Evidence map›Paper›PMID 39496167›Full record

ArticleJMIR serious games2024

Interprofessional Team Training With Virtual Reality: Acceptance, Learning Outcome, and Feasibility Evaluation Study.

Andrea N Neher, Rafael Wespi, Benjamin D Rapphold, Thomas C Sauter, Juliane E Kämmer, Tanja Birrenbach

Abstract read
In one paragraph

Article in JMIR serious games, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

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  9. Scoping Review: The Effectiveness of Interprofessional Virtual Reality Simulation.Journal of medical education and curricular development
    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

6 authors.

Andrea N Neher *Department of Emergency Medicine, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland.ORCID 0009-0001-4911-8806
Rafael Wespi *Department of Emergency Medicine, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland.ORCID 0000-0002-3416-3938
Benjamin D RappholdDepartment of Health Professions, Division of Nursing, Bern University of Applied Sciences, Bern, Switzerland.ORCID 0000-0002-8028-6613
Thomas C SauterDepartment of Emergency Medicine, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland.ORCID 0000-0002-6646-5789
Juliane E Kämmer *Department of Emergency Medicine, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland.ORCID 0000-0001-6042-8453
Tanja Birrenbach *Department of Emergency Medicine, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland.ORCID 0000-0002-3046-0900

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Effective interprofessional teamwork is vital for ensuring high-quality patient care, especially in emergency medicine. However, interprofessional education often fails to facilitate meaningful interaction among health care disciplines. It is therefore imperative to afford early opportunities for cultivating interprofessional teamwork skills. While in-person simulation-based training has been shown to improve performance, this is resource-intensive, especially if it involves multiple professions. Virtual reality (VR)-based training is an innovative instructional approach that demands fewer resources and offers the flexibility of location-independent learning. Objective: This study aimed to develop and evaluate the acceptance, learning outcome, and feasibility of an interprofessional team (INTEAM) training course that included a VR simulation of a neurological emergency case. Methods: This 1-group study used a pre- and posttest design to evaluate the 2-hour INTEAM training course for nursing and medical students. The course included an e-learning part, VR simulation, and debriefing. The main learning objectives were derived from the entrustable professional activity 6, namely to handle a common problem in emergency medicine (headache due to subarachnoid hemorrhage and epileptic seizure) that requires interprofessional collaboration, including a structured handover. We used validated and self-constructed questionnaires, pre- and posttests, and open questions to assess the acceptance, learning outcome, and feasibility of the course. Results: The data of 42 students (21 nursing and 21 medical students) were analyzed and showed good usability in the System Usability Scale (median 72.5, IQR 65-80). The perception of usefulness (median 6, IQR 5.8-6.9) and ease of use (median 5.9, IQR 5.1-6.3) was good among all students. There was a significant increase in the handover performance from pre- (median 8, IQR 6-9) to posttraining (median 8, IQR 7-9; z=-2.01; P=.045; r=0.33) and of the confidence in caring for patients with seizures (median 3, IQR 2-3 and median 3.5, IQR 3-4, respectively; z=-3.8; P<.001; r=0.60). In 67% (14/21) of the simulations, technical issues occurred, but all simulations could be carried out completely. Conclusions: The new INTEAM training course was well received by nursing and medical students. The handover skills and confidence in caring for patients with seizures were improved after the course. Despite technical challenges with the VR simulations, none required termination, and this demonstrates that our approach is feasible. These promising results encourage the use of VR simulations for team training in the education of nursing and medical students.

Indexed as

assessmenteffectivenessemergency medicineepileptic seizureevaluation studyheadachehemorrhageinterprofessional team trainingmedical educationmedical studentsnursing studentspatient caresimulationsimulation-based trainingvirtual realityVR

Identifiers

PMID39496167
PMCPMC11554288

What OpenQuestion holds

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Registered trials

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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.