ insight, attitudes and concerns about having sensor-based technology to measure frailty in the home. Our qualitative findings indicate that knowing frailty status is important and useful and would allow older adults to remain independent longer. Participants also noted concerns with data management and the hope that this technology would not replace in-person visits with their healthcare provider. Conclusions This study found that study participants of each frailty status expressed high interest and acceptance of sensor-based technologies. Based on the qualitative findings of this study, sensor-based technologies show promise for frailty assessment of older adults with care needs. The main concerns identified related to the volume of data collected and strategies for responsible and secure transfer, reporting, and distillation of data into useful and timely care information. Sensor-based technologies should be piloted for feasibility and utility. This will inform the larger goal of helping older adults to maintain independence while tracking potential health declines, especially among the most vulnerable, for early detection and intervention. Keywords: Frailty, wearable, health services. Supplementary Information The online version contains supplementary material available at 10.1186/s12877-021-02041-z.

Objectives: 1) create metrics for lifting techniques and transferring mechanisms, 2) calibrate sensors for data collection 3) identify potential injurious posture among home health aides (HHAs) while transferring patients. Participants: 7 HHAs and a physical therapist. Interview and sensor data were collected. Outcome variables included improper lifting techniques and improper body mechanisms. Obesity of HHAs was associated with worse scores of body mechanics (p < 0.0001), while fear of injury with better body mechanics (p < 0.0001). GEE results identified that twisting the spine during transfers (OR = 6.3; 95% CI: 1.09-36.7) and not using a wide support base when lifting from supine to sitting (OR= 6.0, 95% CI: 2.03-17.7) were associated with improper lifting technique and body mechanics. Results show it is viable to use sensor technology to collect HHAs' data to design intervention for injury prevention. A larger-scale study is needed to validate the results.

NEW ACCELEROMETRY PATTERNS IN FRAILTY: HOURLY ACTIVITY AND VARIANCE.
Megan Huisingh-Scheetz, 1 Kristen Wroblewski, 1 Linda Waite, 1 Elbert Huang, 1 Donald Hedeker, 1 and L. P. Schumm 1 , 1. University of Chicago, Chicago, Illinois, United States Wearable sensors may improve our ability to identify frailty in the community. Frailty has been historically defined, in part, by reduced average activity; however, new analytic methods of aggregate, free-living accelerometry data suggest that frailty may be more fully characterized above and beyond reduced average activity. Using mixed-effect regression models of awake hourly activity from the National Social Life, Health and Aging Project dataset, we have shown that frail adult activity is most reduced in the morning relative to pre-and non-frail adults rather than the afternoon or evening. High residual between-and within-subject activity variance in this model prompted further study of activity variance. A follow-up analysis using a mixed-effect locationscale model of hourly activity data revealed that increasing frailty in older adults is associated with greater betweensubject as well as within-subject hourly activity variability, particularly in the morning and afternoon. Study implications and future directions will be discussed.

DEVELOPING A SENSOR-BASED MOBILE APPLICATION FOR IN-HOME FRAILTY ASSESSMENT: A QUALITATIVE STUDY
Frailty is an important concept in the care of older adults, and there is great interest in incorporating user-friendly frailty assessments into research and clinical settings. In-home, sensor-based technologies may provide a more dynamic, sensitive, and accurate assessment of frailty measures. To investigate user perspectives for use of sensor-based technologies and mobile applications, we held five focus groups with community-dwelling older adults (n= 10), their informal caregivers (n=9), and medical professionals (n=8). We used qualitative inductive analysis to organize thematic content. Caregivers and care-recipients viewed the early identification of frailty as beneficial, but highlighted the need for secure data infrastructure and clear demonstration of how frailty assessment would improve care. They also expressed concerns that technology-based communication could reduce in-person interactions. Medical providers noted the utility of objective data for difficult conversations with caregivers of frail patients, but worried about resources for analyses and interpretation of sensor-based health information. A profusion of technologies and protocols have been developed to more effectively assess and deliver care to older adults with cognitive impairment, challenged health and declining function. These technologies take advantage of important developments in sensing and pervasive computing, wearable technologies, mobile and wireless communications, and "big data" analytics. Despite great promise challenges remain to realizing their full potential and achieving wider uptake and dissemination in research and practice. This presentation will review and provide an overview of major technologies, their integration, and their use-cases, as well as key challenges present in the current landscape. The presentation will highlight ongoing developments addressing these challenges with particular attention to the Collaborative Aging Research using Technology (CART) initiative supported by the NIH and VA, an initiative directed toward providing an open technology research platform to be used by diverse investigators across the U.S. to facilitate and improve aging research using technology.

AFU PRINCIPLES IN ACTION: ENGAGING STUDENTS THROUGH HANDS-ON AGE-RELATED ACTIVITIES
Cassandra Barragan, 1 and Stephanie Wladkowski 1 ,

Eastern Michigan University, Ypsilanti, Michigan, United States
The Age-Friendly University (AFU) Initiative is a global network of universities working to embrace and promote the growing population of older adults (OAs) on campuses. Integrating inter-generational learning is a proven benefit to share knowledge (Gerpott, Lehmann-Willenbrock, & Velopel, 2017) and to mutually benefit both older and more traditional learners (Pstross, Corrigan, Knopf, et al., 2017). To thoughtfully develop AFU initiatives on their campus, one midwestern university created an educational activity for students to better understand the needs of OAs. This presentation will cover results of this activity and offer suggestions for aging-focused learning activities. In winter 2019, 23 undergraduate students from 5 disciplines participated in a guided sensory activity with 5 Masters in Social Work (MSW) students that simulated impaired vision, hearing, and dexterity. Afterwards, using the AARP walking audit, they walked campus to understand challenges those with limitations might face. Students then completed a guided reflection and thought of ways to advocate for anyone with physical challenges, both off and on campus. This activity resulted in several successful learning outcomes and provided concrete experiences, establishing grounds to think about advocacy in a practical way. First, the undergraduate students presented their experiences at a campus-wide activism and advocacy event. They aimed to 1) increase awareness of the challenges those with visual and physical challenges and 2) promote the AFU initiatives. MSW students further analyzed their experience from a policy perspective and presented to the AFU steering committee with recommendations to influence policy in alignment with the AFU principles. Senior mentoring programs have been established that provide medical students exposure to a community-dwelling older adult mentor with whom they meet multiple times throughout the program. The goal of these programs is to expose students to healthy older adults, increase knowledge of geriatrics, and prepare them to care for an aging population. However, even while participating in a senior mentoring program, health professions students still demonstrate some discriminatory language towards older adults (e.g., Gendron, Inker, & Welleford, 2018). In fact, research suggests ageist practices occur, intentionally or not, among health professions in disciplines such as medicine, nursing, and social work and even within assisted and long-term care facilities (e.g., Bowling, 1999;Dobbs et al., 2008;Kane & Kane, 2005). We evaluated a senior mentoring program to gauge the impact of a new pedagogical approach and to gain a deeper understanding of the learning gained in relation to ageism and elderhood. This qualitative content analysis explored first-year medical students' opinions of their own aging and attitudes towards caring for older adults. Students (n = 216) participating in a brief curriculum model of a senior mentoring program responded to the following openended prompts before and after the program: 1) How do you feel about your own aging?; 2) How do you feel about working with older adult patients after you complete your