Leveraging Technology to Blend Large-Scale Epidemiologic Surveillance With Social and Behavioral Science Methods: Successes, Challenges, and Lessons Learned Implementing the UNITE Longitudinal Cohort Study of HIV Risk Factors Among Sexual Minority Men in the United States

Abstract

Abstract The use of digital technologies to conduct large-scale research with limited interaction (i.e., no in-person contact) and objective endpoints (i.e., biological testing) has significant potential for the field of epidemiology, but limited research to date has been published on the successes and challenges of such approaches. We analyzed data from a cohort study of sexual minority men across the United States, collected using digital strategies during a 10-month period from 2017 to 2018. Overall, 113,874 individuals were screened, of whom 26,000 were invited to the study, 10,691 joined the study, and 7,957 completed all enrollment steps, including return of a human immunodeficiency virus–negative sample. We examined group differences in completion of the steps towards enrollment to inform future research and found significant differences according to several factors, including age and race. This study adds to prior work to provide further proof-of-concept for this limited-interaction, technology-mediated methodology, highlighting some of its strengths and challenges, including rapid access to more diverse populations but also potential for bias due to differential enrollment. This method has strong promise, and future implementation research is needed to better understand the roles of burden, privacy, access, and compensation, to enhance representativeness and generalizability of the data generated.