Aging with AI companionship: the role of artificial intelligence in enhancing the mental wellbeing of older adults

Abstract

Introduction: With the intensification of global population aging, mental health problems among older adults have become increasingly prominent. As an important innovative approach in smart eldercare, artificial intelligence (AI) has been gradually applied to older populations due to its advantages in emotional support, cognitive stimulation, and social interaction. However, there is still a lack of systematic empirical evidence regarding the mechanisms through which AI affects older adults' mental wellbeing. Methods: Drawing on Self-Determination Theory and the Technology Acceptance Model, this study constructs a five-dimensional analytical framework consisting of autonomy, perceived ease of use, perceived usefulness, competence, and relatedness, and combines structural equation modeling (SEM) with fuzzy-set qualitative comparative analysis (fsQCA). Using survey data from 418 Chinese older adults aged 60 and above, we systematically explore the pathways through which AI influences their mental wellbeing. Results: The findings indicate that autonomy exerts the most significant positive effect on older adults' mental wellbeing, while perceived ease of use, perceived usefulness, competence, and relatedness also have positive impacts. Discussion: By granting older adults greater choice and decision-making power, AI enhances their sense of control over life and self-efficacy, thereby effectively promoting mental wellbeing. At the same time, the ease of use and practicality of AI technologies lower the threshold for adoption, increasing older adults' intention to use and satisfaction. Furthermore, AI supports cognitive training, health management, and emotional communication, helping older adults maintain cognitive vitality, strengthen self-care abilities, and receive emotional support and social connection, which in turn further enhance their sense of wellbeing and quality of life. This study not only enriches the theoretical foundation of research on AI and mental wellbeing among older adults, but also provides empirical evidence for the optimization, design, and promotion of related technologies.

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