Evidence map›Paper›PMID 35122126›Full record

SynthesisActa neurochirurgica2022

Evaluation of simulation models in neurosurgical training according to face, content, and construct validity: a systematic review.

Shreya Chawla, Sharmila Devi, Paola Calvachi, William B Gormley, Roberto Rueda-Esteban

Abstract readSystematic Review
PubMed Full text at PMC Publisher
In one paragraph

Synthesis in Acta neurochirurgica, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
35citing 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

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

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  10. Application of transformer architectures in generative video modeling for neurosurgical education.International journal of computer assisted radiology and surgery · 2025
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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.

Shreya ChawlaComputational Neuroscience Outcomes Center, Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.ORCID 0000-0003-4720-2104
Sharmila DeviComputational Neuroscience Outcomes Center, Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
Paola CalvachiComputational Neuroscience Outcomes Center, Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
William B GormleyComputational Neuroscience Outcomes Center, Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
Roberto Rueda-EstebanComputational Neuroscience Outcomes Center, Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA. rj.rueda32@uniandes.edu.co.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundNeurosurgical training has been traditionally based on an apprenticeship model. However, restrictions on clinical exposure reduce trainees' operative experience. Simulation models may allow for a more efficient, feasible, and time-effective acquisition of skills. Our objectives were to use face, content, and construct validity to review the use of simulation models in neurosurgical education.

methodsPubMed, Web of Science, and Scopus were queried for eligible studies. After excluding duplicates, 1204 studies were screened. Eighteen studies were included in the final review.

resultsNeurosurgical skills assessed included aneurysm clipping (n = 6), craniotomy and burr hole drilling (n = 2), tumour resection (n = 4), and vessel suturing (n = 3). All studies assessed face validity, 11 assessed content, and 6 assessed construct validity. Animal models (n = 5), synthetic models (n = 7), and VR models (n = 6) were assessed. In face validation, all studies rated visual realism favourably, but haptic realism was key limitation. The synthetic models ranked a high median tactile realism (4 out of 5) compared to other models. Assessment of content validity showed positive findings for anatomical and procedural education, but the models provided more benefit to the novice than the experienced group. The cadaver models were perceived to be the most anatomically realistic by study participants. Construct validity showed a statistically significant proficiency increase among the junior group compared to the senior group across all modalities.

conclusionOur review highlights evidence on the feasibility of implementing simulation models in neurosurgical training. Studies should include predictive validity to assess future skill on an individual on whom the same procedure will be administered. This study shows that future neurosurgical training systems call for surgical simulation and objectively validated models.

Indexed as

Clinical CompetenceNeurosurgical ProceduresAnimalsCadaverComputer SimulationCraniotomyHumansConstruct/content/face validityNeurosimulationNeurosurgical educationNeurosurgical simulationResidency trainingSurgical; Surgical simulation

Identifiers

PMID35122126
PMCPMC8815386

What OpenQuestion holds

Textmetadata
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.