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Record W4289769319 · doi:10.2196/35000

Virtual Reality Applications in Medicine During the COVID-19 Pandemic: Systematic Review

2022· review· en· W4289769319 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJMIR Serious Games · 2022
Typereview
Languageen
FieldComputer Science
TopicVirtual Reality Applications and Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsPsycINFOMEDLINEPandemicVirtual realitySystematic reviewHealth careInclusion (mineral)Critical appraisalCoronavirus disease 2019 (COVID-19)MedicineAnxietyMedical educationPsychologyNursingAlternative medicineComputer sciencePsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: Virtual reality can play an important role during the COVID-19 pandemic in the health care sector. This technology has the potential to supplement the traditional in-hospital medical training and treatment, and may increase access to training and therapies in various health care settings. OBJECTIVE: This systematic review aimed to describe the literature on health care-targeted virtual reality applications during the COVID-19 crisis. METHODS: We conducted a systematic search of the literature on the PsycINFO, Web of Science, and MEDLINE databases, according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines. The search string was as follows: "[(virtual reality)] AND [(COVID-19) OR (coronavirus) OR (SARS-CoV-2) OR (healthcare)]." Papers published in English after December 2019 in peer-reviewed journals were selected and subjected to the inclusion and exclusion criteria. We used the Mixed Methods Appraisal Tool to assess the quality of studies and the risk of bias. RESULTS: Thirty-nine studies met the inclusion criteria. Seventeen studies showed the usefulness of virtual reality during the COVID-19 crisis for reducing stress, anxiety, depression, and pain, and promoting physical activity. Twenty-two studies revealed that virtual reality was a helpful learning and training tool during the COVID-19 crisis in several areas, including emergency medicine, nursing, and pediatrics. This technology was also used as an educational tool for increasing public understanding of the COVID-19 pandemic. Different levels of immersion (ie, immersive and desktop virtual reality), types of head-mounted displays (ie, PC-based, mobile, and standalone), and content (ie, 360° videos and photos, virtual environments, virtual reality video games, and embodied virtual agents) have been successfully used. Virtual reality was helpful in both face-to-face and remote trials. CONCLUSIONS: Virtual reality has been applied frequently in medicine during the COVID-19 pandemic, with positive effects for treating several health conditions and for medical education and training. Some barriers need to be overcome for the broader adoption of virtual reality in the health care panorama. TRIAL REGISTRATION: International Platform of Registered Systematic Review and Meta-analysis Protocols (INPLASY) INPLASY202190108; https://inplasy.com/inplasy-2021-9-0108/.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.937
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0040.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.109
GPT teacher head0.410
Teacher spread0.300 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it