Misleading Information Research Articles

Using A Google Web Search Analysis to Assess the Utility of ChatGPT in Stem Cell Therapy.

Since its introduction, the use of ChatGPT has increased significantly for medically related purposes. However, current research has not captured its applications in providing information on stem cell therapy. To address this gap, the present study compared the effectiveness of ChatGPT to Google in answering medical questions related to stem cell therapy. The search term "stem cell therapy" was used to perform a Google web search, and the top 20 frequently asked questions along with answers were recorded together with relevant website sources. Of these questions, the top 10 questions were separately entered into ChatGPT, and the answers and the sources were recorded. Then, the following statement was entered into ChatGPT: "Do a Google search with the search term 'stem cell therapy' and record 20 common questions related to the search term." After obtaining these questions, each question was separately entered into ChatGPT for an answer and source. A majority of the top 20 questions provided by Google were related to fact, whereas a majority of the questions provided by ChatGPT were related to policy. The answer sources used by Google were mostly drawn from medical practice, while those used by ChatGPT were mostly drawn from academic information. Compared to Google, ChatGPT exhibits stronger capabilities in promoting awareness of stem cell therapy. ChatGPT has the ability to eliminate misleading information by providing accurate and reliable answers. However, the responses provided by ChatGPT are still general in nature and cannot substitute academic sources for providing specialized knowledge.

Combating the COVID-19 infodemic using Prompt-Based curriculum learning.

The COVID-19 pandemic has been accompanied by a proliferation of online misinformation and disinformation about the virus. Combating this 'infodemic' has been identified as one of the top priorities of the World Health Organization, because false and misleading information can lead to a range of negative consequences, including the spread of false remedies, conspiracy theories, and xenophobia. This paper aims to combat the COVID-19 infodemic on multiple fronts, including determining the credibility of information, identifying its potential harm to society, and the necessity of intervention by relevant organizations. We present a prompt-based curriculum learning method to achieve this goal. The proposed method could overcome the challenges of data sparsity and class imbalance issues. Using online social media texts as input, the proposed model can verify content from multiple perspectives by answering a series of questions concerning the text's reliability. Experiments revealed the effectiveness of prompt tuning and curriculum learning in assessing the reliability of COVID-19-related text. The proposed method outperforms typical text classification methods, including fastText and BERT. In addition, the proposed method is robust to the hyperparameter settings, making it more applicable with limited infrastructure resources.

A survey on deepfake video detection datasets

Deepfake video has usefulness in entertainment and multimedia technology, however, the danger of deepfake is significant to the social, economical, and political sectors so far. Specifically, to diverge any public opinion by generating fake news and spreading misleading information, national security may be under risk due to misrepresenting statements given by political leaders. The creation of such manipulated videos are getting easier day by day and at the same time it is necessary to detect and prevent them. In order to do that, researchers are creating challenging fake video databases for artificial intelligence (AI) based detection models to contribute to the research. This paper reviewed the existing deepfake video detection datasets available online and used in the previous research articles. We analyzed the literature from two different perspectives, datasets and detection models. The goal of this study is to introduce all publicly available datasets in this field including the discussion of techniques used to generate the data. In addition to our contribution, we showed a result comparison among different deepfake datasets and discussed the findings.

Leveraging a Peer-to-Peer Approach to Mitigate Vaccine Misinformation and Improve Vaccine Communication During a Pandemic: Experiences From the Development of a Massive Open Online Course.

The COVID-19 pandemic has not only led to massive global mortality and morbidity, but it has also fueled an infodemic of false and misleading information about COVID-19 and vaccines. The spread of misinformation and disinformation on vaccine safety and efficacy has contributed to vaccine hesitancy and distrust of public health institutions and has undermined the public health response to the COVID-19 pandemic. Because communication plays a monumental role in pandemic preparedness, a promising approach to countering the COVID-19 infodemic is empowering peers to serve as trusted messengers to provide accurate information using evidence-based communication approaches. With this in mind, we developed a massive open online course (MOOC) to provide the general public with the knowledge, skills, and resources to effectively navigate potentially contentious vaccine conversations with their peers, with a specific focus on parents. Within the first year of the course launch, 29,000 people had enrolled. Learners appreciated the information related to vaccine development, communication tips and techniques, and identifying and responding to vaccine misinformation. Over 1,000 learners who completed the course participated in an online evaluation survey. To address public distrust in healthcare providers, government, and science, our survey results indicate that peer-to-peer approaches to addressing vaccine hesitancy can empower community members to educate others and promote vaccine acceptance at scale.

Sustainability Disclosure in The Malaysian Construction Sector: The Effect of Community and Media Legitimacies

"Research Aims: The objective of the study is to examine the effects of stakeholder pressure on sustainability disclosure (SD). The study includes the effect of community on SD when the company considers the media as one of the legitimate stakeholders. Design/Methodology/Approach: Stakeholder legitimacy is evaluated using SD via content analysis based on panel data samples from the construction and property sectors. Research Findings: It was found that legitimacy is an antecedent and has a positive relationship with SD. Furthermore, this relationship between community legitimacy and SD is stronger when mediated by media legitimacy. Theoretical Contribution/Originality: This study shows the effects of the legitimacy attribute on SD instead of the influence of stakeholders in general (regardless of the legitimacy concept) and the incremental value for companies to include the interest of the media in SD apart from the communities alone. Managerial Implications in the South East Asian Context: It guides managers in forming a comprehensive stakeholder engagement plan and budget to increase company value. This illustrates to the managers the motivation behind making disclosures about the media in the SD more so in this rapid social media where fake and misleading information threatens the public trust in Southeast Asia. Research Limitations & Implications: The study does not include power and urgency factors along with legitimacy. Keywords: Stakeholder Legitimacy, Stakeholder Salience Theory, Stakeholder Theory, Sustainability Disclosure, Construction, Endogeneity"

Measuring the quality of YouTube videos on anxiety: a study using the global quality scale and discern tool

Anxiety is a persistent feeling of fear. The onset usually starts in childhood and can have adverse effects in adolescence. In the past, the public used to seek medical advice from professionals. In the modern era, free video-sharing platforms like YouTube have gained popularity among the masses. It has been observed that the public consults medical information from these videos. Therefore, it has become necessary for medical experts to assess the quality of these videos and prevent misinformation. On 15 August 2022, a YouTube search was done on treating and managing anxiety. 75 videos were selected according to inclusion criteria. The videos were divided into two categories: useful and misleading. The global quality scale (GQS) and DISCERN tool were used to review and assess these videos independently. Out of 169 videos analyzed, 137 had useful information and 32 had misleading information content. Useful content videos had a higher number of DISCERN and GQS than misleading content videos. The analysis showed that physician-based 51 videos have useful information. It was also observed that useful videos had more likes and views. Therefore, medical professionals should be encouraged to make medical education and awareness videos because physician-based videos seem to have the highest credibility and popularity among the general public.

Obesity of Information Covid-19 Children Vaccine and Parents Digital Literacy Ability

This study aims to obtain data related to the “tabbayun” attitude of parents in understanding digital literacy in accessing information through social media, especially information on Covid-19 vaccinations for children aged between 06 and 11 years. The purposeless information in our brains can make us lose focus and ultimately make us unable to believe anything. Therefore, it is important to know how tabbayun parents are able to access information, especially the Covid-19 vaccination. Reasoned action theory with quantitative research methods and descriptive approaches chosen for this research, with data collection techniques were carried out through questionnaires, interviews, and supported by documentation, observation, and surveys. This research is expected to be a reference for parents in understanding digital literacy so that they are not trapped in with loads of information, as well as policymakers in conducting socialization and information related to health in the community, especially related to children’s health. To gain an understanding of how parents filter the rapid flow of information so that they are not trapped by inaccurate or even misleading information regarding the Covid-19 vaccination. The results of this study indicate that parents already understand well and are able to filter the information they get. But often, others, including spouses have different understanding patterns, causing debate. And parents also convey vaccination information to children in a language that is easy for children to understand, especially regarding information on Covid-19 vaccination. Impractical information to this literacy ability will be effected to the children vaccination permission and causes parents misunderstanding about the information.
 Keywords: digital literacy, obesity information, family communication, online media, Covid-19 vaccination

A Study on Evaluating the Impact of Social Media's Fake News on The Attitudes and Beliefs of a Society

The widespread availability of misleading information in this age of instantaneous information dissemination through social media platforms has prompted significant worry about its possible impact on people's worldviews. The major purpose of this research is to assess the influence of false news on social media on people's opinions and worldviews. Using a combination of quantitative surveys and qualitative content analysis, this research examines the frequency with which people are exposed to fake news. And moreover, it investigates the cognitive processes underlying the approval or rejection of such news, as well as its subsequent impact on individuals' attitudes and beliefs. The findings demonstrate a multifaceted correlation between misinformation exposure and changes in attitudes and beliefs. Regular exposure to misinformation is statistically associated with a decline in trust in conventional media outlets, according to the findings of a quantitative study. Individuals and society are affected by the implications of these findings, which have far-reaching effects. The decline in trust in conventional media underscores the critical need for media literacy education, which equips individuals with the ability to evaluate the veracity of information critically. In addition, the research highlights the importance of users in appropriately sharing content and the value of social media platforms in limiting the spread of disinformation. The results add to our growing knowledge of the complex link between fake news and public opinion. This provides policymakers, journalists, and educators with useful knowledge for navigating the current media environment. By illuminating the interplay between information intake, belief formation, and the rise of digital communication, this study betters our capacity to comprehend the multifaceted effects of fake news on social media. This research has important implications for the design of effective measures to reduce the societal harm caused by deception.
 Keyword: Social Media's, Fake News, Attitudes,

Artificial intelligence and increasing misinformation.

With the recent advances in artificial intelligence (AI), patients are increasingly exposed to misleading medical information. Generative AI models, including large language models such as ChatGPT, create and modify text, images, audio and video information based on training data. Commercial use of generative AI is expanding rapidly and the public will routinely receive messages created by generative AI. However, generative AI models may be unreliable, routinely make errors and widely spread misinformation. Misinformation created by generative AI about mental illness may include factual errors, nonsense, fabricated sources and dangerous advice. Psychiatrists need to recognise that patients may receive misinformation online, including about medicine and psychiatry.

Inflammatory Bowel Disease and X (Formerly Twitter) Influencers: Who Are They and What Do They Say?

Background and objective More than half of the population suffering from inflammatory bowel disease (IBD) use the internet as a primary source of information on their condition. X (formerly Twitter) has been increasingly used to disseminate healthcare-related information. In this study, we aimed to identify top influencers on the topic of IBD on Xand correlate the relevance of their social media engagements with their professional expertise or academic productivity. Methods X (formerly Twitter) influence scores for the search topicIBD were obtained using Cronycle API, a proprietary software employing multiple algorithms to rank influencers. Data regarding gender, profession, location, and research productivity represented as h-index was collected. Results We collected information on the top 100 IBD influencers on X. The majority of influencers were gastroenterologists, followed by IBD advocates. Of note, 62% of the IBD influencers were from the USfollowed by the UK and Canada. A positive correlation was observed between the Xtopic score and the h-index of the influencer (r=+0.488, p<0.001) Conclusions The strong correlation observed between the Xtopic score and h-index suggests that social media is a viable platform for gaining information regarding IBD. Further research aimed at counteracting misleading information by providing facts and data in a succinct manner about IBD on social media is required to improve disease awareness.

Are ChatGPT's Free-Text Responses on Periprosthetic Joint Infections of the Hip and Knee Reliable and Useful?

This study aimed to evaluate ChatGPT's performance on questions about periprosthetic joint infections (PJI) of the hip and knee. Twenty-seven questions from the 2018 International Consensus Meeting on Musculoskeletal Infection were selected for response generation. The free-text responses were evaluated by three orthopedic surgeons using a five-point Likert scale. Inter-rater reliability (IRR) was assessed via Fleiss' kappa (FK). Overall, near-perfect IRR was found for disagreement on the presence of factual errors (FK: 0.880, 95% CI [0.724, 1.035], p < 0.001) and agreement on information completeness (FK: 0.848, 95% CI [0.699, 0.996], p < 0.001). Substantial IRR was observed for disagreement on misleading information (FK: 0.743, 95% CI [0.601, 0.886], p < 0.001) and agreement on suitability for patients (FK: 0.627, 95% CI [0.478, 0.776], p < 0.001). Moderate IRR was observed for agreement on "up-to-dateness" (FK: 0.584, 95% CI [0.434, 0.734], p < 0.001) and suitability for orthopedic surgeons (FK: 0.505, 95% CI [0.383, 0.628], p < 0.001). Question- and subtopic-specific analysis revealed diverse IRR levels ranging from near-perfect to poor. ChatGPT's free-text responses to complex orthopedic questions were predominantly reliable and useful for orthopedic surgeons and patients. Given variations in performance by question and subtopic, consulting additional sources and exercising careful interpretation should be emphasized for reliable medical decision-making.

A Digital Personal Health Library for the Management of Abortion-Related Care via Telemedicine.

Abortion remains a highly controversial topic in many countries, particularly in the United States. As the COVID-19 pandemic introduced new challenges and restrictions, society saw a marked increase in demand for self-managed care. Likewise, the utilization of abortion care via telemedicine sparked interest, especially in communities with high infection rates. However, as unregulated online forums became an outlet for the discussion of sensitive health-related topics, the spread of false and misleading information markedly increased. As patients continue seeking reliable health-related information, personalized solutions are needed to provide accurate, evidence-based insight. As a pillar in digital precision health, precision health promotion via Personal Health Library (PHL) could aid in equipping patients with the necessary information to support informed health decision-making. In previous works, we have proposed the utilization of a PHL for the self-management of disease and health promotion/education. Herein, we introduce our work-in-progress in implementing the PHL-Enabled Abortion Care and Education (PEACE) platform for facilitating and supporting reliable access to informative reproductive care, such as abortion via telemedicine.

Exploring the Dunning-Kruger Effect in Health Communication: How Perceived Food and Media Literacy and Actual Knowledge Drift Apart When Evaluating Misleading Food Advertising

Marketers often advertise products high in sugar, fat or calories as healthy products. With this potentially misleading information, they can influence eating decisions with negative consequences for human health. Consumers need the ability to uncover misleading food advertising. However, individuals’ perceived knowledge and their actual objective abilities often drift apart – a phenomenon which has come to be known as the Dunning-Kruger Effect. Thus, this study set out to uncover the phenomenon’s potential existence in health communication, more precisely in the area of food and media literacy. In a quantitative survey representative of the Austrian population (n = 1000) the Dunning-Kruger Effect (DKE) could be detected: Individuals who were most knowledgeable underestimated their food and media literacy, but – on the positive side – they acted as opinion leaders. Individuals who were least knowledgeable about advertising strategies used to market an unhealthy product as healthy and about the actual nutrition score of the advertised product were most likely to overestimate their own food and media literacy. Worryingly, further concerning consequences emerged, especially for least knowledgeable individuals. The study’s results provide important implications for public health campaigns.

Security-guaranteed filter design for discrete-time Markovian jump delayed systems subject to deception attacks and sensor saturation

This work is devoted the problem of a security-guaranteed filter design for a class of discrete-time Markov jump systems that are vulnerable to stochastic deception attacks and have random sensor saturation. Deception attacks, in particular, are taken into account in the filter when the attacker attempts to modify the broadcast signal in communication networks by inserting some misleading information data into the assessment output. The Bernoulli distribution is satisfied by two sets of introduced stochastic variables. It shows the likelihood that the broadcaster’s data transmissions will be the focus of deception attacks and sensor saturation. The Lyapunov functional technique is established, and criteria are derived to ensure that the system is mean-square stable. Furthermore, explicit expression of the filter gains is obtained by solving a set of linear matrix inequalities. Lastly, two simulation examples including a synthetic genetic regulatory network are provided to further demonstrate the validity and efficiency of the suggested theoretical results.

Article retractions rates in selected MeSH term categories in PubMed published between 2010 - 2020

ABSTRACT Background Academic article retractions occur across all disciplines, though few studies have examined the association between research topics and retraction rates. Objectives We assessed and compared the rate of retraction across several important clinical research topics. Methods Information about the number of publications, the number of retractions, the retraction rate, and the time to retraction was collected for articles identified by 15 Medical Subject Headings (MeSH) terms. These articles were published between 1 January 2010, and 31 December 2020. The searches took place between 18 September 2021, and 24 October 2021. The MeSH terms were selected based on our clinical experience with the expectation that there will be multiple publications during the timeframe to use for the searches. Additional topics were selected based on the frequency of controversy in the public media and were identified by the Altmetric Top 100 report. Results The mean number of publications for all categories was 181,975 ± 332,245; the median number of publications was 67,991 [Q1-Q3; 31951.5, 138,981.5]. The mean number of retractions was 100.3 ± 251.3, and the median number of retractions was 22 [Q1, Q3; 6.5,53]. The mean time to retraction ranged from 114 days to 1,409.5 days; the median was 857.3 days [Q1, Q3; 684.7, 1098.6], depending on the topic. The various MeSH term categories used in this study had significant differences in retraction rate and time to retraction. The “Neoplasms” category had the highest total number of retractions (993) and one of the highest retraction rates (75.4 per 100,000 publications). Discussion All PubMed categories analyzed in this study had retracted articles. The median time to retraction was 857 days. The long delays in some categories could contribute to potentially misleading information which might have adverse effects on clinical decisions in patient care and on research design. Conclusion Rate of retraction varies across research topics and further studies are needed to explore this relationship.

Content Analysis of YouTube Videos on the Effect of Vitamin C on Common Cold.

With the growth of the Internet, social media platforms have emerged as major sources of medical information. We assessed the reliability, quality, and accuracy of the most-viewed YouTube videos containing information on the effect of vitamin C on the common cold. The YouTube videos were searched on August 1, 2022, using the keywords: ("ascorbic acid" OR "vitamin C" OR "Sodium Ascorbate" OR "L-ascorbic") AND "common cold". The 30 most-viewed videos were included in our study. The reliability and quality of the videos were analyzed using modified DISCERN and Global Quality Scales, respectively. When the videos included at least one correct or inaccurate scientific statement about the effect of vitamin C on the common cold, they were classified as accurate or misleading videos, respectively; those without any pertinent information were considered neither accurate nor misleading. If a video contained both accurate and inaccurate statements, it was classified as misleading. Of the 30 most-viewed videos, 73% were unreliable, and 67% contained misleading information and were of a poor quality. Of these 30 videos, 14 videos were produced and posted by customers who were not specialized in medicine or nutrition. Moreover, these videos were of significantly lower reliability, quality, and accuracy than those produced by nutrition or fitness channels or by medical or nutrition professionals. The reliability, quality, and accuracy of videos uploaded by non-professionals were low. Therefore, video creators should upload reliable, high-quality videos to ensure the dissemination of accurate medical information.

Characterizing Precision Nutrition Discourse on Twitter: Quantitative Content Analysis.

It is possible that tailoring dietary approaches to an individual's genomic profile could provide optimal dietary inputs for biological functioning and support adherence to dietary management protocols. The science required for such nutrigenetic and nutrigenomic profiling is not yet considered ready for broad application by the scientific and medical communities; however, many personalized nutrition products are available in the marketplace, creating the potential for hype and misleading information on social media. Twitter provides a unique big data source that provides real-time information. Therefore, it has the potential to disseminate evidence-based health information, as well as misinformation. We sought to characterize the landscape of precision nutrition content on Twitter, with a specific focus on nutrigenetics and nutrigenomics. We focused on tweet authors, types of content, and presence of misinformation. Twitter Archiver was used to capture tweets from September 1, 2020, to December 1, 2020, using keywords related to nutrition and genetics. A random sample of tweets was coded using quantitative content analysis by 4 trained coders. Codebook-driven, quantified information about tweet authors, content details, information quality, and engagement metrics were compiled and analyzed. The most common categories of tweets were precision nutrition products and nutrigenomic concepts. About a quarter (132/504, 26.2%) of tweet authors presented themselves as science experts, medicine experts, or both. Nutrigenetics concepts most frequently came from authors with science and medicine expertise, and tweets about the influence of genes on weight were more likely to come from authors with neither type of expertise. A total of 14.9% (75/504) of the tweets were noted to contain untrue information; these were most likely to occur in the nutrigenomics concepts topic category. By evaluating social media discourse on precision nutrition on Twitter, we made several observations about the content available in the information environment through which individuals can learn about related concepts and products. Tweet content was consistent with the indicators of medical hype, and the inclusion of potentially misleading and untrue information was common. We identified a contingent of users with scientific and medical expertise who were active in discussing nutrigenomics concepts and products and who may be encouraged to share credible expert advice on precision nutrition and tackle false information as this technology develops.

Youtube is an unreliable source of information about delayed ejaculation treatment.

Social platforms such as YouTube have become sources of information about diseases as they can be easily and rapidly accessed. However, this also has the risk of ill-intentioned content and misleading information. To evaluate the reliability of YouTube video content about delayed ejaculation treatment. YouTube videos were searched using the terms "delayed ejaculation," "retarded ejaculation," "inhibited ejaculation," and "anejaculation." Videos were excluded if they were not in English, were not related to the subject, or did not have audio and visual content. In accordance with the scientifically proven accurate information, the videos were separated as reliable (Group 2, n: 112) and unreliable videos (Group 1, n: 94). The groups were compared in respect of the video characteristics, and the scores obtained in the DISCERN-5, Global Quality Scale, the Patient Education Materials Assessment Tool Audiovisual, and the Journal of the American Medical Association scales. Intraclass correlation test was used to evaluate the level of agreement between the two investigators. Of the 1200 videos, 994 were excluded. No significant difference was determined between the Group 1 and Group 2 in respect of the median number of views [1672 (4555) vs 1547 (28,559), p = 0.63] and likes [10 (42) vs 17 (255), p = 0.07]. There was a greater number of videos in the Group 2 (54.4%) and the points obtained on the scoring scales were significantly higher than the Group 1 (p < 0.001). The videos originating from universities/professional organizations/non-profit physician/physician group were comprised the majority of the reliable videos (55.3%) and the unreliable videos had more content related to treatment (71.4%) (p < 0.001). Although there was a greater number of reliable videos related to the problem of delayed ejaculation, the content could be misleading and should be avoided by patients seeking treatment without consulting a physician.

The efficacy and reliability of English YouTube videos as a source of information for pregnant rheumatoid arthritis patients.

Online platforms are used by many patients to access health care information, but the quality and accuracy of information on these platforms are unknown. Our goal was to assess the quality and reliability of YouTube video content for pregnant rheumatoid arthritis (RA) patients. YouTube was searched on January 13, 2022, using the keywords "rheumatoid arthritis pregnancy," "rheumatoid arthritis conception," "rheumatoid arthritis fertility" and "rheumatoid arthritis breastfeeding". The top 200 videos were viewed. Two rheumatologists then categorized the videos into useful and misleading groups. Videos were excluded if they were irrelevant or duplicates. To assess the reliability and quality of the videos, a modified DISCERN tool and the Global Quality Score (GQS) were applied. Patient interaction was assessed using predictors of video popularity such as the like ratio, view ratio, and video power index scales. A total of 54 videos were examined; the majority (51.8%) of them were uploaded by health information websites. A total of 94.4% of the videos were useful, and 5.5% were misleading. All three misleading videos were uploaded by patients. The GQS, the modified DISCERN score, and usefulness differed significantly by uploader source (p < 0.001 for both). According to the GQS evaluation, health information websites were the source of high-quality videos with more useful information and higher modified DISCERN scores. The GQS and modified DISCERN score had moderately negative (r = -.526, r = -.548, respectively) and very significant (p < 0.001 for both) correlations with the assessment of usefulness. Almost all YouTube videos for pregnant RA patients were educational and useful. Similar patient interactions in videos with misleading and useful information showed that patients were unable to differentiate between videos based on video quality. Patients should be informed about the importance of video sources when viewing YouTube videos. Key Points • Most YouTube videos for pregnant RA patients were useful, were uploaded by health information websites and had physicians as the speakers • All misleading YouTube videos were uploaded by patients using their own accounts • In terms of patient interactions, there was no noticeable difference between useful and misleading videos • When dealing with a sensitive topic such as pregnancy, patients should be educated on the importance of video sources.

Misleading information created by tobacco industry

Misleading information created by tobacco industry