ArticleEuropean oral research2023
Youtube videos as a source of information on digital indirect bonding: A content analysis.
Article in European oral research, 2023. 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.
- A Scoping Review of the Quality of Orthodontic Information on YouTube.Orthodontics & craniofacial research · 2025Article
- Is YouTube a reliable source for learning pre-endodontic build-up? A cross-sectional study.Restorative dentistry & endodontics · 2025Article
- Evaluation of the Quality of Educational Content of YouTube Videos on Silver Diamine Fluoride.International journal of clinical pediatric dentistry · 2024Article
- A Critical Review of YouTube Videos on the Socket-shield Technique: A Content-quality Analysis.Contemporary clinical dentistryArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Purpose: The aim of this study was to evaluate YouTube videos as a source of information for digital indirect bonding techniques. Materials and methods: The keyword "digital indirect bonding" was first searched on YouTube, resulting in 57 recorded videos. Descriptive parameters, including source, target audience, purpose, duration, upload date, number of likes, dislikes, views, and comments, were then evaluated. After this initial assessment, the interaction index and viewing rate were calculated. Video content quality was determined using a 5-point scale that categorized videos as having poor, moderate, or good content quality. This rating was based on the presence and discussion of various topics related to digital indirect bonding, including digital scan, digital bracket placement, transfer tray production from a 3D-printed model or direct production as a 3D-printed tray, clinical application, and advantages and/or disadvantages. The videos were assessed for quality using the global quality scale (GQS) and video information and quality index (VIQI). Statistical evaluation was conducted using Kruskal-Wallis, Chi-square, and Pearson correlation analysis, and intraclass correlation coefficients were calculated to determine the rating reliability. Results: The majority of the videos were classified as having poor content quality (41.9%), followed by moderate (38.7%) and good (19.4%) content quality. No significant differences were found between the videos in terms of descriptive parameters. However, videos with good content quality had significantly higher GQS and VIQI scores than moderate and poor content videos. The total content showed significant correlations with GQS and VIQI (r=0.780 and r=0.446, respectively; plt;0.05). Conclusion: In conclusion, while the majority of YouTube videos regarding digital indirect bonding were of poor content quality, those that were of good content quality could be considered a useful source of professional information.
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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.