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Patient Reactions to Artificial Intelligence-Clinician Discrepancies: Web-Based Randomized Experiment
Farrah Madanay1, Laura S O'Donohue2, Brian J Zikmund-Fisher3
1Center for Bioethics and Social Sciences in Medicine, University of Michigan-Ann Arbor, Ann Arbor, MI, United States.
Journal of Medical Internet Research
|May 22, 2025
Summary
When a radiologist recommends less lung cancer screening than artificial intelligence (AI), patients lose confidence. Patient trust also depends on whether their preference for aggressive treatment (maximizing) or conservative treatment (minimizing) aligns with the AI-assisted recommendation.
Area of Science:
- Medical Imaging
- Artificial Intelligence in Healthcare
- Radiology
Background:
- The integration of artificial intelligence (AI) in medical imaging, particularly for lung cancer screening, is increasing.
- AI offers potential benefits like earlier cancer detection but raises concerns about patient confidence when AI and radiologist interpretations differ.
Purpose of the Study:
- To investigate how discrepancies between AI and radiologist recommendations impact patient agreement and satisfaction.
- To analyze the moderating role of patients' medical maximizing-minimizing preferences in these relationships.
Main Methods:
- A randomized experiment involving 1606 US adults simulating a lung cancer screening scenario.
- Participants were exposed to four conditions: radiologist only, AI and radiologist agreement, radiologist overcalling AI, and radiologist undercalling AI.
- Patient-reported outcomes included agreement with recommendations, likelihood to recommend the radiologist, and perceived radiologist quality, alongside measurement of maximizing-minimizing preferences.
Main Results:
- Patient agreement and positive ratings for radiologists were significantly lower when the radiologist recommended less testing than AI (undercalled AI).
- No significant differences in agreement or ratings were found among the conditions where the radiologist agreed with AI, overcalled AI, or had no AI.
- Patient preferences moderated agreement: maximizers aligned with overcalling radiologists, while minimizers disagreed with overcalling radiologists.
Conclusions:
- Radiologists recommending less aggressive findings than AI may experience reduced patient confidence.
- Patient trust in radiologists is influenced by the alignment of recommendations with their individual treatment preferences (maximizing vs. minimizing).
- Further research is needed on communication strategies for disclosing AI discrepancies to patients.
Keywords:
artificial intelligencecommunicationdecision makingearly detection of cancermedical maximizing-minimizingpatient satisfactionpatient-physician relationshipradiologistsMore Related Videos
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