Beyond size and structure: how social network quality influences diabetes management self-efficacy in black/African American men

Abstract

The quality of social connections plays a vital role in chronic disease management, particularly for populations experiencing health disparities in Type 2 diabetes (T2D) outcomes. This study examined the influence of social network characteristics on diabetes management self-efficacy among Black/African American men with T2D, a population experiencing significant health disparities. Using a national sample of 1225 Black/African American men, we investigated how network composition, support patterns, and perceived health behaviors within networks relate to diabetes self-efficacy. Results revealed complex relationships between social network characteristics and self-efficacy. Having highly supportive network members emerged as the strongest positive predictor of diabetes self-efficacy (β = 0.27, p < 0.001), followed by network members’ perceived engagement in healthy eating (β = 0.17, p < 0.001). Having a higher proportion of friends in one’s network was positively associated with self-efficacy (β = 0.08, p = 0.005), while having a higher proportion of infrequent contacts showed a negative association (β = – 0.15, p = 0.001). Other network composition variables, including family relationships and healthcare provider presence, showed no significant associations with self-efficacy. Network structural characteristics, including size (β = − 0.01, p = 0.78) and relationship heterogeneity (β = 0.02, p = 0.49), also showed no significant associations. These findings suggest that the quality and nature of social relationships, particularly the presence of highly supportive friends and those modeling healthy behaviors, may be more important than network size or composition in promoting diabetes self-efficacy among Black/African American men. Results indicate a need for interventions that focus on fostering quality friendships and encouraging regular contact within networks, while also leveraging the positive influence of health behavior modeling among network members.