AI information literacy in healthcare context: profiles and associated variables among healthcare professionals

This study examines AI information literacy among healthcare professionals and identifies differences across professional roles. An online survey was administered to 390 healthcare professionals, including 22.3% medical doctors, 42.1% nurses, and 35.6% health professionals. AI information literacy was measured using the AI Information Literacy Scale (AILIS), which captures perceived confidence across four dimensions: process/create, assess, retrieve, and ethics. Findings indicated that across AILIS dimensions, participants reported the greatest confidence in retrieving information with AI and the least confidence in critically assessing AI-generated outputs. Medical doctors scored significantly higher than nurses and health professionals on process/create and retrieve. Across the main regression models, five predictors were included: age, perceived AI knowledge, frequency of AI use, number of AI tools used, and self-perceived understanding of how AI tools work. Self-perceived understanding showed the strongest association with all four AI information literacy dimensions. The models explained between 27.3% and 48.3% of the variance. Age showed small negative associations in most models. Self-reported AI information literacy among healthcare professionals appeared uneven across dimensions, with relatively lower confidence in critical assessment. GenAI integration in healthcare should therefore be approached as a literacy and training challenge, with particular attention to evaluation skills and reflective understanding of AI outputs.