Evidence map›Paper›PMID 35787488›Full record

ArticleJMIR serious games2022

Effectiveness of Using Augmented Reality for Training in the Medical Professions: Meta-analysis.

Yahia Baashar, Gamal Alkawsi, Wan Nooraishya Wan Ahmad, Hitham Alhussian, Ayed Alwadain, Luiz Fernando Capretz, Areej Babiker, Adnan Alghail

Abstract read
In one paragraph

Article in JMIR serious games, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

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

  1. Pooled it
  2. Pooled it
  3. Trial
  4. Article
  5. Review
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Review
  13. Article
  14. 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

8 authors.

Yahia BaasharFaculty of Computing and Informatics, Universiti Malaysia Sabah, Labuan, Malaysia.ORCID https://orcid.org/0000-0002-8004-3929
Gamal AlkawsiInstitute of Sustainable Energy, Universiti Tenaga Nasional, Kajang, Malaysia.ORCID https://orcid.org/0000-0002-2456-4033
Wan Nooraishya Wan AhmadFaculty of Computing and Informatics, Universiti Malaysia Sabah, Labuan, Malaysia.ORCID https://orcid.org/0000-0003-0023-0896
Hitham AlhussianDepartment of Computer and Information Sciences, Universiti Teknologi Petronas, Seri Iskandar, Malaysia.ORCID https://orcid.org/0000-0003-3947-269X
Ayed AlwadainDepartment of Computer Science, King Saud University, Riyadh, Saudi Arabia.ORCID https://orcid.org/0000-0001-5104-372X
Luiz Fernando CapretzDepartment of Electrical & Computer Engineering, Western University, Ontario, ON, Canada.ORCID https://orcid.org/0000-0001-6966-2369
Areej BabikerDepartment of Computer Engineering, Future University, Khartoum, Sudan.ORCID https://orcid.org/0000-0002-8105-1664
Adnan AlghailDepartment of World Languages, Greece Central School District, New York, NY, United States.ORCID https://orcid.org/0000-0003-0682-2470

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAugmented reality (AR) is an interactive technology that uses persuasive digital data and real-world surroundings to expand the user's reality, wherein objects are produced by various computer applications. It constitutes a novel advancement in medical care, education, and training.

objectiveThe aim of this work was to assess how effective AR is in training medical students when compared to other educational methods in terms of skills, knowledge, confidence, performance time, and satisfaction.

methodsWe performed a meta-analysis on the effectiveness of AR in medical training that was constructed by using the Cochrane methodology. A web-based literature search was performed by using the Cochrane Library, Web of Science, PubMed, and Embase databases to find studies that recorded the effect of AR in medical training up to April 2021. The quality of the selected studies was assessed by following the Cochrane criteria for risk of bias evaluations.

resultsIn total, 13 studies with a total of 654 participants were included in the meta-analysis. The findings showed that using AR in training can improve participants' performance time (I

conclusionsThe findings of this work suggest that AR can effectively improve performance time, satisfaction, and confidence in medical training but is not very effective in areas such as knowledge and skill. Therefore, more AR technologies should be implemented in the field of medical training and education. However, to confirm these findings, more meticulous research with more participants is needed.

Indexed as

augmented realitymedicalmeta-analysistrainingvirtual

Identifiers

PMID35787488
PMCPMC9297143

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.