Characterization of misleading fluoride information on Instagram: An infodemiology study (Preprint)

Oral cancer: analysis of the clarity of publications in Instagram profiles of official health agencies in Brazil

This article aims to analyze the clarity and engagement measures of publications on oral cancer in the Instagram profiles of official health agencies in Brazil. An infodemiological study was conducted with 81 profiles. Data collected concerned content classification, account and media, manner of addressing the topic, number of posts, likes, comments, views and hashtags. The clarity of the educational publications was assessed with the Brazilian version of the Clear Communication Index (BR-CDC-CCI). Data analysis involved Spearman's correlation and the Mann-Whitney test (α = 5%). A total of 775 publications on oral cancer were found. The average BR-CDC-CCI score was 69.8 (SD = 15.5). The clarity of the information was adequate in 9.5% of the educational publications. Positive correlations were found between the number of likes and engagement (comments [r = 0.49], views [r = 0.96]), number of hashtags (r = 0.13) and year of publication (r = 0.21). Publications from the Health Ministry had a significantly higher BR-CDC-CCI score compared to the other profiles. Publications on oral cancer were correlated with engagement, year of publication and number of hashtags. Public agencies increased publications to reach the population, but the clarity of the content was low.

Should we be concerned about the use of non-fluoride toothpaste? A survey study in two European countries

BACKGROUND

Toothpastes available in Europe contain a range of fluoride concentrations, with some meeting the recommended level for caries prevention (>1000 ppm fluoride (ppm)) and others containing low or no fluoride. This study evaluated toothpaste fluoride concentrations in Latvia and Lithuania to inform targeted public health strategies in regions with a high prevalence of dental caries.

METHODS

This cross-sectional study was conducted from May 2019 to May 2020, using a validated questionnaire in Latvia and Lithuania. Nationally representative samples (1309 families and 5436 members) provided data through a mixed-mode survey (paper and online) on sociodemographic information, toothpaste type, brand, and type. Descriptive statistics and chi-square tests (p < 0.05) were used for analysis.

RESULTS

Fifteen percent of families used non-fluoridated toothpaste and 12% used <1000 part per million (ppm) fluoride. In Latvia, 56.8% of preschoolers and 28.7% of schoolchildren used <1000 ppm or non-fluoride toothpaste, whereas in Lithuania, 47.2% of preschoolers and 29.1% of schoolchildren used <1000 ppm or non-fluoride toothpaste; 63% of adolescents and 73% of adults used toothpaste with optimal fluoride content (≥1000 ppm). Of the 228 registered toothpaste types, 62% contained more than 1000 ppm, which is optimal for caries prevention; 29% of Latvian and 24% of Lithuanian families used at least one non-fluoridated toothpaste.

CONCLUSION

This study revealed significant gaps in the use of fluoride toothpaste among families in Latvia and Lithuania, especially among children. To effectively prevent dental caries, targeted interventions, and education must promote optimal fluoride toothpaste use, particularly among vulnerable populations.

Online Health Search Via Multidimensional Information Quality Assessment Based on Deep Language Models: Algorithm Development and Validation

BACKGROUND

Widespread misinformation in web resources can lead to serious implications for individuals seeking health advice. Despite that, information retrieval models are often focused only on the query-document relevance dimension to rank results.

OBJECTIVE

We investigate a multidimensional information quality retrieval model based on deep learning to enhance the effectiveness of online health care information search results.

METHODS

In this study, we simulated online health information search scenarios with a topic set of 32 different health-related inquiries and a corpus containing 1 billion web documents from the April 2019 snapshot of Common Crawl. Using state-of-the-art pretrained language models, we assessed the quality of the retrieved documents according to their usefulness, supportiveness, and credibility dimensions for a given search query on 6030 human-annotated, query-document pairs. We evaluated this approach using transfer learning and more specific domain adaptation techniques.

RESULTS

In the transfer learning setting, the usefulness model provided the largest distinction between help- and harm-compatible documents, with a difference of +5.6%, leading to a majority of helpful documents in the top 10 retrieved. The supportiveness model achieved the best harm compatibility (+2.4%), while the combination of usefulness, supportiveness, and credibility models achieved the largest distinction between help- and harm-compatibility on helpful topics (+16.9%). In the domain adaptation setting, the linear combination of different models showed robust performance, with help-harm compatibility above +4.4% for all dimensions and going as high as +6.8%.

CONCLUSIONS

These results suggest that integrating automatic ranking models created for specific information quality dimensions can increase the effectiveness of health-related information retrieval. Thus, our approach could be used to enhance searches made by individuals seeking online health information.

Unveiling deception: Characterizing false amber necklace messages on Facebook

BACKGROUND

Messages promoting the benefits of amber necklaces for children are common on social media, despite their health risks.

AIM

This study characterized Facebook posts with false content about the efficacy of amber necklaces in teething.

DESIGN

A sample of 500 English-language Facebook posts was analyzed by two investigators to determine the motivations, author's profile, and sentiments of posts. Latent Dirichlet Allocation topic modeling was used to identify salient terms and topics. An intertopic distance map was created to calculate the topic similarity. These data were analyzed using descriptive analysis, the Mann-Whitney U test, Cramer's V test, and multiple logistic regression models, regarding the time since initial posting and interaction metrics.

RESULTS

Most posts were made by business profiles and expressed positive sentiments, with social, psychological, and financial motivations. The posts were categorized into the topics "giveaway," "healing features," and "sales." Overperforming scores and total interaction increased with time since the initial posting. Posts with links had higher overperforming scores.

CONCLUSION

The findings suggest that Facebook posts about the efficacy of amber necklaces in teething are motivated by financial interests, using psychological and social mechanisms to achieve greater interaction with their target audience.

Uncovering a pseudoscience: an analysis of 'biological dentistry' Instagram posts

OBJECTIVE

This infodemiology study aimed to analyze characteristics of English-language Instagram posts on 'Biological Dentistry'.

MATERIALS AND METHODS

Using CrowdTangle, we analyzed 500 'Biological Dentistry' posts published on Instagram from May 2017 to May 2022. Two researchers assessed each post for facticity, motivation, author's profile, sentiment, and interaction metrics. Statistical analysis was employed to compare interaction metrics between dichotomized categories of posts' characteristics and determine predictors of misinformation and user engagement.

RESULTS

Over half of the posts (58.4%) were from health-related authors, and a considerable number contained misinformation (68.2%) or were financially motivated (52%). Sentiment was mostly negative or neutral (59.8%). Misinformation was associated with financial motivation (OR = 2.12) and health-related authors (OR = 5.56), while non-health-related authors' posts associated with higher engagement (OR = 1.98). Reliable content, non-health-related authorship, and positive sentiment were associated with increased user interaction.

CONCLUSION

Misinformation about 'Biological Dentistry' on Instagram is mainly spread by financially incentivized health-related authors. Yet, non-health-related authors' posts resonate more with audiences, highlighting a nuanced relationship between content facticity, authorship, and engagement.

Determinants of multimodal fake review generation in China's E-commerce platforms

This paper develops a theoretical model of determinants influencing multimodal fake review generation using the theories of signaling, actor-network, motivation, and human-environment interaction hypothesis. Applying survey data from users of China's three leading E-commerce platforms (Taobao, Jingdong, and Pinduoduo), we adopt structural equation modeling, machine learning technique, and Bayesian complex networks analysis to perform factor identification, path analysis, feature factor importance ranking, regime division, and network centrality analysis of full sample, male sample, and female sample to reach the following conclusions: (1) platforms' multimodal recognition and governance capabilities exert significant negative moderating effects on merchants' information behavior, while it shows no apparent moderating effect on users' information behavior; users' emotional venting, perceived value, reward mechanisms, and subjective norms positively influence multimodal fake review generation through perceptual behavior control; (2) feature factors of multimodal fake review generation can be divided into four regimes, i.e., regime 1 includes reward mechanisms and perceived social costs, indicating they are key feature factors of multimodal fake review generation; merchant perception impact is positioned in regime 2, signifying its pivotal role in multimodal fake review generation; regime 3 includes multimodal recognition and governance capabilities, supporting/disparaging merchants, and emotional venting; whereas user perception impact is positioned in regime 4, indicating its weaker influence on multimodal fake review generation; (3) both in full sample, male sample, and female sample, reward mechanisms play a crucial role in multimodal fake review generation; perceived value, hiring review control agency, multimodal recognition and governance capabilities exhibit a high degree of correlation; however, results of network centrality analysis also exhibit heterogeneity between male and female samples, i.e., male sample has different trends in closeness centrality values and betweenness centrality values than female sample. This indicates that determinants influencing multimodal fake review generation are complex and interconnected.

Dental Practice Websites in Germany-How Do They Inform about Fluoridation?

Fluoridation (Fl) is effective in preventing caries; however, it is unclear to what extent its use is counteracted by misinformation on the internet. This study aimed to evaluate the information provided on professional websites of German dental practices regarding fluoridation. A systematic search was performed by two independent examiners, utilizing three search engines, from 10 September 2021 to 11 December 2021. Modified, validated questionnaires (LIDA, DISCERN) were used to evaluate technical and functional aspects, generic quality, and risk of bias. Demographic information and statements about Fl were also collected. The intra- and inter-rater reliability assessments were excellent. Of the 81 websites analyzed, 64 (79%) mentioned Fl, and 31 (38%) indicated it as a primary focus. Most websites met at least 50% of the LIDA (90%) and DISCERN criteria (99%), indicating that the general quality was good. Thirty (37%) of the websites explained the impact of Fl, and forty-five (56%) indicated an opinion (for/against) on Fl. The practice location and the clinical focus were not associated with the overall quality of websites. Only a minority of websites explained the effects of Fl. Taken together, this study highlights that there is a distinct lack of good-quality information on FL.

Exploring How People Interact With Dental Misinformation on Social Media: A Cross-Sectional Study

BACKGROUND

Social media has been widely utilized to spread health-related information, which has led to the possibility of spreading medical misinformation. The extent of the issue is unknown, even though policymakers, researchers, and medical professionals agree that health misinformation must be controlled and combated.

OBJECTIVE

A cross-sectional study was conducted by the faculty of dentistry at Damascus University.

METHODS

This quantitative cross-sectional study used a voluntary questionnaire distributed online in social media groups. Participants were of different ages, genders, and educational levels.

RESULTS

Of the 301 questionnaires collected, 291 were analyzed. The study sample comprised secondary education certificates, university students, and postgraduate students. 96.6% of the study sample used two or more SM applications. 71.5% of the study sample uses Facebook more than other applications for dental information research, followed by Instagram (14.8%), Telegram (8.2%), and finally WhatsApp (5.5%). There was a significant difference between the age of the respondents and the SM application they used most (p = 0.027). 46.4% of the study sample were neutral in their answer about what they believed in the trust of information on SM sites, followed by 42.3% who did not agree with the trust of information on SM sites and 11.3 who agreed. 89.7% of the study sample visit the dentist when facing a medical problem, while 10.3% follow advice on SM sites. There was a significant difference between the age of respondents and the source they relied on when facing a medical problem (p = 0.019). 50.2% of the study sample sometimes feels that the advice on SM sites is marketing for a company or product or advertising for doctors and not others.

CONCLUSION

In particular, understanding the methods and prevalence of health misinformation, as well as the current gaps in knowledge in this area, will help us to guide future research and, more specifically, to develop evidence-based digital policy action plans targeted at addressing this public health issue through various social media platforms.

What is the impact of artificial intelligence-based chatbots on infodemic management?

Artificial intelligence (AI) chatbots have the potential to revolutionize online health information-seeking behavior by delivering up-to-date information on a wide range of health topics. They generate personalized responses to user queries through their ability to process extensive amounts of text, analyze trends, and generate natural language responses. Chatbots can manage infodemic by debunking online health misinformation on a large scale. Nevertheless, system accuracy remains technically challenging. Chatbots require training on diverse and representative datasets, security to protect against malicious actors, and updates to keep up-to-date on scientific progress. Therefore, although AI chatbots hold significant potential in assisting infodemic management, it is essential to approach their outputs with caution due to their current limitations.

Cross-cultural adaptation of the Digital Health Literacy Instrument (DHLI) for use on Brazilian adolescents

The present study aimed to perform the cross-cultural adaptation of the Digital Health Literacy Instrument (DHLI) for native Brazilian Portuguese-speaking adolescents (DHLI-BrA). Cross-cultural adaptation consisted of the following steps: translation, assessment, and adjustments by the expert committee to ensure cultural equivalence; back-translation, and synthesis of back-translations. Cognitive testing was then performed in a pretest with adolescents using cognitive interviews with probing questions on the item's understanding interpretation and response options. Cronbach's alpha coefficient and McDonald's omega were used to estimate the instrument's reliability. Forty-two Brazilian adolescents participated in the study (mean age: 16.0 ± 2.0 years; range: 13 to 19 years). Items that were difficult to understand were adapted to the context of Brazilian adolescents. Cronbach's alpha coefficient and McDonald's omega for the 21 items of the DHLI-BrA were, respectively, 0.79 and 0.80. Cronbach's alpha coefficient for the subscales of the self-report instrument was 0.53-0.79 (range), demonstrating good reliability in the total instrument and moderate reliability in the subscales. This study provides the cross-cultural adapted version of the Digital Health Literacy Instrument (DHLI), which is an instrument for measuring digital Health literacy, for use in Brazilian adolescents (DHLI-BrA).

Toothpaste-related interests of Google users from different countries

The Internet is a growing source of knowledge and can provide information about oral health. This ecological study aimed to characterize the interests in toothpaste among Google users from different countries. Our hypothesis was that there would be an increase in Google users' interest in information about toothpaste. This retrospective longitudinal ecological study analyzed the toothpaste-related interest of Google users from 10 countries between January 2004 and December 2020. The monthly variation in relative search volume (RSV) and the main related queries were determined using Google Trends. Autoregressive integrated moving average (ARIMA) forecasting models were built to establish the predictive RSV values for toothpaste for an additional 12 months. Autocorrelation plots and the generalized additive model (GAM) were used to diagnose trends and seasonality in RSV curves. Additionally, the influence of social isolation related to the outbreak of COVID-19 was analyzed. Although not detected by autocorrelation function (ACF) and partial autocorrelation function (PACF) analyses, the heuristic analysis showed an increase in the interest in toothpaste-related information in all countries, with a stable trend observed in the 12-month forecasts, except for the increases in the United Kingdom and South Africa. Also, GAM analyses demonstrated a non-significant monthly or quarterly seasonal influence on data. In addition, social isolation during the COVID-19 pandemic did not influence the online information-seeking behavior of Google Search users linked to this topic. We confirmed the hypothesis that the interest of Google Search users in information about toothpaste increased in all of the 10 assessed countries.

Decoding early childhood caries: an in-depth analysis of YouTube videos for effective parental education

PURPOSE

To assess the coverage of information about early childhood caries (ECC) available on YouTube videos in three different languages, regarding technical characteristics of videos and interaction metrics.

METHODS

Search strategies were developed in English, Spanish, and Portuguese to make a comprehensive collection of videos from YouTube, encompassing 60 samples for each language, regarding all video types. The videos were assessed by a thematic checklist regarding 17 items on ECC. Videos were dichotomized according to the median of the thematic score and the nature of their authorship (health and non-health authors) to compare groups. The statistical analysis was performed using the Statistical Package for Social Science (version 25.0), applying Spearman's rank correlation coefficient and Mann-Whitney U test. P < 0.05 values were considered significant.

RESULTS

Among 120 videos meeting inclusion criteria, ECC aetiology and prevention information proved incomplete, with a median score of 5 (Q1-Q3 = 3-7). No correlation emerged between this score and other video characteristics. However, interaction metrics like views, likes, dislikes, and viewing rates displayed significant correlations. Health authors primarily created these videos, yet non-health author channels had more subscribers. Surprisingly, videos focused on the impact of regular sugary food and beverage consumption on ECC progression received the most attention.

CONCLUSIONS

Videos that presented information about the aetiology and prevention of ECC invariably focused on partial aspects of the disease. This highlights the need for better-quality educational videos and the importance of dental professionals in guiding patients toward reliable sources of information.

Clarity of publications on HPV in Instagram profiles of official health agencies in Brazil

The study analyzed the clarity of publications on human papillomavirus (HPV) in the Instagram profiles of official Brazilian health agencies. An infodemiological study analyzed publications on HPV in the 81 Instagram profiles selected from the Health Ministry, States' Health Departments, and dental councils and associations. The following data were collected: classification of content, type of profiles, type of media, how the content was addressed, number of posts, frequency, likes, comments, viewings, and hashtags, and how the HPV vaccine was addressed. The clarity of the educational publications was assessed using the Brazilian version of the Clear Communication Index (BR-CDC-CCI). Data analysis was performed with Spearman's correlation and the Mann-Whitney test (p < 0.05). A total of 504 publications on HPV were found. The average number of likes was 528.3 (SD = 2388.2) and the average BR-CDC-CCI score was 67.1 (SD = 14.1). The quality and clarity of the information was considered adequate (BR-CDC-CCI score ≥ 90) in 6.9% of the publications. A weak positive correlation was found between the number of likes and both the BR-CDC-CCI score (r = 0.195) and number of posts (r = 0.124). Publications from the Health Ministry had a significantly higher BR-CDC-CCI score (72.9) compared to the other profiles analyzed (p = 0.01). Most publications concerned government actions, had low engagement, and written educational information was of low clarity and quality. However, the effort to reach the population was evident, with an increase in publications over the years.

Fluoride hesitancy: A mixed methods study on decision-making about forms of fluoride

OBJECTIVES

To investigate whether professionally applied topical fluoride-hesitant caregivers are also hesitant about other forms of fluoride for their child.

METHODS

This was a mixed methods study of 56 caregivers hesitant about professionally applied topical fluoride for their child recruited from the University of Washington Center for Paediatric Dentistry and Seattle Children's Hospital's Odessa Brown Children's Dental Clinic. A 32-item semi-structured interview script was piloted and finalized. One-time interviews with caregivers were conducted by phone in 2019. Associations between hesitancy of topical fluoride, fluoridated water and toothpaste were assessed quantitatively via two-tailed chi-squared tests. Qualitative data were coded using an inductive approach and content analytic methods to investigate reasons for hesitancy.

RESULTS

There were significant associations between hesitancy in all three pairwise comparisons of fluoride form (p < .01). Similar proportions of caregivers strongly or somewhat opposed fluoridated water compared with toothpaste (75% and 65%, respectively), but four times as many caregivers strongly or somewhat favoured fluoridated toothpaste compared to water for their child (25% and 7%, respectively). Concerns about harm were the most common reason caregivers opposed both fluoridated water and toothpaste. However, fluoride-hesitant caregivers reported being more comfortable with fluoridated toothpaste because amount and frequency can be controlled, and ingestion can be prevented.

CONCLUSIONS

Professionally applied topical fluoride hesitancy is significantly associated with fluoridated water and toothpaste hesitancy, but caregivers who were hesitant about topical fluoride was more comfortable with fluoridated toothpaste than fluoridated water for their child.

The "Loci" of Misinformation and Its Correction in Peer- and Expert-Led Online Communities for Mental Health: Content Analysis

BACKGROUND

Mental health problems are recognized as a pressing public health issue, and an increasing number of individuals are turning to online communities for mental health to search for information and support. Although these virtual platforms have the potential to provide emotional support and access to anecdotal experiences, they can also present users with large amounts of potentially inaccurate information. Despite the importance of this issue, limited research has been conducted, especially on the differences that might emerge due to the type of content moderation of online communities: peer-led or expert-led.

OBJECTIVE

We aim to fill this gap by examining the prevalence, the communicative context, and the persistence of mental health misinformation on Facebook online communities for mental health, with a focus on understanding the mechanisms that enable effective correction of inaccurate information and differences between expert-led and peer-led groups.

METHODS

We conducted a content analysis of 1534 statements (from 144 threads) in 2 Italian-speaking Facebook groups.

RESULTS

The study found that an alarming number of comments (26.1%) contained medically inaccurate information. Furthermore, nearly 60% of the threads presented at least one misinformation statement without any correction attempt. Moderators were more likely to correct misinformation than members; however, they were not immune to posting content containing misinformation, which was an unexpected finding. Discussions about aspects of treatment (including side effects or treatment interruption) significantly increased the probability of encountering misinformation. Additionally, the study found that misinformation produced in the comments of a thread, rather than as the first post, had a lower probability of being corrected, particularly in peer-led communities.

CONCLUSIONS

The high prevalence of misinformation in online communities, particularly when left uncorrected, underscores the importance of conducting additional research to identify effective mechanisms to prevent its spread. This is especially important given the study's finding that misinformation tends to be more prevalent around specific "loci" of discussion that, once identified, can serve as a starting point to develop strategies for preventing and correcting misinformation within them.

Analysis of Fluoride-Free Content on Twitter: Topic Modeling Study

BACKGROUND

Although social media has the potential to spread misinformation, it can also be a valuable tool for elucidating the social factors that contribute to the onset of negative beliefs. As a result, data mining has become a widely used technique in infodemiology and infoveillance research to combat misinformation effects. On the other hand, there is a lack of studies that specifically aim to investigate misinformation about fluoride on Twitter. Web-based individual concerns on the side effects of fluoridated oral care products and tap water stimulate the emergence and propagation of convictions that boost antifluoridation activism. In this sense, a previous content analysis-driven study demonstrated that the term fluoride-free was frequently associated with antifluoridation interests.

OBJECTIVE

This study aimed to analyze "fluoride-free" tweets regarding their topics and frequency of publication over time.

METHODS

A total of 21,169 tweets published in English between May 2016 and May 2022 that included the keyword "fluoride-free" were retrieved by the Twitter application programming interface. Latent Dirichlet allocation (LDA) topic modeling was applied to identify the salient terms and topics. The similarity between topics was calculated through an intertopic distance map. Moreover, an investigator manually assessed a sample of tweets depicting each of the most representative word groups that determined specific issues. Lastly, additional data visualization was performed regarding the total count of each topic of fluoride-free record and its relevance over time, using Elastic Stack software.

RESULTS

We identified 3 issues by applying the LDA topic modeling: "healthy lifestyle" (topic 1), "consumption of natural/organic oral care products" (topic 2), and "recommendations for using fluoride-free products/measures" (topic 3). Topic 1 was related to users' concerns about leading a healthier lifestyle and the potential impacts of fluoride consumption, including its hypothetical toxicity. Complementarily, topic 2 was associated with users' personal interests and perceptions of consuming natural and organic fluoride-free oral care products, whereas topic 3 was linked to users' recommendations for using fluoride-free products (eg, switching from fluoridated toothpaste to fluoride-free alternatives) and measures (eg, consuming unfluoridated bottled water instead of fluoridated tap water), comprising the propaganda of dental products. Additionally, the count of tweets on fluoride-free content decreased between 2016 and 2019 but increased again from 2020 onward.

CONCLUSIONS

Public concerns toward a healthy lifestyle, including the adoption of natural and organic cosmetics, seem to be the main motivation of the recent increase of "fluoride-free" tweets, which can be boosted by the propagation of fluoride falsehoods on the web. Therefore, public health authorities, health professionals, and legislators should be aware of the spread of fluoride-free content on social media to create and implement strategies against their potential health damage for the population.

Tweeting for Health Using Real-time Mining and Artificial Intelligence-Based Analytics: Design and Development of a Big Data Ecosystem for Detecting and Analyzing Misinformation on Twitter

BACKGROUND

Digital misinformation, primarily on social media, has led to harmful and costly beliefs in the general population. Notably, these beliefs have resulted in public health crises to the detriment of governments worldwide and their citizens. However, public health officials need access to a comprehensive system capable of mining and analyzing large volumes of social media data in real time.

OBJECTIVE

This study aimed to design and develop a big data pipeline and ecosystem (UbiLab Misinformation Analysis System [U-MAS]) to identify and analyze false or misleading information disseminated via social media on a certain topic or set of related topics.

METHODS

U-MAS is a platform-independent ecosystem developed in Python that leverages the Twitter V2 application programming interface and the Elastic Stack. The U-MAS expert system has 5 major components: data extraction framework, latent Dirichlet allocation (LDA) topic model, sentiment analyzer, misinformation classification model, and Elastic Cloud deployment (indexing of data and visualizations). The data extraction framework queries the data through the Twitter V2 application programming interface, with queries identified by public health experts. The LDA topic model, sentiment analyzer, and misinformation classification model are independently trained using a small, expert-validated subset of the extracted data. These models are then incorporated into U-MAS to analyze and classify the remaining data. Finally, the analyzed data are loaded into an index in the Elastic Cloud deployment and can then be presented on dashboards with advanced visualizations and analytics pertinent to infodemiology and infoveillance analysis.

RESULTS

U-MAS performed efficiently and accurately. Independent investigators have successfully used the system to extract significant insights into a fluoride-related health misinformation use case (2016 to 2021). The system is currently used for a vaccine hesitancy use case (2007 to 2022) and a heat wave-related illnesses use case (2011 to 2022). Each component in the system for the fluoride misinformation use case performed as expected. The data extraction framework handles large amounts of data within short periods. The LDA topic models achieved relatively high coherence values (0.54), and the predicted topics were accurate and befitting to the data. The sentiment analyzer performed at a correlation coefficient of 0.72 but could be improved in further iterations. The misinformation classifier attained a satisfactory correlation coefficient of 0.82 against expert-validated data. Moreover, the output dashboard and analytics hosted on the Elastic Cloud deployment are intuitive for researchers without a technical background and comprehensive in their visualization and analytics capabilities. In fact, the investigators of the fluoride misinformation use case have successfully used the system to extract interesting and important insights into public health, which have been published separately.

CONCLUSIONS

The novel U-MAS pipeline has the potential to detect and analyze misleading information related to a particular topic or set of related topics.

Exploring online oral health misinformation: a content analysis

Considering the unfavorable implications of health falsehoods and the lack of dental research into information disorder, this study aimed to identify and characterize online oral health misinformation. A total of 410 websites published in English were retrieved using Google Advanced Search and screened by two independent investigators to compile falsehoods through thematic content analysis. Afterward, 318 pieces of misinformation were consensually divided into four groups concerning their informational interest (G1), financial, psychological, and social interests produced/disseminated by non-dental professionals (G2) or by dental professionals (G3), and political interests (G4). Social media (Facebook and Instagram) and fact-checking tool (Snopes) were also screened to determine the spread of falsehoods by identifying corresponding posts and warnings. As a result, misinformation was mainly associated with gum diseases (12.0%), root canal treatment (11.6%), toothache (10.4%), fluoride (10.4%), and dental caries (9.8%), with a special highlight on recommendations for the usage of natural products, toxicity concerns, and anti-fluoridation propaganda. Additionally, most misinformation was allocated in G3 (41.9%), which presented a statistically higher frequency of financial interests than G4. Finally, falsehoods were considerably identified on Facebook (62.9%) and Instagram (49.4%), especially G3 and G4. Nevertheless, Snopes has debunked only 5.9% of these content items. Therefore, misinformation was predominantly produced or disseminated by dental professionals mainly motivated by financial interests and usually linked to alternative/natural treatments. Although these items were shared on social media, fact-checking agencies seemed to have limited knowledge about their dissemination.

Reacting, Sharing, and Commenting: How Many Facebook Users Are Engaging with Posts Related to Dental Caries That Contain Misinformation?

Recent studies have been concerned about the vast amount of misinformation detected on social media that directly hampers the prevention and control of chronic diseases. Based on these facts, the aim of this study was to identify and characterize misinformation about dental caries-related content found on Facebook, regarding the predictive factors of user interaction with posts. Then, CrowdTangle retrieved 2,436 posts published in English, ordered by the total interaction of the highest users. A total of 1,936 posts were selected for inclusion and exclusion criteria to select a sample of 500 posts. Subsequently, two independent investigators characterized the posts by their time of publication, author's profile, motivation, the aim of content, content facticity, and sentiment. The statistical analysis was performed using Mann-Whitney U and χ2 tests and multiple logistic regression models to determine differences and associations between dichotomized characteristics. p values <0.05 were considered significant. In general, posts were predominantly originated from the USA (74.8%), related to business profiles (89%), presented preventive content (58.6%), and noncommercial motivation (91.6%). Furthermore, misinformation was detected in 40.8% of the posts and was positively associated with positive sentiment (OR = 3.43), business profile (OR = 2.22), and treatment of dental caries (OR = 1.60). While the total interaction was only positively associated with misinformation (OR = 1.44), the overperforming score was associated with posts from the business profile (OR = 5.67), older publications (OR = 1.57), and positive sentiment (OR = 0.66). In conclusion, misinformation was the unique predictive factor of increased user interaction with dental caries-related posts on Facebook. However, it did not predict the performance of the diffusion of posts such as business profiles, older publications, and negative/neutral sentiment. Therefore, it is essential to promote the development of specific policies toward good quality information on social media, which includes the production of adequate materials, the increase of the critical sense of consuming health content, and information filtering mediated by digital solutions.

Social Media Use Among Parents and Women of Childbearing Age in the US

Many parents and pregnant women in the US use social media to access health-related information. Estimates of current use of different platforms among these populations are needed. We used data from a 2021 Pew Research Center survey to describe use of commercial social media platforms by US parents and US women aged 18 to 39 years. Most US parents and women of childbearing age use YouTube, Facebook, and Instagram, with most engaging daily. Understanding social media use patterns can help public health professionals, health care systems, and researchers reach selected populations with evidence-based health information and health promotion programs.

Ethical principles for infodemiology and infoveillance studies concerning infodemic management on social media

Big data originating from user interactions on social media play an essential role in infodemiology and infoveillance outcomes, supporting the planning and implementation of public health actions. Notably, the extrapolation of these data requires an awareness of different ethical elements. Previous studies have investigated and discussed the adoption of conventional ethical approaches in the contemporary public health digital surveillance space. However, there is a lack of specific ethical guidelines to orient infodemiology and infoveillance studies concerning infodemic on social media, making it challenging to design digital strategies to combat this phenomenon. Hence, it is necessary to explore if traditional ethical pillars can support digital purposes or whether new ones must be proposed since we are confronted with a complex online misinformation scenario. Therefore, this perspective provides an overview of the current scenario of ethics-related issues of infodemiology and infoveillance on social media for infodemic studies.

Psychophysiological reactions of Internet users exposed to fluoride information and disinformation: Protocol for a randomized controlled trial (Preprint)

Background

False messages on the internet continually propagate possible adverse effects of fluoridated oral care products and water, despite their essential role in preventing and controlling dental caries.

Objective

This study aims to evaluate the patterns of psychophysiological reactions of adults after the consumption of internet-based fluoride-related information and disinformation.

Methods

A 2-armed, single-blinded, parallel, and randomized controlled trial will be conducted with 58 parents or caregivers of children who attend the Clinics of Pediatric Dentistry at the Bauru School of Dentistry, considering an attrition of 10% and a significance level of 5%. The participants will be randomized into test and intervention groups, being respectively exposed to fluoride-related information and disinformation presented on a computer with simultaneous monitoring of their psychophysiological reactions, including analysis of their heart rates (HRs) and 7 facial features (mouth outer, mouth corner, eye area, eyebrow activity, face area, face motion, and facial center of mass). Then, participants will respond to questions about the utility and truthfulness of content, their emotional state after the experiment, eHealth literacy, oral health knowledge, and socioeconomic characteristics. The Shapiro-Wilk and Levene tests will be used to determine the normality and homogeneity of the data, which could lead to further statistical analyses for elucidating significant differences between groups, using parametric (Student t test) or nonparametric (Mann-Whitney U test) analyses. Moreover, multiple logistic regression models will be developed to evaluate the association of distinct variables with the psychophysiological aspects. Only factors with significant Wald statistics in the simple analysis will be included in the multiple models (P<.2). Furthermore, receiver operating characteristic curve analysis will be performed to determine the accuracy of the remote HR with respect to the measured HR. For all analyses, P<.05 will be considered significant.

Results

From June 2022, parents and caregivers who frequent the Clinics of Pediatric Dentistry at the Bauru School of Dentistry will be invited to participate in the study and will be randomized into 1 of the 2 groups (control or intervention). Data collection is expected to be completed in December 2023. Subsequently, the authors will analyze the data and publish the findings of the clinical trial by June 2024.

Conclusions

This randomized controlled trial aims to elucidate differences between psychophysiological patterns of adults exposed to true or false oral health content. This evidence may support the development of further studies and digital strategies, such as neural network models to automatically detect disinformation available on the internet.

Trial Registration

Brazilian Clinical Trials Registry (RBR-7q4ymr2) U1111-1263-8227; https://tinyurl.com/2kf73t3d

International Registered Report Identifier (IRRID)

PRR1-10.2196/39133