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| http://dx.doi.org/10.1016/j.jaim.2021.05.013 | DOI Listing |
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Explicating college students' COVID-19 prevention behaviors: Integrating information seeking and response efficacy into the reasoned action approach.
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Department of Communication, University of Illinois Urbana-Champaign, Urbana, Illinois, USA.
This study investigated correlations between college students' intentions to adopt COVID-19 prevention behaviors (i.e., handwashing, mask wearing, and social distancing) and their attitudes, perceived norms, perceived efficacy, and information seeking.
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Department of Infection and Immunity, Shanghai Public Health Clinical Center, Fudan University, Shanghai, China.
Background: The global resurgence of disseminated tuberculosis (TB) after the coronavirus disease 2019 pandemic highlights the necessity of understanding host risk factors, especially in adults without human immunodeficiency virus.
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Emergence of a bla-carrying extensively drug-resistant Enterobacter cloacae ST1718 in Saudi Arabia: Insights from comprehensive genome analysis.
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Public health Laboratory, The regional laboratory, Jazan Health Cluster, Jazan, Saudi Arabia.
Background: Patients with severe COVID-19 may require intensive care unit (ICU) admission to manage life-threatening complications. However, ICU admission is associated with an increased risk of acquiring nosocomial infections caused by multidrug-resistant (MDR) bacteria, particularly carbapenem-resistant Enterobacterale (CRE). Enterobacter cloacae complex (ECC), a group of closely related species including Enterobacter cloacae, is a common cause of healthcare-associated infections (HAIs).
View Article and Find Full Text PDFDetermining the feasibility of linked claims and vaccination data for a COVID-19 vaccine pharmacoepidemiological study in Germany-RiCO feasibility study protocol.
BMJ Open
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PMV Research Group, Medical Faculty and University Hospital Cologne, University of Cologne, Koln, Germany
Introduction: In Germany, there has been no population-level pharmacoepidemiological study on the safety of the COVID-19 vaccines. One factor preventing such a study so far relates to challenges combining the different relevant data bodies on vaccination with suitable outcome data, specifically statutory health insurance claims data. Individual identifiers used across these data bodies are of unknown quality and reliability for data linkage.
View Article and Find Full Text PDFHierarchical graph-based integration network for propaganda detection in textual news articles on social media.
Sci Rep
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EIAS Data Science Lab, College of Computer and Information Sciences, Prince Sultan University, 11586, Riyadh, Saudi Arabia.
During the Covid-19 pandemic, the widespread use of social media platforms has facilitated the dissemination of information, fake news, and propaganda, serving as a vital source of self-reported symptoms related to Covid-19. Existing graph-based models, such as Graph Neural Networks (GNNs), have achieved notable success in Natural Language Processing (NLP). However, utilizing GNN-based models for propaganda detection remains challenging because of the challenges related to mining distinct word interactions and storing nonconsecutive and broad contextual data.
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