#Coronavirus on TikTok: user engagement with misinformation as a potential threat to public health behavior

Coronavirus disease (COVID)-related misinformation is prevalent online, including on social media. The purpose of this study was to explore factors associated with user engagement with COVID-related misinformation on the social media platform, TikTok. A sample of TikTok videos associated with the hashtag #coronavirus was downloaded on September 20, 2020. Misinformation was evaluated on a scale (low, medium, and high) using a codebook developed by experts in infectious diseases. Multivariable modeling was used to evaluate factors associated with number of views and presence of user comments indicating intention to change behavior. One hundred and sixty-six TikTok videos were identified and reviewed. Moderate misinformation was present in 36 (22%) videos viewed a median of 6.8 million times (interquartile range [IQR] 3.6-16 million), and high-level misinformation was present in 11 (7%) videos viewed a median of 9.4 million times (IQR 5.1-18 million). After controlling for characteristics and content, videos containing moderate misinformation were less likely to generate a user response indicating intended behavior change. By contrast, videos containing high-level misinformation were less likely to be viewed but demonstrated a nonsignificant trend towards higher engagement among viewers. COVID-related misinformation is less frequently viewed on TikTok but more likely to engage viewers. Public health authorities can combat misinformation on social media by posting informative content of their own. Lay Summary Coronavirus disease (COVID)-related misinformation is prevalent online, including on social media. The purpose of this study was to explore factors associated with user engagement with COVID-related misinformation on the social media platform, TikTok. We reviewed a sample of 166 TikTok videos associated with the hashtag #coronavirus posted between the beginning of the pandemic and September 2020. Misinformation was evaluated on a scale (low, medium, and high) using a codebook developed by experts in infectious diseases. Moderate misinformation was present in 36 (22%) videos viewed a median of 6.8 million times, and high-level misinformation was present in 11 (7%) videos view a median of 9.4 million times. After controlling for characteristics and content, videos containing moderate misinformation were less likely to generate a user response indicating intended behavior change. By contrast, videos containing high-level misinformation were less likely to be viewed but demonstrated a trend towards higher engagement among viewers. Public health authorities can combat misinformation on social media by posting informative content of their own.