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.

Major Depressive Disorder (MDD) and Posttraumatic Stress Disorder (PTSD) are highly prevalent illnesses that can result in profound impairment (Alegria et al., 2006; CTPTSD, 2007). While many patients with these disorders present in primary care, research suggests that physicians under-detect and suboptimally manage MDD and PTSD in their patients Satter et al., 2012). The development of more effective training interventions to aid primary care providers in diagnosing mental health disorders is of the utmost importance. This research focuses on evaluating computer-based training tools

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