Exploring the Roles of Age and Gender in User Satisfaction and Usage of AI-Driven Chatbots in Digital Health Services: A Multigroup Analysis

As chatbot technology becomes increasingly prevalent across a wide range of industries, it is crucial to explore the factors that shape user satisfaction with this AI-driven innovation. This research provides insights into how age and gender impact user perceptions and engagement with AI-driven health technologies in Saudi Arabia. The information systems success model has been utilised to determine the effect of age and gender on user satisfaction. A self-administered questionnaire was distributed in two hospitals in Makkah City, Saudi Arabia, and 527 responses were collected from chatbot users. Structural equation modelling via analysis of moment structures validated the model constructs. The findings revealed that the privacy issue on user satisfaction has been significantly greater with males than with females. However, the correlation between user satisfaction and continuance usage intention, as well as net benefits, has been much higher among the females. Also, notable differences were found between user satisfaction and net benefits and continuance usage intention and net benefits, especially when comparing younger and older participants. Across all age groups, user satisfaction consistently emerged as a central driver of continuance usage intention and net benefits, underscoring the importance of fostering satisfaction to enhance the effectiveness of AI-driven chatbots in digital health services. This study can serve as a guide to highlight the importance of chatbot user satisfaction and provide implications, limitations, and future research opportunities.