Cited by 76Misinformation and Its ImpactsSocial Media in Health EducationDental Health and Care Utilization

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

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Lotto, Matheus, Sá Menezes, Tamires, Zakir Hussain, Irfhana, Tsao, Shu-Feng, Ahmad Butt, Zahid, P Morita, Plinio, Cruvinel, Thiago·2022·Journal of Medical Internet Research

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Abstract

BACKGROUND: 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. OBJECTIVE: The aim of this study was to characterize the false or misleading fluoride-related content on Instagram. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.

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  • False or misleading fluoride content online may generate fear, reduce acceptance of fluoridation and fluoride-based prevention, and worsen inequalities.

    “False or misleading fluoride content online may generate fear, reduce acceptance of fluoridation and fluoride-based prevention, and worsen inequalities (Lotto et al 2022).”

    From New Frontiers for Implementation Science in Oral Health: Digital and Equity-Driven Pathways (2026) · cites this paper as Lotto et al 2022

    The Introduction (page unavailable) says online misinformation discourages consumption of fluoridated water and oral-care products and may generate or reinforce fluoride refusal. The Discussion’s Principal Findings (page unavailable) describe users’ fears surrounding fluoridated products and water. The cited passages do not address whether misinformation worsens inequalities. (LLM, conf=0.87)

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Research works printed but not linked: 38

  1. [1]Cruvinel T Ayala Aguirre PE Lotto M Marchini Oliveira T Rios D Pereira Cruvinel AF Digital behavior surveillance: monitoring dental caries and toothache interests of Google users from developing countries Oral Dis 2019 01 25 1 339 347 10.1111/odi.12986 30270556 30270556 · DOI
  2. [2]Rizzato VL Lotto M Lourenço Neto N Oliveira TM Cruvinel T Digital surveillance: the interests in toothache-related information after the outbreak of COVID-19 Oral Dis 2021 08 27 1 10 10.1111/odi.14012 34448289 PMC8661568 34448289 · DOI
  3. [3]Eysenbach G Infodemiology and infoveillance: framework for an emerging set of public health informatics methods to analyze search, communication and publication behavior on the Internet J Med Internet Res 2009 03 27 11 1 e11 10.2196/jmir.1157 19329408 v11i1e11 19329408 PMC2762766 · DOI · Paper page
  4. [4]Heaivilin N Gerbert B Page JE Gibbs JL Public health surveillance of dental pain via Twitter J Dent Res 2011 09 90 9 1047 1051 10.1177/0022034511415273 21768306 0022034511415273 21768306 PMC3169887 · DOI
  5. [5]Graf I Gerwing H Hoefer K Ehlebracht D Christ H Braumann B Social media and orthodontics: a mixed-methods analysis of orthodontic-related posts on Twitter and Instagram Am J Orthod Dentofacial Orthop 2020 08 158 2 221 228 10.1016/j.ajodo.2019.08.012 32576427 S0889-5406(20)30227-4 32576427 · DOI
  6. [7]Barber SK Lam Y Hodge TM Pavitt S Is social media the way to empower patients to share their experiences of dental care? J Am Dent Assoc 2018 06 149 6 451 459 10.1016/j.adaj.2018.01.007 29656806 S0002-8177(18)30011-4 29656806 · DOI
  7. [8]Giglietto F Iannelli L Valeriani A Rossi L ‘Fake news’ is the invention of a liar: how false information circulates within the hybrid news system Curr Sociol 2019 04 08 67 4 625 642 10.1177/0011392119837536 · DOI
  8. [9]Strieder AP Aguirre PEA Lotto M Cruvinel AFP Cruvinel T Digital behavior surveillance for monitoring the interests of Google users in amber necklace in different countries Int J Paediatr Dent 2019 09 29 5 603 614 10.1111/ipd.12500 30920686 30920686 · DOI
  9. [10]Swire-Thompson B Lazer D Public health and online misinformation: challenges and recommendations Annu Rev Public Health 2020 04 02 41 433 451 10.1146/annurev-publhealth-040119-094127 31874069 31874069 · DOI · Paper page
  10. [11]Rovetta A Bhagavathula AS Global infodemiology of COVID-19: analysis of Google web searches and Instagram hashtags J Med Internet Res 2020 08 25 22 8 e20673 10.2196/20673 32748790 v22i8e20673 32748790 PMC7458585 · DOI · Paper page
  11. [12]Massey PM Kearney MD Hauer MK Selvan P Koku E Leader AE Dimensions of misinformation about the HPV vaccine on Instagram: content and network analysis of social media characteristics J Med Internet Res 2020 12 03 22 12 e21451 10.2196/21451 33270038 v22i12e21451 33270038 PMC7746500 · DOI
  12. [13]Niknam F Samadbeik M Fatehi F Shirdel M Rezazadeh M Bastani P COVID-19 on Instagram: A content analysis of selected accounts Health Policy Technol 2021 03 10 1 165 173 10.1016/j.hlpt.2020.10.016 33723502 S2211-8837(20)30125-8 33723502 PMC7950219 · DOI
  13. [14]Mackert M Bouchacourt L Lazard A Wilcox GB Kemp D Kahlor LA George C Stewart B Wolfe J Social media conversations about community water fluoridation: formative research to guide health communication J Public Health Dent 2021 06 81 2 162 166 10.1111/jphd.12404 33058200 33058200 · DOI
  14. [15]Mertz A Allukian M Community water fluoridation on the Internet and social media J Mass Dent Soc 2014 63 2 32 36 25230407 25230407
  15. [17]Oh HJ Kim CH Jeon JG Public sense of water fluoridation as reflected on Twitter 2009-2017 J Dent Res 2020 01 99 1 11 17 10.1177/0022034519885610 31682777 31682777 · DOI
  16. [18]Eliacik BK Topical fluoride applications related posts analysis on Twitter using natural language processing Oral Health Prev Dent 2021 01 07 19 1 457 464 10.3290/j.ohpd.b2048359 34546013 2048359 34546013 PMC11641408 · DOI
  17. [19]Walsh T Worthington HV Glenny A Marinho VC Jeroncic A Fluoride toothpastes of different concentrations for preventing dental caries Cochrane Database Syst Rev 2019 03 04 3 CD007868 10.1002/14651858.CD007868.pub3 30829399 30829399 PMC6398117 · DOI · Paper page
  18. [20]Belotti L Frazão P Effectiveness of water fluoridation in an upper-middle-income country: a systematic review and meta-analysis Int J Paediatr Dent. Preprint posted online on September 26, 2021 10.1111/ipd.12928 34564916 34564916 · DOI
  19. [21]Whelton HP Spencer AJ Do LG Rugg-Gunn AJ Fluoride revolution and dental caries: evolution of policies for global use J Dent Res 2019 07 98 8 837 846 10.1177/0022034519843495 31282846 31282846 · DOI
  20. [23]Lotto M Menezes TS Hussain IZ Tsao SF Butt ZA Morita PP Cruvinel T Raw data of the manuscript: Characterization of false or misleading fluoride content on Instagram: Infodemiology study Figshare 2022 01 31 2022-02-22 https://figshare.com/articles/dataset/Raw_data_of_the_manuscript_Characterization_of_misleading_fluoride_information_on_Instagram_/19099733 PMC9164089 35588055
  21. [26]Franz D Marsh HE Chen JI Teo AR Using Facebook for qualitative research: a brief primer J Med Internet Res 2019 08 13 21 8 e13544 10.2196/13544 31411143 v21i8e13544 31411143 PMC6711038 · DOI
  22. [30]Lim S Academic library guides for tackling fake news: a content analysis J Acad Librariansh 2020 09 46 5 102195 10.1016/j.acalib.2020.102195 · DOI
  23. [32]Aikin SF Poe's Law, group polarization, and argumentative failure in religious and political discourse Soc Semiot 2013 06 23 3 301 317 10.1080/10350330.2012.719728 · DOI
  24. [33]Asmussen CB Møller C Smart literature review: a practical topic modelling approach to exploratory literature review J Big Data 2019 10 19 6 1 93 10.1186/s40537-019-0255-7 · DOI
  25. [34]Xue J Chen J Chen C Zheng C Li S Zhu T Public discourse and sentiment during the COVID 19 pandemic: using latent Dirichlet allocation for topic modeling on Twitter PLoS One 2020 15 9 e0239441 10.1371/journal.pone.0239441 32976519 PONE-D-20-11036 32976519 PMC7518625 · DOI
  26. [35]Pang PC McKay D Chang S Chen Q Zhang X Cui L Privacy concerns of the Australian My Health Record: implications for other large-scale opt-out personal health records Inf Process Manag 2020 11 57 6 102364 10.1016/j.ipm.2020.102364 · DOI
  27. [36]Hagen L Content analysis of e-petitions with topic modeling: how to train and evaluate LDA models? Inf Process Manag 2018 11 54 6 1292 1307 10.1016/j.ipm.2018.05.006 · DOI
  28. [37]Jockers ML Mimno D Significant themes in 19th-century literature Poetics 2013 12 41 6 750 769 10.1016/j.poetic.2013.08.005 · DOI
  29. [38]Blei DM Probabilistic topic models Commun ACM 2012 04 01 55 4 77 84 10.1145/2133806.2133826 · DOI · Paper page
  30. [39]Nikolenko SI Koltcov S Koltsova O Topic modelling for qualitative studies J Inf Sci 2016 07 10 43 1 88 102 10.1177/0165551515617393 · DOI
  31. [40]Röder M Both A Hinneburg A Exploring the space of topic coherence measures 2015 8th ACM International Conference on Web Search and Data Mining 2015 Shanghai, China 339 408 10.1145/2684822.2685324 · DOI
  32. [41]Basch CH Milano N Hillyer GC An assessment of fluoride related posts on Instagram Health Promot Perspect 2019 9 1 85 88 10.15171/hpp.2019.11 30788272 30788272 PMC6377697 · DOI
  33. [43]Kim A Moravec PL Dennis AR Combating fake news on social media with source ratings: the effects of user and expert reputation ratings J Manag Inf Syst 2019 08 04 36 3 931 968 10.1080/07421222.2019.1628921 · DOI
  34. [44]Scherer LD Pennycook G Who is susceptible to online health misinformation? Am J Public Health 2020 10 110 S3 S276 S277 10.2105/AJPH.2020.305908 33001736 33001736 PMC7532320 · DOI
  35. [45]Boutyline A Willer R The social structure of political echo chambers: variation in ideological homophily in online networks Polit Psychol 2016 05 05 38 3 551 569 10.1111/pops.12337 · DOI · Paper page
  36. [46]Bauler LD Santos CSD Lima GS Moraes RR Charcoal-based dentifrices and powders: analyses of product labels, Instagram engagement, and altmetrics Braz Dent J 2021 32 2 80 89 10.1590/0103-6440202104233 34614064 S0103-64402021000200080 34614064 · DOI
  37. [47]Lotto M Strieder AP Ayala Aguirre PE Oliveira TM Andrade Moreira Machado MA Rios D Cruvinel T Parental-oriented educational mobile messages to aid in the control of early childhood caries in low socioeconomic children: A randomized controlled trial J Dent 2020 10 101 103456 10.1016/j.jdent.2020.103456 32827598 S0300-5712(20)30202-5 32827598 PMC7438225 · DOI
  38. [48]Hussain A Tahir A Hussain Z Sheikh Z Gogate M Dashtipour K Ali A Sheikh A Artificial intelligence-enabled analysis of public attitudes on Facebook and Twitter toward COVID-19 vaccines in the United Kingdom and the United States: observational study J Med Internet Res 2021 04 05 23 4 e26627 10.2196/26627 33724919 v23i4e26627 33724919 PMC8023383 · DOI

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Sorted by citations

Authors
Lotto, M., Sá Menezes, T., Zakir Hussain, I., Tsao, S.-F., Ahmad Butt, Z., P Morita, P., & Cruvinel, T.
Affiliations
  • University of Waterloo (CA)
  • Universidade de São Paulo (BR)
Corresponding author
Cruvinel, Thiago
Venue
Journal of Medical Internet Research
Published
2022-05-19
Volume
24
Issue
5
Pages
e37519
ISSN
1438-8871 (ISSN-L)
OpenAlex
W4224015395
Cited by
76
References
5
Citations by year
2026: 15 · 2025: 17 · 2024: 24 · 2023: 17 · 2022: 3
FWCI
21.94
Type
journal article
Language
en
Open access
Licence
cc-by
Locations
  • Journal of Medical Internet Research (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
Funders
Fundação de Amparo à Pesquisa do Estado de São Paulo (2019/, 2021/)
Topics
  • Social Sciences › Sociology and Political Science › Misinformation and Its Impacts
  • Social Sciences › Health › Social Media in Health Education
  • Health Sciences › Dentistry › Periodontics › Dental Health and Care Utilization
Keywords
Instagram, social media misinformation, political misinformation, fluoride toxicity, fluoridated water, dental caries prevention, engagement metrics, sentiment analysis, topic modeling, infodemiology
MeSH terms
Infodemiology, Communication, Dental Caries, Fluorides, Humans, Social Media

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