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

Our research highlights the role of process design features of AI systems used in medicine in shaping professional identity perceptions, mediated through increased trust in AI. An explainable AI-based CDSS and an AI-generated system advice, which is deeply integrated into the clinical workflow, reinforce trust, thereby mitigating perceived professional identity threats. However, explainable AI and individual accountability of the system directly exacerbate threat perceptions. Our findings illustrate the complex nature of the behavioral patterns of AI in health care and have broader implications for supporting the implementation of AI-based CDSSs in a context where AI systems may impact professional identity.

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Publication Details

Journal
JMIR Formative Research
Published
2025-03-26
DOI
https://doi.org/10.2196/64266
Citations
11
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
7.20
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article

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

Kai Wehkamp, Carsten Schultz, Rainer Petzina, Sophia Ackerhans et al.
11 citations
JMIR Formative Research
Artificial Intelligence in Healthcare and Education
7.20
article

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

Kai Wehkamp, Carsten Schultz, Rainer Petzina, Sophia Ackerhans, Daniel Dumitrescu
article en
11 citations

Abstract

Our research highlights the role of process design features of AI systems used in medicine in shaping professional identity perceptions, mediated through increased trust in AI. An explainable AI-based CDSS and an AI-generated system advice, which is deeply integrated into the clinical workflow, reinforce trust, thereby mitigating perceived professional identity threats. However, explainable AI and individual accountability of the system directly exacerbate threat perceptions. Our findings illustrate the complex nature of the behavioral patterns of AI in health care and have broader implications for supporting the implementation of AI-based CDSSs in a context where AI systems may impact professional identity.

JMIR Formative ResearchVol. 9
Kiel Institute for the World Economy (DE), Heart and Diabetes Center North Rhine-Westphalia (DE), MSH Medical School Hamburg – University of Applied Sciences and Medical University (DE), Ruhr University Bochum (DE)
Peace, Justice and strong institutions
Openalex Percentile: Top 3%
Artificial Intelligence in Healthcare and Education
7.20
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