Evidence map›Paper›PMID 36412148›Full record

SynthesisSurgical innovation2023

The Role of Augmented Reality in Surgical Training: A Systematic Review.

Dhivya Suresh, Abdullatif Aydin, Stuart James, Kamran Ahmed, Prokar Dasgupta

Abstract readSystematic Review
In one paragraph

Synthesis in Surgical innovation, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers, 6 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
47citing papers in PubMed, 6 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

47 citing papers in PubMed, 6 syntheses or guidelines pooled it.

  1. Pooled it
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  7. Trial
  8. Trial
  9. Article
  10. Perceptions of Artificial Intelligence in Gynecologic Oncology Education: Insights from a Qualitative Study Using Semi-Structured Interviews.Journal of cancer education : the official journal of the American Association for Cancer Education · 2026
    Article
  11. Article
  12. Article
  13. The evolution of cardiothoracic surgery training: from apprenticeship to AI-assisted simulation.Kardiochirurgia i torakochirurgia polska = Polish journal of cardio-thoracic surgery · 2026
    Review
  14. Article
  15. Article
  16. Medical Digital Twin Technology for Interoperability: Challenges and Opportunities.Biomedical engineering and computational biology · 2026
    Review
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  18. Review
  19. 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

5 authors.

Dhivya SureshGuy's, King's and St Thomas' School of Medical Education, King's College London, London, UK.ORCID 0000-0001-6133-7326
Abdullatif AydinMRC Centre for Transplantation, Guy's Hospital, King's College London, London, UK.ORCID 0000-0002-5440-7741
Stuart JamesDepartment of General Surgery, Princess Royal University Hospital, London, UK.ORCID 0000-0003-0608-0745
Kamran AhmedMRC Centre for Transplantation, Guy's Hospital, King's College London, London, UK.
Prokar DasguptaMRC Centre for Transplantation, Guy's Hospital, King's College London, London, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This review aims to provide an update on the role of augmented reality (AR) in surgical training and investigate whether the use of AR improves performance measures compared to traditional approaches in surgical trainees. PUBMED, EMBASE, Google Scholar, Cochrane Library, British Library and Science Direct were searched following PRIMSA guidelines. All English language original studies pertaining to AR in surgical training were eligible for inclusion. Qualitative analysis was performed and results were categorised according to simulator models, subsequently being evaluated using Messick's framework for validity and McGaghie's translational outcomes for simulation-based learning. Of the 1132 results retrieved, 45 were included in the study. 29 platforms were identified, with the highest 'level of effectiveness' recorded as 3. In terms of validity parameters, 10 AR models received a strong 'content validity' score of 2.15 models had a 'response processes' score ≥ 1. 'Internal structure' and 'consequences' were largely not discussed. 'Relations to other variables' was the best assessed criterion, with 9 platforms achieving a high score of 2. Overall, the Microsoft HoloLens received the highest level of recommendation for both validity and level of effectiveness. Augmented reality in surgical education is feasible and effective as an adjunct to traditional training. The Microsoft HoloLens has shown the most promising results across all parameters and produced improved performance measures in surgical trainees. In terms of the other simulator models, further research is required with stronger study designs, in order to validate the use of AR in surgical training.

Indexed as

Augmented RealityClinical CompetenceComputer Simulationgynecologic laparoscopyneurosurgeryorthopedic surgerysimulationsurgical educationurologyvascular surgery

Identifiers

PMID36412148
PMCPMC10331622

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.