Mixed Methods for Research on Support Networks of People Experiencing Chronic Illness and Social Marginalization.

Abstract

Substantial research has focused on how social networks help individuals navigate the illness experience. Sociologists have begun to theorize beyond the binary of strong and weak social network ties (e.g., compartmental, elastic, and disposable ties), citing the social, economic, and health conditions that shape their formation. However, limited research has employed mixed social network methods, which we argue is especially critical for examining the "non-traditional" social support networks of marginalized individuals. We employ quantitative social network methods (i.e., the egocentric network approach) in addition to in-depth interviews and observations, with a novel tool for capturing network data about social groups, to surface these kinds of supportive relationships. Using the case of "nameless ties"-non-kin, non-provider ties who were unidentifiable by given name or were grouped by context or activity rather than individually distinguished-we show how mixed social network methods can illuminate supporters who are commonly overlooked when only using traditional social network analysis. We conclude with a proposal for mixed methods and group alter approaches to successfully observe liminal support ties that is ideal for research about individuals experiencing chronic disability, poverty, housing insecurity, and other forms of social marginalization.