Abstract
Social support is a multidimensional construct that consists of the type of support, the direction of support, the sources or targets of support, and whether support is actual or potential. We used latent class analysis to uncover network types based on these dimensions and to examine the association between network types and well-being among 6,824 adults ( M age = 54 at T1) in the two most recent waves (1992–1993 and 2003–2005) of the Wisconsin Longitudinal Study. We found six classes of social support networks. Class membership at T1 significantly predicted changes in depressive symptomatology and self-rated health over time. Our findings are discussed in light of the utility of a pattern-centered approach for uncovering heterogeneity in the social networks of adults.