scholarly journals Primacy, Congruence and Confidence in Diagnostic Decision-Making

2020 ◽  
Author(s):  
Thomas F. Frotvedt ◽  
Øystein Bondevik ◽  
Vanessa T. Seeligmann ◽  
Bjørn Sætrevik
Keyword(s):  
Decision Making ◽  
Real Life ◽  
Primacy Effect ◽  
Symptom Presentation ◽  
Human Decision ◽  
Decision Making Processes ◽  
Complex Decision Making ◽  
Disconfirming Information ◽  
Diagnostic Decision Making

Some heuristics and biases are assumed to be universal for human decision-making, and may thus be expected to appear consistently and need to be considered when planning for real-life decision-making. Yet results are mixed when exploring the biases in applied settings, and few studies have attempted to robustly measure the combined impact of various biases during a decision-making process. We performed three pre-registered classroom experiments in which trained medical students read case descriptions and explored follow-up information in order to reach and adjust mental health diagnoses (∑N = 224). We tested whether the order of presenting the symptoms led to a primacy effect, whether there was a congruence bias in selecting follow-up questions, and whether confidence increased during the decision process. Our results showed increased confidence for participants that did not change their decision or sought disconfirming information. There was some indication of a weak congruence bias in selecting follow-up questions. There was no indication of a stronger congruence bias when confidence was high, and there was no support for a primacy effect of the order of symptom presentation. We conclude that the biases are difficult to demonstrate in pre-registered analyses of complex decision-making processes in applied settings.

Rxpert: A Prototype Expert System for Formulary Decision Making

1992 ◽  
Vol 26 (2) ◽  
pp. 244-250 ◽  
Author(s):  
Marianne L. Greer
Keyword(s):  
Decision Making ◽  
Expert System ◽  
Expert Systems ◽  
Knowledge Engineering ◽  
Drug Product ◽  
Computer Assisted ◽  
Health Related ◽  
Human Decision ◽  
Decision Making Processes ◽  
Complex Decision Making

OBJECTIVE: RXPERT, a prototype, computer-based, expert system that models the decision-making processes for an ambulatory (non-hospital) formulary, is described as an example of how expert systems may be used to support pharmacy decision making. Basic information about expert-system technology is provided through this example. BACKGROUND: Computer-assisted decision making is becoming an important and accepted aspect of complex, health-related decisions. Because expert-system support may become an integral component of future, complex, pharmacy decision making, it is important for pharmacists to become familiar with this technology and its possibilities for supporting pharmacy decisions. METHOD: Expert systems offer the potential advantages of making the human decision-making process explicit, more consistent, easily duplicated in many locations simultaneously, and easy to update and document. Although an expert system is seldom intended to replace human decision makers, it can provide valuable support for complex, multivariable decisions. Typical knowledge-acquisition and knowledge-engineering techniques, as well as the characteristics and structure of expert systems, are described, relative to the development of the RXPERT prototype. CONCLUSIONS: Although RXPERT is not yet in use, the process for using an expert system to support an individual committee member's personal assessment of a drug product is described. Decision-support expert systems are potentially useful to pharmacists in complex decision-making tasks.

Diagnostic Decision-Making Processes

2019 ◽  
pp. 79-85
Author(s):  
Julia Hodgson ◽  
Kevin Moore ◽  
Trisha Acri ◽  
Glenn Jordan Treisman
Keyword(s):  
Decision Making ◽  
Diagnostic Decision ◽  
Decision Making Processes ◽  
Diagnostic Decision Making

scholarly journals ЭФФЕКТИВНОСТЬ МЕТОДОВ ОПРЕДЕЛЕНИЯ ГРУППОВЫХ СИСТЕМ ПРЕДПОЧТЕНИЙ ДИСПЕТЧЕРОВ НА ОПАСНОСТИ ХАРАКТЕРНЫХ ОШИБОК, СОВЕРШАЕМЫХ В ПРОЦЕССЕ УПРАВЛЕНИЯ ВОЗДУШНЫМ ДВИЖЕНИЕМ

2018 ◽  
pp. 93-103
Author(s):  
Алексей Николаевич Рева ◽  
Шахин Шахвели-оглы Насиров ◽  
Бала Мушгюль-оглы Мирзоев
Keyword(s):  
Decision Making ◽  
Parametric Optimization ◽  
Professional Activity ◽  
Air Traffic Controllers ◽  
Main Emphasis ◽  
Decision Making Processes ◽  
Complex Decision Making ◽  
Coefficient Of Concordance ◽  
Complex Decision ◽  
Non Parametric

The human factor problem should be solved by identifying, qualifying and preventing the erroneous actions of the air traffic controllers. It is presented two schemes explaining the structure of human qualimetry factor and the interaction of the components of the ICAO safety concept, where the main emphasis is on an aviation personnel’ attitude to dangerous actions or conditions, which is revealed by the qualimetry of the decision-making processes’ characteristics: the attitude towards risk (the main dominants and fuzzy assessments), levels of claims, dangerous qualities and preferences systems. The preferences systems are considered as ordered characteristics and indicators of professional activity, which are subjectively compared with the positions of influence on flight safety. The spectrum of n = 21 characteristic errors was formed considering the recommendations of ICAO, EUROCONTROL and accident statistics. It is determined that procedures of collecting the information of errors danger contribute their recognition, memorization, and avoidance: controllers who passed the test according to the proposed method before training made by one third fewer errors in its process. Two criteria for assessing group preferences are realized: the level of consensus (known as Kendall’s coefficient of concordance) and the severity of the ranking, determined by the presence of "related" ranks, for which a special indicator is introduced. It is defined that this indicator should be determined both for the sample of respondents and for the preferences group systems of developed with the chosen method of individual opinions’ aggregation. It was performed the comparative analysis of complex decision-making strategies of effectiveness in the construction of a preferences group systems m = 65 controllers: sum and averaging of ranks, classical criteria (Wald's, Savage's and Laplace's criterion), optimal prediction, applying the non-parametric optimization of the preferences group systems. The non-parametric optimization of the group system of pre-readings was carried out by Kemeny median and it was proved that it was the closest to all the results obtained by other methods and strategies

Introduction and Historical Background

2019 ◽  
pp. 1-26
Keyword(s):  
Decision Making ◽  
Historical Development ◽  
Real Life ◽  
Literature Survey ◽  
Historical Background ◽  
Simultaneous Occurrence ◽  
Special Interests ◽  
Life Problems ◽  
Complex Decision Making ◽  
Complex Decision

This chapter describes the evolution of different multi-objective decision-making (MODM) models with their historical backgrounds. Starting from MODM models in deterministic environments along with various solution techniques, the chapter presents how different kinds of uncertainties may be associated with such decision-making models. Among several types of uncertainties, it has been found that probabilistic and possibilistic uncertainties are of special interests. A brief literature survey on different existing methods to solve those types of uncertainties, independently, is discussed and focuses on the need of considering simultaneous occurrence of those types of uncertainties in MODM contexts. Finally, a bibliographic survey on several approaches for MODM under hybrid fuzzy environments has been presented. Through this chapter the readers can be able to get some concepts about the historical development of MODM models in hybrid fuzzy environments and their importance in solving various real-life problems in the current complex decision-making arena.

Decision Making Approaches for Advanced Manufacturing Technology Evaluation and Selection

2012 ◽  
pp. 403-438 ◽  
Author(s):  
Aidé Maldonado-Macías ◽  
Jorge Luis García-Alcaraz ◽  
Francisco Javier Marrodan Esparza ◽  
Carlos Alberto Ochoa Ortiz Zezzatti
Keyword(s):  
Decision Making ◽  
Manufacturing Technology ◽  
Advanced Manufacturing Technology ◽  
Advanced Manufacturing ◽  
Manufacturing Companies ◽  
Decision Making Processes ◽  
Complex Decision Making ◽  
Broad Variety ◽  
Complex Decision ◽  
Selection Of

Advanced Manufacturing Technology (AMT) constitutes one of the most important resources of manufacturing companies to achieve success in an extremely competitive world. Decision making processes for the Evaluation and Selection of AMT in these companies must lead to the best alternative available. Industry is looking for a combination of flexibility and high quality by doing significant investments in AMT. The proliferation of this technology has generated a whole field of knowledge related to the design, evaluation and management of AMT systems which includes a broad variety of methodologies and applications. This chapter presents a theoretical review of the term AMT, its diverse classification and a collection of the most effective multi-attribute models and methodologies available to support these processes. Relevant advantages are found in these models since they can manage complex decision making problems which involve large amount of information and attributes. These attributes frequently can be tangible and intangible when vagueness and uncertainty exist. There are several multi-attribute methodologies which are extensively known and used in literature; nevertheless, a new fuzzy multi-attribute axiomatic design approach is explained for an ergonomic compatibility evaluation of AMT.

Decision Support Systems and Decision-Making Processes

2010 ◽  
pp. 135-143 ◽  
Author(s):  
Udo Richard Averweg
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Support Systems ◽  
Support Systems ◽  
Management Problem ◽  
Upper Management ◽  
Structured Problems ◽  
Decision Making Processes ◽  
Complex Decision Making ◽  
Computer Based

Decision support systems (DSS) deal with semi-structured problems. Such problems arise when managers in organisations are faced with decisions where some but not all aspects of a task or procedure are known. To solve these problems and use the results for decision-making requires judgement of the manager using the system. Typically such systems include models, data manipulation tools, and the ability to handle uncertainty and risk. These systems involve information and decision technology (Forgionne, 2003). Many organisations are turning to DSS to improve decision-making (Turban, McLean, & Wetherbe, 2004). This is a result of the conventional information systems (IS) not being sufficient to support an organisation’s critical response activities—especially those requiring fast and/or complex decision-making. In general, DSS are a broad category of IS (Power, 2003). A DSS is defined as “an interactive, flexible, and adaptable computer-based information system, specially developed for supporting the solution of a non-structured management problem for improved decision-making. It utilises data, it provides easy user interface, and it allows for the decision maker’s own insights” (Turban, 1995). There is a growing trend to provide managers with IS that can assist them in their most important task—making decisions. All levels of management can benefit from the use of DSS capabilities. The highest level of support is usually for middle and upper management (Sprague & Watson, 1996). The question of how a DSS supports decision-making processes will be described in this article. This article is organised as follows: The background to decisionmaking is introduced. The main focus (of this article) describes the development of the DSS field. Some future trends for the DSS field are then suggested. Thereafter a conclusion is given.

Decision Support Systems and Decision-Making Processes

2010 ◽  
pp. 218-224 ◽  
Author(s):  
Udo Richard Averweg
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Support Systems ◽  
Support Systems ◽  
Management Problem ◽  
Upper Management ◽  
Structured Problems ◽  
Decision Making Processes ◽  
Complex Decision Making ◽  
Computer Based

Decision support systems (DSS) deal with semi-structured problems. Such problems arise when managers in organisations are faced with decisions where some but not all aspects of a task or procedure are known. To solve these problems and use the results for decision-making requires judgement of the manager using the system. Typically such systems include models, data manipulation tools, and the ability to handle uncertainty and risk. These systems involve information and decision technology (Forgionne, 2003). Many organisations are turning to DSS to improve decision-making (Turban, McLean, & Wetherbe, 2004). This is a result of the conventional information systems (IS) not being sufficient to support an organisation’s critical response activities—especially those requiring fast and/or complex decision-making. In general, DSS are a broad category of IS (Power, 2003). A DSS is defined as “an interactive, flexible, and adaptable computer-based information system, specially developed for supporting the solution of a non-structured management problem for improved decision-making. It utilises data, it provides easy user interface, and it allows for the decision maker’s own insights” (Turban, 1995). There is a growing trend to provide managers with IS that can assist them in their most important task—making decisions. All levels of management can benefit from the use of DSS capabilities. The highest level of support is usually for middle and upper management (Sprague & Watson, 1996). The question of how a DSS supports decision-making processes will be described in this article. This article is organised as follows: The background to decisionmaking is introduced. The main focus (of this article) describes the development of the DSS field. Some future trends for the DSS field are then suggested. Thereafter a conclusion is given.

Defining the Phenomenon of Mental Models for Critical Events

2013 ◽  
Author(s):  
Kanter van Deurzen ◽  
Imre Horváth ◽  
Regine Vroom
Keyword(s):  
Decision Making ◽  
Mental Models ◽  
Mental Model ◽  
Real Life ◽  
Critical Events ◽  
Cognitive Representations ◽  
Related Information ◽  
Strong Relation ◽  
Decision Making Processes ◽  
Definition Of

People use cognitive representations in order to characterize, understand, reason and predict the surrounding world. A class of these representations are called mental models. Designers of informing systems are interested in how mental models influence decision making, especially during critical events. With this knowledge they could optimize the content and amount of information that is needed for a dependable decision making process. New insights are needed about the operation of mental models in the course of critical events, as well as on how informing influences the real life operationalization of mental models. Most of the definitions available in the literature are overly general, and no definition was found that would support the design of informing systems for critical events. Therefore, the objective of our research was to derive a definition of mental models that play a role in critical events. Actually, we systematically constructed a definition from those attributes of mental model descriptions that were found to be relevant to critical events. First we decomposed 125 published descriptions to a set of attributes, and then assessed each attribute to see if they were associated with critical events, or not. In fact, this analysis involved not only the relevance of the attributes to critical events, but also the frequency of occurrence in the surveyed papers. This exploration provided a large number of attributes for a new mental model definition. Based on the top rated attributes, a definition was synthesized which, theoretically, has a strong relation to critical events. Though further validation will be needed, we argue that the derived mental model definition is strong because it establishes relationships with all generic features of critical events and makes the related information contents explicit. Hence the proposed definition can be considered a starting platform for investigations of the influence of informing on decision making processes in critical events.

scholarly journals Using a coupled agent-based modeling approach to analyze the role of risk perception in water management decisions

2019 ◽  
Vol 23 (5) ◽  
pp. 2261-2278 ◽  
Author(s):  
Jin-Young Hyun ◽  
Shih-Yu Huang ◽  
Yi-Chen Ethan Yang ◽  
Vincent Tidwell ◽  
Jordan Macknick
Keyword(s):  
Decision Making ◽  
Risk Perception ◽  
Regional Scale ◽  
Agent Based ◽  
Natural Processes ◽  
Complex Adaptive ◽  
San Juan River ◽  
Human Decision ◽  
Decision Making Processes ◽  
Engineered Systems

Abstract. Managing water resources in a complex adaptive natural–human system is a challenge due to the difficulty of modeling human behavior under uncertain risk perception. The interaction between human-engineered systems and natural processes needs to be modeled explicitly with an approach that can quantify the influence of incomplete/ambiguous information on decision-making processes. In this study, we two-way coupled an agent-based model (ABM) with a river-routing and reservoir management model (RiverWare) to address this challenge. The human decision-making processes is described in the ABM using Bayesian inference (BI) mapping joined with a cost–loss (CL) model (BC-ABM). Incorporating BI mapping into an ABM allows an agent's psychological thinking process to be specified by a cognitive map between decisions and relevant preceding factors that could affect decision-making. A risk perception parameter is used in the BI mapping to represent an agent's belief on the preceding factors. Integration of the CL model addresses an agent's behavior caused by changing socioeconomic conditions. We use the San Juan River basin in New Mexico, USA, to demonstrate the utility of this method. The calibrated BC-ABM–RiverWare model is shown to capture the dynamics of historical irrigated area and streamflow changes. The results suggest that the proposed BC-ABM framework provides an improved representation of human decision-making processes compared to conventional rule-based ABMs that do not take risk perception into account. Future studies will focus on modifying the BI mapping to consider direct agents' interactions, up-front cost of agent's decision, and upscaling the watershed ABM to the regional scale.

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