A Structural Equation Model Approach to Enhance Chinese Older Adults’ Intention Towards Using AI Assistants in Nursing Care Units

Abstract

The growing significance of artificial intelligence in nursing care underscores the need to understand its adoption factors. The paper deals with the factors influencing the adoption of AI assistants in nursing care units. This research collect 552 older adults participants stay in nursing homes across ten major Chinese cities within a convinient sampling method. The data were analyzed using descriptive analysis, confirmatory factor analysis (CFA), and structural equation modeling (SEM). The findings reveal that perceived ease of use, service quality, and self-efficacy significantly impact the intention to use AI assistants, with attitude acting as a key mediator. Notably, perceived usefulness directly affects adoption intentions without mediation by attitude. Furthermore, the digital divide moderates the strength of these relationships, with individuals possessing higher digital literacy demonstrating stronger intentions to adopt AI technologies. These results highlight the importance of service quality, ease of use, and digital access in driving AI adoption in older adults care. The findings provide insights for healthcare administrators and policymakers to enhance AI integration and address digital literacy gaps in nursing care units.