Characterization of Decision-Making Deficits in Adolescence

2003 ◽  
Author(s):  
Dustin Wahlstrom
Keyword(s):  
Decision Making

Exploring the Differences in Macrocognition Between Experts and Non-CHD Experts Managing Congenital Heart Disease (CHD)

2021 ◽  
Vol 10 (1) ◽  
pp. 335-339
Author(s):  
Azadeh Assadi ◽  
Peter C. Laussen ◽  
Patricia Trbovich
Keyword(s):  
Decision Making ◽  
Emergency Medicine ◽  
Congenital Heart Disease ◽  
Heart Disease ◽  
Congenital Heart ◽  
Pediatric Emergency ◽  
Acute Management ◽  
Naturalistic Decision Making ◽  
The Face

Background and aims: Children with congenital heart disease (CHD) are at risk of deterioration in the face of common childhood illnesses, and their resuscitation and acute management is often best achieved with the guidance of CHD experts. Access to such expertise may be limited outside specialty heart centers and the fragility of these patients is cause for discomfort among many emergency medicine physicians. An understanding of the differences in macrocognition of these clinicians could shed light on some of the causes of discomfort and facilitate the development of a sociotechnological solution to this problem. Methods: Cardiac intensivists (CHD experts) and pediatric emergency medicine physicians (non-CHD experts) in a major academic cardiac center were interviewed using the critical decision method. Interview transcripts were coded deductively based on Klein’s macrocognitive framework and inductively to allow for new or modified characterization of dimensions. Results: While both CHD-experts and non-CHD experts relied on the macrocognitive functions of sensemaking, naturalistic decision making and detecting problems, the specific data and mental models used to understand the patients and course of therapy differed between CHD-experts and non-CHD experts. Conclusion: Characterization of differences between the macrocognitive processes of CHD experts and non-CHD experts can inform development of sociotechnological solutions to augment decision making pertaining to the acute management of pediatric CHD patients.

scholarly journals Characterization of Kentucky dairy producer decision-making behavior

2013 ◽  
Vol 96 (7) ◽  
pp. 4751-4758 ◽  
Author(s):  
R.A. Russell ◽  
J.M. Bewley
Keyword(s):  
Decision Making ◽  
Decision Making Behavior

Overview

2021 ◽  
pp. 11-26
Author(s):  
Elvira Silva ◽  
Spiro E. Stefanou ◽  
Alfons Oude Lansink
Keyword(s):  
Decision Making ◽  
Transaction Costs ◽  
Capital Stock ◽  
Adjustment Costs ◽  
Dynamic Structure ◽  
Dynamic Decision Making ◽  
Rapid Rate ◽  
Absolute Rate ◽  
Decision Environment

This chapter characterizes production in a dynamic decision-making environment. The classic characterization of static firm decision making is contrasted with the dynamic decision environment where not all inputs are freely adjusted. The latter characterization is motivated by the conjecture that transaction costs are associated with adjusting the capital stock at a rapid rate per unit of time and these costs increase rapidly with the absolute rate of investment. In fact, these costs increase so rapidly that the firm may never attempt to achieve a jump in its capital stock at any given moment. Such transaction (or adjustment) costs have implications for the nature of the technology. This interplay is introduced in this chapter and serves as a foundation for the dynamic structure that follows throughout the book.

scholarly journals How Many Urine Samples Are Needed to Accurately Assess Exposure to Non-Persistent Chemicals? The Biomarker Reliability Assessment Tool (BRAT) for Scientists, Research Sponsors, and Risk Managers

2020 ◽  
Vol 17 (23) ◽  
pp. 9102
Author(s):  
Marc-André Verner ◽  
Hassan Salame ◽  
Conrad Housand ◽  
Linda S. Birnbaum ◽  
Maryse F. Bouchard ◽  
...  
Keyword(s):  
Decision Making ◽  
Monte Carlo ◽  
Human Exposure ◽  
Assessment Tool ◽  
Reliability Assessment ◽  
Population Based ◽  
Environmental Chemicals ◽  
Urine Samples ◽  
Risk Managers

In epidemiologic and exposure research, biomonitoring is often used as the basis for assessing human exposure to environmental chemicals. Studies frequently rely on a single urinary measurement per participant to assess exposure to non-persistent chemicals. However, there is a growing consensus that single urine samples may be insufficient for adequately estimating exposure. The question then arises: how many samples would be needed for optimal characterization of exposure? To help researchers answer this question, we developed a tool called the Biomarker Reliability Assessment Tool (BRAT). The BRAT is based on pharmacokinetic modeling simulations, is freely available, and is designed to help researchers determine the approximate number of urine samples needed to optimize exposure assessment. The BRAT performs Monte Carlo simulations of exposure to estimate internal levels and resulting urinary concentrations in individuals from a population based on user-specified inputs (e.g., biological half-life, within- and between-person variability in exposure). The BRAT evaluates—through linear regression and quantile classification—the precision/accuracy of the estimation of internal levels depending on the number of urine samples. This tool should guide researchers towards more robust biomonitoring and improved exposure classification in epidemiologic and exposure research, which should in turn improve the translation of that research into decision-making.

Perspectives on Decision Analysis for Decision Support System Design

1993 ◽  
Vol 37 (16) ◽  
pp. 1101-1101 ◽  
Author(s):  
Barbara J. Barnett
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Support System ◽  
System Design ◽  
Support System ◽  
Information Organization ◽  
Human Decision ◽  
Tactical Decision ◽  
Decision Making Behavior

This symposium addresses the characterization of human decision making within a complex environment for the purpose of developing improved decision support systems. All of the work presented in this symposium was conducted under a Navy research program entitled “Tactical Decision Making Under Stress” (TADMUS). The overall objective of the TADMUS program is to improve tactical decision making of anti-air warfare (AAW) crew members within the Aegis cruiser's combat information center (CIC) under conditions of stress and uncertainty. The unique aspect of this effort is that each presentation addresses decision making behavior, within a single domain, from a different perspective. The goal of each effort is to characterize some aspect of expert decision making performance within the AAW task environment, and to make recommendations for the resulting decision support system design based upon these characterizations. The result is a multi-faceted, human-centered approach to information organization and interface display design for a decision support system.

scholarly journals Jury Verdicts and Preference Diversity

2000 ◽  
Vol 94 (2) ◽  
pp. 395-406 ◽  
Author(s):  
Dino Gerardi
Keyword(s):  
Decision Making ◽  
Equilibrium Strategy ◽  
Correct Decision ◽  
Unanimity Rule ◽  
Voting Rule ◽  
Jury Verdicts ◽  
Asymptotically Efficient

I develop a model of decision making in juries when there is uncertainty about jurors' preferences. I provide a characterization of the equilibrium strategy under any voting rule and show that nonunanimous rules are asymptotically efficient. Specifically, large juries make the correct decision with probability close to one. My analysis also demonstrates that under the unanimous rule, large juries almost never convict the defendant. The last result contrasts markedly with the literature and suggests that the unanimity rule can protect the innocent only at the price of acquitting the guilty.

PATHWAY REGULATORY ANALYSIS IN THE CONTEXT OF BAYESIAN NETWORKS USING THE COEFFICIENT OF DETERMINATION

2011 ◽  
Vol 19 (04) ◽  
pp. 651-682 ◽  
Author(s):  
CHEN ZHAO ◽  
IVAN IVANOV ◽  
MICHAEL L. BITTNER ◽  
EDWARD R. DOUGHERTY
Keyword(s):  
Decision Making ◽  
Bayesian Networks ◽  
Network Structure ◽  
Signal Transmission ◽  
Coefficient Of Determination ◽  
Tree Model ◽  
Cellular Decision Making ◽  
Sufficient Detail ◽  
Regulatory Analysis

To effectively intervene when cells are trapped in pathological modes of operation it is necessary to build models that capture relevant network structure and include characterization of dynamical changes within the system. The model must be of sufficient detail that it facilitates the selection of intervention points where pathological cell behavior arising from improper regulation can be stopped. What is known about this type of cellular decision-making is consistent with the general expectations associated with any kind of decision-making operation. If the result of a decision at one node is serially transmitted to other nodes, resetting their states, then the process may suffer from mechanistic inefficiencies of transmission or from blockage or activation of transmission through the action of other nodes acting on the same node. A standard signal-processing network model, Bayesian networks, can model these properties. This paper employs a Bayesian tree model to characterize conditional pathway logic and quantify the effects of different branching patterns, signal transmission efficiencies and levels of alternate or redundant inputs. In particular, it characterizes master genes and canalizing genes within the quantitative framework. The model is also used to examine what inferences about the network structure can be made when perturbations are applied to various points in the network.

scholarly journals Implementación del método de aprendizaje activo y colaborativo en las prácticas de laboratorio de Materiales Ecoeficientes en modalidad virtual

2021 ◽  
Author(s):  
Cristina Pavon ◽  
Miguel Aldas ◽  
Maria Dolores Samper ◽  
Juan López-Martínez
Keyword(s):  
Decision Making ◽  
Collaborative Learning ◽  
Laboratory Practice ◽  
Face To Face ◽  
Active And Collaborative Learning ◽  
Second Year ◽  
Characterization Of Materials ◽  
The University ◽  
Academic Year

During the 2020/21 academic year, the active and collaborative learning methodology was implemented in the development of a laboratory practice of the Eco-efficient Materials course of the second year of the University Master's Degree in Engineering, Processing and Characterization of Materials, in virtual modality. The use of this methodology aims to promote student participation and increase their level of responsibility in the laboratory practice, making use of the advantages of a virtual modality. Before carrying out the practice, students were given a script and then an explanatory session and resolution of doubts was held. The practices were carried out in a virtual and synchronous way. The students were responsible for setting the parameters and the teacher was in charge of reproducing them in the laboratory. The objective of this work was to observe the behavior of the students in decision-making, to appreciate if they acquired the necessary knowledge for the development of the practice and to solve the problems that may arise during it. Subsequently, the learning methodology between a virtual and a face-to-face modality was compared, and an active and collaborative learning methodology was developed that can be applied in either of the two scenarios.

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