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Evaluation of YouTube As A Source For Graves' Disease Information: Is High-Quality Guideline-Based Information
Oluwatobiloba Ayo-Ajibola1, Ryan J Davis1, Claire Theriault1
1Keck School of Medicine of the University of Southern California Los Angeles California USA.
Objective:
To understand the quality of informational Graves' disease (GD) videos on YouTube for treatment decision-making quality and inclusion of American Thyroid Association (ATA) treatment guidelines.
Study Design:
Cross-sectional cohort.
Setting:
Informational YouTube videos with subject matter "Graves' Disease treatment."
Method:
The top 50 videos based on our query were assessed using the DISCERN instrument. This validated algorithm discretely rates treatment-related information from excellent (≥4.5) to very poor (<1.9). Videos were also screened for ATA guideline inclusion. Descriptive statistics were used for cohort characterization. Univariate and multivariate linear regressions characterized factors associated with DISCERN scores. Significance was set at P < .05.
Results:
The videos featured 57,513.43 views (SD = 162,579.25), 1054.70 likes (SD = 2329.77), and 168.80 comments (SD = 292.97). Most were patient education (52%) or patient experience (24%). A minority (40%) were made by thyroid specialists (endocrinologists, endocrine surgeons, or otolaryngologists). Under half did not mention all 3 treatment modalities (44%), and 54% did not mention any ATA recommendations. Overall, videos displayed poor reliability (mean = 2.26, SD = 0.67), treatment information quality (mean = 2.29, SD = 0.75), and overall video quality (mean = 2.47, SD = 1.07). Physician videos were associated with lower likes, views, and comments (P < .001) but higher DISCERN reliability (P = .015) and overall score (P = .019). Longer videos (P = .015), patient accounts (P = .013), and patient experience (P = .002) were associated with lower scores.
Conclusion:
The most available GD treatment content on YouTube varies significantly in the quality of medical information. This may contribute to suboptimal disease understanding, especially for patients highly engaged with online health information sources.
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