Artificial intelligence readiness among emergency department healthcare professionals: cross-sectional study from Ethiopia

Résumé fourni par la source

Artificial intelligence (AI) is increasingly transforming clinical care, particularly in emergency departments (EDs), where rapid decision-making is essential. However, successful AI implementation depends on healthcare professionals’ readiness, including their knowledge, skills, attitudes, and ethical awareness. Evidence from Ethiopia remains scarce. This study assessed AI readiness and associated factors among ED healthcare professionals in Ethiopia using the Medical Artificial Intelligence Readiness Scale (MAIRS). An institution-based cross-sectional study was conducted from February 1 to March 22, 2026. A total of 211 participants were surveyed using a structured questionnaire adapted from the Medical Artificial Intelligence Readiness Scale for Medical Students (MAIRS-MS) and contextualized for emergency department healthcare professionals, with additional items assessing perceived barriers to AI adoption. Data were analyzed using descriptive statistics, bivariate analyses, and multivariable linear regression. Internal consistency of the adapted instrument was assessed using Cronbach’s alpha. Overall, 63 (29.9%) participants reported previous AI use, and AI readiness was high (mean = 4.12 ± 0.85). Ethical awareness (mean = 4.20 ± 0.75) and attitude toward AI (mean = 3.76 ± 0.80) were strong, whereas knowledge and skills were moderate (mean = 3.43). Major perceived barriers included lack of training, limited infrastructure, and trust concerns (mean = 3.69 ± 0.62). Vision (β = 0.673, p < 0.001), perceived barriers (β = 0.349, p < 0.001), and ethics (β = 0.165, p = 0.006) were significant predictors of readiness. Emergency department healthcare professionals among surveyed emergency department healthcare professionals supported by strong positive attitudes and ethical awareness. However, moderate technical skills and significant structural barriers pose challenges to successful AI integration. We recommend strengthening AI-focused professional training programs, integrating AIconcepts into health professional education, improving digital infrastructure within healthcareinstitutions, and establishing national regulatory and ethical frameworks to support the safe andeffective adoption of AI in emergency care settings.