Aims: This study introduces and evaluates a virtual reality (VR) prototype designed for the Loving-Kindness Meditation (LKM) to support mental health rehabilitation and relaxation in clinical contexts. The aims include the co-creation of a VR-based mindfulness experience with clinical experts and the evaluation of its usability, user experience, and short-term effects on relaxation, affect, and self-compassion.

Methods: Following a design thinking and co-creation approach, the VR-based LKM experience was developed iteratively with input from clinicians and computer scientists. The final prototype was implemented for the Meta Quest 3 and included five immersive scenes representing phases of the LKM and transition moments guided by a professional voice recording. Eleven participants (M = 36.5 years, SD = 14.6) experienced the 12-minute session. Pre- and post-session measures included relaxation, positive and negative affect schedule, self-compassion, and usability, complemented by the Igroup Presence Questionnaire and a semi-structured qualitative interview.

Results: Participants reported significant decreases in negative affect (t(10) = -2.512, p = .0307, d = -1.037) and stress (t(10) = -3.318, p = .007, d = -1.328), as well as increases in relaxation (t(10) = 5.487, p < .0001, d = 2.471) and self-compassion (t(10) = 2.231, p = .0497, d = 0.283). Usability was rated as excellent (M = 92.5), and presence as good (M = 4.0, SD = 0.43). Qualitative feedback described the experience as calming, aesthetically pleasing, and easy to engage with, highlighting the falling leaves and pulsating orb as effective design elements.

Conclusion: The co-designed VR-LKM prototype was perceived as highly usable and beneficial for inducing relaxation and self-compassion, suggesting its potential as a supportive tool for clinical mindfulness interventions. The results indicate that immersive VR can effectively facilitate engagement and emotional regulation, providing a foundation for future clinical trials and broader implementation in therapeutic and wellness settings.

Aims: We present an early investigation of how people interact with human-like Artificial Intelligence (AI) agents in virtual reality when discussing ideologically sensitive topics. Specifically, it examines how users respond to AI agents that express either congruent or incongruent opinions on a controversial issue, and how alignment, modality, and agent behaviors shape perceived conversation quality, psychological comfort, and agent credibility.

Methods: We conducted a 2 (agent opinion: congruent vs. incongruent) × 2 (input modality: text vs. voice) between-subjects experiment with 36 participants who engaged in five-minute virtual reality (VR)-based conversations with a GPT-4-powered AI agent about U.S. gun laws. Participants completed pre- and post-study measures of opinion and emotional states, evaluated the agent, and reflected on the interaction. In addition, dialogue transcripts were analyzed using the Issue-based Information System (IBIS) framework to characterize argument structure and engagement patterns.

Results: Participants engaged willingly with the AI agent regardless of its stance, and qualitative responses suggest that the interactions were generally respectful and characterized by low emotional intensity. Quantitative results show that opinion alignment influenced perceived bias and conversational impact, but did not affect the agent’s competence or likability. While voice input yielded richer dialogue, it also heightened perceived bias. Qualitative findings further highlight participants’ sensitivity to the agent’s ideological stance and their preference for AI agents whose views aligned with their own.

Conclusion: Our study suggests that AI agents embodied in VR can support ideologically challenging conversations without inducing defensiveness or discomfort when designed for neutrality and emotional safety. These findings point to early design directions for conversational agents that scaffold reflection and perspective-taking in politically or ethically sensitive domains.

Aims: This study examined the speed of approach-avoidance actions in virtual reality (VR) as an indicator of psychological “readiness” to interact with social avatars.

Aims: This study examined the speed of approach-avoidance actions in virtual reality (VR) as an indicator of psychological “readiness” to interact with social avatars.

Methods: Given that fast response is a key psychological factor reflecting a user’s interest, motivation, and willingness to engage, we analyzed the response time of pulling or pushing inputs, typical actions showing approach-avoidance tendency, via bare-hand interaction in VR. We specifically investigated how the response time varied according to participants’ social resources, particularly the richness of their social lives characterized by broader networks of friends, social groups, and frequent interactions.

Results: Results showed that participants with richer social lives exhibited faster pulling (vs. pushing) actions toward both same- and opposite-sex avatars. These effects remained significant regardless of participants’ gender, age, and prior VR experience. Notably, the observed effects were specific to social stimuli (i.e., avatars) and were not revealed with non-social stimuli (i.e., a flag). Additionally, the effects did not occur with other indirect interactions (i.e., a mouse wheel or a virtual joystick).

Conclusion: The findings suggest that social resources may facilitate approach-oriented bodily affordances in VR environments.

Aims: This scoping review systematically maps the existing literature at the intersection of virtual reality (VR), synthetic speech, and affective computing. As immersive and voice-based technologies gain traction in education, mental health, and entertainment, it is critical to understand how synthetic speech shapes emotional experiences in VR environments. The review clarifies how these concepts are defined, how they contribute to empathic computing, and identifies common applications, methodological approaches, research gaps, and ethical considerations.

Methods: A comprehensive search across multiple databases (e.g., ACM Digital Library, IEEE Xplore, ScienceDirect) was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) framework. Eligible studies investigated synthetic or computer-generated speech in VR or comparable immersive 3D settings and assessed emotional responses or related outcomes. Data were extracted on study characteristics, applied technologies, affect-related measures, and reported effects.

Results: The findings reveal a growing interdisciplinary body of research at the convergence of synthetic speech technologies, embodied virtual agents, and affective data processing in immersive environments. Interest in this area has accelerated with the development of advanced text-to-speech models, suggesting increasing relevance and expansion of this topic.

Conclusion: This review underscores a rapidly expanding yet fragmented research landscape. It highlights conceptual and methodological gaps, stressing the need for clearer definitions, standardized evaluation measures, and ethically informed design of synthetic speech in VR. The results provide a foundation for advancing research and applications in emotionally responsive virtual environments.

Aims: Storytelling has evolved alongside human culture, giving rise to new media such as social robots. While these robots employ modalities similar to those used by humans, they can also utilize non-biomimetic modalities, such as color, which are commonly associated with emotions. As research on the use of colored light in robotic storytelling remains limited, this study investigates its integration through three empirical studies.

Methods: We conducted three studies to explore the impact of colored light in robotic storytelling. The first study examined the effect of emotion-inducing colored lighting in romantic storytelling. The second study employed an online survey to determine appropriate light colors for specific emotions, based on images of the robot’s emotional expressions. The third study compared four lighting conditions in storytelling: emotion-driven colored lights, context-based colored lights, constant white light, and no additional lighting.

Results: The first study found that while colored lighting did not significantly influence storytelling experience or perception of the robot, it made recipients felt more serene. The second study showed improved recognition of amazement, rage, and neutral emotional states when colored light accompanied body language. The third study revealed no significant differences across lighting conditions in terms of storytelling experience, emotions, or robot perception; however, participants generally appreciated the use of colored lights. Emotion-driven lighting received slightly more favorable subjective evaluations.

Conclusion: Colored lighting can enhance the emotional expressiveness of robots. Both emotion- driven and context-based lighting strategies are appropriate for robotic storytelling. Through this series of studies, we contribute to the understanding of how colored lights are perceived in robotic communication, particularly within storytelling contexts.

Aims: This study aims to enhance the design of augmented reality (AR) technologies for remote collaboration by examining the complex relationships among individual factors (user characteristics), psychological and physiological states during AR-mediated remote collaboration, and outcomes within an Input-Mediator-Output (IMO) model. The goal is to evaluate how individual characteristics influence psychological and physiological experiences, as well as task performance, in AR-mediated collaboration.

Methods: We hypothesize and evaluate an IMO model and use correlation analyses to examine the relationships among person-related input variables (e.g., predispositions, traits, attitudes, states, and contextual factors), psychological and physiological emergent states, and performance-related output variables.

Results: Our results demonstrate that individual characteristics significantly influence subjective experiences, physiological responses, and task performance, emphasizing the critical role of individual differences, alongside task- and technology-related factors, in shaping collaboration experiences and performance. These findings highlight the importance of considering individual characteristics in the design of AR tools to optimize user well-being and performance outcomes.

Conclusion: Our study provides a foundational framework for understanding the interplay between individuals, tasks, and technology, underscoring the need for AR tools that align with user characteristics. It also lays the groundwork for future IMO research in AR-mediated remote collaboration, contributing to the development of more effective and health-promoting AR technologies.

This paper explores two virtual child simulators, BabyX and the VR Baby Training Tool, which provide immersive, interactive platforms for child-focused research and training. These technologies address key ethical and practical constraints, enabling the systematic study of caregiver-infant interactions and the development of professional relational skills with young children. We examine their design, features, and applications, as well as their future trajectories, highlighting their potential to advance research and improve training methodologies.

Aims: To give a comprehensive understanding of current research on immersive empathic computing, this paper aims to present a systematic review of the use of Virtual Reality (VR), Mixed Reality (MR), and Augmented Reality (AR) technologies in empathic computing, to identify key research trends, gaps, and future directions.

Methods: The PRISMA methodology was applied using keyword-based searches, publishing venue selection, and citation thresholds to identify 77 papers for detailed review. We analyze these papers to categorize the key areas of empathic computing research, including emotion elicitation, emotion recognition, fostering empathy, and cross-disciplinary applications such as healthcare, learning, entertainment and collaboration.

Results: Our findings reveal that VR has been the dominant platform for empathic computing research over the past two decades, while AR and MR remain underexplored. Dimensional emotional models have influenced this domain more than discrete emotional models for eliciting, recognizing emotions and fostering empathy. Additionally, we identify perception and cognition as pivotal factors influencing user engagement and emotional regulation.

Conclusion: Future research should expand the exploration of AR and MR for empathic computing, refine emotion models by integrating hybrid frameworks, and examine the relationship between lower body postures and emotions in immersive environments as an emerging research opportunity.

Aims: Recent world events have resulted in companies using remote meeting tools more often in design processes. The shift to remote meeting tools has had a notable impact on collaborative design activities, such as design reviews (DRs). When DRs depend on computer-aided design (CAD) software, the lack of direct support for CAD functionalities in videoconferencing applications introduces novel communication challenges, i.e. friction. This study investigates friction encountered in real world remote DRs when using a combination of standard CAD and videoconferencing applications. The objective was to understand the main sources of friction when carrying out DRs using a combination of CAD and videoconferencing applications.

Methods: At a single Swedish automobile manufacturer, 15 DRs of a fixture component were passively observed. These observations were subjected to a qualitative thematic analysis to identify categories and sources of friction during these DRs. The DRs were carried out using a combination of CATIA CAD software and Microsoft Teams for videoconferencing.

Results: The analysis of the 15 remote DRs identified four recurring friction categories: requesting specific viewpoints, indicating specific elements, expressing design change ideas, and evaluating ergonomics. Each category highlights specific challenges that were observed during the DRs and emerged due to constraints imposed by existing methods and technologies for remote meetings.

Conclusion: This study provides a framework for understanding the current sources of friction in remote DRs using videoconferencing tools. These insights can support the future development of DR software tools, guiding the integration of features that address these friction points. Additionally, the results serve as a guideline for organizations to implement methods that reduce friction in remote DRs and improve DR quality and efficacy.