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Background: Fake health-related news has spread rapidly through the internet, causing harm to individuals and society. Despite interventions, a fenbendazole scandal recently spread among patients with lung cancer in South Korea. It is crucial to intervene appropriately to prevent the spread of fake news.
Objective: This study investigated the appropriate timing of interventions to minimize the side effects of fake news.
Methods: A simulation was conducted using the susceptible-infected-recovered (SIR) model, which is a representative model of the virus spread mechanism. We applied this model to the fake news spread mechanism. The parameters were set similarly to those in the digital environment, where the fenbendazole scandal occurred. NetLogo, an agent-based model, was used as the analytical tool.
Results: Fake news lasted 278 days in the absence of interventions. As a result of adjusting and analyzing the timing of the intervention in response to the fenbendazole scandal, we found that faster intervention leads to a shorter duration of fake news (intervention at 54 days = fake news that lasted for 210 days; intervention at 16 days = fake news that lasted for 187 days; and intervention at 10 days = fake news that lasted for 157 days). However, no significant differences were observed when the intervention was performed within 10 days.
Conclusions: Interventions implemented within 10 days were effective in reducing the duration of the spread of fake news. Our findings suggest that timely intervention is critical for preventing the spread of fake news in the digital environment. Additionally, a monitoring system that can detect fake news should be developed for a rapid response.
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http://dx.doi.org/10.2196/48284 | DOI Listing |
J Eval Clin Pract
September 2025
Academic Unit of Population and Lifespan Sciences, School of Medicine, Nottingham City Hospital Campus, University of Nottingham, Clinical Sciences Building, Nottingham, UK.
Background: Artificial intelligence (AI) is increasingly applied across healthcare and public health, with evidence of benefits including enhanced diagnostics, predictive modelling, operational efficiency, medical education, and disease surveillance.However, potential harms - such as algorithmic bias, unsafe recommendations, misinformation, privacy risks, and sycophantic reinforcement - pose challenges to safe implementation.Far less attention has been directed to the public health threats posed by artificial general intelligence (AGI), a hypothetical form of AI with human-level or greater cognitive capacities.
View Article and Find Full Text PDFPublic Health Rep
September 2025
Brown School, Washington University, St. Louis, MO, USA.
Objectives: Although wastewater monitoring for virus detection has increased in communities worldwide, public awareness, understanding, questions, and concerns about wastewater monitoring are largely unknown. We assessed awareness, knowledge, and support for wastewater monitoring for detection of viruses and bacteria among US residents and elicited questions and concerns from residents about its use.
Methods: We conducted a survey among a racially and ethnically diverse sample of residents in Colorado, Maryland, Missouri, Nebraska, and Texas to assess awareness, knowledge, and support of wastewater monitoring.
PLoS One
September 2025
Faculty of Economics and Business Administration, Graduate School of Management, Tokyo Metropolitan University, Tokyo, Japan.
When different information sources on a given topic are combined, they interact in a nontrivial manner for a rational receiver of these information sources. Suppose that there are two information sources, one is genuine and the other contains disinformation. It is shown that under the conditions that the signal-to-noise ratio of the genuine information source is sufficiently large, and that the noise terms in the two information sources are positively correlated, the effect of disinformation is reversed from its original intent.
View Article and Find Full Text PDFJ Med Internet Res
September 2025
Institute of Learning, Mohammed Bin Rashid University of Medicine and Health Sciences, Dubai Health, Dubai, United Arab Emirates.
Background: Misinformation in health and health care contexts threatens public health by undermining initiatives, spreading dangerous behaviors, and influencing decision-making. Given its reach on online platforms and social media, there is growing demand for interventions addressing misinformation. Literature highlights the importance of theoretical underpinnings (frameworks and models) to guide the development of educational interventions targeting both the features of misinformation and the human traits that increase susceptibility.
View Article and Find Full Text PDFAnn Med Surg (Lond)
September 2025
Department of Mass Communication, Caleb University Lagos, Nigeria.
This study investigates media literacy and the perception of fake news among residents of Ikeja, Lagos State, during the COVID-19 pandemic. Using a descriptive survey design, data were collected from 378 respondents selected through a multi-stage sampling approach across two wards. A structured questionnaire assessed participants' exposure to news, awareness of misinformation, and their strategies for verification.
View Article and Find Full Text PDF