Climate and weather factors of temperature and humidity are widely reported to be associated with xerosis (dry skin), a common inflammatory skin condition and frequent driver of pruritus (itchy skin) and reduced quality of life. Growing evidence supports links between environmental conditions and skin barrier function, with extreme climates associated with increased atopic dermatitis-related clinical visits. Mechanistically, temperature and humidity affect the stratum corneum, the skin's primary permeability barrier, with low humidity and high temperature increasing transepidermal water loss and promoting cutaneous inflammation. This study examines the relationship between climate, namely temperature and humidity, and the general public's experience in dry skin and moisturizing products, throughout the United States. This study sought to address gaps in traditional epidemiologic approaches by linking climate conditions with population-level online search behavior related to dry skin and moisturizer use across the United States. Publicly available climate data were obtained from the National Oceanic and Atmospheric Administration (NOAA), including average temperature and dew point by state over a recent nine-year period (2016-2025). Dew point served as a proxy for ambient humidity. Google Trends was used to assess relative search interest for five dry skin- and moisturizer-related terms by state during the same period. Search interest was normalized per million residents, and associations between climate variables and search interest were evaluated using linear regression analyses. Statistical analyses were conducted using R. Lower average temperatures and lower dew points were associated with higher dry skin-related search interest, while warmer, more humid states showed lower interest. Both temperature and dew point demonstrated significant negative associations with Google search interest. This work was not funded and data collection was performed using publicly available, free databases. Population-level search behavior related to xerosis reflects national patterns of climate-associated dermatologic burden.
Elder mistreatment (EM) is a significant public health problem that is frequently underdetected and underreported. Insufficient public recognition and engagement have been hypothesized as one contributor to this underreporting; however, few data sources exist to quantify public awareness or engagement with EM at the population level. This study examined relative internet search interest in EM compared with other forms of abuse (child abuse and domestic violence) in the United States using Google Trends data. We analyzed Google Trends data to compare the Relative Search Index (RSI) for the terms "elder abuse," "child abuse," and "domestic violence" in the United States from December 2018 to December 2023. RSI values reflect normalized search activity relative to the maximum search volume within the specified period. Mean RSI values for "elder abuse" were substantially lower than those for "child abuse" (11.35 vs 50.21) and "domestic violence" (6.96 vs 63.50). Ad hoc tests for stationarity indicated that RSI values for all 3 terms remained stable over the 5-year study period. During Elder Abuse Awareness Month, RSI for "elder abuse" increased relative to "child abuse" and "domestic violence" by 8.3 and 5.7 points, respectively, compared with other months of the year. Relative search interest in elder abuse appears to be persistently lower than that for child abuse and domestic violence, despite modest increases during Elder Abuse Awareness Month. Although Google Trends does not provide a validated measure of public awareness, search-based metrics such as RSI may offer a scalable, low-cost complement to traditional data sources for contextualizing public engagement with EM and informing future awareness, detection, and prevention efforts.
Vitiligo significantly impairs quality of life. Topical ruxolitinib is a novel Janus kinase inhibitor approved for nonsegmental vitiligo, but real-world patient experiences, particularly regarding efficacy, side effects, and access challenges following approval, are not fully captured by clinical trials. Online patient forums like Reddit offer valuable insights into these aspects. This study analyzed discussions on the r/Vitiligo subreddit regarding topical ruxolitinib to understand real-world patient experiences, perceived treatment success, side effects, access barriers, and overall sentiment. We conducted a retrospective, cross-sectional infodemiology study of posts and comments mentioning ruxolitinib or Opzelura on r/Vitiligo between January 2022 and December 2024. After filtering and preprocessing, 2950 entries were analyzed. Computational linguistics (all-MiniLM-L6-v2), including sentence-transformer embeddings for semisupervised topic classification into therapy success, side effects, insurance and cost, and off-topic, were used. Valence Aware Dictionary and Sentiment Reasoner (-1 to +1) for sentiment analysis was assessed. Temporal trends were analyzed; model performance was validated manually against blinded manual annotation of 500 entries. Representative qualitative data were reviewed. Discussions increased following regulatory approvals. Therapy success was the largest cluster (entries: 1765/2950 , 59.83%; 95% CI 58.1 to 61.6) with positive sentiment (mean score 0.473, 95% CI 0.46 to 0.48), frequently describing facial repigmentation and adjunctive use with phototherapy. Users reported encouraging hair repigmentation within treated areas and success even on vitiligo spots present for over 20 years, while noting that areas like hands and feet were particularly treatment-resistant. The side effects cluster (entries: 558/2950, 18.91%; 95% CI 17.5 to 20.3) had negative sentiment (mean score -0.110, 95% CI -0.14 to 0.07), frequently mentioning application-site acne, fatigue, and panic attacks or anemia. The insurance and cost cluster (entries: 491/2950, 16.64%; 95% CI 15.3 to 18.0) had positive sentiment (mean score 0.349, 95% CI 0.31 to 0.39), dominated by discussions on high costs and access difficulties, alongside strategies like co-pay programs but also noting insurance denials. Manual model validation showed substantial agreement (accuracy 88.4%, 95% CI 86 to 91; F1-score 0.893, 95% CI 0.865 to 0.918; Cohen κ 0.801, 95% CI 0.760 to 0.840). Real-world Reddit narratives broadly corroborate clinical trial efficacy signals, particularly facial repigmentation and utility alongside phototherapy, while highlighting practical barriers including frequent application-site acne and cost or insurance friction. These findings have direct clinical and policy implications: clinicians can proactively counsel about the expected benefit on facial areas, monitor and manage acne or irritation, and discuss combination with phototherapy; practices and payers can mitigate access delays using before authorization templates and co-pay assistance. Social media infodemiology thus complements pharmacovigilance and health services research by quantifying patient-reported outcomes and surfacing access issues at scale, informing patient counseling and coverage decisions in routine care.
The month of June has been recognized as the National Cytomegalovirus (CMV) Awareness Month since 2011 in the United States. Established by government resolution, the goal is to increase awareness and reduce the incidence of congenital CMV infection, a leading cause of preventable birth defects and developmental disabilities. Social media is a powerful tool to support public health by making health information easily accessible. With an estimated 246 million users in the United States and more than half of adults seeking health information through such platforms, social media offers an unparalleled opportunity to promote CMV awareness and prevention. This study aimed to evaluate social media messaging before, during, and after the National CMV Awareness Month to assess how the campaign influenced messaging patterns and sentiment related to specific CMV health topics. Publicly available posts on Twitter/X from May to August 2023 that contained at least one of the five most used CMV-related hashtags were collected using a media monitoring platform. The dataset was preprocessed using a customized Bidirectional Encoder Representations from Transformers tokenizer and a language detection package to remove irrelevant and non-English posts. Validated and artificial intelligence (AI) methods (Cohen κ=0.69) were used to determine the thematic content of posts (N=14,900), such as awareness and prevention messaging, and to characterize the sentiment. Changes in post characteristics were measured in relation to the National CMV Awareness Month. CMV-relevant post volume increased by 55% during the campaign month and returned to precampaign levels in July. Overall, academic/university researchers were the most frequent authors, pediatrics was the most frequent population discussed, and vaccines were the most frequently mentioned prevention. Significant associations were observed between the month of post publication and the target audience (χ22=144.3, P<.001), awareness or prevention messaging (χ22=107.8, P<.001), and post sentiment (χ24=163.6, P<.001). The intended audience of posts shifted toward the general population from scientists/health care professionals during the campaign month (adjusted Pearson residuals, P=.009). Awareness messaging increased in June 2023, particularly in relation to CMV transmission and disease burden, while prevention messaging decreased (adjusted Pearson residuals, P=.008). Finally, although posts were generally neutral in sentiment, a significant shift occurred toward a positive sentiment during the campaign month (adjusted Pearson residuals, P=.006), a sentiment that was more likely to engage the user (Kruskal-Wallis; χ22=194.31, P<.001). The National CMV Awareness Month in 2023 shifted the digital CMV conversation toward public-facing messaging and raised awareness efforts. Although posts related to CMV prevention generally conveyed a positive sentiment, prevention messaging declined during the campaign. These findings highlight opportunities for future CMV social media initiatives to balance awareness with prevention through evaluation and strategic design using AI models to strengthen CMV public health communication and engagement.
In China, lung cancer remains a major public health concern and accounts for a substantial proportion of cancer-related deaths nationwide. However, limited research has examined public perceptions of lung cancer in the digital sphere, where health-related information is increasingly disseminated and accessed. This study aims to systematically examine patterns of public attention and perceptions toward lung cancer in China by integrating search engine query data and social media content, thereby enhancing current understanding of web-based health information dynamics related to lung cancer. Data were collected from Baidu Index (BI) (2011-2025) and Sina Weibo (2010-2025) to represent web-based search behavior and social media discourse on lung cancer, respectively. Spatiotemporal patterns of BI, per capita Baidu Index (PBI), and Weibo posts were examined to capture temporal trends and spatial variations. Additionally, the spatial autocorrelation of PBI was assessed using global and local Moran I statistics. PBI-related explanatory variables were assessed using a spatial panel Durbin model. Topic modeling and lexicon-based sentiment analysis were applied to Weibo content to uncover thematic evolution and emotional polarity across years, sex/organization groups, and user types. Public attention toward lung cancer, as reflected by BI, increased initially, peaked in 2019, and subsequently declined, whereas Weibo discussions demonstrated a fluctuating but generally upward trend before stabilizing after 2022. Similar temporal patterns were observed across most provinces. Significant spatial heterogeneity was identified, with higher BI levels concentrated in eastern coastal regions and persistently lower levels in western and southwestern provinces. Spatial autocorrelation analysis revealed stable positive clustering over time, with low-low clusters particularly concentrated in southwestern regions such as Guangxi, and no significant high-high clusters were detected. Panel spatial regression analyses indicated that the provincial PBI was positively associated with gross domestic product (GDP) per capita and average years of education per capita, but negatively associated with the urbanization rate. Moreover, significant spatial spillover effects were observed, suggesting that socioeconomic factors were associated not only with local public attention but also with that of neighboring regions. Topic modeling revealed a clear thematic evolution over time. Although personal experiences initially dominated web-based discourse, discussions progressively shifted toward health care service-related issues, which became the most prominent theme by 2025. Sentiment analysis indicated an overall positive emotional tone throughout the study period, with "Good" and "Disgust" representing the predominant positive and negative emotions, respectively. Emotional expression varied across demographic groups and user types, with noticeable differences in both intensity and temporal trends. This study offers a comprehensive overview of public attention and discourse on lung cancer in China's digital landscape, providing valuable evidence to inform targeted health communication and policy interventions.
A high prevalence of dry eye disease (DED) has intensified public health concerns in Taiwan. With the growing reliance on online resources for health information, platforms such as Google Trends (GT) provide a valuable method for capturing public interest. This approach also allows for the exploration of potential associations between public interest in DED and environmental parameters, which may further elucidate underlying factors contributing to the disease's rising prevalence. This study aims to (1) analyze public interest in DED in Taiwan using GT data, (2) investigate correlations between search interest and environmental parameters, and (3) identify shifts in the focus of search over time. We analyzed GT data from December 2018 to July 2024, focusing on relative search volume (RSV) for DED across Taiwan and its 6 special municipalities. Temporal trends in RSV were assessed using spline regression models, and monthly variations were assessed using the Kruskal-Wallis test. The Spearman correlation analysis was used to evaluate the association between RSV and environmental parameters, while dynamic time warping analysis clarified the temporal alignment of RSV with these parameters. Rising search queries were analyzed to identify shifts in public interest over time. Furthermore, top Google search results for DED-related keywords were assessed for topic coverage, quality, and readability. A significant rising trend in RSV for DED was observed over the study period in Taiwan (mean instantaneous derivative=0.445; P<.001) and across all 6 special municipalities. Environmental parameters such as methane (CH4), total hydrocarbons, and nonmethane hydrocarbons were identified as novel pollutants strongly correlated with RSV (P<.001), along with known pollutants such as nitric oxide (NO), nitrogen dioxide (NO2), sulfur dioxide (SO2), nitrogen oxides (NOx), and carbon monoxide (CO). Dynamic time warping analysis revealed the strongest temporal alignment was between RSV and hydrocarbons, including CH4 and total hydrocarbons, further emphasizing their potential role in influencing public interest. Assessment of web-based DED information of 80 websites revealed generally low quality (DISCERN score: mean 2.14, SD 0.40), and the average readability corresponded to a college reading level (grade: mean 21.1, SD 4.5). Rising search queries shifted from diagnostic and treatment methods before the COVID-19 pandemic to natural remedies during the COVID-19 lockdown and self-diagnosis and treatment options after the pandemic. Gaps were also identified between public interest and the availability of online information. Public interest in DED has increased significantly in Taiwan from 2018 to 2024, with hydrocarbons identified as strongly associated environmental parameters. The shifts in related queries reflect changing public interest, accentuating the need for health care information that aligns with public interest and addresses gaps in available resources.
The quality of health information on social media is a major concern, especially during the early stages of public health crises. While the quality of the results of the popular search engines related to particular diseases has been analyzed in the literature, the quality of health-related information on social media, such as X (formerly Twitter), during the early stages of a public health crisis has not been addressed. This study aims to evaluate the quality of health-related information on social media during the early stages of a public health crisis. A cross-sectional analysis was conducted on health-related tweets in the early stages of the most recent public health crisis (the COVID-19 pandemic). The study analyzed the top 100 websites that were most frequently retweeted in the early stages of the crisis, categorizing them by content type, website affiliation, and exclusivity. Quality and reliability were assessed using the DISCERN and JAMA (Journal of the American Medical Association) benchmarks. Our analyses showed that 95% (95/100) of the websites met only 2 of the 4 JAMA quality criteria. DISCERN scores revealed that 81% (81/100) of the websites were evaluated as low scores, and only 11% (11/100) of the websites were evaluated as high scores. The analysis revealed significant disparities in the quality and reliability of health information across different website affiliations, content types, and exclusivity. This study highlights a significant issue with the quality, reliability, and transparency of online health-related information during a public health challenge. The extensive shortcomings observed across frequently shared websites on Twitter highlight the critical need for continuous evaluation and improvement of online health content during the early stages of future health crises. Without consistent oversight and improvement, we risk repeating the same shortcomings in future, potentially more challenging situations.
Social media platforms offer extensive data, as they are widely used globally. Social media mining (SMM) enables real-time monitoring of user-reported health information and serves as a supplement to traditional health data analytics. However, the rapid proliferation of literature has produced fragmentation, and a comprehensive knowledge map regarding SMM is lacking. Further, existing bibliometric reviews in health fields are easily undermined by synonym fragmentation and parameter settings, reducing their robustness. Thus, a more robust, reproducible, and decision-oriented bibliometric framework is required. This study aimed to (1) outline key thematic clusters in health-related SMM and map their dynamic evolution, and (2) methodologically demonstrate how machine learning-based bibliometric analysis can strengthen the robustness, transparency, and foresight capacity of evidence synthesis. This study designed a fully automated and reproducible bibliometric analysis of PubMed journal articles published from 2015 to 2025 (n=250) and analyzed records with both abstracts and keywords (n=189). We performed cleaning and standardization for titles, abstracts, author keywords, and MeSH terms, and carried out an exploratory descriptive analysis to obtain preliminary insights into publication patterns. Subsequently, we used SPECTER2 and PubMedBERT embeddings with keywords and abstracts to construct a hybrid similarity matrix. Then, we applied Uniform Manifold Approximation and Projection for dimensionality reduction, followed by Hierarchical Density-Based Spatial Clustering of Applications with Noise for thematic clustering, and visualized the results in a 3D strategic coordinate system (maturity, influence, and recency). We performed intercluster relationship analysis and time-slice analysis to examine thematic intersections and evolution. To ensure robustness and enhance interpretability, we implemented dual-level validation. We identified 6 thematic clusters: cluster 1 (candidate incubator pool of peripheral cross-cutting topics in health-related SMM), cluster 2 (computational methods in health informatics), cluster 3 (public attitudes and sociopsychological determinants), cluster 4 (infodemiology and the COVID-19 information ecosystem), cluster 5 (health communication and public health engagement), and cluster 6 (social media analysis and network methods). Strategic 3D mapping revealed that methodological clusters (clusters 2 and 6) occupied high-maturity and high-influence positions, while application-driven clusters (clusters 3 and 4) occupied high-influence and high-recency positions, representing rapidly expanding frontiers. Clusters 1 and 5 demonstrated strong potential for further growth. Temporal slicing confirmed a trajectory moving from methodological consolidation and thematic diversification to a renewed focus on convergence and problem-solving. Validation showed strong semantic coherence and robustness of the methods and findings. We developed a semantic-structural hybrid bibliometric framework with dual-level validation, reducing synonym fragmentation and parameter sensitivity inherent in traditional approaches. The resulting decision-oriented knowledge map offers strategic guidance for infodemiology-informed and audience-segmented public health communication, research priority settings, and the deployment and evaluation of real-world surveillance and pharmacovigilance workflows while supporting evidence-driven and patient-centered decision-making in public health and health care.
Nearly 1 in 4 young adults has a chronic condition, yet many feel well despite their diagnosis. Asymptomatic conditions such as prediabetes and hypertension create a unique vulnerability to digital health misinformation, particularly on platforms where inaccurate content is prevalent. Conventional clinical responses, which often just warn patients about online misinformation, fail to address the underlying drivers of this behavior. This viewpoint proposes a novel disease characteristic-based vulnerability framework to understand this challenge, grounded in established behavioral science theories such as the capability, opportunity, and motivation-behavior model; temporal discounting; and the concept of information voids in infodemiology. We identify a critical "information void" for asymptomatic conditions managed primarily through lifestyle modification. This void, created by the absence of symptomatic feedback combined with delayed clinical biomarker feedback, compels patients to seek information online. Instead of viewing this information seeking as a problematic deviation, we reframe it as a "digital phenotype" indicating a patient's readiness for behavior change. Through case studies illustrating how this framework applies to specific conditions (prediabetes, nonalcoholic fatty liver disease, and untreated hypertension), we demonstrate its practical utility for clinicians, health systems, and policymakers. Evidence supports a multipronged approach: integrating digital health literacy into clinical encounters, providing curated evidence-based resources, and pursuing strategic institutional engagement in digital spaces. While acknowledging the framework's deliberate simplification and the need for culturally sensitive adaptation across diverse health care settings, this viewpoint offers a generalizable strategy for engaging with patients' information needs, helping transform a public health challenge into an opportunity for empowerment.
The global rise of K-pop, particularly the influence of BTS-a South Korean boy band with over 90 million international fans known as ARMY-has shaped youth culture and online communities. Music fandoms are increasingly engaging digital platforms like YouTube not only for entertainment but also as spaces for emotional expression and mutual support. Despite growing interest in the mental health potential of music-based coping strategies, limited research has examined how fandom cultures differentially express emotional needs and supportive interactions online. This study investigates specific mental health language patterns and coping mechanisms expressed by BTS fans in online spaces, examining how different linguistic features (including self-referential language and emotional expression patterns) may reflect psychological states and mental health needs. We utilize YouTube comments of fan-curated "sad" playlists of BTS. We further included YouTube comments from a Taylor Swift "sad" playlist as a reference group. The analysis aims to identify linguistic and emotional expression patterns in BTS fan comments and examine the potential mental health implications of music engagement in digital communities. Using Natural Language Processing (NLP) and Linguistic Inquiry and Word Count (LIWC), we analyzed a total of 13,224 YouTube comments-11,772 comments on a BTS "sad playlist" video and 1,452 comments on a Taylor Swift equivalent. Statistical comparisons were conducted to evaluate differences in comment length, word count, pronoun use, and emotional valence. Representative comments were examined to contextualize the emotion classification results. BTS comments were significantly longer (M = 253.38 words) and had higher word counts (M = 38.93) compared to Taylor Swift comments (M = 89.84 words, M = 16.08), p < .001. BTS fans used more first-person singular pronouns (10.24% vs. 7.43%) and expressed greater sadness (19.8% vs. 7.0%). In contrast, Taylor Swift fans exhibited higher admiration (8.0% vs. 5.0%). Among reply comments, BTS fans demonstrated more caring (7.5% vs. 2.0%), gratitude (9.1% vs. 4.2%), and optimism (5.0% vs. 1.7%). Linguistic analysis also revealed a broader international user base for BTS, including higher proportions of Spanish (6.11%) and Portuguese (1.89%) comments. Examination of comment content showed that fans used these spaces to disclose personal struggles, express gratitude for the community, and offer peer support, with many describing the fandom as a safe space for emotional expression they could not access elsewhere. The findings underscore the significant role that music and fan communities-particularly BTS fandom-play in fostering emotional expression, mutual care, and informal mental health support online. These results suggest implications for culturally responsive, community-based, and digitally mediated mental health interventions among youth and global populations.
Language barriers between Canadian patients and health care providers are associated with poorer health outcomes, including decreased patient safety and quality of care, misdiagnosis and longer treatment initiation times, and increased mortality. However, research exploring language as a social determinant of health is limited, as Canadian health data are scattered across many jurisdictions, each with its own policies and procedures. This fragmentation makes it difficult for researchers to identify, locate, and use existing data. This paper presents the results of a pilot study that attempts to address this gap by creating a metadata repository (MDR) to act as a central source of information about what data are available at which data holdings across Canada. This project aimed to (1) create a proof-of-concept MDR for Canadian health data at the variable level; (2) identify and label language-related variables existing within the MDR data; and (3) develop an interactive, public-facing web application to let users browse and search the MDR. Metadata were collected from 5 Canadian health data sources, including 4 provincial data holdings and 1 national survey, and pooled to create a data repository. Then, we performed bottom-up labeling of language-related variables within the pooled metadata by first using a search string algorithm across all variable labels, names, and definitions and then consensus screening these variables using a derived, standardized definition of language or linguistic variables. Using the Shiny web framework in R, we then developed an openly accessible web application to allow users to search the proof-of-concept MDR. A total of 850,343 variables were collected and included in the repository, with most coming from Ontario (n=712,037, 83.7%) and Manitoba (n=97,051, 11.4%) provincial data holdings. Among all variables in the repository, 213,696 (25.1%) were confirmed to be language related. Developing a national MDR would be a transformative opportunity for Canadian researchers to leverage the full scope of Canadian health administrative data. Although a top-down approach with consistent engagement of and collaboration between provincial data holdings and federal data agencies is ideal to develop a national MDR, this study demonstrates the feasibility of a bottom-up approach in contributing to this overarching goal.
Patients increasingly rely on short-video platforms for information regarding in vitro fertilization (IVF), yet the relationship between the scientific quality of this content and its algorithmic dissemination remains unclear. This study aimed to assess the quality, reliability, and key drivers of dissemination of IVF-related short videos on major Chinese social media platforms. A cross-sectional content analysis was conducted on 300 popular IVF-related videos (the top 100 results from each platform) retrieved from Douyin, Bilibili, and Xiaohongshu between January 10 and 15, 2025. Video quality and reliability were evaluated using the Global Quality Score and a modified DISCERN instrument. Predictors of video dissemination were identified using an Extreme Gradient Boosting machine learning model, with the number of "likes" serving as the primary outcome variable. Content produced by medical professionals demonstrated significantly higher quality and reliability (median mDISCERN 11.0, IQR 9.0-15.0) compared to non-medical sources (median mDISCERN 8.0, IQR 5.0-13.0; P< .001). However, the Extreme Gradient Boosting analysis identified the uploader's follower count as the most powerful predictor of video "likes." In contrast, quality metrics (Global Quality Score and modified DISCERN scores) had a negligible impact on dissemination. In the current Chinese social media landscape, the dissemination of IVF-related videos is strongly associated with creator influence rather than scientific merit. This disconnect between engagement and quality poses a potential risk of misinformation, highlighting the need for medical professionals to adopt platform-native communication strategies to ensure that high-quality information reaches patients.
Male mental health remains a major global concern, with men underrepresented in mental health care and overrepresented in suicide statistics. Masculine norms that link emotional restraint with strength can discourage help-seeking and vulnerability. Anonymous digital spaces such as Reddit (Reddit Inc) and YouTube (Google LLC) have become informal support environments where men share experiences and emotions outside traditional constraints. Understanding these interactions offers insight into masculine identity and help-seeking behavior. This study examines how men discuss and negotiate mental health within anonymous online communities. It explores whether these spaces support emotional openness, peer validation, and challenges to hegemonic masculinity norms. It triangulates digital discourse with survey and interview data to assess how these patterns align with men's lived experiences and perceived barriers to support. This cross-sectional, exploratory mixed methods study analyzed publicly available online discourse from Reddit (n=740 posts) and YouTube (n=6287 comments). The qualitative component included 23 adult men (aged 18-55 years, predominantly Asian and employed) recruited via LinkedIn (Microsoft) who completed an anonymous online survey. Of these, 9 volunteered for follow-up semistructured interviews. Data underwent computational text mining using the Natural Language Toolkit and National Research Council Lexicon for word frequency and emotion analysis, followed by Braun and Clarke's 6-phase reflexive thematic analysis. Online discourse patterns were then compared with survey and interview data. Theoretical frameworks included hegemonic masculinity, toxic positivity, and peer-support theory. Four themes emerged across the datasets: (1) normalizing emotional expression, (2) mutual validation and peer support, (3) coping through humor and irony, and (4) pushback against toxic positivity and societal norms. Emotion analysis showed prominent expressions of sadness, fear, trust, and anger across the Reddit and YouTube corpus. Survey data showed that 20 of 23 (87%) respondents reported having no safe offline space to discuss mental health. Interview participants (n=9) largely confirmed digital discourse themes, though some divergence emerged regarding whether humor functioned as deflection or connection. This study combines large-scale analysis of online discourse with qualitative triangulation across Reddit, YouTube, surveys, and interviews. Theoretically, it extends inclusive masculinity theory into anonymous online contexts, showing how digital platforms enable men to negotiate emotional expression outside traditional masculine constraints. It introduces the concept of "digitally mediated sanctuaries" to describe online spaces where men practice vulnerability and mutual support with less social risk. From an infodemiological perspective, the findings show how mental health information and peer-support narratives circulate and gain legitimacy within male-dominated online communities. Findings can inform gender-sensitive digital mental health interventions that build on features men already use, including humor, anonymity, and peer validation. Digital peer environments may complement formal mental health services by reducing help-seeking barriers for men hesitant to access traditional care.
Youths are increasingly turning to TikTok for mental health information, making the platform an important space where young people encounter portrayals of mental illness. While such visibility can raise awareness, reduce stigma, and make young people feel more connected and understood in their experiences, concerns have been raised about the diagnostic accuracy of this content, which is often produced by nonprofessionals and presented using emotionally appealing stylistic features. Although prior research has examined mental health content on TikTok broadly, little is known about how depression-related symptoms are portrayed by creators on the platform. Given depression's rising prevalence among youth and its prominent presence on TikTok, this study examined (1) the diagnostic accuracy of TikTok videos about depression, (2) differences in diagnostic accuracy and stylistic features by creator type (medical professionals vs nonprofessionals), and (3) how diagnostic accuracy, stylistic features (personal experiences, emotional appeals, and background music), and creator type relate to user engagement. A quantitative content analysis was conducted of 210 English-language TikTok videos retrieved using symptom-focused search terms (eg, "depression symptoms"). Videos were coded for diagnostic accuracy using a standardized coding scheme based on the International Classification of Diseases, 11th Revision diagnostic criteria for depressive episodes. In addition, videos were coded for creator type, presentation style, and the presence of emotionally appealing stylistic features. Engagement was operationalized as the sum of a video's likes, comments, saves, and shares. Intercoder reliability was assessed using Krippendorff α, percent agreement, and Gwet AC1 (agreement coefficient 1). Analyses included Mann-Whitney U tests, chi-square tests, and hierarchical regression. Diagnostic accuracy was low overall (mean score 1.21, SD 1.04, on a 0-4 scale) and did not differ significantly between medical professionals and nonprofessionals (median 1.40 [IQR 1-2] vs 1.11 [IQR 0-2]; P=.06). Hierarchical regression analysis showed that diagnostic accuracy did not predict engagement (B=-0.10; P=.19). In contrast, engagement was higher for videos containing personal experiences (B=0.41; P=.02), emotional appeals (B=0.73; P=.001), and background music (B=0.54; P=.01). Across regression models, direct-to-camera formats (Bs -0.49 to -0.69; .003≤P≤.04) and text-centered videos (Bs -0.56 to -0.64; .002≤P<.01) were associated with lower engagement. Depression-related content on TikTok is characterized by limited diagnostic completeness, regardless of creator type. Engagement appears to be driven primarily by stylistic features rather than diagnostic accuracy. These patterns raise concerns about concept creep-the gradual expansion of the psychological concept for depression-and the potential for premature self-diagnosis among young users, while also highlighting opportunities for medical professionals to adapt their communication styles on TikTok to increase both accuracy and engagement.
Digital media memes have emerged as influential tools in health communication, particularly during the COVID-19 pandemic. While they offer opportunities for emotional engagement and community resilience, they also act as vectors for health misinformation, contributing to the global infodemic. Despite growing interest in their communicative power, the role of memes in shaping public perception and misinformation diffusion remains underexplored in infodemiology. This integrative review aims to analyze how memes influence emotional, behavioral, and ideological responses to health crises, and to examine their dual role as both contributors to and potential mitigators of infodemics. The paper also explores strategies for integrating memes into public health campaigns and infodemic management. A comprehensive literature search was conducted across 3 major databases (MEDLINE, Scopus, and Web of Science), identifying a total of 386 records. Following duplicate removal and eligibility screening, 14 peer-reviewed studies published between 2020 and 2025 were included. An integrative narrative approach was used to synthesize evidence on social media behavior, misinformation dynamics, and digital health campaigns. The analysis was grounded in infodemiological and infoveillance frameworks as established by Eysenbach, incorporating insights from psychology, media studies, and public health. Memes function as emotionally salient and visually potent carriers of health-related narratives. While they can simplify complex messages and foster adaptive humor during crises, they are also susceptible to distortion, particularly in echo chambers and conspiracy communities. Findings reveal that misinformation-laden memes often leverage humor and disgust to bypass critical thinking, and their viral potential is linked to emotional intensity. However, memes have also been successfully integrated into prebunking strategies, increasing engagement and reducing susceptibility to false claims when culturally tailored. The review identifies key mechanisms that enhance or hinder the infodemiological value of memes, including political orientation, digital literacy, and narrative framing. Memes are a double-edged sword in the context of infodemics. Their integration into infodemic surveillance and digital health campaigns requires a nuanced understanding of their emotional, cultural, and epistemic effects. Public health institutions should incorporate meme analysis into real-time infoveillance systems, apply evidence-based meme formats in prebunking efforts, and foster digital literacy that enables critical meme consumption. Future infodemiology research should further explore the long-term behavioral impacts of memetic misinformation and the scalability of meme-based interventions.
Incorporating prespecified Google Trends indicators into leakage-controlled stacked-ensemble models improved a 2025 holdout prediction of subjective well-being by using 2022-2025 data from Japan's 47 prefectures, reducing the mean squared error from 0.0050 to 0.0045.
Alcohol consumption in China poses significant public health challenges. Alcohol marketing has been shown to increase public alcohol consumption, with social media platforms such as Douyin (TikTok in Mainland China) being among the main channels for alcohol marketing. This study aimed to analyze the thematic content of alcohol advertising on the Douyin platform and to explore the factors influencing the popularity of these types of advertising. Using data from the JINGDONG platform and alcohol industry reports, we identified 40 popular alcohol brands. For each brand, we located their official Douyin accounts and selected the top 20 most-liked videos posted between November 1, 2020, and November 1, 2021. In total, 659 videos from 37 brands were collected for analysis. Two trained researchers independently coded each video using a predefined codebook, which consisted of 7 sections and 20 items. Binary logistic regression was conducted with the grouping of the number of likes as the dependent variable, and the marketing strategies and warning elements of each video as independent variables. Among the 659 videos analyzed, 320 (48.6%) garnered more than 1000 likes. A significant portion of the videos was direct advertisements (281/659, 42.6%) and short skits (255/659, 38.7%), with 56.0% (369/659) featuring characters engaging in drinking-related behaviors or directly consuming alcohol. Additionally, many videos highlighted brand elements (510/659, 77.4%) and extended features (161/659, 24.4%). Cultural themes were also common, with 23.2% (153/659) of the videos promoting the enjoyment of life and 6.8% (45/659) emphasizing balance in life. However, age restrictions were missing for 26.9% (177/659) of the videos, and only 1.2% (8/659) included a health warning stating that "Drinking is harmful to health." Certain marketing strategies were significantly associated with greater video popularity, including the use of short skits (odds ratio [OR] 2.77, 95% CI 1.42-5.41), highlighting brand elements (OR 2.96, 95% CI 1.59-5.51), and emphasizing life balance (OR 3.44, 95% CI 1.11-10.66). In contrast, the presence of age restrictions (OR 0.32, 95% CI 0.15-0.67) and explicit health warnings (OR 0.06, 95% CI 0.01-0.84) were associated with lower popularity. The period from July to September and November was the peak release period for alcohol advertisements on Douyin. Alcohol marketing strategies on Douyin leverage experiential, brand-driven, collaborative, and cultural marketing techniques to enhance video attractiveness and create alcogenic environments. Moreover, effective age restrictions and health warnings are largely absent. It is essential to legislate and enforce stricter alcohol marketing regulations to reduce the health risks associated with alcohol marketing.
As TikTok (ByteDance) grows as a major platform for health information, the quality and accuracy of Arabic-language cancer prevention content remain unknown. Limited access to culturally relevant and evidence-based information may exacerbate disparities in cancer knowledge and prevention behaviors. Although large language models offer scalable approaches for analyzing online health content, their utility for short-form video data, especially in underrepresented languages, has not been well established. We aimed to characterize and evaluate the quality of Arabic-language TikTok videos on cancer prevention and explore the use of large language models for scalable content analysis. We used the TikTok research application programming interface and a GPT-assisted keyword strategy to collect Arabic-language TikTok videos (2021-2024). From an initial collection of 1800 TikTok videos, 320 were eligible after preprocessing. Of these, the top 25% (N=30) most-viewed were analyzed and manually coded for content type, cancer type, uploader identity, tone and register, scientific citation, and disclaimers. Video quality was assessed using the Patient Education Materials Assessment Tool for Audiovisual Materials for understandability and actionability, and the Global Quality Scale (GQS). GPT-4 was used to generate artificial intelligence annotations, which were compared to human coding for select variables. The top 25% (N=30) most-viewed videos amassed a total of 21.6 million views. Diet and alternative therapies were most common (15/30, 50%), which included recommendations to reduce hydrogenated oils, increase fruit and vegetable intake, and the use of traditional remedies such as garlic and black seed. Only 6.6% (2/30) of videos cited scientific literature. General cancer (15/30, 53%), breast (5/30, 17%), and cervical (4/30, 13%) cancers were most frequently mentioned. Doctors led 30% (9/30) of videos and were more likely to produce higher quality content, including significantly higher global quality scores (GQS=4, median 4, IQR 4-4 vs 3, median 3, IQR 2-3, P=.06). Over half of the videos had low understandability (16/30, 53%) and actionability (18/30, 60%). Emotionally framed content had the highest engagement across likes and shares, although this did not reach statistical significance (P=.08 and P=.05, respectively). However, emotional tone was significantly associated with lower GQS scores (P=.01). GPT-4 showed high agreement with human coders for cancer type (Cohen κ=1.0), strong agreement for GQS (κ=0.94), but low agreement for tone classification (κ=0.15), due to misclassification of emotional delivery from text-only input. Arabic-language TikTok cancer prevention content is highly engaging but variable in quality, with emotionally framed videos attracting substantial attention despite lower informational value. Artificial intelligence-assisted tools show strong potential for scalable, multilingual health content analysis, but multimodal approaches are needed to accurately interpret tonal and audiovisual features.
Tetanus is a severe but vaccine-preventable neurological disease that remains a public health concern, especially in resource-limited settings. As social media becomes an important source of health information, concerns persist regarding the quality and reliability of tetanus-related content online. This study aimed to evaluate the quality, reliability, and thematic characteristics of tetanus-related videos on YouTube and TikTok and to examine the relationship between engagement metrics and information quality. A cross-sectional study was conducted using tetanus-related videos retrieved from YouTube and TikTok on August 1, 2025. The top 100 eligible videos from each platform were included (n=200). Video quality was assessed using the Global Quality Scale, whereas reliability and transparency were evaluated using the modified DISCERN tool and the Journal of the American Medical Association benchmark criteria. A thematic content analysis based on predefined coding categories was also performed. Video characteristics, source types, and engagement metrics were also collected. Spearman correlation analysis was used to examine associations between engagement indicators and quality scores. YouTube videos showed significantly higher quality and reliability than TikTok videos, with higher median Global Quality Scale, modified DISCERN, and Journal of the American Medical Association scores (all P<.001). Compared with TikTok, YouTube videos more frequently discussed symptoms (92% vs 81%, P=.02), prevention (95% vs 78%, P<.001), treatment (88% vs 70%, P=.002), and wound management (77% vs 38%, P<.001). Lower-quality videos commonly contained incomplete prevention information, vague symptom descriptions, and limited source attribution. Videos produced by official medical organizations and professional health care creators generally achieved higher quality scores. Although engagement indicators were strongly correlated with each other, their associations with informational quality were relatively limited. YouTube provided more comprehensive and reliable tetanus-related information than TikTok, although content quality on both platforms remained inconsistent. Greater involvement from health care professionals and clearer evidence-based communication may help improve the quality of health information shared on social media platforms.
Tuberculosis (TB) remains one of the world's deadliest infectious diseases. Yet, despite the growing role of online health communities (OHCs) as key sources of social support, research on TB-related online communities remains scarce. Network analysis has been increasingly used to study OHCs and identify opinion leaders (OLs), offering a valuable approach to advancing knowledge about TB-related online communities. This study examined the types of social support and the influence of OLs in a prominent TB-related online forum in China, with a particular focus on its curated subforum that served as a centralized space for user interaction. The subforum consisted of posts recommended by the forum's administrator and the corresponding user replies they generated. The data consisted of all 438 administrator-recommended posts and the 150,570 associated user replies over 18 years, from the forum's launch in 2004 to 2021. The study used content analysis to examine the types of social support present in administrator-recommended posts, which are commonly considered high-quality. It then applied social network analysis to these posts and their associated user replies to identify OLs by using a Borda ranking method based on centrality measures and user tenure. Finally, semantic network analysis was used to explore topic clusters within each OL's posts and their associated user replies. The content analysis showed a high prevalence of informational and emotional support in the administrator-recommended posts. Of the 438 posts, 296 (67.5%) contained social support, with 150 containing informational support and 136 containing emotional support. Social support varied by post theme and whether the intent was to provide or seek it. Among disease knowledge posts, 74 out of 75 provided informational support. Emotional support was most frequently provided in nontreatment sharing posts (28/113) and most frequently sought in treatment experience posts (47/129). The social network analysis identified 10 OLs. The first was a former patient with TB, and the second was a pulmonary TB doctor. Together, they contributed 30.4% (133/438) of all the posts. Across the semantic network analyses of each OL's posts and their associated user replies, informational support was more prominent than emotional support. The findings suggest that the examined TB-related online forum served as an important source of social support for people affected by TB in China, fostering an environment for both informational and emotional support. OLs played an important role by contributing posts and establishing a central position through reply interactions with users.