Diagnostic decision-making is complex, and errors affect up to 15% of emergency patients. While artificial intelligence (AI) shows potential to improve diagnostic accuracy, its acceptance remains limited due to user trust issues. This study investigates psychological and contextual factors influencing AI acceptance among both patients and physicians. Using a mixed-methods approach, we identify barriers, analyze the role of trust, and propose strategies to enhance adoption. Findings highlight concerns around physician supervision, data security, and the doctor-patient relationship. We offer practical insights to guide developers, healthcare providers, and policymakers in designing ethical AI tools that align with user needs, fostering trust and responsible integration of AI in healthcare.
Konya-Baumbach et al. (Sun,) studied this question.