Abstract: The development of smart aging is an important measure to meet the challenge of rapid population aging, which can ease the pressure on social aging and meet the increasingly diversified needs of the elderly. However, the current applications of smart aging systems face a series of problems such as low acceptance of the elderly, low interaction effectiveness, low trust, and unclear responsibility allocations. Although researchers have begun to emphasize the human-computer integration mechanism between elderly users and intelligent systems, the existing research is still limited and lacks a holistic theoretical framework and empirical results to support it.
Therefore, this study aims to construct a theoretical framework for the integration relationship between elderly users and intelligent systems from multiple levels, including user needs, interaction behavior, human-machine trust, and human-machine responsibility, and to deeply explore the influence mechanism of users-related, system-related, and situational factors on the human-system integration.
First, at the level of user demand and interaction behavior, this study focuses on the actual demand characteristics of different family members in the home environment, analyzes the age effect, constructs the user persona, enhances the understanding of the relevant stakeholders of the needs of elderly users, and matches the intelligent system services with the needs of elderly users; further explores the interaction behavior mechanism between elderly users and intelligent systems, and investigates the comprehensive effects of interaction terminals, social characteristics of intelligent systems and other factors on the intention to use, interaction efficiency, and interaction experience of elderly users, to improve the interaction efficacy and experience of the elderly users.
Second, at the level of human-machine trust, this study explores the dynamic trust construction process between elderly users and intelligent systems, including the construction process of initial trust at the beginning of use, continuous trust during use, and trust recovery process when the task fails. On this basis, this study explores the comprehensive influence mechanism of multi-dimensional factors of users, systems, and contexts on dynamic trust to promote the establishment of a stable trust relationship between elderly users and intelligent systems.
Third, at the level of human-machine responsibility, this study focuses on the positive and negative outcomes brought about by the application of intelligent systems in home scenarios, explores the effects of the outcome valences, interaction terminals, the mediating and moderating roles of perceptual characteristics and task characteristics, analyzes the advantages, disadvantages, and potential risks of the application of intelligent systems, and establishes a mechanism for attributing responsibility for human-machine integration in home scenarios.
In summary, this study adopts a holistic research perspective to construct a theory of the human-machine integration relationship between elderly users and intelligent systems in home-based smart aging scenarios at multiple levels, and to explore the comprehensive influence mechanism of multi-dimensional factors of users, systems, and contexts on human-machine integration. The issues of user needs, interaction behavior, human-machine trust, and human-machine responsibility are closely linked in the process of human-computer integration. The level of user demand and interaction behavior focuses on enabling older users to start using the intelligent system efficiently and naturally, the level of human-machine trust focuses on supporting the ongoing use behavior of older users, and the level of human-machine the level of human-machine focuses on the handling of the interaction results.
Moreover, existing studies mainly focus on the influence of single-category factors on a certain level of human-machine integration. This study investigates the influence mechanism of multi-dimensional factors on different levels of human-computer integration. This study enriches the theory of human-machine integration management and provides theoretical support for human-machine collaboration. Meanwhile, the research results are conducive to promoting the age-friendly design of intelligent systems, facilitating high-quality interaction between elderly users and intelligent systems, resolving the digital divide, and contributing to realizing an age-friendly smart society.

Key words: human-machine integration, user need, interaction behavior, human-machine trust, human-machine responsibility