Evidence map›Paper›PMID 38114940›Full record

ArticleBMC nursing2023

Virtual reality simulation for nursing education: effectiveness and feasibility.

Debra Kiegaldie, Louise Shaw

Abstract read
In one paragraph

Article in BMC nursing, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed, 2 pooled it
–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

22 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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  15. iENDEAVORS: Development and Testing of Virtual Reality Simulations for Nutrition and Dietetics.International journal of environmental research and public health · 2025
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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

2 authors.

Debra KiegaldieEastern Health Clinical School, Monash University, Victoria, 3128, Australia.ORCID http://orcid.org/0000-0002-4077-5818
Louise ShawCentre for Digital Transformation of Health, University of Melbourne, Grattan Street, Parkville, Vic, 3010, Australia. Louise.shaw@unimelb.edu.au.ORCID http://orcid.org/0000-0001-8188-2313

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Virtual Reality simulation (VRS) is an innovative and emerging technology that has the potential to offer increased numbers of pre-registration students authentic learning experiences compared to traditional simulation- based education (SBE) with simulated participants. The aim was to evaluate learner outcomes of SBE compared to 4 fully immersive VRS scenarios, for vocational and higher education nursing students at a training and further education institute in Melbourne, Australia. A mixed methods quasi-experimental design study was conducted over two semesters from 2019 to 2020. Participants were 675 pre-registration nursing students. The intervention group (VRS n = 393) received 4 three-dimensional, immersive VRS modules. The control group (SBE n = 282) received 4 face-to-face large group immersive simulations. In the VRS group 95% of students actively participated, compared to SBE (on average 15%). Knowledge test scores were initially significantly greater (p < 0.01) for VRS versus SBE students, but not maintained post clinical placement. Intervention students found VRS to be realistic and prepared them for clinical practice. Some technical difficulties were identified with VRS. VRS was found to be more cost effective than SBE. VRS fostered critical thinking and provided an efficient and sustainable platform for learning about complex clinical situations.

Indexed as

Nursing educationOnlineScenarioSimulation-based educationVirtual reality simulation

Identifiers

PMID38114940
PMCPMC10729454

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.