ABSTRACT
The emergence of COVID-19, caused by novel Coronavirus SARS-CoV-2, became a pandemic in just 10 weeks. Without effective medications or vaccines available, authorities turned toward mitigation measures such as use of face masks, school's closings, shelter-in-place, telework and social distancing. People found refuge on the internet and social media apps; however, there was a proliferation of instant messaging containing hoaxed, deliberate misleading information: fake news messaging (FNM). The aim of this study was to assess FNM through content analysis and to discriminate them in a proposed taxonomy structure. A sample of convenience of messages, memes, tweets or cartoons in several languages was selected from the most popular social media outlets, i.e. Facebook, WhatsApp, Twitter etc. More than 300 FNM were identified. Descriptive statistics were used for highlighting potential relationships between variables. Content analysis determined that FNM could be divided into Health- and non-health-related types. There are several sub-types considering, but not limited to, religious beliefs, politics, economy, nutrition, behaviors, prevention of the infection, the origin of the disease and conspiracy theories. The parallel FNM pandemic affected the response from an already debilitated public health system through the confusion created in the community and the erosion in the credibility of genuine media. Public health practitioners had to face people's unpredictable behaviors, panic, tensions with the communities and, in some cases, a hostile climate toward frontline workers. Public health practitioners must adjust ongoing and future health promotion and education interventions including plans to neutralize fake news messages.
Subject(s)
COVID-19/epidemiology , Health Communication/methods , Health Communication/standards , Social Media/standards , COVID-19/prevention & control , COVID-19/psychology , Communicable Disease Control/methods , Cross-Sectional Studies , Health Behavior , Humans , Pandemics , Politics , Religion , SARS-CoV-2ABSTRACT
Personalized genomic diagnostics, often in combination with targeted therapeutics, have become an important component of clinical oncologic practice over the last decade. However, there is a dearth of studies examining utilization of specific genomic diagnostics and their influence on clinical practice patterns in health systems. In order to begin to explore and understand the clinical utility of particular genomic diagnostics in current use, we developed an instrument to collect data on utilization and clinical practice patterns in health systems. We focused our efforts on gene-expression profiling (GEP) assays, particularly on a commonly used GEP in breast cancer: Oncotype DX® (Genomic Health, Inc., CA, USA). This article presents a method we have developed for the retrospective collection of data on the utilization of GEP among breast cancer patients of a real-world, real-time health system.
