Training doctors’ social skills to break bad news: evaluation of the impact of virtual environment displays on the sense of presence

Abstract

The way doctors deliver bad news has a significant impact on the therapeutic process. In order to facilitate doctor's training, we have developed an embodied conversational agent simulating a patient to train doctors to break bad news. In this article, we present an evaluation of the virtual reality training platform comparing the users' experience depending on the virtual environment displays: a PC desktop, a virtual reality headset, and four wall fully immersive systems. The results of the experience, including both real doctors and naive participants, reveal a significant impact of the environment display on the perception of the user (sense of presence, sense of co-presence, perception of the believability of the virtual patient), showing, moreover, the different perceptions of the participants depending on their level of expertise.

Special issue editorial: Virtual Agents for Social Skills Training

“…The users had to communicate a medical situation to a virtual patient via the three different displays. Results showed higher scores on the sense of presence for the HMD and virtual reality cave compared to the PC screen [2]. This adds to the growing body of evidence that more immersive devices lead to higher presence in the virtual world.…”

Toward an Automatic Prediction of the Sense of Presence in Virtual Reality Environment

“…Note that the goal of this work is not to predict the different interaction modes (PC, virtual reality headset, or virtual reality room), but the levels of presence and co-presence. We have shown in [18] that the three interaction modes imply different levels of presence and co-presence.…”

“…A statistical analysis of the effects of the virtual reality displays and of the type of the participant (doctors versus naive) on the behavior displayed and on the sense of presence and co-presence is described in details in [18]. In this paper, we focus on the automatic prediction of the sense of presence and co-presence by considering the type of participant and their verbal and non-verbal behavior as key features.…”

Multimodal Cues of the Sense of Presence and Co-presence in Human-Virtual Agent Interaction

“…A platform has been developed with a virtual patient with which the doctors can interact in natural language. In total, the corpus is composed of interactions of 38 persons (28 males, 10 females) with a mean age of 29 years (SD:10.5), each of them interacting three times in three different environment (PC, VR headset, and CAVE) (for more details on the collected corpus see [9]). Each interaction is described by a set of features characterizing user's and agent's verbal and non-verbal cues and described in details in [8].…”

“…Moreover, we have collected questionnaires assessing the sense of presence and co-presence of the user after the interaction. Technically, different virtual reality displaysknown to generate different degrees of immersion -have been used to collect different experiences in terms of sense of presence (the corpus is described in more details in [9]). Starting from this dataset, we have learned different models to analyze the importance of verbal and non-verbal cues as features to predict different levels of presence and co-presence.…”