Graduate Theses and Dissertations (2019 - present)

Date of Award

8-2025

Document Type

Dissertation

Degree Name

Ph.D.

Department

Systems Engineering

Committee Chair

Sean Walker

Abstract

A growing number of patients in the US come from diverse backgrounds, but healthcare professionals may not always reflect this diversity. Because of this, healthcare professionals may develop unintentional cognitive biases resulting from cultural stereotypes. This can perpetuate health inequities, affecting interactions between patients and clinicians, hiring, and promotion. Unconscious bias training can help healthcare professionals mitigate this issue by enabling them to identify, acknowledge, and minimize their biases. Ultimately, this can create a more respectful, safe, and diverse workplace. Simulation-based training using virtual patients has become increasingly popular among medical professionals. This type of training allows students to practice scenarios, make mistakes, reflect, receive feedback, and develop clinical skills without compromising patient safety. In addition to promoting ethical decision-making, virtual patients can increase learners' enthusiasm and engagement in their educational pursuits. Using virtual patients, this study aims to identify or trigger unconscious biases among final-year medical students based on race, age, biological sex, socioeconomic status, and weight, utilizing a system framework. A unique feature of this study is the use of virtual patients to trigger unconscious biases.

Available for download on Wednesday, July 14, 2027

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