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Use of artificial intelligence and health-related life satisfaction among older adults: A structural equation
1College of Nursing, Ewha Womans University, Seoul, Korea.
Background:
As artificial intelligence (AI) tools become increasingly integrated into healthcare, AI tools support disease management and well-being in older population. However, adoption of AI technologies is often hindered in the population, raising questions about how technology acceptance translates into direct health benefits for older adults.
Objectives:
Guided by the Technology Acceptance Model, this study aims to examine the structural mechanisms by which AI healthcare technology variables, including AI competency, attitude, or use frequency, influence health-related life satisfaction among middle- to older-aged adults.
Methods:
This study was a secondary analysis using data from 2024 Digital Divide Survey in South Korea. The analytic sample included 582 participants aged ≥ 55 years. Structural equation modeling was used to examine associations among AI competency, attitude, or perceived helpfulness, AI use frequency, and health-related life satisfaction.
Results:
The measurement and structural equation models demonstrated acceptable fit. AI competency was positively associated with AI healthcare helpfulness (β = .23, p < .001), AI attitude (β = .53, p < .001), and health-related life satisfaction (β = .28, p < .001). AI attitude was significantly associated with AI healthcare use frequency (β = .29, p < .001), whereas AI healthcare use frequency and helpfulness showed no significant direct effects on health-related life satisfaction.
Conclusions:
AI competency, a psychological aspect of AI use, is a more crucial determinant of physical and mental well-being in later life than the increased frequency of AI healthcare use. Interventions should prioritize strengthening AI literacy and self-efficacy among underserved older adults.
