ArticleRisk management and healthcare policy2026
How Does Social Frailty Evolve Among Patients with Prostate Cancer? Evidence from Regression Models versus Fuzzy Set Qualitative Comparative Analysis.
Article in Risk management and healthcare policy, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: Social frailty is a critical indicator of declining social functioning and affects quality of life in older adults. Prostate cancer patients face greater challenges in social frailty than the general elderly population, due to the physical burden of the disease, treatment-related adverse effects, and psychological stress. However, its multidimensional influencing factors and risk patterns remain unclear. Objective: To identify key factors and configurations associated with social frailty in patients with prostate cancer. Methods: This study was guided by the Health Ecology Model and used a cross-sectional design. A total of 211 patients were recruited from Shanghai East Hospital between April and September 2025. Structured questionnaires assessed sociodemographic characteristics, family function, living space, depressive symptoms, and social frailty. Data were analyzed using hierarchical regression and fuzzy-set qualitative comparative analysis (fsQCA), enabling the examination of both net effects and complex configurational pathways. Results: The mean age of participants was (69.20 ± 5.63) years, and the prevalence of social frailty was 39.81%. The final regression model was significant (F=101.37, Conclusion: Social frailty among patients with prostate cancer reflects the influence of psychosocial, behavioral, and environmental conditions. Social frailty was significantly associated with depression, family function, living space, residence, and exercise frequency. High social frailty was associated with specific configurations of these factors. These results advance understanding of social frailty from isolated risk factors to combined pathway patterns. They help inform targeted screening and tailored intervention strategies for this population.
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