Misinformation In Social Media Research Articles

Seeing is Not Believing: A Nuanced View of Misinformation Warning Efficacy on Video-Sharing Social Media Platforms

Misinformation warnings have become the de facto solution for fighting fake news online. Our study brings attention to the challenge of developing effective misinformation warnings on short video-sharing platforms. We conducted semi-structured interviews with the think-aloud protocol to understand how users interact with and perceive misinformation warnings, specifically the interstitial and contextual warnings adopted by TikTok and Instagram Reels. We recruited 28 regular users of TikTok and Instagram Reels for this study. We contribute to the evolving scholarship on social media misinformation mitigation by casting light on nuanced participant interactions with and perceptions of misinformation warnings and how these interactions and perceptions influence the perceived accuracy of short video content. Our findings are threefold. First, the present study shows that specific contextual warnings do not always elicit behavioral adherence but can alert users to be vigilant about misinformation. Second, users' perceptions of interstitial and contextual warnings are influenced by the warning's explicitness and the risk level of the misinformation. Third, we identify the least and most effective/favored warning designs to help make accuracy judgments according to the participants. To this end, our findings have implications for improving the design of misinformation warnings on short video-sharing platforms.

How to Deal With Social Media Misinformation

How to Deal With Social Media Misinformation

The Impact Of Misinformation In Social Media That Caused Panic Behavior On Covid-19 Pandemic Among University Students In Ipoh, Perak

Social networking has become a regular part of everyone's life. Nowadays, practically everyone uses social media and messaging platforms for communication, especially university students who frequently use smartphones and other devices for social interaction and communication. Due to this, university students began to believe the information shared on social media without verifying its accuracy. The veracity of the information shared on social media is unconfirmed for a number of reasons. Some of the false information spread has led to students at the university behaving panicked. As a result, the focus of this study will be on the effect of misleading news on Covid-19 among Malaysian university students. This will help to ensure that the study's goals, which include determining how social media misinformation influences university students' behaviour and fostering the spread of fear about COVID-19 in Malaysia, are successfully attained. In due to that the study uses quantitative methodology as its main research approach. Information was gathered by the researcher from university students using online surveys. The findings of this study indicated that disinformation disseminated via social media platforms, particularly the amplifying of dread that resulted in increased worry and anxiety, was likely to have an impact on university students in Ipoh, Perak. In order to discover the trends that may spread to other new consumers, particularly with the increased adoption of mobile connectivity, this study should be continued by focusing on the behavioural patterns and attitudes of this news consumption segment.

Political quarrel overshadows vaccination advocacy: How the vaccine debate on Brazilian Twitter was framed by anti-vaxxers during Bolsonaro administration

Despite Brazil's tradition of successful mass immunization programs, the country has been experiencing alarming declines in vaccination coverage, especially among children. That is aggravated by the growth of anti-vaccine movements and the spread of health misinformation in social media in the last decade, which have worsened during the COVID-19 outbreak. Several reports link populism and far-right politicians to anti-vaccination support worldwide, which was also the case in Brazil during president Jair Bolsonaro's administration. This project aimed to identify the circulating pro and anti-vaccine narratives in Portuguese on Twitter, during a crucial decision-making period regarding childhood vaccination in Brazil, from December 9, 2021, until February 9, 2022. From the over one million tweets and four million retweets collected, we identified two well-defined groups, one in favor and another against vaccination. Within the sample, we selected 1500 influencer tweets with the highest impact (>500 retweets) and conducted content analysis. Although the pro-vaccine influencers were more retweeted than anti-vaxxer ones, we observed that anti-vaccine movements were more succesful in framing discussions on Twitter. The subject of COVID-19 was the target of political polarization embedded in populist, anti-science and anti-traditional media discourses promoted by anti-vaxxers. As a counterpart, the pro-vaccine influencers reacted inarticulately, focusing on criticizing the anti-vaccination actors, attitudes, and policies instead of promoting vaccines. Based on reults, we claim that a well-coordinated network of health communicators from science centers and health institutions, in partnership with properly briefed social media influencers and fact-checking sources, would more efectively pre-tempt the public about vaccine misinformation.

Методология выявления и отслеживания дезинформации в социальных сетях о воздействии пандемии COVID-19 на репродуктивное здоровье

Цель исследования заключалась в разработке методики выявления и отслеживания дезинформации в социальных сетях, в частности в Твиттере, о влиянии коронавируса и COVID-вакцины на репродуктивное здоровье, одной из причин чего является недостаточная информированность об аспектах коронавирусной инфекции. Мы используем сочетание машинных и экспертных методов, последние научные статьи как эталон выявления дезинформации. Предлагаемая методика включает в себя изучение научных статей как источника достоверной правдивой информации по теме (стандарт информации) и сообщений в Твиттере (оценка соответствия информации стандарту). Результатом исследования является методика выявления дезинформации в сообщениях пользователей социальной сети. На основе этой методологии разработаны следующие аспекты проблемы: 1) формирование научного стандарта; 2) принцип сопоставления направлений научных исследований и дискуссий в Твиттере; 3) принцип контекстуального сопоставления пользовательского и научного представлений о проблемах. В отличие от существующих работ, сформулированы принципы, основанные на обработке информации из содержания научных статей и сообщений в социальных сетях. The purpose of the study was to develop a methodology for identifying and tracking social media misinformation in tweets about the impact of the coronavirus and COVID-vaccine on reproductive health, one of the reasons for which is the lack of awareness about aspects of the coronavirus infection. We use a combination of machine and expert methods, the latest scientific articles as the standard for detecting disinformation. The proposed methodology includes the study of scientific articles as a source of reliable truthful information about the topic (information standard) and Twitter messages (assessment of information compliance with the standard). The result of the study is the methodology for detecting disinformation in the messages of social network users. Based on this methodology, the following aspects of the problem have been developed: 1) the formation of a scientific standard; 2) the principle of comparing the directions of scientific research and discussions on Twitter; 3) the principle of contextual comparison of user and scientific ideas about problems. In contrast to the existing works, the principles based on the information from the content of scientific articles and messages from social networks processing are formulated.

Not all skepticism is “healthy” skepticism: Theorizing accuracy- and identity-motivated skepticism toward social media misinformation

Fostering skepticism has been seen as key to addressing misinformation on social media. This article reveals that not all skepticism is “healthy” skepticism by theorizing, measuring, and testing the effects of two types of skepticism toward social media misinformation: accuracy- and identity-motivated skepticism. A two-wave panel survey experiment shows that when people’s skepticism toward social media misinformation is driven by accuracy motivations, they are less likely to believe in congruent misinformation later encountered. They also consume more mainstream media, which in turn reinforces accuracy-motivated skepticism. In contrast, when skepticism toward social media misinformation is driven by identity motivations, people not only fall for congruent misinformation later encountered, but also disregard platform interventions that flag a post as false. Moreover, they are more likely to see social media misinformation as favoring opponents and intentionally avoid news on social media, both of which form a vicious cycle of fueling more identity-motivated skepticism.

(324) TikTok’s Misinformation about COVID-19 Infections and Vaccinations on Male Fertility

Abstract Introduction The effect of the SARS-CoV-2 infection and vaccine on male fertility has been a cause of controversy. Studies have found that while active or recovering COVID-19 disease can be associated with decreased sperm counts and quality, the COVID vaccine is not. Despite evidence about the lack of association between the COVID-19 vaccine and male fertility, social media platforms continue to contribute to the spread of misleading information. TikTok is a popular application that has become critical in this regard. Objective To identify the role TikTok contributes to misinformation around the COVID-19 virus, vaccination, and male infertility. Methods 72 videos using the terms #covidvaccine and #malefertility were identified on Tiktok from January 1, 2020 to December 31, 2021. Videos not related to the topic were excluded, leaving 58 videos. Videos were reviewed by five independent researchers. Information collected included video publication date, length, views, likes, comments, presence of US certified medical professional, demographic details of main subject, scientific article cited or displayed, belief held on COVID-19 vaccine, infection and infertility, modified DISCERN score and Patient Materials Assessment Tool (PEMAT). U.S. medical professional certification was determined using certificationmatters.org. The PEMAT score evaluated 17 items regarding understandability and actionability. The modified DISCERN based reliability score ranked quality from 1 = poor, to 5 = excellent. Data was analyzed using SPSS statistics software v24. Results The average video was 51 seconds long, received 34,678 views, 3,301 likes, and 160 comments. The main subject of the videos were predominantly female (53.4%) and white (55.2%). A majority of videos featured a medical professional (67.2%) and were published by medical professionals (63.8%). Up to 46.4% of videos featured a scientific article that was either cited or displayed on the screen. Most videos were of the opinion that the COVID-19 infection causes infertility in men (48.3%) but not the vaccine (37.9%). Only a select few videos believed that the vaccine was responsible for male infertility (6.9%). The most popular video stating the COVID vaccine caused infertility in men had 2,708 views, 336 likes, and 18 comments. The average DISCERN score for the 58 videos was 2.93, PEMAT Understandability score was 76.1%, and PEMAT Actionability score was 25.7%. With the presence of a certified US Medical Professional in the TikTok video, the average DISCERN score (2.00 vs. 3.38, p= .001), PEMAT Understandability Score (67.68 vs. 80.26, p = .015), and PEMAT Actionability Score (13.16 vs. 31.82, p = .024) increased significantly. Videos with medical professionals present had a lower average number of views (31,996 vs. 40179, p = .691), fewer likes (1,902 vs. 6,173, p = .290), and fewer comments (150 vs. 182, p = .737), but none of these differences were statistically significant. Conclusions This study demonstrates that TikTok videos endorsing misinformation are popularly viewed. Among all the misinformation in social media, it is reassuring to see that there are medical professionals interested in promoting medically accurate information. Disclosure No

Multifaceted Role of Social Media in Healthcare: Opportunities, Challenges, and the Need for Quality Control.

Social media, leveraging Web 2.0 technologies, plays a vital role in healthcare, medical education, and research by fostering collaboration and enabling research dissemination. Healthcare professionals use these platforms to improve public health literacy, but concerns about misinformation and content accuracy persist. In 2023, platforms like Facebook (Meta Platforms, Inc., Menlo Park, California, United States), YouTube (Google LLC, Mountain View, California, United States), Instagram (Meta Platforms, Inc.), TikTok (ByteDance Ltd, Beijing, China), and Twitter (X Corp., Carson City, Nevada, United States) have become essential in healthcare, offering patient communication, professional development, and knowledge-sharing opportunities. However, challenges such as breaches of patient confidentiality and unprofessional conduct remain. Social media has transformed medical education, providing unique networking and professional development opportunities. Further studies are needed to determine its educational value. Healthcare professionals must follow ethical and professional guidelines, particularly regarding patient privacy, confidentiality, disclosure rules, and copyright laws. Social media significantly impacts patient education and healthcare research. Platforms like WhatsApp (Meta Platforms, Inc.) effectively improve patient compliance and outcomes. Yet, the rapid dissemination of false news and misinformation on social media platforms presents risks. Researchers must consider potential biases and content quality when extracting data. Quality control and regulation are crucial in addressing potential dangers and misinformation in social media and healthcare. Stricter regulations and monitoring are needed due to cases of deaths resulting from social media trends and false news spread. Ethical frameworks, informed consent practices, risk assessments, and appropriate data management strategies are essential for responsible research using social media technologies. Healthcare professionals and researchers must judiciously use social media, considering its risks to maximize benefits and mitigate potential drawbacks. By striking the right balance, healthcare professionals can enhance patient outcomes, medical education, research, and the overall healthcare experience.

Predicting and characterising persuasion strategies in misinformation content over social media based on the multi-label classification approach

Persuasion aims at affecting the audience’s attitude and behaviour through a series of messages containing persuasion strategies. In the context of misinformation spread, identifying the persuasion strategies is important in order to warn people to be aware of the analogous persuasion attempts in the future. In this work, we address the prediction of persuasion strategies in micro-blogging posts through a multi-label classification approach based on a variety of lexical and semantic features. We conduct our experiments using a set of well-known multi-label classification algorithms, including multi-label decision tree, multi-label k-nearest neighbours, multi-label random forest, binary relevance and classifier chains. The results show that the model incorporating classifier chains and XGBoost algorithm achieves the best subset accuracy of 0.779 and the highest macro F1-score of 0.847. In addition, we evaluated and compared the features’ importance for different persuasion strategies and analysed the major errors of miss-out prediction. The findings of this article provide a benchmark for the multi-label classification of persuasion strategies in micro-blogging posts and lead to a better understanding of different persuasion attempts contained in social media misinformation.

MP45-18 MISINFORMATION ON TIKTOK ABOUT THE EFFECT OF COVID-19 INFECTIONS AND VACCINATIONS ON MALE FERTILITY

You have accessJournal of UrologyCME1 Apr 2023MP45-18 MISINFORMATION ON TIKTOK ABOUT THE EFFECT OF COVID-19 INFECTIONS AND VACCINATIONS ON MALE FERTILITY Meher Pandher, Jacob Veliky, John Fastenau, Gabriel Fernandez Pedrosa, Anh Nguyen, and Hossein Sadeghi-Nejad Meher PandherMeher Pandher More articles by this author , Jacob VelikyJacob Veliky More articles by this author , John FastenauJohn Fastenau More articles by this author , Gabriel Fernandez PedrosaGabriel Fernandez Pedrosa More articles by this author , Anh NguyenAnh Nguyen More articles by this author , and Hossein Sadeghi-NejadHossein Sadeghi-Nejad More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000003291.18AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: The effect of the SARS-CoV-2 infection and vaccine on male fertility has been a cause of controversy. Studies have found that while COVID-19 disease can be associated with decreased sperm counts and quality, the vaccine is not. Despite evidence about the lack of association between the COVID-19 vaccine and male fertility, social media platforms, including TikTok, continue to spread misleading information. Objective: To identify how TikTok contributes to misinformation regarding the COVID-19 virus, vaccination, and male infertility. METHODS: After excluding unrelated videos, 58 videos using the terms #covidvaccine and #malefertility were identified on Tiktok from January 1 to December 31, 2021. Videos were reviewed by five independent researchers. Information collected included video publication date, length, views, likes, comments, presence of US certified medical professional, demographic details, scientific article cited, belief held on COVID-19 vaccine, infection and infertility, modified DISCERN score and Patient Materials Assessment Tool (PEMAT). The PEMAT score evaluated 17 items regarding understandability and actionability. The modified DISCERN based reliability score ranked quality from 1=poor, to 5=excellent. Data was analyzed using SPSS statistics software v24. RESULTS: The average video was 51 seconds long, received 34,678 views, 3,301 likes, and 160 comments. A majority of videos featured a medical professional (67.2%). Most videos were of the opinion that the COVID-19 infection causes infertility in men (48.3%) but not the vaccine (37.9%). Few videos believed that the vaccine was responsible for male infertility (6.9%). The average DISCERN score for the 58 videos was 2.93, PEMAT Understandability score was 76.1%, and PEMAT Actionability score was 25.7%. With the presence of a certified US Medical Professional in the TikTok video, the average DISCERN score (2.00 vs. 3.38, p=.001), PEMAT Understandability Score (67.68 vs. 80.26, p=.015), and PEMAT Actionability Score (13.16 vs. 31.82, p=.024) increased significantly. Videos with medical professionals present had a lower average number of views (31,996 vs. 40179, p=.691), fewer likes (1,902 vs. 6,173, p=.290), and fewer comments (150 vs. 182, p=.737), but none of these differences were statistically significant. CONCLUSIONS: This study demonstrates that TikTok videos endorsing misinformation are popularly viewed. Among all the misinformation in social media, it is reassuring to see that there are medical professionals interested in promoting medically accurate information. Source of Funding: N/A © 2023 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 209Issue Supplement 4April 2023Page: e628 Advertisement Copyright & Permissions© 2023 by American Urological Association Education and Research, Inc.MetricsAuthor Information Meher Pandher More articles by this author Jacob Veliky More articles by this author John Fastenau More articles by this author Gabriel Fernandez Pedrosa More articles by this author Anh Nguyen More articles by this author Hossein Sadeghi-Nejad More articles by this author Expand All Advertisement PDF downloadLoading ...

The influencer sent me! Examining how social media influencers affect social media engagement, social self-efficacy, knowledge acquisition, and social interaction

This study examined how exposure to social media influencer (SMI) content affects social media engagement (SME), knowledge acquisition, social self-efficacy (SSE), and social interaction. Structural equation analysis indicated that exposure to SMI content improves SME, perceptions of knowledge acquisition, and SSE. In turn, perceptions of knowledge acquisition improved SSE and improved both online and offline social interaction. Perceptions of knowledge acquisition positively mediated between exposure to SMI content and online social interaction, between SME and online social interaction, and between SME and SSE. The study concludes that following an SMI empowers users regarding perceptions of knowledge and SSE, and that these two then improve social interaction with others. These effects are important in the context of social media misinformation and the fact that SMI content is widely consumed and yet remains largely unvetted for accuracy and authenticity.

Harm Related to Social Media Misinformation on Pelvic Organ Prolapse in YouTube, Instagram, and Pinterest Posts

Social media can improve patient education but may pose risks due to misinformation. There is no consensus on categorizing types of misinformation and harm. This study aimed to categorize and quantify misinformation and resultant harm from posts on YouTube, Pinterest, and Instagram on pelvic organ prolapse (POP), a prevalent benign condition that impacts quality of life. We conducted a descriptive study of 300 posts presented in these platforms in 2019. Using Fisher exact test, we show a significant difference in the distribution of misinformation between social media platforms. Harmful posts were most frequently present on Pinterest, leading to harmful inaction and economic harm.

Knowledge, Attitudes, and Perception as Predictors of COVID-19 Safety Practices of Ride-Hailing Operators in Ghana: A Cross-Sectional Study

Since its outbreak, health authorities have launched vigorous COVID-19 health promotion campaigns. This study assesses ride-hailing operators' COVID-19 knowledge, attitudes, and practices in Ghana, with the aim of engendering precautionary behaviour among the populace. A complementary mixed methods approach was adopted. This involved a cross-sectional survey of 1014 participants who were also allowed to share their COVID-19-related lived experiences qualitatively after successfully completing the survey. The aggregate correct knowledge score was 84%. Most respondents were frightful of the virus (96%), but the majority had faith in the COVID-19 protocols (87%). Thus, most participants reported high use of face masks (95%) and practise personal hygiene (92%). However, social media misinformation and the subsequent complacency have dissuaded some participants from complying with the safety protocols. The qualitative data also show evidence of high susceptibility to COVID-19. The perceived benefits of safe behaviour, including masking up, were equally high among drivers surveyed, albeit barriers to preventative behaviours remain rife. Therefore, this study emphasises the importance of sustaining and improving public awareness by highlighting the susceptibility of all demographic groups to the virus and the need to counteract misinformation on social media.

Fake news, disinformation and misinformation in social media: a review.

Online social networks (OSNs) are rapidly growing and have become a huge source of all kinds of global and local news for millions of users. However, OSNs are a double-edged sword. Although the great advantages they offer such as unlimited easy communication and instant news and information, they can also have many disadvantages and issues. One of their major challenging issues is the spread of fake news. Fake news identification is still a complex unresolved issue. Furthermore, fake news detection on OSNs presents unique characteristics and challenges that make finding a solution anything but trivial. On the other hand, artificial intelligence (AI) approaches are still incapable of overcoming this challenging problem. To make matters worse, AI techniques such as machine learning and deep learning are leveraged to deceive people by creating and disseminating fake content. Consequently, automatic fake news detection remains a huge challenge, primarily because the content is designed in a way to closely resemble the truth, and it is often hard to determine its veracity by AI alone without additional information from third parties. This work aims to provide a comprehensive and systematic review of fake news research as well as a fundamental review of existing approaches used to detect and prevent fake news from spreading via OSNs. We present the research problem and the existing challenges, discuss the state of the art in existing approaches for fake news detection, and point out the future research directions in tackling the challenges.

Lessons Learned From Interdisciplinary Efforts to Combat COVID-19 Misinformation: Development of Agile Integrative Methods From Behavioral Science, Data Science, and Implementation Science.

Despite increasing awareness about and advances in addressing social media misinformation, the free flow of false COVID-19 information has continued, affecting individuals' preventive behaviors, including masking, testing, and vaccine uptake. In this paper, we describe our multidisciplinary efforts with a specific focus on methods to (1) gather community needs, (2) develop interventions, and (3) conduct large-scale agile and rapid community assessments to examine and combat COVID-19 misinformation. We used the Intervention Mapping framework to perform community needs assessment and develop theory-informed interventions. To supplement these rapid and responsive efforts through large-scale online social listening, we developed a novel methodological framework, comprising qualitative inquiry, computational methods, and quantitative network models to analyze publicly available social media data sets to model content-specific misinformation dynamics and guide content tailoring efforts. As part of community needs assessment, we conducted 11 semistructured interviews, 4 listening sessions, and 3 focus groups with community scientists. Further, we used our data repository with 416,927 COVID-19 social media posts to gather information diffusion patterns through digital channels. Our results from community needs assessment revealed the complex intertwining of personal, cultural, and social influences of misinformation on individual behaviors and engagement. Our social media interventions resulted in limited community engagement and indicated the need for consumer advocacy and influencer recruitment. The linking of theoretical constructs underlying health behaviors to COVID-19-related social media interactions through semantic and syntactic features using our computational models has revealed frequent interaction typologies in factual and misleading COVID-19 posts and indicated significant differences in network metrics such as degree. The performance of our deep learning classifiers was reasonable, with an F-measure of 0.80 for speech acts and 0.81 for behavior constructs. Our study highlights the strengths of community-based field studies and emphasizes the utility of large-scale social media data sets in enabling rapid intervention tailoring to adapt grassroots community interventions to thwart misinformation seeding and spread among minority communities. Implications for consumer advocacy, data governance, and industry incentives are discussed for the sustainable role of social media solutions in public health.

Social Media as a Conduit for Spreading Misinformation: An Examination of Antivaccination Messages in the Wake of the 2019 Washington Measles Outbreak

Public health experts have studied global pandemics long before the COVID-19 outbreak of 2020. Since the worldwide spread of HIV, SARS, H1N1, and Ebola among others, scholars have focused on identifying best practices for risk mitigation and reaching disparate publics to engage in appropriate risk mitigation behaviors. The 2019 measles outbreak in Washington, USA flourished in large part due to the viral spread of misinformation on social networking platforms. Due to the intended openness of these platforms, antivaccination messaging became prominent, and the U.S. among other countries to have eradicated measles saw a number of outbreaks. In the U.S. in 2019, many of these occurred in Washington state. These outbreaks served as an impetus for social media platforms to reconsider their role in spreading health misinformation and its contribution to real-world danger. This analysis considers open media ethics to understand social media platforms’ initial decisions to allow vaccine misinformation and the role of communication scholars and practitioners have in understanding, and acting on misinformation. Using a case study approach, this article examines online discourse about the measles, mumps, and rubella vaccine, policy measures related to vaccine exemption, and social media organization formal responses in 2019 directly related to the increase in U.S. measles outbreaks. Using an open media ethics framework, findings from this study illustrate the ways in which these organizations initially intended to have an open platform for health-related discussions. Further analysis demonstrates that these organizations focused on existing terms of use to put in place protective measures that would prevent the further spread of this mis- and disinformation. However, conclusions drawn illustrate that placing the onus on social media organizations alone is insufficient to prevent outbreaks such as this to occur, and as the COVID-19 pandemic began the following year, the implications of this study continue to pose questions about social media misinformation management. Keywords: media ethics; misinformation; social networks; user-generated content; vaccine hesitancy

Assessing the Validity of Health Messages Used by the Saudi Public in WhatsApp.

WhatsApp is the most frequently used social media platform in Saudi Arabia. Inaccurate information could negatively impact public health. The number of studies worldwide investigating health-related misinformation in social media increased steadily, with limited data from Arabic-speaking communities. This study aimed to estimate the validity and safety of Arabic-language health information messages circulated on WhatsApp and identify the different categories of these messages based on their credibility. A descriptive, analytical cross-sectional study was conducted from February to April 2021. A total of 374 students were randomly selected from the common first preparatory year college at King Saud University in Riyadh, Saudi Arabia, and participated by sharing up to three health-related WhatsApp messages per student that they or their relatives had recently read. Four board-certified physicians reviewed and classified the messages based on their credibility and sources. 282 students provided 326 messages (1.2 messages per student). Most messages (86%) had either invalid or inaccurate content, and 83.7% came from unknown sources. Only 26 messages (8%) of the total were written by trusted scientific sources. Most of the messages from unknown sources or unqualified persons were either invalid or invalid, with potential health risks for the public, and the difference from trusted sources was statistically significant. This study showed a high percentage of inaccurate and invalid health-related messages on WhatsApp. Invalid messages with potential health risks were authored mostly by unknown sources or unqualified persons. Most health messages written by trusted authorities and qualified persons were valid. Trusted scientific authorities should thus be more active in public education on social media platforms. They should advise their communities on how to discern the validity of such messages. More efforts are needed to guide patients from where to obtain accurate and valid health information.

Extending the Norm Activation Model and Unpacking Laypeople's Social Media Misinformation Correction Process: The Multilayered Roles of Misinformation Awareness, Personal Norms, and Efficacy

Extending the Norm Activation Model and Unpacking Laypeople's Social Media Misinformation Correction Process: The Multilayered Roles of Misinformation Awareness, Personal Norms, and Efficacy

What Happened to Ethiopian Youth during the Covid-19 Pandemic?

Abstract The purpose of this qualitative study was to investigate Ethiopian urban youth’s changing risk beliefs, contributing factors, and global south lessons in relation to the COVID-19 pandemic. Researchers conducted in-depth interviews and focus group discussions with urban youth in Ethiopia’s East-Gojjam district. The findings revealed three major stages in the youth’s risk perception: the high perceived risk stage associated with early pandemic outbreaks, the steady decline stage associated with economic stress that outweighed perceived health risk, and the zero risk stage when all safety measures appear to have been completely abandoned. The government’s self-contradictory rhetoric and practice, the contradiction between religious teachings and scientific messages, and misinformation in social media are factors for the evolved risk beliefs. A major lesson from the global south is the active participation of key stakeholders in bridging the gap between government and society.

Intention of health experts to counter health misinformation in social media: Effects of perceived threat to online users, correction efficacy, and self-affirmation.

Our study analyzes the intention of Chinese health experts (health professionals and medical students) to correct health misinformation in social media. In an experimental 2 × 2 × 2 between-subjects factorial design (n = 415), we manipulated the experts' perception of the threat that health misinformation poses for online users, their self-efficacy with respect to correcting misinformation, and their self-affirmation. To select the potential influence factors, we draw on self-affirmation theory and the extended parallel process model. Results of our experiment revealed that correction intention increases if experts perceive the threat for online users as severe, believe that they are capable of countering the impact of misinformation, and have a high motivation to maintain a positive self-image of caring for others. We discuss the consequences of our findings for motivating experts to help reduce the adverse effects of health misinformation in social media.