Stay Home or Not? Modeling Individuals’ Decisions During the COVID-19 Pandemic

2021 ◽  
Author(s):  
Qifeng Wan ◽  
Xuanhua Xu ◽  
Kyle Hunt ◽  
Jun Zhuang
Keyword(s):  
Decision Making ◽  
Policy Development ◽  
Medical Knowledge ◽  
Optimal Strategies ◽  
Real Data ◽  
Personal Exposure ◽  
Control Measures ◽  
Strategic Decisions ◽  
Trade Offs ◽  
At Home

During the COVID-19 pandemic, staying home proved to be an effective way to mitigate the spread of the virus. Stay-at-home orders and guidelines were issued by governments across the globe and were followed by a large portion of the population in the early stages of the outbreak when there was a lack of COVID-specific medical knowledge. The decision of whether to stay home came with many trade-offs, such as risking personal exposure to the virus when leaving home or facing financial and mental health burdens when remaining home. In this research, we study how individuals make strategic decisions to balance these conflicting outcomes. We present a model to study individuals’ decision making based on decision and prospect theory, and we conduct sensitivity analysis to study the fluctuations in optimal strategies when there are changes made to the model’s parameters. A Monte Carlo simulation is implemented to further study the performance of our model, and we compare our simulation results with real data that captures individuals’ stay-at-home decisions. Overall, this research models and analyzes the behaviors of individuals during the COVID-19 pandemic and can help support decision making regarding control measures and policy development when public health emergencies appear in the future.

Methodology of ECG Interpretation in the Padova Program

1990 ◽  
Vol 29 (04) ◽  
pp. 386-392 ◽  
Author(s):  
R. Degani ◽  
G. Bortolan
Keyword(s):  
Decision Making ◽  
Medical School ◽  
Fuzzy Set ◽  
Medical Knowledge ◽  
Main Aspect ◽  
Measurement Evaluation ◽  
Possibility Distributions ◽  
Linguistic Decision Making ◽  
The University ◽  
Ecg Interpretation

AbstractThe main lines ofthe program designed for the interpretation of ECGs, developed in Padova by LADSEB-CNR with the cooperation of the Medical School of the University of Padova are described. In particular, the strategies used for (i) morphology recognition, (ii) measurement evaluation, and (iii) linguistic decision making are illustrated. The main aspect which discerns this program in comparison with other approaches to computerized electrocardiography is its ability of managing the imprecision in both the measurements and the medical knowledge through the use of fuzzy-set methodologies. So-called possibility distributions are used to represent ill-defined parameters as well as threshold limits for diagnostic criteria. In this way, smooth conclusions are derived when the evidence does not support a crisp decision. The influence of the CSE project on the evolution of the Padova program is illustrated.

Did Groupthink or Polythink Derail the 2016 Raqqa Offensive?

2019 ◽  
Author(s):  
Kasey Barr ◽  
Alex Mintz
Keyword(s):  
Decision Making ◽  
Group Dynamics ◽  
Decision Making Process ◽  
Islamic State ◽  
Study Analysis ◽  
Strategic Decisions ◽  
Case Study Analysis ◽  
The Us ◽  
Tactical Decisions

This chapter examines the effect of group dynamics on the 2016 decision within the administration of President Barack Obama to lead the international coalition in a mission to liberate Raqqa, Syria, from the Islamic State. The authors show that whereas the groupthink syndrome characterized the decision-making process of the US-led coalition’s decision to attack Raqqa, it was polythink that characterized the decision-making dynamics both in the US-led coalition and within the inner circle of Obama’s own foreign policy advisors. Through case-study analysis, the authors illustrate that groupthink is more likely in strategic decisions, whereas polythink is more likely in tactical decisions.

scholarly journals Explaining deep neural networks for knowledge discovery in electrocardiogram analysis

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Steven A. Hicks ◽  
Jonas L. Isaksen ◽  
Vajira Thambawita ◽  
Jonas Ghouse ◽  
Gustav Ahlberg ◽  
...  
Keyword(s):  
Decision Making ◽  
Deep Learning ◽  
Deep Neural Networks ◽  
Clinical Decision Making ◽  
Medical Knowledge ◽  
Clinical Decision ◽  
Medical Data ◽  
Medical Doctors ◽  
Medical Tests ◽  
Deep Learning Model

AbstractDeep learning-based tools may annotate and interpret medical data more quickly, consistently, and accurately than medical doctors. However, as medical doctors are ultimately responsible for clinical decision-making, any deep learning-based prediction should be accompanied by an explanation that a human can understand. We present an approach called electrocardiogram gradient class activation map (ECGradCAM), which is used to generate attention maps and explain the reasoning behind deep learning-based decision-making in ECG analysis. Attention maps may be used in the clinic to aid diagnosis, discover new medical knowledge, and identify novel features and characteristics of medical tests. In this paper, we showcase how ECGradCAM attention maps can unmask how a novel deep learning model measures both amplitudes and intervals in 12-lead electrocardiograms, and we show an example of how attention maps may be used to develop novel ECG features.

Voluntary food fortification policy in Australia: did ‘formal’ stakeholder consultation influence the outcome?

2021 ◽  
Author(s):  
Bronwyn Ashton ◽  
Cassandra Star ◽  
Mark Lawrence ◽  
John Coveney
Keyword(s):  
Public Health ◽  
Decision Making ◽  
Policy Process ◽  
Policy Development ◽  
Food Fortification ◽  
Policy Debate ◽  
Stakeholder Consultation ◽  
Regulatory Decision ◽  
Food Regulation ◽  
Ministerial Council

Summary This research aimed to understand how the policy was represented as a ‘problem’ in food regulatory decision-making in Australia, and the implications for public health nutrition engagement with policy development processes. Bacchi’s ‘what’s the problem represented to be?’ discourse analysis method was applied to a case study of voluntary food fortification policy (VFP) developed by the then Australia and New Zealand Food Regulation Ministerial Council (ANZFRMC) between 2002 and 2012. As a consultative process is a legislated aspect of food regulatory policy development in Australia, written stakeholder submissions contributed most of the key documents ascertained as relevant to the case. Four major categories of stakeholder were identified in the data; citizen, public health, government and industry. Predictably, citizen, government and public health stakeholders primarily represented voluntary food fortification (VF) as a problem of public health, while industry stakeholders represented it as a problem of commercial benefit. This reflected expected differences regarding decision-making control and power over regulatory activity. However, at both the outset and conclusion of the policy process, the ANZFRMC represented the problem of VF as commercial benefit, suggesting that in this case, a period of ‘formal’ stakeholder consultation did not alter the outcome. This research indicates that in VFP, the policy debate was fought and won at the initial framing of the problem in the earliest stages of the policy process. Consequently, if public health nutritionists leave their participation in the process until formal consultation stages, the opportunity to influence policy may already be lost.

Renewable energy selection based on a new entropy and dissimilarity measure on an interval-valued neutrosophic set

2021 ◽  
pp. 1-18
Author(s):  
ShuoYan Chou ◽  
Truong ThiThuy Duong ◽  
Nguyen Xuan Thao
Keyword(s):  
Decision Making ◽  
Renewable Energy ◽  
Membership Function ◽  
Fossil Fuels ◽  
Multiple Criteria Decision Making ◽  
Clean Energy ◽  
Dissimilarity Measure ◽  
Neutrosophic Set ◽  
Trade Offs ◽  
And Performance

Energy plays a central part in economic development, yet alongside fossil fuels bring vast environmental impact. In recent years, renewable energy has gradually become a viable source for clean energy to alleviate and decouple with a negative connotation. Different types of renewable energy are not without trade-offs beyond costs and performance. Multiple-criteria decision-making (MCDM) has become one of the most prominent tools in making decisions with multiple conflicting criteria existing in many complex real-world problems. Information obtained for decision making may be ambiguous or uncertain. Neutrosophic is an extension of fuzzy set types with three membership functions: truth membership function, falsity membership function and indeterminacy membership function. It is a useful tool when dealing with uncertainty issues. Entropy measures the uncertainty of information under neutrosophic circumstances which can be used to identify the weights of criteria in MCDM model. Meanwhile, the dissimilarity measure is useful in dealing with the ranking of alternatives in term of distance. This article proposes to build a new entropy and dissimilarity measure as well as to construct a novel MCDM model based on them to improve the inclusiveness of the perspectives for decision making. In this paper, we also give out a case study of using this model through the process of a renewable energy selection scenario in Taiwan performed and assessed.

Needs, issues, and expectations on dementia care at home across Europe to inform policy development: findings from a transnational research study

Health Policy ◽  
2021 ◽  
Author(s):  
Valentina Bressan ◽  
Henriette Hansen ◽  
Kim Koldby ◽  
Knud Damgaard Andersen ◽  
Allette Snijder ◽  
...  
Keyword(s):  
Policy Development ◽  
Research Study ◽  
Dementia Care ◽  
Care At Home ◽  
At Home

scholarly journals Development of an electronic conversation aid to support shared decision making for children with acute otitis media

JAMIA Open ◽  
2021 ◽  
Vol 4 (2) ◽  
Author(s):  
Jana L Anderson ◽  
e Silva Lucas Oliveira J ◽  
Juan P Brito ◽  
Ian G Hargraves ◽  
Erik P Hess
Keyword(s):  
Decision Making ◽  
Shared Decision Making ◽  
Otitis Media ◽  
Acute Otitis Media ◽  
Medical Knowledge ◽  
Complication Rates ◽  
Shared Decision ◽  
Web Based ◽  
Quality Issue ◽  
The Impact

Abstract Objective The overuse of antibiotics for acute otitis media (AOM) in children is a healthcare quality issue in part arising from conflicting parent and physician understanding of the risks and benefits of antibiotics for AOM. Our objective was to develop a conversation aid that supports shared decision making (SDM) with parents of children who are diagnosed with non-severe AOM in the acute care setting. Materials and Methods We developed a web-based encounter tool following a human-centered design approach that includes active collaboration with parents, clinicians, and designers using literature review, observations of clinical encounters, parental and clinician surveys, and interviews. Insights from these processes informed the iterative creation of prototypes that were reviewed and field-tested in patient encounters. Results The ear pain conversation aid includes five sections: (1) A home page that opens the discussion on the etiologies of AOM; (2) the various options available for AOM management; (3) a pictograph of the impact of antibiotic therapy on pain control; (4) a pictograph of complication rates with and without antibiotics; and (5) a summary page on management choices. This open-access, web-based tool is located at www.earpaindecisionaid.org. Conclusions We collaboratively developed an evidence-based conversation aid to facilitate SDM for AOM. This decision aid has the potential to improve parental medical knowledge of AOM, physician/parent communication, and possibly decrease the overuse of antibiotics for this condition.

scholarly journals Using Deliberative Democracy for Better Urban Decision-Making through Integrative Thinking

Urban Science ◽  
2020 ◽  
Vol 5 (1) ◽  
pp. 3
Author(s):  
Janette Hartz-Karp ◽  
Dora Marinova
Keyword(s):  
Decision Making ◽  
Case Studies ◽  
Deliberative Democracy ◽  
Decision Makers ◽  
Capital City ◽  
City Region ◽  
Multiple Sources ◽  
Trade Offs ◽  
Urban Issues ◽  
Sustainability Challenges

This article expands the evidence about integrative thinking by analyzing two case studies that applied the collaborative decision-making method of deliberative democracy which encourages representative, deliberative and influential public participation. The four-year case studies took place in Western Australia, (1) in the capital city Perth and surrounds, and (2) in the city-region of Greater Geraldton. Both aimed at resolving complex and wicked urban sustainability challenges as they arose. The analysis suggests that a new way of thinking, namely integrative thinking, emerged during the deliberations to produce operative outcomes for decision-makers. Building on theory and research demonstrating that deliberative designs lead to improved reasoning about complex issues, the two case studies show that through discourse based on deliberative norms, participants developed different mindsets, remaining open-minded, intuitive and representative of ordinary people’s basic common sense. This spontaneous appearance of integrative thinking enabled sound decision-making about complex and wicked sustainability-related urban issues. In both case studies, the participants exhibited all characteristics of integrative thinking to produce outcomes for decision-makers: salience—grasping the problems’ multiple aspects; causality—identifying multiple sources of impacts; sequencing—keeping the whole in view while focusing on specific aspects; and resolution—discovering novel ways that avoided bad choice trade-offs.

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