ArticlePeerJ2024
Assessing the quality and reliability of YouTube videos as a source of information on inflammatory back pain.
Article in PeerJ, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed, 24 citations in OpenAlex.
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- Readability analysis of breast cancer resources shared on X-implications for patient education and the potential of AI.Breast cancer research and treatment · 2025Article
- Web-Based Video Platforms as Sources of Information on Body Image Dissatisfaction in Adolescents: Content and Quality Analysis of a Cross-Sectional Study.JMIR formative research · 2025Article
- Social media best practices for the spine care professional.North American Spine Society journal · 2025Article
- Video platforms and sexual healthcare in China: assessment of content on premature ejaculation.Translational andrology and urology · 2025Article
- Educational performance of TikTok short videos for age related macular degeneration and its link to user engagement.Frontiers in medicine · 2025Article
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- Videos in short-video sharing platforms as sources of information on osteoarthritis: cross-sectional content analysis study.Frontiers in digital health · 2025Article
- YouTube as a source of information in cardiopulmonary resuscitation for 2020 AHA Resuscitation Guidelines.PeerJ · 2024Observational
- Assessment of health information in Chinese atopic dermatitis-related videos: A cross-sectional study.Digital healthArticle
- Article
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 at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Inflammatory back pain is a chronic condition with localized pain, particularly in the axial spine and sacroiliac joints, that is associated with morning stiffness and improves with exercise. YouTube is the second most frequently used social media platform for accessing health information. This study sought to investigate the quality and reliability of YouTube videos on inflammatory back pain (IBP). Methods: The study design was planned as cross-sectional. A search was conducted using the term "inflammatory back pain," and the first 100 videos that met the inclusion criteria were selected on October 19, 2023. The data of the videos selected according to the inclusion and exclusion criteria in the study settings were examined. Videos with English language, with audiovisual content , had a duration >30 s, non-duplicated and primary content related to IBP were included in the study. A number of video parameters such as the number of likes, number of views, duration, and content categories were assessed. The videos were assessed for reliability using the Journal of the American Medical Association (JAMA) Benchmark criteria and the DISCERN tool. Quality was assessed using the Global Quality Score (GQS). Continuous variables were checked for normality of distribution using Shapiro-Wilk test and Kolmogorov-Smirnov test. Kruskal-Wallis test and Mann-Whitney U test were used to analyze the continuous data depending on the number of groups. Categorical data were analyzed using Pearson's chi-square test. Results: Reliability assessment based on JAMA scores showed 21% of the videos to have high reliability. Quality assessment based on GQS results showed 19% of the videos to have high quality. JAMA, DISCERN, and GQS scores differed significantly by source of video ( Conclusion: The results of the present study showed that YouTube offers videos of low reliability and low quality on inflammatory back pain. Health authorities have a responsibility to protect public health and should take proactive steps regarding health information shared on social media platforms.
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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.