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Related Experiment Video

Updated: May 24, 2026

Virtual Agent for Real-Time Motivational Interviewing by Integrating Adaptive Nonverbal Behavior and Language Models
07:14

Virtual Agent for Real-Time Motivational Interviewing by Integrating Adaptive Nonverbal Behavior and Language Models

Published on: December 23, 2025

How AI Agreement Shapes Confidence: Evidence Across Clinical Skill Levels.

Federico Cabitza1,2, Alessia Papale1

  • 1University of Milano-Bicocca, Milan, Italy.

Studies in Health Technology and Informatics
|May 23, 2026
PubMed
Summary
This summary is machine-generated.

Clinicians

Keywords:
Human-AI collaborationautomation biasclinical decision supportdiagnostic confidenceuser skills

Related Experiment Videos

Last Updated: May 24, 2026

Virtual Agent for Real-Time Motivational Interviewing by Integrating Adaptive Nonverbal Behavior and Language Models
07:14

Virtual Agent for Real-Time Motivational Interviewing by Integrating Adaptive Nonverbal Behavior and Language Models

Published on: December 23, 2025

Area of Science:

  • Medical Informatics
  • Human-Computer Interaction
  • Clinical Psychology

Background:

  • Artificial intelligence (AI) integration into clinical workflows is growing.
  • The psychological impact of AI on diagnostic confidence is not well understood.

Purpose of the Study:

  • To investigate how agreement or disagreement with AI recommendations influences clinician confidence.
  • To determine if these effects differ based on clinician skill level.

Main Methods:

  • 292 clinicians across three diagnostic areas rated confidence pre- and post-AI advice.
  • Analysis focused on confidence changes related to agreement/disagreement with AI and user skill.

Main Results:

  • Agreement with AI boosted confidence, even when AI was incorrect (M = 0.048).
  • Disagreement with AI slightly decreased confidence (M = -0.008).
  • Effects were uniform across all skill levels.

Conclusions:

  • AI agreement reinforces confidence irrespective of accuracy or clinician skill.
  • This highlights potential risks of overreliance on AI in diagnostic settings.