Case Report: Feasibility of a Novel Virtual Reality-Based Intervention for Patients With Schizophrenia

A Literature Review Examining Virtual Reality Exposure Therapy for Individuals Diagnosed With Social Anxiety Disorder

ABSTRACT

Social anxiety disorder (SAD) is a specific subtype of anxiety disorder where individuals experience uncomfortable social situations that induce anxious feelings including nervousness and panic. Computer technology has been applied in interventions for many mental health disorders. We aim to understand and explore the use of virtual reality exposure therapy (VRET) to treat adults with SAD. We conducted a literature search using relevant mesh keywords in PubMed and PsycINFO. Six studies met inclusion criteria in our final qualitative synthesis review. Results showed a significant reduction in SAD symptom severity based on primary measures in all studies, suggesting that VRET is an effective option in treating SAD. Studies have shown the success of VRET in formats such as a single-user implementation, one-session treatment, and self-training intervention. In conclusion, VRET is effective in reducing SAD symptoms. The limitations of most studies included a small sample size and weak ecological validity. Future research can examine VRET with a more extensive clinical sample and broader social behaviors.

Use of Technologies in the Therapy of Social Cognition Deficits in Neurological and Mental Diseases: A Systematic Review

Objective: This article systematically reviews the effects of technology-based (TB) treatments on impaired social cognition (SC) in neurological and mental disorders. Methods: Strictly adhering to the PRISMA guidelines, a systematic search was carried out in PsycINFO, PubMed, and Web of Science (last search: April 22, 2021) to identify studies that, implementing a control group design, evaluated TB treatments targeting deficits in emotion recognition, Theory of Mind (ToM) and social behavior in adult patients with nondevelopmental and nonprogressive neurological or mental disorders. Risk of bias was assessed using the PEDro Scale, certainty assessment followed the GRADE approach. Results: Sixteen studies involving 857 patients, all focusing on psychotic disorders, were retrieved. The most pronounced effects were observed concerning emotion recognition with all studies revealing overall improvements. Regarding ToM and social behavior, results were mixed. However, the number of studies including outcome measures for these domains, is significantly lower compared to the domain of emotion recognition, limiting the validity of the results. Risk of bias and certainty assessment revealed further limitations of evidence. Conclusion: TB treatment achieves positive effects especially with regard to emotion recognition impairments, at least for patients with schizophrenia. Future research should expand the evaluation of TB training of other SC domains, ought to be carried out in more diverse patient populations, rely on different devices, and include follow-up measurements.

Virtual reality in the diagnostic and therapy for mental disorders: A systematic review

BACKGROUND

Virtual reality (VR) technologies are playing an increasingly important role in the diagnostics and treatment of mental disorders.

OBJECTIVE

To systematically review the current evidence regarding the use of VR in the diagnostics and treatment of mental disorders.

DATA SOURCE

Systematic literature searches via PubMed (last literature update: 9^th of May 2022) were conducted for the following areas of psychopathology: Specific phobias, panic disorder and agoraphobia, social anxiety disorder, generalized anxiety disorder, posttraumatic stress disorder (PTSD), obsessive-compulsive disorder, eating disorders, dementia disorders, attention-deficit/hyperactivity disorder, depression, autism spectrum disorder, schizophrenia spectrum disorders, and addiction disorders.

ELIGIBILITY CRITERIA

To be eligible, studies had to be published in English, to be peer-reviewed, to report original research data, to be VR-related, and to deal with one of the above-mentioned areas of psychopathology.

STUDY EVALUATION

For each study included, various study characteristics (including interventions and conditions, comparators, major outcomes and study designs) were retrieved and a risk of bias score was calculated based on predefined study quality criteria.

RESULTS

Across all areas of psychopathology, k = 9315 studies were inspected, of which k = 721 studies met the eligibility criteria. From these studies, 43.97% were considered assessment-related, 55.48% therapy-related, and 0.55% were mixed. The highest research activity was found for VR exposure therapy in anxiety disorders, PTSD and addiction disorders, where the most convincing evidence was found, as well as for cognitive trainings in dementia and social skill trainings in autism spectrum disorder.

CONCLUSION

While VR exposure therapy will likely find its way successively into regular patient care, there are also many other promising approaches, but most are not yet mature enough for clinical application.

REVIEW REGISTRATION

PROSPERO register CRD42020188436.

FUNDING

The review was funded by budgets from the University of Bonn. No third party funding was involved.

How Interpersonal Distance Between Avatar and Human Influences Facial Affect Recognition in Immersive Virtual Reality

Purpose: The purpose of this study was to determine the optimal interpersonal distance (IPD) between humans and affective avatars in facial affect recognition in immersive virtual reality (IVR). The ideal IPD is the one in which the humans show the highest number of hits and the shortest reaction times in recognizing the emotions displayed by avatars. The results should help design future therapies to remedy facial affect recognition deficits.

Methods: A group of 39 healthy volunteers participated in an experiment in which participants were shown 65 dynamic faces in IVR and had to identify six basic emotions plus neutral expression presented by the avatars. We decided to limit the experiment to five different distances: D1 (35 cm), D2 (55 cm), D3 (75 cm), D4 (95 cm), and D5 (115 cm), all belonging to the intimate and personal interpersonal spaces. Of the total of 65 faces, 13 faces were presented for each of the included distances. The views were shown at different angles: 50% in frontal view, 25% from the right profile, and 25% from the left profile. The order of appearance of the faces presented to each participant was randomized.

Results: The overall success rate in facial emotion identification was 90.33%, being D3 the IPD with the best overall emotional recognition hits, although statistically significant differences could not be found between the IPDs. Consistent with results obtained in previous studies, identification rates for negative emotions were higher with increasing IPD, whereas the recognition task improved for positive emotions when IPD was closer. In addition, the study revealed irregular behavior in the facial detection of the emotion surprise.

Conclusions: IVR allows us to reliably assess facial emotion recognition using dynamic avatars as all the IPDs tested showed to be effective. However, no statistically significant differences in facial emotion recognition were found among the different IPDs.