Accuracy, Quality and Readability of Knee Osteoarthritis Information on Social Media (Instagram e TikTok) and Search Platforms (Google e YouTube): A Cross‐Sectional Study
Year: 2026
Type: article
Abstract: BACKGROUND: Knee osteoarthritis (KOA) is a chronic condition with a high global prevalence, often resulting in functional decline. Faced with this, many people turn to the internet to find information about the disease and available treatments. Besides the amount of content available online, it does not ensure its accuracy, quality and readability. This study aims to evaluate the accuracy, quality and readability of KOA-related information available on Instagram, TikTok, Google and YouTube in Brazilian Portuguese. METHODS: Google and YouTube searches were performed using 'Tratamento de osteoartrite de joelho', 'Tratamento de artrose no joelho' and 'Tratamento de artrite no joelho'. For each term, the first 20 results were selected. Searches on Instagram and TikTok were conducted using the hashtags: #artrosenojoelho, #artrosedojoelho, and #artrosedejoelho, selecting the first 100 posts for each term. All the research was done on June 19, 2024. Content accuracy was assessed against a reference resource on knee osteoarthritis, information quality was assessed using DISCERN, and the readability of Google content was evaluated using the Flesch-Kincaid Grade Level scale. RESULTS: We found that the information about medical management was the most classified as inaccurate. The overall DISCERN score indicated low quality (2.3 ± 0.7) and 78% of Google texts required at least 14 years of schooling to read. CONCLUSION: As digital platforms have become a widely used source of health information, our findings raise concerns about the potential for misinformation to delay effective treatment and perpetuate low-value care.
Source: Musculoskeletal Care
DOI: 10.1002/msc.70267
Institution: Universidade Federal de Juiz de Fora
Language: English
Subfield: General Health Professions
Field: Health Professions
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid: $3,240
OpenAlex ID: W7224407694