Evidence map›Paper›PMID 35990836›Full record

ReviewEvidence-based complementary and alternative medicine : eCAM2022

Application of Virtual Reality Technology in Clinical Practice, Teaching, and Research in Complementary and Alternative Medicine.

Huifang Guan, Yan Xu, Dexi Zhao

Abstract readReview
In one paragraph

Review in Evidence-based complementary and alternative medicine : eCAM, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 2 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

10 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
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  6. Review
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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

3 authors.

Huifang GuanCollege of Traditional Chinese Medicine, Changchun University of Chinese Medicine, Changchun 130117, China.ORCID https://orcid.org/0000-0003-1677-6949
Yan XuCollege of Pediatrics, Henan University of Chinese Medicine, Zhengzhou 450000, Henan, China.ORCID https://orcid.org/0000-0001-5258-339X
Dexi ZhaoDepartment of Encephalopathy, The Affiliated Hospital of Changchun University of Chinese Medicine, No. 1478 Gong-Nong Road, Changchun, Jilin 130021, China.ORCID https://orcid.org/0000-0001-7890-9212

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The application of virtual reality (VR) in clinical settings is growing rapidly, with encouraging results. As VR has been introduced into complementary and alternative medicine (CAM), a systematic review must be undertaken to understand its current status. Aim: This review aims to evaluate and summarize the current applications of VR in CAM, as well as to explore potential directions for future research and development. Methods: After a brief description of VR technology, we discuss the past 20 years of clinical VR applications in the medical field. Then, we discuss the theoretical basis of the combination of VR technology and CAM, the research thus far, and practical factors regarding usability, etc., from the following three main aspects: clinical application, teaching, and scientific research. Finally, we summarize and propose hypotheses on the application of VR in CAM and its limitations. Results: Our review of the theoretical underpinnings and research findings to date leads to the prediction that VR and CAM will have a significant impact on future research and practice. Conclusion: Although there is still much research needed to advance the science in this area, we strongly believe that VR applications will become indispensable tools in the toolbox of CAM researchers and practitioners and will only grow in relevance and popularity in the era of digital health.

Identifiers

PMID35990836
PMCPMC9388243

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.