Perceived Trust and Professional Identity Threat in AI-Based Clinical Decision Support Systems: Scenario-Based Experimental Study on AI Process Design Features

作者：Sophia Ackerhans, Kai Wehkamp, R. Petzina, Daniel Dumitrescu, Carsten Schultz · 发表于：JMIR Formative Research · 年份：2025 · DOI：10.2196/64266 · 被引用次数：25 · 研究领域：Medicine

Background Artificial intelligence (AI)–based systems in medicine like clinical decision support systems (CDSSs) have shown promising results in health care, sometimes outperforming human specialists. However, the integration of AI may challenge medical professionals’ identities and lead to limited trust in technology, resulting in health care professionals rejecting AI-based systems. Objective This study aims to explore the impact of AI process design features on physicians’ trust in the AI solution and on perceived threats to their professional identity. These design features involve the explainability of AI-based CDSS decision outcomes, the integration depth of the AI-generated advice into the clinical workflow, and the physician’s accountability for the AI system-induced medical decisions. Methods We conducted a 3-factorial web-based between-subject scenario-based experiment with 292 medical students in their medical training and experienced physicians across different specialties. The participants were presented with an AI-based CDSS for sepsis prediction and prevention for use in a hospital. Each participant was given a scenario in which the 3 design features of the AI-based CDSS were manipulated in a 2×2×2 factorial design. SPSS PROCESS (IBM Corp) macro was used for hypothesis testing. Results The results suggest that the explainability of the AI-based CDSS was positively associated with both trust in the AI system (β=.508; P<.001) and professional identity threat perc...