Evidence map›Paper›PMID 41157821›Full record

ArticleJournal of dental education2026

The Effect of 3D Printed Models on the Ability of Dental Students to Locate the Second Mesiobuccal Canal in Maxillary First Molars.

Eda Gürsu Şahin, Remzi Orkun Akgün

Abstract read
In one paragraph

Article in Journal of dental education, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

2 authors.

Eda Gürsu ŞahinDepartment of Endodontics at the Faculty of Dentistry, Cankiri Karatekin University, Çankırı, Turkey.ORCID https://orcid.org/0000-0001-9226-3454
Remzi Orkun AkgünDepartment of Basic Sciences at the Faculty of Dentistry, Cankiri Karatekin University, Çankırı, Turkey.ORCID https://orcid.org/0000-0001-6648-7059

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesEndodontic treatment is one of the final options aimed at preserving a tooth before extraction. The complex root canal anatomy of maxillary first molars (MFMs), particularly the detection of the second canal located in the mesiobuccal root, presents a significant clinical challenge. This study evaluates the influence of 3D-printed MFM models on the ability of dental students to identify the second mesiobuccal (MB2) canal.

methodsA total of 50 dental students who had completed their preclinical endodontic training were included in the study. In the first phase, standardized 3D printed models (3DPMs) were given to the students, who were then instructed to perform access cavity preparations and locate the root canals. Subsequently, a theoretical lecture on the morphology of the MB2 canal was delivered using digital 3D visualizations, supported by an enlarged 3DPM magnified fivefold. Following the theoretical training, the same procedure was repeated using new models. Participants' feedback was collected through a five-point Likert scale questionnaire.

resultsPrior to the training, only one student was able to accurately identify the MB2 canal; however, this number increased significantly following the educational intervention (p < 0.001). A total of 96% of the participants reported that the 3DPM were effective in distinguishing canal locations, and 100% indicated that the models contributed educationally to their understanding of endodontic anatomy.

conclusionEducational materials based on 3D printing technology enhance the effectiveness of preclinical endodontic training and improve students' ability to perceive and identify complex root canal anatomies.

Indexed as

Dental Pulp CavityEducation, DentalEndodonticsModels, DentalMolarPrinting, Three-DimensionalStudents, DentalClinical CompetenceHumansMaxilla3D printingdental educationmaxillar first molar

Identifiers

PMID41157821
PMCPMC13371994

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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.