A Study on the Factors Influencing Older Adults’ Willingness to Adopt Health Information in Human-AI Hybrid Interaction Contexts

Yiwei Sun; Yuan Tian

doi:10.6918/IJOSSER.202608_9(8).0006

Authors

Yiwei Sun College of Applied Arts and Science, Beijing Union University; Beijing 100080 China
Yuan Tian College of Applied Science and Technology, Beijing Union University; Beijing 100080 China

DOI:

https://doi.org/10.6918/IJOSSER.202608_9(8).0006

Keywords:

Online Healthcare; Human-AI Hybrid Interaction; Health Information Adoption; Silver Economy.

Abstract

With the accelerated penetration of AI agents driven by large language models such as ChatGPT and DeepSeek into the healthcare field, human-AI collaborative hybrid interaction has become the mainstream form of online medical services. Against the macro backdrop of an aging society and the rise of the “Silver Economy,” it carries significant expectations for enhancing the health and well-being of the elderly population. Therefore, an in-depth exploration of the key influencing factors and mechanisms underlying users’ adoption of AI-generated health information holds substantial theoretical and practical value. This study is grounded in the Stimulus-Organism-Response (S-O-R) theoretical framework, integrating the Elaboration Likelihood Model (ELM) and the Unified Theory of Acceptance and Use of Technology (UTAUT) to construct a multidimensional theoretical model. Through validation using structural equation modeling, it not only expands the application of human-computer interaction and information adoption theories in the contexts of smart healthcare and aging but also provides empirical evidence and targeted insights for AI health tool designers to optimize age-friendly interactive experiences, as well as for policymakers to establish a scientific and inclusive regulatory and service system for “Internet + Healthcare.”

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