The use of digital gamification, extended reality, artificial intelligence, and integrated digital learning tools in palliative care education of undergraduate nurses: A systematic review.

BACKGROUND: Nurses are at the forefront of providing palliative care, playing a critical role in ensuring high-quality support for patients and their families. Emerging digital and immersive technologies offer new opportunities to simulate complex palliative care scenarios, bridging the gap of limited clinical experiences and developing palliative care competence. OBJECTIVES: To explore and analyse what type of interventions have been implemented within palliative care education of undergraduate nursing students using digital and immersive technologies. Secondary aims were exploring the experiences and effect on palliative care competence. DESIGN: A systematic review of mixed-methods interventional studies, based on Joanna Briggs Institute guidelines. METHODS: A comprehensive literature search was conducted across Ovid Medline, CINAHL, Scopus, Web of Science, Cochrane Library, and ERIC in March 2025. Eligible studies included empirical research on undergraduate nursing students using digital and immersive technologies to deliver palliative care education. Quality assessment followed JBI critical appraisal tools. Quantitative studies were analysed by Cohen d effect sizes and qualitative studies with content analysis. RESULTS: Six studies met the inclusion criteria and were published in 2023 or 2024. Interventions varied between use of immersive simulation and screen-based simulation. Quantitative findings indicated statistically significant improvements in palliative care attitudes, abilities and readiness for practice with effect size ranging from 0.40 (p = .01) to 1.13 (p < .001). Qualitative content analysis identified two main themes: clinical experience and digital learning experience. CONCLUSIONS: Digital and immersive simulation holds significant promise in addressing gaps in undergraduate nursing palliative care competences. Research in this field is highly limited, with no use of artificial intelligence within simulations used in the reviewed research. Further high-quality, standardised, and longitudinal studies are essential to determine sustained impact and generalisability.