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

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

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)1137-1150
Number of pages14
JournalJournal of Biomedical Informatics
Volume45
Issue number6
DOIs
StatePublished - Dec 2012

Keywords

  • Avatar(s)
  • Education
  • Major Depressive Disorder
  • Posttraumatic Stress Disorder
  • Primary care
  • Simulation
  • Training

ASJC Scopus subject areas

  • Computer Science Applications
  • Health Informatics

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