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Attention guidance augmentation of virtual reality exposure therapy for social anxiety disorder: a pilot randomized controlled trial.

ABSTRACT: Biased attention to social threats has been implicated in social anxiety disorder. Modifying visual attention during exposure therapy offers a direct test of this mechanism. We developed and tested a brief virtual reality exposure therapy (VRET) protocol using 360°-video and eye tracking. Participants (N = 21) were randomized to either standard VRET or VRET + attention guidance training (AGT). Multilevel Bayesian models were used to test (1) whether there was an effect of condition over time and (2) whether post-treatment changes in gaze patterns mediated the effect of condition at follow-up. There was a large overall effect of the intervention on symptoms of social anxiety, as well as an effect of the AGT augmentation on changes in visual attention to audience members. There was weak evidence against an effect of condition on fear of public speaking and weak evidence supporting a mediation effect, however these estimates were strongly influenced by model priors. Taken together, our findings suggest that attention can be modified within and during VRET and that modification of visual gaze avoidance may be casually linked to reductions in social anxiety. Replication with a larger sample size is needed.

SUBMITTER: Rubin M

PROVIDER: S-EPMC9458616 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature

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Attention guidance augmentation of virtual reality exposure therapy for social anxiety disorder: a pilot randomized controlled trial.

Rubin Mikael M Muller Karl K Hayhoe Mary M MM Telch Michael J MJ

Cognitive behaviour therapy 20220406 5

Biased attention to social threats has been implicated in social anxiety disorder. Modifying visual attention during exposure therapy offers a direct test of this mechanism. We developed and tested a brief virtual reality exposure therapy (VRET) protocol using 360°-video and eye tracking. Participants (N = 21) were randomized to either standard VRET or VRET + attention guidance training (AGT). Multilevel Bayesian models were used to test (1) whether there was an effect of condition over time and ...[more]

PMID: 35383544

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Project description:BackgroundSocial anxiety disorder (SAD) is a long-term and overwhelming fear of social situations that can affect work, school, and other daily activities. Although cognitive behavioral therapy is effective, few seek treatment, and many who do start often drop out. This may be due to the component of exposure inherent to cognitive behavioral therapy, where the patient confronts feared stimuli outside the therapist's office, which they otherwise try to avoid. As an alternative, research has explored the effectiveness of virtual reality (VR)-based exposure therapy with promising results. However, few studies have investigated the feasibility of VR tools using mixed methodologies before assessing their efficacy.ObjectiveThis study aims to assess the usability, feasibility, and presence of four 360° virtual environments and whether these were able to evoke anxiety in patients with SAD.MethodsA total of 10 adult participants with SAD and 10 healthy controls were recruited for 1 experimental session (age range 21-32 y; 12/20, 60% male participants). Questionnaire and interview data were collected and analyzed. A mixed methods triangulation design was applied to analyze and compare the data.ResultsParticipants with SAD experienced increased anxiety when exposed to VR, and environments were considered relevant and useful as an exposure tool. Participants with SAD reported significantly higher average anxiety levels (P=.01) and peak anxiety levels (P=.01) compared with controls during exposure; however, significant differences in anxiety when accounting for baseline anxiety levels were only found in 2 of 4 environments (P=.01, P=.01, P=.07, and P=.06). While presence scores were acceptable in both groups, participants with SAD scored significantly lower than controls. Qualitative analyses highlight this finding within the SAD group, where some participants experienced presence reduction due to being observed while in VR and in situations with reduced interaction in VR.ConclusionsVR exposure with 360° videos seems to be useful as a first step of exposure therapy for patients with SAD. Future exploration in the clinical application of VR-based exposure for SAD, as well as means of increasing presence within the virtual environments, may be useful.

Project description:BackgroundSocial anxiety disorder (SAD) is a debilitating psychiatric disorder that affects occupational and social functioning. Virtual reality (VR) therapies can provide effective treatment for people with SAD. However, with rapid innovations in immersive VR technology, more contemporary research is required to examine the effectiveness and concomitant user experience outcomes (ie, safety, usability, acceptability, and attrition) of emerging VR interventions for SAD.ObjectiveThe aim of this systematic review was to examine the effectiveness and user experience of contemporary VR interventions among people with SAD.MethodsThe Cochrane Library, Emcare, PsycINFO, PubMed, ScienceDirect, Scopus, and Web of Science databases were searched between January 1, 2012, and April 26, 2022. Deduplicated search results were screened based on title and abstract information. Full-text examination was conducted on 71 articles. Studies of all designs and comparator groups were included if they appraised the effectiveness and user experience outcomes of any immersive VR intervention among people with SAD. A standardized coding sheet was used to extract data on key participant, intervention, comparator, outcome, and study design items.ResultsThe findings were tabulated and discussed using a narrative synthesis. A total of 18 studies met the inclusion criteria.ConclusionsThe findings showed that VR exposure therapy-based interventions can generally provide effective, safe, usable, and acceptable treatments for adults with SAD. The average attrition rate from VR treatment was low (11.36%) despite some reported user experience difficulties, including potential simulator sickness, exposure-based emotional distress, and problems with managing treatment delivered in a synchronous group setting. This review also revealed several research gaps, including a lack of VR treatment studies on children and adolescents with SAD as well as a paucity of standardized assessments of VR user experience interactions. More studies are required to address these issues.Trial registrationPROSPERO CRD42022353891; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=353891.

Project description:IntroductionMachine learning (ML) is an effective tool for predicting mental states and is a key technology in digital psychiatry. This study aimed to develop ML algorithms to predict the upper tertile group of various anxiety symptoms based on multimodal data from virtual reality (VR) therapy sessions for social anxiety disorder (SAD) patients and to evaluate their predictive performance across each data type.MethodsThis study included 32 SAD-diagnosed individuals, and finalized a dataset of 132 samples from 25 participants. It utilized multimodal (physiological and acoustic) data from VR sessions to simulate social anxiety scenarios. This study employed extended Geneva minimalistic acoustic parameter set for acoustic feature extraction and extracted statistical attributes from time series-based physiological responses. We developed ML models that predict the upper tertile group for various anxiety symptoms in SAD using Random Forest, extreme gradient boosting (XGBoost), light gradient boosting machine (LightGBM), and categorical boosting (CatBoost) models. The best parameters were explored through grid search or random search, and the models were validated using stratified cross-validation and leave-one-out cross-validation.ResultsThe CatBoost, using multimodal features, exhibited high performance, particularly for the Social Phobia Scale with an area under the receiver operating characteristics curve (AUROC) of 0.852. It also showed strong performance in predicting cognitive symptoms, with the highest AUROC of 0.866 for the Post-Event Rumination Scale. For generalized anxiety, the LightGBM's prediction for the State-Trait Anxiety Inventory-trait led to an AUROC of 0.819. In the same analysis, models using only physiological features had AUROCs of 0.626, 0.744, and 0.671, whereas models using only acoustic features had AUROCs of 0.788, 0.823, and 0.754.ConclusionsThis study showed that a ML algorithm using integrated multimodal data can predict upper tertile anxiety symptoms in patients with SAD with higher performance than acoustic or physiological data obtained during a VR session. The results of this study can be used as evidence for personalized VR sessions and to demonstrate the strength of the clinical use of multimodal data.

Project description:BackgroundSocial anxiety disorder (SAD) is the fear of social situations where a person anticipates being evaluated negatively. Changes in autonomic response patterns are related to the expression of anxiety symptoms. Virtual reality (VR) sickness can inhibit VR experiences.ObjectiveThis study aimed to predict the severity of specific anxiety symptoms and VR sickness in patients with SAD, using machine learning based on in situ autonomic physiological signals (heart rate and galvanic skin response) during VR treatment sessions.MethodsThis study included 32 participants with SAD taking part in 6 VR sessions. During each VR session, the heart rate and galvanic skin response of all participants were measured in real time. We assessed specific anxiety symptoms using the Internalized Shame Scale (ISS) and the Post-Event Rumination Scale (PERS), and VR sickness using the Simulator Sickness Questionnaire (SSQ) during 4 VR sessions (#1, #2, #4, and #6). Logistic regression, random forest, and naïve Bayes classification classified and predicted the severity groups in the ISS, PERS, and SSQ subdomains based on in situ autonomic physiological signal data.ResultsThe severity of SAD was predicted with 3 machine learning models. According to the F1 score, the highest prediction performance among each domain for severity was determined. The F1 score of the ISS mistake anxiety subdomain was 0.8421 using the logistic regression model, that of the PERS positive subdomain was 0.7619 using the naïve Bayes classifier, and that of total VR sickness was 0.7059 using the random forest model.ConclusionsThis study could predict specific anxiety symptoms and VR sickness during VR intervention by autonomic physiological signals alone in real time. Machine learning models can predict the severe and nonsevere psychological states of individuals based on in situ physiological signal data during VR interventions for real-time interactive services. These models can support the diagnosis of specific anxiety symptoms and VR sickness with minimal participant bias.Trial registrationClinical Research Information Service KCT0003854; https://cris.nih.go.kr/cris/search/detailSearch.do/13508.

Project description:BackgroundAttention-deficit/hyperactivity disorder (ADHD) is one of the most common neurodevelopmental disorders among children. Children with ADHD have challenges in understanding social cues and behavioral problems when entering a social setting. Virtual reality (VR) has been applied to improve cognitive behaviors in children with ADHD. Previous studies have not adopted VR to improve social interaction competence and appropriateness in children with ADHD. VR offers a more effective alternative to therapeutic strategies for children with ADHD.ObjectiveThis study aims to examine the feasibility and effectiveness of social VR training in enhancing social interaction skills compared to traditional social skills training in children with ADHD. We hypothesize that participants in the social VR training group are likely to perform better on social interaction skills than those in the traditional social skills training group.MethodsIn this nonblinded, 3-arm randomized controlled trial (RCT), 90 participants with ADHD recruited from the community will be randomized 1:1:1 to the social VR intervention group, traditional social skills training group, or waitlist control group. The child psychiatrist will conduct assessments for each participant at baseline and after the intervention. The Social Skills Rating Scale-Parent will be used to assess the social interaction skills of the participants before and after the intervention. Participants in the social VR intervention group and traditional social skills training group will receive twelve 20-minute training sessions for 3 weeks. The participants in the waitlist control group will receive no training. The primary outcome measure is training acceptability and compliance. The secondary outcome measures are the child psychiatrist's assessment and the Social Skills Rating Scale-Parent before and after the intervention. Another outcome measure is the Behavior Rating Inventory of Executive Function and Attention. Differences in the scale scores will be examined using a t test and an F test.ResultsThis study is set to commence in the fourth quarter of 2023. It is anticipated that participants in the social VR intervention group will exhibit superior social interaction skills than those in the traditional social skills training group.ConclusionsTo our knowledge, this RCT is the first study examining the feasibility and effectiveness of a social VR-based intervention for enhancing the social interaction skills of children with ADHD in Hong Kong. The VR-based social skills training is expected to provide a safer and more effective environment for children with ADHD to learn than the traditional approach. This study can lead to a full-scale RCT.Trial registrationClinicalTrials.gov NCT05778526; https://clinicaltrials.gov/study/NCT05778526.International registered report identifier (irrid)PRR1-10.2196/48208.

Dataset Information

Attention guidance augmentation of virtual reality exposure therapy for social anxiety disorder: a pilot randomized controlled trial.

Publications

Attention guidance augmentation of virtual reality exposure therapy for social anxiety disorder: a pilot randomized controlled trial.

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