Evidence map›Paper›PMID 39047289›Full record

ArticleJMIR serious games2024

Extended Reality for Mental Health Evaluation: Scoping Review.

Olatunji Mumini Omisore, Ifeanyi Odenigbo, Joseph Orji, Amelia Itzel Hernandez Beltran, Sandra Meier, Nilufar Baghaei, Rita Orji

Abstract readScoping Review
In one paragraph

Article in JMIR serious games, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Observational
  2. Review
  3. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Olatunji Mumini OmisoreResearch Centre for Medical Robotics and Minimally Invasive Surgical Devices, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.ORCID https://orcid.org/0000-0002-9740-5471
Ifeanyi OdenigboFaculty of Computer Science, Dalhousie University, Halifax, NS, Canada.ORCID https://orcid.org/0000-0001-6937-0876
Joseph OrjiFaculty of Computer Science, Dalhousie University, Halifax, NS, Canada.ORCID https://orcid.org/0000-0001-9822-8377
Amelia Itzel Hernandez BeltranFaculty of Computer Science, Dalhousie University, Halifax, NS, Canada.ORCID https://orcid.org/0000-0003-2362-0950
Sandra MeierDepartment of Psychiatry, Dalhousie University, Halifax, NS, Canada.ORCID https://orcid.org/0000-0002-3287-5894
Nilufar BaghaeiSchool of Electrical Engineering and Computer Science, University of Queensland, St Lucia, Australia.ORCID https://orcid.org/0000-0003-1776-7075
Rita OrjiFaculty of Computer Science, Dalhousie University, Halifax, NS, Canada.ORCID https://orcid.org/0000-0001-6152-8034

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMental health disorders are the leading cause of health-related problems worldwide. It is projected that mental health disorders will be the leading cause of morbidity among adults as the incidence rates of anxiety and depression grow worldwide. Recently, "extended reality" (XR), a general term covering virtual reality (VR), augmented reality (AR), and mixed reality (MR), is paving the way for the delivery of mental health care.

objectiveWe aimed to investigate the adoption and implementation of XR technology used in interventions for mental disorders and to provide statistical analyses of the design, usage, and effectiveness of XR technology for mental health interventions with a worldwide demographic focus.

methodsIn this paper, we conducted a scoping review of the development and application of XR in the area of mental disorders. We performed a database search to identify relevant studies indexed in Google Scholar, PubMed, and the ACM Digital Library. A search period between August 2016 and December 2023 was defined to select papers related to the usage of VR, AR, and MR in a mental health context. The database search was performed with predefined queries, and a total of 831 papers were identified. Ten papers were identified through professional recommendation. Inclusion and exclusion criteria were designed and applied to ensure that only relevant studies were included in the literature review.

resultsWe identified a total of 85 studies from 27 countries worldwide that used different types of VR, AR, and MR techniques for managing 14 types of mental disorders. By performing data analysis, we found that most of the studies focused on high-income countries, such as the United States (n=14, 16.47%) and Germany (n=12, 14.12%). None of the studies were for African countries. The majority of papers reported that XR techniques lead to a significant reduction in symptoms of anxiety or depression. The majority of studies were published in 2021 (n=26, 30.59%). This could indicate that mental disorder intervention received higher attention when COVID-19 emerged. Most studies (n=65, 76.47%) focused on a population in the age range of 18-65 years, while few studies (n=2, 3.35%) focused on teenagers (ie, subjects in the age range of 10-19 years). In addition, more studies were conducted experimentally (n=67, 78.82%) rather than by using analytical and modeling approaches (n=8, 9.41%). This shows that there is a rapid development of XR technology for mental health care. Furthermore, these studies showed that XR technology can effectively be used for evaluating mental disorders in a similar or better way that conventional approaches.

conclusionsIn this scoping review, we studied the adoption and implementation of XR technology for mental disorder care. Our review shows that XR treatment yields high patient satisfaction, and follow-up assessments show significant improvement with large effect sizes. Moreover, the studies adopted unique designs that were set up to record and analyze the symptoms reported by their participants. This review may aid future research and development of various XR mechanisms for differentiated mental disorder procedures.

Indexed as

anxietydepressionexposure therapyextended realitymental disorder

Identifiers

PMID39047289
PMCPMC11306946

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.