YouTube is often used by patients and healthcare professionals to obtain medical information. Reactive arthritis (ReA) is atype of inflammatory arthritis triggered by infection, usually in the genitourinary or gastrointestinal tract. However, the accuracy and quality of ReA-related information on YouTube are not fully known. This study aimed to assess the reliability and quality of YouTube videos pertaining to ReA. AYouTube search was performed on August1, 2023, using the keywords "reactive arthritis," "Reiter's disease," and "Reiter's syndrome." The number of days since upload; the number of views, likes, and comments; and the duration of videos were recorded. The modified DISCERN tool (mDISCERN) and the global quality scale (GQS) were used to evaluate the reliability and quality of the videos. Two physicians independently classified videos as low, moderate, or high quality and rated them on afive-point GQS (1 = poor quality, 5 = excellent quality). The source of videos was also noted. Of the 180videos screened, 68met the inclusion criteria. The most common topic (61, 89.7%) was "ReA overview." Among the 68videos analyzed, the main source of uploads was physicians 45(66.2%), and 66(97%) were categorized as useful. Around half of the YouTube videos about ReA were of high quality (33, 48.5%) according to the GQS. Upon comparing videos uploaded by rheumatologists, non-rheumatology healthcare professionals, and independent users, significant differences were found in mDISCERN and GQS but not in the number of views, likes, and comments or duration. Upon comparing high-, moderate-, and low-quality videos, significant differences were found in the number of views, likes, and comments; duration; and in mDISCERN and GQS. YouTube is asource of information on ReA of variable quality, with wide viewership and the potential to influence patients' knowledge and behavior. Our results showed that most YouTube videos on ReA were of high quality. Videos presented by physicians had higher quality. YouTube should consider avoiding low-quality videos by using validity scales such as mDISCERN and GQS.