  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.
