Care model selection for older adult stroke survivors with disabilities: insights from the eighth wave of CLHLS data and influencing factors - Xiang, Liping; Liu, Qin; Shi, Zijuan; Zhang, Li; Wu, Li; Chen, Yuqin (Frontiers in Public Health, 2024)
Background Analyzing the differences in caregiving models for disabled older adult individuals after stroke and the influencing factors, to provide a basis for addressing relevant social demographic issues. Methods The older adult diagnosed with stroke were screened from the Chinese Geriatric Health Survey (CLHLS), and were further divided into subgroups of disability, which was based on their ability of or whether they need help in performing activities such as dressing, bathing, eating, toileting or bowel and bladder control using the international common Katz scale. The care model was divided into formal care, informal care and home care. Multivariate logistic regression was used to screen the influencing factors of the choice of care model for the disabled older adult after stroke. Results The results of univariate analysis showed that there were statistical differences in the choice of care mode among different ages, household registration types, number of children, years of education, degree of disability, community services, retirement pension, marital status and medical insurance. Multiple logistic regression showed that, The rural older adult with more children, shorter education years, living with spouse and no help from community tend to choose informal care. Older adult people with higher levels of education, urban household registration, and access to community services are more likely to choose formal care. Older adult women with multiple children are more likely to receive care from their children. Conclusion In the future, vigorous support for the development of formal caregiving institutions and the improvement of the management system of formal caregiving will help enhance the subjective initiative of disabled older adult individuals in choosing caregiving models and alleviate the burden of family caregiving.