Dataset Information

Effectiveness and User Experience of Virtual Reality for Social Anxiety Disorder: Systematic Review.

ABSTRACT:

Background

Social 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.

Objective

The aim of this systematic review was to examine the effectiveness and user experience of contemporary VR interventions among people with SAD.

Methods

The 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.

Results

The findings were tabulated and discussed using a narrative synthesis. A total of 18 studies met the inclusion criteria.

Conclusions

The 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 registration

PROSPERO CRD42022353891; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=353891.

SUBMITTER: Shahid S

PROVIDER: S-EPMC10884902 | biostudies-literature | 2024 Feb

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Effectiveness and User Experience of Virtual Reality for Social Anxiety Disorder: Systematic Review.

Shahid Simon S Kelson Joshua J Saliba Anthony A

JMIR mental health 20240208

<h4>Background</h4>Social 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.<h4>Objective</h4> ...[more]

PMID: 38329804

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Project description:BackgroundSocial anxiety disorder (SAD) is characterized by excessive fear of negative evaluation and humiliation in social interactions and situations. Virtual reality (VR) treatment is a promising intervention option for SAD.ObjectiveThe purpose of this study was to create a participatory and interactive VR intervention for SAD. Treatment progress, including the severity of symptoms and the cognitive and emotional aspects of SAD, was analyzed to evaluate the effectiveness of the intervention.MethodsIn total, 32 individuals with SAD and 34 healthy control participants were enrolled in the study through advertisements for online bulletin boards at universities. A VR intervention was designed consisting of three stages (introduction, core, and finishing) and three difficulty levels (easy, medium, and hard) that could be selected by the participants. The core stage was the exposure intervention in which participants engaged in social situations. The effectiveness of treatment was assessed through Beck Anxiety inventory (BAI), State-Trait Anxiety Inventory (STAI), Internalized Shame Scale (ISS), Post-Event Rumination Scale (PERS), Social Phobia Scale (SPS), Social Interaction Anxiety Scale (SIAS), Brief-Fear of Negative Evaluation Scale (BFNE), and Liebowitz Social Anxiety Scale (LSAS).ResultsIn the SAD group, scores on the BAI (F=4.616, P=.009), STAI-Trait (F=4.670, P=.004), ISS (F=6.924, P=.001), PERS-negative (F=1.008, P<.001), SPS (F=8.456, P<.001), BFNE (F=6.117, P=.004), KSAD (F=13.259, P<.001), and LSAS (F=4.103, P=.009) significantly improved over the treatment process. Compared with the healthy control group before treatment, the SAD group showed significantly higher scores on all scales (P<.001), and these significant differences persisted even after treatment (P<.001). In the comparison between the VR treatment responder and nonresponder subgroups, there was no significant difference across the course of the VR session.ConclusionsThese findings indicated that a participatory and interactive VR intervention had a significant effect on alleviation of the clinical symptoms of SAD, confirming the usefulness of VR for the treatment of SAD. VR treatment is expected to be one of various beneficial therapeutic approaches in the future.Trial registrationClinical Research Information Service (CRIS) KCT0003854; https://cris.nih.go.kr/cris/search/search_result_st01.jsp?seq=13508.

Project description:BackgroundVirtual reality is increasingly being utilized by clinicians to facilitate analgesia and anxiolysis within an inpatient setting. There is however, a lack of a clinically relevant review to guide its use for this purpose.ObjectiveTo systematically review the current evidence for the efficacy of virtual reality as an analgesic in the management of acute pain and anxiolysis in an inpatient setting.MethodsA comprehensive search was conducted up to and including January 2019 on PubMed, Ovid Medline, EMBASE, and Cochrane Database of Systematic reviews according to PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Search terms included virtual reality, vr, and pain. Primary articles with a focus on acute pain in the clinical setting were considered for the review. Primary outcome measures included degree of analgesia afforded by virtual reality therapy, degree of anxiolysis afforded by virtual reality therapy, effect of virtual reality on physiological parameters, side effects precipitated by virtual reality, virtual reality content type, and type of equipment utilized.ResultsEighteen studies were deemed eligible for inclusion in this systematic review; 67% (12/18) of studies demonstrated significant reductions in pain with the utilization of virtual reality; 44% (8/18) of studies assessed the effects of virtual reality on procedural anxiety, with 50% (4/8) of these demonstrating significant reductions; 28% (5/18) of studies screened for side effects with incidence rates of 0.5% to 8%; 39% (7/18) of studies evaluated the effects of virtual reality on autonomic arousal as a biomarker of pain, with 29% (2/7) demonstrating significant changes; 100% (18/18) of studies utilized a head mounted display to deliver virtual reality therapy, with 50% being in active form (participants interacting with the environment) and 50% being in passive form (participants observing the content only).ConclusionsAvailable evidence suggests that virtual reality therapy can be applied to facilitate analgesia for acute pain in a variety of inpatient settings. Its effects, however, are likely to vary by patient population and indication. This highlights the need for individualized pilot testing of virtual reality therapy's effects for each specific clinical use case rather than generalizing its use for the broad indication of facilitating analgesia. In addition, virtual reality therapy has the added potential of concurrently providing procedural anxiolysis, thereby improving patient experience and cooperation, while being associated with a low incidence of side effects (nausea, vomiting, eye strain, and dizziness). Furthermore, findings indicated a head mounted display should be utilized to deliver virtual reality therapy in a clinical setting with a slight preference for active over passive virtual reality for analgesia. There, however, appears to be insufficient evidence to substantiate the effect of virtual reality on autonomic arousal, and this should be considered at best to be for investigational uses, at present.

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:BackgroundVirtual reality (VR) has been used successfully and effectively in psychotherapy for a variety of disorders. In the field of depression, there are only a few VR interventions and approaches. Although simple social interactions have been successfully modeled in VR for several mental disorders, there has been no transfer to the field of depression therapy. VR may be employed for psychodynamic psychotherapy to work on interpersonal conflict patterns. In this study, we developed and evaluated a VR intervention for the simulation of roleplay situations in the context of supportive-expressive therapy.MethodsWe conducted a clinical user experience (UX) study at a psychotherapeutic clinic in Düsseldorf, Germany. Eight inpatients with depression and four therapists were included. Semi-structured interviews and qualitative content analysis were used to identify UX issues of the developed VR intervention. Usability questionnaires and technical usage data were also considered. The VR intervention consisted of two therapist-controlled roleplay scenarios designed to support work on the core conflictual relationship theme by allowing patients to interact in typical problematic social situations. Recorded VR roleplays allow for therapeutic debriefing with a change of perspective. Therapists were given the option of using the roleplay in multiple sessions.ResultsAll therapists conducted one session per patient with the VR intervention. From the patient interviews, 26 UX issues were extracted, of which one technical malfunction and two unclarities in the interaction with the VR agent were rated as major problems. From the therapist interviews, 14 UX issues were extracted, of which five were rated as major problems related to the interface in the dialog control or the complex system setup.ConclusionThe main problem was designing a dialog structure that allows both complex conversational flows and a clear control interface. In principle, VR roleplays could be integrated well and safely into therapy. The VR intervention shows promise for providing an emotional experience of interpersonal conflict patterns in the context of psychotherapy. Additionally, other roleplay situations involving various social problem areas must be created and evaluated in terms of the fit to the patients' core conflictual relationship themes.

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 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.

Dataset Information

Effectiveness and User Experience of Virtual Reality for Social Anxiety Disorder: Systematic Review.

Background

Objective

Methods

Results

Conclusions

Trial registration

Publications

Effectiveness and User Experience of Virtual Reality for Social Anxiety Disorder: Systematic Review.

Similar Datasets

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