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Protocol for a systematic review of the predictive and translational validity of simulation-based training in neurosurgery
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DOI：10.1186/s13643-026-03274-y.png)
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Abstract
En 中文
Simulation-based training (SBT) has become integral in neurosurgical education, aiming to enhance technical skills and patient safety. While advanced modalities, such as virtual reality (VR), augmented reality (AR), three-dimensional (3D) printing, and artificial intelligence (AI)-enhanced platforms, are increasingly adopted, evidence linking simulator performance to operative competence and patient or system-level outcomes remains limited. This protocol describes a systematic review evaluating the predictive and translational validity of neurosurgical SBT. Eligible studies will include neurosurgical trainees and practitioners undergoing SBT or assessment. A comprehensive search strategy, developed with an information specialist, will interrogate MEDLINE, Embase, Scopus, Web of Science, CINAHL, and the Cochrane Library. Inclusion criteria will focus on studies reporting outcomes related to operative competence, technical performance, or patient outcomes; studies assessing only learner satisfaction or knowledge without performance metrics will be excluded. Three reviewers will independently screen studies, extract data using a structured tool, and assess study quality using Messick’s validity framework, the Beckman scale, and the Modified Translational Outcomes of Simulation-Based Mastery Learning (TO-SBML) framework to inform an integrated, structured narrative synthesis. This review will provide an evidence-informed synthesis of the predictive and translational validity of neurosurgical SBT, including AI-enhanced platforms, and identify methodological gaps that limit translation from simulator performance to operative, patient, and system-level outcomes. The findings are expected to inform curriculum design, competency-based assessment, credentialling, and decisions regarding the implementation and resourcing of SBT, while helping prioritise future research in areas where robust translational evidence remains limited. PROSPERO registration: CRD420251131906.
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