The Application of Generative Artificial Intelligence Tools in Healthcare Communication Education: A Systematic Review

Healthcare communication education plays a pivotal role in relationship-centred care and career development of healthcare practitioners, although it is resource-intensive to deliver as it requires authentic contexts and diverse patient encounters. The rapid emergence of generative artificial intelligence (GenAI) presents new opportunities for transforming the way healthcare communication is taught and evaluated. Following PRISMA guidelines, this systematic review synthesised 29 empirical studies identified across eight databases. Pedagogically, GenAI was mainly applied as a virtual patient, followed by a feedback provider and a content generator. These applications enhanced learner engagement, instructional support, and communication skill development, while also raising concerns about ethics, pedagogy, and content quality, particularly algorithm bias, vague feedback, and inaccurate information. Regarding research design, this review mapped theoretical frameworks and methodological approaches employed across included studies. Three key gaps were identified: limited theoretical grounding, insufficient reporting of reliability and validity evidence, and over-reliance on text-based interaction. Collectively, the findings highlight an early but promising stage of GenAI adoption in healthcare communication education. Future research should focus on developing theoretically informed frameworks, employing interactional and longitudinal methods to capture human-AI interaction dynamics, and promoting critical GenAI literacy to ensure that innovation remains pedagogically meaningful, ethically sound, and learner-centred.