As AI-generated health information proliferates online and becomes increasingly indistinguishable from human-sourced information, it becomes critical to understand how people trust and label such content, especially when the information is inaccurate. We conducted two complementary studies: (1) a mixed-methods survey (N=142) employing a 2 (source: Human vs. LLM) x 2 (label: Human vs. AI) x 3 (type: General, Symptom, Treatment) design, and (2) a within-subjects lab study (N=40) incorporating eye-tracking and physiological sensing (ECG, EDA, skin temperature). Participants were presented with health information varying by source-label combina tions and asked to rate their trust, while their gaze behavior and physiological signals were recorded. We found that LLM-generated information was trusted more than human-generated content, whereas information labeled as human was trusted more than that labeled as AI. Trust remained consistent across information types. Eye-tracking and physiological responses varied significantly by source and label. Machine learning models trained on these behavioral and physiological features predicted binary self-reported trust levels with 73 % accuracy and infor mation source with 65 % accuracy. Our findings demonstrate that adding transparency labels to online health information modulates trust. Behavioral and physiological features show potential to verify trust perceptions and indicate if additional transparency is needed.

Background:Virtual reality (VR) is showing increasing promise for assessing, understanding, and treating mental health difficulties. Virtual humans (VHs) represent a key aspect within many VR mental health applications. While VHs can play diverse roles and display varied characteristics, their design and influence have rarely been the primary focus of mental health research. Objective:We aimed to carry out a systematic review of how VHs in immersive VR have been used in applications for mental health, focusing on their roles and interaction types, and the human characteristics being tested. Methods:Following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, we searched PubMed, MEDLINE, PsycINFO, Scopus, and Web of Science, using defined keyword combinations involving VR, VHs, and mental health. Eligible studies included peer-reviewed research using immersive VR with VHs in a mental health context, without restrictions on study design or population. We excluded nonimmersive VR, nonmental health applications, and papers without empirical data. Data were synthesized narratively, and a taxonomy to categorize VHs that we developed was used. Results:A total of 79 studies met all eligibility criteria. VHs were most frequently applied in studies on social anxiety (n=18), eating disorders (n=18), and psychosis (n=15). They were primarily used as active social interaction partners (n=40), as part of virtual crowds (n=16), and as virtual bodies for participants (n=23). Explicit interactions dominated active partner studies, while implicit and passive or no interactions were prevalent in crowd and body studies. Over half of the studies (n=44) varied the VH characteristics, with body size and gender being the most common variables, and personality was explored in fewer studies (n=5). Only a limited number of studies provided detailed descriptions of VH appearance and behavior, with some including still images and videos. Conclusions:VHs are versatile tools to be used within VR mental health applications, but their design features are inconsistently reported and insufficiently examined in relation to intervention outcomes. Evidence is limited by heterogeneity in study aims, designs, and populations, and by incomplete reporting of VH characteristics, which constrains replication and cross-study comparison. Standardized reporting and systematic investigations of VH design are needed to optimize their roles in evidence-based mental health applications.

Virtual coaches in virtual reality (VR) offer scalable mental health treatment without an on-site therapist, yet their impact on psychophysiological responses remains unclear. We examine how VR content and coach design influence physiological measures, such as heart rate (HR) and electrodermal activity (EDA), in a therapeutic setting. 120 participants with a fear of heights interacted with a virtual coach that varied in facial warmth (with/without) and affirmative nods (with/without) during a virtual consultation, followed by a virtual height exposure. Physiological responses were recorded. Virtual heights exposure elicited significantly higher HR (p < 0.001, r = 0.347) and EDA (p = 0.003, r = 0.292), but also increased heart rate variability (HRV, p = 0.005, r = 0.272) compared to the VR consultation. Warm facial expressions increased EDA peak amplitudes (p = 0.043, eta(2)(p) = 0.574) during the consultation and raised HRV during height exposure (p = 0.036, eta(2)(p) = 0.041). This study highlights VR coach design's impact on physiological responses, emphasising the need for thoughtful emotional design to enhance therapeutic outcomes in automated VR therapies.

The Internet of Multisensory, Multimedia, and Mu-sical Things (Io3MT) is an emerging field at the intersection of computer science, arts, and humanities. It focuses on integrating technologies and datasets to explore human sensory perception, multimedia elements, and musical compositions for artistic and entertainment purposes. This position paper advocates for merging Io3mtwith Extended Reality (XR) in creative contexts. Through literature review and expert focus group discussions, we have identified five key design guidelines that aid in the development of immersive environments for artistic creation within the Io3mtframework. We developed PhysioDrum as a practical demonstration of these guidelines. This work provides insights into the infrastructure, tools, opportunities, and research challenges arising from integrating Io3mtand XR.

AbstractVirtual reality (VR) is increasingly used in the study and treatment of paranoia. This is based on the finding that people who mistakenly perceive hostile intent from other people also perceive similar threat from virtual characters. However, there has been no study of the programming characteristics of virtual characters that may influence their interpretation. We set out to investigate how the animation and expressions of virtual humans may affect paranoia. In a two-by-two factor, between-groups, randomized design, 122 individuals with elevated paranoia rated their perceptions of virtual humans, set in an eye-tracking enabled VR lift scenario, that varied in facial animation (static or animated) and expression (neutral or positive). Both facial animation (group difference = 102.328 [51.783, 152.872], p < 0.001, $${\eta }_{p}^{2}\hspace{0.17em}$$ η p 2 = 0.125) and positive expressions (group difference = 53.016 [0.054, 105.979], p = 0.049, $${\eta }_{p}^{2}\hspace{0.17em}$$ η p 2 = 0.033) led to less triggering of paranoid thoughts about the virtual humans. Facial animation (group difference = 2.442 [− 4.161, − 0.724], p = 0.006, $${\eta }_{p}^{2}\hspace{0.17em}$$ η p 2 = 0.063) but not positive expressions (group difference = 0.344 [− 1.429, 2.110], p = 0.681, $${\eta }_{p}^{2}\hspace{0.17em}$$ η p 2 = 0.001) significantly increased the likelihood of neutral thoughts about the characters. Our study shows that the detailed programming of virtual humans can impact the occurrence of paranoid thoughts in VR. The programming of virtual humans needs careful consideration depending on the purpose of their use.

We set out to understand the visual attention and perception of virtual humans in individuals vulnerable to paranoia in a VR eye-tracking study. In a factorial between-groups design, 122 individuals with elevated paranoia experienced a virtual lift ride with virtual humans that varied in facial animation (static or animated) and expression (neutral or positive). Facial animation (p = 0.053) led to a significant reduction in co-presence. Positive expressions (p-adj = 0.046) significantly decreased the visual attention to virtual humans when their faces were static. Our results indicate that virtual human programming could influence user perception and visual behaviours for people with mistrust.

We introduce a VR gravity calculator for the "Next-Gen Calculators" challenge. This interactive tool enables users to calculate gravitational forces by inputting planetary radius and mass, employing advanced controller movement tracking and eye-hand coordination for interaction. It also has different planets and materials presets, allowing automatic data retrieval and hypothetical exploration. It visualises and simulates the gravitational forces in real-time through a fun fruit-falling effect. Our calculator aims to transform geophysics education by making complex concepts accessible and engaging through tangible simulation. This innovative approach bridges theoretical knowledge with practical application, offering a responsive and interactive learning experience in geophysics.

We set out to test whether positive non-verbal behaviours of a virtual coach can enhance people's engagement in automated virtual reality therapy. 120 individuals scoring highly for fear of heights participated. In a two-by-two factor, between-groups, randomised design, participants met a virtual coach that varied in warmth of facial expression (with/without) and affirmative nods (with/without). The virtual coach provided a consultation about treating fear of heights. Participants rated the therapeutic alliance, treatment credibility, and treatment expectancy. Both warm facial expressions (group difference = 7.44 [3.25, 11.62], p = 0.001, eta_p^2 =0.10) and affirmative nods (group difference = 4.36 [0.21, 8.58], p = 0.040, eta_p^2 = 0.04) by the virtual coach independently increased therapeutic alliance. Affirmative nods increased the treatment credibility (group difference = 1.76 [0.34, 3.11], p = 0.015, eta_p^2 = 0.05) and expectancy (group difference = 2.28 [0.45, 4.12], p = 0.015, eta_p^2 = 0.05) but warm facial expressions did not increase treatment credibility (group difference = 0.64 [− 0.75, 2.02], p = 0.363, eta_p^2 = 0.01) or expectancy (group difference = 0.36 [− 1.48, 2.20], p = 0.700, eta_p^2 = 0.001). There were no significant interactions between head nods and facial expressions in the occurrence of therapeutic alliance (p = 0.403, eta_p^2 = 0.01), credibility (p = 0.072, eta_p^2 = 0.03), or expectancy (p = 0.275, eta_p^2 = 0.01). Our results demonstrate that in the development of automated VR therapies there is likely to be therapeutic value in detailed consideration of the animations of virtual coaches.

This paper presents the preliminary results of an accuracy testing of the Meta Quest Pro’s eye tracker. We conducted user testing to evaluate the spatial accuracy, spatial precision and subjective performance under head-free and head-restrained conditions. Our measurements indicated an average accuracy of 1.652° with a precision of 0.699° (standard deviation) and 0.849° (root mean square) for a visual field spanning 15° during head-free. The signal quality of Quest Pro’s eye-tracker is comparable to existing AR/VR eye-tracking headsets. Notably, careful considerations are required when designing the size of scene objects, mapping areas of interest, and determining the interaction flow. Researchers should also be cautious about interpreting the fixation results when multiple targets are within close proximity. Further investigation and better specification information transparency are needed to establish its capabilities and limitations.

This PhD research aims to implement dynamic facial expressions on virtual humans and explore their potential to enhance the efficacy of virtual reality (VR) mental health therapy. A systematic review of virtual humans in mental health VR indicated that only around 10% of applications used dynamic facial expressions. The potential of virtual humans' emotion richness is understudied and it is unclear how the facial expressions affect the individuals in VR. Therefore, we will focus on understanding people's behavioural, physiological, and psychological reactions toward facial-animated humans in VR experimental studies. The first study examines whether particular non-verbal behaviours can enhance people's therapy engagement, by applying warm facial expressions and head nods on a virtual coach. Future experiments will further look at individuals' interpretations of facial expressions on virtual crowds and the virtual infant. This research will explore how best to use facial expressions to facilitate VR therapy through the practice of psychiatric research, VR programming and 3D animation.

Virtual reality (VR) simulations with virtual characters have been increasingly deployed to understand context-based human behaviour. The current study investigated the effects of perceived agency of the other players, who were either (human-controlled) avatars or (computer-controlled) agents, on the player’s overall presence levels (with 3 subscales of spatial presence, involvement, and realism). We also tested the relationship between the player’s perception of the agency of the other players, in-game prosocial behaviour (voluntary behaviour to help other players) and their own real-life prosocial traits. 32 university students played a VR game with agents, but half the participants were told they were playing with avatars (an experimental deception). The group who were told they were playing with other humans had higher overall presence than the group who knew they were playing with agents, due to increased spatial presence and involvement. While there was no direct link between the player’s perceived agency of the other players and their own in-game behaviours, higher prosocial scores increased their chance of helping the other players in the agent group. Overall, this study suggests that multi-player VR experiences (or those purported to be multi-player) lead to greater influence on people’s psychological and behavioural reactions over single-player experiences.