%0 Journal Article %@ 1438-8871 %I JMIR Publications %V 27 %N %P e73062 %T Impact of Social Media Influencers on Amplifying Positive Public Health Messages %A Flaherty,Gerard Thomas %A Mangan,Ryan Michael %+ School of Medicine, College of Medicine, Nursing and Health Sciences, Ollscoil na Gaillimhe – University of Galway, University Road, Galway, H91TK33, Ireland, 353 91495469, gerard.flaherty@universityofgalway.ie %K social media %K COVID-19 %K vaccination %K personal brands %K public health %K wellness %K global health %K pandemic %K Twitter %K tweets %K vaccine %K longitudinal design %K wellness influencers %K hand annotation %K antivaccination %K infodemiology %D 2025 %7 21.3.2025 %9 Letter to the Editor %J J Med Internet Res %G English %X %M 40117580 %R 10.2196/73062 %U https://www.jmir.org/2025/1/e73062 %U https://doi.org/10.2196/73062 %U http://www.ncbi.nlm.nih.gov/pubmed/40117580 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 14 %N %P e41175 %T Digital Health Intervention (SANGYAN Podcast) to Enhance Knowledge Related to COVID-19 and Other Health Conditions: Protocol for an Implementation and Evaluation Study %A Joshi,Ashish %A Mohan,Surapaneni Krishna %A Pandya,Apurva Kumar %A Grover,Ashoo %A Saggu,Sofia Rani %A Revathi,Saravanavel Kalpana %A Sharma,Shruti %+ , School of Public Health, University of Memphis, Robison Hall 3825 DeSoto Avenue, Memphis, TN, 38152, United States, 1 443 570 6018, ashish1875@gmail.com %K podcast %K human-centered behavior %K pandemic %K coronavirus %K intervention %K digital health %K usefulness %K effectiveness %K usability %D 2025 %7 20.1.2025 %9 Protocol %J JMIR Res Protoc %G English %X Background: Podcasts are an unconventional method of disseminating information through audio to the masses. They are an emerging portable technology and a valuable resource that provides unlimited access for promoting health among participants. Podcasts related to health care have been used as a source of medical education, but there is a dearth of studies on the use of podcasts as a source of health information. This study will provide new perspectives by implementing the SANGYAN podcast, which contains information about COVID-19 and other health conditions.  Objective: The study aims to determine the usefulness and effectiveness of the SANGYAN podcast as a digital health intervention to address misinformation related to COVID-19 and other health conditions among individuals in Chennai, Tamil Nadu, India. Methods: An implementation and evaluation study will be conducted with 500 participants from the Panimalar Medical College Hospital & Research Institute (PMCHRI) and Rural Health Training Centre in Chennai. Among individuals aged 18 years and older, those residing in the selected urban and rural settings who visit the outpatient department of the PMCHRI and Rural Health Training Centre will be recruited. For participants who consent to the study, their sociodemographic details will be noted and their health literacy will be assessed using the Rapid Estimate of Adult Literacy in Medicine scale. Once the participants have listened to the podcast, the usability, acceptance, and user satisfaction of the podcast will be assessed. Descriptive analysis will be used for continuous variables, and frequency analysis will be used for categorical variables. Bivariate analysis will be conducted to understand the correlation of sociodemographic features in response to perception, usefulness, acceptance, and user satisfaction of the podcast. All analysis will be performed using SPSS (version 24), and the results will be reported with 95% CIs and P<.05. Results: As of December 2024, the SANGYAN podcast has been launched for voluntary usage in the PMCHRI. Conclusions: The finding from this research project will aid in the development and implementation of data-driven, evidence-based, and human-centered behavior change interventions using podcasts to address public health challenges among populations living in diverse settings. This would also help in enhancing the acceptability of podcasts as a source of health-related information. International Registered Report Identifier (IRRID): DERR1-10.2196/41175 %M 39832172 %R 10.2196/41175 %U https://www.researchprotocols.org/2025/1/e41175 %U https://doi.org/10.2196/41175 %U http://www.ncbi.nlm.nih.gov/pubmed/39832172 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 27 %N %P e59786 %T US State Public Health Agencies' Use of Twitter From 2012 to 2022: Observational Study %A Mendez,Samuel R %A Munoz-Najar,Sebastian %A Emmons,Karen M %A Viswanath,Kasisomayajula %+ Department of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, 677 Huntington Ave, Boston, MA, 02115, United States, 1 617 432 1135, smendez@g.harvard.edu %K social media %K health communication %K Twitter %K tweet %K public health %K state government %K government agencies %K information technology %K data science %K communication tool %K COVID-19 pandemic %K data collection %K theoretical framework %K message %K interaction %D 2025 %7 3.1.2025 %9 Original Paper %J J Med Internet Res %G English %X Background: Twitter (subsequently rebranded as X) is acknowledged by US health agencies, including the US Centers for Disease Control and Prevention (CDC), as an important public health communication tool. However, there is a lack of data describing its use by state health agencies over time. This knowledge is important amid a changing social media landscape in the wake of the COVID-19 pandemic. Objective: The study aimed to describe US state health agencies’ use of Twitter from 2012 through 2022. Furthermore, we organized our data collection and analysis around the theoretical framework of the networked public to contribute to the broader literature on health communication beyond a single platform. Methods: We used Twitter application programming interface data as indicators of state health agencies’ engagement with the 4 key qualities of communication in a networked public: scalability, persistence, replicability, and searchability. To assess scalability, we calculated tweet volume and audience engagement metrics per tweet. To assess persistence, we calculated the portion of tweets that were manual retweets or included an account mention. To assess replicability, we calculated the portion of tweets that were retweets or quote tweets. To assess searchability, we calculated the portion of tweets using at least 1 hashtag. Results: We observed a COVID-19 pandemic–era shift in state health agency engagement with scalability. The overall volume of tweets increased suddenly from less than 50,000 tweets in 2019 to over 94,000 in 2020, resulting in an average of 5.3 per day. Though mean tweets per day fell in 2021 and 2022, this COVID-19 pandemic–era low was still higher than the pre–COVID-19 pandemic peak. We also observed a more fragmented approach to searchability aligning with the start of the COVID-19 pandemic. More state-specific hashtags were among the top 10 during the COVID-19 pandemic, compared with more general hashtags related to disease outbreaks and natural disasters in years before. We did not observe such a clear COVID-19 pandemic–era shift in engagement with replicability. The portion of tweets mentioning a CDC account gradually rose and fell around a peak of 7.0% in 2018. Similarly, the rate of retweets of a CDC account rose and fell gradually around a peak of 5.4% in 2018. We did not observe a clear COVID-19 pandemic–era shift in persistence. The portion of tweets mentioning any account reached a maximum of 21% in 2013. It oscillated for much of the study period before dropping off in 2021 and reaching a minimum of 10% in 2022. Before 2018, the top 10 mentioned accounts included at least 2 non-CDC or corporate accounts. From 2018 onward, state agencies were much more prominent. Conclusions: Overall, we observed a more fragmented approach to state health agency communication on Twitter during the pandemic, prioritizing volume over searchability, formally replicating existing messages, and leaving traces of interactions with other accounts. %M 39752190 %R 10.2196/59786 %U https://www.jmir.org/2025/1/e59786 %U https://doi.org/10.2196/59786 %U http://www.ncbi.nlm.nih.gov/pubmed/39752190 %0 Journal Article %@ 1947-2579 %I JMIR Publications %V 16 %N %P e57718 %T Google Trends Assessment of Keywords Related to Smoking and Smoking Cessation During the COVID-19 Pandemic in 4 European Countries: Retrospective Analysis %A Jagomast,Tobias %A Finck,Jule %A Tangemann-Münstedt,Imke %A Auth,Katharina %A Drömann,Daniel %A Franzen,Klaas F %+ Airway Research Center North, Deutsches Zentrum für Lungenforschung, Wöhrendamm 80, Großhansdorf, 22927, Germany, 49 45150075562, klaas.franzen@uni-luebeck.de %K internet %K coronavirus %K COVID-19 %K SARS-CoV-2 %K pandemics %K public health %K smoking cessation %K tobacco products %K Google Trends %K relative search volume %K Europe %K online %K search %K smoking %K addiction %K quit %K cessation %K trend %K cluster %K public interest %K lockdown %K vaccination %K spread %K incidence %D 2024 %7 3.12.2024 %9 Original Paper %J Online J Public Health Inform %G English %X Background: Smoking is a modifiable risk factor for SARS-CoV-2 infection. Evidence of smoking behavior during the pandemic is ambiguous. Most investigations report an increase in smoking. In this context, Google Trends data monitor real-time public information–seeking behavior and are therefore useful to characterize smoking-related interest over the trajectory of the pandemic. Objective: This study aimed to use Google Trends data to evaluate the effect of the pandemic on public interest in smoking-related topics with a focus on lockdowns, vaccination campaigns, and incidence. Methods: The weekly relative search volume was retrieved from Google Trends for England, Germany, Italy, and Spain from December 31, 2017, to April 18, 2021. Data were collected for keywords concerning consumption, cessation, and treatment. The relative search volume before and during the pandemic was compared, and general trends were evaluated using the Wilcoxon rank-sum test. Short-term changes and hereby temporal clusters linked to lockdowns or vaccination campaigns were addressed by the flexible spatial scan statistics proposed by Takahashi and colleagues. Subsequently, the numbers of clusters after the onset of the pandemic were compared by chi-square test. Results: Country-wise minor differences were observed while 3 overarching trends prevailed. First, regarding cessation, the statistical comparison revealed a significant decline in interest for 58% (7/12) of related keywords, and fewer clusters were present during the pandemic. Second, concerning consumption, significantly reduced relative search volume was observed for 58% (7/12) of keywords, while treatment-related keywords exhibited heterogeneous trends. Third, substantial clusters of increased interest were sparsely linked to lockdowns, vaccination campaigns, or incidence. Conclusions: This study reports a substantial decline in overall relative search volume and clusters for cessation interest. These results underline the importance of intensifying cessation aid during times of crisis. Lockdowns, vaccination, and incidence had less impact on information-seeking behavior. Other public measures that positively affect smoking behavior remain to be determined. %M 39626237 %R 10.2196/57718 %U https://ojphi.jmir.org/2024/1/e57718 %U https://doi.org/10.2196/57718 %U http://www.ncbi.nlm.nih.gov/pubmed/39626237 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e56651 %T Wellness Influencer Responses to COVID-19 Vaccines on Social Media: A Longitudinal Observational Study %A O'Brien,Gabrielle %A Ganjigunta,Ronith %A Dhillon,Paramveer S %+ School of Information, University of Michigan, 105 S. State Street, Ann Arbor, MI, 48103, United States, 1 (734) 764 1555, elleobri@umich.edu %K social media, COVID-19, vaccination %K personal brands %K public health %K wellness %K global health %K pandemic %K Twitter %K tweets %K vaccine %K longitudinal design %K wellness influencers %K hand-annotation %K anti-vaccination %K infodemiology %D 2024 %7 27.11.2024 %9 Original Paper %J J Med Internet Res %G English %X Background: Online wellness influencers (individuals dispensing unregulated health and wellness advice over social media) may have incentives to oppose traditional medical authorities. Their messaging may decrease the overall effectiveness of public health campaigns during global health crises like the COVID-19 pandemic. Objective: This study aimed to probe how wellness influencers respond to a public health campaign; we examined how a sample of wellness influencers on Twitter (rebranded as X in 2023) identified before the COVID-19 pandemic on Twitter took stances on the COVID-19 vaccine during 2020-2022. We evaluated the prevalence of provaccination messaging among wellness influencers compared with a control group, as well as the rhetorical strategies these influencers used when supporting or opposing vaccination. Methods: Following a longitudinal design, wellness influencer accounts were identified on Twitter from a random sample of tweets posted in 2019. Accounts were identified using a combination of topic modeling and hand-annotation for adherence to influencer criteria. Their tweets from 2020-2022 containing vaccine keywords were collected and labeled as pro- or antivaccination stances using a language model. We compared their stances to a control group of noninfluencer accounts that discussed similar health topics before the pandemic using a generalized linear model with mixed effects and a nearest-neighbors classifier. We also used topic modeling to locate key themes in influencer’s pro- and antivaccine messages. Results: Wellness influencers (n=161) had lower rates of provaccination stances in their on-topic tweets (20%, 614/3045) compared with controls (n=242 accounts, with 42% or 3201/7584 provaccination tweets). Using a generalized linear model of tweet stance with mixed effects to model tweets from the same account, the main effect of the group was significant (β1=–2.2668, SE=0.2940; P<.001). Covariate analysis suggests an association between antivaccination tweets and accounts representing individuals (β=–0.9591, SE=0.2917; P=.001) but not social network position. A complementary modeling exercise of stance within user accounts showed a significant difference in the proportion of antivaccination users by group (χ21[N=321]=36.1, P<.001). While nearly half of the influencer accounts were labeled by a K-nearest neighbor classifier as predominantly antivaccination (48%, 58/120), only 16% of control accounts were labeled this way (33/201). Topic modeling of influencer tweets showed that the most prevalent antivaccination themes were protecting children, guarding against government overreach, and the corruption of the pharmaceutical industry. Provaccination messaging tended to encourage followers to take action or emphasize the efficacy of the vaccine. Conclusions: Wellness influencers showed higher rates of vaccine opposition compared with other accounts that participated in health discourse before the pandemic. This pattern supports the theory that unregulated wellness influencers have incentives to resist messaging from establishment authorities such as public health agencies. %M 39602782 %R 10.2196/56651 %U https://www.jmir.org/2024/1/e56651 %U https://doi.org/10.2196/56651 %U http://www.ncbi.nlm.nih.gov/pubmed/39602782 %0 Journal Article %@ 2369-2960 %I JMIR Publications %V 10 %N %P e44845 %T All-Cause and Cause-Specific Burden of Asthma in a Transitioning City in China: Population Study %A Cheng,Xuelin %A Wu,Xiaoling %A Ye,Wenjing %A Chen,Yichen %A Fu,Peihua %A Jia,Wenchang %A Zhang,Wei %A Xu,Xiaoyun %A Gong,Di %A Mou,Changhua %A Gu,Wen %A Luo,Zheng %A Jiang,Sunfang %A Li,Xiaopan %K asthma %K mortality %K years of life lost %K trend analysis %K decomposition method %K Pudong %D 2024 %7 14.11.2024 %9 %J JMIR Public Health Surveill %G English %X Background: Understanding the impact of asthma on public health is crucial for evidence-based prevention and treatment strategies. Objective: This study aimed to identify the causes of asthma-related mortality in Pudong, Shanghai, China, offering insights for managing similar regions or countries in transition. Methods: Mortality statistics were obtained from the Vital Statistics System of Pudong for 2005‐2021. Temporal patterns for the burden of asthma were examined. The crude mortality rate (CMR), age-standardized mortality rate by Segi’s world standard population (ASMRW), and years of life lost (YLL) for both all-cause and asthma-specific deaths were computed. Mortality rates associating with aging and other variables were categorized using the decomposition technique. The autoregressive integrated moving average model was used to forecast the asthma-related death mortality rate by 2035. Results: A total of 1568 asthma-related deaths occurred during the follow-up period, with the CMR and ASMRW being 3.25/105 and 1.22/105 person-years, respectively. The primary underlying causes of death were chronic lower respiratory diseases, coronary heart diseases, and cerebrovascular disease. The YLL due to total asthma-related deaths added up to 14,837.76 years, with a YLL rate of 30.73/105 person-years. Male individuals had more YLL (8941.81 vs 5895.95 y) and a higher YLL rate (37.12/105 vs 24.38/105 person-years) than female individuals. From 2005 to 2021, the ASMRW declined by 3.48%, and both the CMR and YLL rate decreased in the 0‐29, 70‐79, and ≥80 years age groups (all P<.01). However, asthma-related deaths increased from 329 people between 2005 and 2008 to 472 people between 2017 and 2021. The proportion of the population aged 80 years and older gradually increased by 1.43% (95% CI 0.20%-2.68%; P=.03), and the mortality rates of asthma deaths attributable to population aging rose by 21.97% (95% CI, 11.58%-33.32%; P<.001) annually. Conclusions: Asthma remains a significant public health challenge in transitioning countries, requiring increased attention and resource allocation. %R 10.2196/44845 %U https://publichealth.jmir.org/2024/1/e44845 %U https://doi.org/10.2196/44845 %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 %@ 1438-8871 %I JMIR Publications %V 26 %N %P e50343 %T Online Interest in Elf Bar in the United States: Google Health Trends Analysis %A Bhagavathula,Akshaya Srikanth %A Dobbs,Page D %+ Department of Health, Human Performance and Recreation, University of Arkansas, Suite 317, 346 West Ave, Fayetteville, AR, 72701, United States, 1 479 575 2858, pdobbs@uark.edu %K e-cigarettes %K Elf Bar %K JUUL %K tobacco %K Google Trends %K Google Health Trends %D 2024 %7 5.11.2024 %9 Original Paper %J J Med Internet Res %G English %X Background: Despite the popularity of JUUL e-cigarettes, other brands (eg, Elf Bar) may be gaining digital attention. Objective: This study compared Google searches for Elf Bar and JUUL from 2022 to 2023 using Google Health Trends Application Programming Interface data. Methods: Using an infodemiology approach, we examined weekly trends in Google searches (per 10 million) for “Elf Bar” and “JUUL” at the US national and state levels from January 1, 2022, to December 31, 2023. Joinpoint regression was used to assess statistically significant trends in the search probabilities for “Elf Bar” and “JUUL” during the study period. Results: Elf Bar had less online interest than JUUL at the beginning of 2022. When the US Food and Drug Administration denied JUUL marketing authority on June 23, 2022, JUUL searches peaked at 2609.3 × 107 and fell to 83.9 × 107 on September 3, 2023. Elf Bar searches surpassed JUUL on July 10, 2022, and steadily increased, reaching 523.2 × 107 on December 4, 2022. Overall, Elf Bar’s weekly search probability increased by 1.6% (95% CI 1.5%-1.7%; P=.05) from January 2022 to December 2023, with the greatest increase between May 29 and June 19, 2022 (87.7%, 95% CI 35.9%-123.9%; P=.001). Elf Bar searches increased after JUUL’s suspension in Pennsylvania (1010%), Minnesota (872.5%), Connecticut (803.5%), New York (738.1%), and New Jersey (702.9%). Conclusions: Increasing trends in Google searches for Elf Bar indicate that there was a growing online interest in this brand in the United States in 2022. %M 39499924 %R 10.2196/50343 %U https://www.jmir.org/2024/1/e50343 %U https://doi.org/10.2196/50343 %U http://www.ncbi.nlm.nih.gov/pubmed/39499924 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 13 %N %P e59345 %T Misinformation About Climate Change and Related Environmental Events on Social Media: Protocol for a Scoping Review %A Vivion,Maryline %A Trottier,Valérie %A Bouhêlier,Ève %A Goupil-Sormany,Isabelle %A Diallo,Thierno %+ Department of Social and Preventive Medicine, Université Laval, Pavillon Ferdinand-Vandry, 1050, avenue de la Médecine, Québec, QC, G1V 0A6, Canada, 1 418 656 2131, maryline.vivion@fmed.ulaval.ca %K misinformation %K disinformation %K infodemiology %K infoveillance %K climate change %K global warming %K greenhouse effect %K social media %K online social network %K environmental health %K public support %K global challenges %K Google %K health policy %D 2024 %7 31.10.2024 %9 Protocol %J JMIR Res Protoc %G English %X Background: Climate change and related environmental events represent major global challenges and are often accompanied by the spread of misinformation on social media. According to previous reviews, the dissemination of this misinformation on various social media platforms requires deeper exploration. Moreover, the findings reported applied mainly to the context of the United States, limiting the possibility of extending the results to other settings. Objective: This study aims to assess the current state of knowledge about misinformation concerning climate change and related environmental events that are circulating on social media. More specifically, we will explore past and current themes, actors, and sources, and the dissemination of this misinformation within the Canadian context. Methods: This scoping review protocol follows the methodological approach developed by Arksey and O’Malley and advanced by Levac, complemented by the PRISMA-ScR (Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews) checklist and the best practice guidance for the development of scoping review protocols. Following the identification of the research questions and assisted by a specialized librarian, we developed search strategies for selected bibliographic databases (MEDLINE, Embase, Web of Science, and GreenFILE) and for gray literature (Google and pertinent databases) searches. Bibliographic and gray literature will be searched to identify relevant publications. In total, 2 members of our team will use the review software Covidence (Veritas Health Innovation) to independently select publications to include in the review. Publications specifically addressing our research questions, peer-reviewed, evidence-based, and published from January 1, 2000, in the full-text version in English or French will be included. Data will be extracted from the included publications to chart, among other items, the years of publication, geographic areas, themes, actors, and sources of the climate change–related misinformation and conclusions reported. Our team will then synthesize the extracted data to articulate the current state of knowledge relating to our research inquiries. Results: The research questions were identified in January 2024. The search strategies were developed from January to March 2024 for MEDLINE, Embase, and Web of Science and in July 2024 for GreenFILE and gray literature. MEDLINE, Embase, and Web of Science searches were launched on March 26, 2024. The first of 2 rounds of selection of publications identified through these databases was achieved in April 2024. Conclusions: This protocol will enable us to identify the evolution of themes, actors, and sources of misinformation regarding climate change and related environmental events on social media, including the latest platforms, and to potentially identify a context particular to Canada. As misinformation is known to undermine actions and public support in the fight against climate change, we intend to facilitate the targeting of efforts to combat misinformation related to climate change in an up-to-date and contextualized manner. International Registered Report Identifier (IRRID): DERR1-10.2196/59345 %M 39481105 %R 10.2196/59345 %U https://www.researchprotocols.org/2024/1/e59345 %U https://doi.org/10.2196/59345 %U http://www.ncbi.nlm.nih.gov/pubmed/39481105 %0 Journal Article %@ 2817-1705 %I JMIR Publications %V 3 %N %P e55059 %T Targeting COVID-19 and Human Resources for Health News Information Extraction: Algorithm Development and Validation %A Ravaut,Mathieu %A Zhao,Ruochen %A Phung,Duy %A Qin,Vicky Mengqi %A Milovanovic,Dusan %A Pienkowska,Anita %A Bojic,Iva %A Car,Josip %A Joty,Shafiq %+ Nanyang Technological University, 50 Nanyang Avenue, Singapore, 639798, Singapore, 65 88947729, mathieuj001@e.ntu.edu.sg %K COVID-19 %K SARS-CoV-2 %K summary %K summarize %K news articles %K deep learning %K classification %K summarization %K machine learning %K extract %K extraction %K news %K media %K NLP %K natural language processing %D 2024 %7 30.10.2024 %9 Original Paper %J JMIR AI %G English %X Background: Global pandemics like COVID-19 put a high amount of strain on health care systems and health workers worldwide. These crises generate a vast amount of news information published online across the globe. This extensive corpus of articles has the potential to provide valuable insights into the nature of ongoing events and guide interventions and policies. However, the sheer volume of information is beyond the capacity of human experts to process and analyze effectively. Objective: The aim of this study was to explore how natural language processing (NLP) can be leveraged to build a system that allows for quick analysis of a high volume of news articles. Along with this, the objective was to create a workflow comprising human-computer symbiosis to derive valuable insights to support health workforce strategic policy dialogue, advocacy, and decision-making. Methods: We conducted a review of open-source news coverage from January 2020 to June 2022 on COVID-19 and its impacts on the health workforce from the World Health Organization (WHO) Epidemic Intelligence from Open Sources (EIOS) by synergizing NLP models, including classification and extractive summarization, and human-generated analyses. Our DeepCovid system was trained on 2.8 million news articles in English from more than 3000 internet sources across hundreds of jurisdictions. Results: Rules-based classification with hand-designed rules narrowed the data set to 8508 articles with high relevancy confirmed in the human-led evaluation. DeepCovid’s automated information targeting component reached a very strong binary classification performance of 98.98 for the area under the receiver operating characteristic curve (ROC-AUC) and 47.21 for the area under the precision recall curve (PR-AUC). Its information extraction component attained good performance in automatic extractive summarization with a mean Recall-Oriented Understudy for Gisting Evaluation (ROUGE) score of 47.76. DeepCovid’s final summaries were used by human experts to write reports on the COVID-19 pandemic. Conclusions: It is feasible to synergize high-performing NLP models and human-generated analyses to benefit open-source health workforce intelligence. The DeepCovid approach can contribute to an agile and timely global view, providing complementary information to scientific literature. %M 39475833 %R 10.2196/55059 %U https://ai.jmir.org/2024/1/e55059 %U https://doi.org/10.2196/55059 %U http://www.ncbi.nlm.nih.gov/pubmed/39475833 %0 Journal Article %@ 2564-1891 %I JMIR Publications %V 4 %N %P e60678 %T Evaluating the Influence of Role-Playing Prompts on ChatGPT’s Misinformation Detection Accuracy: Quantitative Study %A Haupt,Michael Robert %A Yang,Luning %A Purnat,Tina %A Mackey,Tim %+ Global Health Program, Department of Anthropology, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA, 92093, United States, 1 858 534 4145, tkmackey@ucsd.edu %K large language models %K ChatGPT %K artificial intelligence %K AI %K experiment %K prompt engineering %K role-playing %K social identity %K misinformation detection %K COVID-19 %D 2024 %7 26.9.2024 %9 Original Paper %J JMIR Infodemiology %G English %X Background: During the COVID-19 pandemic, the rapid spread of misinformation on social media created significant public health challenges. Large language models (LLMs), pretrained on extensive textual data, have shown potential in detecting misinformation, but their performance can be influenced by factors such as prompt engineering (ie, modifying LLM requests to assess changes in output). One form of prompt engineering is role-playing, where, upon request, OpenAI’s ChatGPT imitates specific social roles or identities. This research examines how ChatGPT’s accuracy in detecting COVID-19–related misinformation is affected when it is assigned social identities in the request prompt. Understanding how LLMs respond to different identity cues can inform messaging campaigns, ensuring effective use in public health communications. Objective: This study investigates the impact of role-playing prompts on ChatGPT’s accuracy in detecting misinformation. This study also assesses differences in performance when misinformation is explicitly stated versus implied, based on contextual knowledge, and examines the reasoning given by ChatGPT for classification decisions. Methods: Overall, 36 real-world tweets about COVID-19 collected in September 2021 were categorized into misinformation, sentiment (opinions aligned vs unaligned with public health guidelines), corrections, and neutral reporting. ChatGPT was tested with prompts incorporating different combinations of multiple social identities (ie, political beliefs, education levels, locality, religiosity, and personality traits), resulting in 51,840 runs. Two control conditions were used to compare results: prompts with no identities and those including only political identity. Results: The findings reveal that including social identities in prompts reduces average detection accuracy, with a notable drop from 68.1% (SD 41.2%; no identities) to 29.3% (SD 31.6%; all identities included). Prompts with only political identity resulted in the lowest accuracy (19.2%, SD 29.2%). ChatGPT was also able to distinguish between sentiments expressing opinions not aligned with public health guidelines from misinformation making declarative statements. There were no consistent differences in performance between explicit and implicit misinformation requiring contextual knowledge. While the findings show that the inclusion of identities decreased detection accuracy, it remains uncertain whether ChatGPT adopts views aligned with social identities: when assigned a conservative identity, ChatGPT identified misinformation with nearly the same accuracy as it did when assigned a liberal identity. While political identity was mentioned most frequently in ChatGPT’s explanations for its classification decisions, the rationales for classifications were inconsistent across study conditions, and contradictory explanations were provided in some instances. Conclusions: These results indicate that ChatGPT’s ability to classify misinformation is negatively impacted when role-playing social identities, highlighting the complexity of integrating human biases and perspectives in LLMs. This points to the need for human oversight in the use of LLMs for misinformation detection. Further research is needed to understand how LLMs weigh social identities in prompt-based tasks and explore their application in different cultural contexts. %M 39326035 %R 10.2196/60678 %U https://infodemiology.jmir.org/2024/1/e60678 %U https://doi.org/10.2196/60678 %U http://www.ncbi.nlm.nih.gov/pubmed/39326035 %0 Journal Article %@ 2564-1891 %I JMIR Publications %V 4 %N %P e53899 %T Public Perception of the Tobacco 21 Amendment on Twitter in the United States: Observational Study %A Schneller-Najm,Liane M %A Xie,Zidian %A Chen,Jiarui %A Lee,Sarah %A Xu,Emily %A Li,Dongmei %+ Department of Health Behavior, Roswell Park Comprehensive Cancer Center, Elm and Carlton Streets, Buffalo, NY, 14203, United States, 1 716 845 5881, Liane.Najm@RoswellPark.org %K tobacco policy %K tobacco regulation %K social media %K tobacco use %K tobacco %K health belief %K sentiment analysis %K smoking %K cigarettes %K social media analysis %K vaping %K e-cigarettes %K health behavior %K public opinion %D 2024 %7 25.9.2024 %9 Original Paper %J JMIR Infodemiology %G English %X Background: Following the signing of the Tobacco 21 Amendment (T21) in December 2019 to raise the minimum legal age for the sale of tobacco products from 18 to 21 years in the United States, there is a need to monitor public responses and potential unintended consequences. Social media platforms, such as Twitter (subsequently rebranded as X), can provide rich data on public perceptions. Objective: This study contributes to the literature using Twitter data to assess the knowledge and beliefs of T21. Methods: Twitter data were collected from November 2019 to February 2021 using the Twitter streaming application programming interface with keywords related to vaping or e-cigarettes, such as “vape,” “ecig,” etc. The temporal trend of the T21 discussion on Twitter was examined using the mean number of daily T21-related tweets. Inductive methods were used to manually code the tweets into different sentiment groups (positive, neutral, and negative) based on the attitude expressed toward the policy by 3 coders with high interrater reliability. Topics discussed were examined within each sentiment group through theme analyses. Results: Among the collected 3197 tweets, 2169 tweets were related to T21, of which 444 tweets (20.5%) showed a positive attitude, 736 (33.9%) showed a negative attitude, and 989 (45.6%) showed a neutral attitude. The temporal trend showed a clear peak in the number of tweets around January 2020, following the enactment of this legislation. For positive tweets, the most frequent topics were “avoidance of further regulation” (120/444, 27%), “Enforce T21” (110/444, 24.8%), and “health benefits” (81/444, 18.2%). For negative tweets, the most frequent topics were “general disagreement or frustration” (207/736, 28.1%) and “will still use tobacco” (188/736, 25.5%). Neutral tweets were primarily “public service announcements (PSA) or news posts” (782/989, 79.1%). Conclusions: Overall, we find that one-third of tweets displayed a negative attitude toward T21 during the study period. Many were frustrated with T21 and reported that underage consumers could still obtain products. Social media data provide a timely opportunity to monitor public perceptions and responses to regulatory actions. Continued monitoring can inform enforcement efforts and potential unintended consequences of T21. %M 39321452 %R 10.2196/53899 %U https://infodemiology.jmir.org/2024/1/e53899 %U https://doi.org/10.2196/53899 %U http://www.ncbi.nlm.nih.gov/pubmed/39321452 %0 Journal Article %@ 1947-2579 %I JMIR Publications %V 16 %N %P e55104 %T Vaccine Hesitancy in Taiwan: Temporal, Multilayer Network Study of Echo Chambers Shaped by Influential Users %A Yin,Jason Dean-Chen %+ School of Public Health, Li Ka Shing Faculty of Medicine, University of Hong Kong, 7 Sassoon Road, Pokfulam, Hong Kong, China (Hong Kong), 852 97907044, jdyin@hku.hk %K network analysis %K infodemiology %K vaccine hesitancy %K Taiwan %K multiplex network %K echo chambers %K influential users %K information dissemination %K health communication %K Taiwanese data set %K multilayer network model %K vaccine hesitant %K antivaccination %K infoveillance %K disease surveillance %K public health %D 2024 %7 9.8.2024 %9 Original Paper %J Online J Public Health Inform %G English %X Background: Vaccine hesitancy is a growing global health threat that is increasingly studied through the monitoring and analysis of social media platforms. One understudied area is the impact of echo chambers and influential users on disseminating vaccine information in social networks. Assessing the temporal development of echo chambers and the influence of key users on their growth provides valuable insights into effective communication strategies to prevent increases in vaccine hesitancy. This also aligns with the World Health Organization’s (WHO) infodemiology research agenda, which aims to propose new methods for social listening. Objective: Using data from a Taiwanese forum, this study aims to examine how engagement patterns of influential users, both within and across different COVID-19 stances, contribute to the formation of echo chambers over time. Methods: Data for this study come from a Taiwanese forum called PTT. All vaccine-related posts on the “Gossiping” subforum were scraped from January 2021 to December 2022 using the keyword “vaccine.” A multilayer network model was constructed to assess the existence of echo chambers. Each layer represents either provaccination, vaccine hesitant, or antivaccination posts based on specific criteria. Layer-level metrics, such as average diversity and Spearman rank correlations, were used to measure chambering. To understand the behavior of influential users—or key nodes—in the network, the activity of high-diversity and hardliner nodes was analyzed. Results: Overall, the provaccination and antivaccination layers are strongly polarized. This trend is temporal and becomes more apparent after November 2021. Diverse nodes primarily participate in discussions related to provaccination topics, both receiving comments and contributing to them. Interactions with the antivaccination layer are comparatively minimal, likely due to its smaller size, suggesting that the forum is a “healthy community.” Overall, diverse nodes exhibit cross-cutting engagement. By contrast, hardliners in the vaccine hesitant and antivaccination layers are more active in commenting within their own communities. This trend is temporal, showing an increase during the Omicron outbreak. Hardliner activity potentially reinforces their stances over time. Thus, there are opposing forces of chambering and cross-cutting. Conclusions: Efforts should be made to moderate hardliner and influential nodes in the antivaccination layer and to support provaccination users engaged in cross-cutting exchanges. There are several limitations to this study. One is the bias of the platform used, and another is the lack of a comprehensive definition of “influence.” To address these issues, comparative studies across different platforms can be conducted, and various metrics of influence should be explored. Additionally, examining the impact of influential users on network structure and chambering through network simulations and regression analysis provides more robust insights. The study also lacks an explanation for the reasons behind chambering trends. Conducting content analysis can help to understand the nature of engagement and inform interventions to address echo chambers. These approaches align with and further the WHO infodemic research agenda. %R 10.2196/55104 %U https://ojphi.jmir.org/2024/1/e55104 %U https://doi.org/10.2196/55104 %0 Journal Article %@ 2368-7959 %I %V 11 %N %P e57234 %T Using Large Language Models to Understand Suicidality in a Social Media–Based Taxonomy of Mental Health Disorders: Linguistic Analysis of Reddit Posts %A Bauer,Brian %A Norel,Raquel %A Leow,Alex %A Rached,Zad Abi %A Wen,Bo %A Cecchi,Guillermo %K natural language processing %K explainable AI %K suicide %K mental health disorders %K mental health disorder %K mental health %K social media %K online discussions %K online %K large language model %K LLM %K downstream analyses %K trauma %K stress %K depression %K anxiety %K AI %K artificial intelligence %K explainable artificial intelligence %K web-based discussions %D 2024 %7 16.5.2024 %9 %J JMIR Ment Health %G English %X Background: Rates of suicide have increased by over 35% since 1999. Despite concerted efforts, our ability to predict, explain, or treat suicide risk has not significantly improved over the past 50 years. Objective: The aim of this study was to use large language models to understand natural language use during public web-based discussions (on Reddit) around topics related to suicidality. Methods: We used large language model–based sentence embedding to extract the latent linguistic dimensions of user postings derived from several mental health–related subreddits, with a focus on suicidality. We then applied dimensionality reduction to these sentence embeddings, allowing them to be summarized and visualized in a lower-dimensional Euclidean space for further downstream analyses. We analyzed 2.9 million posts extracted from 30 subreddits, including r/SuicideWatch, between October 1 and December 31, 2022, and the same period in 2010. Results: Our results showed that, in line with existing theories of suicide, posters in the suicidality community (r/SuicideWatch) predominantly wrote about feelings of disconnection, burdensomeness, hopeless, desperation, resignation, and trauma. Further, we identified distinct latent linguistic dimensions (well-being, seeking support, and severity of distress) among all mental health subreddits, and many of the resulting subreddit clusters were in line with a statistically driven diagnostic classification system—namely, the Hierarchical Taxonomy of Psychopathology (HiTOP)—by mapping onto the proposed superspectra. Conclusions: Overall, our findings provide data-driven support for several language-based theories of suicide, as well as dimensional classification systems for mental health disorders. Ultimately, this novel combination of natural language processing techniques can assist researchers in gaining deeper insights about emotions and experiences shared on the web and may aid in the validation and refutation of different mental health theories. %R 10.2196/57234 %U https://mental.jmir.org/2024/1/e57234 %U https://doi.org/10.2196/57234 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e49928 %T Emerging Trends in Information-Seeking Behavior for Alpha-Gal Syndrome: Infodemiology Study Using Time Series and Content Analysis %A Romeiser,Jamie L %A Jusko,Nicole %A Williams,Augusta A %+ Department of Public Health and Preventive Medicine, Upstate Medical University, 766 Irving Ave, Syracuse, NY, 13210, United States, 1 315 464 6897, RomeiseJ@upstate.edu %K alpha-gal %K alpha gal %K alpha-gal syndrome %K lone star tick %K infodemiology %K time series %K content analysis %K Google Trends %K allergy %K allergic %K immune %K immunology %K immunological %K information behavior %K information behaviour %K information seeking %K geographic %D 2024 %7 8.5.2024 %9 Original Paper %J J Med Internet Res %G English %X Background: Alpha-gal syndrome is an emerging allergy characterized by an immune reaction to the carbohydrate molecule alpha-gal found in red meat. This unique food allergy is likely triggered by a tick bite. Cases of the allergy are on the rise, but prevalence estimates do not currently exist. Furthermore, varying symptoms and limited awareness of the allergy among health care providers contribute to delayed diagnosis, leading individuals to seek out their own information and potentially self-diagnose. Objective: The study aimed to (1) describe the volume and patterns of information-seeking related to alpha-gal, (2) explore correlations between alpha-gal and lone star ticks, and (3) identify specific areas of interest that individuals are searching for in relation to alpha-gal. Methods: Google Trends Supercharged-Glimpse, a new extension of Google Trends, provides estimates of the absolute volume of searches and related search queries. This extension was used to assess trends in searches for alpha-gal and lone star ticks (lone star tick, alpha gal, and meat allergy, as well as food allergy for comparison) in the United States. Time series analyses were used to examine search volume trends over time, and Spearman correlation matrices and choropleth maps were used to explore geographic and temporal correlations between alpha-gal and lone star tick searches. Content analysis was performed on related search queries to identify themes and subcategories that are of interest to information seekers. Results: Time series analysis revealed a rapidly increasing trend in search volumes for alpha-gal beginning in 2015. After adjusting for long-term trends, seasonal trends, and media coverage, from 2015 to 2022, the predicted adjusted average annual percent change in search volume for alpha-gal was 33.78%. The estimated overall change in average search volume was 627%. In comparison, the average annual percent change was 9.23% for lone star tick, 7.34% for meat allergy, and 2.45% for food allergy during this time. Geographic analysis showed strong significant correlations between alpha-gal and lone star tick searches especially in recent years (ρ=0.80; P<.001), with primary overlap and highest search rates found in the southeastern region of the United States. Content analysis identified 10 themes of primary interest: diet, diagnosis or testing, treatment, medications or contraindications of medications, symptoms, tick related, specific sources of information and locations, general education information, alternative words for alpha-gal, and unrelated or other. Conclusions: The study provides insights into the changing information-seeking patterns for alpha-gal, indicating growing awareness and interest. Alpha-gal search volume is increasing at a rapid rate. Understanding specific questions and concerns can help health care providers and public health educators to tailor communication strategies. The Google Trends Supercharged-Glimpse tool offers enhanced features for analyzing information-seeking behavior and can be valuable for infodemiology research. Further research is needed to explore the evolving prevalence and impact of alpha-gal syndrome. %M 38717813 %R 10.2196/49928 %U https://www.jmir.org/2024/1/e49928 %U https://doi.org/10.2196/49928 %U http://www.ncbi.nlm.nih.gov/pubmed/38717813 %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 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 %@ 1947-2579 %I JMIR Publications %V 15 %N %P e51984 %T Health Information Seeking Behavior on Social Networking Sites and Self-Treatment: Pilot Survey Study %A Silver,Reginald A %A Johnson,Chandrika %+ Belk College of Business, University of North Carolina at Charlotte, 9201 University City Blvd, Charlotte, NC, 28223, United States, 1 704 687 6181, rsilver5@uncc.edu %K health care seeking behavior %K online social networking %K sociodemographic factors %K community survey %K logistic regression %K self-treatment %D 2023 %7 20.12.2023 %9 Original Paper %J Online J Public Health Inform %G English %X Background: Social networking site use and social network–based health information seeking behavior have proliferated to the point that the lines between seeking health information from credible social network–based sources and the decision to seek medical care or attempt to treat oneself have become blurred. Objective: We contribute to emerging research on health information seeking behavior by investigating demographic factors, social media use for health information seeking purposes, and the relationship between health information seeking and occurrences of self-treatment. Methods: Data were collected from an online survey in which participants were asked to describe sociodemographic factors about themselves, social media use patterns, perceptions about their motivations for health information seeking on social media platforms, and whether or not they attempted self-treatment after their social media–related health information seeking. We conducted a binomial logistic regression with self-treatment as a dichotomous categorical dependent variable. Results: Results indicate that significant predictors of self-treatment based on information obtained from social networking sites include race, exercise frequency, and degree of trust in the health-related information received. Conclusions: With an understanding of how sociodemographic factors might influence the decision to self-treat based on information obtained from social networking sites, health care providers can assist patients by educating them on credible social network–based sources of health information and discussing the importance of seeking medical advice from a health care provider. %M 38179207 %R 10.2196/51984 %U https://ojphi.jmir.org/2023/1/e51984 %U https://doi.org/10.2196/51984 %U http://www.ncbi.nlm.nih.gov/pubmed/38179207 %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 %@ 1438-8871 %I JMIR Publications %V 25 %N %P e43701 %T Characterizing Precision Nutrition Discourse on Twitter: Quantitative Content Analysis %A Batheja,Sapna %A Schopp,Emma M %A Pappas,Samantha %A Ravuri,Siri %A Persky,Susan %+ Social and Behavioral Research Branch, National Human Genome Research Institute, 31 Center Drive, B1B36, Bethesda, MD, 20892, United States, 1 3014430098, perskys@mail.nih.gov %K nutrigenetics %K nutrigenomics %K precision nutrition %K Twitter %K credibility %K misinformation %K content analysis %D 2023 %7 12.10.2023 %9 Original Paper %J J Med Internet Res %G English %X Background: It is possible that tailoring dietary approaches to an individual’s genomic profile could provide optimal dietary inputs for biological functioning and support adherence to dietary management protocols. The science required for such nutrigenetic and nutrigenomic profiling is not yet considered ready for broad application by the scientific and medical communities; however, many personalized nutrition products are available in the marketplace, creating the potential for hype and misleading information on social media. Twitter provides a unique big data source that provides real-time information. Therefore, it has the potential to disseminate evidence-based health information, as well as misinformation. Objective: We sought to characterize the landscape of precision nutrition content on Twitter, with a specific focus on nutrigenetics and nutrigenomics. We focused on tweet authors, types of content, and presence of misinformation. Methods: Twitter Archiver was used to capture tweets from September 1, 2020, to December 1, 2020, using keywords related to nutrition and genetics. A random sample of tweets was coded using quantitative content analysis by 4 trained coders. Codebook-driven, quantified information about tweet authors, content details, information quality, and engagement metrics were compiled and analyzed. Results: The most common categories of tweets were precision nutrition products and nutrigenomic concepts. About a quarter (132/504, 26.2%) of tweet authors presented themselves as science experts, medicine experts, or both. Nutrigenetics concepts most frequently came from authors with science and medicine expertise, and tweets about the influence of genes on weight were more likely to come from authors with neither type of expertise. A total of 14.9% (75/504) of the tweets were noted to contain untrue information; these were most likely to occur in the nutrigenomics concepts topic category. Conclusions: By evaluating social media discourse on precision nutrition on Twitter, we made several observations about the content available in the information environment through which individuals can learn about related concepts and products. Tweet content was consistent with the indicators of medical hype, and the inclusion of potentially misleading and untrue information was common. We identified a contingent of users with scientific and medical expertise who were active in discussing nutrigenomics concepts and products and who may be encouraged to share credible expert advice on precision nutrition and tackle false information as this technology develops. %M 37824190 %R 10.2196/43701 %U https://www.jmir.org/2023/1/e43701 %U https://doi.org/10.2196/43701 %U http://www.ncbi.nlm.nih.gov/pubmed/37824190 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 25 %N %P e49220 %T Appraising Unmet Needs and Misinformation Spread About Polycystic Ovary Syndrome in 85,872 YouTube Comments Over 12 Years: Big Data Infodemiology Study %A Malhotra,Kashish %A Kempegowda,Punith %+ Institute of Applied Health Research, College of Medical and Dental Sciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT, United Kingdom, 44 7721 930 777, P.Kempegowda@bham.ac.uk %K polycystic ovary syndrome %K PCOS %K public %K YouTube %K global health %K online trends %K global equity %K infodemiology %K big data %K comments %K sentiment %K network analysis %K contextualization %K word association %K misinformation %K endocrinopathy %K women %K gender %K users %K treatment %K fatigue %K pain %K motherhood %D 2023 %7 11.9.2023 %9 Original Paper %J J Med Internet Res %G English %X Background: Polycystic ovary syndrome (PCOS) is the most common endocrinopathy in women, resulting in substantial burden related to metabolic, reproductive, and psychological complications. While attempts have been made to understand the themes and sentiments of the public regarding PCOS at the local and regional levels, no study has explored worldwide views, mainly due to financial and logistical limitations. YouTube is one of the largest sources of health-related information, where many visitors share their views as questions or comments. These can be used as a surrogate to understand the public’s perceptions. Objective: We analyzed the comments of all videos related to PCOS published on YouTube from May 2011 to April 2023 and identified trends over time in the comments, their context, associated themes, gender-based differences, and underlying sentiments. Methods: After extracting all the comments using the YouTube application programming interface, we contextually studied the keywords and analyzed gender differences using the Benjamini-Hochberg procedure. We applied a multidimensional approach to analyzing the content via association mining using Mozdeh. We performed network analysis to study associated themes using the Fruchterman-Reingold algorithm and then manually screened the comments for content analysis. The sentiments associated with YouTube comments were analyzed using SentiStrength. Results: A total of 85,872 comments from 940 PCOS videos on YouTube were extracted. We identified a specific gender for 13,106 comments. Of these, 1506 were matched to male users (11.5%), and 11,601 comments to female users (88.5%). Keywords including diagnosing PCOS, symptoms of PCOS, pills for PCOS (medication), and pregnancy were significantly associated with female users. Keywords such as herbal treatment, natural treatment, curing PCOS, and online searches were significantly associated with male users. The key themes associated with female users were symptoms of PCOS, positive personal experiences (themes such as helpful and love), negative personal experiences (fatigue and pain), motherhood (infertility and trying to conceive), self-diagnosis, and use of professional terminology detailing their journey. The key themes associated with male users were misinformation regarding the “cure” for PCOS, using natural and herbal remedies to cure PCOS, fake testimonies from spammers selling their courses and consultations, finding treatment for PCOS, and sharing perspectives of female family members. The overall average positive sentiment was 1.6651 (95% CI 1.6593-1.6709), and the average negative sentiment was 1.4742 (95% CI 1.4683-1.4802) with a net positive difference of 0.1909. Conclusions: There may be a disparity in views on PCOS between women and men, with the latter associated with non–evidence-based approaches and misinformation. The improving sentiment noticed with YouTube comments may reflect better health care services. Prioritizing and promoting evidence-based care and disseminating pragmatic online coverage is warranted to improve public sentiment and limit misinformation spread. %M 37695666 %R 10.2196/49220 %U https://www.jmir.org/2023/1/e49220 %U https://doi.org/10.2196/49220 %U http://www.ncbi.nlm.nih.gov/pubmed/37695666 %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 %@ 1947-2579 %I JMIR Publications %V 11 %N 2 %P e10141 %T Roles of Health Literacy in Relation to Social Determinants of Health and Recommendations for Informatics-Based Interventions: Systematic Review %D 2019 %7 ..2019 %9 %J Online J Public Health Inform %G English %X Over the years, there has been a lot of transformation in the way health care is delivered and how individuals access health. Rapid growth in technology has been attributed to the advancement. The internet has played a key role in the delivery of health care and serves currently as a huge source of health information to individuals regardless of their location, language or time.This cross sectional study was conducted in the Kwahu West Municipal to determine factors influencing online health information seeking behaviors among patients. Three hospitals in the municipality were purposively selected for the study. Outpatients attending these facilities were systematically selected. Data was collected using structured interviewer administered questionnaire.The study findings revealed that internet usage rate among patients was 85.8%. However, only 35.7% of patients ever used the internet to access health information. Sex, education and average monthly income were significant factors associated with online health information seeking. The study also showed that, computer and internet experience factors increased the probability of using internet for health information. After adjusting for confounding factors, being employed, earning higher income and owning computer were positive predictors of online health information seeking.It is important to explore other means of reducing the disparity in information access by improving skill and health literacy among the low social class who cannot afford internet ready devices. Health care providers should recognize that patients are using the internet for health information and should be prepared to assist and promote internet user skills among their patients. %M 31632607 %R 10.5210/ojphi.v11i2.10141 %U %U https://doi.org/10.5210/ojphi.v11i2.10141 %U http://www.ncbi.nlm.nih.gov/pubmed/31632607 %0 Journal Article %@ 1947-2579 %I JMIR Publications %V 4 %N 1 %P e3849 %T Roles of Health Literacy in Relation to Social Determinants of Health and Recommendations for Informatics-Based Interventions: Systematic Review %D 2012 %7 ..2012 %9 %J Online J Public Health Inform %G English %X Background: Human immunodeficiency virus and acquired immunodeficiency syndrome (HIV/AIDS) remains a significant international public health challenge. The Statewide HIV/AIDS Information Network (SHINE) Project was created to improve HIV/AIDS health information use and access for health care professionals, patients, and affected communities in Indiana.Objective: Our objective was to assess the information-seeking behaviors of health care professionals and consumers who seek information on the testing, treatment, and management of HIV/AIDS and the usability of the SHINE Project’s resources in meeting end user needs. The feedback was designed to help SHINE Project members improve and expand the SHINE Project’s online resources.Methods: A convenience sample of health care professionals and consumers participated in a usability study. Participants were asked to complete typical HIV/AIDS information-seeking tasks using the SHINE Project website. Feedback was provided in the form of standardized questionnaire and usability “think-aloud” responses.Results: Thirteen participants took part in the usability study. Clinicians generally reported the site to be “very good,” while consumers generally found it to be “good.” Health care professionals commented that they lack access to comprehensive resources for treating patients with HIV/AIDS. They requested new electronic resources that could be integrated in clinical practice and existing information technology infrastructures. Consumers found the SHINE website and its collected information resources overwhelming and difficult to navigate. They requested simpler, multimedia-content rich resources to deliver information on HIV/AIDS testing, treatment, and disease management.Conclusions: Accessibility, usability, and user education remain important challenges that public health and information specialists must address when developing and deploying interventions intended to empower consumers and support coordinated, patient-centric care. %M 23569627 %R 10.5210/ojphi.v4i1.3849 %U %U https://doi.org/10.5210/ojphi.v4i1.3849 %U http://www.ncbi.nlm.nih.gov/pubmed/23569627