Exploring the factors driving higher interactions in false amber necklace posts on Facebook.

The consumption and sharing of information on social media contribute to the circulation of false health content. In this sense, popular belief-driven posts recommending the use of amber necklaces to prevent symptoms of teething can be easily found on social media, even when they offer health risks for children. Accordingly, this study aimed to characterize posts in Portuguese by identifying message-based factors associated with higher user interactions of Facebook. A total of 500 Facebook posts published in Portuguese between August 2016 and August 2021 were retrieved by CrowdTangle, and analyzed quantitatively according to time of publication, total user interaction, and post overperforming score, and then qualitatively by two independent investigators, according to motivation, authors' profiles, and sentiment. The data were evaluated by descriptive analysis, Mann-Whitney U test, chi-square test, and multiple logistic regression models regarding interaction metrics. The posts were published predominantly by commercial profiles, with social, psychological, and financial motivations, and expressed positive sentiment. Furthermore, time of publication (OR=2.65), regular user profiles (OR=3.30), and neutral/negative sentiment (OR=2.76) were associated positively with total interactions, whereas only time of publication was associated with post overperforming scores (OR=1.65). In conclusion, Facebook posts promoting efficacy of amber necklaces in managing teething symptoms are primarily created by commercial profiles with vested interests in marketing the product. The key factors that contribute to the success of posts containing false information about amber necklaces on Facebook can be identified by considering the author's profile, sentiment, and time of publication.

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.

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.

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.

Digital surveillance: The interest in mouthwash-related information.

BACKGROUND: The comprehension of the interests of Internet users regarding their health-related searches may reveal the community's demands about oral health. The study aimed to characterize the interests of Google users related to mouthwash in Australia, Brazil, Chile, Japan, Mexico, Russia, the United Kingdom, the United States, Saudi Arabia and South Africa applying the Google Trends. METHODS: This longitudinal retrospective study analysed the mouthwash-related interest of Google users from January 2004 to December 2020. The monthly variation of relative search volume (RSV) and the main queries related were determined using Google Trends. Autoregressive integrated moving average (ARIMA) forecasting models were built to establish the predictive RSV values for mouthwash for additional 12 months. Auto-correlation plots and a general additive model (GAM) were used to diagnose trends and seasonality in RSV curves. In addition, the influence of social isolation related to the outbreak of COVID-19 were analysed. RESULTS: The RSVs curves showed a considerable increase in searches related to mouthwash to AUS, BRA, JAP, MEX, GBR and USA (RSV > 25), while the growth was slight to CHI, KSA, RSA and RUS (RSV < 25) over the years, without influence of monthly seasonality. All countries showed a significant increase in mouthwash interest after the outbreak of COVID-19, except for KSA and RUS. The mouthwash-related searches were associated to specific brands or chemical compositions, treatments, whitening agents, homemade mouthwash and indications for the 'best mouthwash'. CONCLUSIONS: In general, there was an increasing interest of Google users in mouthwash-related topics between 2004 and 2020. In addition, in most countries, there was an expansion in searches during the social isolation of the COVID-19 pandemics.

Exploring the factors driving higher interactions in false amber necklace posts on Facebook

Abstract The consumption and sharing of information on social media contribute to the circulation of false health content. In this sense, popular belief-driven posts recommending the use of amber necklaces to prevent symptoms of teething can be easily found on social media, even when they offer health risks for children. Accordingly, this study aimed to characterize posts in Portuguese by identifying message-based factors associated with higher user interactions of Facebook. A total of 500 Facebook posts published in Portuguese between August 2016 and August 2021 were retrieved by CrowdTangle, and analyzed quantitatively according to time of publication, total user interaction, and post overperforming score, and then qualitatively by two independent investigators, according to motivation, authors' profiles, and sentiment. The data were evaluated by descriptive analysis, Mann-Whitney U test, chi-square test, and multiple logistic regression models regarding interaction metrics. The posts were published predominantly by commercial profiles, with social, psychological, and financial motivations, and expressed positive sentiment. Furthermore, time of publication (OR=2.65), regular user profiles (OR=3.30), and neutral/negative sentiment (OR=2.76) were associated positively with total interactions, whereas only time of publication was associated with post overperforming scores (OR=1.65). In conclusion, Facebook posts promoting efficacy of amber necklaces in managing teething symptoms are primarily created by commercial profiles with vested interests in marketing the product. The key factors that contribute to the success of posts containing false information about amber necklaces on Facebook can be identified by considering the author's profile, sentiment, and time of publication.

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.

Can heart rate variability data from the Apple Watch electrocardiogram quantify stress?

Chronic stress has become an epidemic with negative health risks including cardiovascular disease, hypertension, and diabetes. Traditional methods of stress measurement and monitoring typically relies on self-reporting. However, wearable smart technologies offer a novel strategy to continuously and non-invasively collect objective health data in the real-world. A novel electrocardiogram (ECG) feature has recently been introduced to the Apple Watch device. Interestingly, ECG data can be used to derive Heart Rate Variability (HRV) features commonly used in the identification of stress, suggesting that the Apple Watch ECG app could potentially be utilized as a simple, cost-effective, and minimally invasive tool to monitor individual stress levels. Here we collected ECG data using the Apple Watch from 36 health participants during their daily routines. Heart rate variability (HRV) features from the ECG were extracted and analyzed against self-reported stress questionnaires based on the DASS-21 questionnaire and a single-item LIKERT-type scale. Repeated measures ANOVA tests did not find any statistical significance. Spearman correlation found very weak correlations (p < 0.05) between several HRV features and each questionnaire. The results indicate that the Apple Watch ECG cannot be used for quantifying stress with traditional statistical methods, although future directions of research (e.g., use of additional parameters and Machine Learning) could potentially improve stress quantification with the device.

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.

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.

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.

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.

eHEALS as a predictive factor of digital health information seeking behavior among Brazilian undergraduate students.

This study aimed to perform the cross-cultural adaptation and validation of the eHealth Literacy Scale (eHEALS) for Brazilian Portuguese. The cross-cultural adaptation was conducted through conceptual equivalence, verbatim translation, semantic, item and operational equivalence, and back-translation. Subsequently, 521 undergraduate students answered the adapted version of the eHEALS, the General Perceived Self-Efficacy Scale (GSES), the Oral Health Impact Profile-14 (OHIP-14) and sociodemographic and health-related questions. Statistical analysis was performed to determine the dimensionality, internal consistency, stability and concurrent/convergent/discriminant/predictive validities of the eHEALS (p < 0.05). The adequacy of sample size was confirmed by a non-identity correlation matrix (Bartlett's test of sphericity, p < 0.001), without influence of multicollinearity (determinant = 0.026). The confirmatory factor analysis identified four factors in agreement to the constructs namely as online searching self-efficacy, awareness of available sources, information usage ability, and critical analysis of useful information. The eHEALS displayed an excellent internal consistency (Cronbach's alpha = 0.88), a good stability (ICC = 0.71, 95% CI: 0.49-0.84), and it was significantly correlated with GSES (concurrent validity). Higher eHEALS scores were identified among (i) white and (ii) younger students, (iii) from health sciences courses, (iv) with more years of graduation, (v) who their fathers were working in specialized functions (discriminant validity), and (vi) among those who were frequently interested in digital health information (convergent validity). The students with higher eHealth literacy levels were more likely to seek health information in the last 24 h (predictive validity). In conclusion, the eHEALS demonstrated adequate psychometric properties to be applied for the Brazilian population.

The eHealth Literacy Scale (eHEALS) is a self-fulfilling tool designed to determine individuals' levels of electronic health literacy. It helps to determine how people deal with electronic health-related information, being useful to identify potential difficulties of accessing, evaluating and using online health information, with potential to support the planning of educational interventions. This study aimed to adapt and validate the eHealth Literacy Scale (eHEALS) for being applied to Brazilian Portuguese native speakers. Five hundred twenty-one undergraduate students answered the adapted version of the eHEALS, the General Perceived Self-Efficacy Scale (GSES), the Oral Health Impact Profile-14 (OHIP-14), and sociodemographic and health-related questions. The tool showed sufficient consistency and stability, with the detection of higher eHEALS scores among white and younger people who reported a frequent interest for seeking digital health information, students from health sciences courses, those with more years of graduation, and who their fathers were working in specialized functions. Also, the students with higher eHealth literacy scores were more likely to seek health information in the last 24 h. In conclusion, the eHEALS demonstrated being adequate to be applied for the Brazilian population.

Toothpaste-related interests of Google users from different countries

Abstract 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.

Exploring online oral health misinformation: a content analysis

Abstract 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.

Psychophysiological Reactions of Internet Users Exposed to Fluoride Information and Disinformation: Protocol for a Randomized Controlled Trial.

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.

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

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.

Digital surveillance: Monitoring the activity of Internet users searching for information related to early childhood caries.

This study evaluated the behavior of Internet users from seven countries through the analysis of the monthly variation of the Relative Search Volume (RSV) for queries related to early childhood caries (ECC), retrieved by Google Trends application programming interface between January 2004 to December 2020. The association of RSV with years lived with disability (YLDs) for untreated dental caries in deciduous teeth and Internet penetration were tested by regression models. Forecasting models were developed to predict the interests until December 2021. Relevant topics linked to searches were assessed qualitatively. Increasing levels of interests were observed in most countries, regarding the comparison of periods 2004-2012 and 2013-2021, without influence of seasonality. These results were associated with YLDs only in France and with the Internet penetration in Mexico and France. Searches were mostly related to the definition, risk factors, and preventive care of ECC. The interests of Internet users in ECC-related information increased in the last years in all seven countries, although it was maintained low over time. It might indicate a lack of awareness about the negative consequences of the disease in the early stages of life. Specific policies should be developed toward the dissemination of oral health information and the prevention of the disease.