%0 Journal Article %@ 2561-326X %I JMIR Publications %V 9 %N %P e59687 %T COVID-19 Public Health Communication on X (Formerly Twitter): Cross-Sectional Study of Message Type, Sentiment, and Source %A Parveen,Sana %A Pereira,Agustin Garcia %A Garzon-Orjuela,Nathaly %A McHugh,Patricia %A Surendran,Aswathi %A Vornhagen,Heike %A Vellinga,Akke %K public health communication %K surveillance %K COVID-19 %K SARS-CoV-2 %K coronavirus %K respiratory %K infectious %K pulmonary %K pandemic %K public health messaging %K healthcare information %K social media %K tweets %K text mining %K data mining %K social marketing %K infoveillance %K intervention planning %D 2025 %7 19.3.2025 %9 %J JMIR Form Res %G English %X Background: Social media can be used to quickly disseminate focused public health messages, increasing message reach and interaction with the public. Social media can also be an indicator of people’s emotions and concerns. Social media data text mining can be used for disease forecasting and understanding public awareness of health-related concerns. Limited studies explore the impact of type, sentiment and source of tweets on engagement. Thus, it is crucial to research how the general public reacts to various kinds of messages from different sources. Objective: The objective of this paper was to determine the association between message type, user (source) and sentiment of tweets and public engagement during the COVID-19 pandemic. Methods: For this study, 867,485 tweets were extracted from January 1, 2020 to March 31, 2022 from Ireland and the United Kingdom. A 4-step analytical process was undertaken, encompassing sentiment analysis, bio-classification (user), message classification and statistical analysis. A combination of manual content analysis with abductive coding and machine learning models were used to categorize sentiment, user category and message type for every tweet. A zero-inflated negative binomial model was applied to explore the most engaging content mix. Results: Our analysis resulted in 12 user categories, 6 message categories, and 3 sentiment classes. Personal stories and positive messages have the most engagement, even though not for every user group; known persons and influencers have the most engagement with humorous tweets. Health professionals receive more engagement with advocacy, personal stories/statements and humor-based tweets. Health institutes observe higher engagement with advocacy, personal stories/statements, and tweets with a positive sentiment. Personal stories/statements are not the most often tweeted category (22%) but have the highest engagement (27%). Messages centered on shock/disgust/fear-based (32%) have a 21% engagement. The frequency of informative/educational communications is high (33%) and their engagement is 16%. Advocacy message (8%) receive 9% engagement. Humor and opportunistic messages have engagements of 4% and 0.5% and low frequenciesof 5% and 1%, respectively. This study suggests the optimum mix of message type and sentiment that each user category should use to get more engagement. Conclusions: This study provides comprehensive insight into Twitter (rebranded as X in 2023) users’ responses toward various message type and sources. Our study shows that audience engages with personal stories and positive messages the most. Our findings provide valuable guidance for social media-based public health campaigns in developing messages for maximum engagement. %R 10.2196/59687 %U https://formative.jmir.org/2025/1/e59687 %U https://doi.org/10.2196/59687 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 9 %N %P e56720 %T YouTube User Traffic to Paired Epilepsy Education Videos in English and Spanish: Comparative Study %A Varela,Luna Kimahri %A Horton,Stephanie %A Abdelmoity,Ahmed %A Le Pichon,Jean-Baptiste %A Hoffman,Mark A %K epilepsy %K patient education %K informatics %K social media %K biomedical research %K social determinants of health %K accessibility %K engagement %K comparative analysis %K clinical videos %K English %K Spanish %K neurological disorder %K YouTube %K bilingual %K audience engagement %K clinical knowledge %D 2025 %7 13.3.2025 %9 %J JMIR Form Res %G English %X Background: Effectively managing epilepsy in children necessitates the active engagement of parents, a factor that is reliant on their understanding of this neurological disorder. Widely available, high-quality, patient-focused, bilingual videos describing topics important for managing epilepsy are limited. YouTube Analytics is a helpful resource for gaining insights into how users of differing backgrounds consume video content. Objective: This study analyzes traffic to paired educational videos of English and Spanish versions of the same content. By examining the use patterns and preferences of individuals seeking information in different languages, we gained valuable insights into how language influences the use of clinical content. Methods: Physician experts created epilepsy management videos for the REACT (Reaching Out for Epilepsy in Adolescents and Children Through Telemedicine) YouTube channel about 17 subjects, with an English and Spanish version of each. The Children’s Mercy Kansas City neurology clinic incorporated these into the department’s educational process. YouTube Analytics enabled analysis of traffic patterns and video characteristics between September 2, 2021, and August 31, 2023. Results: The Spanish group had higher engagement and click-through rates. The English versions of all videos had 141,605 total impressions, while impressions for the Spanish versions totaled 156,027. The Spanish videos had 11,339 total views, while the English videos had 3366. The views per month were higher for the Spanish videos (mean 472, SD 292) compared to the English set (mean 140, SD 91; P<.001). The two groups also differed in search behavior and external traffic sources, with WhatsApp driving more traffic to the Spanish videos than the English versions (94 views compared to 1). The frequency of search terms used varied by language. For example, “tonic clonic” was the most frequent term (n=372) resulting in views for English videos, while “tipos de convulsiones” (types of convulsions) was the most common expression (n=798) resulting in views for Spanish videos. We noted increased monthly views for all videos after adding tags on YouTube. Before tagging, the mean number of views per month for the English-language group was 61 (SD 28), which increased to 220 (SD 53) post tagging. A similar trend can be observed in the Spanish-language group as well. Before tagging, the mean number of monthly views was 201 (SD 71), which increased to 743 (SD 144) after tagging. Conclusions: This study showed high traffic for Spanish video content related to epilepsy in a set of paired English/Spanish videos. This highlights the importance of bilingual health content and optimizing video content based on viewer preferences and search behavior. Understanding audience engagement patterns through YouTube Analytics can further enhance the dissemination of clinical video content to users seeking content in their primary language, and tagging videos can have a substantial impact on views. %R 10.2196/56720 %U https://formative.jmir.org/2025/1/e56720 %U https://doi.org/10.2196/56720 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 9 %N %P e66207 %T Medical Misinformation in AI-Assisted Self-Diagnosis: Development of a Method (EvalPrompt) for Analyzing Large Language Models %A Zada,Troy %A Tam,Natalie %A Barnard,Francois %A Van Sittert,Marlize %A Bhat,Venkat %A Rambhatla,Sirisha %K ChatGPT %K health care %K LLM %K misinformation %K self-diagnosis %K large language model %D 2025 %7 10.3.2025 %9 %J JMIR Form Res %G English %X Background: Rapid integration of large language models (LLMs) in health care is sparking global discussion about their potential to revolutionize health care quality and accessibility. At a time when improving health care quality and access remains a critical concern for countries worldwide, the ability of these models to pass medical examinations is often cited as a reason to use them for medical training and diagnosis. However, the impact of their inevitable use as a self-diagnostic tool and their role in spreading health care misinformation has not been evaluated. Objective: This study aims to assess the effectiveness of LLMs, particularly ChatGPT, from the perspective of an individual self-diagnosing to better understand the clarity, correctness, and robustness of the models. Methods: We propose the comprehensive testing methodology evaluation of LLM prompts (EvalPrompt). This evaluation methodology uses multiple-choice medical licensing examination questions to evaluate LLM responses. Experiment 1 prompts ChatGPT with open-ended questions to mimic real-world self-diagnosis use cases, and experiment 2 performs sentence dropout on the correct responses from experiment 1 to mimic self-diagnosis with missing information. Humans then assess the responses returned by ChatGPT for both experiments to evaluate the clarity, correctness, and robustness of ChatGPT. Results: In experiment 1, we found that ChatGPT-4.0 was deemed correct for 31% (29/94) of the questions by both nonexperts and experts, with only 34% (32/94) agreement between the 2 groups. Similarly, in experiment 2, which assessed robustness, 61% (92/152) of the responses continued to be categorized as correct by all assessors. As a result, in comparison to a passing threshold of 60%, ChatGPT-4.0 is considered incorrect and unclear, though robust. This indicates that sole reliance on ChatGPT-4.0 for self-diagnosis could increase the risk of individuals being misinformed. Conclusions: The results highlight the modest capabilities of LLMs, as their responses are often unclear and inaccurate. Any medical advice provided by LLMs should be cautiously approached due to the significant risk of misinformation. However, evidence suggests that LLMs are steadily improving and could potentially play a role in health care systems in the future. To address the issue of medical misinformation, there is a pressing need for the development of a comprehensive self-diagnosis dataset. This dataset could enhance the reliability of LLMs in medical applications by featuring more realistic prompt styles with minimal information across a broader range of medical fields. %R 10.2196/66207 %U https://formative.jmir.org/2025/1/e66207 %U https://doi.org/10.2196/66207 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 9 %N %P e59875 %T Person-Specific Analyses of Smartphone Use and Mental Health: Intensive Longitudinal Study %A Cerit,Merve %A Lee,Angela Y %A Hancock,Jeffrey %A Miner,Adam %A Cho,Mu-Jung %A Muise,Daniel %A Garròn Torres,Anna-Angelina %A Haber,Nick %A Ram,Nilam %A Robinson,Thomas N %A Reeves,Byron %+ Graduate School of Education, Stanford University, 520 Galvez Mall, Stanford, CA, 94305, United States, 1 650 723 21 46, mervecer@stanford.edu %K media use %K mental health %K mHealth %K uHealth %K digital health %K precision mental health %K idiographic analysis %K person-specific modeling %K p-technique %K longitudinal study %K precision interventions %K smartphones %K idiosyncrasy %K psychological well-being %K canonical correlation analysis %K United States %D 2025 %7 26.2.2025 %9 Original Paper %J JMIR Form Res %G English %X Background: Contrary to popular concerns about the harmful effects of media use on mental health, research on this relationship is ambiguous, stalling advances in theory, interventions, and policy. Scientific explorations of the relationship between media and mental health have mostly been found null or have small associations, with the results often blamed on the use of cross-sectional study designs or imprecise measures of media use and mental health. Objective: This exploratory empirical demonstration aims to answer whether mental health effects are associated with media use experiences by (1) redirecting research investments to granular and intensive longitudinal recordings of digital experiences to build models of media use and mental health for single individuals over the course of 1 year, (2) using new metrics of fragmented media use to propose explanations of mental health effects that will advance person-specific theorizing in media psychology, and (3) identifying combinations of media behaviors and mental health symptoms that may be more useful for studying media effects than single measures of dosage and affect or assessments of clinical symptoms related to specific disorders. Methods: The activity on individuals’ smartphone screens was recorded every 5 seconds when devices were in use over 1 year, resulting in a dataset of 6,744,013 screenshots and 123 fortnightly surveys from 5 adult participants. Each participant contributed between 0.8 and 2.7 million screens. Six media use metrics were derived from smartphone metadata. Fortnightly surveys captured symptoms of depression, attention-deficit/hyperactivity disorder, state anxiety, and positive affect. Idiographic filter models (p-technique canonical correlation analyses) were applied to explore person-specific associations. Results: Canonical correlations revealed substantial person-specific associations between media use and mental health, ranging from r=0.82 (P=.008) to r=0.92 (P=.03). The specific combinations of media use metrics and mental health dimensions were different for each person, reflecting significant individual variability. For instance, the media use canonical variate for 1 participant was characterized by higher loadings for app-switching, which, in combination with other behaviors, correlated strongly with a mental health variate emphasizing anxiety symptoms. For another, prolonged screen time, alongside other media use behaviors, contributed to a mental health variate weighted more heavily toward depression symptoms. These within-person correlations are among the strongest reported in this literature. Conclusions: Results suggest that the relationships between media use and mental health are highly individualized, with implications for the development of personalized models and precision smartphone-informed interventions in mental health. We discuss how our approach can be extended generally, while still emphasizing the importance of idiographic approaches. This study highlights the potential for granular, longitudinal data to reveal person-specific patterns that can inform theory development, personalized screening, diagnosis, and interventions in mental health. %M 39808832 %R 10.2196/59875 %U https://formative.jmir.org/2025/1/e59875 %U https://doi.org/10.2196/59875 %U http://www.ncbi.nlm.nih.gov/pubmed/39808832 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 9 %N %P e63344 %T Instagram Posts Promoting Colorectal Cancer Awareness: Content Analysis of Themes and Engagement During Colorectal Cancer Awareness Month %A Srivastava,Aditi %A Stimpson,Jim P %K social media %K colorectal neoplasms %K early detection of cancer %K public health %K health inequities %K harnessing %K Instagram %K colorectal cancer %K colorectal cancer awareness %K content analysis %K cancer-related deaths %K detection %K screening %K mortality %K post %K early detection %D 2025 %7 19.2.2025 %9 %J JMIR Form Res %G English %X Background: Colorectal cancer (CRC) is a leading cause of cancer-related deaths worldwide, with early detection and screening being critical for reducing mortality. Social media platforms like Instagram offer a unique opportunity to raise awareness about CRC, particularly during designated awareness months. However, there is limited research on the effectiveness of CRC-related content on Instagram. Objective: This study aims to examine how Instagram is used to raise awareness about CRC during Colorectal Cancer Awareness Month by analyzing the thematic content and engagement metrics of related posts. The research seeks to identify the prevalent themes, assess audience interaction with these messages, and highlight areas for improvement in leveraging Instagram as a tool for cancer awareness campaigns. Methods: A total of 150 Instagram posts were collected based on their use of specific hashtags related to CRC awareness (#colorectalcancer, #colorectalcancerawareness, #colorectalcancerawarenessmonth) during March 2024. The text and images in the posts were categorized into themes such as screening and early detection, symptoms, general awareness, risk factors, individual’s experiences, representation of racial and ethnic minoritized communities, and representation of women. Engagement metrics, including the number of likes and comments, were also analyzed. Two researchers independently coded the posts, achieving high interrater reliability (Cohen κ=0.93). Results: Organizational accounts were more active, contributing 82% (n=123) of the 150 posts, compared to 18% (n=27) from individual users. The most frequently mentioned theme was screening and early detection, which made up 37.3% (n=56) of all posts. General awareness came in second at 19.3% (n=29), and risk factors came in third at 12% (n=18). Posts about individual experiences and general awareness received the highest engagement, indicating the effectiveness of personal narratives and broad informational content. Themes related to symptoms and representation of racial and ethnic minoritized communities and women were underrepresented. Conclusions: This study highlights the potential of Instagram as a platform for promoting CRC awareness, particularly through posts about screening and early detection and personal experiences. However, there is a need for more inclusive and diverse content to ensure a broader reach and impact. %R 10.2196/63344 %U https://formative.jmir.org/2025/1/e63344 %U https://doi.org/10.2196/63344 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 9 %N %P e60862 %T Privacy Concerns Versus Personalized Health Content—Pregnant Individuals’ Willingness to Share Personal Health Information on Social Media: Survey Study %A Hao,Haijing %A Lee,Yang W %A Sharko,Marianne %A Li,Qilu %A Zhang,Yiye %K privacy concerns %K trust %K pregnancy %K health information seeking %K pregnant women %K maternal %K maternity %K childbearing %K web-based information %K health information %K mental health %K internet %K social support %K technology %K mobile health %K mHealth %K digital health %K health informatics %K social media %D 2025 %7 10.2.2025 %9 %J JMIR Form Res %G English %X Background: Often lacking immediate access to care providers, pregnant individuals frequently turn to web-based sources for information to address their evolving physical and mental health needs. Social media has gained increasing prominence as a source of news and information despite privacy concerns and unique risks posed to the pregnant population. Objectives: This study investigated the extent to which patients may be willing to disclose personal health information to social media companies in exchange for more personalized health content. Methods: We designed and deployed an electronic survey to pregnant individuals worldwide electronically in 2023. We used the classical Internet Users’ Information Privacy Concerns (IUIPC) model to examine how privacy concerns modulate pregnant individuals’ behaviors and beliefs regarding risk and trust when using social media for health purposes. Results were analyzed using partial least squares structural equation modeling. Results: Among 317 respondents who initiated the survey, 84% (265/317) of the respondents remained in the study, providing complete responses. Among them, 54.7% (145/265) indicated willingness to provide their personalized health information for receiving personalized health content via social media, while 26% (69/265) were uncertain and 19.3% (51/265) were opposed. Our estimated IUIPC model results are statistically significant and qualitatively align with the classic IUIPC model for the general population, which was previously found in an e-commerce context. The structural model revealed that privacy concerns (IUIPC) negatively affected trusting beliefs (β=−0.408; P<.001) and positively influenced risk beliefs (β=0.442; P<.001). Trusting beliefs negatively impacted risk beliefs (β=−o.362; P<.001) and positively affected the intention to disclose personal health information (β=o.266; P<.001). Risk beliefs negatively influenced the intention to disclose (β=−0.281; P<.001). The model explained 41.5% of the variance in the intention to disclose personal health information (R²=0.415). In parallel with pregnant individuals’ willingness to share, we find that they have heightened privacy concerns and their use of social media for information seeking is largely impacted by their trust in the platforms. This heightened concern significantly affects both their trusting beliefs, making them less inclined to trust social media companies, and their risk beliefs, leading them to perceive greater risks in sharing personal health information. However, within this population, an increase in trust toward social media companies leads to a more substantial decrease in perceived risks than what has been previously observed in the general population. Conclusions: We find that more than half of the pregnant individuals are open to sharing their personal health information to receive personalized content about health via social media, although they have more privacy concerns than the general population. This study emphasizes the need for policy regarding the protection of health data on social media for the pregnant population and beyond. %R 10.2196/60862 %U https://formative.jmir.org/2025/1/e60862 %U https://doi.org/10.2196/60862 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 9 %N %P e56126 %T Proficiency, Clarity, and Objectivity of Large Language Models Versus Specialists’ Knowledge on COVID-19's Impacts in Pregnancy: Cross-Sectional Pilot Study %A Bragazzi,Nicola Luigi %A Buchinger,Michèle %A Atwan,Hisham %A Tuma,Ruba %A Chirico,Francesco %A Szarpak,Lukasz %A Farah,Raymond %A Khamisy-Farah,Rola %+ Laboratory for Industrial and Applied Mathematics, Department of Mathematics and Statistics, York University, 4700 Keele Street, Toronto, ON, M3J 1P3, Canada, 1 416 736 2100, robertobragazzi@gmail.com %K COVID-19 %K vaccine %K reproductive health %K generative artificial intelligence %K large language model %K chatGPT %K google bard %K microsoft copilot %K vaccination %K natural language processing %K obstetric %K gynecology %K women %K text mining %K sentiment %K accuracy %K zero shot %K pregnancy %K readability %K infectious %D 2025 %7 5.2.2025 %9 Original Paper %J JMIR Form Res %G English %X Background: The COVID-19 pandemic has significantly strained health care systems globally, leading to an overwhelming influx of patients and exacerbating resource limitations. Concurrently, an “infodemic” of misinformation, particularly prevalent in women’s health, has emerged. This challenge has been pivotal for health care providers, especially gynecologists and obstetricians, in managing pregnant women’s health. The pandemic heightened risks for pregnant women from COVID-19, necessitating balanced advice from specialists on vaccine safety versus known risks. In addition, the advent of generative artificial intelligence (AI), such as large language models (LLMs), offers promising support in health care. However, they necessitate rigorous testing. Objective: This study aimed to assess LLMs’ proficiency, clarity, and objectivity regarding COVID-19’s impacts on pregnancy. Methods: This study evaluates 4 major AI prototypes (ChatGPT-3.5, ChatGPT-4, Microsoft Copilot, and Google Bard) using zero-shot prompts in a questionnaire validated among 159 Israeli gynecologists and obstetricians. The questionnaire assesses proficiency in providing accurate information on COVID-19 in relation to pregnancy. Text-mining, sentiment analysis, and readability (Flesch-Kincaid grade level and Flesch Reading Ease Score) were also conducted. Results: In terms of LLMs’ knowledge, ChatGPT-4 and Microsoft Copilot each scored 97% (32/33), Google Bard 94% (31/33), and ChatGPT-3.5 82% (27/33). ChatGPT-4 incorrectly stated an increased risk of miscarriage due to COVID-19. Google Bard and Microsoft Copilot had minor inaccuracies concerning COVID-19 transmission and complications. In the sentiment analysis, Microsoft Copilot achieved the least negative score (–4), followed by ChatGPT-4 (–6) and Google Bard (–7), while ChatGPT-3.5 obtained the most negative score (–12). Finally, concerning the readability analysis, Flesch-Kincaid Grade Level and Flesch Reading Ease Score showed that Microsoft Copilot was the most accessible at 9.9 and 49, followed by ChatGPT-4 at 12.4 and 37.1, while ChatGPT-3.5 (12.9 and 35.6) and Google Bard (12.9 and 35.8) generated particularly complex responses. Conclusions: The study highlights varying knowledge levels of LLMs in relation to COVID-19 and pregnancy. ChatGPT-3.5 showed the least knowledge and alignment with scientific evidence. Readability and complexity analyses suggest that each AI’s approach was tailored to specific audiences, with ChatGPT versions being more suitable for specialized readers and Microsoft Copilot for the general public. Sentiment analysis revealed notable variations in the way LLMs communicated critical information, underscoring the essential role of neutral and objective health care communication in ensuring that pregnant women, particularly vulnerable during the COVID-19 pandemic, receive accurate and reassuring guidance. Overall, ChatGPT-4, Microsoft Copilot, and Google Bard generally provided accurate, updated information on COVID-19 and vaccines in maternal and fetal health, aligning with health guidelines. The study demonstrated the potential role of AI in supplementing health care knowledge, with a need for continuous updating and verification of AI knowledge bases. The choice of AI tool should consider the target audience and required information detail level. %M 39794312 %R 10.2196/56126 %U https://formative.jmir.org/2025/1/e56126 %U https://doi.org/10.2196/56126 %U http://www.ncbi.nlm.nih.gov/pubmed/39794312 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 9 %N %P e55309 %T Understanding Health-Related Discussions on Reddit: Development of a Topic Assignment Method and Exploratory Analysis %A Chan,Garrett J %A Fung,Mark %A Warrington,Jill %A Nowak,Sarah A %+ Larner College of Medicine, University of Vermont, 89 Beaumont Ave, Burlington, VT, 05405, United States, 1 802 656 0359, sarah.nowak@med.uvm.edu %K digital health %K internet %K open data %K social networking %K social media %D 2025 %7 29.1.2025 %9 Original Paper %J JMIR Form Res %G English %X Background: Social media has become a widely used way for people to share opinions about health care and medical topics. Social media data can be leveraged to understand patient concerns and provide insight into why patients may turn to the internet instead of the health care system for health advice. Objective: This study aimed to develop a method to investigate Reddit posts discussing health-related conditions. Our goal was to characterize these topics and identify trends in these social media–based medical discussions. Methods: Using an initial query, we collected 1 year of Reddit posts containing the phrases “get tested” and “get checked.” These posts were manually reviewed, and subreddits containing irrelevant posts were excluded from analysis. This selection of posts was manually read by the investigators to categorize posts into topics. A script was developed to automatically assign topics to additional posts based on keywords. Topic and keyword selections were refined based on manual review for more accurate topic assignment. Topic assignment was then performed on the entire 1-year Reddit dataset containing 347,130 posts. Related topics were grouped into broader medical disciplines. Analysis of the topic assignments was then conducted to assess condition and medical topic frequencies in medical condition–focused subreddits and general subreddits. Results: We created an automated algorithm to assign medical topics to Reddit posts. By iterating through multiple rounds of topic assignment, we improved the accuracy of the algorithm. Ultimately, this algorithm created 82 topics sorted into 17 broader medical disciplines. Of all topics, sexually transmitted infections (STIs), eye disorders, anxiety, and pregnancy had the highest post frequency overall. STIs comprised 7.44% (5876/78,980) of posts, and anxiety comprised 5.43% (4289/78,980) of posts. A total of 34% (28/82) of the topics comprised 80% (63,184/78,980) of all posts. Of the medical disciplines, those with the most posts were psychiatry and mental health; genitourinary and reproductive health; infectious diseases; and endocrinology, nutrition, and metabolism. Psychiatry and mental health comprised 26.6% (21,009/78,980) of posts, and genitourinary and reproductive health comprised 13.6% (10,741/78,980) of posts. Overall, most posts were also classified under these 4 medical disciplines. During analysis, subreddits were also classified as general if they did not focus on a specific health issue and topic-specific if they discussed a specific medical issue. Topics that appeared most frequently in the top 5 in general subreddits included addiction and drug anxiety, attention-deficit/hyperactivity disorder, abuse, and STIs. In topic-specific subreddits, most posts were found to discuss the topic of that subreddit. Conclusions: Certain health topics and medical disciplines are predominant on Reddit. These include topics such as STIs, eye disorders, anxiety, and pregnancy. Most posts were classified under the medical disciplines of psychiatry and mental health, as well as genitourinary and reproductive health. %M 39879094 %R 10.2196/55309 %U https://formative.jmir.org/2025/1/e55309 %U https://doi.org/10.2196/55309 %U http://www.ncbi.nlm.nih.gov/pubmed/39879094 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 9 %N %P e57395 %T Public Health Discussions on Social Media: Evaluating Automated Sentiment Analysis Methods %A Gandy,Lisa M %A Ivanitskaya,Lana V %A Bacon,Leeza L %A Bizri-Baryak,Rodina %+ Department of Computer Science, College of Sciences and Liberal Arts, Kettering University, 1700 University Ave, 2300 AB, Flint, MI, 48504, United States, 1 9898547001, lgandy@kettering.edu %K ChatGPT %K VADER %K valence aware dictionary for sentiment reasoning %K LIWC-22 %K machine learning %K social media %K sentiment analysis %K public health %K population health %K opioids %K drugs %K pharmacotherapy %K pharmaceuticals %K medications %K YouTube %D 2025 %7 8.1.2025 %9 Original Paper %J JMIR Form Res %G English %X Background: Sentiment analysis is one of the most widely used methods for mining and examining text. Social media researchers need guidance on choosing between manual and automated sentiment analysis methods. Objective: Popular sentiment analysis tools based on natural language processing (NLP; VADER [Valence Aware Dictionary for Sentiment Reasoning], TEXT2DATA [T2D], and Linguistic Inquiry and Word Count [LIWC-22]), and a large language model (ChatGPT 4.0) were compared with manually coded sentiment scores, as applied to the analysis of YouTube comments on videos discussing the opioid epidemic. Sentiment analysis methods were also examined regarding ease of programming, monetary cost, and other practical considerations. Methods: Evaluation methods included descriptive statistics, receiver operating characteristic (ROC) curve analysis, confusion matrices, Cohen κ, accuracy, specificity, precision, sensitivity (recall), F1-score harmonic mean, and the Matthews correlation coefficient. An inductive, iterative approach to content analysis of the data was used to obtain manual sentiment codes. Results: A subset of comments were analyzed by a second coder, producing good agreement between the 2 coders’ judgments (κ=0.734). YouTube social media about the opioid crisis had many more negative comments (4286/4871, 88%) than positive comments (79/662, 12%), making it possible to evaluate the performance of sentiment analysis models in an unbalanced dataset. The tone summary measure from LIWC-22 performed better than other tools for estimating the prevalence of negative versus positive sentiment. According to the ROC curve analysis, VADER was best at classifying manually coded negative comments. A comparison of Cohen κ values indicated that NLP tools (VADER, followed by LIWC’s tone and T2D) showed only fair agreement with manual coding. In contrast, ChatGPT 4.0 had poor agreement and failed to generate binary sentiment scores in 2 out of 3 attempts. Variations in accuracy, specificity, precision, sensitivity, F1-score, and MCC did not reveal a single superior model. F1-score harmonic means were 0.34-0.38 (SD 0.02) for NLP tools and very low (0.13) for ChatGPT 4.0. None of the MCCs reached a strong correlation level. Conclusions: Researchers studying negative emotions, public worries, or dissatisfaction with social media face unique challenges in selecting models suitable for unbalanced datasets. We recommend VADER, the only cost-free tool we evaluated, due to its excellent discrimination, which can be further improved when the comments are at least 100 characters long. If estimating the prevalence of negative comments in an unbalanced dataset is important, we recommend the tone summary measure from LIWC-22. Researchers using T2D must know that it may only score some data and, compared with other methods, be more time-consuming and cost-prohibitive. A general-purpose large language model, ChatGPT 4.0, has yet to surpass the performance of NLP models, at least for unbalanced datasets with highly prevalent (7:1) negative comments. %R 10.2196/57395 %U https://formative.jmir.org/2025/1/e57395 %U https://doi.org/10.2196/57395 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 9 %N %P e68792 %T Quality Assessment of Medical Institutions’ Websites Regarding Prescription Drug Misuse of Glucagon-Like Peptide-1 Receptor Agonists by Off-Label Use for Weight Loss: Website Evaluation Study %A Oyama,Rie %A Okuhara,Tsuyoshi %A Furukawa,Emi %A Okada,Hiroko %A Kiuchi,Takahiro %+ Department of Health Communication, School of Public Health, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8655, Japan, 81 3 5800 6549, rooyama-oss@umin.ac.jp %K prescription drug misuse %K GLP-1 receptor agonists %K off-label use %K weight loss %K information quality %K DISCERN %K web-based information %K information provision %K misinformation %K advertising guidelines %K exaggerated advertisements %D 2025 %7 1.1.2025 %9 Original Paper %J JMIR Form Res %G English %X Background: Misuse of glucagon-like peptide-1 receptor agonists (GLP-1RAs) has emerged globally as individuals increasingly use these drugs for weight loss because of unrealistic and attractive body images advertised and shared on the internet. Objective: This study assesses the quality of information and compliance with Japan’s medical advertising guidelines on the websites of medical institutions that prescribe GLP-1RAs off-label for weight loss. Methods: Websites were identified by searching Google and Yahoo! by using keywords related to GLP-1RAs and weight loss in August 2024. The quality of information on these websites was assessed using the DISCERN instrument. To comply with Japan’s medical advertising guidelines, we evaluated whether the 5 mandatory items for advertisements of self-paid medical treatments involving the off-label use of drugs were stated and whether there were any exaggerated claims. The content of the exaggerated advertisements was categorized into themes. Results: Of the 87 websites included, only 1 website stated all 5 mandatory items. Websites listing “ineligible for the relief system for sufferers from adverse drug reactions” had the lowest percentage at 9% (8/87), while 83% (72/87) of the websites listed exaggerated advertisements. Approximately 69% (60/87) of the websites suggested that no exercise or dietary therapy was required, 24% (21/87) suggested that using GLP-1RAs is a natural and healthy method, and 31% (27/87) of the websites provided the author’s personal opinions on the risks of using GLP-1RAs. The mean total DISCERN score for all 87 websites was 32.6 (SD 5.5), indicating low quality. Only 1 website achieved a good rating, and 9 websites were rated as fair. The majority of the websites were rated as poor (72 websites) or very poor (5 websites). Conclusions: We found that the quality of information provided by the websites of medical institutions prescribing GLP-1RAs off-label for weight loss was very low and that many websites violated Japan’s medical advertising guidelines. The prevalence of exaggerated advertisements, which may lead consumers to believe that they can lose weight without dietary or exercise therapy, suggests the risk of GLP-1RA misuse among consumers. Public institutions and health care providers should monitor and regulate advertisements that violate guidelines and provide accurate information regarding GLP-1RAs, obesity, and weight loss. %M 39742456 %R 10.2196/68792 %U https://formative.jmir.org/2025/1/e68792 %U https://doi.org/10.2196/68792 %U http://www.ncbi.nlm.nih.gov/pubmed/39742456 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 8 %N %P e49567 %T An Analysis of the Prevalence and Trends in Drug-Related Lyrics on Twitter (X): Quantitative Approach %A Luo,Waylon %A Jin,Ruoming %A Kenne,Deric %A Phan,NhatHai %A Tang,Tang %+ Department of Computer Science, Kent State University, 1300 Lester A Lefton Esplanade, Kent, OH, 44241, United States, 1 330 672 9063, rjin1@kent.edu %K Twitter (X) %K popular music %K big data analysis %K music %K lyrics %K big data %K substance abuse %K tweet %K social media %K drug %K alcohol %D 2024 %7 30.12.2024 %9 Original Paper %J JMIR Form Res %G English %X Background: The pervasiveness of drug culture has become evident in popular music and social media. Previous research has examined drug abuse content in both social media and popular music; however, to our knowledge, the intersection of drug abuse content in these 2 domains has not been explored. To address the ongoing drug epidemic, we analyzed drug-related content on Twitter (subsequently rebranded X), with a specific focus on lyrics. Our study provides a novel finding on the prevalence of drug abuse by defining a new subcategory of X content: “tweets that reference established drug lyrics.” Objective: We aim to investigate drug trends in popular music on X, identify and classify popular drugs, and analyze related artists’ gender, genre, and popularity. Based on the collected data, our goal is to create a prediction model for future drug trends and gain a deeper understanding of the characteristics of users who cite drug lyrics on X. Methods: X data were collected from 2015 to 2017 through the X streaming application programming interface (API). Drug lyrics were obtained from the Genius lyrics database using the Genius API based on drug keywords. The Smith-Waterman text-matching algorithm is used to detect the drug lyrics in posts. We identified famous drugs in lyrics that were posted. Consequently, the analysis was extended to related artists, songs, genres, and popularity on X. The frequency of drug-related lyrics on X was aggregated into a time-series, which was then used to create prediction models using linear regression, Facebook Prophet, and NIXTLA TimeGPT-1. In addition, we analyzed the number of followers of users posting drug-related lyrics to explore user characteristics. Results: We analyzed over 1.97 billion publicly available posts from 2015 to 2017, identifying more than 157 million that matched drug-related keywords. Of these, 150,746 posts referenced drug-related lyrics. Cannabinoids, opioids, stimulants, and hallucinogens were the most cited drugs in lyrics on X. Rap and hip-hop dominated, with 91.98% of drug-related lyrics from these genres and 84.21% performed by male artists. Predictions from all 3 models, linear regression, Facebook Prophet, and NIXTLA TimeGPT-1, indicate a slight decline in the prevalence of drug-related lyrics on X over time. Conclusions: Our study revealed 2 significant findings. First, we identified a previously unexamined subset of drug-related content on X: drug lyrics, which could play a critical role in models predicting the surge in drug-related incidents. Second, we demonstrated the use of cutting-edge time-series forecasting tools, including Facebook Prophet and NIXTLA TimeGPT-1, in accurately predicting these trends. These insights contribute to our understanding of how social media shapes public behavior and sentiment toward drug use. %M 39753225 %R 10.2196/49567 %U https://formative.jmir.org/2024/1/e49567 %U https://doi.org/10.2196/49567 %U http://www.ncbi.nlm.nih.gov/pubmed/39753225 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 8 %N %P e60033 %T Quality of Pancreatic Neuroendocrine Tumor Videos Available on TikTok and Bilibili: Content Analysis %A Niu,Zheyu %A Hao,Yijie %A Yang,Faji %A Jiang,Qirong %A Jiang,Yupeng %A Zhang,Shizhe %A Song,Xie %A Chang,Hong %A Zhou,Xu %A Zhu,Huaqiang %A Gao,Hengjun %A Lu,Jun %K pancreatic neuroendocrine tumors %K short videos %K quality analysis %K TikTok %K Bilibili %K social media %D 2024 %7 11.12.2024 %9 %J JMIR Form Res %G English %X Background: Disseminating disease knowledge through concise videos on various platforms is an innovative and efficient approach. However, it remains uncertain whether pancreatic neuroendocrine tumor (pNET)-related videos available on current short video platforms can effectively convey accurate and impactful information to the general public. Objective: Our study aims to extensively analyze the quality of pNET-related videos on TikTok and Bilibili, intending to enhance the development of pNET-related social media content to provide the general public with more comprehensive and suitable avenues for accessing pNET-related information. Methods: A total of 168 qualifying videos pertaining to pNETs were evaluated from the video-sharing platforms Bilibili and TikTok. Initially, the fundamental information conveyed in the videos was documented. Subsequently, we discerned the source and content type of each video. Following that, the Global Quality Scale (GQS) and modified DISCERN (mDISCERN) scale were employed to appraise the educational value and quality of each video. A comparative evaluation was conducted on the videos obtained from these two platforms. Results: The number of pNET-related videos saw a significant increase since 2020, with 9 videos in 2020, 19 videos in 2021, 29 videos in 2022, and 106 videos in 2023. There were no significant improvements in the mean GQS or mDISCERN scores from 2020 to 2023, which were 3.22 and 3.00 in 2020, 3.33 and 2.94 in 2021, 2.83 and 2.79 in 2022, and 2.78 and 2.94 in 2023, respectively. The average quality scores of the videos on Bilibili and Tiktok were comparable, with GQS and mDISCERN scores of 2.98 on Bilibili versus 2.77 on TikTok and 2.82 on Bilibili versus 3.05 on TikTok, respectively. The source and format of the videos remained independent factors affecting the two quality scores. Videos that were uploaded by professionals (hazard ratio=7.02, P=.002) and recorded in specialized popular science formats (hazard ratio=12.45, P<.001) tended to exhibit superior quality. Conclusions: This study demonstrates that the number of short videos on pNETs has increased in recent years, but video quality has not improved significantly. This comprehensive analysis shows that the source and format of videos are independent factors affecting video quality, which provides potential measures for improving the quality of short videos. %R 10.2196/60033 %U https://formative.jmir.org/2024/1/e60033 %U https://doi.org/10.2196/60033 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 8 %N %P e54092 %T Understanding Membership in Alternative Health Social Media Groups and Its Association with COVID-19 and Influenza Vaccination: Web-Based Cross-Sectional Survey %A Na,Kilhoe %A Zimdars,Melissa %A Cullinan,Megan E %+ Department of Communication and Media, Merrimack College, Cushing Hall 306B, 315 Turnpike St., North Andover, MA, 01845, United States, 1 9788375765, nak@merrimack.edu %K alternative health %K social media %K misinformation %K vaccination %K COVID-19 %K Coronavirus %D 2024 %7 5.12.2024 %9 Original Paper %J JMIR Form Res %G English %X Background: Social media platforms have become home to numerous alternative health groups where people share health information and scientifically unproven treatments. Individuals share not only health information but also health misinformation in alternative health groups on social media. Yet, little research has been carried out to understand members of these groups. This study aims to better understand various characteristics of members in alternative health groups and the association between membership and attitudes toward vaccination and COVID-19 and influenza vaccination–related behaviors. Objective: This study aims to test hypotheses about different potential characteristics of members in alternative health groups and the association between membership and attitudes toward vaccination and vaccine-related behaviors. Methods: A web-based cross-sectional survey (N=1050) was conducted. Participants were recruited from 19 alternative health social media groups and Amazon’s Mechanical Turk. A total of 596 participants were members of alternative health groups and 454 were nonmembers of alternative health groups. Logistic regressions were performed to test the hypotheses about the relationship between membership and the variables of interest. Results: Logistic regression revealed that there is a positive association between alternative health social media group membership and 3 personal characteristics: sharing trait (B=.83, SE=.11; P<.01; odds ratio [OR] 2.30, 95% CI 1.85-2.86), fear of negative evaluations (B=.19, SE=.06; P<.001, OR 1.21, 95% CI 1.06-1.37), and conspiratorial mentality (B=.33, SE=.08; P<.01; OR 1.40, 95% CI 1.18-1.65). Also, the results indicate that there is a negative association between membership and 2 characteristics: health literacy (B=–1.09, SE=.17; P<.001; OR .33, 95% CI 0.23-0.47) and attitudes toward vaccination (B=– 2.33, SE=.09; P=.02; OR 0.79, 95% CI 0.65-0.95). However, there is no association between membership and health consciousness (B=.12, SE=.10; P=.24; OR 1.13, 95% CI 0.92-1.38). Finally, membership is negatively associated with COVID-19 vaccination status (B=–.84, SE=.17; P<.001; OR 48, 95% CI 0.32-0.62), and influenza vaccination practice (B=–1.14, SE=.17; P<.001; OR .31, 95% CI 0.22-0.45). Conclusions: Our findings indicate that people joining alternative health social media groups differ from nonmembers in different aspects, such as sharing, fear of negative evaluations, conspiratorial mentality, and health literacy. They also suggest that there is a significant relationship between membership and vaccination. By more thoroughly exploring the demographic, or by better understanding the people for whom interventions are designed, this study is expected to help researchers to more strategically and effectively develop and implement interventions. %M 39636665 %R 10.2196/54092 %U https://formative.jmir.org/2024/1/e54092 %U https://doi.org/10.2196/54092 %U http://www.ncbi.nlm.nih.gov/pubmed/39636665 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 8 %N %P e63281 %T Health-Related Messages About Herbs, Spices, and Other Botanicals Appearing in Print Issues and Websites of Legacy Media: Content Analysis and Evaluation %A Gaba,Ann %A Bennett,Richard %+ Department of Environmental, Occupational, and Geospatial Health Sciences, Graduate School of Public Health and Health Policy, City University of New York, 55 West 125th Street, New York, NY, 10027, United States, 1 (646) 364 9512, Ann.Gaba@sph.cuny.edu %K legacy media %K health applications %K health communication %K botanical products %K content analysis %D 2024 %7 4.12.2024 %9 Original Paper %J JMIR Form Res %G English %X Background: Legacy media are publications that existed before the internet. Many of these have migrated to a web format, either replacing or in parallel to their print issues. Readers place an economic value on access to the information presented as they pay for subscriptions and place a higher degree of trust in their content. Much has been written about inaccurate and misleading health information in social media; however, the content and accuracy of information contained in legacy media has not been examined in detail. Discussion of herbs, spices, and other botanicals has been absent from this context. Objective: The objectives of this study were to (1) identify the health associations of botanical products mentioned in legacy media targeted to a range of demographic groups and (2) evaluate these health associations for accuracy against published scientific studies. Methods: In total, 10 popular magazines targeting a range of gender, race/ethnicity, and sexual orientation demographic groups were selected for analysis. Relevant content was extracted and coded over 1 year. Associations between specific botanical products and health factors were identified. For the most frequent botanical–health application associations, a PubMed search was conducted to identify reviews corresponding to each item’s indicated applications. Where no systematic reviews were available, single research studies were sought. Results: A total of 237 unique botanical products were identified. There were 128 mentions of these in the print issues and 1215 on the websites. In total, 18 health applications were identified and used to categorize the indicated uses for the various products individually and as general categories. The most frequently mentioned applications were skin care, with 913 mentions, immunity enhancement, with 705 mentions, gastrointestinal health and probiotics, with 184 mentions, and cognitive function (stress and mental health), with 106 mentions. Comparison to published literature evaluating the efficacy of these functions identified positive support for aloe vera, argan oil, chamomile, jojoba oil, lavender, rosemary, and tea tree oil in skin care. Berries, ginger, turmeric, and green tea had the strongest evidence for a role in immunity enhancement. Ginger and oats were supported as having a role in gastrointestinal health. Finally, berries, lavender, ashwagandha, and cannabidiol were supported as having a role in managing stress. Other frequently mentioned items such as aloe vera, ashwagandha, or mushrooms for immunity were less strongly supported. Conclusions: Comparison of the most prevalent associations between botanical products and health applications to published literature indicates that, overall, these associations were consistent with current scientific reports about the health applications of botanical products. While some products had a greater degree of research support than others, truly egregious falsehoods were absent. Therefore, legacy media may be considered a credible source of information to readers about these topics. %M 39631062 %R 10.2196/63281 %U https://formative.jmir.org/2024/1/e63281 %U https://doi.org/10.2196/63281 %U http://www.ncbi.nlm.nih.gov/pubmed/39631062 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 8 %N %P e52871 %T The Resilience of Attitude Toward Vaccination: Web-Based Randomized Controlled Trial on the Processing of Misinformation %A Béchard,Benoît %A Gramaccia,Julie A %A Gagnon,Dominique %A Laouan-Sidi,Elhadji Anassour %A Dubé,Ève %A Ouimet,Mathieu %A de Hemptinne,Delphine %A Tremblay,Sébastien %+ School of Psychology, Université Laval, 2325 Allée des Bibliothèques, Pavillon Félix-Antoine-Savard, Québec, QC, G1V 0A6, Canada, 1 4186565383, benoit.bechard.1@ulaval.ca %K attitude toward vaccination %K misinformation %K reinformation %K confidence %K perceived tentativeness %K vaccine hesitancy %K COVID-19 %D 2024 %7 4.12.2024 %9 Original Paper %J JMIR Form Res %G English %X Background: Before the COVID-19 pandemic, it was already recognized that internet-based misinformation and disinformation could influence individuals to refuse or delay vaccination for themselves, their families, or their children. Reinformation, which refers to hyperpartisan and ideologically biased content, can propagate polarizing messages on vaccines, thereby contributing to vaccine hesitancy even if it is not outright disinformation. Objective: This study aimed to evaluate the impact of reinformation on vaccine hesitancy. Specifically, the goal was to investigate how misinformation presented in the style and layout of a news article could influence the perceived tentativeness (credibility) of COVID-19 vaccine information and confidence in COVID-19 vaccination. Methods: We conducted a web-based randomized controlled trial by recruiting English-speaking Canadians aged 18 years and older from across Canada through the Qualtrics (Silver Lake) paid opt-in panel system. Participants were randomly assigned to 1 of 4 distinct versions of a news article on COVID-19 vaccines, each featuring variations in writing style and presentation layout. After reading the news article, participants self-assessed the tentativeness of the information provided, their confidence in COVID-19 vaccines, and their attitude toward vaccination in general. Results: The survey included 537 participants, with 12 excluded for not meeting the task completion time. The final sample comprised 525 participants distributed about equally across the 4 news article versions. Chi-square analyses revealed a statistically significant association between general attitude toward vaccination and the perceived tentativeness of the information about COVID-19 vaccines included in the news article (χ21=37.8, P<.001). The effect size was small to moderate, with Cramer V=0.27. An interaction was found between vaccine attitude and writing style (χ21=6.2, P=.01), with a small effect size, Cramer V=0.11. In addition, a Pearson correlation revealed a significant moderate to strong correlation between perceived tentativeness and confidence in COVID-19 vaccination, r(523)=0.48, P<.001. The coefficient of determination (r2) was 0.23, indicating that 23% of the variance in perceived tentativeness was explained by confidence in COVID-19 vaccines. In comparing participants exposed to a journalistic-style news article with those exposed to an ideologically biased article, Cohen d was calculated to be 0.38, indicating a small to medium effect size for the difference in the perceived tentativeness between these groups. Conclusions: Exposure to a news article conveying misinformation may not be sufficient to change an individual’s level of vaccine hesitancy. The study reveals that the predominant factor in shaping individuals’ perceptions of COVID-19 vaccines is their attitude toward vaccination in general. This attitude also moderates the influence of writing style on perceived tentativeness; the stronger one’s opposition to vaccines, the less pronounced the impact of writing style on perceived tentativeness. International Registered Report Identifier (IRRID): RR2-10.2196/41012 %M 39413215 %R 10.2196/52871 %U https://formative.jmir.org/2024/1/e52871 %U https://doi.org/10.2196/52871 %U http://www.ncbi.nlm.nih.gov/pubmed/39413215 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 8 %N %P e63035 %T Public Perceptions of Very Low Nicotine Content on Twitter: Observational Study %A Xie,Zidian %A Liu,Xinyi %A Lou,Xubin %A Li,Dongmei %+ Department of Clinical and Translational Research, University of Rochester Medical Center, 265 Crittenden Boulevard Cu 420708, Rochester, NY, 14642-0001, United States, 1 5852767285, Dongmei_Li@urmc.rochester.edu %K very low nicotine %K Twitter %K public perception %K observational study %K content analysis %D 2024 %7 4.12.2024 %9 Original Paper %J JMIR Form Res %G English %X Background: Nicotine is a highly addictive agent in tobacco products. On June 21, 2022, the US Food and Drug Administration (FDA) announced a plan to propose a rule to establish a maximum nicotine level in cigarettes and other combusted tobacco products. Objective: This study aimed to understand public perception and discussion of very low nicotine content (VLNC) on Twitter (rebranded as X in July 2023). Methods: From December 12, 2021, to January 1, 2023, we collected Twitter data using relevant keywords such as “vln,” “low nicotine,” and “reduced nicotine.” After a series of preprocessing steps (such as removing duplicates, retweets, and commercial tweets), we identified 3270 unique noncommercial tweets related to VLNC. We used an inductive method to assess the public perception and discussion of VLNC on Twitter. To establish a codebook, we randomly selected 300 tweets for hand-coding, including the attitudes (positive, neutral, and negative) toward VLNC (including its proposed rule) and major topics (13 topics). The Cohen κ statistic between the 2 human coders reached over 70%, indicating a substantial interrater agreement. The rest of the tweets were single-coded according to the codebook. Results: We observed a significant peak in the discussion of VLNC on Twitter within 4 days of the FDA’s announcement of the proposed rule on June 21, 2022. The proportion of tweets with a negative attitude toward VLNC was significantly lower than those with a positive attitude, 24.5% (801/3270) versus 37.09% (1213/3270) with P<.001 from the 2-proportion z test. Among tweets with a positive attitude, the topic “Reduce cigarette consumption or help smoking cessation” was dominant (1097/1213, 90.44%). Among tweets with a negative attitude, the topic “VLNC leads to more smoking” was the most popular topic (227/801, 28.34%), followed by “Similar toxicity of VLNC as a regular cigarette” (223/801, 27.84%), and “VLNC is not a good method for quitting smoking” (211/801, 26.34%). Conclusions: There is a more positive attitude toward VLNC than a negative attitude on Twitter, resulting from different opinions about VLNC. Discussions around VLNC mainly focused on whether VLNC could help people quit smoking. %M 39631065 %R 10.2196/63035 %U https://formative.jmir.org/2024/1/e63035 %U https://doi.org/10.2196/63035 %U http://www.ncbi.nlm.nih.gov/pubmed/39631065 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 8 %N %P e56006 %T Association of Drugs for Sale on the Internet and Official Health Indicators: Darknet Parsing and Correlational Study %A Soshnikov,Sergey %A Bekker,Svetlana %A Idrisov,Bulat %A Vlassov,Vasiliy %+ Public Health Division, School of Health Scienses, Central Michigan University, Health Professions Building, CMU, Mount Pleasant, MI, 48859, United States, 1 9897742744, soshn1s@cmich.edu %K darknet %K Internet black market %K illicit drugs %K Hydra %K marketplace %K cannabis %K opiates %K zakladka %K Bitcoin %K crypto %K public health %K overdose %K harmful drug use %K drug availability %K drug use %D 2024 %7 15.11.2024 %9 Original Paper %J JMIR Form Res %G English %X Background: Studying illicit drug circulation and its effects on population health is complicated due to the criminalization of trade and consumption. Illicit drug markets have evolved with IT, moving digital to the “darknet.” Previous research has analyzed darknet market listings and customer reviews. Research tools include public health surveys and medical reports but lack neutral data on drugs' spread and impact. This study fills this gap with an analysis of the volume of drugs traded on the darknet market. Objective: We aimed to use the dark web data and officially published indicators to identify the most vulnerable regions of Russia and the correlations between the pairs of variables to measure how illicit drug trade can affect population well-being. Methods: We web-parsed the Hydra darknet drug marketplace using Python code. The dataset encompassed 3045 individual sellers marketing 6721 unique products via 58,563 distinct postings, each representing specific quantities sold in different Russian regions during 2019. In the second stage, we collected 31 variables from official sources to compare officially collected data with darknet data about amounts and types of selling drugs in every 85 regions of Russia. The health-related data were obtained from official published sources—statistical yearbooks. Maps, diagrams, correlation matrixes, and applied observational statistical methods were used. Results: In 2019, a minimum of 124 kilograms of drugs circulated daily in small batches on the Russian darknet. Cannabis dominated the market, being 10 times more prevalent than opiates, and cannabis products' higher availability in the region is correlated with a lower incidence of opiate overdoses. The “grams of opiates in the region” variable is significantly correlated with drug overdose deaths (r=.41; P=.003), HIV-positive cases due to drug use (r=.51; P=.002), and drug court convictions in Russia (r=.39; P=.004). The study identified significant correlations between opiate sales on the darknet and higher rates of HIV among injection drug users (r=.47; P=.003). Conversely, regions with higher cannabis sales exhibited significant negative correlations with indicators of harmful drug use (r=–.52; P=.002) and its prevalence (r=–.49; P=.001). These findings suggest regional variations in drug sales on the darknet may be associated with differing public health outcomes. These indicators accurately reflect regional drug issues, though some official statistics may be incomplete or biased. Conclusions: Our findings point to varying levels of risk associated with different types of drugs sold on the darknet, but further research is needed to explore these relationships in greater depth. The study's findings highlight the importance of considering regional variations in darknet drug sales when developing public health strategies. The significant correlations between drug sales data and public health indicators suggest that region-specific interventions could be more effective in addressing the diverse challenges posed by illicit drug use. %M 39546792 %R 10.2196/56006 %U https://formative.jmir.org/2024/1/e56006 %U https://doi.org/10.2196/56006 %U http://www.ncbi.nlm.nih.gov/pubmed/39546792 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 8 %N %P e59395 %T Trends in Exercise-Related Internet Search Keywords by Sex, Age, and Lifestyle: Infodemiological Study %A Uemura,Kosuke %A Miyagami,Taiju %A Saita,Mizue %A Uchida,Takuro %A Yuasa,Shun %A Kondo,Keita %A Miura,Shun %A Matsushita,Mizuki %A Shirai,Yuka %A Misawa,Richard Baku %A Naito,Toshio %+ Department of General Medicine, Faculty of Medicine, Juntendo University, 3-1-3 Hongo Bunkyo-ku, Tokyo, 113-8421, Japan, 81 3 5802 1190, k.uemura.sh@juntendo.ac.jp %K exercise prescriptions %K sex %K age %K lifestyle %K internet search keywords %K infodemiology %K demographic %K physical activity %D 2024 %7 11.11.2024 %9 Original Paper %J JMIR Form Res %G English %X Background: Exercise prescription by physicians is beneficial for initiating or intensifying physical activity. However, providing specific exercise prescriptions is challenging; therefore, few physicians prescribe exercise. Objective: This infodemiological study aimed to understand trends in exercise-related internet search keywords based on sex, age, and environmental factors to help doctors prescribe exercise more easily. Methods: Search keyword volume was collected from Yahoo! JAPAN for 2022. Ten exercise-related terms were analyzed to assess exercise interest. Total search activities were analyzed by sex and age. Characteristic scores were based on the Japanese prefecture. By performing hierarchical cluster analysis, regional features were examined, and Kruskal-Wallis tests were used to assess relationships with population and industry data. Results: The top-searched term was “Pilates” (266,000 queries). Male individuals showed higher interest in activities such as “running” (25,400/40,700, 62.4%), “muscle training” (65,800/111,000, 59.3%), and “hiking” (23,400/40,400, 57.9%) than female individuals. Female individuals exhibited higher interest in “Pilates” (199,000/266,000, 74.8%), “yoga” (86,200/117,000, 73.7%), and “tai chi” (45,300/65,900, 68.7%) than male individuals. Based on age, search activity was highest in the 40-49 years age group for both male and female individuals across most terms. For male individuals, 7 of the 10 searched terms’ volume peaked for those in their 40s; “stretch” was most popular among those in their 50s; and “tai chi” and “radio calisthenics” had the highest search volume for those in their 70s. Female individuals in their 40s led the search volume for 9 of the 10 terms, with the exception of “tai chi,” which peaked for those in their 70s. Hierarchical cluster analysis using a characteristic score as a variable classified prefectures into 4 clusters. The characteristics of these clusters were as follows: cluster 1 had the largest population and a thriving tertiary industry, and individuals tended to search for Pilates and yoga. Following cluster 1, cluster 2, with its substantial population, had a thriving secondary industry, with searches for radio calisthenics and exercise bike. Cluster 4 had a small population, a thriving primary industry, and the lowest search volume for any term. Cluster 3 had a similar population to that of cluster 4 but had a larger secondary industry. Conclusions: Male individuals show more interest in individual activities, such as running, whereas female individuals are interested in group activities, such as Pilates. Despite the high search volume among individuals in their 40s, actual exercise habits are low among those in their 30s to 50s. Search volumes for instructor-led exercises are higher in cluster 1 than in other cluster areas, and the total number of searches decreases as the community size decreases. These results suggest that trends in search behavior depending on sex, age, and environment factors are essential when prescribing exercise for effective behavioral change. %M 39527804 %R 10.2196/59395 %U https://formative.jmir.org/2024/1/e59395 %U https://doi.org/10.2196/59395 %U http://www.ncbi.nlm.nih.gov/pubmed/39527804 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 8 %N %P e60541 %T Body Positivity, Physical Health, and Emotional Well-Being Discourse on Social Media: Content Analysis of Lizzo’s Instagram %A Albert,Stephanie L %A Massar,Rachel E %A Cassidy,Omni %A Fennelly,Kayla %A Jay,Melanie %A Massey,Philip M %A Bragg,Marie A %+ Department of Population Health, NYU Grossman School of Medicine, 180 Madison Avenue, New York, NY, 10016, United States, 1 917 689 1163, stephanie.albert@nyulangone.org %K weight stigma %K body positivity %K health at every size %K emotional well-being %K social media %K qualitative content analysis %K well-being %K social media %K influencers %K mental health outcomes %K psychological health %K body shaming %K bullying %D 2024 %7 4.11.2024 %9 Original Paper %J JMIR Form Res %G English %X Background: Weight stigma is a fundamental cause of health inequality. Body positivity may be a counterbalance to weight stigma. Social media is replete with weight-stigmatizing content and is a driver of poor mental health outcomes; however, there remains a gap in understanding its potential to mitigate the prevalence and impact of harmful messaging and to promote positive effects on a large scale. Objective: We selected musical artist Lizzo, whose brand emphasizes body positivity and empowerment, for an instrumental case study on the discourse on social media and specifically Instagram. We focused on 3 domains, including body positivity, physical health, and emotional well-being. These domains challenge social norms around weight and body size and have the potential to positively affect the physical and psychological health of people with diverse body sizes. Methods: We evaluated posts by Lizzo, comments from Instagram users, and replies to comments over a 2-month period (October 11 to December 12, 2019). Two coders rated Lizzo’s posts and Instagram users’ comments for their sentiments on the 3 domains. Replies to Instagram users’ comments were assessed for their reactions to comments (ie, did they oppose or argue against the comment or did they support or bolster the comment). Engagement metrics, including the number of “likes,” were also collected. Results: The final sample included 50 original posts by Lizzo, 250 comments from Instagram users, and 1099 replies to comments. A proportion of Lizzo’s content included body positive sentiments (34%) and emotional well-being (18%); no posts dealt explicitly with physical health. A substantial amount Instagram users’ comments and replies contained stigmatizing content including the use of nauseated and vomiting emojis, implications that Lizzo’s body was shameful and should be hidden away, accusations that she was promoting obesity, and impeachments of Lizzo’s health. In spite of the stigmatizing content, we also discovered content highlighting the beneficial nature of having positive representation of a Black woman living in a larger body who is thriving. Moreover, analysis of the discourse between users illustrated that stigmatizing expressions are being combated online, at least to some degree. Conclusions: This study demonstrates that Lizzo has exposed millions of social media users to messages about body positivity and provided more visibility for conversations about weight and shape. Future research should examine the extent to which body positive messages can lead to greater acceptance of individuals living in larger bodies. Instagram and other social media platforms should consider ways to reduce body-shaming content while finding ways to promote content that features diverse bodies. Shifting the landscape of social media could decrease stereotypes about weight and shape while increasing dialog about the need for greater acceptance and inclusion of people with diverse bodies. %M 39496156 %R 10.2196/60541 %U https://formative.jmir.org/2024/1/e60541 %U https://doi.org/10.2196/60541 %U http://www.ncbi.nlm.nih.gov/pubmed/39496156 %0 Journal Article %@ 2562-0959 %I JMIR Publications %V 7 %N %P e50408 %T Popular Skin-of-Color Dermatology Social Media Hashtags on TikTok From 2021 to 2022: Content Analysis %A Kang,Jeemin %A Szeto,Mindy D %A Suh,Lois %A Olayinka,Jadesola T %A Dellavalle,Robert P %K dermatology %K dermatologist %K social media %K TikTok %K skin of color %K hashtag %K content analysis %K education %K influencers %K diversity %K inclusion %K disparities %D 2024 %7 18.10.2024 %9 %J JMIR Dermatol %G English %X TikTok is a social media platform that can educate users about dermatology, but this longitudinal analysis of skin of color–related TikTok hashtags from 2021 to 2022 suggests that nondermatologist influencers continue to dominate content creation, highlighting the need for more participation from board-certified dermatologists to actively counter misinformation and address potential disparities in skin-of-color health care. %R 10.2196/50408 %U https://derma.jmir.org/2024/1/e50408 %U https://doi.org/10.2196/50408 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 8 %N %P e57720 %T Oral Diabetes Medication Videos on Douyin: Analysis of Information Quality and User Comment Attitudes %A Zhang,Baolu %A Kalampakorn,Surintorn %A Powwattana,Arpaporn %A Sillabutra,Jutatip %A Liu,Gang %+ Department of Public Health Nursing, Faculty of Public Health, Mahidol University, 420/1 Rajavithi Rd, Bangkok, 10400, Thailand, 66 96 646 2696, surintorn.kal@mahidol.ac.th %K diabetes %K oral diabetes medication %K information quality %K user comment attitude %K video analysis %K Douyin %D 2024 %7 18.10.2024 %9 Original Paper %J JMIR Form Res %G English %X Background: Oral diabetes medications are important for glucose management in people with diabetes. Although there are many health-related videos on Douyin (the Chinese version of TikTok), the quality of information and the effects on user comment attitudes are unclear. Objective: The purpose of this study was to analyze the quality of information and user comment attitudes related to oral diabetes medication videos on Douyin. Methods: The key phrase “oral diabetes medications” was used to search Douyin on July 24, 2023, and the final samples included 138 videos. The basic information in the videos and the content of user comments were captured using Python. Each video was assigned a sentiment category based on the predominant positive, neutral, or negative attitude, as analyzed using the Weiciyun website. Two independent raters assessed the video content and information quality using the DISCERN (a tool for assessing health information quality) and PEMAT-A/V (Patient Education Materials Assessment Tool for Audiovisual Materials) instruments. Results: Doctors were the main source of the videos (136/138, 98.6%). The overall information quality of the videos was acceptable (median 3, IQR 1). Videos on Douyin showed relatively high understandability (median 75%, IQR 16.6%) but poor actionability (median 66.7%, IQR 48%). Most content on oral diabetes medications on Douyin related to the mechanism of action (75/138, 54.3%), precautions (70/138, 50.7%), and advantages (68/138, 49.3%), with limited content on indications (19/138, 13.8%) and contraindications (14/138, 10.1%). It was found that 10.1% (14/138) of the videos contained misinformation, of which 50% (7/14) were about the method of administration. Regarding user comment attitudes, the majority of videos garnered positive comments (81/138, 58.7%), followed by neutral comments (46/138, 33.3%) and negative comments (11/138, 8%). Multinomial logistic regression revealed 2 factors influencing a positive attitude: user comment count (adjusted odds ratio [OR] 1.00, 95% CI 1.00-1.00; P=.02) and information quality of treatment choices (adjusted OR 1.49, 95% CI 1.09-2.04; P=.01). Conclusions: Despite most videos on Douyin being posted by doctors, with generally acceptable information quality and positive user comment attitudes, some content inaccuracies and poor actionability remain. Users show more positive attitudes toward videos with high-quality information about treatment choices. This study suggests that health care providers should ensure the accuracy and actionability of video content, enhance the information quality of treatment choices of oral diabetes medications to foster positive user attitudes, help users access accurate health information, and promote medication adherence. %M 39423367 %R 10.2196/57720 %U https://formative.jmir.org/2024/1/e57720 %U https://doi.org/10.2196/57720 %U http://www.ncbi.nlm.nih.gov/pubmed/39423367 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 8 %N %P e52977 %T Seasonal and Weekly Patterns of Korean Adolescents’ Web Search Activity on Insomnia: Retrospective Study %A Baek,Kwangyeol %A Jeong,Jake %A Kim,Hyun-Woo %A Shin,Dong-Hyeon %A Kim,Jiyoung %A Lee,Gha-Hyun %A Cho,Jae Wook %+ Department of Neurology, Pusan National University Yangsan Hospital, Pusan National University School of Medicine, Mulgeum up, 20 Geumo-ro, Yangsan, 50612, Republic of Korea, 82 553602122, sleepcho@pusan.ac.kr %K insomnia %K sleep %K internet search %K adolescents %K school %K seasonal %K weekly %K NAVER %K infodemiology %K inforveillance %D 2024 %7 11.10.2024 %9 Original Paper %J JMIR Form Res %G English %X Background: Sleep deprivation in adolescents is a common but serious public health issue. Adolescents often have a progressive circadian delay and suffer from insufficient sleep during weekdays due to the school schedule. Temporal patterns in internet search activity data can provide relevant information for understanding the characteristic sleep problems of the adolescent population. Objective: We aimed to reveal whether adolescents exhibit distinct temporal seasonal and weekly patterns in internet search activity on insomnia compared to adults. Methods: We hypothesized that adolescents exhibit larger variations in the internet search volume for insomnia, particularly in association with the school schedule (e.g., academic vacations and weekends). We extracted the daily search volume for insomnia in South Korean adolescents (13-18 years old), adults (19-59 years old), and young adults (19-24 years old) during the years 2016-2019 using NAVER DataLab, the most popular search engine in South Korea. The daily search volume data for each group were normalized with the annual median of each group. The time series of the search volume was decomposed into slow fluctuation (over a year) and fast fluctuation (within a week) using fast Fourier transform. Next, we compared the normalized search volume across months in a year (slow fluctuation) and days in a week (fast fluctuation). Results: In the annual trend, 2-way ANOVA revealed a significant (group) × (month) interaction (P<.001). Adolescents exhibited much greater seasonal variations across a year than the adult population (coefficient of variation=0.483 for adolescents vs 0.131 for adults). The search volume for insomnia in adolescents was notably higher in January, February, and August, which are academic vacation periods in South Korea (P<.001). In the weekly pattern, 2-way ANOVA revealed a significant (group) × (day) interaction (P<.001). Adolescents showed a considerably increased search volume on Sunday and Monday (P<.001) compared to adults. In contrast, young adults demonstrated seasonal and weekly patterns similar to adults. Conclusions: Adolescents demonstrate distinctive seasonal and weekly patterns in internet searches on insomnia (ie, increased search in vacation months and weekend–weekday transitions), which are closely associated with the school schedule. Adolescents’ sleep concerns might be potentially affected by the disrupted daily routine and the delayed sleep phase during vacations and weekends. As we demonstrated, comparing various age groups in infodemiology and infoveillance data might be helpful in identifying distinctive features in vulnerable age groups. %M 39311496 %R 10.2196/52977 %U https://formative.jmir.org/2024/1/e52977 %U https://doi.org/10.2196/52977 %U http://www.ncbi.nlm.nih.gov/pubmed/39311496 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 8 %N %P e56371 %T Public Perceptions of the Food and Drug Administration's Regulatory Authority Over Synthetic Nicotine on Twitter: Observational Study %A Zou,Jonathan %A Feliciano,Juan Ramon %A Xie,Zidian %A Li,Dongmei %+ Department of Clinical and Translational Research, University of Rochester Medical Center, 265 Crittenden Boulevard Cu 420708, Rochester, NY, 14642-0708, United States, 1 5852767285, Dongmei_Li@urmc.rochester.edu %K FDA %K synthetic nicotine %K omnibus %K Twitter %K Food and Drug Administration %D 2024 %7 19.9.2024 %9 Original Paper %J JMIR Form Res %G English %X Background: The Omnibus Budget Bill, known as H. R. 2471, passed through Congress on March 10, 2022, and was eventually signed by President Biden on March 15, 2022. This bill amended the Federal Food, Drug, and Cosmetic Act granting the Food and Drug Administration (FDA) regulatory authority over synthetic nicotine. Objective: This study aims to examine the public perceptions of the Omnibus Bill that regulates synthetic nicotine products as tobacco products on Twitter (rebranded as X). Methods: Through the X streaming application programming interface, we collected and identified 964 tweets related to the Omnibus Bill on synthetic nicotine between March 8, 2022, and April 13, 2022. The longitudinal trend was used to examine the discussions related to the bill over time. An inductive method was used for the content analysis of related tweets. By hand-coding 200 randomly selected tweets by 2 human coders respectively with high interrater reliability, the codebook was developed for relevance, major topics, and attitude to the bill, which was used to single-code the rest of the tweets. Results: Between March 8, 2022, and April 13, 2022, we identified 964 tweets related to the Omnibus Bill regulating synthetic nicotine. Our longitudinal trend analysis showed a spike in the number of tweets related to the bill during the immediate period following the bill’s introduction, with roughly half of the tweets identified being posted between March 8 and 11, 2022. A majority of the tweets (497/964, 51.56%) had a negative sentiment toward the bill, while a much smaller percentage of tweets (164/964, 17.01%) had a positive sentiment toward the bill. Around 31.43% (303/964) of all tweets were categorized as objective news or questions about the bill. The most popular topic for opposing the bill was users believing that this bill would lead users back to smoking (145/497, 29.18%), followed by negative implications for small vape businesses (122/497, 24.55%) and government or FDA mistrust (94/497, 18.91%). The most popular topic for supporting the bill was that this bill would take a dangerous tobacco product targeted at teens off the market (94/164, 57.32%). Conclusions: We observed a more negative sentiment toward the bill on X, largely due to users believing it would lead users back to smoking and negatively impact small vape businesses. This study provides insight into public perceptions and discussions of this bill on X and adds valuable information for future regulations on alternative nicotine products. %M 39298747 %R 10.2196/56371 %U https://formative.jmir.org/2024/1/e56371 %U https://doi.org/10.2196/56371 %U http://www.ncbi.nlm.nih.gov/pubmed/39298747 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 8 %N %P e54025 %T Japanese Perception of Brain Death and Implications for New Medical Technologies: Quantitative and Qualitative Social Media Analysis %A Vargas Meza,Xanat %A Oikawa,Masanori %+ Institute for the Advanced Study of Human Biology, Faculty of Medicine, Kyoto University, Building B, Yoshida-Konoe-cho, Sakyo-ku, Kyoto, 606-8501, Japan, 81 75 753 9882, vargasmeza.xanat.8z@kyoto-u.ac.jp %K brain death %K Japan %K social media %K multidimensional analysis %K Twitter %K YouTube %D 2024 %7 18.9.2024 %9 Original Paper %J JMIR Form Res %G English %X Background: Brain death has been used to decide whether to keep sustained care and treatment. It can facilitate tissue, organ, and body donation for several purposes, such as transplantation and medical education and research. In Japan, brain death has strict diagnostic criteria and family consent is crucial, but it has been a challenging concept for the public since its introduction, including knowledge and communication issues. Objective: We analyzed data across YouTube and Twitter in Japan to uncover actors and assess the quality of brain death communication, providing recommendations to communicate new medical technologies. Methods: Using the keyword “脳死” (brain death), we collected recent data from YouTube and Twitter, classifying the data into 5 dimensions: time, individuality (type of users), place, activity, and relations (hyperlinks). We employed a scale to evaluate brain death information quality. We divided YouTube videos into 3 groups and assessed their differences through statistical analysis. We also provided a text-based analysis of brain death–related narratives. Results: Most videos (20/61, 33%) were uploaded in 2019, while 10,892 tweets peaked between July 3 and 9, 2023, and June 12 and 18, 2023. Videos about brain death were mostly uploaded by citizens (18/61, 27%), followed by media (13/61, 20%) and unknown actors (10/61, 15%). On the other hand, most identified users in a random sample of 100 tweets were citizens (73/100, 73%), and the top 10 retweeted and liked tweets were also mostly authored by citizens (75/100, 75%). No specific information on location was uncovered. Information videos contained guides for accreditation of the National Nursing Exam and religious points of view, while misinformation videos mostly contained promotions by spirituality actors and webtoon artists. Some tweets involved heart transplantation and patient narratives. Most hyperlinks pointed to YouTube and Twitter. Conclusions: Brain death has become a common topic in everyday life, with some actors disseminating high-quality information, others disseminating no medical information, and others disseminating misinformation. Recommendations include partnering with interested actors, discussing medical information in detail, and teaching people to recognize pseudoscience. %M 39291895 %R 10.2196/54025 %U https://formative.jmir.org/2024/1/e54025 %U https://doi.org/10.2196/54025 %U http://www.ncbi.nlm.nih.gov/pubmed/39291895 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 8 %N %P e46531 %T The Portrayal of Cesarean Section on Instagram: Mixed Methods Social Media Analysis %A Zahroh,Rana Islamiah %A Cheong,Marc %A Hazfiarini,Alya %A Vazquez Corona,Martha %A Ekawati,Fitriana Murriya %A Emilia,Ova %A Homer,Caroline SE %A Betrán,Ana Pilar %A Bohren,Meghan A %+ Gender and Women’s Health Unit, Nossal Institute for Global Health, School of Population and Global Health, University of Melbourne, 207 Bouverie Street, Carlton, Victoria, 3053, Australia, 61 481386220, r.zahroh@unimelb.edu.au %K cesarean section %K social media analysis %K maternal health %K childbirth %K mode of birth %K instagram %D 2024 %7 6.9.2024 %9 Original Paper %J JMIR Form Res %G English %X Background: Cesarean section (CS) rates in Indonesia are rapidly increasing for both sociocultural and medical reasons. However, there is limited understanding of the role that social media plays in influencing preferences regarding mode of birth (vaginal or CS). Social media provides a platform for users to seek and exchange information, including information on the mode of birth, which may help unpack social influences on health behavior. Objective: This study aims to explore how CS is portrayed on Instagram in Indonesia. Methods: We downloaded public Instagram posts from Indonesia containing CS hashtags and extracted their attributes (image, caption, hashtags, and objects and texts within images). Posts were divided into 2 periods—before COVID-19 and during COVID-19—to examine changes in CS portrayal during the pandemic. We used a mixed methods approach to analysis using text mining, descriptive statistics, and qualitative content analysis. Results: A total of 9978 posts were analyzed quantitatively, and 720 (7.22%) posts were sampled and analyzed qualitatively. The use of text (527/5913, 8.91% vs 242/4065, 5.95%; P<.001) and advertisement materials (411/5913, 6.95% vs 83/4065, 2.04%; P<.001) increased during the COVID-19 pandemic compared to before the pandemic, indicating growth of information sharing on CS over time. Posts with CS hashtags primarily promoted herbal medicine for faster recovery and services for choosing auspicious childbirth dates, encouraging elective CS. Some private health facilities offered discounts on CS for special events such as Mother’s Day and promoted techniques such as enhanced recovery after CS for comfortable, painless birth, and faster recovery after CS. Hashtags related to comfortable or painless birth (2358/5913, 39.88% vs 278/4065, 6.84%; P<.001), enhanced recovery after CS (124/5913, 2.1% vs 0%; P<.001), feng shui services (110/5913, 1.86% vs 56/4065, 1.38%; P=.03), names of health care providers (2974/5913, 50.3% vs 304/4065, 7.48%; P<.001), and names of hospitals (1460/5913, 24.69% vs 917/4065, 22.56%; P=.007) were more prominent during compared to before the pandemic. Conclusions: This study highlights the necessity of enforcing advertisement regulations regarding birth-related medical services in the commercial and private sectors. Enhanced health promotion efforts are crucial to ensure that women receive accurate, balanced, and appropriate information about birth options. Continuous and proactive health information dissemination from government organizations is essential to counteract biases favoring CS over vaginal birth. %M 39241228 %R 10.2196/46531 %U https://formative.jmir.org/2024/1/e46531 %U https://doi.org/10.2196/46531 %U http://www.ncbi.nlm.nih.gov/pubmed/39241228 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 8 %N %P e51513 %T The Quality of Short Videos as a Source of Coronary Heart Disease Information on TikTok: Cross-Sectional Study %A Gong,Xun %A Chen,Meijuan %A Ning,Lihong %A Zeng,Lingzhong %A Dong,Bo %+ Department of Cardiology and Cardiac Rehabilitation Center, Hunan Provincial People's Hospital (The First Affiliated Hospital of Hunan Normal University), No.61 West Jiefang Road, Furong District, Changsha, China, 86 18874832298, dt2008bj@sina.com %K coronary heart disease %K content quality %K social media %K short-video platform %K TikTok %D 2024 %7 3.9.2024 %9 Original Paper %J JMIR Form Res %G English %X Background: Coronary heart disease (CHD) is a leading cause of death worldwide and imposes a significant economic burden. TikTok has risen as a favored platform within the social media sphere for disseminating CHD-related information and stands as a pivotal resource for patients seeking knowledge about CHD. However, the quality of such content on TikTok remains largely unexplored. Objective: This study aims to assess the quality of information conveyed in TikTok CHD-related videos. Methods: A comprehensive cross-sectional study was undertaken on TikTok videos related to CHD. The sources of the videos were identified and analyzed. The comprehensiveness of content was assessed through 6 questions addressing the definition, signs and symptoms, risk factors, evaluation, management, and outcomes. The quality of the videos was assessed using 3 standardized evaluative instruments: DISCERN, the Journal of the American Medical Association (JAMA) benchmarks, and the Global Quality Scale (GQS). Furthermore, correlative analyses between video quality and characteristics of the uploaders and the videos themselves were conducted. Results: The search yielded 145 CHD-related videos from TikTok, predominantly uploaded by health professionals (n=128, 88.3%), followed by news agencies (n=6, 4.1%), nonprofit organizations (n=10, 6.9%), and for-profit organizations (n=1, 0.7%). Content comprehensiveness achieved a median score of 3 (IQR 2-4). Median values for the DISCERN, JAMA, and GQS evaluations across all videos stood at 27 (IQR 24-32), 2 (IQR 2-2), and 2 (IQR 2-3), respectively. Videos from health professionals and nonprofit organizations attained significantly superior JAMA scores in comparison to those of news agencies (P<.001 and P=.02, respectively), whereas GQS scores for videos from health professionals were also notably higher than those from news agencies (P=.048). Within health professionals, cardiologists demonstrated discernibly enhanced performance over noncardiologists in both DISCERN and GQS assessments (P=.02). Correlative analyses unveiled positive correlations between video quality and uploader metrics, encompassing the positive correlations between the number of followers; total likes; average likes per video; and established quality indices such as DISCERN, JAMA, or GQS scores. Similar investigations relating to video attributes showed correlations between user engagement factors—likes, comments, collections, shares—and the aforementioned quality indicators. In contrast, a negative correlation emerged between the number of days since upload and quality indices, while a longer video duration corresponded positively with higher DISCERN and GQS scores. Conclusions: The quality of the videos was generally poor, with significant disparities based on source category. The content comprehensiveness coverage proved insufficient, casting doubts on the reliability and quality of the information relayed through these videos. Among health professionals, video contributions from cardiologists exhibited superior quality compared to noncardiologists. As TikTok’s role in health information dissemination expands, ensuring accurate and reliable content is crucial to better meet patients’ needs for CHD information that conventional health education fails to fulfill. %M 39226540 %R 10.2196/51513 %U https://formative.jmir.org/2024/1/e51513 %U https://doi.org/10.2196/51513 %U http://www.ncbi.nlm.nih.gov/pubmed/39226540 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 8 %N %P e48389 %T Investigating Topical Steroid Withdrawal Videos on TikTok: Cross-Sectional Analysis of the Top 100 Videos %A Haddad,Firas %A Abou Shahla,William %A Saade,Dana %+ Department of Dermatology, American University of Beirut Medical Center, Bliss Street, Beirut, 1107 2020, Lebanon, 961 1350000 ext 5333, ds45@aub.edu.lb %K steroid withdrawal %K medical dermatology %K drug response %K social media %K videos %K TikTok %K steroids %K content analysis %K information quality %K skin %K topical %K dermatology %K misinformation %D 2024 %7 29.8.2024 %9 Original Paper %J JMIR Form Res %G English %X Background: Social media platforms like TikTok are a very popular source of information, especially for skin diseases. Topical steroid withdrawal (TSW) is a condition that is yet to be fully defined and understood. This did not stop the hashtag #topicalsteroidwithdrawal from amassing more than 600 million views on TikTok. It is of utmost importance to assess the quality and content of TikTok videos on TSW to prevent the spread of misinformation. Objective: This study aims to assess the quality and content of the top 100 videos dedicated to the topic of TSW on TikTok. Methods: This observational study assesses the content and quality of the top 100 videos about TSW on TikTok. A total of 3 independent scoring systems: DISCERN, Journal of the American Medical Association, and Global Quality Scale were used to assess the video quality. The content of the videos was coded by 2 reviewers and analyzed for recurrent themes and topics. Results: This study found that only 10.0% (n=10) of the videos clearly defined what TSW is. Videos were predominantly posted by White, middle-aged, and female creators. Neither cause nor mechanism of the disease were described in the videos. The symptoms suggested itching, peeling, and dryness which resembled the symptoms of atopic dermatitis. The videos fail to mention important information regarding the use of steroids such as the reason it was initially prescribed, the name of the drug, concentration, mechanism of usage, and method of discontinuation. Management techniques varied from hydration methods approved for treatment of atopic dermatitis to treatment options without scientific evidence. Overall, the videos had immense reach with over 200 million views, 45 million likes, 90,000 comments, and 100,000 shares. Video quality was poor with an average DISCERN score of 1.63 (SD 0.56)/5. Video length, total view count, and views/day were all associated with increased quality, indicating that patients were interacting more with higher quality videos. However, videos were created exclusively by personal accounts, highlighting the absence of dermatologists on the platform to discuss this topic. Conclusions: The videos posted on TikTok are of low quality and lack pertinent information. The content is varied and not consistent. Health care professionals, including dermatologists and residents in the field, need to be more active on the topic, to spread proper information and prevent an increase in steroid phobia. Health care professionals are encouraged to ride the wave and produce high-quality videos discussing what is known about TSW to avoid the spread of misinformation. %M 39208411 %R 10.2196/48389 %U https://formative.jmir.org/2024/1/e48389 %U https://doi.org/10.2196/48389 %U http://www.ncbi.nlm.nih.gov/pubmed/39208411 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 8 %N %P e55535 %T Evaluation of the Quality and Readability of Web-Based Information Regarding Foreign Bodies of the Ear, Nose, and Throat: Qualitative Content Analysis %A Ko,Tsz Ki %A Tan,Denise Jia Yun %A Fan,Ka Siu %+ Department of Surgery, Royal Stoke Hospital, Newcastle Road, Stoke, United Kingdom, 44 7378977812, tszkiko95@gmail.com %K foreign body %K quality of internet information %K readability of internet information %K EQIP %K Ensuring Quality Information for Patients %K medical informatics %K readability %K readable %K health information %K online information %K information resource %K information resources %K website %K websites %K quality %K evaluation %K evaluations %K reading level %K grade level %D 2024 %7 15.8.2024 %9 Original Paper %J JMIR Form Res %G English %X Background: Foreign body (FB) inhalation, ingestion, and insertion account for 11% of emergency admissions for ear, nose, and throat conditions. Children are disproportionately affected, and urgent intervention may be needed to maintain airway patency and prevent blood vessel occlusion. High-quality, readable online information could help reduce poor outcomes from FBs. Objective: We aim to evaluate the quality and readability of available online health information relating to FBs. Methods: In total, 6 search phrases were queried using the Google search engine. For each search term, the first 30 results were captured. Websites in the English language and displaying health information were included. The provider and country of origin were recorded. The modified 36-item Ensuring Quality Information for Patients tool was used to assess information quality. Readability was assessed using a combination of tools: Flesch Reading Ease score, Flesch-Kincaid Grade Level, Gunning-Fog Index, and Simple Measure of Gobbledygook. Results: After the removal of duplicates, 73 websites were assessed, with the majority originating from the United States (n=46, 63%). Overall, the quality of the content was of moderate quality, with a median Ensuring Quality Information for Patients score of 21 (IQR 18-25, maximum 29) out of a maximum possible score of 36. Precautionary measures were not mentioned on 41% (n=30) of websites and 30% (n=22) did not identify disk batteries as a risky FB. Red flags necessitating urgent care were identified on 95% (n=69) of websites, with 89% (n=65) advising patients to seek medical attention and 38% (n=28) advising on safe FB removal. Readability scores (Flesch Reading Ease score=12.4, Flesch-Kincaid Grade Level=6.2, Gunning-Fog Index=6.5, and Simple Measure of Gobbledygook=5.9 years) showed most websites (56%) were below the recommended sixth-grade level. Conclusions: The current quality and readability of information regarding FBs is inadequate. More than half of the websites were above the recommended sixth-grade reading level, and important information regarding high-risk FBs such as disk batteries and magnets was frequently excluded. Strategies should be developed to improve access to high-quality information that informs patients and parents about risks and when to seek medical help. Strategies to promote high-quality websites in search results also have the potential to improve outcomes. %M 39145998 %R 10.2196/55535 %U https://formative.jmir.org/2024/1/e55535 %U https://doi.org/10.2196/55535 %U http://www.ncbi.nlm.nih.gov/pubmed/39145998 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 8 %N %P e48284 %T Effects of Intervention Timing on Health-Related Fake News: Simulation Study %A Gwon,Nahyun %A Jeong,Wonjeong %A Kim,Jee Hyun %A Oh,Kyoung Hee %A Jun,Jae Kwan %+ Cancer Knowledge and Information Center, National Cancer Control Institute, National Cancer Center, 323 Ilsan-ro, Ilsandong-gu, Goyang, 10408, Republic of Korea, 82 31 920 2184, jkjun@ncc.re.kr %K disinformation %K fenbendazole %K cancer information %K simulation %K fake news %K online social networking %K misinformation %K lung cancer %D 2024 %7 7.8.2024 %9 Original Paper %J JMIR Form Res %G English %X Background: Fake health-related news has spread rapidly through the internet, causing harm to individuals and society. Despite interventions, a fenbendazole scandal recently spread among patients with lung cancer in South Korea. It is crucial to intervene appropriately to prevent the spread of fake news. Objective: This study investigated the appropriate timing of interventions to minimize the side effects of fake news. Methods: A simulation was conducted using the susceptible-infected-recovered (SIR) model, which is a representative model of the virus spread mechanism. We applied this model to the fake news spread mechanism. The parameters were set similarly to those in the digital environment, where the fenbendazole scandal occurred. NetLogo, an agent-based model, was used as the analytical tool. Results: Fake news lasted 278 days in the absence of interventions. As a result of adjusting and analyzing the timing of the intervention in response to the fenbendazole scandal, we found that faster intervention leads to a shorter duration of fake news (intervention at 54 days = fake news that lasted for 210 days; intervention at 16 days = fake news that lasted for 187 days; and intervention at 10 days = fake news that lasted for 157 days). However, no significant differences were observed when the intervention was performed within 10 days. Conclusions: Interventions implemented within 10 days were effective in reducing the duration of the spread of fake news. Our findings suggest that timely intervention is critical for preventing the spread of fake news in the digital environment. Additionally, a monitoring system that can detect fake news should be developed for a rapid response %M 39109788 %R 10.2196/48284 %U https://formative.jmir.org/2024/1/e48284 %U https://doi.org/10.2196/48284 %U http://www.ncbi.nlm.nih.gov/pubmed/39109788 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 8 %N %P e51327 %T Public Perceptions and Discussions of the US Food and Drug Administration's JUUL Ban Policy on Twitter: Observational Study %A Liu,Pinxin %A Lou,Xubin %A Xie,Zidian %A Shang,Ce %A Li,Dongmei %+ Department of Clinical and Translational Research, University of Rochester Medical Center, 265 Crittenden Boulevard CU 420708, Rochester, NY, 14642-0708, United States, 1 5852767285, Dongmei_Li@urmc.rochester.edu %K e-cigarettes %K JUUL %K Twitter %K deep learning %K FDA %K Food and Drug Administration %K vape %K vaping %K smoking %K social media %K regulation %D 2024 %7 11.7.2024 %9 Original Paper %J JMIR Form Res %G English %X Background: On June 23, 2022, the US Food and Drug Administration announced a JUUL ban policy, to ban all vaping and electronic cigarette products sold by Juul Labs. Objective: This study aims to understand public perceptions and discussions of this policy using Twitter (subsequently rebranded as X) data. Methods: Using the Twitter streaming application programming interface, 17,007 tweets potentially related to the JUUL ban policy were collected between June 22, 2022, and July 25, 2022. Based on 2600 hand-coded tweets, a deep learning model (RoBERTa) was trained to classify all tweets into propolicy, antipolicy, neutral, and irrelevant categories. A deep learning model (M3 model) was used to estimate basic demographics (such as age and gender) of Twitter users. Furthermore, major topics were identified using latent Dirichlet allocation modeling. A logistic regression model was used to examine the association of different Twitter users with their attitudes toward the policy. Results: Among 10,480 tweets related to the JUUL ban policy, there were similar proportions of propolicy and antipolicy tweets (n=2777, 26.5% vs n=2666, 25.44%). Major propolicy topics included “JUUL causes youth addition,” “market surge of JUUL,” and “health effects of JUUL.” In contrast, major antipolicy topics included “cigarette should be banned instead of JUUL,” “against the irrational policy,” and “emotional catharsis.” Twitter users older than 29 years were more likely to be propolicy (have a positive attitude toward the JUUL ban policy) than those younger than 29 years. Conclusions: Our study showed that the public showed different responses to the JUUL ban policy, which varies depending on the demographic characteristics of Twitter users. Our findings could provide valuable information to the Food and Drug Administration for future electronic cigarette and other tobacco product regulations. %M 38990633 %R 10.2196/51327 %U https://formative.jmir.org/2024/1/e51327 %U https://doi.org/10.2196/51327 %U http://www.ncbi.nlm.nih.gov/pubmed/38990633 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 8 %N %P e56755 %T Barriers to, and Facilitators of, Checking Drugs for Adulterants in the Era of Fentanyl and Xylazine: Qualitative Study %A Aronson,Ian David %A Ardouin-Guerrier,Mary-Andrée %A Baus,Juan Esteban %A Bennett,Alex S %+ Center for Technology-based Education and Community Health, NDRI-USA, 31 W 34th St Suite 8006, New York, NY, 10001, United States, 1 212 845 4444, aronson@ndri-usa.org %K overdose %K overdoses %K fentanyl %K xylazine %K benzodiazepines %K adulterants %K drug %K drugs %K substance %K substances %K illicit drug %K illicit drugs %K drug test %K drug testing %K drug checking %K qualitative %K interview %K interviews %K digital health %K digital technology %K digital intervention %K digital interventions %K technological intervention %K technological interventions %K technology-based intervention %K technology-based interventions %D 2024 %7 3.7.2024 %9 Original Paper %J JMIR Form Res %G English %X Background: Overdose deaths continue to reach new records in New York City and nationwide, largely driven by adulterants such as fentanyl and xylazine in the illicit drug supply. Unknowingly consuming adulterated substances dramatically increases risks of overdose and other health problems, especially when individuals consume multiple adulterants and are exposed to a combination of drugs they did not intend to take. Although test strips and more sophisticated devices enable people to check drugs for adulterants including fentanyl and xylazine prior to consumption and are often available free of charge, many people who use drugs decline to use them. Objective: We sought to better understand why people in the New York City area do or do not check drugs before use. We plan to use study findings to inform the development of technology-based interventions to encourage consistent drug checking. Methods: In summer 2023, team members who have experience working with people who use drugs conducted 22 semistructured qualitative interviews with a convenience sample of people who reported illicit drug use within the past 90 days. An interview guide examined participants’ knowledge of and experience with adulterants including fentanyl, xylazine, and benzodiazepines; using drug testing strips; and whether they had ever received harm reduction services. All interviews were audio recorded, transcribed, and analyzed for emerging themes. Results: Most participants lacked knowledge of adulterants, and only a few reported regularly checking drugs. Reasons for not checking included lacking convenient access to test supplies, or a place to check samples out of the public’s view, as well as time considerations. Some participants also reported a strong belief that they were not at risk from fentanyl, xylazine, or other adulterants because they exclusively used cocaine or crack, or that they were confident the people they bought drugs from would not sell them adulterated substances. Those who did report testing their drugs described positive interactions with harm reduction agency staff. Conclusions: New forms of outreach are needed not only to increase people’s knowledge of adulterated substances and awareness of the increasing risks they pose but also to encourage people who use drugs to regularly check their substances prior to use. This includes new intervention messages that highlight the importance of drug checking in the context of a rapidly changing and volatile drug supply. This messaging can potentially help normalize drug checking as an easily enacted behavior that benefits public health. To increase effectiveness, messages can be developed with, and outreach can be conducted by, trusted community members including people who use drugs and, potentially, people who sell drugs. Pairing this messaging with access to no-cost drug-checking supplies and equipment may help address the ongoing spiral of increased overdose deaths nationwide. %M 38959505 %R 10.2196/56755 %U https://formative.jmir.org/2024/1/e56755 %U https://doi.org/10.2196/56755 %U http://www.ncbi.nlm.nih.gov/pubmed/38959505 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 8 %N %P e54587 %T Availability of Alcohol on an Online Third-Party Delivery Platform Across London Boroughs, England: Exploratory Cross-Sectional Study %A Sharpe,Casey %A Bhuptani,Saloni %A Jecks,Mike %A Sheron,Nick %A Henn,Clive %A Burton,Robyn %+ Institute for Social Marketing and Health, University of Stirling, Stirling, FK9 4LA, United Kingdom, 44 7595 417304, robyn.burton@stir.ac.uk %K alcohol %K availability %K online %K third-party delivery platforms %K England %K cross-sectional study %K exploratory %K licensing %K public health %K policy %D 2024 %7 28.6.2024 %9 Short Paper %J JMIR Form Res %G English %X Background: Higher availability of alcohol is associated with higher levels of alcohol consumption and harm. Alcohol is increasingly accessible online, with rapid delivery often offered by a third-party driver. Remote delivery and online availability are important from a public health perspective, but to date, relatively little research has explored the availability of alcohol offered by online platforms. Objective: This cross-sectional exploratory study describes the availability of alcohol on the third-party platform Deliveroo within London, England. Methods: We extracted the number of outlets offering alcohol on Deliveroo for each London borough and converted these into crude rates per 1000 population (18-64 years). Outlets were grouped as outlets exclusively selling alcohol, off-licenses, and premium. We calculated Pearson correlation coefficients to explore the association between borough’s crude rate of outlets per 1000 population and average Indices of Multiple Deprivation (IMD) 2019 scores. We extracted the number of outlets also selling tobacco or e-cigarettes and used non-Deliveroo drivers. We searched addresses of the top 20 outlets delivering to the most boroughs by outlet type (60 total) to determine their associated premise. Results: We identified 4277 total Deliveroo-based outlets offering alcohol across London, including outlets delivering in multiple boroughs. The crude rate of outlets per 1000 population aged 18-64 years was 0.73 and ranged from 0.22 to 2.29 per borough. Most outlets exclusively sold alcohol (3086/4277, 72.2%), followed by off-licenses (770/4277, 18.0%) and premium (421/4277, 9.8%). The majority of outlets exclusively selling alcohol sold tobacco or e-cigarettes (2951/3086, 95.6%) as did off-licenses to a lesser extent (588/770, 76.4%). Most outlets exclusively offering alcohol used drivers not employed by Deliveroo (2887/3086, 93.6%), and the inverse was true for premium outlets (50/421, 11.9%) and off-licenses (73/770, 9.5%). There were 1049 unique outlets, of which 396 (37.8%) were exclusively offering alcohol—these outlets tended to deliver across multiple boroughs unlike off-licenses and premium outlets. Of outlets with confirmed addresses, self-storage units were listed as the associated premise for 85% (17/20) of outlets exclusively offering alcohol, 11% (2/19) of off-licenses, and 12% (2/17) of premium outlets. We found no significant relationship between borough IMD scores and crude rate of outlets per 1000 population overall (P=.87) or by any outlet type: exclusively alcohol (P=.41), off-license (P=.58), and premium (P=.18). Conclusions: London-based Deliveroo outlets offering alcohol are common and are sometimes operating from self-storage units that have policies prohibiting alcohol storage. This and the potential for increased alcohol accessibility online have implications for public health given the relationship between alcohol’s availability and consumption or harm. There is a need to ensure that regulations for delivery are adequate for protecting children and vulnerable adults. The Licensing Act 2003 may require modernization in the digital age. Future research must explore a relationship between online alcohol availability and deprivation. %M 38941596 %R 10.2196/54587 %U https://formative.jmir.org/2024/1/e54587 %U https://doi.org/10.2196/54587 %U http://www.ncbi.nlm.nih.gov/pubmed/38941596 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 8 %N %P e51094 %T Mediterranean Diet Information on TikTok and Implications for Digital Health Promotion Research: Social Media Content Analysis %A Raber,Margaret %A Allen,Haley %A Huang,Sophia %A Vazquez,Maria %A Warner,Echo %A Thompson,Debbe %+ Department of Health Disparities Research, MD Anderson Cancer Center, 1400 Pressler Street Dr., Houston, TX, 77030, United States, 1 713 702 4801, mpraber@mdanderson.org %K misinformation %K social media %K Mediterranean Diet %K content analysis %K health communication %K communication %K TikTok %K diet %K cardiometabolic disease %K cardiometabolic %K consumer %K eating %K social media %K quality %K mHealth %K mobile health %K digital health %K promotion research %K nutrition therapy %K healthy diet %D 2024 %7 19.6.2024 %9 Original Paper %J JMIR Form Res %G English %X Background: The Mediterranean diet has been linked to reduced risk for several cardiometabolic diseases. The lack of a clear definition of the Mediterranean diet in the scientific literature and the documented proliferation of nutrition misinformation on the internet suggest the potential for confusion among consumers seeking web-based Mediterranean diet information. Objective: We conducted a social media content analysis of information about the Mediterranean diet on the influential social media platform, TikTok, to examine public discourse about the diet and identify potential areas of misinformation. We then analyzed these findings in the context of health promotion to identify potential challenges and opportunities for the use of TikTok in promoting the Mediterranean diet for healthy living. Methods: The first-appearing 202 TikTok posts that resulted from a search of the hashtag #mediterraneandiet were downloaded and qualitatively examined. Post features and characteristics, poster information, and engagement metrics were extracted and synthesized across posts. Posts were categorized as those created by health professionals and those created by nonhealth professionals based on poster-reported credentials. In addition to descriptive statistics of the entire sample, we compared posts created by professionals and nonprofessionals for content using chi-square tests. Results: TikTok posts varied in content, but posts that were developed by health professionals versus nonprofessionals were more likely to offer a definition of the Mediterranean diet (16/106, 15.1% vs 2/96, 2.1%; P=.001), use scientific citations to support claims (26/106, 24.5% vs 0/96, 0%; P<.001), and discuss specific nutrients (33/106, 31.1% vs 6/96, 6.3%; P<.001) and diseases related to the diet (27/106, 25.5% vs 5/96, 5.2%; P<.001) compared to posts created by nonhealth professionals. Conclusions: Social media holds promise as a venue to promote the Mediterranean diet, but the variability in information found in this study highlights the need to create clear definitions about the diet and its components when developing Mediterranean diet interventions that use new media structures. %M 38896841 %R 10.2196/51094 %U https://formative.jmir.org/2024/1/e51094 %U https://doi.org/10.2196/51094 %U http://www.ncbi.nlm.nih.gov/pubmed/38896841 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 8 %N %P e54023 %T Illicit Trade of Prescription Medications Through X (Formerly Twitter) in Japan: Cross-Sectional Study %A Hakariya,Hayase %A Yokoyama,Natsuki %A Lee,Jeonse %A Hakariya,Arisa %A Ikejiri,Tatsuki %+ Interfaculty Institute of Biochemistry, University of Tuebingen, Auf der Morgenstelle 15, Tuebingen, 72076, Germany, 49 7071 29 75377, hayase.hakariya@uni-tuebingen.de %K illegal trading %K pharmacovigilance %K social networking service %K SNS %K overdose %K social support %K antipsychotics %K Japan %K prescription medication %K cross-sectional study %K prescription drug %K social networking %K medication %K pharmaceutical %K pharmaceutical drugs %K Japanese %K psychiatric %K support %D 2024 %7 28.5.2024 %9 Original Paper %J JMIR Form Res %G English %X Background: Nonmedical use of prescription drugs can cause overdose; this represents a serious public health crisis globally. In this digital era, social networking services serve as viable platforms for illegal acquisition of excessive amounts of medications, including prescription medications. In Japan, such illegal drug transactions have been conducted through popular flea market applications, social media, and auction websites, with most of the trades being over-the-counter (OTC) medications. Recently, an emerging unique black market, where individuals trade prescription medications—predominantly nervous system drugs—using a specific keyword (“Okusuri Mogu Mogu”), has emerged on X (formerly Twitter). Hence, these dynamic methods of illicit trading should routinely be monitored to encourage the appropriate use of medications. Objective: This study aimed to specify the characteristics of medications traded on X using the search term “Okusuri Mogu Mogu” and analyze individual behaviors associated with X posts, including the types of medications traded and hashtag usage. Methods: We conducted a cross-sectional study with publicly available posts on X between September 18 and October 1, 2022. Posts that included the term “Okusuri Mogu Mogu” during this period were scrutinized. Posts were categorized on the basis of their contents: buying, selling, self-administration, heads-up, and others. Among posts categorized as buying, selling, and self-administration, medication names were systematically enumerated and categorized using the Anatomical Therapeutic Chemical (ATC) classification. Additionally, hashtags in all the analyzed posts were counted and classified into 6 categories: medication name, mental disorder, self-harm, buying and selling, community formation, and others. Results: Out of 961 identified posts, 549 were included for analysis. Of these posts, 119 (21.7%) referenced self-administration, and 237 (43.2%; buying: n=67, 12.2%; selling: n=170, 31.0%) referenced transactions. Among these 237 posts, 1041 medication names were mentioned, exhibiting a >5-fold increase from the study in March 2021. Categorization based on the ATC classification predominantly revealed nervous system drugs, representing 82.1% (n=855) of the mentioned medications, consistent with the previous survey. Of note, the diversity of medications has expanded to include medications that have not been approved by the Japanese government. Interestingly, OTC medications were frequently mentioned in self-administration posts (odds ratio 23.6, 95% CI 6.93-80.15). Analysis of hashtags (n=866) revealed efforts to foster community connections among users. Conclusions: This study highlighted the escalating complexity of trading of illegal prescription medication facilitated by X posts. Regulatory measures to enhance public awareness should be considered to prevent illegal transactions, which may ultimately lead to misuse or abuse such as overdose. Along with such pharmacovigilance measures, social approaches that could direct individuals to appropriate medical or psychiatric resources would also be beneficial as our hashtag analysis shed light on the formation of a cohesive or closed community among users. %M 38805262 %R 10.2196/54023 %U https://formative.jmir.org/2024/1/e54023 %U https://doi.org/10.2196/54023 %U http://www.ncbi.nlm.nih.gov/pubmed/38805262 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 8 %N %P e54433 %T Examining the Gateway Hypothesis and Mapping Substance Use Pathways on Social Media: Machine Learning Approach %A Yuan,Yunhao %A Kasson,Erin %A Taylor,Jordan %A Cavazos-Rehg,Patricia %A De Choudhury,Munmun %A Aledavood,Talayeh %+ Department of Computer Science, Aalto University, P.O. Box 11000 (Otakaari 1B), FI-00076 AALTO, Espoo, FI-00076, Finland, 358 509113635, Yunhao.Yuan@aalto.fi %K gateway hypothesis %K substance use %K social media %K deep learning %K natural language processing %D 2024 %7 7.5.2024 %9 Original Paper %J JMIR Form Res %G English %X Background: Substance misuse presents significant global public health challenges. Understanding transitions between substance types and the timing of shifts to polysubstance use is vital to developing effective prevention and recovery strategies. The gateway hypothesis suggests that high-risk substance use is preceded by lower-risk substance use. However, the source of this correlation is hotly contested. While some claim that low-risk substance use causes subsequent, riskier substance use, most people using low-risk substances also do not escalate to higher-risk substances. Social media data hold the potential to shed light on the factors contributing to substance use transitions. Objective: By leveraging social media data, our study aimed to gain a better understanding of substance use pathways. By identifying and analyzing the transitions of individuals between different risk levels of substance use, our goal was to find specific linguistic cues in individuals’ social media posts that could indicate escalating or de-escalating patterns in substance use. Methods: We conducted a large-scale analysis using data from Reddit, collected between 2015 and 2019, consisting of over 2.29 million posts and approximately 29.37 million comments by around 1.4 million users from subreddits. These data, derived from substance use subreddits, facilitated the creation of a risk transition data set reflecting the substance use behaviors of over 1.4 million users. We deployed deep learning and machine learning techniques to predict the escalation or de-escalation transitions in risk levels, based on initial transition phases documented in posts and comments. We conducted a linguistic analysis to analyze the language patterns associated with transitions in substance use, emphasizing the role of n-gram features in predicting future risk trajectories. Results: Our results showed promise in predicting the escalation or de-escalation transition in risk levels, based on the historical data of Reddit users created on initial transition phases among drug-related subreddits, with an accuracy of 78.48% and an F1-score of 79.20%. We highlighted the vital predictive features, such as specific substance names and tools indicative of future risk escalations. Our linguistic analysis showed that terms linked with harm reduction strategies were instrumental in signaling de-escalation, whereas descriptors of frequent substance use were characteristic of escalating transitions. Conclusions: This study sheds light on the complexities surrounding the gateway hypothesis of substance use through an examination of web-based behavior on Reddit. While certain findings validate the hypothesis, indicating a progression from lower-risk substances such as marijuana to higher-risk ones, a significant number of individuals did not show this transition. The research underscores the potential of using machine learning with social media analysis to predict substance use transitions. Our results point toward future directions for leveraging social media data in substance use research, underlining the importance of continued exploration before suggesting direct implications for interventions. %M 38713904 %R 10.2196/54433 %U https://formative.jmir.org/2024/1/e54433 %U https://doi.org/10.2196/54433 %U http://www.ncbi.nlm.nih.gov/pubmed/38713904 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 8 %N %P e38761 %T Media Discourse Regarding COVID-19 Vaccinations for Children Aged 5 to 11 Years in Australia, Canada, the United Kingdom, and the United States: Comparative Analysis Using the Narrative Policy Framework %A Chadwick,Verity L %A Saich,Freya %A Freeman,Joseph %A Martiniuk,Alexandra %+ Faculty of Medicine and Health, University of Sydney, Edward Ford Building, A27 Fisher Road, Camperdown, 2006, Australia, 61 (02) 9351 2222, alexandra.martiniuk@sydney.edu.au %K COVID-19 %K SARS-CoV-2 %K vaccine %K mRNA %K Pfizer-BioNTech %K pediatric %K children %K media %K news %K web-based %K infodemic %K disinformation %D 2024 %7 29.4.2024 %9 Original Paper %J JMIR Form Res %G English %X Background: Media narratives can shape public opinion and actions, influencing the uptake of pediatric COVID-19 vaccines. The COVID-19 pandemic has occurred at a time where infodemics, misinformation, and disinformation are present, impacting the COVID-19 response. Objective: This study aims to investigate how narratives about pediatric COVID-19 vaccines in the media of 4 English-speaking countries: the United States, Australia, Canada, and the United Kingdom. Methods: The Narrative Policy Framework was used to guide the comparative analyses of the major print and web-based news agencies’ media regarding COVID-19 vaccines for children aged 5 to 11 years. Data were sought using systematic searching on Factiva (Dow Jones) of 4 key phases of pediatric vaccine approval and rollout. Results: A total of 400 articles (n=287, 71.8% in the United States, n=40, 10% in Australia, n=60, 15% in Canada, and n=13, 3% in the United Kingdom) met the search criteria and were included. Using the Narrative Policy Framework, the following were identified in each article: hero, villain, survivor, and plot. The United States was the earliest country to vaccinate children, and other countries’ media often lauded the United States for this. Australian and Canadian media narratives about vaccines for children aged 5 to 11 years were commonly about protecting susceptible people in society, whereas the US and the UK narratives focused more on the vaccine helping children return to school. All 4 countries focused on the vaccines for children aged 5 to 11 years as being key to “ending” the pandemic. Australian and Canadian narratives frequently compared vaccine rollouts across states or provinces and bemoaned local progress in vaccine delivery compared with other countries globally. Canadian and US narratives highlighted the “infodemic” about the COVID-19 pandemic and disinformation regarding child vaccines as impeding uptake. All 4 countries—the United States, Australia, the United Kingdom, and Canada—used war imagery in reporting about COVID-19 vaccines for children. The advent of the Omicron variant demonstrated that populations were fatigued by the COVID-19 pandemic, and the media reporting increasingly blamed the unvaccinated. The UK media narrative was unique in describing vaccinating children as a distraction from adult COVID-19 vaccination efforts. The United States and Canada had narratives expressing anger about potential vaccine passports for children. In Australia, general practitioners were labelled as heroes. Finally, the Canadian narrative suggested altruistic forgoing of COVID-19 vaccine “boosters” as well as pediatric COVID-19 vaccines to benefit those in poorer nations. Conclusions: Public health emergencies require clear; compelling and accurate communication. The stories told during this pandemic are compelling because they contain the classic elements of a narrative; however, they can be reductive and inaccurate. %M 36383344 %R 10.2196/38761 %U https://formative.jmir.org/2024/1/e38761 %U https://doi.org/10.2196/38761 %U http://www.ncbi.nlm.nih.gov/pubmed/36383344 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 8 %N %P e50368 %T Preferences on Governance Models for Mental Health Data: Qualitative Study With Young People %A Carey,Emma Grace %A Adeyemi,Faith Oluwasemilore %A Neelakantan,Lakshmi %A Fernandes,Blossom %A Fazel,Mina %A Ford,Tamsin %A , %A Burn,Anne-Marie %+ Department of Psychiatry, University of Cambridge, Herchel Smith Building for Brain and Mind Sciences, Forvie Site, Robinson Way, Cambridge, CB2 0SZ, United Kingdom, 44 01223 336961, amb278@cam.ac.uk %K young people %K mental health %K data %K governance %K deliberative democracy %K mobile phone %D 2024 %7 23.4.2024 %9 Original Paper %J JMIR Form Res %G English %X Background: Improving access to mental health data to accelerate research and improve mental health outcomes is a potentially achievable goal given the substantial data that can now be collected from mobile devices. Smartphones can provide a useful mechanism for collecting mental health data from young people, especially as their use is relatively ubiquitous in high-resource settings such as the United Kingdom and they have a high capacity to collect active and passive data. This raises the interesting opportunity to establish a large bank of mental health data from young people that could be accessed by researchers worldwide, but it is important to clarify how to ensure that this is done in an appropriate manner aligned with the values of young people. Objective: In this study, we discussed the preferences of young people in the United Kingdom regarding the governance, sharing, and use of their mental health data with the establishment of a global data bank in mind. We aimed to determine whether young people want and feel safe to share their mental health data; if so, with whom; and their preferences in doing so. Methods: Young people (N=46) were provided with 2 modules of educational material about data governance models and background in scientific research. We then conducted 2-hour web-based group sessions using a deliberative democracy methodology to reach a consensus where possible. Findings were analyzed using the framework method. Results: Young people were generally enthusiastic about contributing data to mental health research. They believed that broader availability of mental health data could be used to discover what improves or worsens mental health and develop new services to support young people. However, this enthusiasm came with many concerns and caveats, including distributed control of access to ensure appropriate use, distributed power, and data management that included diverse representation and sufficient ethical training for applicants and data managers. Conclusions: Although it is feasible to use smartphones to collect mental health data from young people in the United Kingdom, it is essential to carefully consider the parameters of such a data bank. Addressing and embedding young people’s preferences, including the need for robust procedures regarding how their data are managed, stored, and accessed, will set a solid foundation for establishing any global data bank. %M 38652525 %R 10.2196/50368 %U https://formative.jmir.org/2024/1/e50368 %U https://doi.org/10.2196/50368 %U http://www.ncbi.nlm.nih.gov/pubmed/38652525 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 8 %N %P e53666 %T Social Network Analysis of e-Cigarette–Related Social Media Influencers on Twitter/X: Observational Study %A Zhou,Runtao %A Xie,Zidian %A Tang,Qihang %A Li,Dongmei %+ Department of Clinical and Translational Research, University of Rochester Medical Center, 265 Crittenden Boulevard Cu 420708, Rochester, NY, 14642-0708, United States, 1 5852767285, Dongmei_Li@urmc.rochester.edu %K social network %K social media %K influencer %K electronic cigarettes %K e-cigarette %K vaping %K vape %K Twitter %K observational study %K aerosol %K consumer %K influencers %K social network analysis %K antivaping %K campaigns %D 2024 %7 1.4.2024 %9 Original Paper %J JMIR Form Res %G English %X Background: An e-cigarette uses a battery to heat a liquid that generates an aerosol for consumers to inhale. e-Cigarette use (vaping) has been associated with respiratory disease, cardiovascular disease, and cognitive functions. Recently, vaping has become increasingly popular, especially among youth and young adults. Objective: The aim of this study was to understand the social networks of Twitter (now rebranded as X) influencers related to e-cigarettes through social network analysis. Methods: Through the Twitter streaming application programming interface, we identified 3,617,766 unique Twitter accounts posting e-cigarette–related tweets from May 3, 2021, to June 10, 2022. Among these, we identified 33 e-cigarette influencers. The followers of these influencers were grouped according to whether or not they post about e-cigarettes themselves; specifically, the former group was defined as having posted at least five e-cigarette–related tweets in the past year, whereas the latter group was defined as followers that had not posted any e-cigarette–related tweets in the past 3 years. We randomly sampled 100 user accounts among each group of e-cigarette influencer followers and created corresponding social networks for each e-cigarette influencer. We compared various network measures (eg, clustering coefficient) between the networks of the two follower groups. Results: Major topics from e-cigarette–related tweets posted by the 33 e-cigarette influencers included advocating against vaping policy (48.0%), vaping as a method to quit smoking (28.0%), and vaping product promotion (24.0%). The follower networks of these 33 influencers showed more connections for those who also post about e-cigarettes than for followers who do not post about e-cigarettes, with significantly higher clustering coefficients for the former group (0.398 vs 0.098; P=.005). Further, networks of followers who post about e-cigarettes exhibited substantially more incoming and outgoing connections than those of followers who do not post about e-cigarettes, with significantly higher in-degree (0.273 vs 0.084; P=.02), closeness (0.452 vs 0.137; P=.04), betweenness (0.036 vs 0.008; P=.001), and out-of-degree (0.097 vs 0.014; P=.02) centrality values. The followers who post about e-cigarettes also had a significantly (P<.001) higher number of followers (n=322) than that of followers who do not post about e-cigarettes (n=201). The number of tweets in the networks of followers who post about e-cigarettes was significantly higher than that in the networks of followers who do not post about e-cigarettes (93 vs 43; P<.001). Two major topics discussed in the networks of followers who post about e-cigarettes included promoting e-cigarette products or vaping activity (55.7%) and vaping being a help for smoking cessation and harm reduction (44.3%). Conclusions: Followers of e-cigarette influencers who also post about e-cigarettes have more closely connected networks than those of followers who do not themselves post about e-cigarettes. These findings provide a potentially practical intervention approach for future antivaping campaigns. %M 38557555 %R 10.2196/53666 %U https://formative.jmir.org/2024/1/e53666 %U https://doi.org/10.2196/53666 %U http://www.ncbi.nlm.nih.gov/pubmed/38557555 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 8 %N %P e49198 %T Arabic Web-Based Information on Oral Lichen Planus: Content Analysis %A AlMeshrafi,Azzam %A AlHamad,Arwa F %A AlKuraidees,Hamoud %A AlNasser,Lubna A %+ Dental Services, Ministry of National Gaurd Health Affairs, Prince Mutib bin Abdullah bin Abdulaziz Rd, Riyadh, 11426, Saudi Arabia, 966 118011111, hamadar@mngha.med.sa %K oral lichen planus %K health information %K Arabic %K medical information %K information seeking %K quality %K online information %K Arab %K oral %K inflammatory %K inflammation %K chronic %K mouth %K mucous membrane %K mucous membranes %K reliable %K reliability %K credible %K credibility %K periodontology %K dental %K dentist %K dentistry %D 2024 %7 19.3.2024 %9 Original Paper %J JMIR Form Res %G English %X Background: The use of web-based health information (WBHI) is on the rise, serving as a valuable tool for educating the public about health concerns and enhancing treatment adherence. Consequently, evaluating the availability and quality of context-specific WBHI is crucial to tackle disparities in health literacy and advance population health outcomes. Objective: This study aims to explore and assess the quality of the WBHI available and accessible to the public on oral lichen planus (OLP) in Arabic. Methods: The Arabic translation of the term OLP and its derivatives were searched in three general search platforms, and each platform’s first few hundred results were reviewed for inclusion. We excluded content related to cutaneous LP, content not readily accessible to the public (eg, requiring subscription fees or directed to health care providers), and content not created by health care providers or organizations (ie, community forums, blogs, and social media). We assessed the quality of the Arabic WBHI with three standardized and validated tools: DISCERN, Journal of the American Medical Association (JAMA) benchmarks, and Health On the Net (HON). Results: Of the 911 resources of WBHI reviewed for eligibility, 49 were included in this study. Most WBHI resources were provided by commercial affiliations (n=28, 57.1%), with the remainder from academic or not-for-profit affiliations. WBHI were often presented with visual aids (ie, images; n=33, 67.4%). DISCERN scores were highest for WBHI resources that explicitly stated their aim, while the lowest scores were for providing the effect of OLP (or OLP treatment) on the quality of life. One-quarter of the resources (n=11, 22.4%) met all 4 JAMA benchmarks, indicating the high quality of the WBHI, while the remainder of the WBHI failed to meet one or more of the JAMA benchmarks. HON scores showed that one-third of WBHI sources had scores above 75%, indicating higher reliability and credibility of the WBHI source, while one-fifth of the sources scored below 50%. Only 1 in 7 WBHI resources scored simultaneously high on all three quality instruments. Generally, WBHI from academic affiliations had higher quality scores than content provided by commercial affiliations. Conclusions: There are considerable variations in the quality of WBHI on OLP in Arabic. Most WBHI resources were deemed to be of moderate quality at best. Providers of WBHI could benefit from increasing collaboration between commercial and academic institutions in creating WBHI and integrating guidance from international quality assessment tools to improve the quality and, hopefully, the utility of these valuable WBHI resources. %M 38502161 %R 10.2196/49198 %U https://formative.jmir.org/2024/1/e49198 %U https://doi.org/10.2196/49198 %U http://www.ncbi.nlm.nih.gov/pubmed/38502161 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 8 %N %P e44726 %T Identification of Myths and Misinformation About Treatment for Opioid Use Disorder on Social Media: Infodemiology Study %A ElSherief,Mai %A Sumner,Steven %A Krishnasamy,Vikram %A Jones,Christopher %A Law,Royal %A Kacha-Ochana,Akadia %A Schieber,Lyna %A De Choudhury,Munmun %+ Khoury College of Computer Sciences, Northeastern University, 360 Huntington Ave, Boston, MA, 02115, United States, 1 (617) 373 2462, m.elsherif@northeastern.edu %K addiction treatment %K machine learning %K misinformation %K natural language processing %K opioid use disorder %K social media %K substance use %D 2024 %7 23.2.2024 %9 Original Paper %J JMIR Form Res %G English %X Background: Health misinformation and myths about treatment for opioid use disorder (OUD) are present on social media and contribute to challenges in preventing drug overdose deaths. However, no systematic, quantitative methodology exists to identify what types of misinformation are being shared and discussed. Objective: We developed a multistage analytic pipeline to assess social media posts from Twitter (subsequently rebranded as X), YouTube, Reddit, and Drugs-Forum for the presence of health misinformation about treatment for OUD. Methods: Our approach first used document embeddings to identify potential new statements of misinformation from known myths. These statements were grouped into themes using hierarchical agglomerative clustering, and public health experts then reviewed the results for misinformation. Results: We collected a total of 19,953,599 posts discussing opioid-related content across the aforementioned platforms. Our multistage analytic pipeline identified 7 main clusters or discussion themes. Among a high-yield data set of posts (n=303) for further public health expert review, these included discussion about potential treatments for OUD (90/303, 29.8%), the nature of addiction (68/303, 22.5%), pharmacologic properties of substances (52/303, 16.9%), injection drug use (36/303, 11.9%), pain and opioids (28/303, 9.3%), physical dependence of medications (22/303, 7.2%), and tramadol use (7/303, 2.3%). A public health expert review of the content within each cluster identified the presence of misinformation and myths beyond those used as seed myths to initialize the algorithm. Conclusions: Identifying and addressing misinformation through appropriate communication strategies could be an increasingly important component of preventing overdose deaths. To further this goal, we developed and tested an approach to aid in the identification of myths and misinformation about OUD from large-scale social media content. %M 38393772 %R 10.2196/44726 %U https://formative.jmir.org/2024/1/e44726 %U https://doi.org/10.2196/44726 %U http://www.ncbi.nlm.nih.gov/pubmed/38393772 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 8 %N %P e47245 %T Patient Experiences and Insights on Chronic Ocular Pain: Social Media Listening Study %A Sloesen,Brigitte %A O'Brien,Paul %A Verma,Himanshu %A Asaithambi,Sathyaraj %A Parashar,Nikita %A Mothe,Raj Kumar %A Shaikh,Javed %A Syntosi,Annie %+ Novartis Pharma NV, Medialaan 40, B-1800, Vilvoorde, Belgium, 32 478881453, brigitte.sloesen@novartis.com %K chronic ocular surface pain, patients' experiences %K quality of life %K social media %K Twitter %K unmet needs %K ocular pain %K ophthalmology %K ocular %K listening %K experience %K experiences %K tweet %K eye pain %K eye condition %K social media platforms %K social media use %K patient experience %K chronic pain %K pain %K internet %K eye %K retina %K online health %K digital health %K web %K vision %K optical %D 2024 %7 15.2.2024 %9 Original Paper %J JMIR Form Res %G English %X Background: Ocular pain has multifactorial etiologies that affect activities of daily life, psychological well-being, and health-related quality of life (QoL). Chronic ocular surface pain (COSP) is a persistent eye pain symptom lasting for a period longer than 3 months. Objective: The objective of this social media listening study was to better understand COSP and related symptoms and identify its perceived causes, comorbidities, and impact on QoL from social media posts. Methods: A search from February 2020 to February 2021 was performed on social media platforms (Twitter, Facebook, blogs, and forums) for English-language content posted on the web. Social media platforms that did not provide public access to information or posts were excluded. Social media posts from Australia, Canada, the United Kingdom, and the United States were retrieved using the Social Studio platform—a web-based aggregator tool. Results: Of the 25,590 posts identified initially, 464 posts about COSP were considered relevant; the majority of conversations (98.3%, n=456) were posted by adults (aged >18 years). Work status was mentioned in 52 conversations. Patients’ or caregivers’ discussions across social media platforms were centered around the symptoms (61.9%, n=287) and causes (58%, n=269) of ocular pain. Patients mentioned having symptoms associated with COSP, including headache or head pressure, dry or gritty eyes, light sensitivity, etc. Patients posted that their COSP impacts day-to-day activities such as reading, driving, sleeping, and their social, mental, and functional well-being. Conclusions: Insights from this study reported patients’ experiences, concerns, and the adverse impact on overall QoL. COSP imposes a significant burden on patients, which spans multiple aspects of daily life. %M 38358786 %R 10.2196/47245 %U https://formative.jmir.org/2024/1/e47245 %U https://doi.org/10.2196/47245 %U http://www.ncbi.nlm.nih.gov/pubmed/38358786 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 8 %N %P e52768 %T Exploring the Perspectives of Patients Living With Lupus: Retrospective Social Listening Study %A Spies,Erica %A Andreu,Thomas %A Hartung,Matthias %A Park,Josephine %A Kamudoni,Paul %+ The Healthcare Business of Merck KGaA, Frankfurter Strasse 250, Darmstadt, 64293, Germany, 49 15114543257, paul.kamudoni@emdgroup.com %K systemic lupus erythematosus %K SLE %K cutaneous lupus erythematosus %K CLE %K quality of life %K health-related quality of life %K HRQoL %K social media listening %K lupus %K rare %K cutaneous %K social media %K infodemiology %K infoveillance %K social listening %K natural language processing %K machine learning %K experience %K experiences %K tagged %K tagging %K visualization %K visualizations %K knowledge graph %K chronic %K autoimmune %K inflammation %K inflammatory %K skin %K dermatology %K dermatological %K forum %K forums %K blog %K blogs %D 2024 %7 2.2.2024 %9 Original Paper %J JMIR Form Res %G English %X Background: Systemic lupus erythematosus (SLE) is a chronic autoimmune inflammatory disease affecting various organs with a wide range of clinical manifestations. Cutaneous lupus erythematosus (CLE) can manifest as a feature of SLE or an independent skin ailment. Health-related quality of life (HRQoL) is frequently compromised in individuals living with lupus. Understanding patients’ perspectives when living with a disease is crucial for effectively meeting their unmet needs. Social listening is a promising new method that can provide insights into the experiences of patients living with their disease (lupus) and leverage these insights to inform drug development strategies for addressing their unmet needs. Objective: The objective of this study is to explore the experience of patients living with SLE and CLE, including their disease and treatment experiences, HRQoL, and unmet needs, as discussed in web-based social media platforms such as blogs and forums. Methods: A retrospective exploratory social listening study was conducted across 13 publicly available English-language social media platforms from October 2019 to January 2022. Data were processed using natural language processing and knowledge graph tagging technology to clean, format, anonymize, and annotate them algorithmically before feeding them to Pharos, a Semalytix proprietary data visualization and analysis platform, for further analysis. Pharos was used to generate descriptive data statistics, providing insights into the magnitude of individual patient experience variables, their differences in the magnitude of variables, and the associations between algorithmically tagged variables. Results: A total of 45,554 posts from 3834 individuals who were algorithmically identified as patients with lupus were included in this study. Among them, 1925 (authoring 5636 posts) and 106 (authoring 243 posts) patients were identified as having SLE and CLE, respectively. Patients frequently mentioned various symptoms in relation to SLE and CLE including pain, fatigue, and rashes; pain and fatigue were identified as the main drivers of HRQoL impairment. The most affected aspects of HRQoL included “mobility,” “cognitive capabilities,” “recreation and leisure,” and “sleep and rest.” Existing pharmacological interventions poorly managed the most burdensome symptoms of lupus. Conversely, nonpharmacological treatments, such as exercise and meditation, were frequently associated with HRQoL improvement. Conclusions: Patients with lupus reported a complex interplay of symptoms and HRQoL aspects that negatively influenced one another. This study demonstrates that social listening is an effective method to gather insights into patients’ experiences, preferences, and unmet needs, which can be considered during the drug development process to develop effective therapies and improve disease management. %M 38306157 %R 10.2196/52768 %U https://formative.jmir.org/2024/1/e52768 %U https://doi.org/10.2196/52768 %U http://www.ncbi.nlm.nih.gov/pubmed/38306157 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 8 %N %P e46087 %T A Novel Approach for the Early Detection of Medical Resource Demand Surges During Health Care Emergencies: Infodemiology Study of Tweets %A Kaur,Mahakprit %A Cargill,Taylor %A Hui,Kevin %A Vu,Minh %A Bragazzi,Nicola Luigi %A Kong,Jude Dzevela %+ Dalla Lana School of Public Health, University of Toronto, 155 College St, Room 500, Toronto, ON, M5T 3M7, Canada, 1 416 978 0901, jdkong@yorku.ca %K COVID-19 %K Twitter %K social media %K medical supply shortage %K pandemic %K global health %K Granger %K convergent cross-mapping %K causal analysis %K intensive care unit bed %K ICU bed %D 2024 %7 29.1.2024 %9 Original Paper %J JMIR Form Res %G English %X Background: The COVID-19 pandemic has highlighted gaps in the current handling of medical resource demand surges and the need for prioritizing scarce medical resources to mitigate the risk of health care facilities becoming overwhelmed. Objective: During a health care emergency, such as the COVID-19 pandemic, the public often uses social media to express negative sentiment (eg, urgency, fear, and frustration) as a real-time response to the evolving crisis. The sentiment expressed in COVID-19 posts may provide valuable real-time information about the relative severity of medical resource demand in different regions of a country. In this study, Twitter (subsequently rebranded as X) sentiment analysis was used to investigate whether an increase in negative sentiment COVID-19 tweets corresponded to a greater demand for hospital intensive care unit (ICU) beds in specific regions of the United States, Brazil, and India. Methods: Tweets were collected from a publicly available data set containing COVID-19 tweets with sentiment labels and geolocation information posted between February 1, 2020, and March 31, 2021. Regional medical resource shortage data were gathered from publicly available data sets reporting a time series of ICU bed demand across each country. Negative sentiment tweets were analyzed using the Granger causality test and convergent cross-mapping (CCM) analysis to assess the utility of the time series of negative sentiment tweets in forecasting ICU bed shortages. Results: For the United States (30,742,934 negative sentiment tweets), the results of the Granger causality test (for whether negative sentiment COVID-19 tweets forecast ICU bed shortage, assuming a stochastic system) were significant (P<.05) for 14 (28%) of the 50 states that passed the augmented Dickey-Fuller test at lag 2, and the results of the CCM analysis (for whether negative sentiment COVID-19 tweets forecast ICU bed shortage, assuming a dynamic system) were significant (P<.05) for 46 (92%) of the 50 states. For Brazil (3,004,039 negative sentiment tweets), the results of the Granger causality test were significant (P<.05) for 6 (22%) of the 27 federative units, and the results of the CCM analysis were significant (P<.05) for 26 (96%) of the 27 federative units. For India (4,199,151 negative sentiment tweets), the results of the Granger causality test were significant (P<.05) for 6 (23%) of the 26 included regions (25 states and the national capital region of Delhi), and the results of the CCM analysis were significant (P<.05) for 26 (100%) of the 26 included regions. Conclusions: This study provides a novel approach for identifying the regions of high hospital bed demand during a health care emergency scenario by analyzing Twitter sentiment data. Leveraging analyses that take advantage of natural language processing–driven tweet extraction systems has the potential to be an effective method for the early detection of medical resource demand surges. %M 38285495 %R 10.2196/46087 %U https://formative.jmir.org/2024/1/e46087 %U https://doi.org/10.2196/46087 %U http://www.ncbi.nlm.nih.gov/pubmed/38285495 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 8 %N %P e52306 %T Web-Based Search Volume for HIV Tests and HIV-Testing Preferences During the COVID-19 Pandemic in Japan: Infodemiology Study %A Kanamori,Rie %A Umemura,Futaba %A Uemura,Kosuke %A Miyagami,Taiju %A Valenti,Simon %A Fukui,Nobuyuki %A Yuda,Mayumi %A Saita,Mizue %A Mori,Hirotake %A Naito,Toshio %+ Department of General Medicine, Faculty of Medicine, Juntendo University, 3-1-3 Hongo Bunkyo-ku, Tokyo, 113-8421, Japan, 81 3 5802 1190, naito@juntendo.ac.jp %K HIV test %K infodemiology %K self-test %K COVID-19 %K search engine %K Japan %D 2024 %7 18.1.2024 %9 Original Paper %J JMIR Form Res %G English %X Background: Research has found a COVID-19 pandemic–related impact on HIV medical services, including clinic visits, testing, and antiviral therapy initiation in countries including Japan. However, the change in trend for HIV/AIDS testing during the COVID-19 pandemic has not been explored extensively in the Japanese population. Objective: This infodemiology study examines the web-based search interest for two types of HIV tests, self-test kits and facility-based tests, before and during the COVID-19 pandemic in Japan. Methods: The monthly search volume of queried search terms was obtained from Yahoo! JAPAN. Search volumes for the following terms were collected from November 2017 to October 2018: “HIV test,” “HIV test kit,” and “HIV test health center.” The search term “Corona PCR” and the number of new COVID-19 cases by month were used as a control for the search trends. The number of new HIV cases in the corresponding study period was obtained from the AIDS Trend Committee Quarterly Report from the AIDS Prevention Foundation. Results: Compared to the search volume of “corona-PCR,” which roughly fluctuated corresponding to the number of new COVID-19 cases in Japan, the search volume of “HIV test” was relatively stable from 2019 to 2022. When we further stratified by the type of HIV test, the respective web-based search interest in HIV self-testing and facility-based testing showed distinct patterns from 2018 to 2022. While the search volume of “HIV test kit” remained stable, that of “HIV test health center” displayed a decreasing trend starting in 2018 and has remained low since the beginning of the COVID-19 pandemic. Around 66%-71% of the search volume of “HIV test kits” was attributable to searches made by male internet users from 2018 to 2022, and the top three contributing age groups were those aged 30-39 (27%-32%), 20-29 (19%-32%), and 40-49 (19%-25%) years. On the other hand, the search volume of “HIV test health centers” by male users decreased from more than 500 from 2018 to 2019 to fewer than 300 from 2020 to 2022. Conclusions: Our study found a notable decrease in the search volume of “HIV test health center” during the pandemic, while the search volume for HIV self-testing kits remained stable before and during the COVID-19 crisis in Japan. This suggests that the previously reported COVID-19–related decrease in the number of HIV tests mostly likely referred to facility-based testing. This sheds light on the change in HIV-testing preferences in Japan, calling for a more comprehensive application and regulatory acceptance of HIV self-instructed tests. %M 38236622 %R 10.2196/52306 %U https://formative.jmir.org/2024/1/e52306 %U https://doi.org/10.2196/52306 %U http://www.ncbi.nlm.nih.gov/pubmed/38236622 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 25 %N %P e44610 %T Evaluation of the Needs and Experiences of Patients with Hypertriglyceridemia: Social Media Listening Infosurveillance Study %A Song,Junxian %A Cui,Yuxia %A Song,Jing %A Lee,Chongyou %A Wu,Manyan %A Chen,Hong %+ Beijing Key Laboratory of Early Prediction and Intervention of Acute Myocardial Infarction, Department of Cardiology, Center for Cardiovascular Translational Research, Peking University People’s Hospital, No 11 Xizhimen South Road, Xicheng district, Beijing, 100044, China, 86 10 88325940, chenhongbj@medmail.com.cn %K social media listening %K hypertriglyceridemia %K infosurveillance study %K disease cognition %K lifestyle intervention %K lipid disorder %K awareness %K online search %K telemedicine %K self-medication %K Chinese medicine %K natural language processing %K cardiovascular disease %K stroke %K online platform %K self-management %K Q&A search platform %K social media %D 2023 %7 19.12.2023 %9 Original Paper %J J Med Internet Res %G English %X Background: Hypertriglyceridemia is a risk factor for cardiovascular diseases. Internet usage in China is increasing, giving rise to large-scale data sources, especially to access, disseminate, and discuss medical information. Social media listening (SML) is a new approach to analyze and monitor online discussions related to various health-related topics in diverse diseases, which can generate insights into users’ experiences and expectations. However, to date, no studies have evaluated the utility of SML to understand patients’ cognizance and expectations pertaining to the management of hypertriglyceridemia. Objective: The aim of this study was to utilize SML to explore the disease cognition level of patients with hypertriglyceridemia, choice of intervention measures, and the status quo of online consultations and question-and-answer (Q&A) search platforms. Methods: An infosurveillance study was conducted wherein a disease-specific comprehensive search was performed between 2004 and 2020 in Q&A search and online consultation platforms. Predefined single and combined keywords related to hypertriglyceridemia were used in the search, including disease, symptoms, diagnosis, and treatment indicators; lifestyle interventions; and therapeutic agents. The search output was aggregated using an aggregator tool and evaluated. Results: Disease-specific consultation data (n=69,845) and corresponding response data (n=111,763) were analyzed from 20 data sources (6 Q&A search platforms and 14 online consultation platforms). Doctors from inland areas had relatively high voice volumes and appear to exert a substantial influence on these platforms. Patients with hypertriglyceridemia engaging on the internet have an average level of cognition about the disease and its intervention measures. However, a strong demand for the concept of the disease and “how to treat it” was observed. More emphasis on the persistence of the disease and the safety of medications was observed. Young patients have a lower willingness for drug interventions, whereas patients with severe hypertriglyceridemia have a clearer intention to use drug intervention and few patients have a strong willingness for the use of traditional Chinese medicine. Conclusions: Findings from this disease-specific SML study revealed that patients with hypertriglyceridemia in China actively seek information from both online Q&A search and consultation platforms. However, the integrity of internet doctors’ suggestions on lifestyle interventions and the accuracy of drug intervention recommendations still need to be improved. Further, a combined prospective qualitative study with SML is required for added rigor and confirmation of the relevance of the findings. %M 38113100 %R 10.2196/44610 %U https://www.jmir.org/2023/1/e44610 %U https://doi.org/10.2196/44610 %U http://www.ncbi.nlm.nih.gov/pubmed/38113100 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 7 %N %P e48710 %T Public Perceptions About Monkeypox on Twitter: Thematic Analysis %A Leslie,Abimbola %A Okunromade,Omolola %A Sarker,Abeed %+ Department of Biomedical Informatics, School of Medicine, Emory University, 101 Woodruff Circle, Suite 4101, Atlanta, GA, 30322, United States, 1 6024746203, abeed@dbmi.emory.edu %K monkeypox %K social media %K public health %K Twitter %K perception %K digital platform %K infectious disease %K outbreak %K awareness %K analyses %K misinformation %D 2023 %7 3.11.2023 %9 Short Paper %J JMIR Form Res %G English %X Background: Social media has emerged as an important source of information generated by large segments of the population, which can be particularly valuable during infectious disease outbreaks. The recent outbreak of monkeypox led to an increase in discussions about the topic on social media, thus presenting the opportunity to conduct studies based on the generated data. Objective: By analyzing posts from Twitter (subsequently rebranded X), we aimed to identify the topics of public discourse as well as knowledge and opinions about the monkeypox virus during the 2022 outbreak. Methods: We collected data from Twitter focusing on English-language posts containing key phrases like “monkeypox,” “mpoxvirus,” and “monkey pox,” as well as their hashtag equivalents from August to October 2022. We preprocessed the data using natural language processing to remove duplicates and filter out noise. We then selected a random sample from the collected posts. Three annotators reviewed a sample of the posts and created a guideline for coding based on discussion. Finally, the annotators analyzed, coded, and manually categorized them first into topics and then into coarse-grained themes. Disagreements were resolved via discussion among all authors. Results: A total of 128,615 posts were collected over a 3-month period, and 200 tweets were selected and included for manual analyses. The following 8 themes were generated from the Twitter posts: monkeypox doubts, media, monkeypox transmission, effect of monkeypox, knowledge of monkeypox, politics, monkeypox vaccine, and general comments. The most common themes from our study were monkeypox doubts and media, each accounting for 22% (44/200) of the posts. The posts represented a mix of useful information reflecting emerging knowledge on the topic as well as misinformation. Conclusions: Social networks, such as Twitter, are useful sources of information in the early stages of outbreaks. Close to real-time identification and analyses of misinformation may help authorities take the necessary steps in a timely manner. %M 37921866 %R 10.2196/48710 %U https://formative.jmir.org/2023/1/e48710 %U https://doi.org/10.2196/48710 %U http://www.ncbi.nlm.nih.gov/pubmed/37921866 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 7 %N %P e46874 %T Public Health Surveillance of Behavioral Cancer Risk Factors During the COVID-19 Pandemic: Sentiment and Emotion Analysis of Twitter Data %A Christodoulakis,Nicolette %A Abdelkader,Wael %A Lokker,Cynthia %A Cotterchio,Michelle %A Griffith,Lauren E %A Vanderloo,Leigh M %A Anderson,Laura N %+ Department of Health Research Methods, Evidence, and Impact, McMaster University, CRL-221, 1280 Main Street West, Hamilton, ON, L8S 4L8, Canada, 1 9055259140 ext 21725, ln.anderson@mcmaster.ca %K cancer risk factors %K Twitter %K sentiment analysis %K emotion analysis %K social media %K physical inactivity %K poor nutrition %K alcohol %K smoking %D 2023 %7 2.11.2023 %9 Original Paper %J JMIR Form Res %G English %X Background: The COVID-19 pandemic and its associated public health mitigation strategies have dramatically changed patterns of daily life activities worldwide, resulting in unintentional consequences on behavioral risk factors, including smoking, alcohol consumption, poor nutrition, and physical inactivity. The infodemic of social media data may provide novel opportunities for evaluating changes related to behavioral risk factors during the pandemic. Objective: We explored the feasibility of conducting a sentiment and emotion analysis using Twitter data to evaluate behavioral cancer risk factors (physical inactivity, poor nutrition, alcohol consumption, and smoking) over time during the first year of the COVID-19 pandemic. Methods: Tweets during 2020 relating to the COVID-19 pandemic and the 4 cancer risk factors were extracted from the George Washington University Libraries Dataverse. Tweets were defined and filtered using keywords to create 4 data sets. We trained and tested a machine learning classifier using a prelabeled Twitter data set. This was applied to determine the sentiment (positive, negative, or neutral) of each tweet. A natural language processing package was used to identify the emotions (anger, anticipation, disgust, fear, joy, sadness, surprise, and trust) based on the words contained in the tweets. Sentiments and emotions for each of the risk factors were evaluated over time and analyzed to identify keywords that emerged. Results: The sentiment analysis revealed that 56.69% (51,479/90,813) of the tweets about physical activity were positive, 16.4% (14,893/90,813) were negative, and 26.91% (24,441/90,813) were neutral. Similar patterns were observed for nutrition, where 55.44% (27,939/50,396), 15.78% (7950/50,396), and 28.79% (14,507/50,396) of the tweets were positive, negative, and neutral, respectively. For alcohol, the proportions of positive, negative, and neutral tweets were 46.85% (34,897/74,484), 22.9% (17,056/74,484), and 30.25% (22,531/74,484), respectively, and for smoking, they were 41.2% (11,628/28,220), 24.23% (6839/28,220), and 34.56% (9753/28,220), respectively. The sentiments were relatively stable over time. The emotion analysis suggests that the most common emotion expressed across physical activity and nutrition tweets was trust (69,495/320,741, 21.67% and 42,324/176,564, 23.97%, respectively); for alcohol, it was joy (49,147/273,128, 17.99%); and for smoking, it was fear (23,066/110,256, 20.92%). The emotions expressed remained relatively constant over the observed period. An analysis of the most frequent words tweeted revealed further insights into common themes expressed in relation to some of the risk factors and possible sources of bias. Conclusions: This analysis provided insight into behavioral cancer risk factors as expressed on Twitter during the first year of the COVID-19 pandemic. It was feasible to extract tweets relating to all 4 risk factors, and most tweets had a positive sentiment with varied emotions across the different data sets. Although these results can play a role in promoting public health, a deeper dive via qualitative analysis can be conducted to provide a contextual examination of each tweet. %M 37917123 %R 10.2196/46874 %U https://formative.jmir.org/2023/1/e46874 %U https://doi.org/10.2196/46874 %U http://www.ncbi.nlm.nih.gov/pubmed/37917123 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 7 %N %P e44420 %T Patient Journey Toward a Diagnosis of Light Chain Amyloidosis in a National Sample: Cross-Sectional Web-Based Study %A Dou,Xuelin %A Liu,Yang %A Liao,Aijun %A Zhong,Yuping %A Fu,Rong %A Liu,Lihong %A Cui,Canchan %A Wang,Xiaohong %A Lu,Jin %+ Hematology Department, Peking University People's Hospital, 11 Xizhimen South Street, Beijing, 100044, China, 86 13311491805, jin1lu@sina.com.cn %K systemic light chain amyloidosis %K AL amyloidosis %K rare disease %K big data %K network analysis %K machine model %K natural language processing %K web-based %D 2023 %7 2.11.2023 %9 Original Paper %J JMIR Form Res %G English %X Background: Systemic light chain (AL) amyloidosis is a rare and multisystem disease associated with increased morbidity and a poor prognosis. Delayed diagnoses are common due to the heterogeneity of the symptoms. However, real-world insights from Chinese patients with AL amyloidosis have not been investigated. Objective: This study aimed to describe the journey to an AL amyloidosis diagnosis and to build an in-depth understanding of the diagnostic process from the perspective of both clinicians and patients to obtain a correct and timely diagnosis. Methods: Publicly available disease-related content from social media platforms between January 2008 and April 2021 was searched. After performing data collection steps with a machine model, a series of disease-related posts were extracted. Natural language processing was used to identify the relevance of variables, followed by further manual evaluation and analysis. Results: A total of 2204 valid posts related to AL amyloidosis were included in this study, of which 1968 were posted on haodf.com. Of these posts, 1284 were posted by men (median age 57, IQR 46-67 years); 1459 posts mentioned renal-related symptoms, followed by heart (n=833), liver (n=491), and stomach (n=368) symptoms. Furthermore, 1502 posts mentioned symptoms related to 2 or more organs. Symptoms for AL amyloidosis most frequently mentioned by suspected patients were nonspecific weakness (n=252), edema (n=196), hypertrophy (n=168), and swelling (n=140). Multiple physician visits were common, and nephrologists (n=265) and hematologists (n=214) were the most frequently visited specialists by suspected patients for initial consultation. Additionally, interhospital referrals were also commonly seen, centralizing in tertiary hospitals. Conclusions: Chinese patients with AL amyloidosis experienced referrals during their journey toward accurate diagnosis. Increasing awareness of the disease and early referral to a specialized center with expertise may reduce delayed diagnosis and improve patient management. %M 37917132 %R 10.2196/44420 %U https://formative.jmir.org/2023/1/e44420 %U https://doi.org/10.2196/44420 %U http://www.ncbi.nlm.nih.gov/pubmed/37917132 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 25 %N %P e49400 %T Early Warning and Prediction of Scarlet Fever in China Using the Baidu Search Index and Autoregressive Integrated Moving Average With Explanatory Variable (ARIMAX) Model: Time Series Analysis %A Luo,Tingyan %A Zhou,Jie %A Yang,Jing %A Xie,Yulan %A Wei,Yiru %A Mai,Huanzhuo %A Lu,Dongjia %A Yang,Yuecong %A Cui,Ping %A Ye,Li %A Liang,Hao %A Huang,Jiegang %+ School of Public Health, Guangxi Medical University, 22 Shuangyong Road, Qingxiu District, Nanning, 530021, China, 86 07715334215, jieganghuang@gxmu.edu.cn %K scarlet fever %K Baidu search index %K autoregressive integrated moving average %K ARIMA %K warning %K prediction %D 2023 %7 30.10.2023 %9 Original Paper %J J Med Internet Res %G English %X Background: Internet-derived data and the autoregressive integrated moving average (ARIMA) and ARIMA with explanatory variable (ARIMAX) models are extensively used for infectious disease surveillance. However, the effectiveness of the Baidu search index (BSI) in predicting the incidence of scarlet fever remains uncertain. Objective: Our objective was to investigate whether a low-cost BSI monitoring system could potentially function as a valuable complement to traditional scarlet fever surveillance in China. Methods: ARIMA and ARIMAX models were developed to predict the incidence of scarlet fever in China using data from the National Health Commission of the People’s Republic of China between January 2011 and August 2022. The procedures included establishing a keyword database, keyword selection and filtering through Spearman rank correlation and cross-correlation analyses, construction of the scarlet fever comprehensive search index (CSI), modeling with the training sets, predicting with the testing sets, and comparing the prediction performances. Results: The average monthly incidence of scarlet fever was 4462.17 (SD 3011.75) cases, and annual incidence exhibited an upward trend until 2019. The keyword database contained 52 keywords, but only 6 highly relevant ones were selected for modeling. A high Spearman rank correlation was observed between the scarlet fever reported cases and the scarlet fever CSI (rs=0.881). We developed the ARIMA(4,0,0)(0,1,2)(12) model, and the ARIMA(4,0,0)(0,1,2)(12) + CSI (Lag=0) and ARIMAX(1,0,2)(2,0,0)(12) models were combined with the BSI. The 3 models had a good fit and passed the residuals Ljung-Box test. The ARIMA(4,0,0)(0,1,2)(12), ARIMA(4,0,0)(0,1,2)(12) + CSI (Lag=0), and ARIMAX(1,0,2)(2,0,0)(12) models demonstrated favorable predictive capabilities, with mean absolute errors of 1692.16 (95% CI 584.88-2799.44), 1067.89 (95% CI 402.02-1733.76), and 639.75 (95% CI 188.12-1091.38), respectively; root mean squared errors of 2036.92 (95% CI 929.64-3144.20), 1224.92 (95% CI 559.04-1890.79), and 830.80 (95% CI 379.17-1282.43), respectively; and mean absolute percentage errors of 4.33% (95% CI 0.54%-8.13%), 3.36% (95% CI –0.24% to 6.96%), and 2.16% (95% CI –0.69% to 5.00%), respectively. The ARIMAX models outperformed the ARIMA models and had better prediction performances with smaller values. Conclusions: This study demonstrated that the BSI can be used for the early warning and prediction of scarlet fever, serving as a valuable supplement to traditional surveillance systems. %M 37902815 %R 10.2196/49400 %U https://www.jmir.org/2023/1/e49400 %U https://doi.org/10.2196/49400 %U http://www.ncbi.nlm.nih.gov/pubmed/37902815 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 7 %N %P e49325 %T An Evaluation of the Boys Do Cry Suicide Prevention Media Campaign on Twitter: Mixed Methods Approach %A Scotti Requena,Simone %A Pirkis,Jane %A Currier,Dianne %A Conway,Mike %A Lee,Simon %A Turnure,Jackie %A Cummins,Jennifer %A Nicholas,Angela %+ Centre for Mental Health, Melbourne School of Population and Global Health, The University of Melbourne, Level 4, 207 Bouverie Street, Melbourne, 3010, Australia, 61 383444951, simone.scottirequena@unimelb.edu.au %K help-seeking %K masculinity %K media campaign %K men %K men’s health %K mental health %K self-reliance %K social media %K suicide prevention %K suicide %D 2023 %7 7.9.2023 %9 Original Paper %J JMIR Form Res %G English %X Background: In most countries, men are more likely to die by suicide than women. Adherence to dominant masculine norms, such as being self-reliant, is linked to suicide in men in Western cultures. We created a suicide prevention media campaign, “Boys Do Cry,” designed to challenge the “self-reliance” norm and encourage help-seeking in men. A music video was at the core of the campaign, which was an adapted version of the “Boys Don’t Cry” song from “The Cure.” There is evidence that suicide prevention media campaigns can encourage help-seeking for mental health difficulties. Objective: We aimed to explore the reach, engagement, and themes of discussion prompted by the Boys Do Cry campaign on Twitter. Methods: We used Twitter analytics data to investigate the reach and engagement of the Boys Do Cry campaign, including analyzing the characteristics of tweets posted by the campaign’s hosts. Throughout the campaign and immediately after, we also used Twitter data derived from the Twitter Application Programming Interface to analyze the tweeting patterns of users related to the campaign. In addition, we qualitatively analyzed the content of Boys Do Cry–related tweets during the campaign period. Results: During the campaign, Twitter users saw the tweets posted by the hosts of the campaign a total of 140,650 times and engaged with its content a total of 4477 times. The 10 highest-performing tweets by the campaign hosts involved either a video or an image. Among the 10 highest-performing tweets, the first was one that included the campaign’s core video; the second was a screenshot of the tweet posted by Robert Smith, the lead singer of The Cure, sharing the Boys Do Cry campaign’s video and tagging the campaign’s hosts. In addition, the pattern of Twitter activity for the campaign-related tweets was considerably higher during the campaign than in the immediate postcampaign period, with half of the activity occurring during the first week of the campaign when Robert Smith promoted the campaign. Some of the key topics of discussions prompted by the Boys Do Cry campaign on Twitter involved users supporting the campaign; referencing the original song, band, or lead singer; reiterating the campaign’s messages; and having emotional responses to the campaign. Conclusions: This study demonstrates that a brief media campaign such as Boys Do Cry can achieve good reach and engagement and can prompt discussions on Twitter about masculinity and suicide. Such discussions may lead to greater awareness about the importance of seeking help and providing support to those with mental health difficulties. However, this study suggests that longer, more intensive campaigns may be needed in order to amplify and sustain these results. %M 37676723 %R 10.2196/49325 %U https://formative.jmir.org/2023/1/e49325 %U https://doi.org/10.2196/49325 %U http://www.ncbi.nlm.nih.gov/pubmed/37676723 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 7 %N %P e49452 %T Fact-Checking Cancer Information on Social Media in Japan: Retrospective Study Using Twitter %A Kureyama,Nari %A Terada,Mitsuo %A Kusudo,Maho %A Nozawa,Kazuki %A Wanifuchi-Endo,Yumi %A Fujita,Takashi %A Asano,Tomoko %A Kato,Akiko %A Mori,Makiko %A Horisawa,Nanae %A Toyama,Tatsuya %+ Department of Breast Surgery, Nagoya City University Graduate School of Medical Sciences, 1, Kawasumi, Mizuho-cho, Mizuho-ku, Nagoya, 467-8602, Japan, 81 52 851 5511, mterada@med.nagoya-cu.ac.jp %K cancer %K fact-check %K misinformation %K social media %K twitter %D 2023 %7 6.9.2023 %9 Original Paper %J JMIR Form Res %G English %X Background: The widespread use of social media has made it easier for patients to access cancer information. However, a large amount of misinformation and harmful information that could negatively impact patients’ decision-making is also disseminated on social media platforms. Objective: We aimed to determine the actual amount of misinformation and harmful information as well as trends in the dissemination of cancer-related information on Twitter, a representative social media platform. Our findings can support decision-making among Japanese patients with cancer. Methods: Using the Twitter app programming interface, we extracted tweets containing the term “cancer” in Japanese that were posted between August and September of 2022. The eligibility criteria were the cancer-related tweets with the following information: (1) reference to the occurrence or prognosis of cancer, (2) recommendation or nonrecommendation of actions, (3) reference to the course of cancer treatment or adverse events, (4) results of cancer research, and (5) other cancer-related knowledge and information. Finally, we selected the top 100 tweets with the highest number of “likes.” For each tweet, 2 independent reviewers evaluated whether the information was factual or misinformation, and whether it was harmful or safe with the reasons for the decisions on the misinformation and harmful tweets. Additionally, we examined the frequency of information dissemination using the number of retweets for the top 100 tweets and investigated trends in the dissemination of information. Results: The extracted tweets totaled 69,875. Of the top 100 cancer-related tweets with the most “likes” that met the eligibility criteria, 44 (44%) contained misinformation, 31 (31%) contained harmful information, and 30 (30%) contained both misinformation and harmful information. Misinformation was described as Unproven (29/94, 40.4%), Disproven (19/94, 20.2%), Inappropriate application (4/94, 4.3%), Strength of evidence mischaracterized (14/94, 14.9%), Misleading (18/94, 18%), and Other misinformation (1/94, 1.1%). Harmful action was described as Harmful action (9/59, 15.2%), Harmful inaction (43/59, 72.9%), Harmful interactions (3/59, 5.1%), Economic harm (3/59, 5.1%), and Other harmful information (1/59, 1.7%). Harmful information was liked more often than safe information (median 95, IQR 43-1919 vs 75.0 IQR 43-10,747; P=.04). The median number of retweets for the leading 100 tweets was 13.5 (IQR 0-2197). Misinformation was retweeted significantly more often than factual information (median 29.0, IQR 0-502 vs 7.5, IQR 0-2197; P=.01); harmful information was also retweeted significantly more often than safe information (median 35.0, IQR 0-502 vs 8.0, IQR 0-2197; P=.002). Conclusions: It is evident that there is a prevalence of misinformation and harmful information related to cancer on Twitter in Japan and it is crucial to increase health literacy and awareness regarding this issue. Furthermore, we believe that it is important for government agencies and health care professionals to continue providing accurate medical information to support patients and their families in making informed decisions. %M 37672310 %R 10.2196/49452 %U https://formative.jmir.org/2023/1/e49452 %U https://doi.org/10.2196/49452 %U http://www.ncbi.nlm.nih.gov/pubmed/37672310 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 7 %N %P e50346 %T Twitter Sentiment About the US Federal Tobacco 21 Law: Mixed Methods Analysis %A Dobbs,Page D %A Boykin,Allison Ames %A Ezike,Nnamdi %A Myers,Aaron J %A Colditz,Jason B %A Primack,Brian A %+ Health, Human Performance and Recreation Department, University of Arkansas, 346 West Ave., Suite 317, Fayetteville, AR, 72701, United States, 1 479 575 2858, pdobbs@uark.edu %K social media %K Twitter %K Tobacco 21 %K mixed methods %K tobacco policy %K sentiment %K tweet %K tweets %K tobacco %K smoke %K smoking %K smoker %K policy %K policies %K law %K regulation %K regulations %K laws %K attitude %K attitudes %K opinion %K opinions %D 2023 %7 31.8.2023 %9 Original Paper %J JMIR Form Res %G English %X Background: On December 20, 2019, the US “Tobacco 21” law raised the minimum legal sales age of tobacco products to 21 years. Initial research suggests that misinformation about Tobacco 21 circulated via news sources on Twitter and that sentiment about the law was associated with particular types of tobacco products and included discussions about other age-related behaviors. However, underlying themes about this sentiment as well as temporal trends leading up to enactment of the law have not been explored. Objective: This study sought to examine (1) sentiment (pro-, anti-, and neutral policy) about Tobacco 21 on Twitter and (2) volume patterns (number of tweets) of Twitter discussions leading up to the enactment of the federal law. Methods: We collected tweets related to Tobacco 21 posted between September 4, 2019, and December 31, 2019. A 2% subsample of tweets (4628/231,447) was annotated by 2 experienced, trained coders for policy-related information and sentiment. To do this, a codebook was developed using an inductive procedure that outlined the operational definitions and examples for the human coders to annotate sentiment (pro-, anti-, and neutral policy). Following the annotation of the data, the researchers used a thematic analysis to determine emergent themes per sentiment category. The data were then annotated again to capture frequencies of emergent themes. Concurrently, we examined trends in the volume of Tobacco 21–related tweets (weekly rhythms and total number of tweets over the time data were collected) and analyzed the qualitative discussions occurring at those peak times. Results: The most prevalent category of tweets related to Tobacco 21 was neutral policy (514/1113, 46.2%), followed by antipolicy (432/1113, 38.8%); 167 of 1113 (15%) were propolicy or supportive of the law. Key themes identified among neutral tweets were news reports and discussion of political figures, parties, or government involvement in general. Most discussions were generated from news sources and surfaced in the final days before enactment. Tweets opposing Tobacco 21 mentioned that the law was unfair to young audiences who were addicted to nicotine and were skeptical of the law’s efficacy and importance. Methods used to evade the law were found to be represented in both neutral and antipolicy tweets. Propolicy tweets focused on the protection of youth and described the law as a sensible regulatory approach rather than a complete ban of all products or flavored products. Four spikes in daily volume were noted, 2 of which corresponded with political speeches and 2 with the preparation and passage of the legislation. Conclusions: Understanding themes of public sentiment—as well as when Twitter activity is most active—will help public health professionals to optimize health promotion activities to increase community readiness and respond to enforcement needs including education for retailers and the general public. %M 37651169 %R 10.2196/50346 %U https://formative.jmir.org/2023/1/e50346 %U https://doi.org/10.2196/50346 %U http://www.ncbi.nlm.nih.gov/pubmed/37651169 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 7 %N %P e44031 %T Trends in the Baidu Index in Search Activity Related to Mpox at Geographical and Economic Levels and Associated Factors in China: National Longitudinal Analysis %A Du,Min %A Yan,Wenxin %A Zhu,Lin %A Liang,Wannian %A Liu,Min %A Liu,Jue %+ Department of Epidemiology and Biostatistics, School of Public Health, Peking University, 38 Xueyuan Road, Haidian District, Beijing, 100191, China, 86 13426455743, jueliu@bjmu.edu.cn %K mpox %K internet attention %K emergency %K disparities %K China %D 2023 %7 23.8.2023 %9 Original Paper %J JMIR Form Res %G English %X Background: Research assessing trends in online search activity related to mpox in China is scarce. Objective: We aimed to provide evidence for an overview of online information searching during an infectious disease outbreak by analyzing trends in online search activity related to mpox at geographical and economic levels in China and explore influencing factors. Methods: We used the Baidu index to present online search activity related to mpox from May 19 to September 19, 2022. Segmented interrupted time-series analysis was used to estimate trends in online search activity. Factors influencing these trends were analyzed using a general linear regression (GLM) model. We calculated the concentration index to measure economic-related inequality in online search activity and related trends. Results: Online search activity was highest on the day the first imported case of mpox appeared in Chongqing compared to 3 other cutoff time points. After the day of the first imported mpox case in Taiwan, the declaration of a public health emergency of international concern, the first imported mpox case in Hong Kong, and the first imported mpox case in Chongqing, national online search activity increased by 0.642%, 1.035%, 1.199%, and 2.023%, respectively. The eastern regions had higher increases than the central and western regions. Across 31 provinces, municipalities, and autonomous regions, the top 3 areas with higher increases were Beijing, Shanghai, and Tianjin at 3 time points, with the exception of the day of the first imported mpox case in Chongqing (Chongqing replaced Tianjin on that day). When AIDS incidence increased by 1 per 100,000 people, there was an increase after the day of the first imported mpox case in Chongqing of 36.22% (95% CI 3.29%-69.15%; P=.04) after controlling for other covariates. Online search activity (concentration index=0.18; P<.001) was more concentrated among populations with a higher economic status. Unlike the central area, the eastern (concentration index=0.234; P<.001) and western areas (concentration index=0.047; P=.04) had significant economic-related disparities (P for difference <.001) in online search activity. The overall concentration index of changes in online search activity became lower over time. Conclusions: Regions with a higher economic level showed more interest in mpox, especially Beijing and Shanghai. After the day of the first imported mpox case in Chongqing, changes in online search activity were affected by AIDS incidence rate. Economic-related disparities in changes in online search activity became lower over time. It would be desirable to construct a reliable information source in regions with a higher economic level and higher AIDS incidence rate and promote public knowledge in regions with a lower economic level in China, especially after important public events. %M 37610816 %R 10.2196/44031 %U https://formative.jmir.org/2023/1/e44031 %U https://doi.org/10.2196/44031 %U http://www.ncbi.nlm.nih.gov/pubmed/37610816 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 7 %N %P e47798 %T Assessing Vulnerability to Surges in Suicide-Related Tweets Using Japan Census Data: Case-Only Study %A Mitsuhashi,Toshiharu %+ Center for Innovative Clinical Medicine, Okayama University Hospital, 2-5-1, Shikata-cho, Kita-ku, Okayama, 700-8558, Japan, 81 86 235 6504, mitsuh-t@cc.okayama-u.ac.jp %K case-only approach %K mass media %K public health %K social media %K suicidal risk %K suicide prevention %K suicide %K suicide-related tweets %K Twitter %D 2023 %7 10.8.2023 %9 Original Paper %J JMIR Form Res %G English %X Background: As the use of social media becomes more widespread, its impact on health cannot be ignored. However, limited research has been conducted on the relationship between social media and suicide. Little is known about individuals’ vulnerable to suicide, especially when social media suicide information is extremely prevalent. Objective: This study aims to identify the characteristics underlying individuals’ vulnerability to suicide brought about by an increase in suicide-related tweets, thereby contributing to public health. Methods: A case-only design was used to investigate vulnerability to suicide using individual data of people who died by suicide and tweet data from January 1, 2011, through December 31, 2014. Mortality data were obtained from Japanese government statistics, and tweet data were provided by a commercial service. Tweet data identified the days when suicide-related tweets surged, and the date-keyed merging was performed by considering 3 and 7 lag days. For the merged data set for analysis, the logistic regression model was fitted with one of the personal characteristics of interest as a dependent variable and the dichotomous exposure variable. This analysis was performed to estimate the interaction between the surges in suicide-related tweets and personal characteristics of the suicide victims as case-only odds ratios (ORs) with 95% CIs. For the sensitivity analysis, unexpected deaths other than suicide were considered. Results: During the study period, there were 159,490 suicides and 115,072 unexpected deaths, and the number of suicide-related tweets was 2,804,999. Following the 3-day lag of a highly tweeted day, there were significant interactions for those who were aged 40 years or younger (OR 1.09, 95% CI 1.03-1.15), male (OR 1.12, 95% CI 1.07-1.18), divorced (OR 1.11, 95% CI 1.03 1.19), unemployed (OR 1.12, 95% CI 1.02-1.22), and living in urban areas (OR 1.26, 95% CI 1.17 1.35). By contrast, widowed individuals had significantly lower interactions (OR 0.83, 95% CI 0.77-0.89). Except for unemployment, significant relationships were also observed for the 7-day lag. For the sensitivity analysis, no significant interactions were observed for other unexpected deaths in the 3-day lag, and only the widowed had a significantly larger interaction than those who were married (OR 1.08, 95% CI 1.02-1.15) in the 7-day lag. Conclusions: This study revealed the interactions of personal characteristics associated with susceptibility to suicide-related tweets. In addition, a few significant relationships were observed in the sensitivity analysis, suggesting that such an interaction is specific to suicide deaths. In other words, individuals with these characteristics, such as being young, male, unemployed, and divorced, may be vulnerable to surges in suicide-related tweets. Thus, minimizing public health strain by identifying people who are vulnerable and susceptible to a surge in suicide-related information on the internet is necessary. %M 37561553 %R 10.2196/47798 %U https://formative.jmir.org/2023/1/e47798 %U https://doi.org/10.2196/47798 %U http://www.ncbi.nlm.nih.gov/pubmed/37561553 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 7 %N %P e32592 %T Social Support Among Women With Potential Essure-Related Complaints: Analysis of Facebook Group Content %A van Gastel,Daniëlle %A Antheunis,Marjolijn L %A Tenfelde,Kim %A van de Graaf,Daniëlle L %A Geerts,Marieke %A Nieboer,Theodoor E %A Bongers,Marlies Y %+ Research School GROW, University Maastricht, P Debyelaan 25, Maastricht, 6229 HX, Netherlands, 31 433874800, danielle_vangastel@hotmail.com %K Essure %K social support %K Facebook %K sterilization %K patient online communities %K social media %K social networks %D 2023 %7 3.8.2023 %9 Original Paper %J JMIR Form Res %G English %X Background: Social support groups are an important resource for people to cope with problems. Previous studies have reported the different types of support in these groups, but little is known about the type of reactions that sharing of personal experiences induce among members. It is important to know how and to what extent members of support groups influence each other regarding the consumption of medical care. We researched this in a web-based Facebook group of women sterilized with Essure. Essure was a device intended for permanent contraception. From 2015 onward, women treated with Essure for tubal occlusion raised safety concerns and numerous complaints. Objective: This study aimed to evaluate the use of social support in a Facebook community named “Essure problemen Nederland” (EPN; in English, “Essure problems in the Netherlands”). Methods: All posts in the closed Facebook group EPN between March 8 and May 8, 2018, were included. In total, 3491 Facebook posts were analyzed using a modified version of the Social Support Behavior Codes framework created by Cutrona and Suhr in 1992. Posts were abstracted and aggregated into a database. Two investigators evaluated the posts, developed a modified version of the Social Support Behavior Codes framework, and applied the codes to the collected data. Results: We found that 92% of messages contained a form of social support. In 68.8% of posts, social support was provided, and in 31.2% of posts, social support was received. Informational and emotional support was the most frequently used form of provided social support (40.6% and 55.5%, respectively). The same distribution was seen with received social support: informational support in 81.5% and emotional support in 17.4% of cases. Our analysis showed a strong correlation between providing or receiving social support and the main form of social support (P<.001). In a total of only 74 (2.2%) cases, women advised each other to seek medical care. Conclusions: The main purpose of women in the EPN Facebook group was to provide and receive informational or emotional support or both. %M 37535412 %R 10.2196/32592 %U https://formative.jmir.org/2023/1/e32592 %U https://doi.org/10.2196/32592 %U http://www.ncbi.nlm.nih.gov/pubmed/37535412 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 7 %N %P e43210 %T Using Patient Blogs on Social Media to Assess the Content Validity of Patient-Reported Outcome Measures: Qualitative Analysis of Patient-Written Blogs %A Delnoij,Diana M J %A Derks,Meggie %A Koolen,Laura %A Shekary,Shuka %A Suitela,Jozua %+ Erasmus School of Health Policy & Management, Erasmus University Rotterdam, Burgemeester Oudlaan 50, Rotterdam, 3062 PA, Netherlands, 31 611786435, delnoij@eshpm.eur.nl %K patient stories %K patient-reported outcome measure %K PROM %K social media %K patient stories %K narrative %K patient story %K storytelling %K blogger %K experiential %K experience %K content validity %K content analysis %K qualitative %K cross sectional %K cross-sectional %K chronic disease %K noncommunicable diseases %K NCD %K rheumatoid arthritis %K Parkinson disease, diabetes mellitus %K diabetes %K type II diabetes %K cancer %K breast cancer %K oncology %K International Consortium for Health Outcome Measurement %K ICHOM %K data dictionary %K Health Assessment Questionnaire %K HAQ %K Parkinson Disease Quality of Life Questionnaire %K PDQ %K inductive %K inductive code %D 2023 %7 28.7.2023 %9 Original Paper %J JMIR Form Res %G English %X Background: Patient-reported outcome measures (PROMs) are questionnaires that measure patient outcomes related to quality of life, health, and functioning, and are increasingly used to assess important outcomes from the patient’s perspective. For PROMs to contribute to better health and better care, it is vital that their content validity be adequate. This requires patient involvement in various steps of PROM development. PROM developers not only recognize the benefits of patient involvement but also report difficulties in recruiting patients and experience patient involvement as time-consuming, logistically challenging, and expensive. Objective: This study seeks to explore different strategies for disclosing the experiential knowledge of patients, namely through analyzing patient stories on the web and social media. The research questions are as follows: (1) how do bloggers living with a disease experience their health-related quality of life? (2) How are these experiences reflected in the domains and items of PROMs related to their disease? Methods: First, a qualitative analysis of blogs written by patients was performed. Second, subthemes and underlying codes resulting from this qualitative analysis were systematically compared with the domains and items in PROMs for the respective diseases that the bloggers write about. Blogs were identified via the Google search engine between December 2019 and May 2021. Results: Bloggers describe a wide range of experiences regarding their physical functioning and health; mental well-being; social network and support; daily life, education, work, and leisure; coping; and self-management. Bloggers also write about their positive and negative experiences with health care delivery, the organization of health care, and health care professionals. In general, patients’ experiences as described in blogs were reflected in the domains and items of the PROMs related to their disease. However, except for diabetes mellitus, in all the sets of PROMs, potentially missing topics could be identified. Similarly, with the exception of Parkinson disease, all PROMs address issues that patients did not write about in their blogs and that might therefore be redundant. Conclusions: Web-based patient stories in the form of blogs reveal how people living with a certain disease experience their health-related quality of life. These stories enable analyses of patients’ experiences that can be used to assess the content validity of PROMs. This can be a useful step for researchers who are looking for sets of measuring instruments that match their purposes. %M 37505797 %R 10.2196/43210 %U https://formative.jmir.org/2023/1/e43210 %U https://doi.org/10.2196/43210 %U http://www.ncbi.nlm.nih.gov/pubmed/37505797 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 7 %N %P e43516 %T Identifying Trusted Sources of Lyme Disease Prevention Information Among Internet Users Connected to Academic Public Health Resources: Internet-Based Survey Study %A Kopsco,Heather L %A Krell,Rayda K %A Mather,Thomas N %A Connally,Neeta P %+ Department of Pathobiology, College of Veterinary Medicine, University of Illinois Urbana-Champaign, 2001 South Lincoln Ave, Urbana, IL, 61802, United States, 1 7325709980, hkopsco@illinois.edu %K communication %K consumer health information %K disease %K internet %K Lyme disease %K online %K pathogen %K prevention %K public health %K resources %K social media %K survey %K tickborne disease %K ticks %D 2023 %7 26.7.2023 %9 Original Paper %J JMIR Form Res %G English %X Background: Misinformation about Lyme disease and other tick-transmitted pathogens circulates frequently on the internet and can compete with, or even overshadow, science-based guidance on tick-borne disease (TBD) prevention. Objective: We surveyed internet users connected to academic tick-related resources to identify trusted sources of Lyme disease prevention information, explore confidence in tick bite prevention information, and examine associations of these responses with answers to commonly disputed issues. Methods: The survey was conducted through social media and website pages for Western Connecticut State University Tickborne Disease Prevention Laboratory and the University of Rhode Island TickEncounter Resource Center. Results: Respondents (N=1190) were predominantly female (903/1190, 76.3%), middle-aged (574/1182, 48.6%), and resided in New England states (663/1190, 55.7%). In total 984 of 1186 (83%) respondents identified conventional experts (eg, the Centers for Disease Control [CDC] or other government health agencies, physicians who follow Infectious Diseases Society of America guidelines for Lyme disease treatment guidelines, and academics) as trustworthy TBD prevention resources. However, nearly one-fourth of respondents would first consult personal contacts and web-based communities regarding prevention information before consulting conventional expert sources. The opinions of public health experts and physicians were rated among the top motivators underlying personal prevention decisions; yet, more than 50% of participants revealed distrustful attitudes toward, or were uncertain about, CDC-supported statements related to time to transmission of Lyme disease (708/1190, 59.5%), the safety of diethyltoluamide-based repellents for children (604/1183, 51.1%), and recommended use of antibiotic prophylaxis (773/1181, 65.4%). Multimodal regression models revealed that participants from high-Lyme-disease-incidence states were more likely to first seek TBD prevention information from personal networks and nontraditional sources before approaching conventional sources of TBD prevention information. We found that those reporting high rates of social media usage were more than twice as likely to first seek traditional expert sources of prevention information but were overall more likely to reject CDC-promoted Lyme disease information, in particular the established time to transmission of Lyme disease bacteria. Models also predicted that those participants who disagreed with the conventional scientific view on the antibiotic prophylaxis prevention statement were less likely to be confident in their ability to protect themselves from a tick bite. Overall, uncertainty in one’s ability to protect oneself against tick bites was strongly associated with uncertainty about beliefs in CDC-promoted TBD prevention information. Self-reported trust in experts and frequency of social media use suggest that these platforms may provide opportunities to engage directly with the public about TBD prevention practices. Conclusions: Using strategies to improve public trust and provide information where the public engages on social media may improve prevention communication and adoption of best practices. %M 37494089 %R 10.2196/43516 %U https://formative.jmir.org/2023/1/e43516 %U https://doi.org/10.2196/43516 %U http://www.ncbi.nlm.nih.gov/pubmed/37494089 %0 Journal Article %@ 2564-1891 %I JMIR Publications %V 3 %N %P e41672 %T Exploring Chronic Pain and Pain Management Perspectives: Qualitative Pilot Analysis of Web-Based Health Community Posts %A Harter,Claire %A Ness,Marina %A Goldin,Aleah %A Lee,Christine %A Merenda,Christine %A Riberdy,Anne %A Saha,Anindita %A Araojo,Richardae %A Tarver,Michelle %+ US Food and Drug Administration, WO32 RM2306, 10903 New Hampshire Ave, Silver Spring, MD, 20993, United States, 1 240 402 4228, ChristineS.lee@fda.hhs.gov %K chronic pain %K pain management %K online health community %D 2023 %7 30.5.2023 %9 Original Paper %J JMIR Infodemiology %G English %X Background: Patient perspectives are central to the US Food and Drug Administration’s benefit-risk decision-making process in the evaluation of medical products. Traditional channels of communication may not be feasible for all patients and consumers. Social media websites have increasingly been recognized by researchers as a means to gain insights into patients’ views about treatment and diagnostic options, the health care system, and their experiences living with their conditions. Consideration of multiple patient perspective data sources offers the Food and Drug Administration the opportunity to capture diverse patient voices and experiences with chronic pain. Objective: This pilot study explores posts from a web-based patient platform to gain insights into the key challenges and barriers to treatment faced by patients with chronic pain and their caregivers. Methods: This research compiles and analyzes unstructured patient data to draw out the key themes. To extract relevant posts for this study, predefined keywords were identified. Harvested posts were published between January 1, 2017, and October 22, 2019, and had to include #ChronicPain and at least one other relevant disease tag, a relevant chronic pain management tag, or a chronic pain management tag for a treatment or activity specific to chronic pain. Results: The most common topics discussed among persons living with chronic pain were related to disease burden, the need for support, advocacy, and proper diagnosis. Patients’ discussions focused on the negative impact chronic pain had on their emotions, playing sports, or exercising, work and school, sleep, social life, and other activities of daily life. The 2 most frequently discussed treatments were opioids or narcotics and devices such as transcutaneous electrical nerve stimulation machines and spinal cord stimulators. Conclusions: Social listening data may provide valuable insights into patients’ and caregivers’ perspectives, preferences, and unmet needs, especially when conditions may be highly stigmatized. %M 37252767 %R 10.2196/41672 %U https://infodemiology.jmir.org/2023/1/e41672 %U https://doi.org/10.2196/41672 %U http://www.ncbi.nlm.nih.gov/pubmed/37252767 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 7 %N %P e44754 %T The Digital Impact of Neurosurgery Awareness Month: Retrospective Infodemiology Study %A Malhotra,Kashish %A Dagli,Mert Marcel %A Santangelo,Gabrielle %A Wathen,Connor %A Ghenbot,Yohannes %A Goyal,Kashish %A Bawa,Ashvind %A Ozturk,Ali K %A Welch,William C %+ Department of Neurosurgery, Perelman School of Medicine, University of Pennsylvania, 800 Spruce Street, Philadelphia, PA, 19107, United States, 1 4459429977, Marcel.Dagli@Pennmedicine.upenn.edu %K #NeurosurgeryAwarenessMonth %K #Neurosurgery %K Neurosurgery Awareness Month %K neurosurgery %K neural %K neuro %K health care awareness event %K health care %K awareness %K infodemiology %K social media %K campaign %K neuroscience %K neurological %K sentiment %K public opinion %K Google Trends %K tweet %K Twitter %K brain %K cognition %K cognitive %K machine learning algorithm %K network analysis %K digital media %K sentiment analysis %K node %K Sentiment Viz %K scatterplot %K circumplex model %D 2023 %7 8.5.2023 %9 Original Paper %J JMIR Form Res %G English %X Background: Neurosurgery Awareness Month (August) was initiated by the American Association of Neurological Surgeons with the aim of bringing neurological conditions to the forefront and educating the public about these conditions. Digital media is an important tool for disseminating information and connecting with influencers, general public, and other stakeholders. Hence, it is crucial to understand the impact of awareness campaigns such as Neurosurgery Awareness Month to optimize resource allocation, quantify the efficiency and reach of these initiatives, and identify areas for improvement. Objective: The purpose of our study was to examine the digital impact of Neurosurgery Awareness Month globally and identify areas for further improvement. Methods: We used 4 social media (Twitter) assessment tools (Sprout Social, SocioViz, Sentiment Viz, and Symplur) and Google Trends to extract data using various search queries. Using regression analysis, trends were studied in the total number of tweets posted in August between 2014 and 2022. Two search queries were used in this analysis: one specifically targeting tweets related to Neurosurgery Awareness Month and the other isolating all neurosurgery-related posts. Total impressions and top influencers for #neurosurgery were calculated using Symplur’s machine learning algorithm. To study the context of the tweets, we used SocioViz to isolate the top 100 popular hashtags, keywords, and collaborations between influencers. Network analysis was performed to illustrate the interactions and connections within the digital media environment using ForceAtlas2 model. Sentiment analysis was done to study the underlying emotion of the tweets. Google Trends was used to study the global search interest by studying relative search volume data. Results: A total of 10,007 users were identified as tweeting about neurosurgery during Neurosurgery Awareness Month using the “#neurosurgery” hashtag. These tweets generated over 29.14 million impressions globally. Of the top 10 most influential users, 5 were faculty neurosurgeons at US university hospitals. Other influential users included notable organizations and journals in the field of neurosurgery. The network analysis of the top 100 influencers showed a collaboration rate of 81%. However, only 1.6% of the total neurosurgery tweets were advocating about neurosurgery awareness during Neurosurgery Awareness Month, and only 13 tweets were posted by verified users using the #neurosurgeryawarenessmonth hashtag. The sentiment analysis revealed that the majority of the tweets about Neurosurgery Awareness Month were pleasant with subdued emotion. Conclusions: The global digital impact of Neurosurgery Awareness Month is nascent, and support from other international organizations and neurosurgical influencers is needed to yield a significant digital reach. Increasing collaboration and involvement from underrepresented communities may help to increase the global reach. By better understanding the digital impact of Neurosurgery Awareness Month, future health care awareness campaigns can be optimized to increase global awareness of neurosurgery and the challenges facing the field. %M 37155226 %R 10.2196/44754 %U https://formative.jmir.org/2023/1/e44754 %U https://doi.org/10.2196/44754 %U http://www.ncbi.nlm.nih.gov/pubmed/37155226 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 7 %N %P e44010 %T Critical Analysis and Cross-Comparison Between English and Chinese Websites Providing Online Medical Information for Patients With Adenoid Hypertrophy: Cross-sectional Study %A Jiang,Zheng %A Yang,Xin %A Chen,Fei %A Liu,Jun %+ Department of Otolaryngology, Head and Neck Surgery, West China Hospital, Sichuan University, 37 Guoxue Ln, Wu Hou Qu, Chengdu, 610041, China, 86 18980602242, hxheadneckjunl@163.com %K adenoid hypertrophy %K website quality %K critical analysis %K English and Chinese %K English %K Chinese %K patient %K internet %K online %K decisions %K medical issues %K airway obstruction %K airway %K accessibility %K quality %D 2023 %7 24.4.2023 %9 Original Paper %J JMIR Form Res %G English %X Background: In the information era, patients can easily be misled by inaccurate internet content, thus making not well-informed decisions about medical issues. Adenoid hypertrophy, one of the most common causes of chronic upper airway obstruction in children and adolescents, may lead to serious complications, including sleep apnea and craniofacial change. There have been no critical studies about the quality of websites on adenoid hypertrophy, posing a challenge for users without a medical background to determine which website offers more reliable information. Moreover, the blockage of access to internet search tools such as Google, Yahoo, and others has created an isolated internet environment for the enormous user population in mainland China. Differences in internet legislation, the commercial environment, and culture are also likely to result in varied quality of online health information inside and outside mainland China. To date, no study has compared the quality difference between mainland Chinese and English websites. Objective: The aims of this study were to (1) analyze the quality of websites about adenoid hypertrophy accessible by patients, (2) investigate the quality differences between Chinese and English websites, (3) determine which type of website (eg, government-sponsored, health care provider) is more reliable in terms of medical information, and (4) determine whether the blockage of foreign websites is hindering users’ accessibility to better-quality websites in mainland China. Methods: The first 100 websites (excluding advertisements) displayed on the top three search engines worldwide and in mainland China for the key search term “enlarged adenoids” were collected as the data source. The websites were evaluated based on accessibility, accountability, interactivity, structure, and content quality (accuracy, content coverage, and objectivity). Cohen κ was calculated, and one-way ANOVA and the Kruskal-Wallis test were performed to compare the results between groups and subgroups. Results: The mean score for the content quality of English websites was significantly higher than that of Chinese websites (6.16 vs 4.94, P=.03 for Google, Bing, and Yahoo; 6.16 vs 4.16, P<.001 for Baidu, Sougou, and Bing China). Chinese users who are not influenced by the Internet Censorship System are more likely to access higher-quality online medical information (4.94 vs 4.16, P=.02). In within-group Student-Newman-Keuls q posthoc analysis, professional organization and government-sponsored websites were generally of better quality than other websites for both Chinese and English websites (P<.05). Conclusions: Generally, the English websites on adenoid hypertrophy are of better quality than Chinese websites; thus, Chinese users residing outside of the Chinese mainland are less influenced by inaccurate online medical information. %M 37093621 %R 10.2196/44010 %U https://formative.jmir.org/2023/1/e44010 %U https://doi.org/10.2196/44010 %U http://www.ncbi.nlm.nih.gov/pubmed/37093621 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 7 %N %P e42710 %T Online Health Information Seeking for Mpox in Endemic and Nonendemic Countries: Google Trends Study %A Shepherd,Thomas %A Robinson,Michelle %A Mallen,Christian %+ School of Medicine, Keele University, University Road, Staffordshire, ST5 5BG, United Kingdom, 44 1782 734758, t.a.shepherd1@keele.ac.uk %K monkeypox %K mpox %K infodemiology: surveillance %K public health %K health information seeking %K Google Trends %K joinpoint regression %K epidemic %K outbreak %K infectious disease %K disease %K online %D 2023 %7 13.4.2023 %9 Original Paper %J JMIR Form Res %G English %X Background: The recent global outbreak of mpox (monkeypox) has already been declared a public health emergency of international concern by the World Health Organization. Given the health, social, and economic impacts of the COVID-19 pandemic, there is understandable concern and anxiety around the emergence of another infectious disease—especially one about which little is known. Objective: We used Google Trends to explore online health information seeking patterns for mpox in endemic and nonendemic countries and investigated the impact of the publication of the first in-country case on internet search volume. Methods: Google Trends is a publicly accessible and free data source that aggregates worldwide Google search data. Google search data were used as a surrogate measure of online health information seeking for 178 days between February 18 and August 18, 2022. Searching data were downloaded across this time period for nonendemic countries with the highest case count (United States, Spain, Germany, United Kingdom, and France) and 5 endemic countries (Democratic Republic of Congo, Nigeria, Ghana, Central African Republic, and Cameroon). Joinpoint regression analysis was used to measure changes in searching trends for mpox preceding and following the announcement of the first human case. Results: Online health information seeking significantly increased after the publication of the first case in all the nonendemic countries—United States, Spain, Germany, United Kingdom, and France, as illustrated by significant joinpoint regression models. Joinpoint analysis revealed that models with 3 significant joinpoints were the most appropriate fit for these data, where the first joinpoint represents the initial rise in mpox searching trend, the second joinpoint reflects the start of the decrease in the mpox searching trend, and the third joinpoint represents searching trends’ return to searching levels prior to the first case announcement. Although this model was also found in 2 endemic countries (ie, Ghana and Nigeria), it was not found in Central African Republic, Democratic Republic of Congo, or Cameroon. Conclusions: Findings demonstrate a surge in online heath information seeking relating to mpox after the first in-country case was publicized in all the nonendemic countries and in Ghana and Nigeria among the endemic counties. The observed increases in mpox searching levels are characterized by sharp but short-lived periods of searching before steep declines back to levels observed prior to the publication of the first case. These findings emphasize the importance of the provision of accurate, relevant online public health information during disease outbreaks. However, online health information seeking behaviors only occur for a short time period, and the provision of accurate information needs to be timely in relation to the publication of new case-related information. %M 37052999 %R 10.2196/42710 %U https://formative.jmir.org/2023/1/e42710 %U https://doi.org/10.2196/42710 %U http://www.ncbi.nlm.nih.gov/pubmed/37052999 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 7 %N %P e42346 %T Characterizing e-Cigarette–Related Videos on TikTok: Observational Study %A Xie,Zidian %A Xue,Siyu %A Gao,Yankun %A Li,Dongmei %+ Department of Clinical and Translational Research, University of Rochester Medical Center, 265 Crittenden Boulevard Cu 420708, Rochester, NY, 14642-0001, United States, 1 5852767285, Dongmei_Li@urmc.rochester.edu %K e-cigarette %K TikTok %K video %K provaping %K antivaping %D 2023 %7 5.4.2023 %9 Original Paper %J JMIR Form Res %G English %X Background: As a popular social networking platform for sharing short videos, TikTok has been widely used for sharing e-cigarettes or vaping-related videos, especially among the youth. Objective: This study aims to characterize e-cigarette or vaping-related videos and their user engagement on TikTok through descriptive analysis. Methods: From TikTok, a total of 417 short videos, posted between October 4, 2018, and February 27, 2021, were collected using e-cigarette or vaping-related hashtags. Two human coders independently hand-coded the video category and the attitude toward vaping (provaping or antivaping) for each vaping-related video. The social media user engagement measures (eg, the comment count, like count, and share count) for each video category were compared within provaping and antivaping groups. The user accounts posting these videos were also characterized. Results: Among 417 vaping-related TikTok videos, 387 (92.8%) were provaping, and 30 (7.2%) were antivaping videos. Among provaping TikTok videos, the most popular category is vaping tricks (n=107, 27.65%), followed by advertisement (n=85, 21.95%), customization (n=75, 19.38%), TikTok trend (n=70, 18.09%), others (n=44, 11.37%), and education (n=6, 1.55%). By comparison, videos showing the TikTok trend had significantly higher user engagement (like count per video) than other provaping videos. Antivaping videos included 15 (50%) videos with the TikTok trend, 10 (33.33%) videos on education, and 5 (16.67%) videos about others. Videos with education have a significantly lower number of likes than other antivaping videos. Most TikTok users posting vaping-related videos are personal accounts (119/203, 58.62%). Conclusions: Vaping-related TikTok videos are dominated by provaping videos focusing on vaping tricks, advertisement, customization, and TikTok trend. Videos with the TikTok trend have higher user engagement than other video categories. Our findings provide important information on vaping-related videos shared on TikTok and their user engagement levels, which might provide valuable guidance on future policy making, such as possible restrictions on provaping videos posted on TikTok, as well as how to effectively communicate with the public about the potential health risks of vaping. %M 37018026 %R 10.2196/42346 %U https://formative.jmir.org/2023/1/e42346 %U https://doi.org/10.2196/42346 %U http://www.ncbi.nlm.nih.gov/pubmed/37018026 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 7 %N %P e44055 %T Tracking Population-Level Anxiety Using Search Engine Data: Ecological Study %A Gilbert,Barnabas James %A Lu,Chunling %A Yom-Tov,Elad %+ Department of Brain Sciences, Imperial College London, The Commonwealth Building, Hammersmith Hospital, Du Cane Road, London, W12 0NN, United Kingdom, 44 2075943278, bgilbert@ic.ac.uk %K anxiety disorders %K anxiety themes %K Bing search %K country-level %K epidemiology %K Google trends %K internet search data %K mental disorder %K search engine %K socioeconomic %D 2023 %7 22.3.2023 %9 Original Paper %J JMIR Form Res %G English %X Background: Anxiety disorders are the most prevalent mental disorders globally, with a substantial impact on quality of life. The prevalence of anxiety disorders has increased substantially following the COVID-19 pandemic, and it is likely to be further affected by a global economic recession. Understanding anxiety themes and how they change over time and across countries is crucial for preventive and treatment strategies. Objective: The aim of this study was to track the trends in anxiety themes between 2004 and 2020 in the 50 most populous countries with high volumes of internet search data. This study extends previous research by using a novel search-based methodology and including a longer time span and more countries at different income levels. Methods: We used a crowdsourced questionnaire, alongside Bing search query data and Google Trends search volume data, to identify themes associated with anxiety disorders across 50 countries from 2004 to 2020. We analyzed themes and their mutual interactions and investigated the associations between countries’ socioeconomic attributes and anxiety themes using time-series linear models. This study was approved by the Microsoft Research Institutional Review Board. Results: Query volume for anxiety themes was highly stable in countries from 2004 to 2019 (Spearman r=0.89) and moderately correlated with geography (r=0.49 in 2019). Anxiety themes were predominantly long-term and personal, with “having kids,” “pregnancy,” and “job” the most voluminous themes in most countries and years. In 2020, “COVID-19” became a dominant theme in 27 countries. Countries with a constant volume of anxiety themes over time had lower fragile state indexes (P=.007) and higher individualism (P=.003). An increase in the volume of the most searched anxiety themes was associated with a reduction in the volume of the remaining themes in 13 countries and an increase in 17 countries, and these 30 countries had a lower prevalence of mental disorders (P<.001) than the countries where no correlations were found. Conclusions: Internet search data could be a potential source for predicting the country-level prevalence of anxiety disorders, especially in understudied populations or when an in-person survey is not viable. %M 36947130 %R 10.2196/44055 %U https://formative.jmir.org/2023/1/e44055 %U https://doi.org/10.2196/44055 %U http://www.ncbi.nlm.nih.gov/pubmed/36947130 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 7 %N %P e45147 %T News Media Coverage of the Problem of Purchasing Fake Prescription Medicines on the Internet: Thematic Analysis %A Almomani,Hamzeh %A Patel,Nilesh %A Donyai,Parastou %+ School of Pharmacy, University of Reading, Whiteknights, Reading, RG6 6AP, United Kingdom, 44 118 378 8462, h.q.m.almomani@pgr.reading.ac.uk %K prescription medicine %K internet %K online pharmacy %K fake medicine %K media %K newspaper article %K Theory of Planned Behavior %K thematic analysis %D 2023 %7 21.3.2023 %9 Original Paper %J JMIR Form Res %G English %X Background: More people are turning to internet pharmacies to purchase their prescription medicines. This kind of purchase is associated with serious risks, including the risk of buying fake medicines, which are widely available on the internet. This underresearched issue has been highlighted by many newspaper articles in the past few years. Newspapers can play an important role in shaping public perceptions of the risks associated with purchasing prescription medicines on the internet. Thus, it is important to understand how the news media present this issue. Objective: This study aimed to explore newspaper coverage of the problem of purchasing fake prescription medicines on the internet. Methods: Newspaper articles were retrieved from the ProQuest electronic database using search terms related to the topic of buying fake prescription medicines on the internet. The search was limited to articles published between April 2019 and March 2022 to retrieve relevant articles in this fast-developing field. Articles were included if they were published in English and focused on prescription medicines. Thematic analysis was employed to analyze the articles, and the Theory of Planned Behavior framework was used as a conceptual lens to develop the coding of themes. Results: A total of 106 articles were included and analyzed using thematic analysis. We identified 4 superordinate themes that represent newspaper coverage of the topic of buying prescription medicines on the internet. These themes are (1) the risks of purchasing medicines on the internet (eg, health risks and product quality concerns, financial risks, lack of accountability, risk of purchasing stolen medicines), (2) benefits that entice consumers to make the purchase (eg, convenience and quick purchase, lower cost, privacy of the purchase), (3) social influencing factors of the purchase (influencers, health care providers), and (4) facilitators of the purchase (eg, medicines shortages, pandemic disease such as COVID-19, social media, search engines, accessibility, low risk perception). Conclusions: This theory-based study explored the news media coverage of the problem of fake prescription medicines being purchased on the internet by highlighting the complexity of personal beliefs and the range of external circumstances that could influence people to make these purchases. Further research is needed in this area to identify the factors that lead people to buy prescription medicines on the internet. Identifying these factors could enable the development of interventions to dissuade people from purchasing medicines from unsafe sources on the internet, thus protecting consumers from unsafe or illegal medicines. %M 36943354 %R 10.2196/45147 %U https://formative.jmir.org/2023/1/e45147 %U https://doi.org/10.2196/45147 %U http://www.ncbi.nlm.nih.gov/pubmed/36943354 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 7 %N %P e43334 %T Characterizing Heated Tobacco Products Marketing on Instagram: Observational Study %A Chen,Jiarui %A Xue,Siyu %A Xie,Zidian %A Li,Dongmei %+ Department of Clinical and Translational Research, University of Rochester Medical Center, 265 Crittenden Boulevard Cu 420708, Rochester, NY, 14642-0001, United States, 1 5852767285, Dongmei_Li@urmc.rochester.edu %K IQOS %K Instagram %K heated tobacco products %K web-based tobacco marketing %D 2023 %7 15.3.2023 %9 Original Paper %J JMIR Form Res %G English %X Background: Heated tobacco products (HTPs), including I Quit Ordinary Smoking (IQOS), are new tobacco products that use an electronic device to heat compressed tobacco leaves to generate an aerosol for consumers to inhale. Marketing of HTPs is prevalent on Instagram, a popular social media platform. Objective: This study aims to characterize posts related to HTPs on Instagram and their associations with user engagement. Methods: Through the Instagram application programming interface, 979 Instagram posts were collected using keywords related to HTPs, such as “IQOS” and “heat-not-burn.” Among them, 596 posts were related to IQOS and other HTP marketing. The codebook was developed from a randomly selected 200 posts on the post content by hand coding, which was applied to the remaining 396 Instagram posts. Summary statistics were calculated, and statistical hypothesis testing was conducted to understand the popularity of Instagram posts on HTPs. Negative binomial regression models were applied to identify Instagram post characteristics associated with user engagement (eg, count). Results: Among Instagram posts related to HTP marketing (N=596), “product display” was dominant (n=550, 92.28%), followed by “brand promotion” (n=41, 6.88%), and “others” (n=5, 0.84%). Among posts within “product display,” “device only” was the most popular (n=338, 61.45%), followed by “heatstick only” (n=80, 14.55%), “accessory” (n=66, 12%), “device and heatstick” (n=56, 10.18%), and “capsule” (n=10, 1.82%). A univariate negative binomial regression model with pairwise comparisons across “product display” types showed that the number of likes for posts with HTP heatsticks was significantly lower compared to posts with HTP devices, accessories, and device-heatstick sets. Multivariate negative binomial regression models showed that HTP-related Instagram posts with a model or lifestyle elements (;=.60, 95% CI 0.36-0.84) or without obvious product advertising information (=.69, 95% CI 0.49-0.89) received more likes. Conclusions: It is shown that posts with product displays were dominant among HTP-related posts on Instagram. Posts with model or lifestyle elements are associated with high user engagement, which might be one of the web-based marketing strategies of HTPs. %M 36920463 %R 10.2196/43334 %U https://formative.jmir.org/2023/1/e43334 %U https://doi.org/10.2196/43334 %U http://www.ncbi.nlm.nih.gov/pubmed/36920463 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 7 %N %P e39146 %T Tobacco-Derived Nicotine Pouch Brands and Marketing Messages on Internet and Traditional Media: Content Analysis %A Ling,Pamela M %A Hrywna,Mary %A Talbot,Eugene M %A Lewis,M Jane %+ Center for Tobacco Control Research and Education and Division of General Internal Medicine, University of California San Francisco, 530 Parnassus Ave, Suite 366, San Francisco, CA, 94143, United States, 1 4155148627, pamela.ling@ucsf.edu %K nicotine pouch %K marketing %K tobacco industry %K web-based advertising %K advertising %K advertisement %K smoking %K tobacco %K nicotine %K smoker %K addiction %K industry %K industrial %K economic %K economy %K commercial %K commerce %K consumer %D 2023 %7 15.2.2023 %9 Original Paper %J JMIR Form Res %G English %X Background: Nicotine pouches and lozenges are increasingly available in the United States, and sales are growing. The brands of nicotine pouch products with the largest market share are produced by tobacco companies. Objective: The aim of this study is to examine the marketing of 5 oral nicotine products sold by tobacco companies. Methods: Internet, radio, television, print, and web-based display advertisements between January 2019 and March 2020 for 6 brands of nicotine pouches and lozenges were identified through commercially available marketing surveillance systems supplemented by a manual search of trade press and a review of brand websites. A total of 711 advertisements (122 unique) were analyzed to identify characteristics, themes, marketing strategies, and target audiences, and qualitatively compared by brand. All 5 brand websites were also analyzed. Coders examined the entirety of each advertisement or website for products, marketing claims, and features and recorded the presence or absence of 27 marketing claims and lifestyle elements. Results: All 6 brands of nicotine pouch products spent a total of US $11.2 million on advertising in 2019, with the most (US $10.7 million) spent by the brand Velo, and 86.1% (n=105) of the unique advertisements were web-based. Of the 711 total nicotine pouch advertisements run in 2019, the 2 brands Velo (n=407, 57%) and ZYN (n=303, 42%) dominated. These brands also made the greatest number of advertising claims in general. These claims focused on novelty, modernity, and use in a variety of contexts, including urban contexts, workplaces, transportation, and leisure activities. Of the 122 unique advertisements, ZYN’s most common claims were to be “tobacco-free,” featuring many flavors or varieties, and modern. Velo was the only brand to include urban contexts (n=14, 38.9% of advertisements) or freedom (n=8, 22.2%); Velo advertisements portrayed use in the workplace (n=15, 41.7%), bars or clubs (n=5, 13.9%), leisure activities (n=4, 11.1%), transportation (n=4, 11.1%), sports (n=3, 8.3%), cooking (n=2, 5.6%), and with alcohol (n=1, 2.8%). Velo and ZYN also included most of the images of people, including women and people of color. The 36 Velo ads included people in advertising in 77.8% (n=28) of advertisements, and of those advertisements with identifiable people, 40% (n=4) were young adults and 50% (n=5) were middle-aged. About one-third (n=11, 35.5%) of the 31 unique ZYN advertisements included people, and most identifiable models appeared to be young adults. Brands such as Rogue, Revel, Dryft, and on! focused mainly on product features. All nicotine pouch products made either tobacco-free, smoke-free, spit-free, or vape-free claims. The most common claim overall was “tobacco-free,” found in advertisements from Rogue (1/1, 100%), ZYN (30/31, 96.8%), Velo (19/36, 52.8%), and Dryft (1/3, 33.3%), but not Revel. Conclusions: Nicotine pouches and lozenges may expand the nicotine market as tobacco-free claims alleviate concerns about health harms and advertising features a greater diversity of people and contexts than typical smokeless tobacco advertising. The market leaders and highest-spending brands, ZYN and Velo, included more lifestyle claims. Surveillance of nicotine pouch marketing and uptake, including influence on tobacco use behaviors, is necessary. %M 36790840 %R 10.2196/39146 %U https://formative.jmir.org/2023/1/e39146 %U https://doi.org/10.2196/39146 %U http://www.ncbi.nlm.nih.gov/pubmed/36790840 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 7 %N %P e42706 %T Public Perceptions of the Food and Drug Administration’s Proposed Rules Prohibiting Menthol Cigarettes on Twitter: Observational Study %A Zhou,Runtao %A Tang,Qihang %A Xie,Zidian %A Li,Dongmei %+ Department of Clinical and Translational Research, University of Rochester Medical Center, Saunders Research Building 1.265, 265 Crittenden Boulevard CU 420708, Rochester, NY, 14642-0708, United States, 1 5852767285, Dongmei_Li@urmc.rochester.edu %K menthol cigarettes %K Food and Drug Administration %K FDA %K FDA's proposed rules %K Twitter %K perception %D 2023 %7 10.2.2023 %9 Original Paper %J JMIR Form Res %G English %X Background: On April 28, 2022, the Food and Drug Administration (FDA) proposed rules that prohibited all menthol-flavored cigarettes and other flavored cigars to prevent the initiation of tobacco use in youth and reduce tobacco-related diseases and death. Objective: The objective of this study was to investigate public perceptions of the FDA’s proposed menthol cigarette rules on Twitter. Methods: Through the Twitter streaming application programming interface, tobacco-related tweets were collected between April 28, 2022, and May 27, 2022, using a set of keywords, such as smoking, cigarette, and nicotine. Furthermore, 1941 tweets related to the FDA’s proposed menthol cigarette rules were extracted. Based on 300 randomly selected example tweets, the codebook for the attitudes toward the FDA’s proposed rules and related topics was developed by 2 researchers and was used to label the rest of the tweets. Results: Among tweets related to the FDA’s proposed menthol cigarette rules, 536 (27.61%) showed a positive attitude, 443 (22.82%) had a negative attitude, and 962 (49.56%) had a neutral attitude toward the proposed rules. Social justice (210/536, 39%) and health issues (117/536, 22%) were two major topics in tweets with a positive attitude. For tweets with a negative attitude, alternative tobacco or nicotine products (127/443, 29%) and racial discrimination (84/536, 16%) were two of the most popular topics. Conclusions: In general, the public had a positive attitude toward the FDA’s proposed menthol cigarette rules. Our study provides important information to the FDA on the public perceptions of the proposed menthol cigarette rules, which will be helpful for future FDA regulations on menthol cigarettes. %M 36763414 %R 10.2196/42706 %U https://formative.jmir.org/2023/1/e42706 %U https://doi.org/10.2196/42706 %U http://www.ncbi.nlm.nih.gov/pubmed/36763414 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 7 %N %P e42162 %T Estimating County-Level Overdose Rates Using Opioid-Related Twitter Data: Interdisciplinary Infodemiology Study %A Cuomo,Raphael %A Purushothaman,Vidya %A Calac,Alec J %A McMann,Tiana %A Li,Zhuoran %A Mackey,Tim %+ School of Medicine, University of California, San Diego, 9500 Gilman Dr, La Jolla, CA, 92093, United States, 1 3104352218, racuomo@ucsd.edu %K overdose %K mortality %K geospatial analysis %K social media %K drug overuse %K substance use %K social media data %K mortality estimates %K real-time data %K public health data %K demographic variables %K county-level %D 2023 %7 25.1.2023 %9 Original Paper %J JMIR Form Res %G English %X Background: There were an estimated 100,306 drug overdose deaths between April 2020 and April 2021, a three-quarter increase from the prior 12-month period. There is an approximate 6-month reporting lag for provisional counts of drug overdose deaths from the National Vital Statistics System, and the highest level of geospatial resolution is at the state level. By contrast, public social media data are available close to real-time and are often accessible with precise coordinates. Objective: The purpose of this study is to assess whether county-level overdose mortality burden could be estimated using opioid-related Twitter data. Methods: International Classification of Diseases (ICD) codes for poisoning or exposure to overdose at the county level were obtained from CDC WONDER. Demographics were collected from the American Community Survey. The Twitter Application Programming Interface was used to obtain tweets that contained any of the 36 terms with drug names. An unsupervised classification approach was used for clustering tweets. Population-normalized variables and polynomial population-normalized variables were produced. Furthermore, z scores of the Getis Ord Gi clustering statistic were produced, and both these scores and their polynomial counterparts were explored in regression modeling of county-level overdose mortality burden. A series of linear regression models were used for predictive modeling to explore the interpretability of the analytical output. Results: Modeling overdose mortality with normalized demographic variables alone explained only 7.4% of the variability in county-level overdose mortality, whereas this was approximately doubled by the use of specific demographic and Twitter data covariates based on a backward selection approach. The highest adjusted R2 and lowest AIC (Akaike Info Criterion) were obtained for the model with normalized demographic variables, normalized z scores from geospatial analyses, and normalized topic counts (adjusted R2=0.133, AIC=8546.8). The z scores of the Getis Ord Gi statistic appeared to have improved utility over population-normalization alone. In this model, median age, female population, and tweets about web-based drug sales were positively associated with opioid mortality. Asian race and Hispanic ethnicity were significantly negatively associated with county-level burdens of overdose mortality. Conclusions: Social media data, when transformed using certain statistical approaches, may add utility to the goal of producing closer to real-time county-level estimates of overdose mortality. Prediction of opioid-related outcomes can be advanced to inform prevention and treatment decisions. This interdisciplinary approach can facilitate evidence-based funding decisions for various substance use disorder prevention and treatment programs. %M 36548118 %R 10.2196/42162 %U https://formative.jmir.org/2023/1/e42162 %U https://doi.org/10.2196/42162 %U http://www.ncbi.nlm.nih.gov/pubmed/36548118 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 7 %N %P e38112 %T Estimation of Bedtimes of Reddit Users: Integrated Analysis of Time Stamps and Surveys %A Meyerson,William U %A Fineberg,Sarah K %A Song,Ye Kyung %A Faber,Adam %A Ash,Garrett %A Andrade,Fernanda C %A Corlett,Philip %A Gerstein,Mark B %A Hoyle,Rick H %+ Department of Psychiatry & Behavioral Sciences, Duke University School of Medicine, 3643 N Roxboro St, Durham, NC, 27704, United States, 1 919 695 3567, william.ulysses@gmail.com %K social media %K sleep %K parametric models %K Reddit %K observational model %K research tool %K sleep patterns %K usage data %K model %K bedtime %D 2023 %7 17.1.2023 %9 Original Paper %J JMIR Form Res %G English %X Background: Individuals with later bedtimes have an increased risk of difficulties with mood and substances. To investigate the causes and consequences of late bedtimes and other sleep patterns, researchers are exploring social media as a data source. Pioneering studies inferred sleep patterns directly from social media data. While innovative, these efforts are variously unscalable, context dependent, confined to specific sleep parameters, or rest on untested assumptions, and none of the reviewed studies apply to the popular Reddit platform or release software to the research community. Objective: This study builds on this prior work. We estimate the bedtimes of Reddit users from the times tamps of their posts, test inference validity against survey data, and release our model as an R package (The R Foundation). Methods: We included 159 sufficiently active Reddit users with known time zones and known, nonanomalous bedtimes, together with the time stamps of their 2.1 million posts. The model’s form was chosen by visualizing the aggregate distribution of the timing of users’ posts relative to their reported bedtimes. The chosen model represents a user’s frequency of Reddit posting by time of day, with a flat portion before bedtime and a quadratic depletion that begins near the user’s bedtime, with parameters fitted to the data. This model estimates the bedtimes of individual Reddit users from the time stamps of their posts. Model performance is assessed through k-fold cross-validation. We then apply the model to estimate the bedtimes of 51,372 sufficiently active, nonbot Reddit users with known time zones from the time stamps of their 140 million posts. Results: The Pearson correlation between expected and observed Reddit posting frequencies in our model was 0.997 on aggregate data. On average, posting starts declining 45 minutes before bedtime, reaches a nadir 4.75 hours after bedtime that is 87% lower than the daytime rate, and returns to baseline 10.25 hours after bedtime. The Pearson correlation between inferred and reported bedtimes for individual users was 0.61 (P<.001). In 90 of 159 cases (56.6%), our estimate was within 1 hour of the reported bedtime; 128 cases (80.5%) were within 2 hours. There was equivalent accuracy in hold-out sets versus training sets of k-fold cross-validation, arguing against overfitting. The model was more accurate than a random forest approach. Conclusions: We uncovered a simple, reproducible relationship between Reddit users’ reported bedtimes and the time of day when high daytime posting rates transition to low nighttime posting rates. We captured this relationship in a model that estimates users’ bedtimes from the time stamps of their posts. Limitations include applicability only to users who post frequently, the requirement for time zone data, and limits on generalizability. Nonetheless, it is a step forward for inferring the sleep parameters of social media users passively at scale. Our model and precomputed estimated bedtimes of 50,000 Reddit users are freely available. %M 36649054 %R 10.2196/38112 %U https://formative.jmir.org/2023/1/e38112 %U https://doi.org/10.2196/38112 %U http://www.ncbi.nlm.nih.gov/pubmed/36649054 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 6 %N 12 %P e36755 %T Sample Bias in Web-Based Patient-Generated Health Data of Dutch Patients With Gastrointestinal Stromal Tumor: Survey Study %A Dirkson,Anne %A den Hollander,Dide %A Verberne,Suzan %A Desar,Ingrid %A Husson,Olga %A van der Graaf,Winette T A %A Oosten,Astrid %A Reyners,Anna K L %A Steeghs,Neeltje %A van Loon,Wouter %A van Oortmerssen,Gerard %A Gelderblom,Hans %A Kraaij,Wessel %+ Leiden Institute of Advanced Computer Science, Leiden University, Niels Bohrweg 1, Leiden, 2333 CA, Netherlands, 31 71 527 7096, s.verberne@liacs.leidenuniv.nl %K social media %K patient forum %K sample bias %K representativeness %K pharmacovigilance %K rare cancer %D 2022 %7 15.12.2022 %9 Original Paper %J JMIR Form Res %G English %X Background: Increasingly, social media is being recognized as a potential resource for patient-generated health data, for example, for pharmacovigilance. Although the representativeness of the web-based patient population is often noted as a concern, studies in this field are limited. Objective: This study aimed to investigate the sample bias of patient-centered social media in Dutch patients with gastrointestinal stromal tumor (GIST). Methods: A population-based survey was conducted in the Netherlands among 328 patients with GIST diagnosed 2-13 years ago to investigate their digital communication use with fellow patients. A logistic regression analysis was used to analyze clinical and demographic differences between forum users and nonusers. Results: Overall, 17.9% (59/328) of survey respondents reported having contact with fellow patients via social media. Moreover, 78% (46/59) of forum users made use of GIST patient forums. We found no statistically significant differences for age, sex, socioeconomic status, and time since diagnosis between forum users (n=46) and nonusers (n=273). Patient forum users did differ significantly in (self-reported) treatment phase from nonusers (P=.001). Of the 46 forum users, only 2 (4%) were cured and not being monitored; 3 (7%) were on adjuvant, curative treatment; 19 (41%) were being monitored after adjuvant treatment; and 22 (48%) were on palliative treatment. In contrast, of the 273 patients who did not use disease-specific forums to communicate with fellow patients, 56 (20.5%) were cured and not being monitored, 31 (11.3%) were on curative treatment, 139 (50.9%) were being monitored after treatment, and 42 (15.3%) were on palliative treatment. The odds of being on a patient forum were 2.8 times as high for a patient who is being monitored compared with a patient that is considered cured. The odds of being on a patient forum were 1.9 times as high for patients who were on curative (adjuvant) treatment and 10 times as high for patients who were in the palliative phase compared with patients who were considered cured. Forum users also reported a lower level of social functioning (84.8 out of 100) than nonusers (93.8 out of 100; P=.008). Conclusions: Forum users showed no particular bias on the most important demographic variables of age, sex, socioeconomic status, and time since diagnosis. This may reflect the narrowing digital divide. Overrepresentation and underrepresentation of patients with GIST in different treatment phases on social media should be taken into account when sourcing patient forums for patient-generated health data. A further investigation of the sample bias in other web-based patient populations is warranted. %M 36520526 %R 10.2196/36755 %U https://formative.jmir.org/2022/12/e36755 %U https://doi.org/10.2196/36755 %U http://www.ncbi.nlm.nih.gov/pubmed/36520526 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 6 %N 12 %P e42241 %T Monitoring and Identifying Emerging e-Cigarette Brands and Flavors on Twitter: Observational Study %A Tang,Qihang %A Zhou,Runtao %A Xie,Zidian %A Li,Dongmei %+ Department of Clinical & Translational Research, University of Rochester Medical Center, 265 Crittenden Boulevard CU 420708, Rochester, NY, 14642, United States, 1 808 554 2956, Dongmei_Li@urmc.rochester.edu %K e-cigarettes %K brand %K flavor %K Twitter %D 2022 %7 5.12.2022 %9 Original Paper %J JMIR Form Res %G English %X Background: Flavored electronic cigarettes (e-cigarettes) have become very popular in recent years. e-Cigarette users like to share their e-cigarette products and e-cigarette use (vaping) experiences on social media. e-Cigarette marketing and promotions are also prevalent online. Objective: This study aims to develop a method to identify new e-cigarette brands and flavors mentioned on Twitter and to monitor e-cigarette brands and flavors mentioned on Twitter from May 2021 to December 2021. Methods: We collected 1.9 million tweets related to e-cigarettes between May 3, 2021, and December 31, 2021, by using the Twitter streaming application programming interface. Commercial and noncommercial tweets were characterized based on promotion-related keywords. We developed a depletion method to identify new e-cigarette brands by removing the keywords that already existed in the reference data set (Twitter data related to e-cigarettes from May 3, 2021, to August 31, 2021) or our previously identified brand list from the keywords in the target data set (e-cigarette–related Twitter data from September 1, 2021, to December 31, 2021), followed by a manual Google search to identify new e-cigarette brands. To identify new e-cigarette flavors, we constructed a flavor keyword list based on our previously collected e-cigarette flavor names, which were used to identify potential tweet segments that contain at least one of the e-cigarette flavor keywords. Tweets or tweet segments with flavor keywords but not any known flavor names were marked as potential new flavor candidates, which were further verified by a web-based search. The longitudinal trends in the number of tweets mentioning e-cigarette brands and flavors were examined in both commercial and noncommercial tweets. Results: Through our developed methods, we identified 34 new e-cigarette brands and 97 new e-cigarette flavors from commercial tweets as well as 56 new e-cigarette brands and 164 new e-cigarette flavors from noncommercial tweets. The longitudinal trend of the e-cigarette brands showed that JUUL was the most popular e-cigarette brand mentioned on Twitter; however, there was a decreasing trend in the mention of JUUL over time on Twitter. Menthol flavor was the most popular e-cigarette flavor mentioned in the commercial tweets, whereas mango flavor was the most popular e-cigarette flavor mentioned in the noncommercial tweets during our study period. Conclusions: Our proposed methods can successfully identify new e-cigarette brands and flavors mentioned on Twitter. Twitter data can be used for monitoring the dynamic changes in the popularity of e-cigarette brands and flavors. %M 36469415 %R 10.2196/42241 %U https://formative.jmir.org/2022/12/e42241 %U https://doi.org/10.2196/42241 %U http://www.ncbi.nlm.nih.gov/pubmed/36469415 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 6 %N 11 %P e38425 %T Prevalence and Correlates of COVID-19 Vaccine Information on Family Medicine Practices’ Websites in the United States: Cross-sectional Website Content Analysis %A Ackleh-Tingle,Jonathan V %A Jordan,Natalie M %A Onwubiko,Udodirim N %A Chandra,Christina %A Harton,Paige E %A Rentmeester,Shelby T %A Chamberlain,Allison T %+ Department of Epidemiology, Rollins School of Public Health, Emory University, 1518 Clifton Road, Atlanta, GA, 30322, United States, 1 404 727 6159, jonathan.tingle@emory.edu %K primary care %K vaccine hesitancy %K COVID-19 %K health communications %K health information %K health website %K family practice %K primary care %K vaccine information %K online health %K health platform %K online information %D 2022 %7 17.11.2022 %9 Original Paper %J JMIR Form Res %G English %X Background: Primary care providers are regarded as trustworthy sources of information about COVID-19 vaccines. Although primary care practices often provide information about common medical and public health topics on their practice websites, little is known about whether they also provide information about COVID-19 vaccines on their practice websites. Objective: This study aimed to investigate the prevalence and correlates of COVID-19 vaccine information on family medicine practices’ website home pages in the United States. Methods: We used the Centers for Medicare and Medicaid National Provider Identifier records to create a sampling frame of all family medicine providers based in the United States, from which we constructed a nationally representative random sample of 964 family medicine providers. Between September 20 and October 8, 2021, we manually examined the practice websites of these providers and extracted data on the availability of COVID-19 vaccine information, and we implemented a 10% cross-review quality control measure to resolve discordances in data abstraction. We estimated the prevalence of COVID-19 vaccine information on practice websites and website home pages and used Poisson regression with robust error variances to estimate crude and adjusted prevalence ratios for correlates of COVID-19 vaccine information, including practice size, practice region, university affiliation, and presence of information about seasonal influenza vaccines. Additionally, we performed sensitivity analyses to account for multiple comparisons. Results: Of the 964 included family medicine practices, most (n=509, 52.8%) had ≥10 distinct locations, were unaffiliated with a university (n=838, 87.2%), and mentioned seasonal influenza vaccines on their websites (n=540, 56.1%). In total, 550 (57.1%) practices mentioned COVID-19 vaccines on their practices’ website home page, specifically, and 726 (75.3%) mentioned COVID-19 vaccines anywhere on their practice website. As practice size increased, the likelihood of finding COVID-19 vaccine information on the home page increased (n=66, 27.7% among single-location practices, n=114, 52.5% among practices with 2-9 locations, n=66, 56.4% among practices with 10-19 locations, and n=304, 77.6% among practices with 20 or more locations, P<.001 for trend). Compared to clinics in the Northeast, those in the West and Midwest United States had a similar prevalence of COVID-19 vaccine information on website home pages, but clinics in the south had a lower prevalence (adjusted prevalence ratio 0.8, 95% CI 0.7 to 1.0; P=.02). Our results were largely unchanged in sensitivity analyses accounting for multiple comparisons. Conclusions: Given the ongoing COVID-19 pandemic, primary care practitioners who promote and provide vaccines should strongly consider utilizing their existing practice websites to share COVID-19 vaccine information. These existing platforms have the potential to serve as an extension of providers’ influence on established and prospective patients who search the internet for information about COVID-19 vaccines. %M 36343211 %R 10.2196/38425 %U https://formative.jmir.org/2022/11/e38425 %U https://doi.org/10.2196/38425 %U http://www.ncbi.nlm.nih.gov/pubmed/36343211 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 6 %N 11 %P e38862 %T The Use of 2 e-Learning Modalities for Diabetes Education Using Facebook in 2 Cities of Argentina During the COVID-19 Pandemic: Qualitative Study %A Moyano,Daniela Luz %A Lopez,María Victoria %A Cavallo,Ana %A Candia,Julia Patricia %A Kaen,Aaron %A Irazola,Vilma %A Beratarrechea,Andrea %+ Department of Research on Chronic Diseases, Institute for Clinical Effectiveness and Health Policy, Dr Emilio Ravignani 2024, Buenos Aires, C1414CPV, Argentina, 54 114777 8767, dmoyano@iecs.org.ar %K COVID-19 %K social media %K diabetes mellitus %K public health %K qualitative research %K COVID-19 pandemic %K teaching and learning settings %K online learning %K eHealth literacy %D 2022 %7 16.11.2022 %9 Original Paper %J JMIR Form Res %G English %X Background: The COVID-19 pandemic and the confinement that was implemented in Argentina generated a need to implement innovative tools for the strengthening of diabetes care. Diabetes self-management education (DSME) is a core element of diabetes care; however, because of COVID-19 restrictions, in-person diabetes educational activities were suspended. Social networks have played an instrumental role in this context to provide DSME in 2 cities of Argentina and help persons with diabetes in their daily self-management. Objective: The aim of this study is to evaluate 2 diabetes education modalities (synchronous and asynchronous) using the social media platform Facebook through the content of posts on diabetes educational sessions in 2 cities of Argentina during the COVID-19 pandemic. Methods: In this qualitative study, we explored 2 modalities of e-learning (synchronous and asynchronous) for diabetes education that used the Facebook pages of public health institutions in Chaco and La Rioja, Argentina, in the context of confinement. Social media metrics and the content of the messages posted by users were analyzed. Results: A total of 332 messages were analyzed. We found that in the asynchronous modality, there was a higher number of visualizations, while in the synchronous modality, there were more posts and interactions between educators and users. We also observed that the number of views increased when primary care clinics were incorporated as disseminators, sharing educational videos from the sessions via social media. Positive aspects were observed in the posts, consisting of messages of thanks and, to a lesser extent, reaffirmations, reflections or personal experiences, and consultations related to the subject treated. Another relevant finding was that the educator/moderator role had a greater presence in the synchronous modality, where posts were based on motivation for participation, help to resolve connectivity problems, and answers to specific user queries. Conclusions: Our findings show positive contributions of an educational intervention for diabetes care using the social media platform Facebook in the context of the COVID-19 pandemic. Although each modality (synchronous vs asynchronous) could have differential and particular advantages, we believe that these strategies have potential to be replicated and adapted to other contexts. However, more documented experiences are needed to explore their sustainability and long-term impact from the users' perspective. %M 36322794 %R 10.2196/38862 %U https://formative.jmir.org/2022/11/e38862 %U https://doi.org/10.2196/38862 %U http://www.ncbi.nlm.nih.gov/pubmed/36322794 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 6 %N 11 %P e37698 %T The Emotional Anatomy of the Wuhan Lockdown: Sentiment Analysis Using Weibo Data %A Chen,Xi %A Yik,Michelle %+ Division of Social Science, Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, China, 852 23587815, Michelle.Yik@ust.hk %K Wuhan lockdown %K COVID-19 %K public health emergency %K emotion %K circumplex model of affect %K Weibo %K jiayou %D 2022 %7 14.11.2022 %9 Original Paper %J JMIR Form Res %G English %X Background: On January 23, 2020, the city of Wuhan, China, was sealed off in response to the COVID-19 pandemic. Studies have found that the lockdown was associated with both positive and negative emotions, although their findings are not conclusive. In these studies, emotional responses to the Wuhan lockdown were identified using lexicons based on limited emotion types. Objective: This study aims to map Chinese people’s emotional responses to the Wuhan lockdown and compare Wuhan residents’ emotions with those of people elsewhere in China by analyzing social media data from Weibo using a lexicon based on the circumplex model of affect. Methods: Social media posts on Weibo from 2 weeks before to 2 weeks after the Wuhan lockdown was imposed (January 9, 2020, to February 6, 2020) were collected. Each post was coded using a valence score and an arousal score. To map emotional trajectories during the study period, we used a data set of 359,190 posts. To compare the immediate emotional responses to the lockdown and its longer-term emotional impact on Wuhan residents (n=1236) and non-Hubei residents (n=12,714), we used a second data set of 57,685 posts for multilevel modeling analyses. Results: Most posts (248,757/359,190, 69.25%) made during the studied lockdown period indicated a pleasant mood with low arousal. A gradual increase in both valence and arousal before the lockdown was observed. The posts after the lockdown was imposed had higher valence and arousal than prelockdown posts. On the day of lockdown, the non-Hubei group had a temporarily boosted valence (γ20=0.118; SE 0.021; P<.001) and arousal (γ30=0.293; SE 0.022; P<.001). Compared with non-Hubei residents, the Wuhan group had smaller increases in valence (γ21=−0.172; SE 0.052; P<.001) and arousal (γ31=−0.262; SE 0.053; P<.001) on the day of lockdown. Weibo users’ emotional valence (γ40=0.000; SE 0.001; P=.71) and arousal (γ40=0.001; SE 0.001; P=.56) remained stable over the 2 weeks after the lockdown was imposed regardless of geographical location (valence: γ41=−0.004, SE 0.003, and P=.16; arousal: γ41=0.003, SE 0.003, and P=.26). Conclusions: During the early stages of the pandemic, most Weibo posts indicated a pleasant mood with low arousal. The overall increase in the posts’ valence and arousal after the lockdown announcement might indicate collective cohesion and mutual support in web-based communities during a public health crisis. Compared with the temporary increases in valence and arousal of non-Hubei users on the day of lockdown, Wuhan residents’ emotions were less affected by the announcement. Overall, our data suggest that Weibo users were not influenced by the lockdown measures in the 2 weeks after the lockdown announcement. Our findings offer policy makers insights into the usefulness of social connections in maintaining the psychological well-being of people affected by a lockdown. %M 36166650 %R 10.2196/37698 %U https://formative.jmir.org/2022/11/e37698 %U https://doi.org/10.2196/37698 %U http://www.ncbi.nlm.nih.gov/pubmed/36166650 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 6 %N 11 %P e39912 %T User Engagement Within an Online Peer Support Community (Depression Connect) and Recovery-Related Changes in Empowerment: Longitudinal User Survey %A Smit,Dorien %A Vrijsen,Janna N %A Broekman,Theo %A Groeneweg,Bart %A Spijker,Jan %+ Pro Persona Mental Health Care, Pro Persona Research, Depression Expertise Centre, Nijmeegsebaan 61, Nijmegen, 6525 DX, Netherlands, 31 647074551, d.smit@propersona.nl %K depression %K online peer support community %K internet support group %K experiential knowledge %K self-management %K empowerment %K user engagement %K longitudinal user survey %D 2022 %7 2.11.2022 %9 Original Paper %J JMIR Form Res %G English %X Background: The chronic nature of depression and limited availability of evidence-based treatments emphasize the need for complementary recovery-oriented services, such as peer support interventions (PSIs). Peer support is associated with positive effects on clinical and personal recovery from mental illness, but little is known about the processes of engagement that foster change, and studies targeting individuals with depression specifically are limited. Objective: This study aimed to evaluate whether the level of user engagement, assessed on several dimensions, in an online peer support community for individuals with depression promotes empowerment and the use of self-management strategies and reduces symptom severity and disability. Methods: In a longitudinal survey conducted from June 2019 to September 2020, we analyzed the data of the users of Depression Connect (DC), an online peer support community hosted by the Dutch Patient Association for Depression and the Pro Persona Mental Health Care institute, on measures of empowerment, self-management, depression, and disability. Of the 301 respondents, 49 (16.3%) respondents completed the survey again after 3 months and 74 (24.6%) respondents, after 6 months. Analysis of 3 parameters (ie, total time spent on the platform, number of page views, and number of posts) derived from their data logs yielded 4 engagement profiles. Linear mixed models were fitted to determine whether the outcomes had significantly changed over time and differed for the various profiles. Results: Baseline engagement with the online peer support community was “very low” (177/301, 58.8%) or “low” (87/301, 28.9%) for most of the participants, with few showing “medium” (30/301, 9.9%) or “high” engagement patterns (7/301, 2.3%), while user profiles did not differ in demographic and clinical characteristics. Empowerment, self-management, depressive symptoms, and disability improved over time, but none were associated with the intensity or nature of user engagement. Conclusions: With most DC members showing very low to low engagement and only a few being identified as high-engaged users, it is likely that this flexibility in use frequency is what provides value to online PSI users. In other more formal supportive environments for depression, a certain level of engagement is predetermined either by their organizational or by their societal context; at DC, users can adapt the intensity and nature of their engagement to their current needs on their personal road to recovery. This study added to the current knowledge base on user engagement for PSIs because previous studies targeting depression with an online format focused on active users, precluding passive and flexible engagement. Future studies should explore the content and quality of the interactions in online PSIs to identify optimal user engagement as a function of current, self-reported clinical parameters and reasons to engage in the PSI. %M 36322110 %R 10.2196/39912 %U https://formative.jmir.org/2022/11/e39912 %U https://doi.org/10.2196/39912 %U http://www.ncbi.nlm.nih.gov/pubmed/36322110 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 6 %N 10 %P e40049 %T Examining the Twitter Discourse on Dementia During Alzheimer’s Awareness Month in Canada: Infodemiology Study %A Bacsu,Juanita-Dawne %A Cammer,Allison %A Ahmadi,Soheila %A Azizi,Mehrnoosh %A Grewal,Karl S %A Green,Shoshana %A Gowda-Sookochoff,Rory %A Berger,Corinne %A Knight,Sheida %A Spiteri,Raymond J %A O'Connell,Megan E %+ Department of Psychology, Canadian Centre for Health and Safety in Agriculture, University of Saskatchewan, Arts 182, 9 Campus Drive, Saskatoon, SK, S7N 5A5, Canada, 1 306 250 4399, juanita.bacsu@usask.ca %K Twitter %K social media %K dementia %K Alzheimer disease %K awareness %K public health campaigns %D 2022 %7 26.10.2022 %9 Original Paper %J JMIR Form Res %G English %X Background: Twitter has become a primary platform for public health campaigns, ranging from mental health awareness week to diabetes awareness month. However, there is a paucity of knowledge about how Twitter is being used during health campaigns, especially for Alzheimer’s Awareness Month. Objective: The purpose of our study was to examine dementia discourse during Canada’s Alzheimer’s Awareness Month in January to inform future awareness campaigns. Methods: We collected 1289 relevant tweets using the Twint application in Python from January 1 to January 31, 2022. Thematic analysis was used to analyze the data. Results: Guided by our analysis, 4 primary themes were identified: dementia education and advocacy, fundraising and promotion, experiences of dementia, and opportunities for future actions. Conclusions: Although our study identified many educational, promotional, and fundraising tweets to support dementia awareness, we also found numerous tweets with cursory messaging (ie, simply referencing January as Alzheimer’s Awareness Month in Canada). While these tweets promoted general awareness, they also highlight an opportunity for targeted educational content to counter stigmatizing messages and misinformation about dementia. In addition, awareness strategies partnering with diverse stakeholders (such as celebrities, social media influencers, and people living with dementia and their care partners) may play a pivotal role in fostering dementia dialogue and education. Further research is needed to develop, implement, and evaluate dementia awareness strategies on Twitter. Increased knowledge, partnerships, and research are essential to enhancing dementia awareness during Canada’s Alzheimer’s Awareness Month and beyond. %M 36287605 %R 10.2196/40049 %U https://formative.jmir.org/2022/10/e40049 %U https://doi.org/10.2196/40049 %U http://www.ncbi.nlm.nih.gov/pubmed/36287605 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 6 %N 10 %P e39324 %T Sociodemographics and Transdiagnostic Mental Health Symptoms in SOCIAL (Studies of Online Cohorts for Internalizing Symptoms and Language) I and II: Cross-sectional Survey and Botometer Analysis %A Lorenzo-Luaces,Lorenzo %A Howard,Jacqueline %A Edinger,Andy %A Yan,Harry Yaojun %A Rutter,Lauren A %A Valdez,Danny %A Bollen,Johan %+ Department of Psychological and Brain Sciences, Indiana University-Bloomington, 1101 E 10th Street, Bloomington, IN, 47401, United States, 1 812 856 0866, lolorenz@indiana.edu %K depression %K anxiety %K pain %K alcohol %K social media %D 2022 %7 20.10.2022 %9 Original Paper %J JMIR Form Res %G English %X Background: Internalizing, externalizing, and somatoform disorders are the most common and disabling forms of psychopathology. Our understanding of these clinical problems is limited by a reliance on self-report along with research using small samples. Social media has emerged as an exciting channel for collecting a large sample of longitudinal data from individuals to study psychopathology. Objective: This study reported the results of 2 large ongoing studies in which we collected data from Twitter and self-reported clinical screening scales, the Studies of Online Cohorts for Internalizing Symptoms and Language (SOCIAL) I and II. Methods: The participants were a sample of Twitter-using adults (SOCIAL I: N=1123) targeted to be nationally representative in terms of age, sex assigned at birth, race, and ethnicity, as well as a sample of college students in the Midwest (SOCIAL II: N=1988), of which 61.78% (1228/1988) were Twitter users. For all participants who were Twitter users, we asked for access to their Twitter handle, which we analyzed using Botometer, which rates the likelihood of an account belonging to a bot. We divided participants into 4 groups: Twitter users who did not give us their handle or gave us invalid handles (invalid), those who denied being Twitter users (no Twitter, only available for SOCIAL II), Twitter users who gave their handles but whose accounts had high bot scores (bot-like), and Twitter users who provided their handles and had low bot scores (valid). We explored whether there were significant differences among these groups in terms of their sociodemographic features, clinical symptoms, and aspects of social media use (ie, platforms used and time). Results: In SOCIAL I, most individuals were classified as valid (580/1123, 51.65%), and a few were deemed bot-like (190/1123, 16.91%). A total of 31.43% (353/1123) gave no handle or gave an invalid handle (eg, entered “N/A”). In SOCIAL II, many individuals were not Twitter users (760/1988, 38.23%). Of the Twitter users in SOCIAL II (1228/1988, 61.78%), most were classified as either invalid (515/1228, 41.94%) or valid (484/1228, 39.41%), with a smaller fraction deemed bot-like (229/1228, 18.65%). Participants reported high rates of mental health diagnoses as well as high levels of symptoms, especially in SOCIAL II. In general, the differences between individuals who provided or did not provide their social media handles were small and not statistically significant. Conclusions: Triangulating passively acquired social media data and self-reported questionnaires offers new possibilities for large-scale assessment and evaluation of vulnerability to mental disorders. The propensity of participants to share social media handles is likely not a source of sample bias in subsequent social media analytics. %M 36264616 %R 10.2196/39324 %U https://formative.jmir.org/2022/10/e39324 %U https://doi.org/10.2196/39324 %U http://www.ncbi.nlm.nih.gov/pubmed/36264616 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 6 %N 9 %P e39274 %T Health Information Sourcing and Health Knowledge Quality: Repeated Cross-sectional Survey %A Korshakova,Elena %A Marsh,Jessecae K %A Kleinberg,Samantha %+ Department of Computer Science, Stevens Institute of Technology, 1 Castle Point on Hudson, Hoboken, NJ, 07030, United States, 1 201 216 5614, samantha.kleinberg@stevens.edu %K health knowledge %K health information seeking %K information dissemination %K COVID-19 %K online health information %K public health %K health literacy %K social media %K information quality %K infodemiology %D 2022 %7 28.9.2022 %9 Original Paper %J JMIR Form Res %G English %X Background: People’s health-related knowledge influences health outcomes, as this knowledge may influence whether individuals follow advice from their doctors or public health agencies. Yet, little attention has been paid to where people obtain health information and how these information sources relate to the quality of knowledge. Objective: We aim to discover what information sources people use to learn about health conditions, how these sources relate to the quality of their health knowledge, and how both the number of information sources and health knowledge change over time. Methods: We surveyed 200 different individuals at 12 time points from March through September 2020. At each time point, we elicited participants’ knowledge about causes, risk factors, and preventative interventions for 8 viral (Ebola, common cold, COVID-19, Zika) and nonviral (food allergies, amyotrophic lateral sclerosis [ALS], strep throat, stroke) illnesses. Participants were further asked how they learned about each illness and to rate how much they trust various sources of health information. Results: We found that participants used different information sources to obtain health information about common illnesses (food allergies, strep throat, stroke) compared to emerging illnesses (Ebola, common cold, COVID-19, Zika). Participants relied mainly on news media, government agencies, and social media for information about emerging illnesses, while learning about common illnesses from family, friends, and medical professionals. Participants relied on social media for information about COVID-19, with their knowledge accuracy of COVID-19 declining over the course of the pandemic. The number of information sources participants used was positively correlated with health knowledge quality, though there was no relationship with the specific source types consulted. Conclusions: Building on prior work on health information seeking and factors affecting health knowledge, we now find that people systematically consult different types of information sources by illness type and that the number of information sources people use affects the quality of individuals’ health knowledge. Interventions to disseminate health information may need to be targeted to where individuals are likely to seek out information, and these information sources differ systematically by illness type. %M 35998198 %R 10.2196/39274 %U https://formative.jmir.org/2022/9/e39274 %U https://doi.org/10.2196/39274 %U http://www.ncbi.nlm.nih.gov/pubmed/35998198 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 6 %N 9 %P e37775 %T Actions Speak Louder Than Words: Sentiment and Topic Analysis of COVID-19 Vaccination on Twitter and Vaccine Uptake %A Yousef,Murooj %A Dietrich,Timo %A Rundle-Thiele,Sharyn %+ Social Marketing @ Griffith, Department of Marketing, Griffith University, 170 Kessels Rd, Nathan, 4111, Australia, 61 434066942, m.yousef@griffith.edu.au %K COVID-19 %K COVID-19 vaccination %K sentiment analysis %K public health campaigns %K vaccine uptake %K Twitter %K social media %K vaccines %D 2022 %7 15.9.2022 %9 Original Paper %J JMIR Form Res %G English %X Background: The lack of trust in vaccines is a major contributor to vaccine hesitancy. To overcome vaccine hesitancy for the COVID-19 vaccine, the Australian government launched multiple public health campaigns to encourage vaccine uptake. This sentiment analysis examines the effect of public health campaigns and COVID-19–related events on sentiment and vaccine uptake. Objective: This study aims to examine the relationship between sentiment and COVID-19 vaccine uptake and government actions that impacted public sentiment about the vaccine. Methods: Using machine learning methods, we collected 137,523 publicly available English language tweets published in Australia between February and October 2021 that contained COVID-19 vaccine–related keywords. Machine learning methods were used to extract topics and sentiments relating to COVID-19 vaccination. The relationship between public vaccination sentiment on Twitter and vaccine uptake was examined. Results: The majority of collected tweets expressed negative (n=91,052, 66%) rather than positive (n=21,686, 16%) or neutral (n=24,785, 18%) sentiments. Topics discussed within the study time frame included the role of the government in the vaccination rollout, availability and accessibility of the vaccine, and vaccine efficacy. There was a significant positive correlation between negative sentiment and the number of vaccine doses administered daily (r267=.15, P<.05), with positive sentiment showing the inverse effect. Public health campaigns, lockdowns, and antivaccination protests were associated with increased negative sentiment, while vaccination mandates had no significant effect on sentiment. Conclusions: The study findings demonstrate that negative sentiment was more prevalent on Twitter during the Australian vaccination rollout but vaccine uptake remained high. Australians expressed anger at the slow rollout and limited availability of the vaccine during the study period. Public health campaigns, lockdowns, and antivaccination rallies increased negative sentiment. In contrast, news of increased vaccine availability for the public and government acquisition of more doses were key government actions that reduced negative sentiment. These findings can be used to inform government communication planning. %M 36007136 %R 10.2196/37775 %U https://formative.jmir.org/2022/9/e37775 %U https://doi.org/10.2196/37775 %U http://www.ncbi.nlm.nih.gov/pubmed/36007136 %0 Journal Article %@ 2564-1891 %I JMIR Publications %V 2 %N 2 %P e38242 %T Web-Based Perspectives of Deemed Consent Organ Donation Legislation in Nova Scotia: Thematic Analysis of Commentary in Facebook Groups %A Marcon,Alessandro R %A Wagner,Darren N %A Giles,Carly %A Isenor,Cynthia %+ Health Law Institute, Faculty of Law, University of Alberta, Office 470, Edmonton, AB, T6G 2H5, Canada, 1 613 620 8970, marcon@ualberta.ca %K organ donation %K organ transplantation %K deemed consent %K presumed consent %K social media %K Facebook %K public perceptions %K public policy %K thematic analysis %D 2022 %7 14.9.2022 %9 Original Paper %J JMIR Infodemiology %G English %X Background: The Canadian province of Nova Scotia recently became the first jurisdiction in North America to implement deemed consent organ donation legislation. Changing the consent models constituted one aspect of a larger provincial program to increase organ and tissue donation and transplantation rates. Deemed consent legislation can be controversial among the public, and public participation is integral to the successful implementation of the program. Objective: Social media constitutes key spaces where people express opinions and discuss topics, and social media discourse can influence public perceptions. This project aimed to examine how the public in Nova Scotia responded to legislative changes in Facebook groups. Methods: Using Facebook’s search engine, we searched for posts in public Facebook groups using the terms “deemed consent,” “presumed consent,” “opt out,” or “organ donation” and “Nova Scotia,” appearing from January 1, 2020, to May 1, 2021. The finalized data set included 2337 comments on 26 relevant posts in 12 different public Nova Scotia–based Facebook groups. We conducted thematic and content analyses of the comments to determine how the public responded to the legislative changes and how the participants interacted with one another in the discussions. Results: Our thematic analysis revealed principal themes that supported and critiqued the legislation, raised specific issues, and reflected on the topic from a neutral perspective. Subthemes showed individuals presenting perspectives through a variety of themes, including compassion, anger, frustration, mistrust, and a range of argumentative tactics. The comments included personal narratives, beliefs about the government, altruism, autonomy, misinformation, and reflections on religion and death. Content analysis revealed that Facebook users reacted to popular comments with “likes” more than other reactions. Comments with the most reactions included both negative and positive perspectives about the legislation. Personal donation and transplantation success stories, as well as attempts to correct misinformation, were some of the most “liked” positive comments. Conclusions: The findings provide key insights into perspectives of individuals from Nova Scotia on deemed consent legislation, as well as organ donation and transplantation broadly. The insights derived from this analysis can contribute to public understanding, policy creation, and public outreach efforts that might occur in other jurisdictions considering the enactment of similar legislation. %M 37113450 %R 10.2196/38242 %U https://infodemiology.jmir.org/2022/2/e38242 %U https://doi.org/10.2196/38242 %U http://www.ncbi.nlm.nih.gov/pubmed/37113450 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 6 %N 9 %P e36525 %T Public Interest and Accessibility of Telehealth in Japan: Retrospective Analysis Using Google Trends and National Surveillance %A Kinoshita,Takuya %A Matsumoto,Takehiro %A Taura,Naota %A Usui,Tetsuya %A Matsuya,Nemu %A Nishiguchi,Mayumi %A Horita,Hozumi %A Nakao,Kazuhiko %+ Department of Medical Informatics, Nagasaki University, 1-7-1 Sakamoto, Nagasaki, 852-8501, Japan, 81 95 819 7529, takuya_kinoshita@nagasaki-u.ac.jp %K COVID-19 %K telehealth %K telemedicine %K public interest %K mobile app %K correlation %K infodemiology, infoveillance %K surveillance %K Google Trends %D 2022 %7 14.9.2022 %9 Original Paper %J JMIR Form Res %G English %X Background: Recently, the use of telehealth for patient treatment under the COVID-19 pandemic has gained interest around the world. As a result, many infodemiology and infoveillance studies using web-based sources such as Google Trends were reported, focusing on the first wave of the COVID-19 pandemic. Although public interest in telehealth has increased in many countries during this time, the long-term interest has remained unknown among people living in Japan. Moreover, various mobile telehealth apps have become available for remote areas in the COVID-19 era, but the accessibility of these apps in epidemic versus nonepidemic regions is unknown. Objective: We aimed to investigate the public interest in telehealth during the first pandemic wave and after the wave in the first part of this study, and the accessibility of medical institutions using telehealth in the epidemic and nonepidemic regions, in the second part. Methods: We examined and compared the first wave and after the wave with regards to severe cases, number of deaths, relative search volume (RSV) of telehealth and COVID-19, and the correlation between RSV and COVID-19 cases, using open sources such as Google Trends and the Japanese Ministry of Health, Labour and Welfare (JMHLW) data. The weekly mean and the week-over-week change rates of RSV and COVID-19 cases were used to examine the correlation coefficients. In the second part, the prevalence of COVID-19 cases, severe cases, number of deaths, and the telehealth accessibility rate were compared between epidemic regions and nonepidemic regions, using the JMHLW data. We also examined the regional correlation between telehealth accessibility and the prevalence of COVID-19 cases. Results: Among the 83 weeks with 5 pandemic waves, the overall mean for the RSV of telehealth and COVID-19 was 11.3 (95% CI 8.0-14.6) and 30.7 (95% CI 27.2-34.2), respectively. The proportion of severe cases (26.54% vs 18.16%; P<.001), deaths (5.33% vs 0.99%; P<.001), RSV of telehealth (mean 33.1, 95% CI 16.2-50.0 vs mean 7.3, 95% CI 6.7-8.0; P<.001), and RSV of COVID-19 (mean 52.1, 95% CI 38.3-65.9 vs mean 26.3, 95% CI 24.4-29.2; P<.001) was significantly higher in the first wave compared to after the wave. In the correlation analysis, the public interest in telehealth was 0.899 in the first wave and –0.300 overall. In Japan, the accessibility of telehealth using mobile apps was significantly higher in epidemic regions compared to nonepidemic regions in both hospitals (3.8% vs 2.0%; P=.004) and general clinics (5.2% vs 3.1%; P<.001). In the regional correlation analysis, telehealth accessibility using mobile apps was 0.497 in hospitals and 0.629 in general clinics. Conclusions: Although there was no long-term correlation between the public interest in telehealth and COVID-19, there was a regional correlation between mobile telehealth app accessibility in Japan, especially for general clinics. We also revealed that epidemic regions had higher mobile telehealth app accessibility. Further studies about the actual use of telehealth and its effect after the COVID-19 pandemic are necessary. %M 36103221 %R 10.2196/36525 %U https://formative.jmir.org/2022/9/e36525 %U https://doi.org/10.2196/36525 %U http://www.ncbi.nlm.nih.gov/pubmed/36103221 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 6 %N 9 %P e37984 %T Discovering Long COVID Symptom Patterns: Association Rule Mining and Sentiment Analysis in Social Media Tweets %A Matharaarachchi,Surani %A Domaratzki,Mike %A Katz,Alan %A Muthukumarana,Saman %+ Department of Statistics, University of Manitoba, 66 Chancellors Cir, Winnipeg, MB, R3T 2N2, Canada, 1 431 338 5077, matharas@myumanitoba.ca %K COVID-19 %K long COVID symptoms %K social media analysis %K association rule mining %K bigram analysis %K natural language processing %K Twitter %K content analysis %K data mining %K infodemiology %K health information %D 2022 %7 7.9.2022 %9 Original Paper %J JMIR Form Res %G English %X Background: The COVID-19 pandemic is a substantial public health crisis that negatively affects human health and well-being. As a result of being infected with the coronavirus, patients can experience long-term health effects called long COVID syndrome. Multiple symptoms characterize this syndrome, and it is crucial to identify these symptoms as they may negatively impact patients’ day-to-day lives. Breathlessness, fatigue, and brain fog are the 3 most common continuing and debilitating symptoms that patients with long COVID have reported, often months after the onset of COVID-19. Objective: This study aimed to understand the patterns and behavior of long COVID symptoms reported by patients on the Twitter social media platform, which is vital to improving our understanding of long COVID. Methods: Long COVID–related Twitter data were collected from May 1, 2020, to December 31, 2021. We used association rule mining techniques to identify frequent symptoms and establish relationships between symptoms among patients with long COVID in Twitter social media discussions. The highest confidence level–based detection was used to determine the most significant rules with 10% minimum confidence and 0.01% minimum support with a positive lift. Results: Among the 30,327 tweets included in our study, the most frequent symptoms were brain fog (n=7812, 25.8%), fatigue (n=5284, 17.4%), breathing/lung issues (n=4750, 15.7%), heart issues (n=2900, 9.6%), flu symptoms (n=2824, 9.3%), depression (n=2256, 7.4%) and general pains (n=1786, 5.9%). Loss of smell and taste, cold, cough, chest pain, fever, headache, and arm pain emerged in 1.6% (n=474) to 5.3% (n=1616) of patients with long COVID. Furthermore, the highest confidence level–based detection successfully demonstrates the potential of association analysis and the Apriori algorithm to establish patterns to explore 57 meaningful relationship rules among long COVID symptoms. The strongest relationship revealed that patients with lung/breathing problems and loss of taste are likely to have a loss of smell with 77% confidence. Conclusions: There are very active social media discussions that could support the growing understanding of COVID-19 and its long-term impact. These discussions enable a potential field of research to analyze the behavior of long COVID syndrome. Exploratory data analysis using natural language processing methods revealed the symptoms and medical conditions related to long COVID discussions on the Twitter social media platform. Using Apriori algorithm–based association rules, we determined interesting and meaningful relationships between symptoms. %M 36069846 %R 10.2196/37984 %U https://formative.jmir.org/2022/9/e37984 %U https://doi.org/10.2196/37984 %U http://www.ncbi.nlm.nih.gov/pubmed/36069846 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 6 %N 8 %P e35563 %T Analyzing Suicide Risk From Linguistic Features in Social Media: Evaluation Study %A Lao,Cecilia %A Lane,Jo %A Suominen,Hanna %+ School of Computing, College of Engineering and Computer Science, The Australian National University, 145 Science Road, Canberra, ACT, 2600, Australia, 61 416236920, cecilia.lao@anu.edu.au %K evaluation study %K interdisciplinary research %K linguistics %K machine learning %K mental health %K natural language processing %K social media %K suicide risk %D 2022 %7 30.8.2022 %9 Original Paper %J JMIR Form Res %G English %X Background: Effective suicide risk assessments and interventions are vital for suicide prevention. Although assessing such risks is best done by health care professionals, people experiencing suicidal ideation may not seek help. Hence, machine learning (ML) and computational linguistics can provide analytical tools for understanding and analyzing risks. This, therefore, facilitates suicide intervention and prevention. Objective: This study aims to explore, using statistical analyses and ML, whether computerized language analysis could be applied to assess and better understand a person’s suicide risk on social media. Methods: We used the University of Maryland Suicidality Dataset comprising text posts written by users (N=866) of mental health–related forums on Reddit. Each user was classified with a suicide risk rating (no, low, moderate, or severe) by either medical experts or crowdsourced annotators, denoting their estimated likelihood of dying by suicide. In language analysis, the Linguistic Inquiry and Word Count lexicon assessed sentiment, thinking styles, and part of speech, whereas readability was explored using the TextStat library. The Mann-Whitney U test identified differences between at-risk (low, moderate, and severe risk) and no-risk users. Meanwhile, the Kruskal-Wallis test and Spearman correlation coefficient were used for granular analysis between risk levels and to identify redundancy, respectively. In the ML experiments, gradient boost, random forest, and support vector machine models were trained using 10-fold cross validation. The area under the receiver operator curve and F1-score were the primary measures. Finally, permutation importance uncovered the features that contributed the most to each model’s decision-making. Results: Statistically significant differences (P<.05) were identified between the at-risk (671/866, 77.5%) and no-risk groups (195/866, 22.5%). This was true for both the crowd- and expert-annotated samples. Overall, at-risk users had higher median values for most variables (authenticity, first-person pronouns, and negation), with a notable exception of clout, which indicated that at-risk users were less likely to engage in social posturing. A high positive correlation (ρ>0.84) was present between the part of speech variables, which implied redundancy and demonstrated the utility of aggregate features. All ML models performed similarly in their area under the curve (0.66-0.68); however, the random forest and gradient boost models were noticeably better in their F1-score (0.65 and 0.62) than the support vector machine (0.52). The features that contributed the most to the ML models were authenticity, clout, and negative emotions. Conclusions: In summary, our statistical analyses found linguistic features associated with suicide risk, such as social posturing (eg, authenticity and clout), first-person singular pronouns, and negation. This increased our understanding of the behavioral and thought patterns of social media users and provided insights into the mechanisms behind ML models. We also demonstrated the applicative potential of ML in assisting health care professionals to assess and manage individuals experiencing suicide risk. %M 36040781 %R 10.2196/35563 %U https://formative.jmir.org/2022/8/e35563 %U https://doi.org/10.2196/35563 %U http://www.ncbi.nlm.nih.gov/pubmed/36040781 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 6 %N 8 %P e34422 %T Local Community Response to Mass Asymptomatic COVID-19 Testing in Liverpool, England: Social Media Analysis %A Robin,Charlotte %A Symons,Charles %A Carter,Holly %+ Behavioural Science and Insights Unit, UK Health Security Agency, Cunard Building, Liverpool, L3 1DS, United Kingdom, 44 0151 706 6243, charlotte.robin@ukhsa.gov.uk %K COVID-19 %K asymptomatic testing %K social media %K attitude %K behavioral science %K testing %K behavior %K community %K England %K acceptance %K barrier %K motivator %K hesitancy %K communication %D 2022 %7 4.8.2022 %9 Original Paper %J JMIR Form Res %G English %X Background: Mass asymptomatic testing for COVID-19 was piloted for the first time in the United Kingdom in Liverpool in November 2020. There is limited evidence on uptake of mass testing, and previously where surge testing has been deployed, uptake has been low. Objective: There was an urgent need to rapidly evaluate acceptance of asymptomatic testing, specifically identifying barriers and facilitators to taking part. Methods: As part of the wider evaluation, we conducted a rapid thematic analysis of local community narratives on social media to provide insights from people unlikely to engage in testing or other standard evaluation techniques, such as surveys or interviews. We identified 3 publicly available data sources: the comments section of a local online newspaper, the city council Facebook page, and Twitter. Data were collected between November 2, 2020, and November 8, 2020, to cover the period between announcement of mass testing in Liverpool and the first week of testing. Overall, 1096 comments were sampled: 219 newspaper comments, 472 Facebook comments, and 405 tweets. Data were analyzed using an inductive thematic approach. Results: Key barriers were accessibility, including site access and concerns over queuing. Queues were also highlighted as a concern due to risk of transmission. Consequences of testing, including an increase in cases leading to further restrictions and financial impact of the requirement for self-isolation, were also identified as barriers. In addition, a lack of trust in authorities and the test (including test accuracy and purpose of testing) was identified. Comments coded as indicative of lack of trust were coded in some cases as indicative of strong collective identity with the city of Liverpool and marginalization due to feeling like test subjects. However, other comments coded as identification with Liverpool were coded as indicative of motivation to engage in testing and encourage others to do so; for this group, being part of a pilot was seen as a positive experience and an opportunity to demonstrate the city could successfully manage the virus. Conclusions: Our analysis highlights the importance of promoting honest and open communication to encourage and harness existing community identities to enhance the legitimacy of asymptomatic testing as a policy. In addition, adequate and accessible financial support needs to be in place prior to the implementation of community asymptomatic testing to mitigate any concerns surrounding financial hardship. Rapid thematic analysis of social media is a pragmatic method to gather insights from communities around acceptability of public health interventions, such as mass testing or vaccination uptake. %M 35658094 %R 10.2196/34422 %U https://formative.jmir.org/2022/8/e34422 %U https://doi.org/10.2196/34422 %U http://www.ncbi.nlm.nih.gov/pubmed/35658094 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 6 %N 7 %P e36268 %T Sex Workers’ Lived Experiences With COVID-19 on Social Media: Content Analysis of Twitter Posts %A Al-Rawi,Ahmed %A Zemenchik,Kiana %+ School of Communication, Simon Fraser University, 8888 University Dr., Burnaby, BC, V5A 1S6, Canada, 1 778 782 4419, aalrawi@sfu.ca %K sex work %K social media %K COVID-19 %K pandemic %K Twitter %K infodemiology %K social stigma %K sex worker %K risk %K public health %D 2022 %7 14.7.2022 %9 Original Paper %J JMIR Form Res %G English %X Background: The COVID-19 pandemic has drawn attention to various inequalities in global societies, highlighting discrepancies in terms of safety, accessibility, and overall health. In particular, sex workers are disproportionately at risk due to the nature of their work and the social stigma that comes alongside it. Objective: This study examines how public social media can be used as a tool of professional and personal expression by sex workers during the COVID-19 pandemic. We aimed to explore an underresearched topic by focusing on sex workers’ experiences with the ongoing COVID-19 pandemic on the social media platform Twitter. In particular, we aimed to find the main issues that sex workers discuss on social media in relation to the COVID-19 pandemic. Methods: A literature review followed by a qualitative analysis of 1458 (re)tweets from 22 sex worker Twitter accounts was used for this study. The tweets were qualitatively coded by theme through the use of intercoder reliability. Empirical, experimental, and observational studies were included in this review to provide context and support for our findings. Results: In total, 5 major categories were identified as a result of the content analysis used for this study: concerns (n=542, 37.2%), solicitation (n=336, 23.0%), herd mentality (n=231, 15.8%), humor (n=190, 13.0%), and blame (n=146, 10.0%). The concerns category was the most prominent category, which could be due to its multifaceted nature of including individual concerns, health issues, concerns for essential workers and businesses, as well as concerns about inequalities or intersectionality. When using gender as a control factor, the majority of the results were not noteworthy, save for the blame category, in which sexual and gender minorities (SGMs) were more likely to post content. Conclusions: Though there has been an increase in the literature related to the experiences of sex workers, this paper recommends that future studies could benefit from further examining these 5 major categories through mixed methods research. Examining this phenomenon could recognize the challenges unique to this working community during the COVID-19 pandemic and potentially reduce the widespread stigma associated with sex work in general. %M 35767693 %R 10.2196/36268 %U https://formative.jmir.org/2022/7/e36268 %U https://doi.org/10.2196/36268 %U http://www.ncbi.nlm.nih.gov/pubmed/35767693 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 6 %N 7 %P e36315 %T Exploring Public Perceptions of Dental Care Affordability in the United States: Mixed Method Analysis via Twitter %A Yashpal,Shahen %A Raghunath,Ananditha %A Gencerliler,Nihan %A Burns,Lorel E %+ Department of Endodontics, College of Dentistry, New York University, 345 E 24th Street, New York, NY, 10010, United States, 1 212 998 9332, leb409@nyu.edu %K dentistry %K oral health %K social media %K access to care %K healthcare reform %K COVID-19 %K dental care %K health care service %K twitter %K public health %K health communication %K dental treatment %K health policy %K dental professional %K thematic analysis %D 2022 %7 1.7.2022 %9 Original Paper %J JMIR Form Res %G English %X Background: Dental care expenses are reported to present higher financial barriers than any other type of health care service in the United States. Social media platforms such as Twitter have become a source of public health communication and surveillance. Previous studies have demonstrated the usefulness of Twitter in exploring public opinion on aspects of dental care. To date, no studies have leveraged Twitter to examine public sentiments regarding dental care affordability in the United States. Objective: The aim of this study is to understand public perceptions of dental care affordability in the United States on the social media site, Twitter. Methods: Tweets posted between September 1, 2017, and September 30, 2021, were collected using the Snscrape application. Query terms were selected a priori to represent dentistry and financial aspects associated with dental treatment. Data were analyzed qualitatively using both deductive and inductive approaches. In total, 8% (440/5500) of all included tweets were coded to identify prominent themes and subthemes. The entire sample of included tweets were then independently coded into thematic categories. Quantitative data analyses included geographic distribution of tweets by state, volume analysis of tweets over time, and distribution of tweets by content theme. Results: A final sample of 5314 tweets were included in the study. Thematic analysis identified the following prominent themes: (1) general sentiments (1614 tweets, 30.4%); (2) delaying or forgoing dental care (1190 tweets, 22.4%); (3) payment strategies (1019 tweets, 19.2%); (4) insurance (767 tweets, 14.4%); and (5) policy statements (724 tweets, 13.6%). Geographic distributions of the tweets established California, Texas, Florida, and New York as the states with the most tweets. Qualitative analysis revealed barriers faced by individuals to accessing dental care, strategies taken to cope with dental pain, and public perceptions on aspects of dental care policy. The volume and thematic trends of the tweets corresponded to relevant societal events, including the COVID-19 pandemic and debates on health care policy resulting from the election of President Joseph R. Biden. Conclusions: The findings illustrate the real-time sentiment of social media users toward the cost of dental treatment and suggest shortcomings in funding that may be representative of greater systemic failures in the provision of dental care. Thus, this study provides insights for policy makers and dental professionals who strive to increase access to dental care. %M 35658090 %R 10.2196/36315 %U https://formative.jmir.org/2022/7/e36315 %U https://doi.org/10.2196/36315 %U http://www.ncbi.nlm.nih.gov/pubmed/35658090 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 6 %N 6 %P e36771 %T Using Twitter Data for Cohort Studies of Drug Safety in Pregnancy: Proof-of-concept With β-Blockers %A Klein,Ari Z %A O'Connor,Karen %A Levine,Lisa D %A Gonzalez-Hernandez,Graciela %+ Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Blockley Hall, 4th floor, 423 Guardian Dr, Philadelphia, PA, 19014, United States, 1 310 423 3521, ariklein@pennmedicine.upenn.edu %K natural language processing %K social media %K data mining %K pregnancy %K pharmacoepidemiology %D 2022 %7 30.6.2022 %9 Original Paper %J JMIR Form Res %G English %X Background: Despite the fact that medication is taken during more than 90% of pregnancies, the fetal risk for most medications is unknown, and the majority of medications have no data regarding safety in pregnancy. Objective: Using β-blockers as a proof-of-concept, the primary objective of this study was to assess the utility of Twitter data for a cohort study design—in particular, whether we could identify (1) Twitter users who have posted tweets reporting that they took medication during pregnancy and (2) their associated pregnancy outcomes. Methods: We searched for mentions of β-blockers in 2.75 billion tweets posted by 415,690 users who announced their pregnancy on Twitter. We manually reviewed the matching tweets to first determine if the user actually took the β-blocker mentioned in the tweet. Then, to help determine if the β-blocker was taken during pregnancy, we used the time stamp of the tweet reporting intake and drew upon an automated natural language processing (NLP) tool that estimates the date of the user’s prenatal time period. For users who posted tweets indicating that they took or may have taken the β-blocker during pregnancy, we drew upon additional NLP tools to help identify tweets that report their pregnancy outcomes. Adverse pregnancy outcomes included miscarriage, stillbirth, birth defects, preterm birth (<37 weeks gestation), low birth weight (<5 pounds and 8 ounces at delivery), and neonatal intensive care unit (NICU) admission. Normal pregnancy outcomes included gestational age ≥37 weeks and birth weight ≥5 pounds and 8 ounces. Results: We retrieved 5114 tweets, posted by 2339 users, that mention a β-blocker, and manually identified 2332 (45.6%) tweets, posted by 1195 (51.1%) of the users, that self-report taking the β-blocker. We were able to estimate the date of the prenatal time period for 356 pregnancies among 334 (27.9%) of these 1195 users. Among these 356 pregnancies, we identified 257 (72.2%) during which the β-blocker was or may have been taken. We manually verified an adverse pregnancy outcome—preterm birth, NICU admission, low birth weight, birth defects, or miscarriage—for 38 (14.8%) of these 257 pregnancies. We manually verified a gestational age ≥37 weeks for 198 (90.4%) and a birth weight ≥5 pounds and 8 ounces for 50 (22.8%) of the 219 pregnancies for which we did not identify an adverse pregnancy outcome. Conclusions: Our ability to detect pregnancy outcomes for Twitter users who posted tweets reporting that they took or may have taken a β-blocker during pregnancy suggests that Twitter can be a complementary resource for cohort studies of drug safety in pregnancy. %M 35771614 %R 10.2196/36771 %U https://formative.jmir.org/2022/6/e36771 %U https://doi.org/10.2196/36771 %U http://www.ncbi.nlm.nih.gov/pubmed/35771614 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 6 %N 6 %P e34834 %T Pretrained Transformer Language Models Versus Pretrained Word Embeddings for the Detection of Accurate Health Information on Arabic Social Media: Comparative Study %A Albalawi,Yahya %A Nikolov,Nikola S %A Buckley,Jim %+ Department of Computer Science and Information Systems, University of Limerick, Tierney Building, Limerick, V94 T9PX, Ireland, 353 61213028 ext 3724, yahalbalawi@gmail.com %K social media %K machine learning %K pretrained language models %K bidirectional encoder representations from transformers %K BERT %K deep learning %K health information %K infodemiology %K tweets %K language model %K health informatics %K misinformation %D 2022 %7 29.6.2022 %9 Original Paper %J JMIR Form Res %G English %X Background: In recent years, social media has become a major channel for health-related information in Saudi Arabia. Prior health informatics studies have suggested that a large proportion of health-related posts on social media are inaccurate. Given the subject matter and the scale of dissemination of such information, it is important to be able to automatically discriminate between accurate and inaccurate health-related posts in Arabic. Objective: The first aim of this study is to generate a data set of generic health-related tweets in Arabic, labeled as either accurate or inaccurate health information. The second aim is to leverage this data set to train a state-of-the-art deep learning model for detecting the accuracy of health-related tweets in Arabic. In particular, this study aims to train and compare the performance of multiple deep learning models that use pretrained word embeddings and transformer language models. Methods: We used 900 health-related tweets from a previously published data set extracted between July 15, 2019, and August 31, 2019. Furthermore, we applied a pretrained model to extract an additional 900 health-related tweets from a second data set collected specifically for this study between March 1, 2019, and April 15, 2019. The 1800 tweets were labeled by 2 physicians as accurate, inaccurate, or unsure. The physicians agreed on 43.3% (779/1800) of tweets, which were thus labeled as accurate or inaccurate. A total of 9 variations of the pretrained transformer language models were then trained and validated on 79.9% (623/779 tweets) of the data set and tested on 20% (156/779 tweets) of the data set. For comparison, we also trained a bidirectional long short-term memory model with 7 different pretrained word embeddings as the input layer on the same data set. The models were compared in terms of their accuracy, precision, recall, F1 score, and macroaverage of the F1 score. Results: We constructed a data set of labeled tweets, 38% (296/779) of which were labeled as inaccurate health information, and 62% (483/779) of which were labeled as accurate health information. We suggest that this was highly efficacious as we did not include any tweets in which the physician annotators were unsure or in disagreement. Among the investigated deep learning models, the Transformer-based Model for Arabic Language Understanding version 0.2 (AraBERTv0.2)-large model was the most accurate, with an F1 score of 87%, followed by AraBERT version 2–large and AraBERTv0.2-base. Conclusions: Our results indicate that the pretrained language model AraBERTv0.2 is the best model for classifying tweets as carrying either inaccurate or accurate health information. Future studies should consider applying ensemble learning to combine the best models as it may produce better results. %M 35767322 %R 10.2196/34834 %U https://formative.jmir.org/2022/6/e34834 %U https://doi.org/10.2196/34834 %U http://www.ncbi.nlm.nih.gov/pubmed/35767322