Evidence map›Paper›PMID 41340842›Full record

ArticleJMIR XR and spatial computing2025

A Local Training Program to Increase Awareness of Emerging Extended Reality Technologies Among Health Care Professionals: Development Study.

Charlotte Galvin, Jonathan Watt, Payal Ghatnekar, Nicholas Peres, Jacqueline Rees-Lee

Abstract read
In one paragraph

Article in JMIR XR and spatial computing, 2025. 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

5 authors.

Charlotte GalvinTorbay and South Devon NHS Foundation Trust, Torbay Hospital, Torquay, TQ2 7AA, United Kingdom, 01803 614567.ORCID https://orcid.org/0000-0002-3309-9794
Jonathan WattTorbay and South Devon NHS Foundation Trust, Torbay Hospital, Torquay, TQ2 7AA, United Kingdom, 01803 614567.ORCID https://orcid.org/0009-0009-1060-1516
Payal GhatnekarTorbay and South Devon NHS Foundation Trust, Torbay Hospital, Torquay, TQ2 7AA, United Kingdom, 01803 614567.ORCID https://orcid.org/0000-0002-0135-0593
Nicholas Peres *Torbay and South Devon NHS Foundation Trust, Torbay Hospital, Torquay, TQ2 7AA, United Kingdom, 01803 614567.ORCID https://orcid.org/0009-0009-2642-418X
Jacqueline Rees-Lee *Torbay and South Devon NHS Foundation Trust, Torbay Hospital, Torquay, TQ2 7AA, United Kingdom, 01803 614567.ORCID https://orcid.org/0009-0000-6083-6748

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Demands on health care services can greatly outweigh capacity. Multifactorial causative factors present great challenges, forcing the National Health Service (NHS) to increase efficiency and adaptivity. Concurrently, digital advancements are excelling and long-term plans for NHS sustainability are focusing on the use of technological interventions to benefit patients. As a result, integration of extended reality (XR) technology has become an important focus of health care research. However, models of how the digital literacy of health care workforces can be developed and how frontline staff can be actively involved in the design and development of creative digital interventions are lacking. Such programs are essential to allow the development and upscaling of digital innovation within the NHS for the benefit of the patients.Such a program has been developed in the Digital Futures research lab at Torbay and South Devon NHS Foundation Trust, representing one of the first immersive digital technologies research spaces embedded within the NHS. A "Digital Deep Dive" training program has been developed, allowing local health care workers to recognize the possibilities of digital health care technologies and supporting them in the evolution of ideas for potential bespoke digital solutions appropriate to their own patient groups and care pathways. Objective: This paper aims to explain the development of this unique XR Deep Dive program and present the evaluation that informed future directions for its ongoing development. Methods: The Deep Dive sessions were designed according to relevant pedagogic principles, including experiential, active, and contextual learning theories. Voluntary pilot sessions were held for local clinical teams comprised of junior doctors, consultants, nurses, and allied health professionals. Self-selection sampling was used. Participants completed an anonymous postsession feedback form, which was used to conduct a service evaluation. Data were analyzed using descriptive statistics (quantitative) and thematic analysis (qualitative). Results: In total, 21 completed questionnaires were analyzed. Overall, the sessions were positively received: all participants reported increased awareness of the potential for digital health care innovation postsession and most found it useful and relevant to their clinical careers. Participants valued the sessions being grounded in a context relevant to local practice with opportunities to interact with the technology through the lens of use cases. Conclusions: We have developed a unique training initiative providing contextually relevant XR technology awareness training for health care professionals locally. Despite the growing pace of digital health care innovation, we recognized a knowledge gap in our local workforce regarding the potential of XR technologies within health care. We responded by developing a training program grounded in the concept of digital co-creation-working with staff and service users to develop bespoke solutions integrated within patient pathways. The results from this paper will help to inform future directions for developing digital awareness training in our trust and have implications for wider NHS digital literacy training.

Indexed as

digital awareness trainingdigital deep divedigital futuredigital literacyemerging health care technologyextended realityextended reality in health carehealth care XRvirtual realityvirtual reality in health careVRXR

Identifiers

PMID41340842
PMCPMC12671294

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.