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Social Network Analysis in Schizophrenia: What it Adds to our Understanding of Social Functioning and Loneliness
Samuel J Abplanalp1,2, Michael F Green1,2, Keith Koziol1,2
1Desert Pacific Mental Illness Research, Education and Clinical Center, Veterans Affairs Greater Los Angeles Healthcare System, Los Angeles, CA 90073, United States.
Background And Hypothesis:
Reduced social networks contribute to social dysfunction and loneliness in schizophrenia. However, standard measures of social networks are broad and provide limited information about network structure or characteristics of network members. This study used egocentric social network analysis (SNA)-an approach that has rarely been applied in schizophrenia-to evaluate whether it provides added explanatory value for social functioning and loneliness. We did not specify directional hypotheses.
Study Design:
Individuals with schizophrenia (n = 54) and controls (n = 41) completed a social network interview. SNA metrics derived from the interview included constraint (network interconnectedness), education and race homophily (similarity between participants and network members), and ego-betweenness (the extent to which the participant connects otherwise unconnected alters). Hierarchical regressions within schizophrenia examined associations between SNA metrics, social functioning, and loneliness after accounting for social network size and negative symptoms.
Study Results:
People with schizophrenia had greater constraint than controls, suggesting more redundant networks. After accounting for social network size and negative symptoms, greater constraint (β = -.61, P = .01) and greater ego-betweenness (β = -.35, P = .02) were associated with greater social dysfunction. Lower education homophily (β = .35, P = .01) was associated with greater loneliness. Overall, SNA metrics explained an additional 12% of the variance in social functioning and 15% in loneliness.
Conclusions:
These findings suggest that SNA metrics could serve as more precise indicators of social impairment in schizophrenia than standard measures of social networks and clinical variables alone.
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