Abstract
OBJECTIVES: This study aimed to investigate how individual, problem-related, and environmental factors interact to influence self-management behaviours among rural older adults with multimorbidity in China, to inform more context-sensitive interventions. METHODS: A cross-sectional study was conducted in 9 healthcare facilities across Zhejiang Province, China, from July 2022 to May 2023, involving 487 rural older adults with multimorbidity via convenience sampling, who had been diagnosed with 2 or more chronic conditions. Data were collected through questionnaires and electronic health records to assess self-efficacy, psychological resilience, physical symptoms, the Charlson Comorbidity Index, social support, and resource accessibility. Fuzzy-set qualitative comparative analysis was employed to explore the complex, non-linear interactions between contextual factors, ultimately determining the sufficient conditions for self-management behaviours. RESULTS: Correlation analyses revealed positive associations between self-management behaviours and self-efficacy, psychological resilience, social support, and resource accessibility (r = 0.690-0.850, all P < 0.001), with self-efficacy (r = 0.784) and social support (r = 0.850) demonstrating the strongest correlations. Regression analysis revealed that self-efficacy (β = 0.385) and social support (β = 0.372) were the strongest factors of self-management behaviours. Fuzzy-set qualitative comparative analysis identified six factor configurations, categorized into four contextual types: "triple-enabling context," "symptom-resource driven context," "resource deficiency context," and "symptom-disease overwhelmed context." Self-efficacy was consistently identified as a core condition across all configurations. CONCLUSIONS: Self-management among rural older adults with multimorbidity is shaped by complex, context-dependent interactions. Effective interventions should prioritize enhancing self-efficacy, expanding access to resources, and tailoring strategies to distinct contextual profiles. The study also demonstrates the utility of fuzzy-set qualitative comparative analysis for advancing context-sensitive healthcare solutions.