YouTube online videos as a source for patient education of cervical spondylosis—a reliability and quality analysis

Abstract

Abstract Background Given a prolonged course of Cervical spondylosis (CS) could cause irreversible neurological deficits, it is crucial to disseminate CS-related health information to the public to promote early diagnosis and treatment. YouTube has been widely used to search for medical information. However, the reliability and quality of videos on YouTube vary greatly. Thus, this study aimed to assess the reliability and educational quality of YouTube videos concerning CS and further explore strategies for optimization of patient education. Methods We searched YouTube online library for the keywords “cervical spondylosis”, “cervical radiculopathy” and “cervical myelopathy” on January 15, 2023. Ranked by “relevance”, the first 50 videos of each string were recorded. After exclusions, a total of 108 videos were included. All videos were extracted for characteristics and classified based on different sources or contents. Two raters independently evaluated the videos using Journal of American Medical Association (JAMA) benchmark criteria, Modified DISCERN (mDISCERN) tool, Global Quality Scale (GQS) and Cervical-Spondylosis-Specific Scale (CSSS), followed by statistical analyses. All continuous data were described as median (interquartile range). Results All videos had median values for JAMA, mDISCERN, GQS and CSSS scores of were 3.00 (1.00), 3.00 (2.00), 2.00 (1.00) and 7.00 (8.88), respectively. There were significant differences in VPI (P = 0.009) and JAMA (P = 0.001), mDISCERN (P < 0.001), GQS (P < 0.001) and CSSS (P < 0.001) scores among different sources. Videos from academic source had advantages in reliability and quality scores than other sources. VPI (P < 0.001), mDISCERN (P = 0.001), GQS (P < 0.001) and CSSS (P = 0.001) scores also significantly differed among videos of various contents. Spearman correlation analysis indicated VPI was not correlated with either reliability or quality. Multiple linear regression analysis showed a longer duration and an academic source were independent predictors of higher reliability and quality, while a clinical source also led to the higher video quality. Conclusions The reliability and educational quality of current CS-related videos on YouTube are unsatisfactory. Users face a high risk of encountering inaccurate and misleading information when searching for CS on YouTube. Longer duration, source of academic or clinician were closely correlated to higher video reliability and quality. Improving the holistic reliability and quality of online information requires the concerted effort from multiple parties, including uploaders, the platform and viewers.