DUPUY, Lucile; DE SEVIN, Etienne; BALLOT, Orlane; CASSOUDESALLE, Hélène; DEHAIL, Patrick; AOUIZERATE, Bruno; CUNY, Emmanuel; MICOULAUD-FRANCHI, Jean-Arthur; PHILIP, Pierre

doi:10.1145/3308532.3329429

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DUPUY, Lucile

Sommeil, Addiction et Neuropsychiatrie [Bordeaux] [SANPSY]

DE SEVIN, Etienne
Sommeil, Addiction et Neuropsychiatrie [Bordeaux] [SANPSY]

BALLOT, Orlane
Université Laval [Québec] [ULaval]

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Ce document a été publié dans

Proceedings of the 19th ACM International Conference on Intelligent Virtual Agents, 2019-07-02, Paris.

ACM Press

Résumé en anglais

Psychiatric diagnostic relies on physician’s ability to create an empathic interaction with the patient (i.e., engage the patient in the conversation with empathic sentences, while keeping an emotional distance) in order to accurately extract semiology (i.e., clinical manifestations). Virtual patients (VPs) offer new ways to train these skills but need to be validated in terms of accuracy to measure the skills of interest, and be perceived positively by its users. We recruited 34 medicine students, who interacted with a VP suffering from depressive disorders. Results suggest good abilities for the students to use empathic sentences to communicate with the VP, but results varied regarding semiology extraction, students having a specialty in psychiatry performing better than their counterparts. Additionally, results suggest that students managed to keep an emotional distance during the interaction with the VP, but they let their emotions out when answering semiology questions. Positive feedbacks and limitations raised by students during debriefing interviews provide suggestions for improvements and ideas for future works.< Réduire

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Virtual Patient

Medical training

User experience

Psychiatric Interview

Semiology

Empathic communication skills

Emotion Detection

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A Virtual Patient to Train Semiology Extraction and Empathic Communication Skills for Psychiatric Interview

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