Social Network Analysis of Self-Management Behavior Among Older Adults With Diabetes.

Abstract

Objective: This study explores the influence of social network structures on self-management behaviors among older adults with diabetes in rural Korean villages, focusing on dietary management, physical activity, and blood glucose monitoring.

Design: Employing social network analysis (SNA), the study assessed network structures in three villages, focusing on variations in degree, closeness, and betweenness centralities to understand their impact on health behavior dissemination and adoption.

Results: The analysis identified significant differences in network configurations across the villages. Village C, characterized by the highest closeness centrality, facilitated the efficient diffusion of health-related information, thereby promoting the rapid adoption of self-management behaviors. In contrast, Village B exhibited a prominent central node with considerable influence, underscoring its potential as a strategic focal point for targeted health interventions.

Conclusion: Social network analysis is useful for identifying influential nodes within community structures to enhance chronic disease management strategies. By tailoring interventions to the unique attributes of a community's network, significant improvements in diabetes self-care efficacy can be achieved. This approach presents a scalable and sustainable framework for community-oriented health interventions. It provides a foundation for further research into the structural and functional dynamics of diabetes self-management networks.