Evidence map›Paper›PMID 42540122›Full record

ReviewFrontiers in medicine2026

Research progress on the application of virtual simulation in medical education.

Xiwang Jiang, Haichao Ge, Qianyong Wang

Abstract readReview
In one paragraph

Review in Frontiers in medicine, 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

3 authors.

Xiwang Jiang *Health Science Center, Ningbo University, Ningbo, China.
Haichao Ge *Department of Gastroenterology, The First Affiliated Hospital of Ningbo University, Ningbo, China.
Qianyong WangHealth Science Center, Ningbo University, Ningbo, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Medical education is fundamental to developing clinical competence, directly influencing care quality and patient safety. Traditional teaching models have long faced structural limitations, including scarce physical resources and restricted clinical exposure, which hinder the training of versatile professionals needed in modern health care. Virtual simulation (VS), by providing a high-fidelity, repeatable, and low-risk learning environment, offers a promising solution to these challenges. This narrative article reviews recent applications of VS in basic medicine, clinical medicine, and nursing education. Although existing evidence supports its educational benefits, most studies rely on short-term, small-sample designs and lack evaluation of long-term clinical transfer or cost-effectiveness. Persistent issues include high device heterogeneity and insufficient integration of nontechnical skills training. Future efforts should prioritize multicenter longitudinal research, platform standardization, and the incorporation of artificial intelligence to enable personalized adaptive learning-moving VS toward a core component of medical education.

Indexed as

basic medicineclinical medicinemedical educationnursing medicinevirtual simulation

Identifiers

PMID42540122
PMCPMC13425141

What Socratic 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 Socratic graph.