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Physical simulation models for veterinary surgical training: a systematic review
Javier Salas-Guerra1, Juan A Sánchez-Margallo2, David Durán-Rey1
1Laparoscopy Unit, Jesús Usón Minimally Invasive Surgery Centre, Cáceres, Spain.
Introduction:
Simulation has become an increasingly important educational strategy in veterinary surgical training. This is driven by ethical considerations, the need to standardize skill acquisition, and limitations associated with training based on live animals and cadavers. However, the characteristics, scope, and validation of simulators used in veterinary surgery remain heterogeneous and insufficiently systematized. This study aimed to systematically review and characterize the simulators used in veterinary surgical education, focusing on their characteristics, applications, and validations. This should also identify current limitations and potential future research directions.
Methods:
A systematic review was conducted following the PRISMA 2020 guidelines. The PubMed and Web of Science databases were searched to identify studies on the use of physical simulators in veterinary surgical training published between July 2016 and July 2026. Studies based solely on cadavers, ex vivo models, virtual reality simulators, and those not focused on veterinary practice, were excluded. The results were synthesized descriptively using predefined categorical frameworks.
Results:
A total of 1,409 articles were identified, of which 78 studies were ultimately included. Most simulators were low fidelity (55%) and developed in academic settings. High-fidelity simulators were predominantly commercial (79%). The majority of the simulators identified were canine models (42%) or box trainers (21%), with a focus on sterilization procedures. Comparatively limited representation was found for other species and surgical specialties. Validation approaches were heterogeneous, with face, content and construct validity being the most frequently reported.
Conclusion:
Physical simulators are widely used in veterinary surgical education, but their development remains uneven across species, specialties, and validation standards. There is a clear need for higher-fidelity, species-diverse simulators, as well as more rigorous and standardized validation frameworks to strengthen the educational and clinical impact of simulation-based training.