7,747 Matching Annotations
  1. Jun 2020
    1. Quantifying the Cost of Decision Fatigue: Supoptimal Risk Decisions in Finance
    1. Dynamic causal modelling of COVID-19 [version 1; peer review: awaiting peer review]
  2. riskhomeostasis.org riskhomeostasis.org
    1. Welcome to the Risk Homeostasis and Risk Compensation Resource Centre
    1. Working paper: to be updated1Hate multiverse spreads malicious COVID-19content online beyond individualplatform control
    1. The Extended Moral Foundations Dictionary (eMFD): Development and Applications of a Crowd-Sourced Approach to Extracting Moral Intuitions from Text
    1. Understanding the characteristics of public attention and perception is an essential prerequisite for appropriate crisis management during adverse health events. This is even more crucial during a pandemic such as COVID-19, as primary responsibility of risk management is not centralized to a single institution, but distributed across society. While numerous studies utilize Twitter data in descriptive or predictive context during COVID-19 pandemic, causal modeling of public attention has not been investigated. In this study, we propose a causal inference approach to discover and quantify causal relationships between pandemic characteristics (e.g. number of infections and deaths) and Twitter activity as well as public sentiment. Our results show that the proposed method can successfully capture the epidemiological domain knowledge and identify variables that affect public attention and perception. We believe our work contributes to the field of infodemiology by distinguishing events that correlate with public attention from events that cause public attention.
    2. Causal Modeling of Twitter Activity During COVID-19
    1. The coronavirus disease 2019 (COVID-19) has had psychological impacts on healthcare workers. However, very few scales are available to specifically assess healthcare workers’ work-related stress and anxiety in response to viral epidemics. This study developed a new rating scale, the Stress and Anxiety to Viral Epidemics-9 (SAVE-9), and validated it among healthcare workers directly affected by COVID-19 in Korea. A total of 1,019 healthcare workers responded through anonymous questionnaires during April 20-30, 2020. Internal consistency of the SAVE-9 was measured through Cronbach’s alpha, and principal component analysis with varimax rotation was used to determine its component structure. It was also compared with the Generalized Anxiety Disorder-7 (GAD-7) and Patient Health Questionnaire-9 scales. Its most appropriate cut-off point was determined by conducting receiver operating characteristic analysis. The nine-item scale had satisfactory internal consistency (Cronbach’s α=0.795). It adopted a two-factor structure: (1) anxiety about viral epidemics and (2) work-related stress associated with viral epidemics (Bartlett’s test of sphericity, p < 0.001; Kaiser-Meyer-Olkin=0.85). Correlations between SAVE-9 and the other scales were statistically significant. The cut-off points of the SAVE-9 and its anxiety subcategory were 22 and 15, respectively, compared with a GAD-7 score of 5. The results suggest that the SAVE-9 is a useful, reliable, and valid tool to evaluate stress and anxiety responses in healthcare workers during viral epidemics.
    2. Development of the Stress and Anxiety to Viral Epidemics-9 (SAVE-9) scale for assessing work-related stress and anxiety in healthcare workers in response to viral epidemics
    1. Meaningful Living, Resilience, Affective Balance,and Psychological Health ProblemsduringCOVID-19
    1. 1“If this account is true, it is most enormously wonderful”:Interestingness-if-true and the sharing of true and false news
    1. Perceived Risk and Mental Health Problems Among Healthcare Professionals During COVID-19 Pandemic: Exploring the Mediating Effects of Resilience and Coronavirus Fear
    1. State-level Stay-at-home Orders and Objectively Measured Movement in the United States During the COVID-19 Pandemic
    1. Report 9: Impact of non-pharmaceutical interventions (NPIs) to reduce COVID-19 mortality and healthcare demand
    2. Report 9: Impact of non-pharmaceutical interventions (NPIs) to reduce COVID19 mortality and healthcare demand
    1. Net-COVIDUnderstanding and Exploring Network Epidemiology in the Time of Coronavirus
    1. Call for Papers on "Misinformation, Manipulation and Abuse on Social Media in the Era of COVID-19"
    1. Case Study: Using Facebook Data to Monitor Adherence to Stay-at-home Orders in Colorado and Utah