Title
Exploring Gender Biases With Virtual Patients For High Stakes Interpersonal Skills Training
Keywords
autonomous agents; cranial nerve palsies; gender bias; healthcare; intelligent agents; user studies; virtual humans; Virtual patients
Abstract
The use of virtual characters in a variety of research areas is widespread. One such area is healthcare. The study presented in this paper leveraged virtual patients to examine whether virtual patients are more likely to be correctly diagnosed due to gender and skin tone. Medical students at the University of Florida College of Medicine interacted with six virtual patients across two sessions. The six virtual patients comprised various combinations of gender and skin tone. Each virtual patient presented with a different cranial nerve injury. The results indicate a significant difference in correct diagnosis according to patient gender for one of the cases. In that case, female patients were correctly diagnosed more frequently than their male counterpart. The description of that case required that the virtual patient present with a visible bruise on the forehead. We hypothesize the results obtained could be due to a transfer of a real world gender bias. © 2014 Springer International Publishing Switzerland.
Publication Date
1-1-2014
Publication Title
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume
8637 LNAI
Number of Pages
385-396
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
DOI Link
https://doi.org/10.1007/978-3-319-09767-1_50
Copyright Status
Unknown
Socpus ID
84906505483 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/84906505483
STARS Citation
Rivera-Gutierrez, Diego J.; Kopper, Regis; Kleinsmith, Andrea; Cendan, Juan; and Finney, Glen, "Exploring Gender Biases With Virtual Patients For High Stakes Interpersonal Skills Training" (2014). Scopus Export 2010-2014. 9220.
https://stars.library.ucf.edu/scopus2010/9220