Next-generation encyclopedia: an extended reality artificial intelligence-chatbot simulation for pressure injury prevention in nursing education

Abstract

Integrating artificial intelligence (AI) and extended reality (XR) into nursing education offers innovative strategies to enhance evidence-based prevention of pressure injuries (PIs). Methods An explanatory sequential mixed-methods design was used. Quantitative data were collected from 52 students, with a 3-week follow-up, using measures based on the Health Belief Model (HBM) and Jeffries' Simulation Theory. The qualitative phase included 28 participants in focus groups, and data were analyzed thematically using MAXQDA. Results Quantitative findings showed clear improvements across all measures, including the Pressure Ulcer Knowledge Assessment Tool 2.0 (PUKAT 2.0), Modified Pieper, Virtual Reality Attitude Scale (VRAS), and Behavioral Intention to Use and Learn Chatbot in Education Scale (BIULCES), with gains maintained at the 5-week follow-up. Qualitative results aligned with these outcomes and reflected the core HBM-driven themes of development of clinical risk perception, clinical awareness of the seriousness of PIs, educational benefits of evidence-based technological integration, strengthened clinical self-efficacy and decision-making confidence, and future directions and sustainability in nursing education. Conclusions The XR–AI chatbot simulation model produced measurable gains in students’ knowledge, clinical competence, technology acceptance, and self-efficacy, while strengthening their intention to perform PI prevention, demonstrating a sustainable and impactful approach to technology-enhanced nursing education.