Strengthening Care Networks: Applying Caring Life Course Theory to Enhance Cardiac Rehabilitation through Social Network Analysis

The Caring Life Course Theory (CLCT) offers a comprehensive framework for analyzing care dynamics across the lifespan, focusing on relationships and transitions in care. This study applies CLCT to explore cardiac rehabilitation (CR) programs, particularly in rural and socio-economically disadvantaged areas of South Australia, where CR engagement and completion rates are notably low. By examining these programs through the lens of CLCT, we aim to identify patterns and relationships that could inform targeted interventions to improve CR outcomes. This study conducts a secondary analysis of qualitative data from 15 CR programs originally collected by Beleigoli et al. (2024). The data, comprising interviews and focus groups with CR patients and clinicians, were analyzed using NVivo for thematic coding based on CLCT constructs (Pinero de Plaza, et al. 2024). We then employed Social Network Analysis (SNA) to quantify the relationships among these constructs. Key SNA metrics, including degree centrality, betweenness centrality, and clustering coefficient, were used to evaluate the prominence of each construct within the care network and identify clusters and key relational pathways within the CR context.

The SNA revealed significant insights into the structure of the CR care network. Degree centrality identified Care Network (426 ties), Care Transition (346 ties), and Care Provision (CP) (278 ties) as the most connected nodes, highlighting their central roles in the network. Betweenness centrality underscored the importance of Care Network and Capability as critical intermediaries, suggesting their roles as crucial bridges facilitating interaction and information flow across the network. Strong relational ties were observed between Care Network ↔ Capability (tie strength: 73), Care Network ↔ Care-from-others (73), and Capability ↔ Self-care (55), indicating robust interdependencies among these constructs. Cluster analysis uncovered two primary clusters: a core cluster consisting of Care Network, Care Transition, Care Provision, and Capability, and a secondary cluster centered on Self-care, Capacity, and Care-from-others. These clusters reflect CR programs' dual focus on systemic care processes and individual capacities. Peripheral nodes, such as Care Provision Package (degree centrality: 67) and Care Biography (53), played less central but contextually important roles in providing personalized care and understanding patient histories. The integrated nature of these constructs underscores the pivotal role of Care Network and Capability in effective CR delivery. Strengthening these constructs could significantly enhance CR engagement, particularly by improving Self-care and Care-from-others. Policymakers should prioritize developing robust care networks and enhancing patient capabilities, especially in rural areas with limited resources. Training programs can leverage these insights to equip healthcare providers with the skills and knowledge to support self-care and external care provision effectively.

This study demonstrates the utility of SNA in mapping and understanding the complex interrelationships within CR programs through the CLCT framework, with a specific focus on care networks. By identifying key constructs and relationships, the findings offer actionable insights that could be utilized to strengthen care networks and improve CR engagement and outcomes, particularly for underserved populations. Future research should focus on refining these insights and developing targeted interventions that address the specific needs of these groups.