Akademik Veri Yönetim Sistemi
JOURNAL OF SOCIAL SERVICE RESEARCH, 2025 (SSCI)
Self-rated health (SRH) is a generic measure of health influenced by socioeconomic status and regional disparities. Recognizing the underlying factors of SRH is critically important to better serve the community's needs and improve health and social services research. However, few studies identify the predictors of SRH by considering rural-urban dynamics from a developing country perspective by using a multistep machine learning (ML) analysis strategy. This study fills this void, by examining predictors of SRH using socioeconomic, poverty dynamics, and rural-urban differences. Data came from a cross-sectional national Income and Living Conditions Survey (ILCS) by the Turkish Statistical Institute (TurkStat) for the year 2020. Totally, 25,706 households were surveyed by TurkStat, and information was gathered by face-to-face interviews with individuals. A multidimensional ML analysis strategy is applied, and study findings show that chronic disease is the most important predictor of SRH. Our findings suggest that health and social services professionals should consider regional differences and the dynamics of chronic diseases to better understand the factors behind SRH. Future studies will incorporate the quality of care and accessibility dynamics of care to predict SRH. This will be helpful to better design, deliver, utilize, and evaluate health and social services.