RAPID: Collaborative Research: Social interactions. social connectedness, and health outcomes during the COVID-19 pandemic

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Good mental and physical health depend on a strong sense of social connectedness. The restrictions of the COVID-19 pandemic, and the resultant social isolation and loneliness, have caused that connectedness to deteriorate. Despite decades of research, relatively little is known about the characteristics of social interactions that lead to improvements in social connectedness and, ultimately, to improved health. This project seeks to gain better understanding of how social interactions support social connectedness. It examines the effects of the social isolation and psychological distress that result from social distancing and stay-at-home policies. The research considers activities people perform together, the types of people who serve as interaction partners, the emotional tone and the modality of interaction (in person, phone, text, or video). The study uses longitudinal surveys with a nation-wide panel of U.S. adults to assess the ways in which social interactions provide the route through which social ties are maintained, the regulation of relationships occurs, and social support is exchanged. The project will ultimately inform the development of health-related interventions in this and future pandemic situations. This project seeks to advance theory about how everyday social interactions influence general social connectedness, including loneliness, perceived social support, and strength of social ties. In addition to advancing theory, the research addresses the more immediate need to understand the consequences of social distancing policies. Identifying the most beneficial social interactions can help support just-in-time interventions to improve social connectedness and related public health recommendations. To achieve these goals, the research collects longitudinal survey data over a three-week period in which U.S. adults complete multiple surveys each day to describe the frequency and characteristics of their social interactions. End-of-day surveys measure social connectedness (loneliness, perceived social support, and tie strength) and mental health (positive and negative affect, depression, anxiety, and perceived stress). Statistical techniques for longitudinal data, including structural equation modeling and latent change score analysis, test the relationship between interaction characteristics and the end-of-day surveys. Insight gained by this research will inform future efforts in implementing health-related behavioral change recommendations.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.