Adapting a scale to assess clinicians’ situational trust in AI

Poster Number: P67
Presentation Time: 05:00 PM - 06:30 PM

Abstract Keywords: Clinical Decision Support, Human-computer Interaction, Machine Learning
Primary Track: Applications

Successful implementation of artificial intelligence (AI) in healthcare necessitates understanding human-AI interaction. Trust in AI-based clinical decision support is crucial but understudied among clinicians. We will adapt and validate an existing trust scale from the autonomous vehicle domain to assess clinicians’ situational trust in an AI-derived early warning score (EWS). Survey methodology will be employed for scale adaptation and validation and we will share the results of the validated 6-item trust measure.

Speaker(s):
Elizabeth Sloss, PhD, MBA, RN
University of Utah

Author(s):
Usman Sattar, MBBS, MSHI; Guilherme Del Fiol, MD, PhD - University of Utah; Karl Madaras-Kelly, PharmD, MPH - Idaho State University; Jorie Butler, PhD - University of Utah;