Evidence map›Paper›PMID 38832348›Full record

ArticleFrontiers in digital health2024

Editorial: Immersive media in connected health-volume II.

P E Antoniou, D Economou, A Athanasiou, G Tsoulfas

Abstract readEditorial
In one paragraph

Article in Frontiers in digital health, 2024. 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

4 authors.

P E Antoniou *Lab of Medical Physics and Digital Innovations, Department of Medicine, School of Health Sciences, Aristotle University of Thessaloniki, Thessaloniki, Greece.
D Economou *School of Computer Science, University of Westminster, London, United Kingdom.
A Athanasiou *Lab of Medical Physics and Digital Innovations, Department of Medicine, School of Health Sciences, Aristotle University of Thessaloniki, Thessaloniki, Greece.
G Tsoulfas *Department of Transplantation Surgery, Ippokrateio General Hospital/Aristotle University of Thessaloniki, Thessaloniki, Greece.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Immersive media, particularly Extended Reality (XR), is at the forefront of revolutionizing the healthcare industry. Healthcare provides XR with "silver bullet" use cases that add value and societal effect to the technology. Healthcare interventions frequently require imaging or visualization to be applied correctly, and the sensation of presence that XR can provide is crucial as a training aid for healthcare learners. From anatomy to surgical training, multimodal immersion in the reality of a medical situation increases the impact of an XR resource compared to the usual approach. Thus, healthcare has become a specialized focus for the immersive media sector, with a multitude of development and research underway. This research subject, which followed on from the previous one, yielded an eclectic group of works spanning the gamut of immersive media applications in healthcare. The underlying theme in these works remains a consistent focus on calibrating, validating, verifying, and standardizing procedures, instruments, and technologies in order to constantly rigorously streamline the means and materials that will integrate immersive technologies in healthcare. In that spirit, we share the findings from this research topic as a motivator for rigorous and evidence-based use of immersive media in digital and connected health.

Indexed as

ADHDassistive roboticsco-creationextended realitymedical educationneurosurgeryrehabilitation

Identifiers

PMID38832348
PMCPMC11144886

What OpenQuestion holds

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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.