Assessment of the Quality of Sinus Elevation with Lateral Window Approach Procedure Videos on YouTube: A Content-quality Analysis

Although the lateral window approach allows for greater graft material delivery and bone formation, it is more challenging and invasive, prompting keen interest among dentists to master this method. YouTube is increasingly used for medical training; however, concerns regarding the quality of instructional videos exist. This study proposes new criteria for evaluating YouTube videos on maxillary sinus elevation with the aim of establishing standards for assessing instructional content in the field. We sourced 100 maxillary sinus elevation videos from YouTube and, following exclusion criteria, analyzed 65 remaining videos. The video characteristics, content quality, and newly developed criteria were evaluated. Statistical analyses, employing ordinal logistic regression, identified the factors influencing the quality of instructional videos and evaluated the significance of our new criteria. Although video interaction and view rate exhibited positive relations to content quality, they were not significant ( P =0.818 and 0.826, respectively). Notably, videos of fair and poor quality showed a significant negative relation ( P <0.001). Audio commentary, written commentary, and descriptions of preoperative data displayed positive but statistically insignificant relationships ( P =0.088, 0.228, and 0.612, respectively). The comparison of video evaluation results based on the developed criteria with content quality scores revealed significant negative relationships for good, fair, and poor videos ( P <0.001, Exp(B)=−4.306, −7.853, −10.722, respectively). Among the various video characteristics, only image quality showed a significant relationship with content quality. Importantly, our newly developed criteria demonstrated a significant relationship with video content quality, providing valuable insights for assessing instructional videos on maxillary sinus elevation and laying the foundation for robust standards.