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Simulation for skills training in neurosurgery: a systematic review, meta-analysis, and analysis of progressive scholarly acceptance
Open accessAbstract
At a time of significant global unrest and uncertainty surrounding how the delivery of clinical training will unfold over the coming years, we offer a systematic review, meta-analysis, and bibliometric analysis of global studies showing the crucial role simulation will play in training. Our aim was to determine the types of simulators in use, their effectiveness in improving clinical skills, and whether we have reached a point of global acceptance. A PRISMA-guided global systematic review of the neurosurgical simulators available, a meta-analysis of their effectiveness, and an extended analysis of their progressive scholarly acceptance on studies meeting our inclusion criteria of simulation in neurosurgical education were performed. Improvement in procedural knowledge and technical skills was evaluated. Of the identified 7405 studies, 56 studies met the inclusion criteria, collectively reporting 50 simulator types ranging from cadaveric, low-fidelity, and part-task to virtual reality (VR) simulators. In all, 32 studies were included in the meta-analysis, including 7 randomised controlled trials. A random effects, ratio of means effects measure quantified statistically significant improvement in procedural knowledge by 50.2% (ES 0.502; CI 0.355; 0.649, p < 0.001), technical skill including accuracy by 32.5% (ES 0.325; CI - 0.482; - 0.167, p < 0.001), and speed by 25% (ES - 0.25, CI - 0.399; - 0.107, p < 0.001). The initial number of VR studies (n = 91) was approximately double the number of refining studies (n = 45) indicating it is yet to reach progressive scholarly acceptance. There is strong evidence for a beneficial impact of adopting simulation in the improvement of procedural knowledge and technical skill. We show a growing trend towards the adoption of neurosurgical simulators, although we have not fully gained progressive scholarly acceptance for VR-based simulation technologies in neurosurgical education.
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“In neurosurgery, a great variety of simulation-based trainings have been established to overcome the shortage of practical training time in the OR per resident.”
From Neurosurgery resident training using blended learning concepts: Course development and participant evaluation (2022) · cites this paper as [9]
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“These trainings account for the greater expectations of residents’ surgical skills when treating patients.1,7–9”
From Neurosurgery resident training using blended learning concepts: Course development and participant evaluation (2022) · cites this paper as [9]
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Thiong’o, G. M., & Rutka, J. T. (2022) · Springer eBooks · doi:10.1007/978-3-031-02078-0_23
Elarjani, T., Lu, V. M., Berry, K., Eichberg, D. G., Ivan, M. E., Komotar, R. J., & Luther, E. (2022) · Operative Neurosurgery · doi:10.1227/ons.0000000000000568
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Chen, X., TAKAHASHI, Y., Moeki, K. A. T. O., Tomoki, S. U. D. A., Shibuya, S., Sase, K., Tsujita, T., Oka, K., & 近野, 敦. (2024) · Transactions of the Society of Instrument and Control Engineers · doi:10.9746/sicetr.60.476
Future Applications: New 3D Training Model for Endoscopic Endonasal and Transorbital Approach
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Restelli, F., Mazzapicchi, E., Falco, J., Broggi, M. A., Vetrano, I. G., Ferroli, P., & Acerbi, F. (2024) · Journal of Neurosurgical Sciences · doi:10.23736/s0390-5616.24.06303-3
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Metadata
- Authors
- Davids, J., Manivannan, S., Darzi, A., Giannarou, S., Ashrafian, H., & Marcus, H. J.
- Affiliations
- Imperial College Healthcare NHS Trust (GB)
- University Hospital Southampton NHS Foundation Trust (GB)
- Corresponding author
- Davids, Joseph
- Venue
- Neurosurgical Review
- Published
- 2020-09-18
- Volume
- 44
- Issue
- 4
- Pages
- 1853-1867
- ISSN
- 0344-5607 (ISSN-L)
- 1437-2320
- PMC
- PMC8338820
- OpenAlex
- W3087239859
- Cited by
- 106
- References
- 130
- Citations by year
- 2026: 16 · 2025: 23 · 2024: 26 · 2023: 12 · 2022: 24 · 2021: 5
- FWCI
- 2.32
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- Neurosurgical Review (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Spiral (Imperial College London) (submittedVersion, cc-by)
- UCL Discovery (University College London) (submittedVersion)
- Funders
- Imperial College London
- Topics
- Health Sciences › Medicine › Surgery › Surgical Simulation and Training
- Social Sciences › Education › Simulation-Based Education in Healthcare
- Physical Sciences › Engineering › Biomedical Engineering › Anatomy and Medical Technology
- Keywords
- simulation-based training, neurosurgical training, virtual reality simulator, low-fidelity simulators, procedural knowledge, technical skills
- MeSH terms
- Virtual Reality, Clinical Competence, Computer Simulation, Humans, Neurosurgery, Neurosurgical Procedures
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