JMIR infodemiology最新文献

{"title":"US Black Maternal Health Advocacy Topics and Trends on Twitter: Temporal Infoveillance Study","authors":"D. Grigsby-Toussaint, Ashley Champagne, Justin Uhr, Elizabeth Silva, Madeline Noh, Adam Bradley, Patrick Rashleigh","doi":"10.2196/30885","DOIUrl":"https://doi.org/10.2196/30885","url":null,"abstract":"Background Black women in the United States disproportionately suffer adverse pregnancy and birth outcomes compared to White women. Economic adversity and implicit bias during clinical encounters may lead to physiological responses that place Black women at higher risk for adverse birth outcomes. The novel coronavirus disease of 2019 (COVID-19) further exacerbated this risk, as safety protocols increased social isolation in clinical settings, thereby limiting opportunities to advocate for unbiased care. Twitter, 1 of the most popular social networking sites, has been used to study a variety of issues of public interest, including health care. This study considers whether posts on Twitter accurately reflect public discourse during the COVID-19 pandemic and are being used in infodemiology studies by public health experts. Objective This study aims to assess the feasibility of Twitter for identifying public discourse related to social determinants of health and advocacy that influence maternal health among Black women across the United States and to examine trends in sentiment between 2019 and 2020 in the context of the COVID-19 pandemic. Methods Tweets were collected from March 1 to July 13, 2020, from 21 organizations and influencers and from 4 hashtags that focused on Black maternal health. Additionally, tweets from the same organizations and hashtags were collected from the year prior, from March 1 to July 13, 2019. Twint, a Python programming library, was used for data collection and analysis. We gathered the text of approximately 17,000 tweets, as well as all publicly available metadata. Topic modeling and k-means clustering were used to analyze the tweets. Results A variety of trends were observed when comparing the 2020 data set to the 2019 data set from the same period. The percentages listed for each topic are probabilities of that topic occurring in our corpus. In our topic models, tweets on reproductive justice, maternal mortality crises, and patient care increased by 67.46% in 2020 versus 2019. Topics on community, advocacy, and health equity increased by over 30% in 2020 versus 2019. In contrast, tweet topics that decreased in 2020 versus 2019 were as follows: tweets on Medicaid and medical coverage decreased by 27.73%, and discussions about creating space for Black women decreased by just under 30%. Conclusions The results indicate that the COVID-19 pandemic may have spurred an increased focus on advocating for improved reproductive health and maternal health outcomes among Black women in the United States. Further analyses are needed to capture a longer time frame that encompasses more of the pandemic, as well as more diverse voices to confirm the robustness of the findings. We also concluded that Twitter is an effective source for providing a snapshot of relevant topics to guide Black maternal health advocacy efforts.","PeriodicalId":73554,"journal":{"name":"JMIR infodemiology","volume":"2 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44748924","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identifying Frames of the COVID-19 Infodemic: Thematic Analysis of Misinformation Stories Across Media.","authors":"Ehsan Mohammadi, Iman Tahamtan, Yazdan Mansourian, Holly Overton","doi":"10.2196/33827","DOIUrl":"10.2196/33827","url":null,"abstract":"<p><strong>Background: </strong>The word \"infodemic\" refers to the deluge of false information about an event, and it is a global challenge for today's society. The sheer volume of misinformation circulating during the COVID-19 pandemic has been harmful to people around the world. Therefore, it is important to study different aspects of misinformation related to the pandemic.</p><p><strong>Objective: </strong>This paper aimed to identify the main subthemes related to COVID-19 misinformation on various platforms, from traditional outlets to social media. This paper aimed to place these subthemes into categories, track the changes, and explore patterns in prevalence, over time, across different platforms and contexts.</p><p><strong>Methods: </strong>From a theoretical perspective, this research was rooted in framing theory; it also employed thematic analysis to identify the main themes and subthemes related to COVID-19 misinformation. The data were collected from 8 fact-checking websites that formed a sample of 127 pieces of false COVID-19 news published from January 1, 2020 to March 30, 2020.</p><p><strong>Results: </strong>The findings revealed 4 main themes (attribution, impact, protection and solutions, and politics) and 19 unique subthemes within those themes related to COVID-19 misinformation. Governmental and political organizations (institutional level) and administrators and politicians (individual level) were the 2 most frequent subthemes, followed by origination and source, home remedies, fake statistics, treatments, drugs, and pseudoscience, among others. Results indicate that the prevalence of misinformation subthemes had altered over time between January 2020 and March 2020. For instance, false stories about the origin and source of the virus were frequent initially (January). Misinformation regarding home remedies became a prominent subtheme in the middle (February), while false information related to government organizations and politicians became popular later (March). Although conspiracy theory web pages and social media outlets were the primary sources of misinformation, surprisingly, results revealed trusted platforms such as official government outlets and news organizations were also avenues for creating COVID-19 misinformation.</p><p><strong>Conclusions: </strong>The identified themes in this study reflect some of the information attitudes and behaviors, such as denial, uncertainty, consequences, and solution-seeking, that provided rich information grounds to create different types of misinformation during the COVID-19 pandemic. Some themes also indicate that the application of effective communication strategies and the creation of timely content were used to persuade human minds with false stories in different phases of the crisis. The findings of this study can be beneficial for communication officers, information professionals, and policy makers to combat misinformation in future global health crises or related events.</p>","PeriodicalId":73554,"journal":{"name":"JMIR infodemiology","volume":"2 1","pages":"e33827"},"PeriodicalIF":3.5,"publicationDate":"2022-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9987193/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9363930","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"COVID-19 and Vitamin D Misinformation on YouTube: Content Analysis.","authors":"Emma K Quinn, Shelby Fenton, Chelsea A Ford-Sahibzada, Andrew Harper, Alessandro R Marcon, Timothy Caulfield, Sajjad S Fazel, Cheryl E Peters","doi":"10.2196/32452","DOIUrl":"10.2196/32452","url":null,"abstract":"<p><strong>Background: </strong>The \"infodemic\" accompanying the SARS-CoV-2 virus pandemic has the potential to increase avoidable spread as well as engagement in risky health behaviors. Although social media platforms, such as YouTube, can be an inexpensive and effective method of sharing accurate health information, inaccurate and misleading information shared on YouTube can be dangerous for viewers. The confusing nature of data and claims surrounding the benefits of vitamin D, particularly in the prevention or cure of COVID-19, influences both viewers and the general \"immune boosting\" commercial interest.</p><p><strong>Objective: </strong>The aim of this study was to ascertain how information on vitamin D and COVID-19 was presented on YouTube in 2020.</p><p><strong>Methods: </strong>YouTube video results for the search terms \"COVID,\" \"coronavirus,\" and \"vitamin D\" were collected and analyzed for content themes and deemed useful or misleading based on the accuracy or inaccuracy of the content. Qualitative content analysis and simple statistical analysis were used to determine the prevalence and frequency of concerning content, such as confusing correlation with causation regarding vitamin D benefits.</p><p><strong>Results: </strong>In total, 77 videos with a combined 10,225,763 views (at the time of data collection) were included in the analysis, with over three-quarters of them containing misleading content about COVID-19 and vitamin D. In addition, 45 (58%) of the 77 videos confused the relationship between vitamin D and COVID-19, with 46 (85%) of 54 videos stating that vitamin D has preventative or curative abilities. The major contributors to these videos were medical professionals with YouTube accounts. Vitamin D recommendations that do not align with the current literature were frequently suggested, including taking supplementation higher than the recommended safe dosage or seeking intentional solar UV radiation exposure.</p><p><strong>Conclusions: </strong>The spread of misinformation is particularly alarming when spread by medical professionals, and existing data suggesting vitamin D has immune-boosting abilities can add to viewer confusion or mistrust in health information. Further, the suggestions made in the videos may increase the risks of other poor health outcomes, such as skin cancer from solar UV radiation.</p>","PeriodicalId":73554,"journal":{"name":"JMIR infodemiology","volume":"2 1","pages":"e32452"},"PeriodicalIF":3.5,"publicationDate":"2022-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8924908/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9704499","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identifying the Socioeconomic, Demographic, and Political Determinants of Social Mobility and Their Effects on COVID-19 Cases and Deaths: Evidence From US Counties.","authors":"Niloofar Jalali, N Ken Tran, Anindya Sen, Plinio Pelegrini Morita","doi":"10.2196/31813","DOIUrl":"10.2196/31813","url":null,"abstract":"<p><strong>Background: </strong>The spread of COVID-19 at the local level is significantly impacted by population mobility. The U.S. has had extremely high per capita COVID-19 case and death rates. Efficient nonpharmaceutical interventions to control the spread of COVID-19 depend on our understanding of the determinants of public mobility.</p><p><strong>Objective: </strong>This study used publicly available Google data and machine learning to investigate population mobility across a sample of US counties. Statistical analysis was used to examine the socioeconomic, demographic, and political determinants of mobility and the corresponding patterns of per capita COVID-19 case and death rates.</p><p><strong>Methods: </strong>Daily Google population mobility data for 1085 US counties from March 1 to December 31, 2020, were clustered based on differences in mobility patterns using K-means clustering methods. Social mobility indicators (retail, grocery and pharmacy, workplace, and residence) were compared across clusters. Statistical differences in socioeconomic, demographic, and political variables between clusters were explored to identify determinants of mobility. Clusters were matched with daily per capita COVID-19 cases and deaths.</p><p><strong>Results: </strong>Our results grouped US counties into 4 Google mobility clusters. Clusters with more population mobility had a higher percentage of the population aged 65 years and over, a greater population share of Whites with less than high school and college education, a larger percentage of the population with less than a college education, a lower percentage of the population using public transit to work, and a smaller share of voters who voted for Clinton during the 2016 presidential election. Furthermore, clusters with greater population mobility experienced a sharp increase in per capita COVID-19 case and death rates from November to December 2020.</p><p><strong>Conclusions: </strong>Republican-leaning counties that are characterized by certain demographic characteristics had higher increases in social mobility and ultimately experienced a more significant incidence of COVID-19 during the latter part of 2020.</p>","PeriodicalId":73554,"journal":{"name":"JMIR infodemiology","volume":"2 1","pages":"e31813"},"PeriodicalIF":3.5,"publicationDate":"2022-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8900047/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9704497","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Partisan Differences in Legislators' Discussion of Vaccination on Twitter During the COVID-19 Era: Natural Language Processing Analysis.","authors":"Eden Engel-Rebitzer, Daniel C Stokes, Zachary F Meisel, Jonathan Purtle, Rebecca Doyle, Alison M Buttenheim","doi":"10.2196/32372","DOIUrl":"10.2196/32372","url":null,"abstract":"<p><strong>Background: </strong>The COVID-19 era has been characterized by the politicization of health-related topics. This is especially concerning given evidence that politicized discussion of vaccination may contribute to vaccine hesitancy. No research, however, has examined the content and politicization of legislator communication with the public about vaccination during the COVID-19 era.</p><p><strong>Objective: </strong>The aim of this study was to examine vaccine-related tweets produced by state and federal legislators during the COVID-19 era to (1) describe the content of vaccine-related tweets; (2) examine the differences in vaccine-related tweet content between Democrats and Republicans; and (3) quantify (and describe trends over time in) partisan differences in vaccine-related communication.</p><p><strong>Methods: </strong>We abstracted all vaccine-related tweets produced by state and federal legislators between February 01, 2020, and December 11, 2020. We used latent Dirichlet allocation to define the tweet topics and used descriptive statistics to describe differences by party in the use of topics and changes in political polarization over time.</p><p><strong>Results: </strong>We included 14,519 tweets generated by 1463 state legislators and 521 federal legislators. Republicans were more likely to use words (eg, \"record time,\" \"launched,\" and \"innovation\") and topics (eg, Operation Warp Speed success) that were focused on the successful development of a SARS-CoV-2 vaccine. Democrats used a broader range of words (eg, \"anti-vaxxers,\" \"flu,\" and \"free\") and topics (eg, vaccine prioritization, influenza, and antivaxxers) that were more aligned with public health messaging related to the vaccine. Polarization increased over most of the study period.</p><p><strong>Conclusions: </strong>Republican and Democratic legislators used different language in their Twitter conversations about vaccination during the COVID-19 era, leading to increased political polarization of vaccine-related tweets. These communication patterns have the potential to contribute to vaccine hesitancy.</p>","PeriodicalId":73554,"journal":{"name":"JMIR infodemiology","volume":"2 1","pages":"e32372"},"PeriodicalIF":3.5,"publicationDate":"2022-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8862742/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9358807","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Media data and vaccine hesitancy: a scoping review (Preprint)","authors":"J. Yin","doi":"10.2196/preprints.37300","DOIUrl":"https://doi.org/10.2196/preprints.37300","url":null,"abstract":"\u0000 BACKGROUND\u0000 Media studies are important for vaccine hesitancy research since they analyze how media shapes risk perceptions and uptake of vaccines. Despite a growth in studies in this field due to advances in computing, language processing, and an expanding social media landscape, no study has consolidated the methodological approaches used to study vaccine hesitancy. Synthesizing this information can better structure and set a precedent for this growing subfield of digital epidemiology.\u0000 \u0000 \u0000 OBJECTIVE\u0000 The review aimed to identify and illustrate what media platforms and methods were used to study vaccine hesitancy, and how they build or contribute to the study of media’s influence on vaccine hesitancy and public health.\u0000 \u0000 \u0000 METHODS\u0000 This study followed PRISMA’s (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) guidelines for scoping reviews. A search was done of PubMed, Web of Science, and SCOPUS for any studies that: used media data (social media and/or traditional media); had an outcome related to vaccine sentiment (opinion, uptake, hesitancy, acceptance, stance); were written in English; and published after 2010. Studies were screened by only one reviewer, and extracted for media platform, analysis method, and theoretical models used.\u0000 \u0000 \u0000 RESULTS\u0000 A total of 123 studies were included, 69 which used traditional research methods and 54 which used computational methods. Of the traditional methods, a majority used content analysis (74.2%) and sentiment analysis (37.1%) to analyze texts, with few using campaign evaluation methods (8.1%) and tracking of search activity and/or information spread (11.3%). The most common platform was newspapers, print media, and online news. Computational methods mostly used sentiment analysis (57.4%), topic modelling (31.5%), and network analysis (27.8%). Fewer studies used projections and feature extraction as methods. The most common platforms were Twitter and Facebook. Theoretically, most studies were weak. Of traditional methods, only 8 had a theory-based approach (11.6%); and for computational methods, only 6 (11.1%). Due to a patchwork of studies resulting from combinations of platforms and methods, it is difficult to draw a coherent conclusion on media’s influence on vaccine hesitancy.\u0000 \u0000 \u0000 CONCLUSIONS\u0000 There is heterogeneity in using media data to study vaccine hesitation, evidenced in the medley of combinations of platforms and computer science tools (eg. network analysis, sentiment analysis). Yet, these studies are guided by a preference for using novel methods rather than theory, making their links to public health tenuous. This review suggests and walks through a theory-first approach that can aid in better formulation of knowledge and establish a coherent paradigm in media studies on vaccine hesitancy. It ends with a statement that media data analyses, though groundbreaking in approach, should supplement–not supplant–current practices in public health research.\u0000","PeriodicalId":73554,"journal":{"name":"JMIR infodemiology","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46891027","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"COVID-19 and Tweets About Quitting Cigarette Smoking: Topic Model Analysis of Twitter Posts 2018-2020","authors":"J. Westmaas, M. Masters, Priti Bandi, Anuja Majmundar, S. Asare, W. Diver","doi":"10.2196/36215","DOIUrl":"https://doi.org/10.2196/36215","url":null,"abstract":"Background The risk of infection and severity of illness by SARS-CoV-2 infection is elevated for people who smoke cigarettes and may motivate quitting. Organic public conversations on Twitter about quitting smoking could provide insight into quitting motivations or behaviors associated with the pandemic. Objective This study explored key topics of conversation about quitting cigarette smoking and examined their trajectory during 2018-2020. Methods Topic model analysis with latent Dirichlet allocation (LDA) identified themes in US tweets with the term “quit smoking.” The model was trained on posts from 2018 and was then applied to tweets posted in 2019 and 2020. Analysis of variance and follow-up pairwise tests were used to compare the daily frequency of tweets within and across years by quarter. Results The mean numbers of daily tweets on quitting smoking in 2018, 2019, and 2020 were 133 (SD 36.2), 145 (SD 69.4), and 127 (SD 32.6), respectively. Six topics were extracted: (1) need to quit, (2) personal experiences, (3) electronic cigarettes (e-cigarettes), (4) advice/success, (5) quitting as a component of general health behavior change, and (6) clinics/services. Overall, the pandemic was not associated with changes in posts about quitting; instead, New Year’s resolutions and the 2019 e-cigarette or vaping use–associated lung injury (EVALI) epidemic were more plausible explanations for observed changes within and across years. Fewer second-quarter posts in 2020 for the topic e-cigarettes may reflect lower pandemic-related quitting interest, whereas fourth-quarter increases in 2020 for other topics pointed to a late-year upswing. Conclusions Twitter posts suggest that the pandemic did not generate greater interest in quitting smoking, but possibly a decrease in motivation when the rate of infections was increasing in the second quarter of 2020. Public health authorities may wish to craft messages for specific Twitter audiences (eg, using hashtags) to motivate quitting during pandemics.","PeriodicalId":73554,"journal":{"name":"JMIR infodemiology","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49263236","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Constituents' Inferences of Local Governments' Goals and the Relationship Between Political Party and Belief in COVID-19 Misinformation: Cross-sectional Survey of Twitter Followers of State Public Health Departments.","authors":"Hannah Stevens,&nbsp;Nicholas A Palomares","doi":"10.2196/29246","DOIUrl":"https://doi.org/10.2196/29246","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Amid the COVID-19 pandemic, social media have influenced the circulation of health information. Public health agencies often use Twitter to disseminate and amplify the propagation of such information. Still, exposure to local government-endorsed COVID-19 public health information does not make one immune to believing misinformation. Moreover, not all health information on Twitter is accurate, and some users may believe misinformation and disinformation just as much as those who endorse more accurate information. This situation is complicated, given that elected officials may pursue a political agenda of re-election by downplaying the need for COVID-19 restrictions. The politically polarized nature of information and misinformation on social media in the United States has fueled a COVID-19 infodemic. Because pre-existing political beliefs can both facilitate and hinder persuasion, Twitter users' belief in COVID-19 misinformation is likely a function of their goal inferences about their local government agencies' motives for addressing the COVID-19 pandemic.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;We shed light on the cognitive processes of goal understanding that underlie the relationship between partisanship and belief in health misinformation. We investigate how the valence of Twitter users' goal inferences of local governments' COVID-19 efforts predicts their belief in COVID-19 misinformation as a function of their political party affiliation.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;We conducted a web-based cross-sectional survey of US Twitter users who followed their state's official Department of Public Health Twitter account (n=258) between August 10 and December 23, 2020. Inferences about local governments' goals, demographics, and belief in COVID-19 misinformation were measured. State political affiliation was controlled.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;Participants from all 50 states were included in the sample. An interaction emerged between political party affiliation and goal inference valence for belief in COVID-19 misinformation (∆&lt;i&gt;R&lt;/i&gt; &lt;sup&gt;2&lt;/sup&gt;=0.04; &lt;i&gt;F&lt;/i&gt; &lt;sub&gt;8,249&lt;/sub&gt;=4.78; &lt;i&gt;P&lt;/i&gt;&lt;.001); positive goal inference valence predicted increased belief in COVID-19 misinformation among Republicans (β=.47; &lt;i&gt;t&lt;/i&gt; &lt;sub&gt;249&lt;/sub&gt;=2.59; &lt;i&gt;P&lt;/i&gt;=.01) but not among Democrats (β=.07; &lt;i&gt;t&lt;/i&gt; &lt;sub&gt;249&lt;/sub&gt;=0.84; &lt;i&gt;P&lt;/i&gt;=.40).&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;Our results reveal that favorable inferences about local governments' COVID-19 efforts can accelerate belief in misinformation among Republican-identifying constituents. In other words, accurate COVID-19 transmission knowledge is a function of constituents' sentiment toward politicians rather than science, which has significant implications on public health efforts for minimizing the spread of the disease, as convincing misinformed constituents to practice safety measures might be a political issue just as much as it is a health one. Our work suggests","PeriodicalId":73554,"journal":{"name":"JMIR infodemiology","volume":"2 1","pages":"e29246"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10014089/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9363936","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Factors Affecting Physicians' Credibility on Twitter When Sharing Health Information: Online Experimental Study.","authors":"DaJuan Ferrell,&nbsp;Celeste Campos-Castillo","doi":"10.2196/34525","DOIUrl":"https://doi.org/10.2196/34525","url":null,"abstract":"<p><strong>Background: </strong>Largely absent from research on how users appraise the credibility of professionals as sources for the information they find on social media is work investigating factors shaping credibility within a specific profession, such as physicians.</p><p><strong>Objective: </strong>We address debates about how physicians can show their credibility on social media depending on whether they employ a formal or casual appearance in their profile picture. Using prominence-interpretation theory, we posit that formal appearance will affect perceived credibility based on users' social context-specifically, whether they have a regular health care provider.</p><p><strong>Methods: </strong>For this experiment, we recruited 205 social media users using Amazon Mechanical Turk. We asked participants if they had a regular health care provider and then randomly assigned them to read 1 of 3 Twitter posts that varied only in the profile picture of the physician offering health advice. Next, we tasked participants with assessing the credibility of the physician and their likelihood of engaging with the tweet and the physician on Twitter. We used path analysis to assess whether participants having a regular health care provider impacted how the profile picture affected their ratings of the physician's credibility and their likelihood to engage with the tweet and physician on Twitter.</p><p><strong>Results: </strong>We found that the profile picture of a physician posting health advice in either formal or casual attire did not elicit significant differences in credibility, with ratings comparable to those having no profile image. Among participants assigned the formal appearance condition, those with a regular provider rated the physician higher on a credibility than those without, which led to stronger intentions to engage with the tweet and physician.</p><p><strong>Conclusions: </strong>The findings add to existing research by showing how the social context of information seeking on social media shapes the credibility of a given professional. Practical implications for professionals engaging with the public on social media and combating false information include moving past debates about casual versus formal appearances and toward identifying ways to segment audiences based on factors like their backgrounds (eg, experiences with health care providers).</p>","PeriodicalId":73554,"journal":{"name":"JMIR infodemiology","volume":"2 1","pages":"e34525"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9987183/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9369312","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Themes Surrounding COVID-19 and Its Infodemic: Qualitative Analysis of the COVID-19 Discussion on the Multidisciplinary Healthcare Information for All Health Forum.","authors":"Rakshith Gangireddy,&nbsp;Stuti Chakraborty,&nbsp;Neil Pakenham-Walsh,&nbsp;Branavan Nagarajan,&nbsp;Prerna Krishan,&nbsp;Richard McGuire,&nbsp;Gladson Vaghela,&nbsp;Abi Sriharan","doi":"10.2196/30167","DOIUrl":"https://doi.org/10.2196/30167","url":null,"abstract":"<p><strong>Background: </strong>Healthcare Information for All (HIFA) is a multidisciplinary global campaign consisting of more than 20,000 members worldwide committed to improving the availability and use of health care information in low- and middle-income countries (LMICs). During the COVID-19 pandemic, online HIFA forums saw a tremendous amount of discussion regarding the lack of information about COVID-19, the spread of misinformation, and the pandemic's impact on different communities.</p><p><strong>Objective: </strong>This study aims to analyze the themes and perspectives shared in the COVID-19 discussion on English HIFA forums.</p><p><strong>Methods: </strong>Over a period of 8 months, a qualitative thematic content analysis of the COVID-19 discussion on English HIFA forums was conducted. In total, 865 posts between January 24 and October 31, 2020, from 246 unique study participants were included and analyzed.</p><p><strong>Results: </strong>In total, 6 major themes were identified: infodemic, health system, digital health literacy, economic consequences, marginalized peoples, and mental health. The geographical distribution of study participants involved in the discussion spanned across 46 different countries in every continent except Antarctica. Study participants' professions included public health workers, health care providers, and researchers, among others. Study participants' affiliation included nongovernment organizations (NGOs), commercial organizations, academic institutions, the United Nations (UN), the World Health Organization (WHO), and others.</p><p><strong>Conclusions: </strong>The themes that emerged from this analysis highlight personal recounts, reflections, suggestions, and evidence around addressing COVID-19 related misinformation and might also help to understand the timeline of information evolution, focus, and needs surrounding the COVID-19 pandemic.</p>","PeriodicalId":73554,"journal":{"name":"JMIR infodemiology","volume":"2 1","pages":"e30167"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9100310/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9349982","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}