Multiple Principal Investigators: David E. Conroy (email) and Constantino M. Lagoa (Penn State University)
R61 HL164868
NIH Reporter listing
ClinicalTrials.gov registration: NCT05794178 

Physical activity and weight management are key components of ideal cardiovascular health but many young adults are insufficiently active and gaining weight rapidly (0.5-1.0 kg/year on average). Physical activity is a proven strategy for attenuating weight gain so there is a pressing need for effective interventions that reduce cardiovascular risk by motivating people to move more, sit less, and reduce weight gain. Mobile and wearable technologies are nearly ubiquitous among young adults and provide access to dense digital data about the person and their environment. This technology also provides a means of delivering interventions on a just-in- time basis so each person can receive the right intervention content at the right time. Inspired by the vision of precision behavioral interventions, we have applied system identification tools from control systems engineering to develop computational models and algorithms that optimize person-specific dosing of text messages to promote physical activity. In a series of preliminary studies, we (a) identified weather indices consistently linked with physical activity, (b) demonstrated the feasibility of long-term activity tracker wear and the acceptability of text messages among young adults, (c) enriched our computational model of physical activity using momentary weather data to characterize weather-graded responses to messages, and (d) designed a controller that uses person-specific parameters from the computational model and data on recent behavior and forecasted weather conditions to optimize the selection and timing of text message delivery. This controller is the basis for the Precision Adaptive Intervention Messaging (Precision AIM) intervention. In this application, we propose a single-site clinical trial to answer question, “Does Precision AIM increase insufficiently-active young adults’ physical activity and reduce weight gain more than randomly-assigned intervention messages (Random AIM) from the same message library or an activity tracker with no assigned intervention messages (No AIM)?” The specific aims of this project are (1) to evaluate the efficacy of Precision AIM compared to Random AIM and No AIM for increasing physical activity and reducing weight gain in insufficiently-active young adults, and (2) to identify characteristics of participants who respond more to Precision AIM than Random AIM or No AIM. We propose a three-arm randomized controlled trial to achieve these aims. Insufficiently-active young adults will receive a consumer activity tracker and be randomly assigned to one of three groups: Precision AIM, Random AIM, or No AIM. The intervention period will last for 12 months with a maintenance assessment at 18 months. The primary outcome is average daily step counts based on accumulating evidence that increasing this readily-interpretable and widely-available metric reduces cardiovascular risk in adulthood (assessed at baseline, 3, 6, 12, and 18 months). If successful, the underlying algorithmic analyses informed by dense data from wearable devices will provide a new and scalable approach for using consumer wearables in primordial and primary prevention of cardiovascular risk in young adults.