Evidence map›Paper›PMID 41776623›Full record

ArticleAdvances in simulation (London, England)2026

Setting a research agenda for the use of extended reality in healthcare simulation: an Utstein style meeting.

Barry Issenberg, Doris Ostergaard, Francisco Matos, Pier Luigi Ingrassia, Kirsty Freeman, Lars Konge, Carla Sa-Couto, Gabriel Reedy, Utstein XR in Simulation Expert Group

Abstract read
In one paragraph

Article in Advances in simulation (London, England), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 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

2 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. 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

9 authors.

Barry IssenbergUniversity of Miami Gordon Center for Simulation and Innovation in Medical Education, 1120 Northwest 14th Street, Miami, FL, 33136, USA. bissenbe@miami.edu.
Doris OstergaardCopenhagen Academy for Medical Education and Simulation, Ryesgade 53B, Copenhagen, 2100, Denmark.
Francisco MatosUniversity of Coimbra, Paco das Escolas, Coimbra, 3000-370, Portugal.
Pier Luigi IngrassiaCentro Di Simulazione (CeSi), Via Ronchetto 14, Lugano, Ticino, 6900, Switzerland.
Kirsty FreemanThe University of Western Australia, M Block, QEII Medical Centre, Caladenia Cres (Entrance Off Hampden Road) Nedlands WA: MBDP 709U, 35 Stirling Highway, Perth, WA, 6009, Australia.
Lars KongeCopenhagen Academy for Medical Education and Simulation, Ryesgade 53B, Copenhagen, 2100, Denmark.
Carla Sa-CoutoRISE-Health, Community Medicine, Information and Decision Sciences Department (MEDCIDS), Faculty of Medicine, University of Porto (FMUP), Porto, Portugal.
Gabriel ReedyKings College, Strand, London, WC2R 2LS, UK.
Utstein XR in Simulation Expert Group

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundExtended reality (XR), encompassing virtual, augmented, and mixed reality, is increasingly integrated into healthcare simulation-based education and training. While XR offers immersive, scalable, and potentially cost-effective learning environments, evidence of its educational effectiveness and implementation remains fragmented. To address this gap, an Utstein-style consensus meeting was convened to establish an international research agenda that advances the evidence-based integration of XR in healthcare education.

methodsThe meeting, held in Copenhagen, Denmark, in November 2024, brought together 24 international experts representing diverse disciplines, geographic regions, and simulation expertise. A Delphi-informed pre-meeting survey, based on a targeted review of XR-focused literature, identified key topics across five initial domains. Using an implementation science–informed approach guided by the NASSS (Non-adoption, Abandonment, Scale-up, Spread, and Sustainability) framework, participants engaged in structured breakout and plenary discussions to explore barriers, facilitators, and research priorities related to XR adoption and sustainability.

resultsThrough consensus deliberation, the original five domains were refined into three overarching themes: (1) uses and adoption of XR, (2) barriers to XR adoption and implementation, and (3) facilitators of XR implementation and sustainability. Each theme comprised multiple subthemes addressing critical issues such as technological definitions, economic and infrastructure needs, human resource and faculty development, usability, educational quality, customization, and ethical considerations. Research questions within each subtheme were classified as descriptive, justificatory, or clarificatory to guide future study design and methodological rigor.

conclusionsThis Utstein Style meeting represents the first international, consensus-based effort to develop a structured research agenda for XR in healthcare simulation. Informed by implementation science, particularly the NASSS framework, the resulting agenda provides a roadmap for future research, policy, and practice. It emphasizes faculty readiness, institutional investment, and data-driven evaluation as prerequisites for sustainable integration. By addressing barriers and leveraging facilitators, the healthcare simulation community can advance the responsible adoption of XR technologies, enhancing competency, equity, and innovation in health professions education worldwide.

Indexed as

Augmented Reality (AR)Extended Reality (XR)Healthcare simulationMixed Reality (MR)Research agendaSimulation-based educationUtstein style meetingVirtual Reality (VR)

Identifiers

PMID41776623
PMCPMC12954913

What OpenQuestion 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 OpenQuestion graph.