Virtual Reality Scenarios Research Articles

Stretching immersion in virtual reality: How glitches reveal aspects of presence, interactivity and plausibility

Virtual reality (VR) immerses users in others’ lives, creating empathy and understanding long after the VR scenario has finished. As VR technology has matured, VR scenarios have begun to be used in complex real-world areas such as education, health and organisational change. These scenarios can be of variable technical quality, with limited interactive capacity, unrealistic environments and clunky or absent avatars. In this study, three scenarios related to gender inequality training were constructed with glitches in the core immersive qualities of presence, interactivity and plausibility in order to understand their effect on the immersive experience. Using a multi-step in-depth series of qualitative interviews to examine the whole immersive process, the results show that immersion is not compromised but changed by glitches. Limited interactivity led to uncomfortable interactions that allowed participants to process difficult emotions; implausible situations surfaced buried norms and prejudices; and avatar variation gave rise to a sense presence that also included distance, which gave the user opportunities for critical reflection. These results point towards immersion as a robust and richly textured concept, while interactivity, plausibility and presence can best be understood as dimensions rather than goals. Totally seamless and immersive experiences may not only be utopian but also unnecessary. The glitches in low-end productions can produce powerful communication without expensive technology.

EEG-based spatial elements optimisation design method

In the field of digital design, a recent hot topic is the study of the interaction between spatial environment design and human factors. Electroencephalogram (EEG) and eye tracking can be used as quantitative analysis methods for architectural space evaluation; however, conclusions from existing studies on improving the quality of spatial environments based on human factors tend to remain qualitative. In order to realise the quantitative optimisation design of spatial elements from human physiological data, this research used the digital space optimisation method and perceptual evaluation research. In this way, it established an optimisation method for built space elements in real-time using human psychological indicators. Firstly, this method used the specific indicators of the Meditation value and Attention value in the human EEG signal, taking the ThinkGear AM (TGAM) module as the optimisation objective, the architectural space colour and the window size as the optimisation object, and the multi-objective genetic algorithm as the optimisation tool. Secondly, this research combined virtual reality scenarios and parametric linkage models to realise this optimisation method to establish a tool platform and workflow. Thirdly, this study took the optimisation of a typical living space as an example and recruited 50 volunteers to participate in an optimisation experiment. The results indicated that with the iterative optimisation of the multi-objective genetic algorithm, the specific EEG index decreases significantly and the standard deviation of the in-dex fluctuates and decreases during the iterative process, which further indicates that the optimisation method established in this study with the specific EEG index as the optimisation objective is effective and feasible. In addition, this study laid the foundation for more EEG indicators and more complex spatial element opti-misation research in the future.

Virtual reality wraparound learning modules: an innovative approach to self-debriefing to augment learner experience

Virtual Reality (VR) simulation has opened to a lot of trainees an ability to experience various clinical scenarios in a virtual space at a time and place that suits them [1]. It also gives an opportunity for deliberate practice as one can repeat the scenario as many times as one likes till proficiency is reached. Research over the years has shown most of the learning occurs during the debriefing [2] and the VR scenario gives a unique opportunity for self-debriefing or peer-peer debriefing in small groups [3]. However, in the current VR scenarios available to trainees, there is no provision of any link at the end of the scenario to access current best practice guidelines on the topic/scenario which the learner could use as part of their self-debriefing. The project aims to create wraparound learning module around the Virtual Reality clinical scenario to include a patient journey through the hospital, current guidelines, and teaching videos so that learners could conceptualize and consolidate their learning from the VR experience VR scenarios available to Foundation doctors were chosen and a review of the topic and related standard best practice guidelines were reviewed on NICE, BTS, and similar resources. We also searched for real patient stories and easy to access procedural videos related to the topic and incorporated them on the module. Wraparound learning modules were created using a blended learning approach on Bridge online platform on topics like pneumothorax and infective exacerbation of Chronic Obstructive Pulmonary Disease. More modules are being created for the benefit of the Foundation doctors across East of England. Throughout the module reflection is encouraged and the topic is aligned to the Foundation curriculum and reviewed for quality assurance. A Likert scale survey would be sent out to the trainees who have completed the modules to assess the increase in their confidence in managing a clinical case after finishing the wraparound module. The results of the pre-course and post-course levels of knowledge, skills and confidence are being analysed. Wraparound learning modules could potentially improve learners’ experience of the VR scenario and improve learning and confidence in the clinical setting. 1. Cheng A, Kolbe M, Grant V, Eller S, Hales R, Symon B, Griswold S, Eppich W. A practical guide to virtual debriefings: communities of inquiry perspective. Advances in Simulation. 2020;5(1):1–9. 2. Rudolph JW, Simon R, Dufresne RL, Raemer DB. There’s no such thing as ‘non-judgmental’ debriefing: a theory and method for debriefing with good judgment. Simul Healthcare. 2006;1(1):49–55. 3. Pottle J. Virtual reality and the transformation of medical education. Future healthcare journal. 2019;6(3):181–185.

Application of Machine Learning Techniques for Predicting Potential Vehicle-to-Pedestrian Collisions in Virtual Reality Scenarios

The definition of pedestrian behavior when crossing the street and facing potential collision situations is crucial for the design of new Autonomous Emergency Braking systems (AEB) in commercial vehicles. To this end, this article proposes the generation of classification models through the deployment of machine learning techniques that can predict whether there will be a collision depending on the type of reaction, the lane where it occurs, the visual acuity the level of attention, and consider the most relevant factors that determine the cognitive and movement characteristics of pedestrians. Thereby, the inclusion of this type of model in the decision-making algorithm of the AEB system allows for modulating its response. For this purpose, relevant information on pedestrian behavior is obtained through experiments made in an ad-hoc, Virtual Reality (VR) environment, using a portable backpack system in three urban scenarios with different characteristics. Database generation, feature selection, and k-fold cross-validation generate the inputs to the supervised learning models. A subsequent analysis of the accuracy, optimization, error measurement, variable importance, and classification capability is conducted. The tree-based models provide more balanced results for the performance metrics (with higher accuracy for the single decision tree case) and are more easily interpretable and adaptable to the algorithm. From them it is deduced the high importance of the reaction type and the relative position where it occurs, coinciding with the high significance of these factors in the analyzed collisions.

Study protocol-Evoked craving in high-dose benzodiazepine users.

Benzodiazepine (BDZ) abuse, especially concerning high doses of BDZs, is an impairing substance use disorder (SUD) that is often difficult to treat. Craving and cue reactivity (CR) are two important phenomena that have a prominent role in maintaining addiction and triggering relapses in BDZ abuse; nevertheless, they have rarely been addressed in scientific literature. The present study aims to fill these gaps by implementing a highly innovative virtual reality (VR) design to assess the impact of substance-related environmental cues on BDZ craving, as well as their influence on patients’ affective states. Therefore, on one hand, this research will contribute to the assessment of VR feasibility in the study of these phenomena, and, on the other, it will help disentangle the role that CR and craving have on mood and attention, which are equally important factors to consider when treating SUDs. We will recruit a healthy control group and a patient group comprising people seeking treatment for BDZ detoxification. The experimental design will consist of the presentation of three VR scenarios, one neutral, one BDZ-related but without BDZ cues, and another with BDZ cues. The craving will be measured through a virtual analog scale (VAS); the Profile of Mood States (POMS) and Alcohol Attention Scale (AAS) questionnaires in a modified version will also be administered. We will additionally control for VR-induced feelings of sickness by administering the Simulator Sickness Questionnaire (SSQ), and the Presence Questionnaire (PQ) will be used to investigate participants’ sense of presence in virtual environments. We expect patients to exhibit higher levels of craving, and that the craving will be higher after exposure to a cue-related virtual environment as compared to a neutral scenario.

Artificial intelligence in laparoscopic simulation: a promising future for large-scale automated evaluations.

IntroductionA limitation to expanding laparoscopic simulation training programs is the scarcity of expert evaluators. In 2019, a new digital platform for remote and asynchronous laparoscopic simulation training was validated. Through this platform, 369 trainees have been trained in 14 institutions across Latin America, collecting 6729 videos of laparoscopic training exercises. The use of artificial intelligence (AI) has recently emerged in surgical simulation, showing usefulness in training assessment, virtual reality scenarios, and laparoscopic virtual reality simulation. An AI algorithm to assess basic laparoscopic simulation training exercises was developed. This study aimed to analyze the agreement between this AI algorithm and expert evaluators in assessing basic laparoscopic-simulated training exercises.MethodsThe AI algorithm was trained using 400-bean drop (BD) and 480-peg transfer (PT) videos and tested using 64-BD and 43-PT randomly selected videos, not previously used to train the algorithm. The agreement between AI and expert evaluators from the digital platform (EE) was then analyzed. The exercises being assessed involve using laparoscopic graspers to move objects across an acrylic board without dropping any objects in a determined time (BD < 24 s, PT < 55 s). The AI algorithm can detect object movement, identify if objects have fallen, track grasper clamps location, and measure exercise time. Cohen’s Kappa test was used to evaluate the agreement between AI assessments and those performed by EE, using a pass/fail nomenclature based on the time to complete the exercise.ResultsAfter the algorithm was trained, 79.69% and 93.02% agreement were observed in BD and PT, respectively. The Kappa coefficients test observed for BD and PT were 0.59 (moderate agreement) and 0.86 (almost perfect agreement), respectively.ConclusionThis first approach of AI use in basic laparoscopic skills simulated training assessment shows promising results, providing a preliminary framework to expand the use of AI to other basic laparoscopic skills exercises.Supplementary InformationThe online version contains supplementary material available at 10.1007/s00464-022-09576-1.

Subjective Fear in Virtual Reality: A Linear Mixed-Effects Analysis of Skin Conductance

The investigation of the physiological and pathological processes involved in fear perception is complicated due to the difficulties in reliably eliciting and measuring the complex construct of fear. This study proposes a novel approach to induce and measure subjective fear and its physiological correlates combining virtual reality (VR) with a mixed-effects model based on skin conductance (SC). Specifically, we developed a new VR scenario applying specific guidelines derived from horror movies and video games. Such a VR environment was used to induce fear in eighteen volunteers in an experimental protocol, including two relaxation scenarios and a neutral virtual environment. The SC signal was acquired throughout the experiment, and after each virtual scenario, the emotional state and fear perception level were assessed using psychometric scales. We statistically evaluated the greatest sympathetic activation induced by the fearful scenario compared to the others, showing significant results for most SC-derived features. Finally, we developed a rigorous mixed-effects model to explain the perceived fear as a function of the SC features. Model-fitting results showed a significant relationship between the fear perception scores and a combination of features extracted from both fast- and slow-varying SC components, proposing a novel solution for a more objective fear assessment.

Fear, psychophysiological arousal, and cognitions during a virtual social skills training in social anxiety disorder while manipulating gaze duration

The use of virtual reality (VR) is an option for social skills training and exposure in Social Anxiety Disorder (SAD). In addition, virtual social situations are an ideal tool to study the influence of a counterpart’s social behavior, e. g. eye contact. We developed two scenarios in VR that enable users to practice to assert their rights. The participants’ tasks were to ask a passenger to release their reserved seat in a virtual train and to cancel a trip in a virtual travel agency. In a randomized, crossover design, we compared the effect of a large (during 80% of the conversation time) and a small (20%) amount of direct gaze by the virtual conversational partners in 41 patients with SAD and 21 healthy controls (HCs). We expected fear and psychophysiological arousal to be higher in patients than in HCs and higher in the 80% eye contact condition. The scenarios provoked an increase of fear and psychophysiological arousal over baseline in patients and in HCs. Gaze duration of the virtual agent had no influence on fear and psychophysiological arousal, but affected the experience of presence. Our results suggest a suitability of our scenarios for social skills training and exposure therapy in SAD. The lack of influence of gaze duration on parameters of fear might be explained by the fact that participants did not consciously detect the differences in gaze duration. However, the impact on some parameters (e. g. presence) suggests that participants noticed differences in gaze duration on a subliminal level.

Emulating Textures Using Vibrotactile Technology: HaptTech System and its Adaptation to a Commercial Kinesthetic Interface

This article presents the development and testing of a tactile interface prototype, HaptTech, that applies vibrotactile stimulation patterns to the fingertip, as well as an analysis of its performance when coupled to the commercial kinesthetic interface Novint Falcon. Its applicability in digital entertainment expects to improve the level of immersion into virtual reality scenarios. In the first experiment, a group of 75 subjects compared three different vibration stimuli that emulated different textures. They evaluated the stimuli on a 1 to 10 scale, where 1 means ‘non-perceivable differences’ and 10 means ‘entirely differentiable’. The obtained mean values were 9 (textures 1 and 3), 8,29 (textures 1 and 2), and 7,43 (textures 2 and 3), indicating HaptTech’s capability to reproduce differentiable stimuli. In the second experiment, 31 subjects evaluated the coupling between HaptTech and Novint Falcon. They perceived differences when the HaptTech system was activated in the context of a comparison between kinesthetic and vibrotactile plus kinesthetic stimuli. In the third experiment, the subjects evaluated the similarity between the perceived stimuli on the hand and a visualized texture pattern in a virtual environment. The resulting median values were 8, 8, and 9 for textures 1, 2, and 3, respectively, which demonstrate that the subjects perceived a high correspondence for each one.

Telephone consultations of pediatric patients — how safe is it?

Background. Telemedicine is defined as “the use of electronic information and communications technologies to provide and support health care when participants are separated” (Field M.J., 1998). The technologies range from standard telephone audio consultations to virtual reality scenarios. The accelerated uptake of telemedicine during the coronavirus disease 2019 pandemic has resulted in valuable experience and evidence on the delivery of telemedicine for pediatric patients. Despite the well-documented benefits of telephone medicine in both triage and disease management, the complexity of medically related telephone communications leaves patients vulnerable to errors in management. The purpose of our work was to describe medical errors related to the use of the telephone during communication between the patient/parents of the patient and the doctor, and the means of countering these errors in pediatrics. Materials and methods. The PubMed Central® database was searched using the keywords “telemedicine”, “telephone consultation”, “pediatrics”, “children”, and “patient safety”. Results. According to literature, the main types of mistakes were absence of records of the virtual consultation episode, incorrect triage decisions, incorrect diagnosis, failure to recognize the potential seriousness of repeat calls, lack of telephone consultation protocols and insufficient patient information. Measures to increase patient safety were presented: the use of empirical rules and protocols, experience and intuition, taking into account the thoughts and wishes of parents, non-medical factors and the accessibility of health care for the family, the use of a “safety net”. Conclusions. Further researches that would examine specific ways of the delivering and use of telemedicine are needed to develop evidence-based guidelines for virtual pediatric care.

Smart Sensing and AI for Physical Therapy in IoT Era

It is well known that medical spending increase with disability status. Per capita spending for people with five or more limitations in activities of daily living (ADLs) is nearly five times the amount incurred by those with limitations in only one instrumental activities of daily living (IADLs). Physical therapy is the way to improve the motor capabilities however it takes a lot of time, it requires physiotherapists services, is often painful and the outcome are evaluated in subjective way. New technologies including smart sensors were adopted in healthcare including wearable solutions for cardiac and respiratory activity monitoring and successfully are contributing to reduce the costs of services. In the case of motor activity and particularly in physical rehabilitation the developments are still reduced the physical therapy services are using as hardware mechanical equipment without sensing, embedded processing and internet connectivity that significatively reduce the possibility to measure and evaluate the physical training outcomes in objective way. In this paper the disruptive solutions for physical therapy are presented that are based on hot technologies such as smart sensors, IoT, virtual reality (VR), mixed reality (MR), and artificial intelligence (AI). Applied AI may conduct to develop models, classifiers (gait classification) and short term or medium term prediction of physical therapy outcomes. Highly motivation of the patients under physical rehabilitation can be increased promoting serious game characterized by VR and MR scenarios.

Meta-Reinforcement Learning for Reliable Communication in THz/VLC Wireless VR Networks

In this paper, the problem of enhancing the quality of virtual reality (VR) services is studied for an indoor terahertz (THz)/visible light communication (VLC) wireless network. In the studied model, small base stations (SBSs) transmit high-quality VR images to VR users over THz bands and light-emitting diodes (LEDs) provide accurate indoor positioning services for them using VLC. Here, VR users move in real time and their movement patterns change over time according to their applications, where both THz and VLC links can be blocked by the bodies of VR users. To control the energy consumption of the studied THz/VLC wireless VR network, VLC access points (VAPs) must be selectively turned on so as to ensure accurate and extensive positioning for VR users. Based on the user positions, each SBS must generate corresponding VR images and establish THz links without body blockage to transmit the VR content. The problem is formulated as an optimization problem whose goal is to maximize the average number of successfully served VR users by selecting the appropriate VAPs to be turned on and controlling the user association with SBSs. To solve this problem, a policy gradient-based reinforcement learning (RL) algorithm that adopts a meta-learning approach is proposed. The proposed meta policy gradient (MPG) algorithm enables the trained policy to quickly adapt to new user movement patterns. In order to solve the problem of maximizing the average number of successfully served users for VR scenarios with large numbers of users, a low-complexity dual method based MPG algorithm (D-MPG) with a low complexity is proposed. Simulation results demonstrate that, compared to a baseline trust region policy optimization algorithm (TRPO), the proposed MPG and D-MPG algorithms yield up to 26.8% and 21.9% improvement in the average number of successfully served users as well as 81.2% and 87.5% gains in the convergence speed, respectively.

Affective Image Sequence Viewing in Virtual Reality Theater Environment: Frontal Alpha Asymmetry Responses From Mobile EEG

Background: Numerous studies have investigated emotion in virtual reality (VR) experiences using self-reported data in order to understand valence and arousal dimensions of emotion. Objective physiological data concerning valence and arousal has been less explored. Electroencephalography (EEG) can be used to examine correlates of emotional responses such as valence and arousal in virtual reality environments. Used across varying fields of research, images are able to elicit a range of affective responses from viewers. In this study, we display image sequences with annotated valence and arousal values on a screen within a virtual reality theater environment. Understanding how brain activity responses are related to affective stimuli with known valence and arousal ratings may contribute to a better understanding of affective processing in virtual reality.Methods: We investigated frontal alpha asymmetry (FAA) responses to image sequences previously annotated with valence and arousal ratings. Twenty-four participants viewed image sequences in VR with known valence and arousal values while their brain activity was recorded. Participants wore the Oculus Quest VR headset and viewed image sequences while immersed in a virtual reality theater environment.Results: Image sequences with higher valence ratings elicited greater FAA scores than image sequences with lower valence ratings (F [1, 23] = 4.631, p = 0.042), while image sequences with higher arousal scores elicited lower FAA scores than image sequences with low arousal (F [1, 23] = 7.143, p = 0.014). The effect of valence on alpha power did not reach statistical significance (F [1, 23] = 4.170, p = 0.053). We determined that only the high valence, low arousal image sequence elicited FAA which was significantly higher than FAA recorded during baseline (t [23] = −3.166, p = 0.002), suggesting that this image sequence was the most salient for participants.Conclusion: Image sequences with higher valence, and lower arousal may lead to greater FAA responses in VR experiences. While findings suggest that FAA data may be useful in understanding associations between valence and arousal self-reported data and brain activity responses elicited from affective experiences in VR environments, additional research concerning individual differences in affective processing may be informative for the development of affective VR scenarios.

Modeling subjective fear using skin conductance: a preliminary study in virtual reality.

Reliably measuring fear perception could help evaluate the effectiveness of treatments for pathological conditions such as specific phobias or post-traumatic stress syndrome (e.g., exposure therapy). In this study, we developed a novel vir-tual reality (VR) scenario to induce fear and evaluate the related physiological response by the analysis of skin conductance (SC) signal. Eighteen subjects voluntarily experienced the fear VR scenario while their SC was recorded. After the experiment, each participant was asked to score the perceived subjective fear using a Likert scale from 1 to 10. We used the cvxEDA algorithm to process the collected SC signals and extract several features able to estimate the autonomic response to the fearful stimuli. Finally, the extracted features were linearly combined to model the subjective fear perception scores by means of LASSO linear regression. The sparsification imposed by the LASSO procedure to mitigate the overfitting risk identified an optimal linear model including only the standard deviation of the tonic SC component as a regressor (p = 0.007; R2 = 0.3337). The significant contribution of this feature to the model suggests that subjects experiencing more intense subjective fear have a more variable and unstable sympathetic tone.

Combination of Teddy Bear Hospital and Virtual Reality Training increases empathy of medical students

Introduction: In paediatric practice, healthcare professionals are required to connect with the child and interact at his/her level. However, it can be very difficult for medical students to put themselves in the shoes of the young child, to empathize and understand how a child actually feels while being treated. The Teddy Bear Hospital (TBH) can serve as a platform for medical students to learn how to communicate and empathise with children. Additionally, virtual reality (VR) can be used to portray a child’s viewpoint. This study aims to assess how TBH and VR can improve learning outcomes for medical students. Methods: A cohort study was conducted on 20 first-year medical students taking part in TBH sessions. The medical students did a Pre-, Post- and 1-year Post-intervention Jefferson Scale of Empathy to assess their empathy levels. They also completed a 1-year Post-intervention quantitative and qualitative survey on their experience. Results: There was a significant increase in Jefferson score compared to Pre-intervention (116.95 ± 8.19) for both Post-intervention (121.65 ± 11.03) and 1-year Post-intervention (123.31 ± 8.86). More than 80% believed that participating in TBH improved their confidence and ability to interact with children, while 50% felt that VR scenarios helped prepare them for the TBH. Thematic analysis of qualitative responses described (1) Personal development, (2) Insights into interacting with children, and (3) Structure and curriculum. Conclusion: TBH improved empathy and communication with children among pre-clinical medical students and the use of VR can be used to augment sessions.

Simulation-Based VR Training for the Nuclear Sector—A Pilot Study

Simulation-based training has seen an increased use of extended reality, that is, augmented reality (AR), virtual reality (VR) and mixed reality (MR) displays. The health professions have been using VR for simulation-based training more extensively than others. This method can offer the possibility of immediate feedback, which promotes more accurate training to self-correct mistakes in environments that are otherwise risky or provide unsafe conditions. The nuclear industry has attempted to seize the same digital and educational transformation to train their personnel to handle dangerous scenarios. We ran a pilot study with the aim of evaluating the VR training scenario developed for the specific target group and the acceptance of the VR technology itself for this kind of training. We used the Kirkpatrick framework to evaluate the training and the VR-HAM acceptance model to evaluate the acceptance of VR. A VR scenario was developed to test specific technical skills of nuclear power plant personnel. The 13 participants showed results within the basic level of the Kirkpatrick framework and held both positive reactions and concerns, that is, they enjoyed the training with VR and expressed concerns regarding the stability of the VR technology. The participants also showed positive attitudes towards the perceived ease of use and usefulness of the VR-HAM and its various constructs. Even though the COVID-19 pandemic limited our testing, we could show valuable data and positive attitudes and perceived ease by the participants. Simulation-based VR training could be an important complement to traditional training methods, especially where safety is a priority, but we still need to provide solid evidence.

Exit choice in built environment evacuation combining immersive virtual reality and discrete choice modelling

In the event of a fire emergency in the built environment, occupants face a range of evacuation decisions, including the choice of exits. An important question from the standpoint of evacuation safety is how evacuees make these choices and what factors affect their choices. Understanding how humans weigh these (often) competing factors is essential knowledge for evacuation planning and safe design. Here, we use immersive Virtual Reality (VR) experiments to investigate, in controlled settings, how these decision trade-offs are made using empirical data and econometric choice models. In each VR scenario, participants are confronted with choices between trade-offs between choosing exits that are familiar to them, exits that are less occupied, exits that are nearer to them and exits to which visibility is less affected by fire smoke. The marginal role of these competing factors on their decisions is quantified in a discrete choice model. Post-experiment questionnaires also determine factors such as participants' their perceived realism and emotion evoked by the VR evacuation experience. Results indicate that none of the investigated factors dominated the others in terms of their influence on exit choices. The participants exhibited patterns of multi-attribute conjoint decision-making, consistent with the recent findings in the literature. While lack of familiarity and the presence of smoke both negatively affected the desirability of an exit to evacuees, neither solely determined exit choice. It was also observed that prioritisation of the said factors by participants changed during the repeated scenarios, when compared to the first scenario that they experienced. Results have implications for both fire safety designs and future VR evacuation experiment designs. These empirical models can also be employed as input into computer simulations of building evacuation.

A pilot randomised trial of a brief virtual reality scenario in smokers unmotivated to quit: Assessing the feasibility of recruitment.

Individual-level interventions for smokers unmotivated to quit remain scarce and have had limited success. Little is known about the potential of virtual reality (VR) for delivering messaging to smokers unmotivated to quit. This pilot trial aimed to assess the feasibility of recruitment and acceptability of a brief, theory-informed VR scenario and estimate proximal quitting outcomes. Unmotivated smokers (recruited between February-August 2021) aged 18+ years who had access to, or were willing to receive via post, a VR headset were randomly assigned (1:1) using block randomisation to view the intervention (i.e., a hospital-based scenario with motivational stop smoking messaging) or a 'sham' VR scenario (i.e., a scenario about the human body without any smoking-specific messaging) with a researcher present via teleconferencing software. The primary outcome was feasibility of recruitment (i.e., achieving the target sample size of 60 participants within 3 months of recruitment). Secondary outcomes included acceptability (i.e., positive affective and cognitive attitudes), quitting self-efficacy and intention to stop smoking (i.e., clicking on a weblink with additional stop smoking information). We report point estimates and 95% confidence intervals (CIs). The study protocol was pre-registered (osf.io/95tus). A total of 60 participants were randomised within 6 months (intervention: n = 30; control: n = 30), 37 of whom were recruited within a 2-month period of active recruitment following an amendment to gift inexpensive (£7) cardboard VR headsets via post. The mean (SD) age of participants was 34.4 (12.1) years, with 46.7% identifying as female. The mean (SD) cigarettes smoked per day was 9.8 (7.2). The intervention (86.7%, 95% CI = 69.3%-96.2%) and control (93.3%, 95% CI = 77.9%-99.2%) scenarios were rated as acceptable. Quitting self-efficacy and intention to stop smoking in the intervention (13.3%, 95% CI = 3.7%-30.7%; 3.3%, 95% CI = 0.1%-17.2%) and control (26.7%, 95% CI = 12.3%-45.9%; 0%, 95% CI = 0%-11.6%) arm were comparable. The target sample size was not achieved within the feasibility window; however, an amendment to gift inexpensive headsets via post appeared feasible. The brief VR scenario appeared acceptable to smokers unmotivated to quit.

Effects of Restorative Environment and Presence on Anxiety and Depression Based on Interactive Virtual Reality Scenarios.

Anxiety and depression have been growing global mental health problems. The following studies explored the effect of interactive VR scenarios to find a low-cost and high-efficiency solution. Study 1 designed a 2 (anxiety and depression state) × 4 (interactive VR scenarios) experiment, the results of 20 participants showed that the designed scenarios had good restoration and presence, assisting to improve depression mood for people with mild to moderate anxiety and depression. Study 2 further investigated the intervention effects of two environment types (urban and park) and four interactive activities (automatic viewing, free-roaming, fishing, and watering plants in the park environment), based on data from a 10-minute experiment conducted by 195 participants with mild to moderate anxiety and depression. The subjective scales, EEG and EMG, and scenario experience were analyzed and the results showed that: (1) the restorative and present VR scenarios were beneficial in alleviating state anxiety and depression; (2) the restorative environment and presence were significantly and positively related to the reduction of anxiety and depression respectively, moreover, presence mediated the restorative environment on the recovery from anxiety and depression; (3) the environmental settings, the complexity of interaction, human factors, and maturity of VR devices and technology were also key factors that influenced the effects of interactive VR scenario experience and intervention. These studies revealed VR psychological intervention scenarios could be designed with comprehensive factors. Moreover, they might help pave the way for future study in exploring the physiology and psychology mode in virtual and real spaces, enhancing intervention effectiveness.

Detecting social information processing profiles of boys with aggressive behavior problems: An interactive virtual reality approach

Children with aggressive behavior problems may aggress for different reasons, requiring tailored assessment and treatment. The aim of this study was to test whether it is possible to detect distinct social information processing (SIP) profiles among boys with aggressive behavior problems. We therefore conducted Latent Profile Analyses on boys' SIP patterns assessed in interactive virtual reality. Additionally, we examined the discriminant validity of these SIP profiles by comparing them on theoretically relevant child characteristics (i.e., temperament, executive functioning, aggressive belief systems, punishment insensitivity, sensation seeking). We presented boys (N = 181; ages 7-13) with a virtual classroom where they could play games with virtual peers. They reported on their SIP in four virtual reality scenarios, designed to assess reactive and proactive aggressive SIP. Results revealed four distinct SIP profiles: a general reactive SIP profile, a situation-specific reactive SIP profile, a mixed reactive-proactive SIP profile, and a nonaggressive SIP profile. Planned contrasts revealed that boys with these SIP profiles differed in temperament, aggressive belief systems, and punishment insensitivity, but not in executive functioning and sensation seeking. Overall, findings suggest that boys differ in the exact SIP patterns underlying their aggressive behavior, providing inroads to tailor interventions to children's individual needs.