0225 An assessment of the information quality, understandability, and actionability of popular YouTube videos on sleep and sleep disorders. (25th May 2022) - Monten, Kristen; Loeb, Stacy; Le, Colin; Diaby, Fatoumata; Fray-Witzer, Maya; Van den Bulck, Jan; Robbins, Rebecca
Abstract: Introduction: The Internet and social media are widely used and surprisingly trusted sources of sleep health information. Despite the tremendous promise as platforms for sharing evidence-based information and supporting decision-making about sleep health and sleep disorders, this may not be the case. Few studies have examined the quality, understandability, and actionability of popular sleep health messages on the Internet and/or social media. Methods: We identified the most widely viewed videos about "sleep" and "insomnia" on YouTube, which is the most widely used social media platform in the U.S. Two trained coders reviewed each video using two validated assessment tools: (1) DISCERN which rates the quality of information (scores ranging from 1 to 5, with 3 as the threshold for moderate to good quality), and (2) the Patient Education Material Assessment (PEMAT) tool for understandability and actionability (with scores from 0 to 100%, with 70% used as the threshold value). We also documented video reach (the number of times the video was viewed) and likability (the number of times a viewer provided a "thumbs up" after viewing), metrics provided by YouTube. Results: Our search identified 21 popular videos on sleep and insomnia. The average reach of the videos analyzed was 8.4 million (range: 915, 639 to 39, 201, 665) and average likability was 257, 167 (19, 000 to 1, 600, 000). The average DISCERN score was 2.6, below the threshold for information quality. The average PEMAT scores for understandability (67%) and actionability (63%) were below the threshold for understandability and actionability. Conclusion: The most widely viewed videos about sleep and insomnia on YouTube had generally poor information quality, and were frequently difficult to understand. Support (If Any): SL is supported by the NYU Perlmutter Cancer Center Developmental Project Program, which is partially supported by the Cancer Center Support Grant P30CA016087