SynthesisJournal of dental education2026
Enhancing Oral Surgery Simulation: A Systematic Review of 3D-Printed Patient-Specific Models Compared to Traditional Animal Jaw Models for Presurgical Training.
Synthesis in Journal of dental education, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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.
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.
Who cites it
4 citing papers in PubMed.
- 3D-Printed Models in Oral Surgery Simulation Training: A Scoping Review.Journal of dental education · 2026Article
- Digital workflow for fabricating a patient-specific detachable 3D-printing model for mesiodens extraction to enhance surgical planning and dental education.BMC oral health · 2026Article
- Application of 3D-Printed nasal models in lacrimal surgery training.Head & face medicine · 2026Article
- Knowledge acquisition and retention following small-group case-based learning combined with sheep head animal model training in oral and maxillofacial surgery: a single-arm quasi-experimental study.Frontiers in medicine · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectives3D-printed simulation models are emerging as novel tools in various medical education fields. This study aims to investigate the evidence on the efficacy of 3D-printed jaw models compared to traditional animal models for oral surgical skill training.
methodsA comprehensive literature search was conducted up to June 2024 in Ovid Medline, Embase, Scopus, ProQuest, Epistemonikos, and ERIC databases. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, relevant studies were identified. Data were extracted independently by two reviewers. The Medical Education Research Study Quality Instrument tool (MERSQI) was used for methodological quality assessment.
resultsA total of 1074 potentially relevant publications were initially identified. only three articles met the stringent inclusion criteria. These studies provided unique insights into the application, effectiveness, limitations, and potential of 3D-printed versus animal models in dental oral surgery education, however, their methodological design received only a moderate score based on the MERSQI evaluation. In all three studies, the participants preferred 3D-printed models over traditional cadaveric models in terms of anatomical accuracy, educational value, and surgical simulation. However, limitations were identified, particularly in replicating realistic soft tissue sensations.
conclusions3D-printed models can provide a realistic and novel alternative tool to the animal jaw, enhancing the learning experience in oral surgical skill training of dental students. Despite the limitations of the available studies, integrating 3D printing technology into dental and oral surgery education shows promise for improving educational quality. Future well-designed studies are needed to strengthen the existing evidence on this topic.
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Registered trials
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.