Evidence map›Paper›PMID 41729878›Full record

ArticlePLOS digital health2026

SomaVR: A low-cost virtual reality platform and implementation framework for medical education in resource-limited settings.

Mike Nsubuga, Grace Kebirungi, Helen Please, Paul Buyego, Henry Mutegeki, Rodgers Kimera, Jag Dhanda, Phil Cruz, Meghan McCarthy, Darrell Hurt and 4 more

Abstract read
In one paragraph

Article in PLOS digital health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

14 authors.

Mike NsubugaThe African Center of Excellence in Bioinformatics and Data-intensive Sciences, Makerere University, Kampala, Uganda.ORCID https://orcid.org/0009-0004-7668-3917
Grace KebirungiThe African Center of Excellence in Bioinformatics and Data-intensive Sciences, Makerere University, Kampala, Uganda.
Helen PleaseOxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom.
Paul BuyegoInfectious Diseases Institute, Makerere University, Kampala, Uganda.
Henry MutegekiThe African Center of Excellence in Bioinformatics and Data-intensive Sciences, Makerere University, Kampala, Uganda.
Rodgers KimeraThe African Center of Excellence in Bioinformatics and Data-intensive Sciences, Makerere University, Kampala, Uganda.
Jag DhandaBrighton and Sussex Medical School, Brighton, United Kingdom.
Phil CruzOffice of Cyber Infrastructure and Computational Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, United States of America.
Meghan McCarthyOffice of Cyber Infrastructure and Computational Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, United States of America.
Darrell HurtOffice of Cyber Infrastructure and Computational Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, United States of America.ORCID https://orcid.org/0000-0002-9829-8567
Maria Y GiovanniOffice of Cyber Infrastructure and Computational Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, United States of America.
Christopher WhalenOffice of Cyber Infrastructure and Computational Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, United States of America.
Michael TartakovskyOffice of Cyber Infrastructure and Computational Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, United States of America.
Daudi JjingoThe African Center of Excellence in Bioinformatics and Data-intensive Sciences, Makerere University, Kampala, Uganda.ORCID https://orcid.org/0000-0003-1685-9234

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Quality medical training is vital for effective healthcare worldwide. In low- and middle-income countries (LMICs), traditional training methods often face significant challenges, including limited resources, logistical barriers, and difficulties in safely replicating high-risk scenarios for infectious diseases like COVID-19 and Ebola. Additionally, medical training demands high costs, significant time, and specialized supervision, limiting its accessibility. Although virtual reality (VR) offers promising solutions to these problems, most evidence comes from high-income settings, leaving limited guidance on implementation in resource-constrained settings. We developed SomaVR, a low-cost VR platform and implementation framework for medical training in LMICs. Built with Unity3D, 'SomaVR' (soma - Swahili/Luganda for "to learn") integrates 360-degree and interactive virtual environments to create customizable training experiences aligned with specific curricula needs. Beyond the software, the framework provides a structured approach covering hardware selection, software architecture, content development workflows, and strategies for local capacity building. The platform prioritizes cross-platform compatibility, offline functionality, and cost-effective deployment. SomaVR's modular components support both high-end VR systems and low-cost solutions such as smartphone-based. The platform and framework were validated through two independent case studies: 1. COVID-19 infection prevention; and 2. Surgical training. In the surgical training, trainers from a high-income country guided Ugandan learners remotely, illustrating SomaVR's potential for long-distance knowledge exchange. In both cases, cohorts trained using SomaVR consistently outperformed those receiving conventional training, with significant improvements in procedural understanding and user engagement. Our findings also highlight that as VR technology costs decline, frugal approaches such as delivering 360-degree video via smartphone can maintain educational effectiveness in low-resource environments. This paper provides a practical blueprint for developing and implementing sustainable VR medical training platforms in resource-limited settings. By detailing the technical framework, development processes, and implementation strategies of SomaVR, we offer a replicable model for institutions seeking to leverage VR technology for medical education in LMICs.

Identifiers

PMID41729878
PMCPMC12928446

What OpenQuestion holds

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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.