TimAITED-2024

We conducted a cross-sectional survey targeting two categories of potential stakeholders of AI applications for emergency triage: developers/ technicians and consumers/ medical practitioners, at different levels of career. Respondents were grouped according to their attitudes towards AI (quantified using existing validated scores), rather than their background and career level. We then used this grouping to analyze their answers regarding emergency triage-specific issues and applicable AI methods or tools, all quantified on Likert-type scales.Attitudes and opinions toward AI-enabled emergency triage were further mapped onto the independent factors from the extended Unified Theory of Acceptance and Use of Technology (UTAUT2). The collected data show great heterogeneity across the attitude groups and backgrounds (medical vs. non-medical), and advocate for educational programs and interventions to improve the AI literacy of all medical practitioners. By exploring and comparing the opinions and attitudes of two groups of professional stakeholders who are expected to play a role as developers or consumers of AI-driven solutions in emergency triage, rather than lay individuals, patients, or medical practitioners as homogeneous groups in themselves, this investigation can contribute to building interdisciplinary bridges across professional divisions to further advance cultural readiness for AI solutions in healthcare.