An Immersive Virtual Reality Game for Predicting Risk Taking through the Use of Implicit Measures

Abstract

Risk taking (RT) measurement constitutes a challenge for researchers and practitioners and has been addressed from different perspectives. Personality traits and temperamental aspects such as sensation seeking and impulsivity influence the individual’s approach to RT, prompting risk-seeking or risk-aversion behaviors. Virtual reality has emerged as a suitable tool for RT measurement, since it enables the exposure of a person to realistic risks, allowing embodied interactions, the application of stealth assessment techniques and physiological real-time measurement. In this article, we present the assessment on decision making in risk environments (AEMIN) tool, as an enhanced version of the spheres and shield maze task, a previous tool developed by the authors. The main aim of this article is to study whether it is possible is to discriminate participants with high versus low scores in the measures of personality, sensation seeking and impulsivity, through their behaviors and physiological responses during playing AEMIN. Applying machine learning methods to the dataset we explored: (a) if through these data it is possible to discriminate between the two populations in each variable; and (b) which parameters better discriminate between the two populations in each variable. The results support the use of AEMIN as an ecological assessment tool to measure RT, since it brings to light behaviors that allow to classify the subjects into high/low risk-related psychological constructs. Regarding physiological measures, galvanic skin response seems to be less salient in prediction models.

Virtual reality and speech analysis for the assessment of impulsivity and decision-making: protocol for a comparison with neuropsychological tasks and self-administered questionnaires

“…The VR task successfully discriminated between low-risk and high-risk individuals. 33 However, the SSMT has not been validated in clinical settings. Similarly, speech analysis has not been sufficiently studied as an ecological measure for analysing impulsivity in mental healthcare settings.…”

“…42 43 Eye movement and electrodermal activity are a part of the SSMT VR task that was incorporated in the latest updates of the task to improve the general scores of the VR task. 33 As such, they will not be analysed separately from the VR task.…”

“…This study presents the VR assessment tool ‘Spheres & Shield Maze Task’ (SSMT), a virtual maze that participants must go through while overcoming several obstacles, which provides an immersive experience that can approximate real-life conditions, thus increasing ecological validity. The VR tool has been previously evaluated in non-clinical settings in two studies 32 33. In the first pilot study, the SSMT was explored in 41 students.…”

Combining Virtual Reality and Machine Learning for Leadership Styles Recognition

“…Furthermore, in leadership studies, ML has been used to identify traits that define the leadership role ( Doornenbal et al, 2021 ) and measure personality traits ( Hrazdil et al, 2020 ). The use of ML techniques for implicit measures gathered within virtual environments has occurred primarily in clinical psychology ( Alcañiz Raya et al, 2020a , b ) and less in organisational situations ( De-Juan-Ripoll et al, 2021 ).…”

Recognition of Customers’ Impulsivity from Behavioral Patterns in Virtual Reality

“…In this study, the analysis was performed based on post-interviews conducted after the VR experience [17]. A second study explored the impact of impulsivity on risky decisions through an immersive virtual reality game and physiological signals [66]. A third used self-assessment to investigate the impact of risky environments on the emerged level of impulsivity and sensation-seeking [67].…”