CAREGIVER BURNOUT RESPONSE IN CARING FOR STROKE PATIENTS, SOCIO-DEMOGRAPHIC ANALYSIS WITH BINARY LOGISTIC REGRESSION - Sarah, Maita; Br Ginting, Dameria; Astuty, Mazly (Jurnal Aisyah : Jurnal Ilmu Kesehatan, 2025)
Background: Over the previous two decades, various studies have looked at the burden of stroke caregivers, given that patients typically require long-term care, the role of caregivers at home is critical.Objective: to analyze caregiver burnout response in caring for stroke patients with socio-demographic Methods: A cross-sectional design was used in a correlational analytical study. The sampling technique used was a non-probability sampling is combined with a purposive sampling approach. The population in this study was all caregivers at Medan, North Sumatra, with an average of 113 caregivers. The independent variables were Socioeconomic status, education level, Residence, Age, Employment status, and Wealth status, and the dependent variable was burnout response. Data were collected using the instruments in this study are the Maslach Burnout Inventory (MBI) with Cronbach’s ? coefficient values of 0.837, 0.869, and 0.881 and test-retest reliability was high (p??0.001). Statistical test using the Binary Logistic Regression.Results: Primary education (AOR 2.525; 95% CI 2.522-2.525), Urban residence (AOR 1.092; 95% CI 1.092-1.097), 35-39 age group (AOR 1.772; 95% CI 1.772-1.774), Unemployed (AOR 1.371; 95% CI 1.371-1.375), wealth status (AOR 0.870; 95% CI 0.870-871). Conclusion: Socioeconomic status, education level, place of residence, age, employment status, and wealth status all have a major impact on caregiver tiredness when caring for stroke patients.