Publicaties
The Global Alliance for Infections in Surgery : defining a model for antimicrobial stewardship : results from an international cross-sectional survey Universiteit Gent
Harm reduction and viral hepatitis C in European prisons: a cross-sectional survey of 25 countries Universiteit Hasselt
Menstrual hygiene management and school absenteeism among adolescent students in Indonesia : evidence from a cross-sectional school-based survey Universiteit Gent
Large-scale cross-sectional serological survey of Schmallenberg virus in Belgian cattle at the end of the first vector season Universiteit Gent
Discomfort With Suffering and Dying, a Cross-Sectional Survey of the General Public Vrije Universiteit Brussel
CONTEXT: Death and the process of dying have become increasingly medicalized and professionalized. The associated cultural estrangement from death may affect how comfortable we feel about death and dying. This study examines the general public's discomfort with another person's suffering and dying, and whether these feelings are associated with specific personal characteristics or experiences.
OBJECTIVES: Cross-sectional survey in a ...
Knowledge and awareness of hepatitis B among households in Malaysia: a community-based cross-sectional survey Instituut voor Tropische Geneeskunde
Background: Hepatitis B (HepB) is a major public health concern in Malaysia yet little is known about knowledge and awareness of this infection in the country. Such information is essential for designing effective intervention strategies for HepB prevention and control. The aim of this study was to characterize knowledge and awareness regarding HepB in Malaysia and to identify their associated sociodemographic determinants.
Methods: A ...
Can machine learning models predict maternal and newborn healthcare providers' perception of safety during the COVID-19 pandemic? A cross-sectional study of a global online survey Instituut voor Tropische Geneeskunde
Background Maternal and newborn healthcare providers are essential professional groups vulnerable to physical and psychological risks associated with the COVID-19 pandemic. This study uses machine learning algorithms to create a predictive tool for maternal and newborn healthcare providers' perception of being safe in the workplace globally during the pandemic. Methods We used data collected between 24 March and 5 July 2020 through a global ...