Evidence map›Paper›PMID 40971073›Full record

SynthesisJournal of general internal medicine2025

Effectiveness of Low-cost, Technology-enhanced Simulation Training for Healthcare Training in Low-and Middle-income Countries (LMICs): A Systematic Literature Review.

Julia Messina Gonzaga Ferreira, José Roberto Generoso, Alexandre R Marra, Rodrigo Octávio Deliberato, Maya Dewan, Daniel Loeb, Francis Real, Kelly Collins, Kelly Ely, Matthew Zackoff and 5 more

Abstract readSystematic Review
In one paragraph

Synthesis in Journal of general internal medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Observational
  2. Article
  3. Review
  4. 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

15 authors.

Julia Messina Gonzaga FerreiraHospital Israelita Albert Einstein, São Paulo, SP, Brazil. julia.ferreira@einstein.br.ORCID 0009-0005-3912-8348
José Roberto GenerosoDivision of Critical Care, Department of Pediatrics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, United States.
Alexandre R MarraHospital Israelita Albert Einstein, São Paulo, SP, Brazil.
Rodrigo Octávio DeliberatoDivision of Biomedical Informatics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA.
Maya DewanDivision of Critical Care, Department of Pediatrics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, United States.
Daniel LoebDivision of Critical Care, Department of Pediatrics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, United States.
Francis RealDivision of Critical Care, Department of Pediatrics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, United States.
Kelly CollinsDivision of Critical Care, Department of Pediatrics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, United States.
Kelly ElyCenter for Simulation and Research, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA.
Matthew ZackoffDivision of Critical Care, Department of Pediatrics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, United States.
Gabriel de Oliveira Vasques LopesFaculdade Israelita de Ciências da Saúde Albert Einstein, Hospital Israelita Albert Einstein, São Paulo, SP, Brazil.
Isabele PardoFaculdade Israelita de Ciências da Saúde Albert Einstein, Hospital Israelita Albert Einstein, São Paulo, SP, Brazil.
Maria Celidonio GutfreundFaculdade Israelita de Ciências da Saúde Albert Einstein, Hospital Israelita Albert Einstein, São Paulo, SP, Brazil.
Gustavo Yano CalladoFaculdade Israelita de Ciências da Saúde Albert Einstein, Hospital Israelita Albert Einstein, São Paulo, SP, Brazil.
Eneida A MendonçaDivision of Critical Care, Department of Pediatrics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSimulation-based training is essential for enhancing healthcare education and patient safety. However, its implementation often requires significant financial investment, limiting access in low- and middle-income countries (LMICs). Adapting simulation techniques to low-cost alternatives could improve accessibility and reduce educational disparities across global settings. This review aims to synthesize evidence on low-cost, technology-enhanced educational tools for healthcare training in resource-constrained settings.

methodsWe searched Medline (PubMed), CINAHL, Cochrane CENTRAL, Web of Science, Scopus, and Embase until August 31, 2024. Eligible studies involved LMICs, health trainees, and low-cost, technology-enhanced simulation tools for resource-constrained settings. We excluded comments, reviews, editorials, and studies not meeting these criteria. The review followed PRISMA guidelines, and study quality was assessed via the Downs and Black scale. This study was registered on PROSPERO (CRD42024554815) and received no funding.

resultsA total of 13 studies were included: six randomized trials and seven nonrandomized trials. These studies assessed various learning tools, including smartphone apps (six), virtual or augmented reality (three), telesimulation (two), a virtual simulation website (one), and a high-fidelity simulator (one), across multiple healthcare disciplines. Most studies have reported positive learning outcomes, such as improved skills and knowledge, although none have assessed long-term behavioral changes or patient outcomes. The reported barriers included internet connectivity issues, software instability, language limitations, and variability in prior knowledge. User satisfaction was generally high. DISCUSSION: This review highlights scalable, technological simulation tools for LMICs that improve medical training in resource-limited settings. It adheres to PRISMA guidelines, ensuring rigor, and includes studies from multiple continents and healthcare disciplines. Limitations include variations in low-cost tool definitions, study quality, and a lack of long-term behavior or clinical impact assessment. Additionally, comparisons often involve traditional learning methods rather than high-fidelity simulation tools used in high-income countries, and no cost-effectiveness analyses have been conducted.

Indexed as

Developing CountriesSimulation TrainingCost-Benefit AnalysisHumansaugmented realitydeveloping countrieseducationincomesimulation trainingstudentsvirtual reality

Identifiers

PMID40971073
PMCPMC12686302

What OpenQuestion holds

Textmetadata
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.