The law of non-usage attrition in a technology-based behavioral intervention for black adults with poor cardiovascular health.

Digital health innovations, such as telehealth and remote monitoring, have shown promise in addressing patient barriers to accessing evidence-based programs and providing a scalable path for tailored behavioral interventions that support self-management skills, knowledge acquisition and promotion of relevant behavioral change. However, significant attrition continues to plague internet-based studies, a result we believe can be attributed to characteristics of the intervention, or individual user characteristics. In this paper, we provide the first analysis of determinants of non usage attrition in a randomized control trial of a technology-based intervention for improving self-management behaviors among Black adults who face increased cardiovascular risk factors. We introduce a different way to measure nonusage attrition that considers usage over a specific period of time and estimate a cox proportional hazards model of the impact of intervention factors and participant demographics on the risk of a nonusage event. Our results indicated that not having a coach (compared to having a coach) decreases the risk of becoming an inactive user by 36% (HR = .63, P = 0.04). We also found that several demographic factors can influence Non-usage attrition: The risk of nonusage attrition amongst those who completed some college or technical school (HR = 2.91, P = 0.04) or graduated college (HR = 2.98, P = 0.047) is significantly higher when compared to participants who did not graduate high school. Finally, we found that the risk of nonsage attrition among participants with poor cardiovascular from "at-risk" neighborhoods with higher morbidity and mortality rates related to CVD is significantly higher when compared to participants from "resilient" neighborhoods (HR = 1.99, P = 0.03). Our results underscore the importance of understanding challenges to the use of mhealth technologies for cardiovascular health in underserved communities. Addressing these unique barriers is essential, because a lack of diffusion of digital health innovations exacerbates health disparities