Background/Aim: Since YouTube videos do not have accuracy filters, there are concerns about the information content. There are no studies specifically addressing the link between “Covid-19" and "radiology" in terms of content, reliability, and efficacy. The study aims to analyze videos posted on YouTube concerning Covid-19 and imaging in English.
Methods: The parameters of 120 most viewed videos on YouTube were recorded with the search of keywords "Covid-19 radiology" and "Covid-19 imaging". Quality Criteria for Consumer Health Information (DISCERN) and medical information and content index (MICI) scores were used to assess the reliability and medical content quality, respectively. The content was evaluated by types of radiological modalities and the patient groups included. Efficacy classification was conducted to assess "informative," "misleading," "individual experience" and "news update" groups. Video sources and target audience were analyzed.
Results: After the exclusion criteria, 55 videos were examined. The informative group (n=49) had a higher MICI score (MICI=8) when compared to the other groups (individual experience: 1 (n=3), news update: 1 (n=3), P<0.001). Among the informative ones, 25 videos (51%) were from radiology-related YouTube channels (YC). The MICI and DISCERN scores of the videos, where “radiologists” and “clinicians” make explanations, were significantly higher compared to the “others” group (P=0.001, and P=0.005, respectively). Computed tomography (CT) was the most frequently mentioned radiologic modality (n=49.84%). Pediatric and pregnant population videos were comparatively rarely offered (n=4.7% and n=3.4%).
Conclusion: The most viewed videos on YouTube about Covid-19 and radiology are reliable and informative videos narrated by radiologists and published by radiology-related channels and radiology societies. Accurate and scientific evidence-based information sharing is important on online social and scientific platforms.
Primary Language | English |
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Subjects | Radiology and Organ Imaging |
Journal Section | Research article |
Authors | |
Publication Date | December 1, 2021 |
Published in Issue | Year 2021 |