Virtual reality stimulation and organizational neuroscience for the assessment of empathy - Parra Vargas, Elena; García Delgado, Aitana; Torres, Sergio C.; Carrasco-Ribelles, Lucía A.; Marín-Morales, Javier; Alcañiz Raya, Mariano (Frontiers in Psychology, 2022)
The aim of this study was to evaluate the viability of a new procedure based on machine learning (ML), virtual reality (VR) and implicit measures to discriminate empathy. Specifically, eye-tracking and decision-making patterns were used to classify individuals according to their level in each of the empathy dimensions, while they were immersed in virtual environments that represented social workplace situations. The virtual environments were designed using an evidence-centered design approach. Interaction and gaze patterns were recorded for 82 subjects, who were classified as high or low on each of the empathy dimensions: Perspective Taking, Emotional Understanding, Empathetic Stress, and Empathetic Joy. Dimensions were assessed using Cognitive and Affective Empathy Test. A ML model that combined behavior outputs and eye-gaze patterns was developed to predict empathy dimensions level of subjects (high vs low). The results indicated that the different dimensions could be differentiated by eye-gaze patterns and behaviors carried out during immersive VR. Eye-tracking measures contributed more significantly to this differentiation than behavioral metrics. This study illustrates de potential of a novel virtual reality organizational environment (VROE) coupled with machine learning to discriminate all empathy dimensions.