This paper proposed a comprehensive mixed-methods framework with varied
samples of older adults, including user experience, usability assessments, and
in-depth interviews with the integration of Explainable Artificial Intelligence
(XAI) methods. The experience of older adults' interaction with the Ehealth
interface is collected through interviews and transformed into operatable
databases whereas XAI methods are utilized to explain the collected interview
results in this research work. The results show that XAI-infused e-health
interfaces could play an important role in bridging the age-related digital
divide by investigating elders' preferences when interacting with E-health
interfaces. Furthermore, the study identifies important design factors, such as
intuitive visualization and straightforward explanations, that are critical for
creating efficient Human Computer Interaction (HCI) tools among older users.
Furthermore, this study emphasizes the revolutionary potential of XAI in
e-health interfaces for older users, emphasizing the importance of transparency
and understandability in HCI-driven healthcare solutions. This study's findings
have far-reaching implications for the design and development of user-centric
e-health technologies, intending to increase the overall well-being of older
adults.

研究提出了一个综合的混合方法框架，采用不同样本的老年人，包括用户体验，可用性评估和深入访谈，集成可解释人工智能 (XAI) 方法。研究结果显示，XAI 注入的电子健康界面在调查老年人与电子健康界面交互时的偏好方面，扮演了重要角色，并确定了用户友好的人机交互 (HCI) 工具的重要设计因素。此研究的发现对于用户为中心的电子健康技术的设计和开发，旨在提高老年人的整体幸福感具有深远的意义。