Virtual Reality Training of Social Skills in Autism Spectrum Disorder: An Examination of Acceptability, Usability, User Experience, Social Skills, and Executive Functions

• URL: http://arxiv.org/abs/2304.07498v1
• Date: Sat, 15 Apr 2023 07:54:37 GMT
• Title: Virtual Reality Training of Social Skills in Autism Spectrum Disorder: An Examination of Acceptability, Usability, User Experience, Social Skills, and Executive Functions
• Authors: Panagiotis Kourtesis, Evangelia-Chrysanthi Kouklari, Petros Roussos, Vasileios Mantas, Katerina Papanikolaou, Christos Skaloumbakas, Artemios Pehlivanidis
• Abstract summary: Poor social skills in autism spectrum disorder (ASD) are associated with reduced independence in daily life. Virtual reality (VR) may facilitate social skills training in social environments and situations to real life. Twenty-five participants with ASD attended a neuropsychological evaluation and three sessions of VR social skills training.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Poor social skills in autism spectrum disorder (ASD) are associated with reduced independence in daily life. Current interventions for improving the social skills of individuals with ASD fail to represent the complexity of real-life social settings and situations. Virtual reality (VR) may facilitate social skills training in social environments and situations proximal to real life, however, more research is needed for elucidating aspects such as the acceptability, usability, and user experience of VR systems in ASD. Twenty-five participants with ASD attended a neuropsychological evaluation and three sessions of VR social skills training, incorporating five (5) social scenarios with three difficulty levels for each. Participants reported high acceptability, system usability, and user experience. Significant correlations were observed between performance in social scenarios, self-reports, and executive functions. Working memory and planning ability were significant predictors of functionality level in ASD and the VR system's perceived usability respectively. Yet, performance in social scenarios was the best predictor of usability, acceptability, and functionality level in ASD. Planning ability substantially predicted performance in social scenarios, postulating an implication in social skills. Immersive VR social skills training appears effective in individuals with ASD, yet an error-less approach, which is adaptive to the individual's needs, should be preferred.

Related papers

• Task-Based Role-Playing VR Game for Supporting Intellectual Disability Therapies [2.4150871564195007]
  Space Exodus is a task-based role-playing Virtual Reality (VR) game designed to support therapy for children with Intellectual Disability (ID) Game integrates everyday life scenarios into an immersive environment to enhance skill acquisition and transfer. Results provide empirical evidence supporting VR as a promising tool in ID therapy.
  arXiv  Detail & Related papers  (2024-12-16T09:46:00Z)
• SocialMind: LLM-based Proactive AR Social Assistive System with Human-like Perception for In-situ Live Interactions [3.7400236988012105]
  SocialMind is the first proactive AR social assistive system that provides users with in-situ social assistance. SocialMind employs human-like perception leveraging multi-modal sensors to extract both verbal and nonverbal cues, social factors, and implicit personas. We show that SocialMind achieves 38.3% higher engagement compared to baselines, and 95% of participants are willing to use SocialMind in their live social interactions.
  arXiv  Detail & Related papers  (2024-12-05T10:19:36Z)
• Social Skill Training with Large Language Models [65.40795606463101]
  People rely on social skills like conflict resolution to communicate effectively and to thrive in both work and personal life. This perspective paper identifies social skill barriers to enter specialized fields. We present a solution that leverages large language models for social skill training via a generic framework.
  arXiv  Detail & Related papers  (2024-04-05T16:29:58Z)
• SOTOPIA: Interactive Evaluation for Social Intelligence in Language Agents [107.4138224020773]
  We present SOTOPIA, an open-ended environment to simulate complex social interactions between artificial agents and humans. In our environment, agents role-play and interact under a wide variety of scenarios; they coordinate, collaborate, exchange, and compete with each other to achieve complex social goals. We find that GPT-4 achieves a significantly lower goal completion rate than humans and struggles to exhibit social commonsense reasoning and strategic communication skills.
  arXiv  Detail & Related papers  (2023-10-18T02:27:01Z)
• Learning Roles with Emergent Social Value Orientations [49.16026283952117]
  This paper introduces the typical "division of labor or roles" mechanism in human society. We provide a promising solution for intertemporal social dilemmas (ISD) with social value orientations (SVO) A novel learning framework, called Learning Roles with Emergent SVOs (RESVO), is proposed to transform the learning of roles into the social value orientation emergence.
  arXiv  Detail & Related papers  (2023-01-31T17:54:09Z)
• Social learning spontaneously emerges by searching optimal heuristics with deep reinforcement learning [0.0]
  We employ a deep reinforcement learning model to optimize the social learning strategies of agents in a cooperative game in a multi-dimensional landscape. We find that the agent spontaneously learns various concepts of social learning, such as copying, focusing on frequent and well-performing neighbors, self-comparison, and the importance of balancing between individual and social learning. We demonstrate the superior performance of the reinforcement learning agent in various environments, including temporally changing environments and real social networks.
  arXiv  Detail & Related papers  (2022-04-26T15:10:27Z)
• The world seems different in a social context: a neural network analysis of human experimental data [57.729312306803955]
  We show that it is possible to replicate human behavioral data in both individual and social task settings by modifying the precision of prior and sensory signals. An analysis of the neural activation traces of the trained networks provides evidence that information is coded in fundamentally different ways in the network in the individual and in the social conditions.
  arXiv  Detail & Related papers  (2022-03-03T17:19:12Z)
• Using Psychological Characteristics of Situations for Social Situation Comprehension in Support Agents [8.778914180886833]
  We show that psychological characteristics of situations can be used as input to predict the priority of social situations. We show that psychological characteristics can be successfully used as a basis for explanations given to users about the decisions of an agenda management personal assistant agent.
  arXiv  Detail & Related papers  (2021-10-15T15:42:43Z)
• PHASE: PHysically-grounded Abstract Social Events for Machine Social Perception [50.551003004553806]
  We create a dataset of physically-grounded abstract social events, PHASE, that resemble a wide range of real-life social interactions. Phase is validated with human experiments demonstrating that humans perceive rich interactions in the social events. As a baseline model, we introduce a Bayesian inverse planning approach, SIMPLE, which outperforms state-of-the-art feed-forward neural networks.
  arXiv  Detail & Related papers  (2021-03-02T18:44:57Z)
• Emergent Social Learning via Multi-agent Reinforcement Learning [91.57176641192771]
  Social learning is a key component of human and animal intelligence. This paper investigates whether independent reinforcement learning agents can learn to use social learning to improve their performance.
  arXiv  Detail & Related papers  (2020-10-01T17:54:14Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.