Evidence map›Paper›PMID 40156490›Full record

Trial reportInternational journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics2025

Virtual reality simulation training for childbirth: A cluster randomized crossover study.

Arundhati Gosavi, Abhiram Kanneganti, Eng Tat Khoo, Kuldip Singh, Liang Shen, Mary Rauff, Chang Liu, Mahesh Choolani

Abstract readRandomized Controlled Trial
In one paragraph

Trial report in International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Virtual reality simulation training for childbirth: A cluster randomized crossover study.International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics · 2025
    Trial
  2. Article
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

8 authors.

Arundhati GosaviDepartment of Obstetrics and Gynaecology, National University Centre for Women and Children (NUWoC), National University Health System, Singapore.ORCID https://orcid.org/0000-0002-8785-7335
Abhiram KannegantiDepartment of Obstetrics and Gynaecology, National University Centre for Women and Children (NUWoC), National University Health System, Singapore.ORCID https://orcid.org/0000-0002-5559-4534
Eng Tat KhooImmersive Reality Lab, National University of Singapore, Singapore.ORCID https://orcid.org/0000-0003-1295-3506
Kuldip SinghDepartment of Obstetrics and Gynaecology, National University Centre for Women and Children (NUWoC), National University Health System, Singapore.ORCID https://orcid.org/0000-0003-1114-2648
Liang ShenBiostatistics Unit, Yong Loo Lin School of Medicine, National University of Singapore, Singapore.
Mary RauffDepartment of Obstetrics and Gynaecology, National University Centre for Women and Children (NUWoC), National University Health System, Singapore.
Chang LiuImmersive Reality Lab, National University of Singapore, Singapore.
Mahesh ChoolaniDepartment of Obstetrics and Gynaecology, National University Centre for Women and Children (NUWoC), National University Health System, Singapore.ORCID https://orcid.org/0000-0001-8336-0973

Funding

Department of Obstetrics and Gynaecology, National University of Singapore
6 · The paper itself

Abstract

objectiveTo compare knowledge acquisition and domain-specific feedback between virtual reality (VR) and mannequin-based simulation for teaching medical students normal vaginal delivery (NVD).

methodsWe conducted a cluster randomized crossover study comparing a novel in-house-developed NVD VR simulator utilizing an Oculus® Quest 2 HMD with the PROMPT Flex® mannequin. We randomly assigned medical student clinical groups to either VR or mannequin simulation. Participants took an 11-item knowledge quiz before and after their first simulation before crossing over to the alternate simulation. Participants took a six-domain, 14-item feedback questionnaire evaluating both simulations. The primary outcome was percentage improvement in knowledge scores, while the secondary outcome was adjusted mean difference in mean feedback scores between each simulation.

resultsTwenty clinical groups comprising 111 medical students participated. There was no difference in either arm for baseline characteristics and pre-simulation knowledge scores. Medical students undergoing VR simulation had significantly higher overall post-simulation mean percentage correct scores (79.0% vs. 54.0%; P < 0.001). The mannequin simulator had significantly higher feedback scores (61.0 vs. 58.3; adjusted mean difference 2.45 [95% confidence interval 0.95-3.95]; P = 0.002) and in five of six domains. A total of 40.5% of respondents preferred the mannequin simulation, 4.5% preferred the VR simulation, and 42.5% preferred a mixture of the two.

conclusionsOur novel VR NVD simulator was superior to traditional mannequin simulation in content delivery. As more respondents preferred a mixed approach over any single method, VR simulation could complement legacy mannequin simulation methods by serving as a primer or a distance-learning tool and help increase skill birth attendant training.

Indexed as

Delivery, ObstetricSimulation TrainingVirtual RealityAdultClinical CompetenceCross-Over StudiesFemaleHumansManikinsPregnancyStudents, MedicalSurveys and QuestionnairesYoung Adultdistance learningmedical studentsnormal vaginal deliverysimulationvirtual reality

Identifiers

PMID40156490
PMCPMC12255915

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.