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Joint Diseases and
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Original Article · Open access

Evaluating YouTube as a source of information on limb lengthening surgery: A quality and reliability analysis

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Musa Ergin

Department of Orthopedics and Traumatology, Cihanbeyli State Hospital, Konya, Türkiye

ORCID: 0000-0002-8690-6115

Ebubekir Eravsar

Department of Orthopedics and Traumatology, Selçuk University Faculty of Medicine, Konya, Türkiye

ORCID: 0000-0003-2940-604X

Mustafa Citak

Department of Orthopaedic Surgery, Knappschaft Kliniken Dortmund, Germany

ORCID: 0000-0003-3207-7101

Abstract

Objectives: This study aims to evaluate the content quality and reliability of YouTube videos on limb lengthening surgery.

Materials and methods: On July 5th, 2025, a YouTube search was performed using the keywords “limb lengthening surgery” and “leg lengthening surgery.” The first 100 videos were reviewed; duplicates and those without English audio were excluded, resulting in 53 videos for analysis. Basic characteristics including views, upload time, duration, comments were recorded. Videos were categorized by source as “physician,” “speaker,” or “patient,” and by theme as “general information” or “patient testimony.” Video content quality, including accuracy, reliability, and comprehensibility of information, was assessed using the DISCERN, Journal of the American Medical Association (JAMA) Benchmark Score, Global Quality Score (GQS), and a researcher-developed Limb Lengthening Scoring System (LLSS). Two orthopedic surgeons independently evaluated all videos.

Results: The median view count of the 53 videos was 48,036 (range, 1,229 to 3.734,177), and the mean number of days since upload (as of July 5th, 2025) was 1,331 ± 735 days. The mean DISCERN was 24.4 ± 6.9, median JAMA 2 (range, 1 to 2), median GQS 1.5 (range, 1 to 3.5), and mean LLSS 1.1 ± 0.9. Physician-generated videos achieved significantly higher DISCERN and GQS scores (p = 0.031 and p = 0.040, respectively) than patient-generated videos. Speaker-generated videos had higher LLSS scores than patient-generated videos (p = 0.013). General information videos scored higher than patient testimonies for DISCERN (p = 0.035) and GQS (p = 0.025). Video duration and comment count positively correlated with LLSS (p < 0.001 and p = 0.047, respectively), whereas view counts and ratios showed no significant association with quality scores.

Conclusion: YouTube videos on limb lengthening surgery are usually of low quality, with limited scientific accuracy and educational value. Physician-produced videos receive higher scores; however, their overall quality still remains limited, while patient-generated content shows the lowest reliability. These findings highlight that inaccurate or incomplete online information may influence patient expectations prior to consultation and complicate shared decision-making. Greater involvement of orthopedic surgeons and academic institutions is needed to provide clear, evidence-based, and reliable online educational content to improve patient understanding and clinical communication.

Declarations

Author Contributions

M.E., E.E.: Participated in the design of the study, participated in the interpretation of the results and writing of the manuscript; M.C.: Has supervised and edited the manuscript. All authors reviewed the manuscript. All authors assume full responsibility for the content of the manuscript.

Conflict of Interest

The authors declared no conflicts of interest with respect to the authorship and/or publication of this article.

Financial Disclosure

The authors received no financial support for the research and/or authorship of this article.

Data Sharing Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.

AI Disclosure

The authors declare that artificial intelligence (AI) tools were not used, or were used solely for language editing, and had no role in data analysis, interpretation, or the formulation of conclusions. All scientific content, data interpretation, and conclusions are the sole responsibility of the authors. The authors further confirm that AI tools were not used to generate, fabricate, or ‘hallucinate’ references, and that all references have been carefully verified for accuracy.

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