Understanding how humans evaluate credibility is an important scientific question in the era of fake news. Source credibility is among the most important aspects of credibility evaluations. One of the most direct ways to understand source credibility is to use measurements of brain activity of humans who make credibility evaluations. This article reports the results of an experiment during which we have measured brain activity during credibility evaluation using EEG. In the experiment, participants had to learn source credibility of fictitious students based on a preparatory stage, during which they evaluated message credibility with perfect knowledge. The experiment allowed for identification of brain areas that were active when a participant made positive or negative source credibility evaluations. Based on experimental data, we modeled and predicted human source credibility evaluations using EEG brain activity measurements with F1 score exceeding 0.7 (using 10-fold cross-validation). We are also able to model and predict message credibility evaluations with perfect knowledge, and to compare both models obtained from a single experiment.
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http://dx.doi.org/10.3389/fnhum.2022.808382 | DOI Listing |
Int J Environ Res Public Health
December 2024
Leicester Castle Business School, De Montfort University, Leicester LE1 9BH, UK.
This study examines the relative effectiveness of the UK government's public health messages used during the first wave of the COVID-19 pandemic. We focus on the use of a loss versus gain frame. We look at the effect of framing on behavioural inclination to follow COVID-19 guidance, as well as affective mechanisms and individual characteristic moderators that might explain said willingness.
View Article and Find Full Text PDFPLoS One
January 2025
Substitutive Dental Sciences Department (Prosthodontics), College of Dentistry, Taibah University, Al Madinah, Saudi Arabia.
Background: This study aimed to investigate the quality and readability of online English health information about dental sensitivity and how patients evaluate and utilize these web-based information.
Methods: The credibility and readability of health information was obtained from three search engines. We conducted searches in "incognito" mode to reduce the possibility of biases.
Trop Med Infect Dis
December 2024
School of Population Health, Faculty of Health Sciences, Curtin University, Perth, WA 6102, Australia.
Background: Drug-resistant tuberculosis (DR-TB) remains a major public health challenge in China, with varying treatment outcomes across different regions. Understanding the spatial distribution of DR-TB treatment outcomes is crucial for targeted interventions to improve treatment success in high-burden areas such as Hunan Province. This study aimed to map the spatial distribution of DR-TB treatment outcomes at a local level and identify sociodemographic and environmental factors associated with poor treatment outcomes in Hunan Province, China.
View Article and Find Full Text PDFTo compare the effectiveness of injury prevention programs (IPPs) for improving high-risk knee motion patterns in the context of reducing the risk of noncontact anterior cruciate ligament injury. Systematic review with Bayesian network meta-analysis. PubMed, Embase, Web of Science, Cochrane Library, and the Cumulative Index to Nursing and Allied Health Literature were searched until September 10, 2023.
View Article and Find Full Text PDFJMIR Public Health Surveill
January 2025
Division of Global HIV and TB, Centers for Disease Control and Prevention, 1600 Clifton Rd, Atlanta, GA, 30322, United States, 1 8103383534.
Background: Population size estimation (PSE) for key populations is needed to inform HIV programming and policy.
Objective: This study aimed to examine the utility of applying a recently proposed method using Google Trend (GT) internet search data to generate PSE (Google Trends Population Size Estimate [GTPSE]) for men who have sex with men (MSM) in 54 countries in Africa, Asia, the Americas, and Europe.
Methods: We examined GT relative search volumes (representing the relative internet search frequency of specific search terms) for "porn" and, as a comparator term, "gay porn" for the year 2020.
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