Evidence map›Paper›PMID 35418070›Full record

ArticleBMC medical education2022

Feasibility of virtual reality based training for optimising COVID-19 case handling in Uganda.

Paul Buyego, Elizabeth Katwesigye, Grace Kebirungi, Mike Nsubuga, Shirley Nakyejwe, Phillip Cruz, Meghan C McCarthy, Darrell Hurt, Andrew Kambugu, Joseph Walter Arinaitwe and 2 more

Open access · goldAbstract read
In one paragraph

Article in BMC medical education, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed, 2 pooled it
4.4field-weighted citation impact, top 4% of its field
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

23 citing papers in PubMed, 2 syntheses or guidelines pooled it, 42 citations in OpenAlex.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

12 authors at 3 institutions in 2 countries.

Paul Buyego *Infectious Diseases Institute, Makerere University, Kampala, Uganda.
Elizabeth Katwesigye *Infectious Diseases Institute, Makerere University, Kampala, Uganda.
Grace KebirungiInfectious Diseases Institute, Makerere University, Kampala, Uganda.
Mike NsubugaInfectious Diseases Institute, Makerere University, Kampala, Uganda.
Shirley NakyejweThe African Center of Excellence in Bioinformatics and Data Intensive Sciences, Makerere University, Kampala, Uganda.
Phillip CruzOffice of Cyber Infrastructure and Computational Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, 20892, USA.
Meghan C McCarthyOffice of Cyber Infrastructure and Computational Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, 20892, USA.
Darrell HurtOffice of Cyber Infrastructure and Computational Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, 20892, USA.
Andrew KambuguInfectious Diseases Institute, Makerere University, Kampala, Uganda.
Joseph Walter ArinaitweInfectious Diseases Institute, Makerere University, Kampala, Uganda.
Umaru SsekabiraInfectious Diseases Institute, Makerere University, Kampala, Uganda.
Daudi JjingoInfectious Diseases Institute, Makerere University, Kampala, Uganda. daudi.jjingo@mak.ac.ug.ORCID https://orcid.org/0000-0003-1685-9234
Infectious Diseases Institute · UGNational Institutes of Health · USMakerere University · UG

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundEpidemics and pandemics are causing high morbidity and mortality on a still-evolving scale exemplified by the COVID-19 pandemic. Infection prevention and control (IPC) training for frontline health workers is thus essential. However, classroom or hospital ward-based training portends an infection risk due to the in-person interaction of participants. We explored the use of Virtual Reality (VR) simulations for frontline health worker training since it trains participants without exposing them to infections that would arise from in-person training. It does away with the requirement for expensive personal protective equipment (PPE) that has been in acute shortage and improves learning, retention, and recall. This represents the first attempt in deploying VR-based pedagogy in a Ugandan medical education context.

methodsWe used animated VR-based simulations of bedside and ward-based training scenarios for frontline health workers. The training covered the donning and doffing of PPE, case management of COVID-19 infected individuals, and hand hygiene. It used VR headsets to actualize an immersive experience, via a hybrid of fully-interactive VR and 360° videos. The level of knowledge acquisition between individuals trained using this method was compared to similar cohorts previously trained in a classroom setting. That evaluation was supplemented by a qualitative assessment based on feedback from participants about their experience.

resultsThe effort resulted in a COVID-19 IPC curriculum adapted into VR, corresponding VR content, and a pioneer cohort of VR trained frontline health workers. The formalized comparison with classroom-trained cohorts showed relatively better outcomes by way of skills acquired, speed of learning, and rates of information retention (P-value = 4.0e-09). In the qualitative assessment, 90% of the participants rated the method as very good, 58.1% strongly agreed that the activities met the course objectives, and 97.7% strongly indicated willingness to refer the course to colleagues.

conclusionVR-based COVID-19 IPC training is feasible, effective and achieves enhanced learning while protecting participants from infections within a pandemic setting in Uganda. It is a delivery medium transferable to the contexts of other highly infectious diseases.

Indexed as

COVID-19Virtual RealityFeasibility StudiesHumansPandemicsUgandaCOVID-19Medical educationPandemicsPersonal protective equipmentVirtual reality

Identifiers

PMID35418070
PMCPMC9006530
OpenAlexW4226271819

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.