03428nas a2200265 4500000000100000008004100001260001600042653002800058653001400086653002100100653003100121653001100152653002400163100001900187700001200206700001400218700001800232700001200250245006800262856015300330300000900483490000800492520264800500022001403148 2025 d bElsevier BV10aArtificial Intelligence10aEducation10aHealth Education10aNursing Education Research10aReview10aWounds and Injuries1 aEncarnação R1 aAlves J1 aMarques A1 aNeves-Amado J1 aAlves P00aArtificial intelligence in wound care education: Scoping review uhttps://www.sciencedirect.com/science/article/pii/S0260691725003090/pdfft?md5=54771d72c511e61d18a1e1f9705a792a&pid=1-s2.0-S0260691725003090-main.pdf a1-100 v1553 a
Background
Artificial intelligence is transforming healthcare education, offering innovative teaching and skill development approaches. However, its implementation and effectiveness in wound care education remain unclear.
Objective
To map and analyze the available evidence on the potential impact of artificial intelligence in wound care education, identify knowledge gaps, and provide recommendations for future research.
Design/methods
This scoping review followed the Joanna Briggs Institute guidelines for scoping reviews and the PRISMA-ScR guidelines. The search was first conducted in December 2023 and updated on 30 November 2024 across the following databases: CINAHL Ultimate, MEDLINE, Cochrane Library, Academic Search Complete, Scientific Electronic Library Online (Scielo), Scopus, and Web of Science. Grey literature was accessed through Scientific Open Access Scientific Repositories of Portugal (RCAAP), ProQuest Dissertations and Theses, OpenAIRE, and Open Dissertations. Additional searches were performed in Google Scholar and specific journals, including the International Wound Journal, Skin Research and Technology, Journal of Wound Care, and Wound Repair and Regeneration. Eligibility criteria encompassed any study design exploring the use of artificial intelligence in wound care education, published in English, Portuguese, or Spanish, with no restrictions on publication date.
Results
This review revealed diverse artificial intelligence applications in wound care education, including adaptive e-learning platforms, virtual and augmented reality simulations, generative artificial intelligence for educational content, and diagnostic and treatment tools. These technologies offer personalized learning experiences, real-time feedback, and interactive engagement to enhance clinical skills. Despite their promise, most studies lacked empirical validation, highlighting significant gaps in integrating artificial intelligence into wound care education.
Conclusions
This review highlights artificial intelligence's transformative potential to revolutionize wound care education by fostering interactive and evidence-based learning environments. This work highlights the need for collaboration among educators, policymakers, and researchers. Future research is needed to ensure effective, ethical, and equitable integration of artificial intelligence in wound care education.
a0260-6917