Embodied Conversational Virtual Patients

Embodied Conversational Virtual Patients

Patrick G. Kenny (University of Southern California, USA) and Thomas D. Parsons (University of Southern California, USA)
DOI: 10.4018/978-1-60960-617-6.ch011


Recent research has established the potential for computer generated virtual characters to act as virtual patients (VP) for the assessment and training of novice clinicians in interpersonal skills, interviewing, and diagnosis. These VPs are embodied interactive conversational agents who are designed to simulate a particular clinical presentation of a patient’s illness with a high degree of consistency and realism. In this chapter we describe the architecture developed for virtual patients, and the application of the system to subject testing with virtual patients that exhibit a set of clinical conditions called Post Traumatic Stress Disorder (PTSD). The primary goal of these conversational agents was evaluative: can a VP generate responses that elicit user questions relevant for PTSD categorization? The results of the interactions of clinical students with the VP will be discussed. This chapter also highlights a set of design goals for increasing the visual, physical and cognitive realism when building VP systems including the design of the language, scenarios and artwork that is important when developing these characters. Finally, future research directions and challenges will be discussed for conversational virtual patients.
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2. Need For Clinician Training In Conversation Skills

Developing good conversational skills is essential for clinicians to establish good doctor patient relationships. Many undergraduate and postgraduate medical education and training programs have begun to place greater emphasis on the importance of high-quality conversation skills (ACGME; 2007). Traditional approaches to training clinicians in the conversation skills needed for assessment, diagnosis, and interview performance rely upon a combination of classroom learning and role-playing with human standardized patients.

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