Characterization of False or Misleading Fluoride Content on Instagram: Infodemiology Study

• Published in: Journal of medical Internet research Vol. 24; no. 5; p. e37519
• Main Authors: Lotto, Matheus, Sá Menezes, Tamires, Zakir Hussain, Irfhana, Tsao, Shu-Feng, Ahmad Butt, Zahid, P Morita, Plinio, Cruvinel, Thiago
• Format: Journal Article
• Language: English
• Published: Canada Journal of Medical Internet Research 19.05.2022; Gunther Eysenbach MD MPH, Associate Professor; JMIR Publications
• Subjects: Analysis; Caries; Computational linguistics; Data mining; Datasets; Dental caries; False information; Fluorides; Habits; Investigations; Language processing; Misinformation; Natural language interfaces; News; Oral health; Oral hygiene; Original Paper; Propaganda; Public health; Side effects; Social media; Social networks; Trade; dental caries; dental health; health outcome; misinformation; fluorides; infodemiology; health information; information seeking behavior; social media; eHealth; infoveillance; internet
• ISSN: 1438-8871; 1439-4456; 1438-8871
• DOI: 10.2196/37519

Online false or misleading oral health-related content has been propagated on social media to deceive people against fluoride's economic and health benefits to prevent dental caries. The aim of this study was to characterize the false or misleading fluoride-related content on Instagram. A total of 3863 posts ranked by users' total interaction and published between August 2016 and August 2021 were retrieved by CrowdTangle, of which 641 were screened to obtain 500 final posts. Subsequently, two independent investigators analyzed posts qualitatively to define their authors' interests, profile characteristics, content type, and sentiment. Latent Dirichlet allocation analysis topic modeling was then applied to find salient terms and topics related to false or misleading content, and their similarity was calculated through an intertopic distance map. Data were evaluated by descriptive analysis, the Mann-Whitney U test, the Cramer V test, and multiple logistic regression models. Most of the posts were categorized as misinformation and political misinformation. The overperforming score was positively associated with older messages (odds ratio [OR]=3.293, P<.001) and professional/political misinformation (OR=1.944, P=.05). In this context, time from publication, negative/neutral sentiment, author's profile linked to business/dental office/news agency, and social and political interests were related to the increment of performance of messages. Although political misinformation with negative/neutral sentiments was typically published by regular users, misinformation was linked to positive commercial posts. Overall messages focused on improving oral health habits, side effects, dentifrice containing natural ingredients, and fluoride-free products propaganda. False or misleading fluoride-related content found on Instagram was predominantly produced by regular users motivated by social, psychological, and/or financial interests. However, higher engagement and spreading metrics were associated with political misinformation. Most of the posts were related to the toxicity of fluoridated water and products frequently motivated by financial interests.