Understanding and Predicting End-of-Life Care Preferences Among Urban-Dwelling Older Adults in China

Context

Understanding older adults’ preferences for end-of-life care (EoLC) is vital for respecting their wishes and informing effective service planning and policy development. Previous research has examined factors influencing different dimensions of EoLC preferences separately, but few studies have explored these dimensions as interconnected patterns and viewed older adults as heterogeneous using a person-centered approach.

Objectives

This study aims to: 1) identify heterogeneous latent patterns across seven dimensions of EoLC preferences among Chinese older adults; 2) describe and explain these patterns; and 3) predict membership within these patterns.

Methods

: Survey data from 646 urban-dwelling older adults aged 60 and above across 26 provincial-level administrative divisions in Mainland China were analyzed. EoLC preferences regarding willingness to know diagnosis, willingness to know prognosis, decision-maker, treatment goals, place of care, caregiver, and setting advance directives were assessed alongside demographics, resources, knowledge and attitudes, and caregiving/bereavement experiences. Latent class analysis (LCA), 3-step regressions, and Catboost machine learning models were employed to identify subgroups, examine between-group differences, and predict subgroup membership, respectively.

Results

LCA identified three latent patterns: “low self-determination, quality-goal, family-oriented care” (9.1%), “high self-determination, quality-goal, family-oriented care” (54.0%), and “high self-determination, quantity-goal, professional-oriented care” (36.9%). Significant between-group differences were found in education, marital status, living arrangements, family income, social support, EoLC knowledge, general trust, and professional-patient trust. Machine learning models revealed that high general trust predicts membership in the high self-determination, quality-goal, family-oriented care group, while low filial piety expectations predict membership in the high self-determination, quantity-goal, professional-oriented care group.

Conclusion

Among Chinese older adults, three EoLC preference patterns were found, which were characterized by low family connections, low trust in professionals combined with adequate resources, and extensive knowledge, respectively. High general trust and low filial piety expectations were key predictors for two of the three patterns.