THURS-104 - Analyzing Use Cases of Artificial Intelligence Tools to Promote Physical Activity

Brief Abstract Summary: To gain an understanding of how artificial intelligence (AI) tools can be used to promote physical activity. The use of technological devices that incorporate AI to promote physical activity has slowly progressed in the U.S; however, these devices have limited success in sustaining physical activity behavior among their users. User ability to sustain healthy behaviors could depend on several factors, which may range from their socioeconomic background to psychological motivating factors. The following AI devices served as use cases to promote physical activity: health gamification systems, mobile applications, work, education, and home-based exercise programs, virtual assistants, virtual reality, wearable technology, robots, and other devices. Devices that incorporate rewards and incentives to encourage exercise increased user motivation, and interventions tailored toward specific populations such as youth and young adults and older adults can also help increase exercising behavior.

Detailed abstract description: Regular physical exercise is important to the health and well-being of all individuals regardless of age, race, ethnicity, or any other demographic characteristic. The consequences of not exercising can contribute to heightened risk of both acquiring acute and chronic health conditions, such as cardiovascular disease, obesity, and stroke. The use of technological devices that incorporate artificial intelligence (AI) to promote physical activity has slowly progressed in the U.S., with a few experimental studies to prove its significance. However, these devices are limited in their ability to sustain physical activity behavior among users. User sustainability could depend on several factors ranging from their socioeconomic background to psychological motivating factors. Designing digital interventions by applying evidence-based practices can help understand these factors and improve sustainability. Research suggests that physical activity interventions guided by theoretical frameworks are more successful than non-theory-based physical activity interventions, yet there is limited to no application of theory in published research that evaluates the use of AI devices to promote physical activity. Theoretical application to design interventions can also ensure that these interventions are tailored to meet population needs, including immigrant populations and populations with low SES. The purpose of this study was to perform a theoretical exploration of papers that evaluate AI devices designed to promote physical activity in the U.S. and how functional components of these devices align or could be improved based on past successes of interventions that have been guided by theory to improve physical activity. The following AI devices served as use cases to promote physical activity: health gamification systems (25%), mobile applications (21%), work, education, and home-based exercise programs (12%), virtual assistants (11%), virtual reality (10%), wearable technology (10%), robots, (8%), and other devices (4%). Devices that incorporate rewards and incentives to encourage exercise increased user motivation to exercise, and interventions tailored toward specific populations such as youth and young adults, older adults, or individuals at risk of or either have a chronic disease or are stroke survivors can increase exercising behavior; the importance of incorporating technology to different age groups helps captivate different crowds. Aligned with the constructs of intrapersonal and interpersonal social and behavior change theories, findings supported the premise that individuals who were more willing and motivated to participate in physical activities through the use of technology had positive attitudes toward the behavior, were exposed to an environment that facilitated the behavior, and were able to achieve the self-efficacy needed to exercise.