Due to the digital revolution that has taken place in recent decades, the access to information has been democratized, including health information; however, information is often burdened by falsehoods (misinformation) that can influence people's beliefs negatively and lead to adverse consequences on public health. The interest of Internet users in oral health-related content was demonstrated previously. In general, it was associated with low-quality and false digital information. Thus, this study aims to analyze and characterize the publications in English and Portuguese, present on Facebook and Instagram, related to misinformation about dental caries. This study will comprise 4 stages. First, search strategies will be constructed by the combination of keywords and hashtags related to dental caries using Boolean descriptors in the CrowdTangle platform. Second, the posts will be evaluated considering content, sentiment, interaction, engagement and comments. Third, the images of the posts will be characterized according to their structural properties and visual features. Fourth, a propagation network of URLs and hashtags related to dental caries will be built using the Gephi software. The most influential profiles for the propagation of false information will be analyzed qualitatively. Statistical analysis will be conducted according to normality and homogeneity of data, determined by Kolmogorov-Smirnov and Levene tests respectively. Pearson or Spearman correlation tests will be used to determine the correlation between two parametric and non-parametric variables. Similarly, T or Mann-Whitney tests will be used for comparison between groups. In addition, multivariate regression models will be built to determine which parameters predict the interaction and propagation of publications containing misinformation about dental caries on Facebook and Instagram.
News published in Agência FAPESP Newsletter about the scholarship: