Review finds gaps in veterinary surgical simulation training
Bottom line
Physical simulators are now a well-established part of veterinary surgical education, but a new systematic review suggests the field is still narrow in scope and uneven in quality. In a Frontiers in Veterinary Science review published August 19, 2026, Javier Salas-Guerra and colleagues analyzed 78 studies published from July 2016 through July 2026 and found that most models were low-fidelity, academically developed trainers aimed at basic skills, especially canine sterilization procedures. Across the literature, 55% of simulators were classified as low fidelity, 42% were canine models, and 21% were box trainers, with comparatively limited coverage of other species and surgical specialties. The authors conclude that veterinary simulation is widely used, but validation standards remain heterogeneous and stronger, more standardized frameworks are needed. (frontiersin.org)
Why it matters: For veterinary educators, surgeons, and practice leaders involved in training, the review highlights a gap between where simulation is most available and where workforce needs may be broader. Prior literature has shown that new graduates are often expected to perform common small animal procedures with limited supervision, that students need repeated practice to reach competence, and that additional validated assessment rubrics are still needed. AAVMC guidance also supports using models and simulation as part of a stepwise, competency-based approach, especially when alternatives to live animal use are available. Taken together, the new review suggests simulation is becoming a core training tool, but veterinary programs may need more species-diverse models, stronger outcome measures, and better evidence that simulator performance translates to live clinical care. (onlinelibrary.wiley.com)
What to watch: Expect more attention on validation, competency-based assessment, and whether future simulator development expands beyond low-complexity canine procedures into large animal, specialty, and practice-ready training. (frontiersin.org)
Veterinary surgical simulation is growing, but a new systematic review argues the field still has important blind spots. In the August 19, 2026, Frontiers in Veterinary Science paper, Javier Salas-Guerra and colleagues reviewed 78 studies on physical simulation models for veterinary surgical training and found that most simulators were low-fidelity tools focused on a limited set of procedures, especially canine sterilization. The authors say simulation is now widely used in veterinary education, but the evidence base remains fragmented across species, specialties, and validation methods. (frontiersin.org)
That finding builds on concerns already present in veterinary education literature. A 2021 review of models in veterinary surgical education found room for growth in validity evidence, large animal applications, resident training, and continuing education. A 2022 review in Veterinary Surgery similarly reported that students often need repeated practice to reach competence in common sterilization procedures, while learning curves for many other surgeries remain poorly defined. Meanwhile, AAVMC guidance has increasingly framed simulation as part of competency-based veterinary education and as a preferred alternative when suitable models can replace some live animal use. (pubmed.ncbi.nlm.nih.gov)
The new review screened 1,409 articles and ultimately included 78 studies, covering 91 different physical simulators. Most were developed in academic settings, while high-fidelity models were more likely to be commercial products. By the authors’ count, 55% of simulators were low fidelity, 30% medium fidelity, and 15% high fidelity. Canine models made up 42% of the total, and box trainers 21%, with a strong emphasis on genital tract procedures and sterilization. The review also found that studies used a mix of face, content, construct, predictive, and concurrent validity approaches, but not in a standardized way, making comparisons across models difficult. (frontiersin.org)
The paper’s deeper message is that simulation availability does not necessarily equal simulation readiness for the full range of veterinary practice. The authors argue that the dominance of low-complexity tasks, restricted species representation, and uneven validation may limit how well current models prepare learners for real-world surgical variation. They also note practical reasons for the imbalance: high-fidelity simulators are costlier and technically harder to develop, which may explain why they are more often commercial, while low-fidelity tools are easier for academic programs to build and adopt. (frontiersin.org)
Industry and academic commentary broadly supports that interpretation. A 2026 Frontiers review of physical models and simulators in veterinary education concluded that simulation-based training shows clear educational benefits across multiple domains, but said financial constraints, realism limits, faculty training needs, and weak evidence quality still complicate implementation. Related literature in veterinary laparoscopy and surgical assessment has also emphasized the need for stronger validation language and better proof that simulator gains transfer to clinical performance. In one earlier pilot study, a low-cost spay model performed similarly to a much more expensive silicone model on most assessed items, underscoring that higher fidelity does not automatically mean better educational value. (frontiersin.org)
Why it matters: For veterinary professionals, especially faculty, clinical skills lab leaders, and surgeons mentoring new graduates, this review is less about whether simulation works and more about where it works best, and where evidence is still thin. Programs under pressure to produce practice-ready graduates may be relying heavily on models built around common small animal procedures because those are accessible, affordable, and aligned with entry-level expectations. But if validation remains inconsistent, it becomes harder to compare curricula, justify investment, or know whether simulator success predicts safer, more efficient patient care across species and case types. (onlinelibrary.wiley.com)
The review also lands at a time when competency-based frameworks are pushing veterinary education toward clearer assessment standards. That could increase demand for models paired with objective scoring tools, repeatable performance benchmarks, and evidence of transfer to live surgery. It may also sharpen questions for industry: whether commercial developers can broaden species coverage, whether schools can afford more realistic platforms, and whether low-cost academic models can be validated well enough to remain central in training pipelines. (aavmc.org)
What to watch: The next phase is likely to center on standardized validation frameworks, broader species and specialty coverage, and more studies linking simulator performance to clinical outcomes, not just learner confidence or expert opinion. (frontiersin.org)