Avatar-based simulation in the evaluation of diagnosis and management of mental health disorders in primary care

  • Authors:

  • Rachel M. Satter;Trevor Cohen;Pierina Ortiz;Kanav Kahol;James Mackenzie;Carol Olson;Mina Johnson;Vimla L. Patel

  • Affiliations:

  • Arizona State University, United States;University of Texas at Houston, United States;Arizona State University, United States;Arizona State University, United States;Banner Good Samaritan Medical Center, Phoenix, United States;Maricopa Medical Center, Phoenix, United States;Arizona State University, United States;Center for Cognitive Studies in Medicine and Health, The New York Academy of Medicine, 1216 Fifth Avenue, New York, NY 10029, United States

  • Venue:
  • Journal of Biomedical Informatics
  • Year:
  • 2012

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Abstract

Major Depressive Disorder (MDD) and Posttraumatic Stress Disorder (PTSD) are highly prevalent illnesses, but the literature suggests they are under-detected and suboptimally managed by primary care practitioners (PCPs). In this paper, we propose and use an evaluation method, using digitally simulated patients (avatars) to evaluate the diagnostic and therapeutic reasoning of PCPs and compared it to the traditional use of paper-based cases. Verbal (think-aloud) protocols were captured in the context of a diagnostic and therapeutic reasoning task. Propositional and semantic representational analysis of simulation data during evaluation, showed specific deficiencies in PCP reasoning, suggesting a promise of this technology in training and evaluation in mental health. Avatars are flexible and easily modifiable and are also a cost-effective and easy-to-disseminate educational tool.