Evidence map›Paper›PMID 40904257›Full record

ArticleRestorative dentistry & endodontics2025

Is YouTube a reliable source for learning pre-endodontic build-up? A cross-sectional study.

Merve Gökyar, İdil Özden, Hesna Sazak Öveçoğlu

Abstract read
In one paragraph

Article in Restorative dentistry & endodontics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. Article
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

3 authors.

Merve GökyarDepartment of Endodontics, Faculty of Dentistry, Marmara University, Istanbul, Türkiye.
İdil ÖzdenDepartment of Endodontics, Faculty of Dentistry, Marmara University, Istanbul, Türkiye.
Hesna Sazak ÖveçoğluDepartment of Endodontics, Faculty of Dentistry, Marmara University, Istanbul, Türkiye.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: The aim of this study is to comprehensively analyze the quality, educational value, and demographic characteristics of pre-endodontic build-up videos published on the YouTube™ platform (Google LLC). Methods: The study was conducted on YouTube™ using the keyword "pre-endodontic build-up." The first 100 videos retrieved from the search results were reviewed, and 61 videos meeting the inclusion criteria were analyzed. After assessing the demographic characteristics of the videos, viewing rates and interaction indices were calculated. The quality of the videos was evaluated using the DISCERN instrument and the Global Quality Scale (GQS). Statistical analyses were performed on the obtained results. Results: A total of 61 videos were analyzed, of which 56% were uploaded by endodontists. The majority of the videos were found to be of low quality. As the DISCERN score increased, video duration, number of likes, number of comments, and view rate also increased. Additionally, a significant positive correlation was observed between the DISCERN score and the GQS value (p = 0.004). The relationship between video upload sources and various parameters was analyzed, revealing statistically significant differences (p < 0.05). Conclusions: Considering all the evaluation methods used in this study, it is evident that the number of high-quality videos is low. This finding indicates that YouTube™ does not provide sufficient information on pre-endodontic build-up. To enhance its reliability as a source of medical information, YouTube™ should prioritize content that is not only popular but also accurate and of high quality, preferably created or endorsed by professionals.

Indexed as

EducationEndodonticsInternetYouTube

Identifiers

PMID40904257
PMCPMC12415235

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Registered trials

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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.