Development and Validation of a Questionnaire to Assess Knowledge, Attitudes, and Practices (KAP) Regarding Health Misinformation on Social Media Among the Malaysian General Public

Social media is widely used by the general public as a source of health information because of its convenience. However, the increasing prevalence of health misinformation on social media is becoming a serious concern, and it remains unclear how the general public identifies and responds to it. This study aims to explore the approaches used by the general public for identifying and responding to health misinformation on social media. Semistructured interviews were conducted with 22 respondents from the Malaysian general public. The theory of motivated information management was used as a guiding framework for conducting the interviews. Audio-taped interviews were transcribed verbatim and imported into ATLAS.ti software for analysis. Themes were identified from the qualitative data using a thematic analysis method. The 3 main themes identified were emotional responses and impacts of health misinformation, approaches used to identify health misinformation, and responses to health misinformation. The spread of health misinformation through social media platforms has caused uncertainty and triggered a range of emotional responses, including anxiety and feelings of vulnerability, among respondents who encountered it. The approaches to identifying health misinformation on social media included examining message characteristics and sources. Messages were deemed to be misinformation if they contradicted credible sources or exhibited illogical and exaggerated content. Respondents described multiple response approaches to health misinformation based on the situation. Verification was chosen if the information was deemed important, while misinformation was often ignored to avoid conflict. Respondents were compelled to take action if misinformation affected their family members, had been corrected by others, or if they were knowledgeable about the topic. Taking action involved correcting the misinformation and reporting the misinformation to relevant social media, enforcement authorities, and government bodies. This study highlights the factors and motivations influencing the general public's identification and response to health misinformation on social media. Addressing the challenges of health misinformation identified in this study requires collaborative efforts from all stakeholders to reduce the spread of health misinformation and reduce the general public's belief in it.

Health misinformation on social media has become a pressing public health challenge, particularly among individuals with low digital health literacy. This study examines the relationship between digital health literacy and the spread of misinformation, analyzing systemic factors that contribute to the persistence of misleading health content. A systematic literature review was conducted using academic databases such as PubMed, Scopus, and Google Scholar, with a focus on peer-reviewed studies published in the past decade. The review identifies key demographic, social, and economic determinants influencing digital health literacy and explores the role of social media platforms in misinformation dissemination. Findings reveal that individuals with limited digital health literacy struggle to critically evaluate health-related content, making them more vulnerable to misinformation. Systemic factors, including weak regulatory oversight and social media algorithms prioritizing engagement-driven content, further facilitate the spread of misleading health information. Effective interventions, such as digital literacy education, peer-led initiatives, and collaboration between social media platforms and public health organizations, are crucial in mitigating misinformation. The study highlights the need for targeted policy reforms, improved algorithmic transparency, and community-based health education to enhance digital health literacy and misinformation resilience. Future research should focus on the long-term efficacy of digital health literacy interventions and explore AI-driven solutions for misinformation detection.

BackgroundAlthough at present there is broad agreement among researchers, health professionals, and policy makers on the need to control and combat health misinformation, the magnitude of this problem is still unknown. Consequently, it is fundamental to discover both the most prevalent health topics and the social media platforms from which these topics are initially framed and subsequently disseminated.ObjectiveThis systematic review aimed to identify the main health misinformation topics and their prevalence on different social media platforms, focusing on methodological quality and the diverse solutions that are being implemented to address this public health concern.MethodsWe searched PubMed, MEDLINE, Scopus, and Web of Science for articles published in English before March 2019, with a focus on the study of health misinformation in social media. We defined health misinformation as a health-related claim that is based on anecdotal evidence, false, or misleading owing to the lack of existing scientific knowledge. We included (1) articles that focused on health misinformation in social media, including those in which the authors discussed the consequences or purposes of health misinformation and (2) studies that described empirical findings regarding the measurement of health misinformation on these platforms.ResultsA total of 69 studies were identified as eligible, and they covered a wide range of health topics and social media platforms. The topics were articulated around the following six principal categories: vaccines (32%), drugs or smoking (22%), noncommunicable diseases (19%), pandemics (10%), eating disorders (9%), and medical treatments (7%). Studies were mainly based on the following five methodological approaches: social network analysis (28%), evaluating content (26%), evaluating quality (24%), content/text analysis (16%), and sentiment analysis (6%). Health misinformation was most prevalent in studies related to smoking products and drugs such as opioids and marijuana. Posts with misinformation reached 87% in some studies. Health misinformation about vaccines was also very common (43%), with the human papilloma virus vaccine being the most affected. Health misinformation related to diets or pro–eating disorder arguments were moderate in comparison to the aforementioned topics (36%). Studies focused on diseases (ie, noncommunicable diseases and pandemics) also reported moderate misinformation rates (40%), especially in the case of cancer. Finally, the lowest levels of health misinformation were related to medical treatments (30%).ConclusionsThe prevalence of health misinformation was the highest on Twitter and on issues related to smoking products and drugs. However, misinformation on major public health issues, such as vaccines and diseases, was also high. Our study offers a comprehensive characterization of the dominant health misinformation topics and a comprehensive description of their prevalence on different social media platforms, which can guide future studies and help in the development of evidence-based digital policy action plans.

Background Health misinformation disseminated on social media detrimentally affects the public's reactions toward public health measures. This has led to costly and harmful public health crises. Due to a lack of a comprehensive expert system that collects and analyzes large volumes of social media data, public health officials are incapable of mitigating health misinformation trends online. This study aimed to remedy this by designing and developing a big data pipeline and ecosystem (Health Misinformation Analysis System (HMAS)) capable of identifying and analyzing health misinformation online. Methods The HMAS system relies on Python, Elastic Stack, and the Twitter V2 API as the main technologies forming the backbone of the system. It comprises of five main components: (1) Data Extraction Framework (DEF); (2) Latent Dirichlet Allocation Topic Model; (3) Sentiment Analyzer; (4) Misinformation Classifier; (5) Elastic Cloud Deployment. Components 1-4 are hosted on a virtual machine with low computing and memory requirements. Through the DEF, HMAS extracts data from the Twitter V2 API. The HMAS expert system uses pre-trained models to perform automatic health misinformation analysis. The analyzed data are loaded and visualized in Elastic Cloud through dashboards and analytics. Results The HMAS system performance is accurate and efficient. It has been successfully utilized by independent investigators to extract significant insights, including a fluoride-related health misinformation use case, which analyzed data from 2015 to 2021. Moreover, HMAS has been applied to a vaccine hesitancy use case (2007-2022) and a heat-related illnesses use case (2011-2022). Conclusions The novel HMAS expert system can potentially aid public health officials globally to detect and analyze concerning trends in health misinformation online. This system can also grow to integrate social media data from several platforms for multiplatform analysis and support non-Western language content. Key messages • The novel HMAS pipeline can collect, detect, and analyze the rapidly increasing amounts of misinformation proliferating on social media related to a particular topic or set of related topics. • Identifying and monitoring health misinformation trends prevalent on social media through analytics dashboards and anomaly/risk detection alerts can lead to prompt governmental intervention.

PurposeThe proliferation of health misinformation on social media has increasingly engaged scholarly interest. This research examines the determinants influencing users’ proactive correction of health misinformation, a crucial strategy in combatting health misbeliefs. Grounded in the elaboration likelihood model (ELM), this research investigates how factors including issue involvement, information literacy and active social media use impact health misinformation recognition and intention to correct it.Design/methodology/approachA total of 413 social media users finished a national online questionnaire. SPSS 26.0, AMOS 21.0 and PROCESS Macro 4.1 were used to address the research hypotheses and questions.FindingsResults indicated that issue involvement and information literacy both contribute to health misinformation correction intention (HMCI), while misinformation recognition acts as a mediator between information literacy and HMCI. Moreover, active social media use moderated the influence of information literacy on HMCI.Originality/valueThis study not only extends the ELM into the research domain of correcting health misinformation on social media but also enriches the perspective of individual fact-checking intention research by incorporating dimensions of users’ motivation, capability and behavioral patterns.Peer reviewThe peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-09-2023-0505

Health misinformation on social media can negatively affect knowledge, attitudes, and behaviors, undermining clinical care and public health efforts. Therefore, it is vital to better understand the public's experience with health misinformation on social media. The goal of this analysis was to examine perceptions of the social media information environment and identify associations between health misinformation perceptions and health communication behaviors among US adults. Analyses used data from the 2022 Health Information National Trends Survey (N=6252). Weighted unadjusted proportions described respondents' perceptions of the amount of false or misleading health information on social media ("perceived misinformation amount") and how difficult it is to discern true from false information on social media ("perceived discernment difficulty"). Weighted multivariable logistic regressions examined (1) associations of sociodemographic characteristics and subjective literacy measures with misinformation perceptions and (2) relationships between misinformation perceptions and health communication behaviors (ie, sharing personal or general health information on social media and using social media information in health decisions or in discussions with health care providers). Over one-third of social media users (35.61%) perceived high levels of health misinformation, and approximately two-thirds (66.56%) reported high perceived discernment difficulty. Odds of perceiving high amounts of misinformation were lower among non-Hispanic Black/African American (adjusted odds ratio [aOR] 0.407, 95% CI 0.282-0.587) and Hispanic (aOR 0.610, 95% CI 0.449-0.831) individuals compared to White individuals. Those with lower subjective health literacy were less likely to report high perceived misinformation amount (aOR 0.602, 95% CI 0.374-0.970), whereas those with lower subjective digital literacy were more likely to report high perceived misinformation amount (aOR 1.775, 95% CI 1.400-2.251). Compared to White individuals, Hispanic individuals had lower odds of reporting high discernment difficulty (aOR 0.620, 95% CI 0.462-0.831). Those with lower subjective digital literacy (aOR 1.873, 95% CI 1.478-2.374) or numeracy (aOR 1.465, 95% CI 1.047-2.049) were more likely to report high discernment difficulty. High perceived misinformation amount was associated with lower odds of sharing general health information on social media (aOR 0.742, 95% CI 0.568-0.968), using social media information to make health decisions (aOR 0.273, 95% CI 0.156-0.479), and using social media information in discussions with health care providers (aOR 0.460, 95% CI 0.323-0.655). High perceived discernment difficulty was associated with higher odds of using social media information in health decisions (aOR 1.724, 95% CI 1.208-2.460) and health care provider discussions (aOR 1.389, 95% CI 1.035-1.864). Perceptions of high health misinformation prevalence and discernment difficulty are widespread among social media users, and each has unique associations with sociodemographic characteristics, literacy, and health communication behaviors. These insights can help inform future health communication interventions.

BackgroundThe use of social media platforms to seek information continues to increase. Social media platforms can be used to disseminate important information to people worldwide instantaneously. However, their viral nature also makes it easy to share misinformation, disinformation, unverified information, and fake news. The unprecedented reliance on social media platforms to seek information during the COVID-19 pandemic was accompanied by increased incidents of misinformation and disinformation. Consequently, there was an increase in the number of scientific publications related to the role of social media in disseminating health misinformation and disinformation at the height of the COVID-19 pandemic. Health misinformation and disinformation, especially in periods of global public health disasters, can lead to the erosion of trust in policy makers at best and fatal consequences at worst.ObjectiveThis paper reports a bibliometric analysis aimed at investigating the evolution of research publications related to the role of social media as a driver of health misinformation and disinformation since the start of the COVID-19 pandemic. Additionally, this study aimed to identify the top trending keywords, niche topics, authors, and publishers for publishing papers related to the current research, as well as the global collaboration between authors on topics related to the role of social media in health misinformation and disinformation since the start of the COVID-19 pandemic.MethodsThe Scopus database was accessed on June 8, 2023, using a combination of Medical Subject Heading and author-defined terms to create the following search phrases that targeted the title, abstract, and keyword fields: (“Health*” OR “Medical”) AND (“Misinformation” OR “Disinformation” OR “Fake News”) AND (“Social media” OR “Twitter” OR “Facebook” OR “YouTube” OR “WhatsApp” OR “Instagram” OR “TikTok”) AND (“Pandemic*” OR “Corona*” OR “Covid*”). A total of 943 research papers published between 2020 and June 2023 were analyzed using Microsoft Excel (Microsoft Corporation), VOSviewer (Centre for Science and Technology Studies, Leiden University), and the Biblioshiny package in Bibliometrix (K-Synth Srl) for RStudio (Posit, PBC).ResultsThe highest number of publications was from 2022 (387/943, 41%). Most publications (725/943, 76.9%) were articles. JMIR published the most research papers (54/943, 5.7%). Authors from the United States collaborated the most, with 311 coauthored research papers. The keywords “Covid-19,” “social media,” and “misinformation” were the top 3 trending keywords, whereas “learning systems,” “learning models,” and “learning algorithms” were revealed as the niche topics on the role of social media in health misinformation and disinformation during the COVID-19 outbreak.ConclusionsCollaborations between authors can increase their productivity and citation counts. Niche topics such as “learning systems,” “learning models,” and “learning algorithms” could be exploited by researchers in future studies to analyze the influence of social media on health misinformation and disinformation during periods of global public health emergencies.

Explaining the spread and impact of health misinformation has garnered considerable attention with the uptake of social media and group messaging applications. This study contributes to that line of work by investigating how reliance on multiple digital media may help support or suppress misinformation belief, and how individual differences in misinformation susceptibility condition this process. Alternative health outlets (AH media), advocating home/homeopathic remedies over conventional medicine can be important sources of misinformation, yet are largely ignored previously. In this study, we first test how reliance on different platforms predicts health misinformation belief. Drawing from the elaboration likelihood model, we further investigate how need for cognition (NFC) and faith in intuition (FI) moderate the relationship between news reliance and susceptibility to misinformation. We conducted a survey in Singapore, Turkey, and the U.S (N = 3,664) to measure how these proposed relationships explain misinformed beliefs about vaccines, genetically modified foods and alternative medicine. We found reliance on online legacy news was negatively associated with the likelihood of believing health misinformation, while the reverse was true for social media and AH media. Additionally, those with both greater NFC and FI were more susceptible to health misinformation when they relied on social media and AH media more. In contrast, neither NFC nor FI moderated the relationship between reliance on online legacy news and health misinformation belief. These findings, mostly consistent across countries, also show that extensive reliance on social media and AH media for news mostly overwhelms the individual differences in predicting misinformation belief.

During the COVID-19 pandemic, US Latino individuals were more likely to report accessing coronavirus information on social media than other groups, despite copious amounts of health misinformation documented on these platforms. Among the existing literature on factors associated with engagement and use of health information, racial minority status has been associated with greater susceptibility to health misinformation. However, literature to date has not reported national trends on how Latino individuals engage with or use health information on social media compared to non-Latino White (NLW) individuals, nor whether perceptions of the amount of health misinformation on social media influence health information engagement and usage. This study aimed to examine differences in engagement with and use of health information on social media among Latino and NLW individuals in the United States. We examined a nationally representative cross-sectional sample of Latino (n=827) and NLW (n=2563) respondents of the 2022 Health Information National Trends Survey who used social media in 2022 to assess differences in engagement with and use of health information. Items related to the perceived quantity of health misinformation on social media, social media use frequency, health information engagement (sharing content; watching videos), and health information usage (health decision-making; discussions with health care providers) were selected to conduct weighted bivariate analyses and logistic regressions. Latino individuals perceive lower amounts of health misinformation on social media (28.9% perceived little to no misinformation vs 13.6% NLW individuals, P<.001). Latino audiences also reported higher health information engagement compared to NLW individuals (20% vs 10.2% shared information several times a month or more, P<.001; 42.4% vs 27.2% watched videos several times a month or more, P<.001), as well as higher information usage for health decision-making (22.8% vs 13.7%, P=.003). When controlling for ethnicity and other sociodemographic variables, perceiving lower amounts of health misinformation on social media was associated with higher odds of watching videos more frequently, making health decisions, and discussing health-related content with a health care provider (P<.001). Furthermore, Latino audiences were 1.85 times more likely to watch videos (P<.001), when controlling for the perceived amount of health misinformation and other sociodemographic variables. Finally, when compared to NLW individuals perceiving little to no health misinformation, Latino audiences perceiving little to no health misinformation were 2.91 times more likely to watch videos (P<.001). The findings suggest that Latino individuals engage with visual health (mis)information at higher rates. Digital health literacy interventions should consider video formats and preferred social media platforms among Latino individuals. Further research is warranted to understand sociocultural factors important to Latino social media users when consuming health information, as these may impact the success of digital media literacy interventions that teach users how to navigate misinformation online.

This scoping review accompanies our research study "The Experience of Health Professionals With Misinformation and Its Impact on Their Job Practice: Qualitative Interview Study." It surveys online health misinformation and is intended to provide an understanding of the communication context in which health professionals must operate. Our objective was to illustrate the impact of social media in introducing additional sources of misinformation that impact health practitioners' ability to communicate effectively with their patients. In addition, we considered how the level of knowledge of practitioners mitigated the effect of misinformation and additional stress factors associated with dealing with outbreaks, such as the COVID-19 pandemic, that affect communication with patients. This study used a 5-step scoping review methodology following Arksey and O'Malley's methodology to map relevant literature published in English between January 2012 and March 2024, focusing on health misinformation on social media platforms. We defined health misinformation as a false or misleading health-related claim that is not based on valid evidence or scientific knowledge. Electronic searches were performed on PubMed, Scopus, Web of Science, and Google Scholar. We included studies on the extent and impact of health misinformation in social media, mitigation strategies, and health practitioners' experiences of confronting health misinformation. Our independent reviewers identified relevant articles for data extraction. Our review synthesized findings from 70 sources on online health misinformation. It revealed a consensus regarding the significant problem of health misinformation disseminated on social network platforms. While users seek trustworthy sources of health information, they often lack adequate health and digital literacies, which is exacerbated by social and economic inequalities. Cultural contexts influence the reception of such misinformation, and health practitioners may be vulnerable, too. The effectiveness of online mitigation strategies like user correction and automatic detection are complicated by malicious actors and politicization. The role of health practitioners in this context is a challenging one. Although they are still best placed to combat health misinformation, this review identified stressors that create barriers to their abilities to do this well. Investment in health information management at local and global levels could enhance their capacity for effective communication with patients. This scoping review underscores the significance of addressing online health misinformation, particularly in the postpandemic era. It highlights the necessity for a collaborative global interdisciplinary effort to ensure equitable access to accurate health information, thereby empowering health practitioners to effectively combat the impact of online health misinformation. Academic research will need to be disseminated into the public domain in a way that is accessible to the public. Without equipping populations with health and digital literacies, the prevalence of online health misinformation will continue to pose a threat to global public health efforts.

RationaleThe escalating dissemination of health misinformation on social media platforms poses a significant threat to users' well-being. It is imperative to identify the types of health misinformation that are more susceptible to widespread dissemination and to explore strategies to curb its spread. MethodThis study designed a 2 (emotional appeal type: positive vs. negative) × 2 (fabricated source type: pseudo-common vs. pseudo-authoritative) × 2 (accuracy-nudge label: No vs. Yes) online between-subjects experiment controlling for factors such as e-health literacy, prior sharing experience, and personal involvement. A snowball sampling approach was used to recruit 1952 participants through social media, resulting in a final sample of 1393 valid responses. ResultsCompared to positive emotional appeal and pseudo-common sources, negative emotional appeal and pseudo-authoritative sources resulted in higher levels of sharing intention. Under the condition of negative emotional appeal, the promotion effect of pseudo-authoritative sources on sharing intention was intensified. The accuracy-nudge intervention could significantly mitigate this tendency. The underlying mechanisms revealed more details: both negative emotional appeals and pseudo-authoritative sources increased the perceived credibility of health misinformation, thereby increasing users' sharing intention. However, in contrast to pseudo-authoritative sources, excessive negative emotional appeal induced vigilant verification behavior among users, which reduced sharing to some extent. Adding an accuracy-nudge label to health misinformation reduced users' misguided trust in health misinformation features and stimulated information verification, ultimately reducing health misinformation sharing intention. ConclusionsNegative emotional appeal and pseudo-authoritative sources can enhance the perceived credibility of health misinformation, thereby strengthening the sharing intention of social media users. Therefore, health misinformation with negative emotional appeal and pseudo-authoritative sources is more likely to be widely shared. The accuracy nudge intervention can trigger users' information verification behavior, suppress the persuasive effects of the misinformation features mentioned above, and help prevent the spread of health misinformation on social media.

As digital technologies reshape how faith communities communicate and operate, religious leaders extend their influence into online spaces where spiritual and health-related beliefs converge. This study is the first to investigate health discourse and misinformation on KingsChat, the social networking platform of the Christ Embassy megachurch in Nigeria led by Pastor Chris Oyakhilome, a known source of COVID-19 conspiracy theories and health misinformation. By scraping public KingsChat posts matching selected health search terms in addition to any posts from individuals in Christ Embassy church leadership, a dataset of 12,443 posts was collected. Keyword analysis identified various health discourse patterns, particularly around misinformation concerning COVID-19, vaccines, faith healing and malaria. To better understand health-related content in these posts, a random sample of posts containing health terms was manually coded. This found that 35% of health-related posts contained a debunked or unsubstantiated health-related claim. The largest two categories of misinformation involved faith healing and conspiratorial narratives about vaccines. Additional investigation of the external URLs linked to from KingsChat posts also exposes cross-platform interactions in the way the church distributes and amplifies health messages across digital spaces. These findings underscore challenges facing public health officials working with communities where Christ Embassy church is influential. Understanding the interplay of digital media ecosystems, as well as the motivations and strategies for spreading health information online, will help researchers propose effective interventions and public health measures while respecting community norms.

PurposeThe purpose of this paper is to explore the features of health misinformation on social media sites (SMSs). The primary goal of the study is to investigate the salient features of health misinformation and to develop a tool of features to help users and social media companies identify health misinformation.Design/methodology/approachEmpirical data include 1,168 pieces of health information that were collected from WeChat, a dominant SMS in China, and the obtained data were analyzed through a process of open coding, axial coding and selective coding. Then chi-square test and analysis of variance (ANOVA) were adopted to identify salient features of health misinformation.FindingsThe findings show that the features of health misinformation on SMSs involve surface features, semantic features and source features, and there are significant differences in the features of health misinformation between different topics. In addition, the list of features was developed to identify health misinformation on SMSs.Practical implicationsThis study raises awareness of the key features of health misinformation on SMSs. It develops a list of features to help users distinguish health misinformation as well as help social media companies filter health misinformation.Originality/valueTheoretically, this study contributes to the academic discourse on health misinformation on SMSs by exploring the features of health misinformation. Methodologically, the paper serves to enrich the literature around health misinformation and SMSs that have hitherto mostly drawn data from health websites.

BackgroundSocial media platforms have transformed the dissemination of health information, allowing for rapid and widespread sharing of content. However, alongside valuable medical knowledge, these platforms have also become channels for the spread of health misinformation, including false claims and misleading advice, which can lead to significant public health risks. Susceptibility to health misinformation varies and is influenced by individuals’ cultural, social, and personal backgrounds, further complicating efforts to combat its spread.ObjectiveThis study aimed to examine the extent to which individuals report encountering health-related misinformation on social media and to assess how racial, ethnic, and sociodemographic factors influence susceptibility to such misinformation.MethodsData from the Health Information National Trends Survey (HINTS; Cycle 6), conducted by the National Cancer Institute with 5041 US adults between March and November 2022, was used to explore associations between racial and sociodemographic factors (age, gender, race/ethnicity, annual household income, marital status, and location) and susceptibility variables, including encounters with misleading health information on social media, difficulty in assessing information truthfulness, discussions with health providers, and making health decisions based on such information.ResultsOver 35.61% (1740/4959) of respondents reported encountering “a lot” of misleading health information on social media, with an additional 45% (2256/4959) reporting seeing “some” amount of health misinformation. Racial disparities were evident in comparison with Whites, with non-Hispanic Black (odds ratio [OR] 0.45, 95% CI 0.33-0.6, P<.01) and Hispanic (OR 0.54, 95% CI 0.41-0.71, P<.01) individuals reporting lower odds of finding deceptive information, while Hispanic (OR 1.68, 95% CI 1.48-1.98, P<.05) and non-Hispanic Asian (OR 1.96, 95% CI 1.21-3.18, P<.01) individuals exhibited higher odds in having difficulties in assessing the veracity of health information found on social media. Hispanic and Asian individuals were more likely to discuss with providers and make health decisions based on social media information. Older adults aged ≥75 years exhibited challenges in assessing health information on social media (OR 0.63, 95% CI 0.43-0.93, P<.01), while younger adults (18-34) showed increased vulnerability to health misinformation. In addition, income levels were linked to higher exposure to health misinformation on social media: individuals with annual household incomes between US $50,000 and US $75,000 (OR 1.74, 95% CI 1.14-2.68, P<.01), and greater than US $75,000 (OR 1.78, 95% CI 1.20-2.66, P<.01) exhibited greater odds, revealing complexities in decision-making and information access.ConclusionsThis study highlights the pervasive presence of health misinformation on social media, revealing vulnerabilities across racial, age, and income groups, underscoring the need for tailored interventions.

BackgroundIndoor ultraviolet (UV) tanning is common and consequential, increasing the risk for cancers including melanoma and basal cell carcinoma. At-risk groups include adolescents and young adults, who often report beliefs about benefits of tanning. Adolescent and young adults are also among the most ubiquitous social media users. As previous studies support that content about tanning is common on social media, this may be a way that young women are exposed to influential content promoting tanning, including health misinformation.ObjectiveThe purpose of this study was to evaluate health misinformation promoted by indoor tanning businesses via social media and to understand young women’s perceptions of this misinformation.MethodsThis mixed methods study included (1) retrospective observational content analysis of indoor tanning salons’ content on Facebook over 1 year and (2) qualitative interviews with a purposeful national sample of 46 White non-Hispanic women, age 16 to 23 years, who had recently tanned indoors. We assessed experiences with tanning businesses’ posted content on social media through interviews. We used the constant comparative approach for qualitative analyses.ResultsContent analysis findings included data from indoor tanning businesses (n=147) across 50 states, yielding 4956 total posts. Among 9 health misinformation topics identified, the most common was the promotion of UV tanning as a safe way to get Vitamin D (n=73, 1.5%). An example post was “Stop by Body and Sol to get your daily dose of Vitamin D.” Another misinformation topic was promoting tanning for health benefits (n=31, 0.62%), an example post was “the flu is not a season, it’s an inability to adapt due to decreased sun exposure…” A total of 46 participants completed interviews (age: mean 20 years, SD 2). Almost all participants (45/46, 98%) used Facebook, and 43.5% (20/46) followed an indoor tanning business on social media. Approximately half of participants reported seeing social media posts from tanning salons about Vitamin D, an example of a participant comment was “I have [seen that] a few times...” Among the participants, approximately half believed it was safe to get Vitamin D from indoor UV tanning; a participant stated: “I think it is a valid benefit to UV tanning.”ConclusionsDespite the low frequency (range 0.5%-1.5%) of social media posts promoting health misinformation, participants commonly reported viewing these posts, and their perceptions aligned with health misinformation. Health education campaigns, possibly using social media to target at-risk populations, may be an innovative approach for tanning prevention messages.