Related Experiment Videos
Exploring care adoption intention among older adults using XGBoost: a rural case in Anhui, China
1School of Humanities and Social Sciences, Anhui University of Science and Technology, Huainan, China.
Introduction:
With the development of digital rural construction and rural mutual-aid care for older adults, smart mutual-aid care for older adults has become an important way to improve rural pension services, yet low digital literacy and insufficient adoption intention among rural older adults hinder the popularization of smart care services for older adults.
Methods:
Based on the Technology Acceptance Model, this study collected 320 valid questionnaires from rural older adults in Anhui Province and combined traditional statistical approaches with explainable machine learning to explore factors affecting service adoption intention.
Results:
The questionnaire possessed good reliability and validity with significant correlations across all core variables; perceived ease of use and perceived usefulness significantly boosted adoption intention, while social support lost statistical significance due to collinearity suppression. Perceived ease of use served as the dominant driving factor, social support contributed positively independently, the explanatory power of perceived usefulness decreased, and all variables generated positive nonlinear marginal effects on adoption intention.
Discussion:
These findings offer empirical evidence and practical references for optimizing and promoting rural smart mutual-aid care services for older adults in a targeted manner.