Examining physician perceptions and implicit bias in a virtual reality clinical encounter between physicians and female avatar patients: A qualitative study☆
4 affiliations
- 1National Institutes of Health-National Human Genome Research Institute (NIH/NHGRI), 9000 Rockville Pike, Bethesda, MAD 20892, United States
- 2The Ohio State University, College of Medicine, Department of Biomedical Education and Anatomy, 370 W. 9th Ave Columbus, PH 43210, United States
- 3Emory University, School of Medicine, 1440 Clifton Road NE Atlanta, GA 30322, United States
- 4Currently affiliated with Meharry Medical College, Center for Bioethics, Social and Behavioral Research, 1005 Dr. DB Todd Jr. BLVD, Nashville, TN 37208, United States
Abstract
Implicit bias within hospitals and clinical encounters impacts patient experiences and how physicians and patients interpret perceptions during clinical decision-making. This study attempts to assess how implicit bias happens. We investigate patterns of implicit bias in simulated clinical encounter or immersive virtual reality (VR) clinical encounter to observe its potential influence on how physicians perceive female avatar patients. Implicit bias is difficult to capture and analyze in real clinical settings for a variety of reasons. For example, there are methodological challenges when conducting research with human subjects, such as capturing and measuring biases in communication and behavior for establishing causal relationships. Avatar patients allow us to observe how physicians perceive certain patients as a potential reflection of real-life patients. Each VR clinical encounter consisted of a standardized script of a female avatar-patient who is phenotypically perceived as racially Black or White across high or low socioeconomic class statuses. We randomly assigned to physicians who were internal medicine residents (N = 152) across four sites in the United States. Using qualitative methods, we used a blind- coding strategy, in which each research team member had no prior knowledge of the physician or avatar-patient's racial group. Results show how VR can function as a way for observing bias using a VR study design within biomedical contexts. Based on our results, we were able to gain insight directly from physicians as they projected their views onto avatar patients, often describing patient perceptions during the debriefing process, post-clinical encounters. Assessing bias through VR can further show how implicit bias is concealed and conveyed in patient-provider communication. Implicit bias can be mitigated through continuing medical education and ongoing clinician training programs for ongoing cultural and structural awareness.
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BibTeX
@article{thomas2026examining,
title = {{Examining physician perceptions and implicit bias in a virtual reality clinical encounter between physicians and female avatar patients: A qualitative study☆}},
author = {Shameka Poetry Thomas and K. Jameson Floyd and Rachele Willard and Babajide Owosela and Susan Persky and Vence L. Bonham},
journal = {PEC Innovation},
year = {2026},
month = sep,
doi = {10.1016/j.pecinn.2026.100501},
url = {https://doi.org/10.1016/j.pecinn.2026.100501},
note = {CC BY-NC-ND 4.0},
}
RIS
TY - JOUR
TI - Examining physician perceptions and implicit bias in a virtual reality clinical encounter between physicians and female avatar patients: A qualitative study☆
AU - Shameka Poetry Thomas
AU - K. Jameson Floyd
AU - Rachele Willard
AU - Babajide Owosela
AU - Susan Persky
AU - Vence L. Bonham
PY - 2026
DA - 2026/09/10
JO - PEC Innovation
DO - 10.1016/j.pecinn.2026.100501
UR - https://doi.org/10.1016/j.pecinn.2026.100501
AB - Implicit bias within hospitals and clinical encounters impacts patient experiences and how physicians and patients interpret perceptions during clinical decision-making. This study attempts to assess how implicit bias happens. We investigate patterns of implicit bias in simulated clinical encounter or immersive virtual reality (VR) clinical encounter to observe its potential influence on how physicians perceive female avatar patients. Implicit bias is difficult to capture and analyze in real clinical settings for a variety of reasons. For example, there are methodological challenges when conducting research with human subjects, such as capturing and measuring biases in communication and behavior for establishing causal relationships. Avatar patients allow us to observe how physicians perceive certain patients as a potential reflection of real-life patients. Each VR clinical encounter consisted of a standardized script of a female avatar-patient who is phenotypically perceived as racially Black or White across high or low socioeconomic class statuses. We randomly assigned to physicians who were internal medicine residents (N = 152) across four sites in the United States. Using qualitative methods, we used a blind- coding strategy, in which each research team member had no prior knowledge of the physician or avatar-patient's racial group. Results show how VR can function as a way for observing bias using a VR study design within biomedical contexts. Based on our results, we were able to gain insight directly from physicians as they projected their views onto avatar patients, often describing patient perceptions during the debriefing process, post-clinical encounters. Assessing bias through VR can further show how implicit bias is concealed and conveyed in patient-provider communication. Implicit bias can be mitigated through continuing medical education and ongoing clinician training programs for ongoing cultural and structural awareness.
SN - 2772-6282
ER -