Treffer: Generative artificial intelligence as a source of advice on resuscitation and first aid for laypeople: A scoping review.

Introduction: The performance of cutting-edge generative artificial intelligence (GenAI) in guiding laypeople on how to give help in health emergencies is attracting growing attention. This study aimed to map and summarise original research evidence on the quality of GenAI-synthesised advice on resuscitation and first aid.
Methods: The review encompassed journal publications that reported original quantitative data on the quality (accuracy, correctness, completeness, appropriateness) of GenAI-synthesised advice on how laypeople should perform cardiopulmonary resuscitation or provide first aid. Relevant papers were identified through PubMed, Scopus, and Google Scholar. Studies were included if they were published in English as an article, short report, letter, or note during the period 2017-2025. The review was conducted following the recommendations of the PRISMA extension for Scoping Reviews.
Results: Among the 19 eligible studies, 17 evaluated the performance of text-generating GenAI tools, one tested user-to-GenAI voice interaction and another one investigated text-to-video generation capabilities. The studies exhibited substantial heterogeneity in research design, methods, and reporting. Most of them (89.5 %) presented evidence of flaws in the generation of advice on resuscitation or first aid, including a failure to synthesise requested content (reported by 15.8 % of the studies), the creation of incomplete instructions (57.9 %), inaccurate instructions (57.9 %), or superfluous guidance (36.8 %), irrelevant or potentially harmful. The prevalence of misinformation varied from study to study, at times encompassing the whole sample of evaluated GenAI responses. Some authors did not accentuate the issue of misinformation despite the reported data indicating quality defects.
Conclusions: Current evidence indicates risks associated with the unsupervised generation of resuscitation and first aid guidance by publicly available GenAI, as the synthesised content often contains misinformation that may mislead users and induce harmful actions. There is a growing need for international collaboration to develop coordinated strategies to limit GenAI-driven misinformation and mitigate potential health risks.
(Copyright © 2025 Elsevier B.V. All rights reserved.)

Declaration of competing interest The author declares that the topic under review represents a particular area of research interest and that he served as lead investigator in four of the studies included in this review.