AI-based medical translation in nursing practice: a cross-sectional survey of trust, use, and implications for evidence-based care

Effective communication is a cornerstone of evidence-based nursing practice, particularly in multilingual and multicultural healthcare environments. Language barriers between nurses and patients can compromise the accuracy of clinical information exchange, patient safety, and the quality of care. In response, artificial intelligence (AI)–based medical translation tools are increasingly used in clinical settings to support communication. To examine nurses’ use of AI-based medical translation tools and their perceptions of reliability, satisfaction, trust, and risks for clinical communication and patient safety. A cross-sectional descriptive survey was conducted with 16 registered nurses working in hospital, clinic, and community health center settings. Data were collected in February 2025 using a structured questionnaire developed for this study to assess AI-translation-tool use, perceived reliability, satisfaction, and perceived risks. Descriptive statistics and exploratory Kruskal–Wallis group comparisons were used, with findings interpreted cautiously because of the small sample. Use of AI translation tools varied from frequent to occasional and rare use. Frequent users reported higher perceived reliability than occasional and rare users, although this exploratory group difference should be interpreted cautiously given the small sample. Overall satisfaction was moderate, and participants reported concerns about complex medical terminology, culturally sensitive language, and high-risk clinical situations. Human verification remained important for patient safety. AI-based medical translation tools show potential to support communication in nursing practice; however, concerns about reliability in critical contexts limit full integration into evidence-based care. Clear guidelines, targeted training, and ongoing evaluation are needed to ensure safe and effective use.