The Impact of AI-Driven Chatbots and Virtual Assistants on Users’ Satisfaction and Actual Usage in Digital Healthcare Services
Latifa Alzahrani
Latifa Alzahrani, Associate Professor, Department of Management Information Systems, Taif University, Taif, Saudi Arabia.
Manuscript received on 23 September 2025 | First Revised Manuscript received on 29 September 2025 | Second Revised Manuscript received on 16 October 2025 | Manuscript Accepted on 15 November 2025 | Manuscript published on 30 November 2025 | PP: 1-10 | Volume-14 Issue-4, November 2025 | Retrieval Number: 100.1/ijrte.A113006011125 | DOI: 10.35940/ijrte.A1130.14041125
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The domain of healthcare is undergoing rapid digital transformation, with users increasingly expecting efficient and seamless interactions. AI-powered healthcare chatbots are emerging as key tools in reshaping patient communication and promoting personalised health behaviour goals that align with individual preferences, needs, and constraints. This study draws on four key theoretical models: expectation-confirmation theory, the Technology Acceptance Model, trust theory, and perceived risk. The proposed framework was evaluated using partial least squares structural equation modelling from 434 users in Saudi Arabia. The statistical analysis validates the proposed research framework, which posits that meeting user expectations and ease of use have a strong influence on satisfaction and perceived usefulness. Trust boosts continued use, while perceived risk is surprisingly insignificant. Continuance intention is the strongest predictor of actual chatbot usage behaviour. These results offer valuable insights for healthcare technology developers and providers aiming to improve user adoption of AI-driven healthcare chatbots. The findings suggest that meeting or exceeding user expectations (confirmation) is crucial for satisfaction. Ease of use remains a fundamental requirement for perceived usefulness. Building trust is essential for encouraging continued usage intention. Satisfaction and continuance intention drive actual usage behaviour.
Keywords: Artificial Intelligence, Chatbots, Digital Healthcare, User Satisfaction.
Scope of the Article: Artificial Intelligence and Methods