Evidence map›Paper›PMID 40123778›Full record

ArticleJournal of research in nursing : JRN2025

Virtual reality as an intervention for adult burn patients: an integrative review.

Maria Ramage, Suja P Davis

Abstract readComment
In one paragraph

Article in Journal of research in nursing : JRN, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Trial
  2. Editorial.Journal of research in nursing : JRN · 2025
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors.

Maria RamageClinical Nurse I, Duke University Hospital, Durham, NC, USA.
Suja P DavisClinical Associate Professor, School of Nursing, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.ORCID https://orcid.org/0000-0001-9024-3089

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Virtual reality (VR) allows burn patients to engage in a virtual world and can provide patients with a distraction from pain. Aims: To assess the types of VR models available for use in the adult burn population and determine their efficacy regarding pain management and other health outcomes. Methods: The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines guided this review. We searched the databases of CINAHL and PubMed to identify the peer-reviewed journals that matched the inclusion criteria. We utilised the Joanna Briggs Institute (JBI) quality appraisal tools to evaluate the selected studies. Results: The search results ended in nine studies. The types of VR identified included passive and active scenarios with a focus on natural environments. The findings of the quantitative studies indicated that VR decreased patients' pain during therapeutic interventions. In contrast, the findings of most qualitative studies revealed that VR provided distraction for patients during wound care. Regarding secondary outcomes, VR was shown to improve hand rehabilitation, anxiety and pulmonary functions. Conclusion: This integrative review contributes to nursing by synthesising the evidence on VR as a non-pharmacological and complementary intervention to manage pain among adult burn patients. The implications of this review in nursing practice include consideration of staff training and technical support for practising nurses to successfully and safely implement the VR experience into their practice. Healthcare policies should delineate the best practices for VR use among burn patients to guide its implementation, funds to cover the costs of VR equipment, and equitable access to VR experience for all adult burn patients.

Indexed as

adult burn patientsintegrative reviewpain managementvirtual reality

Identifiers

PMID40123778
PMCPMC11924071

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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.