Application of the Consumer Decision-Making Model to Hearing Aid Adoption in First-Time Users

PubMed Central

Amlani, Amyn M.

2016-01-01

Since 1980, hearing aid adoption rates have remained essentially the same, increasing at a rate equal to the organic growth of the population. Researchers have used theoretical models from psychology and sociology to determine those factors or constructs that lead to the adoption of hearing aids by first-time impaired listeners entering the market. In this article, a theoretical model, the Consumer Decision-Making Model (CDM), premised on the neobehavioral approach that considers an individual's psychological and cognitive emphasis toward a product or service, is described. Three theoretical models (i.e., transtheoretical, social model of disability, Health Belief Model), and their relevant findings to the hearing aid market, are initially described. The CDM is then presented, along with supporting evidence of the model's various factors from the hearing aid literature. Future applications of the CDM to hearing health care also are discussed. PMID:27516718

Application of the Consumer Decision-Making Model to Hearing Aid Adoption in First-Time Users.

PubMed

Amlani, Amyn M

2016-05-01

Since 1980, hearing aid adoption rates have remained essentially the same, increasing at a rate equal to the organic growth of the population. Researchers have used theoretical models from psychology and sociology to determine those factors or constructs that lead to the adoption of hearing aids by first-time impaired listeners entering the market. In this article, a theoretical model, the Consumer Decision-Making Model (CDM), premised on the neobehavioral approach that considers an individual's psychological and cognitive emphasis toward a product or service, is described. Three theoretical models (i.e., transtheoretical, social model of disability, Health Belief Model), and their relevant findings to the hearing aid market, are initially described. The CDM is then presented, along with supporting evidence of the model's various factors from the hearing aid literature. Future applications of the CDM to hearing health care also are discussed.

Decisons To Promote or Hire: The Case of University Administrative Appointments. ASHE Annual Meeting Paper.

ERIC Educational Resources Information Center

Johnsrud, Linda K.; Sagaria, Mary Ann D.

Internal labor market theory is extended to identify market domains that influence administrative staffing decisions, and a theoretical predictive model about the role of market domains in decisions to promote or hire is proposed and tested. Information is presented as follows: theoretical framework; labor markets within higher education; and the…

The perfect family: decision making in biparental care.

PubMed

Akçay, Erol; Roughgarden, Joan

2009-10-13

Previous theoretical work on parental decisions in biparental care has emphasized the role of the conflict between evolutionary interests of parents in these decisions. A prominent prediction from this work is that parents should compensate for decreases in each other's effort, but only partially so. However, experimental tests that manipulate parents and measure their responses fail to confirm this prediction. At the same time, the process of parental decision making has remained unexplored theoretically. We develop a model to address the discrepancy between experiments and the theoretical prediction, and explore how assuming different decision making processes changes the prediction from the theory. We assume that parents make decisions in behavioral time. They have a fixed time budget, and allocate it between two parental tasks: provisioning the offspring and defending the nest. The proximate determinant of the allocation decisions are parents' behavioral objectives. We assume both parents aim to maximize the offspring production from the nest. Experimental manipulations change the shape of the nest production function. We consider two different scenarios for how parents make decisions: one where parents communicate with each other and act together (the perfect family), and one where they do not communicate, and act independently (the almost perfect family). The perfect family model is able to generate all the types of responses seen in experimental studies. The kind of response predicted depends on the nest production function, i.e. how parents' allocations affect offspring production, and the type of experimental manipulation. In particular, we find that complementarity of parents' allocations promotes matching responses. In contrast, the relative responses do not depend on the type of manipulation in the almost perfect family model. These results highlight the importance of the interaction between nest production function and how parents make decisions, factors that have largely been overlooked in previous models.

Nash Equilibria in Theory of Reasoned Action

NASA Astrophysics Data System (ADS)

Almeida, Leando; Cruz, José; Ferreira, Helena; Pinto, Alberto Adrego

2009-08-01

Game theory and Decision Theory have been applied to many different areas such as Physics, Economics, Biology, etc. In its application to Psychology, we introduce, in the literature, a Game Theoretical Model of Planned Behavior or Reasoned Action by establishing an analogy between two specific theories. In this study we take in account that individual decision-making is an outcome of a process where group decisions can determine individual probabilistic behavior. Using Game Theory concepts, we describe how intentions can be transformed in behavior and according to the Nash Equilibrium, this process will correspond to the best individual decision/response taking in account the collective response. This analysis can be extended to several examples based in the Game Theoretical Model of Planned Behavior or Reasoned Action.

Exploring complex dynamics in multi agent-based intelligent systems: Theoretical and experimental approaches using the Multi Agent-based Behavioral Economic Landscape (MABEL) model

NASA Astrophysics Data System (ADS)

Alexandridis, Konstantinos T.

This dissertation adopts a holistic and detailed approach to modeling spatially explicit agent-based artificial intelligent systems, using the Multi Agent-based Behavioral Economic Landscape (MABEL) model. The research questions that addresses stem from the need to understand and analyze the real-world patterns and dynamics of land use change from a coupled human-environmental systems perspective. Describes the systemic, mathematical, statistical, socio-economic and spatial dynamics of the MABEL modeling framework, and provides a wide array of cross-disciplinary modeling applications within the research, decision-making and policy domains. Establishes the symbolic properties of the MABEL model as a Markov decision process, analyzes the decision-theoretic utility and optimization attributes of agents towards comprising statistically and spatially optimal policies and actions, and explores the probabilogic character of the agents' decision-making and inference mechanisms via the use of Bayesian belief and decision networks. Develops and describes a Monte Carlo methodology for experimental replications of agent's decisions regarding complex spatial parcel acquisition and learning. Recognizes the gap on spatially-explicit accuracy assessment techniques for complex spatial models, and proposes an ensemble of statistical tools designed to address this problem. Advanced information assessment techniques such as the Receiver-Operator Characteristic curve, the impurity entropy and Gini functions, and the Bayesian classification functions are proposed. The theoretical foundation for modular Bayesian inference in spatially-explicit multi-agent artificial intelligent systems, and the ensembles of cognitive and scenario assessment modular tools build for the MABEL model are provided. Emphasizes the modularity and robustness as valuable qualitative modeling attributes, and examines the role of robust intelligent modeling as a tool for improving policy-decisions related to land use change. Finally, the major contributions to the science are presented along with valuable directions for future research.

Role of Travel Motivations, Perceived Risks and Travel Constraints on Destination Image and Visit Intention in Medical Tourism: Theoretical model.

PubMed

Khan, Mohammad J; Chelliah, Shankar; Haron, Mahmod S; Ahmed, Sahrish

2017-02-01

Travel motivations, perceived risks and travel constraints, along with the attributes and characteristics of medical tourism destinations, are important issues in medical tourism. Although the importance of these factors is already known, a comprehensive theoretical model of the decision-making process of medical tourists has yet to be established, analysing the intricate relationships between the different variables involved. This article examines a large body of literature on both medical and conventional tourism in order to propose a comprehensive theoretical framework of medical tourism decision-making. Many facets of this complex phenomenon require further empirical investigation.

An EGR performance evaluation and decision-making approach based on grey theory and grey entropy analysis

PubMed Central

2018-01-01

Exhaust gas recirculation (EGR) is one of the main methods of reducing NOX emissions and has been widely used in marine diesel engines. This paper proposes an optimized comprehensive assessment method based on multi-objective grey situation decision theory, grey relation theory and grey entropy analysis to evaluate the performance and optimize rate determination of EGR, which currently lack clear theoretical guidance. First, multi-objective grey situation decision theory is used to establish the initial decision-making model according to the main EGR parameters. The optimal compromise between diesel engine combustion and emission performance is transformed into a decision-making target weight problem. After establishing the initial model and considering the characteristics of EGR under different conditions, an optimized target weight algorithm based on grey relation theory and grey entropy analysis is applied to generate the comprehensive evaluation and decision-making model. Finally, the proposed method is successfully applied to a TBD234V12 turbocharged diesel engine, and the results clearly illustrate the feasibility of the proposed method for providing theoretical support and a reference for further EGR optimization. PMID:29377956

An EGR performance evaluation and decision-making approach based on grey theory and grey entropy analysis.

PubMed

Zu, Xianghuan; Yang, Chuanlei; Wang, Hechun; Wang, Yinyan

2018-01-01

Exhaust gas recirculation (EGR) is one of the main methods of reducing NOX emissions and has been widely used in marine diesel engines. This paper proposes an optimized comprehensive assessment method based on multi-objective grey situation decision theory, grey relation theory and grey entropy analysis to evaluate the performance and optimize rate determination of EGR, which currently lack clear theoretical guidance. First, multi-objective grey situation decision theory is used to establish the initial decision-making model according to the main EGR parameters. The optimal compromise between diesel engine combustion and emission performance is transformed into a decision-making target weight problem. After establishing the initial model and considering the characteristics of EGR under different conditions, an optimized target weight algorithm based on grey relation theory and grey entropy analysis is applied to generate the comprehensive evaluation and decision-making model. Finally, the proposed method is successfully applied to a TBD234V12 turbocharged diesel engine, and the results clearly illustrate the feasibility of the proposed method for providing theoretical support and a reference for further EGR optimization.

A Feedback Learning and Mental Models Perspective on Strategic Decision Making

ERIC Educational Resources Information Center

Capelo, Carlos; Dias, Joao Ferreira

2009-01-01

This study aims to be a contribution to a theoretical model that explains the effectiveness of the learning and decision-making processes by means of a feedback and mental models perspective. With appropriate mental models, managers should be able to improve their capacity to deal with dynamically complex contexts, in order to achieve long-term…

Overcoming Indecision by Changing the Decision Boundary

PubMed Central

2017-01-01

The dominant theoretical framework for decision making asserts that people make decisions by integrating noisy evidence to a threshold. It has recently been shown that in many ecologically realistic situations, decreasing the decision boundary maximizes the reward available from decisions. However, empirical support for decreasing boundaries in humans is scant. To investigate this problem, we used an ideal observer model to identify the conditions under which participants should change their decision boundaries with time to maximize reward rate. We conducted 6 expanded-judgment experiments that precisely matched the assumptions of this theoretical model. In this paradigm, participants could sample noisy, binary evidence presented sequentially. Blocks of trials were fixed in duration, and each trial was an independent reward opportunity. Participants therefore had to trade off speed (getting as many rewards as possible) against accuracy (sampling more evidence). Having access to the actual evidence samples experienced by participants enabled us to infer the slope of the decision boundary. We found that participants indeed modulated the slope of the decision boundary in the direction predicted by the ideal observer model, although we also observed systematic deviations from optimality. Participants using suboptimal boundaries do so in a robust manner, so that any error in their boundary setting is relatively inexpensive. The use of a normative model provides insight into what variable(s) human decision makers are trying to optimize. Furthermore, this normative model allowed us to choose diagnostic experiments and in doing so we present clear evidence for time-varying boundaries. PMID:28406682

Probabilistic sensitivity analysis incorporating the bootstrap: an example comparing treatments for the eradication of Helicobacter pylori.

PubMed

Pasta, D J; Taylor, J L; Henning, J M

1999-01-01

Decision-analytic models are frequently used to evaluate the relative costs and benefits of alternative therapeutic strategies for health care. Various types of sensitivity analysis are used to evaluate the uncertainty inherent in the models. Although probabilistic sensitivity analysis is more difficult theoretically and computationally, the results can be much more powerful and useful than deterministic sensitivity analysis. The authors show how a Monte Carlo simulation can be implemented using standard software to perform a probabilistic sensitivity analysis incorporating the bootstrap. The method is applied to a decision-analytic model evaluating the cost-effectiveness of Helicobacter pylori eradication. The necessary steps are straightforward and are described in detail. The use of the bootstrap avoids certain difficulties encountered with theoretical distributions. The probabilistic sensitivity analysis provided insights into the decision-analytic model beyond the traditional base-case and deterministic sensitivity analyses and should become the standard method for assessing sensitivity.

Factors Influencing the Performance of Dynamic Decision Network for INQPRO

ERIC Educational Resources Information Center

Ting, Choo-Yee; Phon-Amnuaisuk, Somnuk

2009-01-01

There has been an increasing interest in employing decision-theoretic framework for learner modeling and provision of pedagogical support in Intelligent Tutoring Systems (ITSs). Much of the existing learner modeling research work focuses on identifying appropriate learner properties. Little attention, however, has been given to leverage Dynamic…

Game theoretic analysis of physical protection system design

DOE Office of Scientific and Technical Information (OSTI.GOV)

Canion, B.; Schneider, E.; Bickel, E.

The physical protection system (PPS) of a fictional small modular reactor (SMR) facility have been modeled as a platform for a game theoretic approach to security decision analysis. To demonstrate the game theoretic approach, a rational adversary with complete knowledge of the facility has been modeled attempting a sabotage attack. The adversary adjusts his decisions in response to investments made by the defender to enhance the security measures. This can lead to a conservative physical protection system design. Since defender upgrades were limited by a budget, cost benefit analysis may be conducted upon security upgrades. One approach to cost benefitmore » analysis is the efficient frontier, which depicts the reduction in expected consequence per incremental increase in the security budget.« less

Ethics and rationality in information-enriched decisions: A model for technical communication

NASA Astrophysics Data System (ADS)

Dressel, S. B.; Carlson, P.; Killingsworth, M. J.

1993-12-01

In a technological culture, information has a crucial impact upon decisions, but exactly how information plays into decisions is not always clear. Decisions that are effective, efficient, and ethical must be rational. That is, we must be able to determine and present good reasons for our actions. The topic in this paper is how information relates to good reasons and thereby affects the best decisions. A brief sketch of a model for decision-making, is presented which offers a synthesis of theoretical approaches to argument and to information analysis. Then the model is applied to a brief hypothetical case. The main purpose is to put the model before an interested audience in hopes of stimulating discussion and further research.

Conflicts of interest improve collective computation of adaptive social structures

PubMed Central

Brush, Eleanor R.; Krakauer, David C.; Flack, Jessica C.

2018-01-01

In many biological systems, the functional behavior of a group is collectively computed by the system’s individual components. An example is the brain’s ability to make decisions via the activity of billions of neurons. A long-standing puzzle is how the components’ decisions combine to produce beneficial group-level outputs, despite conflicts of interest and imperfect information. We derive a theoretical model of collective computation from mechanistic first principles, using results from previous work on the computation of power structure in a primate model system. Collective computation has two phases: an information accumulation phase, in which (in this study) pairs of individuals gather information about their fighting abilities and make decisions about their dominance relationships, and an information aggregation phase, in which these decisions are combined to produce a collective computation. To model information accumulation, we extend a stochastic decision-making model—the leaky integrator model used to study neural decision-making—to a multiagent game-theoretic framework. We then test alternative algorithms for aggregating information—in this study, decisions about dominance resulting from the stochastic model—and measure the mutual information between the resultant power structure and the “true” fighting abilities. We find that conflicts of interest can improve accuracy to the benefit of all agents. We also find that the computation can be tuned to produce different power structures by changing the cost of waiting for a decision. The successful application of a similar stochastic decision-making model in neural and social contexts suggests general principles of collective computation across substrates and scales. PMID:29376116

Helping Health Care Providers and Clinical Scientists Understand Apparently Irrational Policy Decisions.

PubMed

Demeter, Sandor J

2016-12-21

Health care providers (HCP) and clinical scientists (CS) are generally most comfortable using evidence-based rational decision-making models. They become very frustrated when policymakers make decisions that, on the surface, seem irrational and unreasonable. However, such decisions usually make sense when analysed properly. The goal of this paper to provide a basic theoretical understanding of major policy models, to illustrate which models are most prevalent in publicly funded health care systems, and to propose a policy analysis framework to better understand the elements that drive policy decision-making. The proposed policy framework will also assist HCP and CS achieve greater success with their own proposals.

Occupational Decision-Related Processes for Amotivated Adolescents: Confirmation of a Model

ERIC Educational Resources Information Center

Jung, Jae Yup; McCormick, John

2011-01-01

This study developed and (statistically) confirmed a new model of the occupational decision-related processes of adolescents, in terms of the extent to which they may be amotivated about choosing a future occupation. A theoretical framework guided the study. A questionnaire that had previously been administered to an Australian adolescent sample…

How do small groups make decisions? : A theoretical framework to inform the implementation and study of clinical competency committees.

PubMed

Chahine, Saad; Cristancho, Sayra; Padgett, Jessica; Lingard, Lorelei

2017-06-01

In the competency-based medical education (CBME) approach, clinical competency committees are responsible for making decisions about trainees' competence. However, we currently lack a theoretical model for group decision-making to inform this emerging assessment phenomenon. This paper proposes an organizing framework to study and guide the decision-making processes of clinical competency committees.This is an explanatory, non-exhaustive review, tailored to identify relevant theoretical and evidence-based papers related to small group decision-making. The search was conducted using Google Scholar, Web of Science, MEDLINE, ERIC, and PsycINFO for relevant literature. Using a thematic analysis, two researchers (SC & JP) met four times between April-June 2016 to consolidate the literature included in this review.Three theoretical orientations towards group decision-making emerged from the review: schema, constructivist, and social influence. Schema orientations focus on how groups use algorithms for decision-making. Constructivist orientations focus on how groups construct their shared understanding. Social influence orientations focus on how individual members influence the group's perspective on a decision. Moderators of decision-making relevant to all orientations include: guidelines, stressors, authority, and leadership.Clinical competency committees are the mechanisms by which groups of clinicians will be in charge of interpreting multiple assessment data points and coming to a shared decision about trainee competence. The way in which these committees make decisions can have huge implications for trainee progression and, ultimately, patient care. Therefore, there is a pressing need to build the science of how such group decision-making works in practice. This synthesis suggests a preliminary organizing framework that can be used in the implementation and study of clinical competency committees.

Optimal policy for value-based decision-making.

PubMed

Tajima, Satohiro; Drugowitsch, Jan; Pouget, Alexandre

2016-08-18

For decades now, normative theories of perceptual decisions, and their implementation as drift diffusion models, have driven and significantly improved our understanding of human and animal behaviour and the underlying neural processes. While similar processes seem to govern value-based decisions, we still lack the theoretical understanding of why this ought to be the case. Here, we show that, similar to perceptual decisions, drift diffusion models implement the optimal strategy for value-based decisions. Such optimal decisions require the models' decision boundaries to collapse over time, and to depend on the a priori knowledge about reward contingencies. Diffusion models only implement the optimal strategy under specific task assumptions, and cease to be optimal once we start relaxing these assumptions, by, for example, using non-linear utility functions. Our findings thus provide the much-needed theory for value-based decisions, explain the apparent similarity to perceptual decisions, and predict conditions under which this similarity should break down.

Optimal policy for value-based decision-making

PubMed Central

Tajima, Satohiro; Drugowitsch, Jan; Pouget, Alexandre

2016-01-01

For decades now, normative theories of perceptual decisions, and their implementation as drift diffusion models, have driven and significantly improved our understanding of human and animal behaviour and the underlying neural processes. While similar processes seem to govern value-based decisions, we still lack the theoretical understanding of why this ought to be the case. Here, we show that, similar to perceptual decisions, drift diffusion models implement the optimal strategy for value-based decisions. Such optimal decisions require the models' decision boundaries to collapse over time, and to depend on the a priori knowledge about reward contingencies. Diffusion models only implement the optimal strategy under specific task assumptions, and cease to be optimal once we start relaxing these assumptions, by, for example, using non-linear utility functions. Our findings thus provide the much-needed theory for value-based decisions, explain the apparent similarity to perceptual decisions, and predict conditions under which this similarity should break down. PMID:27535638

Research on Bidding Decision-making of International Public-Private Partnership Projects

NASA Astrophysics Data System (ADS)

Hu, Zhen Yu; Zhang, Shui Bo; Liu, Xin Yan

2018-06-01

In order to select the optimal quasi-bidding project for an investment enterprise, a bidding decision-making model for international PPP projects was established in this paper. Firstly, the literature frequency statistics method was adopted to screen out the bidding decision-making indexes, and accordingly the bidding decision-making index system for international PPP projects was constructed. Then, the group decision-making characteristic root method, the entropy weight method, and the optimization model based on least square method were used to set the decision-making index weights. The optimal quasi-bidding project was thus determined by calculating the consistent effect measure of each decision-making index value and the comprehensive effect measure of each quasi-bidding project. Finally, the bidding decision-making model for international PPP projects was further illustrated by a hypothetical case. This model can effectively serve as a theoretical foundation and technical support for the bidding decision-making of international PPP projects.

Fitting observed and theoretical choices - women's choices about prenatal diagnosis of Down syndrome.

PubMed

Seror, Valerie

2008-05-01

Choices regarding prenatal diagnosis of Down syndrome - the most frequent chromosomal defect - are particularly relevant to decision analysis, since women's decisions are based on the assessment of their risk of carrying a child with Down syndrome, and involve tradeoffs (giving birth to an affected child vs procedure-related miscarriage). The aim of this study, based on face-to-face interviews with 78 women aged 25-35 with prior experience of pregnancy, was to compare the women' expressed choices towards prenatal diagnosis with those derived from theoretical models of choice (expected utility theory, rank-dependent theory, and cumulative prospect theory). The main finding obtained in this study was that the cumulative prospect model fitted the observed choices best: both subjective transformation of probabilities and loss aversion, which are basic features of the cumulative prospect model, have to be taken into account to make the observed choices consistent with the theoretical ones.

Assessment of credit risk based on fuzzy relations

NASA Astrophysics Data System (ADS)

Tsabadze, Teimuraz

2017-06-01

The purpose of this paper is to develop a new approach for an assessment of the credit risk to corporate borrowers. There are different models for borrowers' risk assessment. These models are divided into two groups: statistical and theoretical. When assessing the credit risk for corporate borrowers, statistical model is unacceptable due to the lack of sufficiently large history of defaults. At the same time, we cannot use some theoretical models due to the lack of stock exchange. In those cases, when studying a particular borrower given that statistical base does not exist, the decision-making process is always of expert nature. The paper describes a new approach that may be used in group decision-making. An example of the application of the proposed approach is given.

Three Cases of Adolescent Childbearing Decision-Making: The Importance of Ambivalence

ERIC Educational Resources Information Center

Bender, Soley S.

2008-01-01

Limited information is available about the childbearing decision-making experience by the pregnant adolescent. The purpose of this case study was to explore this experience with three pregnant teenagers. The study is based on nine qualitative interviews. Within-case descriptions applying the theoretical model of decision-making regarding unwanted…

Anxiety: towards a decision-theoretic perspective.

PubMed

Shechter, M; Zeidner, M

1990-05-01

This paper sets out to illustrate how anxiety may be incorporated into a formal decision theoretic utility model of choice, and to suggest several measurement procedures towards that end. The major propositions derived and posited in this paper lend considerable support to intuitive notions with respect to the effects of anxiety on human behaviour in risky decision situations. Namely, that the willingness of an individual to pay to reduce health risks (an economic indicator of individual welfare associated with reduced morbidity or increased longevity) tends to be positive and higher when anxiety is present than when it is not. The formal results of the analysis show that when psychological considerations are incorporated into a state-dependent utility model, the normative results customarily obtained concerning value-of-life need to be qualified.

Theoretical models of parental HIV disclosure: a critical review.

PubMed

Qiao, Shan; Li, Xiaoming; Stanton, Bonita

2013-01-01

This study critically examined three major theoretical models related to parental HIV disclosure (i.e., the Four-Phase Model [FPM], the Disclosure Decision Making Model [DDMM], and the Disclosure Process Model [DPM]), and the existing studies that could provide empirical support to these models or their components. For each model, we briefly reviewed its theoretical background, described its components and/or mechanisms, and discussed its strengths and limitations. The existing empirical studies supported most theoretical components in these models. However, hypotheses related to the mechanisms proposed in the models have not yet tested due to a lack of empirical evidence. This study also synthesized alternative theoretical perspectives and new issues in disclosure research and clinical practice that may challenge the existing models. The current study underscores the importance of including components related to social and cultural contexts in theoretical frameworks, and calls for more adequately designed empirical studies in order to test and refine existing theories and to develop new ones.

Humane Management in Times of Restraint.

ERIC Educational Resources Information Center

Auster, Ethel

1987-01-01

Briefly reviews the theoretical principles of decision making and communication for effective management, and describes management practices in Canadian academic libraries facing retrenchment that deviate from this theoretical model. Suggestions for achieving greater congruency between scholarly theory and management practice, thereby facilitating…

A communication model of shared decision making: accounting for cancer treatment decisions.

PubMed

Siminoff, Laura A; Step, Mary M

2005-07-01

The authors present a communication model of shared decision making (CMSDM) that explicitly identifies the communication process as the vehicle for decision making in cancer treatment. In this view, decision making is necessarily a sociocommunicative process whereby people enter into a relationship, exchange information, establish preferences, and choose a course of action. The model derives from contemporary notions of behavioral decision making and ethical conceptions of the doctor-patient relationship. This article briefly reviews the theoretical approaches to decision making, notes deficiencies, and embeds a more socially based process into the dynamics of the physician-patient relationship, focusing on cancer treatment decisions. In the CMSDM, decisions depend on (a) antecedent factors that have potential to influence communication, (b) jointly constructed communication climate, and (c) treatment preferences established by the physician and the patient.

Analysis and Management of Animal Populations: Modeling, Estimation and Decision Making

USGS Publications Warehouse

Williams, B.K.; Nichols, J.D.; Conroy, M.J.

2002-01-01

This book deals with the processes involved in making informed decisions about the management of animal populations. It covers the modeling of population responses to management actions, the estimation of quantities needed in the modeling effort, and the application of these estimates and models to the development of sound management decisions. The book synthesizes and integrates in a single volume the methods associated with these themes, as they apply to ecological assessment and conservation of animal populations. KEY FEATURES * Integrates population modeling, parameter estimation and * decision-theoretic approaches to management in a single, cohesive framework * Provides authoritative, state-of-the-art descriptions of quantitative * approaches to modeling, estimation and decision-making * Emphasizes the role of mathematical modeling in the conduct of science * and management * Utilizes a unifying biological context, consistent mathematical notation, * and numerous biological examples

Decision theory, reinforcement learning, and the brain.

PubMed

Dayan, Peter; Daw, Nathaniel D

2008-12-01

Decision making is a core competence for animals and humans acting and surviving in environments they only partially comprehend, gaining rewards and punishments for their troubles. Decision-theoretic concepts permeate experiments and computational models in ethology, psychology, and neuroscience. Here, we review a well-known, coherent Bayesian approach to decision making, showing how it unifies issues in Markovian decision problems, signal detection psychophysics, sequential sampling, and optimal exploration and discuss paradigmatic psychological and neural examples of each problem. We discuss computational issues concerning what subjects know about their task and how ambitious they are in seeking optimal solutions; we address algorithmic topics concerning model-based and model-free methods for making choices; and we highlight key aspects of the neural implementation of decision making.

Implementation science: a role for parallel dual processing models of reasoning?

PubMed Central

Sladek, Ruth M; Phillips, Paddy A; Bond, Malcolm J

2006-01-01

Background A better theoretical base for understanding professional behaviour change is needed to support evidence-based changes in medical practice. Traditionally strategies to encourage changes in clinical practices have been guided empirically, without explicit consideration of underlying theoretical rationales for such strategies. This paper considers a theoretical framework for reasoning from within psychology for identifying individual differences in cognitive processing between doctors that could moderate the decision to incorporate new evidence into their clinical decision-making. Discussion Parallel dual processing models of reasoning posit two cognitive modes of information processing that are in constant operation as humans reason. One mode has been described as experiential, fast and heuristic; the other as rational, conscious and rule based. Within such models, the uptake of new research evidence can be represented by the latter mode; it is reflective, explicit and intentional. On the other hand, well practiced clinical judgments can be positioned in the experiential mode, being automatic, reflexive and swift. Research suggests that individual differences between people in both cognitive capacity (e.g., intelligence) and cognitive processing (e.g., thinking styles) influence how both reasoning modes interact. This being so, it is proposed that these same differences between doctors may moderate the uptake of new research evidence. Such dispositional characteristics have largely been ignored in research investigating effective strategies in implementing research evidence. Whilst medical decision-making occurs in a complex social environment with multiple influences and decision makers, it remains true that an individual doctor's judgment still retains a key position in terms of diagnostic and treatment decisions for individual patients. This paper argues therefore, that individual differences between doctors in terms of reasoning are important considerations in any discussion relating to changing clinical practice. Summary It is imperative that change strategies in healthcare consider relevant theoretical frameworks from other disciplines such as psychology. Generic dual processing models of reasoning are proposed as potentially useful in identifying factors within doctors that may moderate their individual uptake of evidence into clinical decision-making. Such factors can then inform strategies to change practice. PMID:16725023

Implementation science: a role for parallel dual processing models of reasoning?

PubMed

Sladek, Ruth M; Phillips, Paddy A; Bond, Malcolm J

2006-05-25

A better theoretical base for understanding professional behaviour change is needed to support evidence-based changes in medical practice. Traditionally strategies to encourage changes in clinical practices have been guided empirically, without explicit consideration of underlying theoretical rationales for such strategies. This paper considers a theoretical framework for reasoning from within psychology for identifying individual differences in cognitive processing between doctors that could moderate the decision to incorporate new evidence into their clinical decision-making. Parallel dual processing models of reasoning posit two cognitive modes of information processing that are in constant operation as humans reason. One mode has been described as experiential, fast and heuristic; the other as rational, conscious and rule based. Within such models, the uptake of new research evidence can be represented by the latter mode; it is reflective, explicit and intentional. On the other hand, well practiced clinical judgments can be positioned in the experiential mode, being automatic, reflexive and swift. Research suggests that individual differences between people in both cognitive capacity (e.g., intelligence) and cognitive processing (e.g., thinking styles) influence how both reasoning modes interact. This being so, it is proposed that these same differences between doctors may moderate the uptake of new research evidence. Such dispositional characteristics have largely been ignored in research investigating effective strategies in implementing research evidence. Whilst medical decision-making occurs in a complex social environment with multiple influences and decision makers, it remains true that an individual doctor's judgment still retains a key position in terms of diagnostic and treatment decisions for individual patients. This paper argues therefore, that individual differences between doctors in terms of reasoning are important considerations in any discussion relating to changing clinical practice. It is imperative that change strategies in healthcare consider relevant theoretical frameworks from other disciplines such as psychology. Generic dual processing models of reasoning are proposed as potentially useful in identifying factors within doctors that may moderate their individual uptake of evidence into clinical decision-making. Such factors can then inform strategies to change practice.

Reward Rate Optimization in Two-Alternative Decision Making: Empirical Tests of Theoretical Predictions

ERIC Educational Resources Information Center

Simen, Patrick; Contreras, David; Buck, Cara; Hu, Peter; Holmes, Philip; Cohen, Jonathan D.

2009-01-01

The drift-diffusion model (DDM) implements an optimal decision procedure for stationary, 2-alternative forced-choice tasks. The height of a decision threshold applied to accumulating information on each trial determines a speed-accuracy tradeoff (SAT) for the DDM, thereby accounting for a ubiquitous feature of human performance in speeded response…

Emerging Adulthood among Palestinian Minority in Israel: The Relation between Perceived Career Barriers, Future Orientation and Career Decisions

ERIC Educational Resources Information Center

Mahajna, Sami

2017-01-01

This study examines the relation between perceived career barriers, future orientation and career decisions among young Palestinian-Israeli youth. The study employs a theoretical model that links perceived career barriers and career decisions via variables of future orientation. Three hundred eighty-eight young Palestinian-Israeli women (73.20%)…

Watershed Management Optimization Support Tool (WMOST) v3: Theoretical Documentation

EPA Science Inventory

The Watershed Management Optimization Support Tool (WMOST) is a decision support tool that facilitates integrated water management at the local or small watershed scale. WMOST models the environmental effects and costs of management decisions in a watershed context, accounting fo...

Watershed Management Optimization Support Tool (WMOST) v2: Theoretical Documentation

EPA Science Inventory

The Watershed Management Optimization Support Tool (WMOST) is a decision support tool that evaluates the relative cost-effectiveness of management practices at the local or watershed scale. WMOST models the environmental effects and costs of management decisions in a watershed c...

The role of affect and cognition in health decision making.

PubMed

Keer, Mario; van den Putte, Bas; Neijens, Peter

2010-03-01

Both affective and cognitive evaluations of behaviours have been allocated various positions in theoretical models of decision making. Most often, they have been studied as direct determinants of either intention or overall evaluation, but these two possible positions have never been compared. The aim of this study was to determine whether affective and cognitive evaluations influence intention directly, or whether their influence is mediated by overall evaluation. A sample of 300 university students filled in questionnaires on their affective, cognitive, and overall evaluations in respect of 20 health behaviours. The data were interpreted using mediation analyses with the application of path modelling. Both affective and cognitive evaluations were found to have significantly predicted intention. The influence of affective evaluation was largely direct for each of the behaviours studied, whereas that of cognitive evaluation was partially direct and partially mediated by overall evaluation. These results indicate that decisions regarding the content of persuasive communication (affective vs. cognitive) are highly dependent on the theoretical model chosen. It is suggested that affective evaluation should be included as a direct determinant of intention in theories of decision making when predicting health behaviours.

A theoretical approach to artificial intelligence systems in medicine.

PubMed

Spyropoulos, B; Papagounos, G

1995-10-01

The various theoretical models of disease, the nosology which is accepted by the medical community and the prevalent logic of diagnosis determine both the medical approach as well as the development of the relevant technology including the structure and function of the A.I. systems involved. A.I. systems in medicine, in addition to the specific parameters which enable them to reach a diagnostic and/or therapeutic proposal, entail implicitly theoretical assumptions and socio-cultural attitudes which prejudice the orientation and the final outcome of the procedure. The various models -causal, probabilistic, case-based etc. -are critically examined and their ethical and methodological limitations are brought to light. The lack of a self-consistent theoretical framework in medicine, the multi-faceted character of the human organism as well as the non-explicit nature of the theoretical assumptions involved in A.I. systems restrict them to the role of decision supporting "instruments" rather than regarding them as decision making "devices". This supporting role and, especially, the important function which A.I. systems should have in the structure, the methods and the content of medical education underscore the need of further research in the theoretical aspects and the actual development of such systems.

21st century neurobehavioral theories of decision making in addiction: Review and evaluation.

PubMed

Bickel, Warren K; Mellis, Alexandra M; Snider, Sarah E; Athamneh, Liqa N; Stein, Jeffrey S; Pope, Derek A

2018-01-01

This review critically examines neurobehavioral theoretical developments in decision making in addiction in the 21st century. We specifically compare each theory reviewed to seven benchmarks of theoretical robustness, based on their ability to address: why some commodities are addictive; developmental trends in addiction; addiction-related anhedonia; self-defeating patterns of behavior in addiction; why addiction co-occurs with other unhealthy behaviors; and, finally, means for the repair of addiction. We have included only self-contained theories or hypotheses which have been developed or extended in the 21st century to address decision making in addiction. We thus review seven distinct theories of decision making in addiction: learning theories, incentive-sensitization theory, dopamine imbalance and systems models, opponent process theory, strength models of self-control failure, the competing neurobehavioral decision systems theory, and the triadic systems theory of addiction. Finally, we have directly compared the performance of each of these theories based on the aforementioned benchmarks, and highlighted key points at which several theories have coalesced. Copyright © 2017 Elsevier Inc. All rights reserved.

International Students Decision-Making Process

ERIC Educational Resources Information Center

Cubillo, Jose Maria; Sanchez, Joaquin; Cervino, Julio

2006-01-01

Purpose--The purpose of this paper is to propose a theoretical model that integrates the different groups of factors which influence the decision-making process of international students, analysing different dimensions of this process and explaining those factors which determine students' choice. Design/methodology/approach--A hypothetical model…

Game Theoretic Modeling of Water Resources Allocation Under Hydro-Climatic Uncertainty

NASA Astrophysics Data System (ADS)

Brown, C.; Lall, U.; Siegfried, T.

2005-12-01

Typical hydrologic and economic modeling approaches rely on assumptions of climate stationarity and economic conditions of ideal markets and rational decision-makers. In this study, we incorporate hydroclimatic variability with a game theoretic approach to simulate and evaluate common water allocation paradigms. Game Theory may be particularly appropriate for modeling water allocation decisions. First, a game theoretic approach allows economic analysis in situations where price theory doesn't apply, which is typically the case in water resources where markets are thin, players are few, and rules of exchange are highly constrained by legal or cultural traditions. Previous studies confirm that game theory is applicable to water resources decision problems, yet applications and modeling based on these principles is only rarely observed in the literature. Second, there are numerous existing theoretical and empirical studies of specific games and human behavior that may be applied in the development of predictive water allocation models. With this framework, one can evaluate alternative orderings and rules regarding the fraction of available water that one is allowed to appropriate. Specific attributes of the players involved in water resources management complicate the determination of solutions to game theory models. While an analytical approach will be useful for providing general insights, the variety of preference structures of individual players in a realistic water scenario will likely require a simulation approach. We propose a simulation approach incorporating the rationality, self-interest and equilibrium concepts of game theory with an agent-based modeling framework that allows the distinct properties of each player to be expressed and allows the performance of the system to manifest the integrative effect of these factors. Underlying this framework, we apply a realistic representation of spatio-temporal hydrologic variability and incorporate the impact of decision-making a priori to hydrologic realizations and those made a posteriori on alternative allocation mechanisms. Outcomes are evaluated in terms of water productivity, net social benefit and equity. The performance of hydro-climate prediction modeling in each allocation mechanism will be assessed. Finally, year-to-year system performance and feedback pathways are explored. In this way, the system can be adaptively managed toward equitable and efficient water use.

Coping with pregnancy resolution among never-married women.

PubMed

Bracken, Michael B; Klerman, Lorraine V; Bracken, Maryann

1978-04-01

The Janis-Mann model of decision-making provides the theoretical orientation for empirical analyses of decisions to deliver or abort in matched samples of never-married women. Results focus on four variables: happiness about pregnancy; initial acceptance of delivery or abortion; ease of decision-making; and satisfaction with final choice. Path analyses summarize findings, which are discussed in terms of conflict resolution strategies.

Information Retrieval: A Sequential Learning Process.

ERIC Educational Resources Information Center

Bookstein, Abraham

1983-01-01

Presents decision-theoretic models which intrinsically include retrieval of multiple documents whereby system responds to request by presenting documents to patron in sequence, gathering feedback, and using information to modify future retrievals. Document independence model, set retrieval model, sequential retrieval model, learning model,…

Social decision-making: insights from game theory and neuroscience.

PubMed

Sanfey, Alan G

2007-10-26

By combining the models and tasks of Game Theory with modern psychological and neuroscientific methods, the neuroeconomic approach to the study of social decision-making has the potential to extend our knowledge of brain mechanisms involved in social decisions and to advance theoretical models of how we make decisions in a rich, interactive environment. Research has already begun to illustrate how social exchange can act directly on the brain's reward system, how affective factors play an important role in bargaining and competitive games, and how the ability to assess another's intentions is related to strategic play. These findings provide a fruitful starting point for improved models of social decision-making, informed by the formal mathematical approach of economics and constrained by known neural mechanisms.

Understanding HIV disclosure: A review and application of the Disclosure Processes Model

PubMed Central

Chaudoir, Stephenie R.; Fisher, Jeffrey D.; Simoni, Jane M.

2014-01-01

HIV disclosure is a critical component of HIV/AIDS prevention and treatment efforts, yet the field lacks a comprehensive theoretical framework with which to study how HIV-positive individuals make decisions about disclosing their serostatus and how these decisions affect them. Recent theorizing in the context of the Disclosure Processes Model has suggested that the disclosure process consists of antecedent goals, the disclosure event itself, mediating processes and outcomes, and a feedback loop. In this paper, we apply this new theoretical framework to HIV disclosure in order to review the current state of the literature, identify gaps in existing research, and highlight the implications of the framework for future work in this area. PMID:21514708

The neural representation of unexpected uncertainty during value-based decision making.

PubMed

Payzan-LeNestour, Elise; Dunne, Simon; Bossaerts, Peter; O'Doherty, John P

2013-07-10

Uncertainty is an inherent property of the environment and a central feature of models of decision-making and learning. Theoretical propositions suggest that one form, unexpected uncertainty, may be used to rapidly adapt to changes in the environment, while being influenced by two other forms: risk and estimation uncertainty. While previous studies have reported neural representations of estimation uncertainty and risk, relatively little is known about unexpected uncertainty. Here, participants performed a decision-making task while undergoing functional magnetic resonance imaging (fMRI), which, in combination with a Bayesian model-based analysis, enabled us to separately examine each form of uncertainty examined. We found representations of unexpected uncertainty in multiple cortical areas, as well as the noradrenergic brainstem nucleus locus coeruleus. Other unique cortical regions were found to encode risk, estimation uncertainty, and learning rate. Collectively, these findings support theoretical models in which several formally separable uncertainty computations determine the speed of learning. Copyright © 2013 Elsevier Inc. All rights reserved.

Multicriteria decision analysis: Overview and implications for environmental decision making

USGS Publications Warehouse

Hermans, Caroline M.; Erickson, Jon D.; Erickson, Jon D.; Messner, Frank; Ring, Irene

2007-01-01

Environmental decision making involving multiple stakeholders can benefit from the use of a formal process to structure stakeholder interactions, leading to more successful outcomes than traditional discursive decision processes. There are many tools available to handle complex decision making. Here we illustrate the use of a multicriteria decision analysis (MCDA) outranking tool (PROMETHEE) to facilitate decision making at the watershed scale, involving multiple stakeholders, multiple criteria, and multiple objectives. We compare various MCDA methods and their theoretical underpinnings, examining methods that most realistically model complex decision problems in ways that are understandable and transparent to stakeholders.

Dropping Out of High School: An Application of the Theory of Reasoned Action.

ERIC Educational Resources Information Center

Prestholdt, Perry H.; Fisher, Jack L.

To develop and test a theoretical model, based on the Theory of Reasoned Action (Fishbein and Ajzen, 1975), for understanding and predicting the decision to stay in or drop out of school, to identify the specific beliefs that are the basis of that decision, and to evaluate the use of moderator variables (sex, race) to individualize the model,…

Model application niche analysis: Assessing the transferability and generalizability of ecological models

EPA Science Inventory

The use of models by ecologist and environmental managers, to inform environmental management and decision-making, has grown exponentially in the past 50 years. Due to logistical, economical and theoretical benefits, model users are frequently transferring preexisting models to n...

Tsallis’ non-extensive free energy as a subjective value of an uncertain reward

NASA Astrophysics Data System (ADS)

Takahashi, Taiki

2009-03-01

Recent studies in neuroeconomics and econophysics revealed the importance of reward expectation in decision under uncertainty. Behavioral neuroeconomic studies have proposed that the unpredictability and the probability of an uncertain reward are distinctly encoded as entropy and a distorted probability weight, respectively, in the separate neural systems. However, previous behavioral economic and decision-theoretic models could not quantify reward-seeking and uncertainty aversion in a theoretically consistent manner. In this paper, we have: (i) proposed that generalized Helmholtz free energy in Tsallis’ non-extensive thermostatistics can be utilized to quantify a perceived value of an uncertain reward, and (ii) empirically examined the explanatory powers of the models. Future study directions in neuroeconomics and econophysics by utilizing the Tsallis’ free energy model are discussed.

Optimal Decision Stimuli for Risky Choice Experiments: An Adaptive Approach.

PubMed

Cavagnaro, Daniel R; Gonzalez, Richard; Myung, Jay I; Pitt, Mark A

2013-02-01

Collecting data to discriminate between models of risky choice requires careful selection of decision stimuli. Models of decision making aim to predict decisions across a wide range of possible stimuli, but practical limitations force experimenters to select only a handful of them for actual testing. Some stimuli are more diagnostic between models than others, so the choice of stimuli is critical. This paper provides the theoretical background and a methodological framework for adaptive selection of optimal stimuli for discriminating among models of risky choice. The approach, called Adaptive Design Optimization (ADO), adapts the stimulus in each experimental trial based on the results of the preceding trials. We demonstrate the validity of the approach with simulation studies aiming to discriminate Expected Utility, Weighted Expected Utility, Original Prospect Theory, and Cumulative Prospect Theory models.

A theoretical model of water and trade

NASA Astrophysics Data System (ADS)

Dang, Qian; Konar, Megan; Reimer, Jeffrey J.; Di Baldassarre, Giuliano; Lin, Xiaowen; Zeng, Ruijie

2016-03-01

Water is an essential input for agricultural production. Agriculture, in turn, is globalized through the trade of agricultural commodities. In this paper, we develop a theoretical model that emphasizes four tradeoffs involving water-use decision-making that are important yet not always considered in a consistent framework. One tradeoff focuses on competition for water among different economic sectors. A second tradeoff examines the possibility that certain types of agricultural investments can offset water use. A third tradeoff explores the possibility that the rest of the world can be a source of supply or demand for a country's water-using commodities. The fourth tradeoff concerns how variability in water supplies influences farmer decision-making. We show conditions under which trade liberalization affect water use. Two policy scenarios to reduce water use are evaluated. First, we derive a target tax that reduces water use without offsetting the gains from trade liberalization, although important tradeoffs exist between economic performance and resource use. Second, we show how subsidization of water-saving technologies can allow producers to use less water without reducing agricultural production, making such subsidization an indirect means of influencing water use decision-making. Finally, we outline conditions under which riskiness of water availability affects water use. These theoretical model results generate hypotheses that can be tested empirically in future work.

The design of patient decision support interventions: addressing the theory-practice gap.

PubMed

Elwyn, Glyn; Stiel, Mareike; Durand, Marie-Anne; Boivin, Jacky

2011-08-01

Although an increasing number of decision support interventions for patients (including decision aids) are produced, few make explicit use of theory. We argue the importance of using theory to guide design. The aim of this work was to address this theory-practice gap and to examine how a range of selected decision-making theories could inform the design and evaluation of decision support interventions. We reviewed the decision-making literature and selected relevant theories. We assessed their key principles, theoretical pathways and predictions in order to determine how they could inform the design of two core components of decision support interventions, namely, information and deliberation components and to specify theory-based outcome measures. Eight theories were selected: (1) the expected utility theory; (2) the conflict model of decision making; (3) prospect theory; (4) fuzzy-trace theory; (5) the differentiation and consolidation theory; (6) the ecological rationality theory; (7) the rational-emotional model of decision avoidance; and finally, (8) the Attend, React, Explain, Adapt model of affective forecasting. Some theories have strong relevance to the information design (e.g. prospect theory); some are more relevant to deliberation processes (conflict theory, differentiation theory and ecological validity). None of the theories in isolation was sufficient to inform the design of all the necessary components of decision support interventions. It was also clear that most work in theory-building has focused on explaining or describing how humans think rather than on how tools could be designed to help humans make good decisions. It is not surprising therefore that a large theory-practice gap exists as we consider decision support for patients. There was no relevant theory that integrated all the necessary contributions to the task of making good decisions in collaborative interactions. Initiatives such as the International Patient Decision Aids Standards Collaboration influence standards for the design of decision support interventions. However, this analysis points to the need to undertake more work in providing theoretical foundations for these interventions. © 2010 Blackwell Publishing Ltd.

People adopt optimal policies in simple decision-making, after practice and guidance.

PubMed

Evans, Nathan J; Brown, Scott D

2017-04-01

Organisms making repeated simple decisions are faced with a tradeoff between urgent and cautious strategies. While animals can adopt a statistically optimal policy for this tradeoff, findings about human decision-makers have been mixed. Some studies have shown that people can optimize this "speed-accuracy tradeoff", while others have identified a systematic bias towards excessive caution. These issues have driven theoretical development and spurred debate about the nature of human decision-making. We investigated a potential resolution to the debate, based on two factors that routinely differ between human and animal studies of decision-making: the effects of practice, and of longer-term feedback. Our study replicated the finding that most people, by default, are overly cautious. When given both practice and detailed feedback, people moved rapidly towards the optimal policy, with many participants reaching optimality with less than 1 h of practice. Our findings have theoretical implications for cognitive and neural models of simple decision-making, as well as methodological implications.

Willingness-to-pay for steelhead trout fishing: Implications of two-step consumer decisions with short-run endowments

NASA Astrophysics Data System (ADS)

McKean, John R.; Johnson, Donn; Taylor, R. Garth

2010-09-01

Choice of the appropriate model of economic behavior is important for the measurement of nonmarket demand and benefits. Several travel cost demand model specifications are currently in use. Uncertainty exists over the efficacy of these approaches, and more theoretical and empirical study is warranted. Thus travel cost models with differing assumptions about labor markets and consumer behavior were applied to estimate the demand for steelhead trout sportfishing on an unimpounded reach of the Snake River near Lewiston, Idaho. We introduce a modified two-step decision model that incorporates endogenous time value using a latent index variable approach. The focus is on the importance of distinguishing between short-run and long-run consumer decision variables in a consistent manner. A modified Barnett two-step decision model was found superior to other models tested.

Dynamic Decision Making in Complex Task Environments: Principles and Neural Mechanisms

DTIC Science & Technology

2013-03-01

Dynamical models of cognition . Mathematical models of mental processes. Human performance optimization. U U U U Dr. Jay Myung 703-696-8487 Reset 1...we have continued to develop a neurodynamic theory of decision making, using a combination of computational and experimental approaches, to address...a long history in the field of human cognitive psychology. The theoretical foundations of this research can be traced back to signal detection

College Crowd-In: How Private Donations Positively Affect Alumni Giving

ERIC Educational Resources Information Center

Gottfried, Michael A.

2008-01-01

The issue of donor behavior and crowding out has been pertinent in the economics literature, both theoretically and empirically. Aggregate research has not been decisive, nor have many studies analyzed education institutions. I begin with a theoretical model of crowding-out versus crowding-in donor behavior. I then employ a fixed effects…

Symbolic Heuristic Search for Factored Markov Decision Processes

NASA Technical Reports Server (NTRS)

Morris, Robert (Technical Monitor); Feng, Zheng-Zhu; Hansen, Eric A.

2003-01-01

We describe a planning algorithm that integrates two approaches to solving Markov decision processes with large state spaces. State abstraction is used to avoid evaluating states individually. Forward search from a start state, guided by an admissible heuristic, is used to avoid evaluating all states. We combine these two approaches in a novel way that exploits symbolic model-checking techniques and demonstrates their usefulness for decision-theoretic planning.

Signal detection with criterion noise: applications to recognition memory.

PubMed

Benjamin, Aaron S; Diaz, Michael; Wee, Serena

2009-01-01

A tacit but fundamental assumption of the theory of signal detection is that criterion placement is a noise-free process. This article challenges that assumption on theoretical and empirical grounds and presents the noisy decision theory of signal detection (ND-TSD). Generalized equations for the isosensitivity function and for measures of discrimination incorporating criterion variability are derived, and the model's relationship with extant models of decision making in discrimination tasks is examined. An experiment evaluating recognition memory for ensembles of word stimuli revealed that criterion noise is not trivial in magnitude and contributes substantially to variance in the slope of the isosensitivity function. The authors discuss how ND-TSD can help explain a number of current and historical puzzles in recognition memory, including the inconsistent relationship between manipulations of learning and the isosensitivity function's slope, the lack of invariance of the slope with manipulations of bias or payoffs, the effects of aging on the decision-making process in recognition, and the nature of responding in remember-know decision tasks. ND-TSD poses novel, theoretically meaningful constraints on theories of recognition and decision making more generally, and provides a mechanism for rapprochement between theories of decision making that employ deterministic response rules and those that postulate probabilistic response rules.

An Empirically Calibrated Model of Cell Fate Decision Following Viral Infection

NASA Astrophysics Data System (ADS)

Coleman, Seth; Igoshin, Oleg; Golding, Ido

The life cycle of the virus (phage) lambda is an established paradigm for the way genetic networks drive cell fate decisions. But despite decades of interrogation, we are still unable to theoretically predict whether the infection of a given cell will result in cell death or viral dormancy. The poor predictive power of current models reflects the absence of quantitative experimental data describing the regulatory interactions between different lambda genes. To address this gap, we are constructing a theoretical model that captures the known interactions in the lambda network. Model assumptions and parameters are calibrated using new single-cell data from our lab, describing the activity of lambda genes at single-molecule resolution. We began with a mean-field model, aimed at exploring the population averaged gene-expression trajectories under different initial conditions. Next, we will develop a stochastic formulation, to capture the differences between individual cells within the population. The eventual goal is to identify how the post-infection decision is driven by the interplay between network topology, initial conditions, and stochastic effects. The insights gained here will inform our understanding of cell fate choices in more complex cellular systems.

Parental, Residential, and Self-Belief Factors Influencing Academic Persistence Decisions of College Freshmen

ERIC Educational Resources Information Center

Walsh, Kelsey J.; Robinson Kurpius, Sharon E.

2016-01-01

Based on Tinto's model of academic persistence, this study explored background and personal factors that theoretically impact the academic persistence decisions of college freshmen. The factors studied were (a) parental educational attainment, (b) parental valuing of education, (c) high school grade point average, (d) residential status (on- vs.…

Optimal Decision Stimuli for Risky Choice Experiments: An Adaptive Approach

PubMed Central

Cavagnaro, Daniel R.; Gonzalez, Richard; Myung, Jay I.; Pitt, Mark A.

2014-01-01

Collecting data to discriminate between models of risky choice requires careful selection of decision stimuli. Models of decision making aim to predict decisions across a wide range of possible stimuli, but practical limitations force experimenters to select only a handful of them for actual testing. Some stimuli are more diagnostic between models than others, so the choice of stimuli is critical. This paper provides the theoretical background and a methodological framework for adaptive selection of optimal stimuli for discriminating among models of risky choice. The approach, called Adaptive Design Optimization (ADO), adapts the stimulus in each experimental trial based on the results of the preceding trials. We demonstrate the validity of the approach with simulation studies aiming to discriminate Expected Utility, Weighted Expected Utility, Original Prospect Theory, and Cumulative Prospect Theory models. PMID:24532856

Combined monitoring, decision and control model for the human operator in a command and control desk

NASA Technical Reports Server (NTRS)

Muralidharan, R.; Baron, S.

1978-01-01

A report is given on the ongoing efforts to mode the human operator in the context of the task during the enroute/return phases in the ground based control of multiple flights of remotely piloted vehicles (RPV). The approach employed here uses models that have their analytical bases in control theory and in statistical estimation and decision theory. In particular, it draws heavily on the modes and the concepts of the optimal control model (OCM) of the human operator. The OCM is being extended into a combined monitoring, decision, and control model (DEMON) of the human operator by infusing decision theoretic notions that make it suitable for application to problems in which human control actions are infrequent and in which monitoring and decision-making are the operator's main activities. Some results obtained with a specialized version of DEMON for the RPV control problem are included.

THE USE OF CELLULAR AUTOMATA MODELING APPROACHES TO UNDERSTAND POTENTIAL IMPACTS OF GM PLANTS ON PLANT COMMUNITIES

EPA Science Inventory

The development of models is of interest to ecologists, regulators and developers, since it may assist theoretical understanding, decision making in experimental design, product development and risk assessment. A successful modeling methodology for investigating such characteris...

School Library Acquisitions: A Model for Calculating Costs

ERIC Educational Resources Information Center

Lauterman, Alfred; Lazarescu, Sandu

1977-01-01

Romanian research findings offer a theoretical model with which financing of the annual acquisition of books per pupil at a given educational level can be objectively ascertained. Methods of financing and acquisitions policy decisions are discussed. (Author/JAB)

Cross-Milieu Terrorist Collaboration: Using Game Theory to Assess the Risk of a Novel Threat.

PubMed

Ackerman, Gary A; Zhuang, Jun; Weerasuriya, Sitara

2017-02-01

This article uses a game-theoretic approach to analyze the risk of cross-milieu terrorist collaboration-the possibility that, despite marked ideological differences, extremist groups from very different milieus might align to a degree where operational collaboration against Western societies becomes possible. Based upon theoretical insights drawn from a variety of literatures, a bargaining model is constructed that reflects the various benefits and costs for terrorists' collaboration across ideological milieus. Analyzed in both sequential and simultaneous decision-making contexts and through numerical simulations, the model confirms several theoretical arguments. The most important of these is that although likely to be quite rare, successful collaboration across terrorist milieus is indeed feasible in certain circumstances. The model also highlights several structural elements that might play a larger role than previously recognized in the collaboration decision, including that the prospect of nonmaterial gains (amplification of terror and reputational boost) plays at least as important a role in the decision to collaborate as potential increased capabilities does. Numerical simulation further suggests that prospects for successful collaboration over most scenarios (including operational) increase when a large, effective Islamist terrorist organization initiates collaboration with a smaller right-wing group, as compared with the other scenarios considered. Although the small number of historical cases precludes robust statistical validation, the simulation results are supported by existing empirical evidence of collaboration between Islamists and right- or left-wing extremists. The game-theoretic approach, therefore, provides guidance regarding the circumstances under which such an unholy alliance of violent actors is likely to succeed. © 2016 Society for Risk Analysis.

Patients' mental models and adherence to outpatient physical therapy home exercise programs.

PubMed

Rizzo, Jon

2015-05-01

Within physical therapy, patient adherence usually relates to attending appointments, following advice, and/or undertaking prescribed exercise. Similar to findings for general medical adherence, patient adherence to physical therapy home exercise programs (HEP) is estimated between 35 and 72%. Adherence to HEPs is a multifactorial and poorly understood phenomenon, with no consensus regarding a common theoretical framework that best guides empirical or clinical efforts. Mental models, a construct used to explain behavior and decision-making in the social sciences, may serve as this framework. Mental models comprise an individual's tacit thoughts about how the world works. They include assumptions about new experiences and expectations for the future based on implicit comparisons between current and past experiences. Mental models play an important role in decision-making and guiding actions. This professional theoretical article discusses empirical research demonstrating relationships among mental models, prior experience, and adherence decisions in medical and physical therapy contexts. Specific issues related to mental models and physical therapy patient adherence are discussed, including the importance of articulation of patients' mental models, assessment of patients' mental models that relate to exercise program adherence, discrepancy between patient and provider mental models, and revision of patients' mental models in ways that enhance adherence. The article concludes with practical implications for physical therapists and recommendations for further research to better understand the role of mental models in physical therapy patient adherence behavior.

A theory of utility conditionals: Paralogical reasoning from decision-theoretic leakage.

PubMed

Bonnefon, Jean-François

2009-10-01

Many "if p, then q" conditionals have decision-theoretic features, such as antecedents or consequents that relate to the utility functions of various agents. These decision-theoretic features leak into reasoning processes, resulting in various paralogical conclusions. The theory of utility conditionals offers a unified account of the various forms that this phenomenon can take. The theory is built on 2 main components: (1) a representational tool (the utility grid), which summarizes in compact form the decision-theoretic features of a conditional, and (2) a set of folk axioms of decision, which reflect reasoners' beliefs about the way most agents make their decisions. Applying the folk axioms to the utility grid of a conditional allows for the systematic prediction of the paralogical conclusions invited by the utility grid's decision-theoretic features. The theory of utility conditionals significantly extends the scope of current theories of conditional inference and moves reasoning research toward a greater integration with decision-making research.

QTest: Quantitative Testing of Theories of Binary Choice.

PubMed

Regenwetter, Michel; Davis-Stober, Clintin P; Lim, Shiau Hong; Guo, Ying; Popova, Anna; Zwilling, Chris; Cha, Yun-Shil; Messner, William

2014-01-01

The goal of this paper is to make modeling and quantitative testing accessible to behavioral decision researchers interested in substantive questions. We provide a novel, rigorous, yet very general, quantitative diagnostic framework for testing theories of binary choice. This permits the nontechnical scholar to proceed far beyond traditionally rather superficial methods of analysis, and it permits the quantitatively savvy scholar to triage theoretical proposals before investing effort into complex and specialized quantitative analyses. Our theoretical framework links static algebraic decision theory with observed variability in behavioral binary choice data. The paper is supplemented with a custom-designed public-domain statistical analysis package, the QTest software. We illustrate our approach with a quantitative analysis using published laboratory data, including tests of novel versions of "Random Cumulative Prospect Theory." A major asset of the approach is the potential to distinguish decision makers who have a fixed preference and commit errors in observed choices from decision makers who waver in their preferences.

Relevance of behavioral and social models to the study of consumer energy decision making and behavior

DOE Office of Scientific and Technical Information (OSTI.GOV)

Burns, B.A.

This report reviews social and behavioral science models and techniques for their possible use in understanding and predicting consumer energy decision making and behaviors. A number of models and techniques have been developed that address different aspects of the decision process, use different theoretical bases and approaches, and have been aimed at different audiences. Three major areas of discussion were selected: (1) models of adaptation to social change, (2) decision making and choice, and (3) diffusion of innovation. Within these three areas, the contributions of psychologists, sociologists, economists, marketing researchers, and others were reviewed. Five primary components of the modelsmore » were identified and compared. The components are: (1) situational characteristics, (2) product characteristics, (3) individual characteristics, (4) social influences, and (5) the interaction or decision rules. The explicit use of behavioral and social science models in energy decision-making and behavior studies has been limited. Examples are given of a small number of energy studies which applied and tested existing models in studying the adoption of energy conservation behaviors and technologies, and solar technology.« less

Moral dilemmas and abortion decision-making: Lessons learnt from abortion research in England and Wales.

PubMed

Hoggart, Lesley

2018-05-21

This paper scrutinises the concepts of moral reasoning and personal reasoning, problematising the binary model by looking at young women's pregnancy decision-making. Data from two UK empirical studies are subjected to theoretically driven qualitative secondary analysis, and illustrative cases show how complex decision-making is characterised by an intertwining of the personal and the moral, and is thus best understood by drawing on moral relativism.

Watershed Management Optimization Support Tool (WMOST) v1: Theoretical Documentation

EPA Science Inventory

The Watershed Management Optimization Support Tool (WMOST) is a screening model that is spatially lumped with options for a daily or monthly time step. It is specifically focused on modeling the effect of management decisions on the watershed. The model considers water flows and ...

Information processing. [in human performance

NASA Technical Reports Server (NTRS)

Wickens, Christopher D.; Flach, John M.

1988-01-01

Theoretical models of sensory-information processing by the human brain are reviewed from a human-factors perspective, with a focus on their implications for aircraft and avionics design. The topics addressed include perception (signal detection and selection), linguistic factors in perception (context provision, logical reversals, absence of cues, and order reversals), mental models, and working and long-term memory. Particular attention is given to decision-making problems such as situation assessment, decision formulation, decision quality, selection of action, the speed-accuracy tradeoff, stimulus-response compatibility, stimulus sequencing, dual-task performance, task difficulty and structure, and factors affecting multiple task performance (processing modalities, codes, and stages).

Monitoring and decision making by people in man machine systems

NASA Technical Reports Server (NTRS)

Johannsen, G.

1979-01-01

The analysis of human monitoring and decision making behavior as well as its modeling are described. Classic and optimal control theoretical, monitoring models are surveyed. The relationship between attention allocation and eye movements is discussed. As an example of applications, the evaluation of predictor displays by means of the optimal control model is explained. Fault detection involving continuous signals and decision making behavior of a human operator engaged in fault diagnosis during different operation and maintenance situations are illustrated. Computer aided decision making is considered as a queueing problem. It is shown to what extent computer aids can be based on the state of human activity as measured by psychophysiological quantities. Finally, management information systems for different application areas are mentioned. The possibilities of mathematical modeling of human behavior in complex man machine systems are also critically assessed.

An Information Theoretic Approach for Measuring Data Discovery and Utilization During Analytical and Decision Making Processes

DTIC Science & Technology

2015-07-31

and make the expected decision outcomes. The scenario is based around a scripted storyboard where an organized crime network is operating in a city to...interdicted by law enforcement to disrupt the network. The scenario storyboard was used to develop a probabilistic vehicle traffic model in order to

Anxiety, Decision Conflict, and Health in Caregivers of Children with ADHD: A Survey.

PubMed

Chen, Jih Yuan; Clark, Mary Jo; Chang, Yong Yuan; Liu, Yea Ying

2015-01-01

The purpose of this study was to test a theoretical model to determine the effect of caregiver anxiety and decision conflict on the health of caregivers of children with ADHD. Cross-sectional analyses were conducted on data derived from caregivers (aged 24-70). Participants completed the Decision Conflict Scale, the Zung Anxiety Scale, the Duke Health Profile, and a demographic form. A path model that fit well indicated that anxiety and decision conflict had direct and indirect effects on the caregivers' health. Future study is needed to clarify factors contributing to uncertainty and to decrease emotional symptoms for caregivers, thus promoting their mental health. Copyright © 2015 Elsevier Inc. All rights reserved.

Core Competencies for Shared Decision Making Training Programs: Insights From an International, Interdisciplinary Working Group

PubMed Central

Légaré, France; Moumjid-Ferdjaoui, Nora; Drolet, Renée; Stacey, Dawn; Härter, Martin; Bastian, Hilda; Beaulieu, Marie-Dominique; Borduas, Francine; Charles, Cathy; Coulter, Angela; Desroches, Sophie; Friedrich, Gwendolyn; Gafni, Amiram; Graham, Ian D.; Labrecque, Michel; LeBlanc, Annie; Légaré, Jean; Politi, Mary; Sargeant, Joan; Thomson, Richard

2014-01-01

Shared decision making is now making inroads in health care professionals’ continuing education curriculum, but there is no consensus on what core competencies are required by clinicians for effectively involving patients in health-related decisions. Ready-made programs for training clinicians in shared decision making are in high demand, but existing programs vary widely in their theoretical foundations, length, and content. An international, interdisciplinary group of 25 individuals met in 2012 to discuss theoretical approaches to making health-related decisions, compare notes on existing programs, take stock of stakeholders concerns, and deliberate on core competencies. This article summarizes the results of those discussions. Some participants believed that existing models already provide a sufficient conceptual basis for developing and implementing shared decision making competency-based training programs on a wide scale. Others argued that this would be premature as there is still no consensus on the definition of shared decision making or sufficient evidence to recommend specific competencies for implementing shared decision making. However, all participants agreed that there were 2 broad types of competencies that clinicians need for implementing shared decision making: relational competencies and risk communication competencies. Further multidisciplinary research could broaden and deepen our understanding of core competencies for shared decision making training. PMID:24347105

How infants' reaches reveal principles of sensorimotor decision making

NASA Astrophysics Data System (ADS)

Dineva, Evelina; Schöner, Gregor

2018-01-01

In Piaget's classical A-not-B-task, infants repeatedly make a sensorimotor decision to reach to one of two cued targets. Perseverative errors are induced by switching the cue from A to B, while spontaneous errors are unsolicited reaches to B when only A is cued. We argue that theoretical accounts of sensorimotor decision-making fail to address how motor decisions leave a memory trace that may impact future sensorimotor decisions. Instead, in extant neural models, perseveration is caused solely by the history of stimulation. We present a neural dynamic model of sensorimotor decision-making within the framework of Dynamic Field Theory, in which a dynamic instability amplifies fluctuations in neural activation into macroscopic, stable neural activation states that leave memory traces. The model predicts perseveration, but also a tendency to repeat spontaneous errors. To test the account, we pool data from several A-not-B experiments. A conditional probabilities analysis accounts quantitatively how motor decisions depend on the history of reaching. The results provide evidence for the interdependence among subsequent reaching decisions that is explained by the model, showing that by amplifying small differences in activation and affecting learning, decisions have consequences beyond the individual behavioural act.

A Custody Evaluation Model for Pre-School Children.

ERIC Educational Resources Information Center

Roseby, Vivienne

This document addresses the needs of mental health consultants involved in decision-making in custody disputes. A psycho-ecological model for assessing contexts of development in cases involving preschool children is presented, and the theoretical basis and rationale for the model are discussed. Issues, instruments, and findings of recent…

Predicting Document Retrieval System Performance: An Expected Precision Measure.

ERIC Educational Resources Information Center

Losee, Robert M., Jr.

1987-01-01

Describes an expected precision (EP) measure designed to predict document retrieval performance. Highlights include decision theoretic models; precision and recall as measures of system performance; EP graphs; relevance feedback; and computing the retrieval status value of a document for two models, the Binary Independent Model and the Two Poisson…

Predictors of Latina/o Community College Student Vocational Choice in STEM

ERIC Educational Resources Information Center

Johnson, Joel D.; Starobin, Soko S.; Santos Laanan, Frankie

2016-01-01

This study confirmed appropriate measurement model fit for a theoretical model, the STEM (science, technology, engineering, and mathematics) vocational choice (STEM-VC) model. This model identified factors that successfully predicted a student's vocational choice decision to pursue a STEM degree for Latina/o and White community college students.…

Model Checking with Edge-Valued Decision Diagrams

NASA Technical Reports Server (NTRS)

Roux, Pierre; Siminiceanu, Radu I.

2010-01-01

We describe an algebra of Edge-Valued Decision Diagrams (EVMDDs) to encode arithmetic functions and its implementation in a model checking library. We provide efficient algorithms for manipulating EVMDDs and review the theoretical time complexity of these algorithms for all basic arithmetic and relational operators. We also demonstrate that the time complexity of the generic recursive algorithm for applying a binary operator on EVMDDs is no worse than that of Multi- Terminal Decision Diagrams. We have implemented a new symbolic model checker with the intention to represent in one formalism the best techniques available at the moment across a spectrum of existing tools. Compared to the CUDD package, our tool is several orders of magnitude faster

Role of Travel Motivations, Perceived Risks and Travel Constraints on Destination Image and Visit Intention in Medical Tourism

PubMed Central

Khan, Mohammad J.; Chelliah, Shankar; Haron, Mahmod S.; Ahmed, Sahrish

2017-01-01

Travel motivations, perceived risks and travel constraints, along with the attributes and characteristics of medical tourism destinations, are important issues in medical tourism. Although the importance of these factors is already known, a comprehensive theoretical model of the decision-making process of medical tourists has yet to be established, analysing the intricate relationships between the different variables involved. This article examines a large body of literature on both medical and conventional tourism in order to propose a comprehensive theoretical framework of medical tourism decision-making. Many facets of this complex phenomenon require further empirical investigation. PMID:28417022

Perceptions of disease risk: from social construction of subjective judgments to rational decision making.

PubMed

McRoberts, N; Hall, C; Madden, L V; Hughes, G

2011-06-01

Many factors influence how people form risk perceptions. Farmers' perceptions of risk and levels of risk aversion impact on decision-making about such things as technology adoption and disease management practices. Irrespective of the underlying factors that affect risk perceptions, those perceptions can be summarized by variables capturing impact and uncertainty components of risk. We discuss a new framework that has the subjective probability of disease and the cost of decision errors as its central features, which might allow a better integration of social science and epidemiology, to the benefit of plant disease management. By focusing on the probability and cost (or impact) dimensions of risk, the framework integrates research from the social sciences, economics, decision theory, and epidemiology. In particular, we review some useful properties of expected regret and skill value, two measures of expected cost that are particularly useful in the evaluation of decision tools. We highlight decision-theoretic constraints on the usefulness of decision tools that may partly explain cases of failure of adoption. We extend this analysis by considering information-theoretic criteria that link model complexity and relative performance and which might explain why users reject forecasters that impose even moderate increases in the complexity of decision making despite improvements in performance or accept very simple decision tools that have relatively poor performance.

Diagnosing and dealing with multicollinearity.

PubMed

Schroeder, M A

1990-04-01

The purpose of this article was to increase nurse researchers' awareness of the effects of collinear data in developing theoretical models for nursing practice. Collinear data distort the true value of the estimates generated from ordinary least-squares analysis. Theoretical models developed to provide the underpinnings of nursing practice need not be abandoned, however, because they fail to produce consistent estimates over repeated applications. It is also important to realize that multicollinearity is a data problem, not a problem associated with misspecification of a theorectical model. An investigator must first be aware of the problem, and then it is possible to develop an educated solution based on the degree of multicollinearity, theoretical considerations, and sources of error associated with alternative, biased, least-square regression techniques. Decisions based on theoretical and statistical considerations will further the development of theory-based nursing practice.

Quality of Life Issues for Families Who Make the Decision to Use a Feeding Tube for Their Child with Disabilities.

ERIC Educational Resources Information Center

Brotherson, Mary Jane; And Others

1995-01-01

Eight families deciding to use a feeding tube to meet the nutrition needs of their children with disabilities were interviewed over a two-year period. Family decision making in the context of quality of life was examined using a theoretical family systems model. Implications for future interventions are addressed. (Author/SW)

From social network (centralized vs. decentralized) to collective decision-making (unshared vs. shared consensus).

PubMed

Sueur, Cédric; Deneubourg, Jean-Louis; Petit, Odile

2012-01-01

Relationships we have with our friends, family, or colleagues influence our personal decisions, as well as decisions we make together with others. As in human beings, despotism and egalitarian societies seem to also exist in animals. While studies have shown that social networks constrain many phenomena from amoebae to primates, we still do not know how consensus emerges from the properties of social networks in many biological systems. We created artificial social networks that represent the continuum from centralized to decentralized organization and used an agent-based model to make predictions about the patterns of consensus and collective movements we observed according to the social network. These theoretical results showed that different social networks and especially contrasted ones--star network vs. equal network--led to totally different patterns. Our model showed that, by moving from a centralized network to a decentralized one, the central individual seemed to lose its leadership in the collective movement's decisions. We, therefore, showed a link between the type of social network and the resulting consensus. By comparing our theoretical data with data on five groups of primates, we confirmed that this relationship between social network and consensus also appears to exist in animal societies.

Gain Modulation by an Urgency Signal Controls the Speed–Accuracy Trade-Off in a Network Model of a Cortical Decision Circuit

PubMed Central

Standage, Dominic; You, Hongzhi; Wang, Da-Hui; Dorris, Michael C.

2011-01-01

The speed–accuracy trade-off (SAT) is ubiquitous in decision tasks. While the neural mechanisms underlying decisions are generally well characterized, the application of decision-theoretic methods to the SAT has been difficult to reconcile with experimental data suggesting that decision thresholds are inflexible. Using a network model of a cortical decision circuit, we demonstrate the SAT in a manner consistent with neural and behavioral data and with mathematical models that optimize speed and accuracy with respect to one another. In simulations of a reaction time task, we modulate the gain of the network with a signal encoding the urgency to respond. As the urgency signal builds up, the network progresses through a series of processing stages supporting noise filtering, integration of evidence, amplification of integrated evidence, and choice selection. Analysis of the network's dynamics formally characterizes this progression. Slower buildup of urgency increases accuracy by slowing down the progression. Faster buildup has the opposite effect. Because the network always progresses through the same stages, decision-selective firing rates are stereotyped at decision time. PMID:21415911

Gain modulation by an urgency signal controls the speed-accuracy trade-off in a network model of a cortical decision circuit.

PubMed

Standage, Dominic; You, Hongzhi; Wang, Da-Hui; Dorris, Michael C

2011-01-01

The speed-accuracy trade-off (SAT) is ubiquitous in decision tasks. While the neural mechanisms underlying decisions are generally well characterized, the application of decision-theoretic methods to the SAT has been difficult to reconcile with experimental data suggesting that decision thresholds are inflexible. Using a network model of a cortical decision circuit, we demonstrate the SAT in a manner consistent with neural and behavioral data and with mathematical models that optimize speed and accuracy with respect to one another. In simulations of a reaction time task, we modulate the gain of the network with a signal encoding the urgency to respond. As the urgency signal builds up, the network progresses through a series of processing stages supporting noise filtering, integration of evidence, amplification of integrated evidence, and choice selection. Analysis of the network's dynamics formally characterizes this progression. Slower buildup of urgency increases accuracy by slowing down the progression. Faster buildup has the opposite effect. Because the network always progresses through the same stages, decision-selective firing rates are stereotyped at decision time.

Clinical cognition and diagnostic error: applications of a dual process model of reasoning.

PubMed

Croskerry, Pat

2009-09-01

Both systemic and individual factors contribute to missed or delayed diagnoses. Among the multiple factors that impact clinical performance of the individual, the caliber of cognition is perhaps the most relevant and deserves our attention and understanding. In the last few decades, cognitive psychologists have gained substantial insights into the processes that underlie cognition, and a new, universal model of reasoning and decision making has emerged, Dual Process Theory. The theory has immediate application to medical decision making and provides an overall schema for understanding the variety of theoretical approaches that have been taken in the past. The model has important practical applications for decision making across the multiple domains of healthcare, and may be used as a template for teaching decision theory, as well as a platform for future research. Importantly, specific operating characteristics of the model explain how diagnostic failure occurs.

Empirical modeling of an alcohol expectancy memory network using multidimensional scaling.

PubMed

Rather, B C; Goldman, M S; Roehrich, L; Brannick, M

1992-02-01

Risk-related antecedent variables can be linked to later alcohol consumption by memory processes, and alcohol expectancies may be one relevant memory content. To advance research in this area, it would be useful to apply current memory models such as semantic network theory to explain drinking decision processes. We used multidimensional scaling (MDS) to empirically model a preliminary alcohol expectancy semantic network, from which a theoretical account of drinking decision making was generated. Subanalyses (PREFMAP) showed how individuals with differing alcohol consumption histories may have had different association pathways within the expectancy network. These pathways may have, in turn influenced future drinking levels and behaviors while the person was under the influence of alcohol. All individuals associated positive/prosocial effects with drinking, but heavier drinkers indicated arousing effects as their highest probability associates, whereas light drinkers expected sedation. An important early step in this MDS modeling process is the determination of iso-meaning expectancy adjective groups, which correspond to theoretical network nodes.

A Theory of Utility Conditionals: Paralogical Reasoning from Decision-Theoretic Leakage

ERIC Educational Resources Information Center

Bonnefon, Jean-Francois

2009-01-01

Many "if p, then q" conditionals have decision-theoretic features, such as antecedents or consequents that relate to the utility functions of various agents. These decision-theoretic features leak into reasoning processes, resulting in various paralogical conclusions. The theory of utility conditionals offers a unified account of the various forms…

Understanding Decision-Making in Specialized Domestic Violence Courts: Can Contemporary Theoretical Frameworks Help Guide These Decisions?

PubMed

Pinchevsky, Gillian M

2016-05-22

This study fills a gap in the literature by exploring the utility of contemporary courtroom theoretical frameworks-uncertainty avoidance, causal attribution, and focal concerns-for explaining decision-making in specialized domestic violence courts. Using data from two specialized domestic violence courts, this study explores the predictors of prosecutorial and judicial decision-making and the extent to which these factors are congruent with theoretical frameworks often used in studies of court processing. Findings suggest that these theoretical frameworks only partially help explain decision-making in the courts under study. A discussion of the findings and implications for future research is provided. © The Author(s) 2016.

The Life Course Health Development Model: A Guide to Children's Health Care Policy and Practice

ERIC Educational Resources Information Center

Halfon, Neal; Russ, Shirley; Regalado, Michael

2005-01-01

As medical knowledge and treatments improve, pediatricians' role in promoting children's health continues to change. Genetics and early experiences may have long-term effects on health and development. Theoretical models that influence providers' decisions about the use of health-care resources are: the disease model, the neuromaturational model,…

Towards representing human behavior and decision making in Earth system models - an overview of techniques and approaches

NASA Astrophysics Data System (ADS)

Müller-Hansen, Finn; Schlüter, Maja; Mäs, Michael; Donges, Jonathan F.; Kolb, Jakob J.; Thonicke, Kirsten; Heitzig, Jobst

2017-11-01

Today, humans have a critical impact on the Earth system and vice versa, which can generate complex feedback processes between social and ecological dynamics. Integrating human behavior into formal Earth system models (ESMs), however, requires crucial modeling assumptions about actors and their goals, behavioral options, and decision rules, as well as modeling decisions regarding human social interactions and the aggregation of individuals' behavior. Here, we review existing modeling approaches and techniques from various disciplines and schools of thought dealing with human behavior at different levels of decision making. We demonstrate modelers' often vast degrees of freedom but also seek to make modelers aware of the often crucial consequences of seemingly innocent modeling assumptions. After discussing which socioeconomic units are potentially important for ESMs, we compare models of individual decision making that correspond to alternative behavioral theories and that make diverse modeling assumptions about individuals' preferences, beliefs, decision rules, and foresight. We review approaches to model social interaction, covering game theoretic frameworks, models of social influence, and network models. Finally, we discuss approaches to studying how the behavior of individuals, groups, and organizations can aggregate to complex collective phenomena, discussing agent-based, statistical, and representative-agent modeling and economic macro-dynamics. We illustrate the main ingredients of modeling techniques with examples from land-use dynamics as one of the main drivers of environmental change bridging local to global scales.

Statistical modeling, detection, and segmentation of stains in digitized fabric images

NASA Astrophysics Data System (ADS)

Gururajan, Arunkumar; Sari-Sarraf, Hamed; Hequet, Eric F.

2007-02-01

This paper will describe a novel and automated system based on a computer vision approach, for objective evaluation of stain release on cotton fabrics. Digitized color images of the stained fabrics are obtained, and the pixel values in the color and intensity planes of these images are probabilistically modeled as a Gaussian Mixture Model (GMM). Stain detection is posed as a decision theoretic problem, where the null hypothesis corresponds to absence of a stain. The null hypothesis and the alternate hypothesis mathematically translate into a first order GMM and a second order GMM respectively. The parameters of the GMM are estimated using a modified Expectation-Maximization (EM) algorithm. Minimum Description Length (MDL) is then used as the test statistic to decide the verity of the null hypothesis. The stain is then segmented by a decision rule based on the probability map generated by the EM algorithm. The proposed approach was tested on a dataset of 48 fabric images soiled with stains of ketchup, corn oil, mustard, ragu sauce, revlon makeup and grape juice. The decision theoretic part of the algorithm produced a correct detection rate (true positive) of 93% and a false alarm rate of 5% on these set of images.

The decision to conduct a head-to-head comparative trial: a game-theoretic analysis.

PubMed

Mansley, Edward C; Elbasha, Elamin H; Teutsch, Steven M; Berger, Marc L

2007-01-01

Recent Medicare legislation calls on the Agency for Healthcare Research and Quality to conduct research related to the comparative effectiveness of health care items and services, including prescription drugs. This reinforces earlier calls for head-to-head comparative trials of clinically relevant treatment alternatives. Using a game-theoretic model, the authors explore the decision of pharmaceutical companies to conduct such trials. The model suggests that an important factor affecting this decision is the potential loss in market share and profits following a result of inferiority or comparability. This hidden cost is higher for the market leader than the market follower, making it less likely that the leader will choose to conduct a trial. The model also suggests that in a full-information environment, it will never be the case that both firms choose to conduct such a trial. Furthermore, if market shares and the probability of proving superiority are similar for both firms, it is quite possible that neither firm will choose to conduct a trial. Finally, the results indicate that incentives that offset the direct cost of a trial can prevent a no-trial equilibrium, even when both firms face the possibility of an inferior outcome.

Predictors of Latina/o Community College Student Vocational Choice of STEM Fields: Testing of the STEM-Vocational Choice Model

ERIC Educational Resources Information Center

Johnson, Joel D.

2013-01-01

This study confirmed appropriate measurement model fit for a theoretical model, the STEM vocational choice (STEM-VC) model. This model identifies exogenous factors that successfully predicted, at a statistically significant level, a student's vocational choice decision to pursue a STEM degree at transfer. The student population examined for this…

Attention and choice: a review on eye movements in decision making.

PubMed

Orquin, Jacob L; Mueller Loose, Simone

2013-09-01

This paper reviews studies on eye movements in decision making, and compares their observations to theoretical predictions concerning the role of attention in decision making. Four decision theories are examined: rational models, bounded rationality, evidence accumulation, and parallel constraint satisfaction models. Although most theories were confirmed with regard to certain predictions, none of the theories adequately accounted for the role of attention during decision making. Several observations emerged concerning the drivers and down-stream effects of attention on choice, suggesting that attention processes plays an active role in constructing decisions. So far, decision theories have largely ignored the constructive role of attention by assuming that it is entirely determined by heuristics, or that it consists of stochastic information sampling. The empirical observations reveal that these assumptions are implausible, and that more accurate assumptions could have been made based on prior attention and eye movement research. Future decision making research would benefit from greater integration with attention research. Copyright © 2013 Elsevier B.V. All rights reserved.

A review of clinical decision making: models and current research.

PubMed

Banning, Maggi

2008-01-01

The aim of this paper was to review the current literature clinical decision-making models and the educational application of models to clinical practice. This was achieved by exploring the function and related research of the three available models of clinical decision making: information-processing model, the intuitive-humanist model and the clinical decision-making model. Clinical decision making is a unique process that involves the interplay between knowledge of pre-existing pathological conditions, explicit patient information, nursing care and experiential learning. Historically, two models of clinical decision making are recognized from the literature; the information-processing model and the intuitive-humanist model. The usefulness and application of both models has been examined in relation the provision of nursing care and care related outcomes. More recently a third model of clinical decision making has been proposed. This new multidimensional model contains elements of the information-processing model but also examines patient specific elements that are necessary for cue and pattern recognition. Literature review. Evaluation of the literature generated from MEDLINE, CINAHL, OVID, PUBMED and EBESCO systems and the Internet from 1980 to November 2005. The characteristics of the three models of decision making were identified and the related research discussed. Three approaches to clinical decision making were identified, each having its own attributes and uses. The most recent addition to the clinical decision making is a theoretical, multidimensional model which was developed through an evaluation of current literature and the assessment of a limited number of research studies that focused on the clinical decision-making skills of inexperienced nurses in pseudoclinical settings. The components of this model and the relative merits to clinical practice are discussed. It is proposed that clinical decision making improves as the nurse gains experience of nursing patients within a specific speciality and with experience, nurses gain a sense of saliency in relation to decision making. Experienced nurses may use all three forms of clinical decision making both independently and concurrently to solve nursing-related problems. It is suggested that O'Neill's clinical decision-making model could be tested by educators and experienced nurses to assess the efficacy of this hybrid approach to decision making.

[Clinical reasoning in undergraduate nursing education: a scoping review].

PubMed

Menezes, Sáskia Sampaio Cipriano de; Corrêa, Consuelo Garcia; Silva, Rita de Cássia Gengo E; Cruz, Diná de Almeida Monteiro Lopes da

2015-12-01

This study aimed at analyzing the current state of knowledge on clinical reasoning in undergraduate nursing education. A systematic scoping review through a search strategy applied to the MEDLINE database, and an analysis of the material recovered by extracting data done by two independent reviewers. The extracted data were analyzed and synthesized in a narrative manner. From the 1380 citations retrieved in the search, 23 were kept for review and their contents were summarized into five categories: 1) the experience of developing critical thinking/clinical reasoning/decision-making process; 2) teaching strategies related to the development of critical thinking/clinical reasoning/decision-making process; 3) measurement of variables related to the critical thinking/clinical reasoning/decision-making process; 4) relationship of variables involved in the critical thinking/clinical reasoning/decision-making process; and 5) theoretical development models of critical thinking/clinical reasoning/decision-making process for students. The biggest challenge for developing knowledge on teaching clinical reasoning seems to be finding consistency between theoretical perspectives on the development of clinical reasoning and methodologies, methods, and procedures in research initiatives in this field.

Explaining Moral Behavior.

PubMed

Osman, Magda; Wiegmann, Alex

2017-03-01

In this review we make a simple theoretical argument which is that for theory development, computational modeling, and general frameworks for understanding moral psychology researchers should build on domain-general principles from reasoning, judgment, and decision-making research. Our approach is radical with respect to typical models that exist in moral psychology that tend to propose complex innate moral grammars and even evolutionarily guided moral principles. In support of our argument we show that by using a simple value-based decision model we can capture a range of core moral behaviors. Crucially, the argument we propose is that moral situations per se do not require anything specialized or different from other situations in which we have to make decisions, inferences, and judgments in order to figure out how to act.

QTest: Quantitative Testing of Theories of Binary Choice

PubMed Central

Regenwetter, Michel; Davis-Stober, Clintin P.; Lim, Shiau Hong; Guo, Ying; Popova, Anna; Zwilling, Chris; Cha, Yun-Shil; Messner, William

2014-01-01

The goal of this paper is to make modeling and quantitative testing accessible to behavioral decision researchers interested in substantive questions. We provide a novel, rigorous, yet very general, quantitative diagnostic framework for testing theories of binary choice. This permits the nontechnical scholar to proceed far beyond traditionally rather superficial methods of analysis, and it permits the quantitatively savvy scholar to triage theoretical proposals before investing effort into complex and specialized quantitative analyses. Our theoretical framework links static algebraic decision theory with observed variability in behavioral binary choice data. The paper is supplemented with a custom-designed public-domain statistical analysis package, the QTest software. We illustrate our approach with a quantitative analysis using published laboratory data, including tests of novel versions of “Random Cumulative Prospect Theory.” A major asset of the approach is the potential to distinguish decision makers who have a fixed preference and commit errors in observed choices from decision makers who waver in their preferences. PMID:24999495

Decision-theoretic approach to data acquisition for transit operations planning

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ritchie, S.G.

The most costly element of transportation planning and modeling activities in the past has usually been that of data acquisition. This is even truer today when the unit costs of data collection are increasing rapidly and at the same time budgets are severely limited by continuing policies of fiscal austerity in the public sector. The overall objectives of this research were to improve the decisions and decision-making capabilities of transit operators or planners in short-range transit planning, and to improve the quality and cost-effectiveness of associated route or corridor-level data collection and service monitoring activities. A new approach was presentedmore » for sequentially updating the parameters of both simple and multiple linear regression models with stochastic regressors, and for determining the expected value of sample information and expected net gain of sampling for associated sample designs. A new approach was also presented for estimating and updating (both spatially and temporally) the parameters of multinomial logit discrete choice models, and for determining associated optimal sample designs for attribute-based and choice-based sampling methods. The approach provides an effective framework for addressing the issue of optimal sampling method and sample size, which to date have been largely unresolved. The application of these methodologies and the feasibility of the decision-theoretic approach was illustrated with a hypothetical case study example.« less

Sampling and assessment accuracy in mate choice: a random-walk model of information processing in mating decision.

PubMed

Castellano, Sergio; Cermelli, Paolo

2011-04-07

Mate choice depends on mating preferences and on the manner in which mate-quality information is acquired and used to make decisions. We present a model that describes how these two components of mating decision interact with each other during a comparative evaluation of prospective mates. The model, with its well-explored precedents in psychology and neurophysiology, assumes that decisions are made by the integration over time of noisy information until a stopping-rule criterion is reached. Due to this informational approach, the model builds a coherent theoretical framework for developing an integrated view of functions and mechanisms of mating decisions. From a functional point of view, the model allows us to investigate speed-accuracy tradeoffs in mating decision at both population and individual levels. It shows that, under strong time constraints, decision makers are expected to make fast and frugal decisions and to optimally trade off population-sampling accuracy (i.e. the number of sampled males) against individual-assessment accuracy (i.e. the time spent for evaluating each mate). From the proximate-mechanism point of view, the model makes testable predictions on the interactions of mating preferences and choosiness in different contexts and it might be of compelling empirical utility for a context-independent description of mating preference strength. Copyright © 2011 Elsevier Ltd. All rights reserved.

Crowd Simulation Incorporating Agent Psychological Models, Roles and Communication

DTIC Science & Technology

2005-01-01

system (PMFserv) that implements human behavior models from a range of ability, stress, emotion , decision theoretic and motivation sources. An...autonomous agents, human behavior models, culture and emotions 1. Introduction There are many applications of computer animation and simulation where...We describe a new architecture to integrate a psychological model into a crowd simulation system in order to obtain believable emergent behaviors

Decision making in cancer primary prevention and chemoprevention.

PubMed

Gorin, Sherri Sheinfeld; Wang, Catharine; Raich, Peter; Bowen, Deborah J; Hay, Jennifer

2006-12-01

We know very little about how individuals decide to undertake, maintain, or discontinue cancer primary prevention or chemoprevention. The aims of this article are to (a) examine whether and, if so, how traditional health behavior change models are relevant for decision making in this area; (b) review the application of decision aids to forming specific, personal choices between options; and (c) identify the challenges of evaluating these decision processes to suggest areas for future research. Theoretical models and frameworks derived from the health behavior change and decision-making fields were applied to cancer primary prevention choices. Decision aids for the human papillomavirus (HPV) vaccine, Hormone Replacement Therapy (HRT), and tamoxifen were systematically examined. Traditional concepts such as decisional balance and cues to action are relevant to understanding cancer primary prevention choices; Motivational Interviewing, Self-Determination Theory, and the Preventive Health Model may also explain the facilitators of decision making. There are no well-tested HPV vaccine decision aids, although there have been some studies on aids for HPV testing. There are several effective decision aids for HRT and tamoxifen; evidence-based decision aid components have also been identified. Additional theory-based empirical research on decision making in cancer primary prevention and chemoprevention, particularly at the interface of psychology and behavioral economics, is suggested.

Decision models in the evaluation of psychotropic drugs : useful tool or useless toy?

PubMed

Barbui, Corrado; Lintas, Camilla

2006-09-01

A current contribution in the European Journal of Health Economics employs a decision model to compare health care costs of olanzapine and risperidone treatment for schizophrenia. The model suggests that a treatment strategy of first-line olanzapine is cost-saving over a 1-year period, with additional clinical benefits in the form of avoided relapses in the long-term. From a clinical perspective this finding is indubitably relevant, but can physicians and policy makers believe it? The study is presented in a balanced way, assumptions are based on data extracted from clinical trials published in major psychiatric journals, and the theoretical underpinnings of the model are reasonable. Despite these positive aspects, we believe that the methodology used in this study-the decision model approach-is an unsuitable and potentially misleading tool for evaluating psychotropic drugs. In this commentary, taking the olanzapine vs. risperidone model as an example, arguments are provided to support this statement.

Decision curve analysis: a novel method for evaluating prediction models.

PubMed

Vickers, Andrew J; Elkin, Elena B

2006-01-01

Diagnostic and prognostic models are typically evaluated with measures of accuracy that do not address clinical consequences. Decision-analytic techniques allow assessment of clinical outcomes but often require collection of additional information and may be cumbersome to apply to models that yield a continuous result. The authors sought a method for evaluating and comparing prediction models that incorporates clinical consequences,requires only the data set on which the models are tested,and can be applied to models that have either continuous or dichotomous results. The authors describe decision curve analysis, a simple, novel method of evaluating predictive models. They start by assuming that the threshold probability of a disease or event at which a patient would opt for treatment is informative of how the patient weighs the relative harms of a false-positive and a false-negative prediction. This theoretical relationship is then used to derive the net benefit of the model across different threshold probabilities. Plotting net benefit against threshold probability yields the "decision curve." The authors apply the method to models for the prediction of seminal vesicle invasion in prostate cancer patients. Decision curve analysis identified the range of threshold probabilities in which a model was of value, the magnitude of benefit, and which of several models was optimal. Decision curve analysis is a suitable method for evaluating alternative diagnostic and prognostic strategies that has advantages over other commonly used measures and techniques.

Process-based models are required to manage ecological systems in a changing world

Treesearch

K. Cuddington; M.-J. Fortin; L.R. Gerber; A. Hastings; A. Liebhold; M. OConnor; C. Ray

2013-01-01

Several modeling approaches can be used to guide management decisions. However, some approaches are better fitted than others to address the problem of prediction under global change. Process-based models, which are based on a theoretical understanding of relevant ecological processes, provide a useful framework to incorporate specific responses to altered...

Decision science and cervical cancer.

PubMed

Cantor, Scott B; Fahs, Marianne C; Mandelblatt, Jeanne S; Myers, Evan R; Sanders, Gillian D

2003-11-01

Mathematical modeling is an effective tool for guiding cervical cancer screening, diagnosis, and treatment decisions for patients and policymakers. This article describes the use of mathematical modeling as outlined in five presentations from the Decision Science and Cervical Cancer session of the Second International Conference on Cervical Cancer held at The University of Texas M. D. Anderson Cancer Center, April 11-14, 2002. The authors provide an overview of mathematical modeling, especially decision analysis and cost-effectiveness analysis, and examples of how it can be used for clinical decision making regarding the prevention, diagnosis, and treatment of cervical cancer. Included are applications as well as theory regarding decision science and cervical cancer. Mathematical modeling can answer such questions as the optimal frequency for screening, the optimal age to stop screening, and the optimal way to diagnose cervical cancer. Results from one mathematical model demonstrated that a vaccine against high-risk strains of human papillomavirus was a cost-effective use of resources, and discussion of another model demonstrated the importance of collecting direct non-health care costs and time costs for cost-effectiveness analysis. Research presented indicated that care must be taken when applying the results of population-wide, cost-effectiveness analyses to reduce health disparities. Mathematical modeling can encompass a variety of theoretical and applied issues regarding decision science and cervical cancer. The ultimate objective of using decision-analytic and cost-effectiveness models is to identify ways to improve women's health at an economically reasonable cost. Copyright 2003 American Cancer Society.

Assessing the Clinical Impact of Risk Prediction Models With Decision Curves: Guidance for Correct Interpretation and Appropriate Use

PubMed Central

Brown, Marshall D.; Zhu, Kehao; Janes, Holly

2016-01-01

The decision curve is a graphical summary recently proposed for assessing the potential clinical impact of risk prediction biomarkers or risk models for recommending treatment or intervention. It was applied recently in an article in Journal of Clinical Oncology to measure the impact of using a genomic risk model for deciding on adjuvant radiation therapy for prostate cancer treated with radical prostatectomy. We illustrate the use of decision curves for evaluating clinical- and biomarker-based models for predicting a man’s risk of prostate cancer, which could be used to guide the decision to biopsy. Decision curves are grounded in a decision-theoretical framework that accounts for both the benefits of intervention and the costs of intervention to a patient who cannot benefit. Decision curves are thus an improvement over purely mathematical measures of performance such as the area under the receiver operating characteristic curve. However, there are challenges in using and interpreting decision curves appropriately. We caution that decision curves cannot be used to identify the optimal risk threshold for recommending intervention. We discuss the use of decision curves for miscalibrated risk models. Finally, we emphasize that a decision curve shows the performance of a risk model in a population in which every patient has the same expected benefit and cost of intervention. If every patient has a personal benefit and cost, then the curves are not useful. If subpopulations have different benefits and costs, subpopulation-specific decision curves should be used. As a companion to this article, we released an R software package called DecisionCurve for making decision curves and related graphics. PMID:27247223

Sex Differences in Animal Models of Decision-Making

PubMed Central

Orsini, Caitlin A.; Setlow, Barry

2016-01-01

The ability to weigh the costs and benefits of various options in order to make an adaptive decision is critical to an organism’s survival and well-being. Many psychiatric diseases are characterized by maladaptive decision-making, indicating the need to better understand the mechanisms underlying this process and the ways in which it is altered in pathological conditions. Great strides have been made in uncovering these mechanisms, but the majority of what is known comes from studies conducted solely in male subjects. In recent years, decision-making research has begun to include females to determine whether sex differences exist and to identify the mechanisms that contribute to such differences. This review will begin by describing studies that have examined sex differences in animal (largely rodent) models of decision-making. Possible explanations, both theoretical and biological, for such differences in decision- making will then be considered. The review will conclude with a discussion of the implications of sex differences in decision-making for understanding psychiatric conditions. PMID:27870448

A Game Theoretic Model Of Strategic Conflict In Cyberspace

DTIC Science & Technology

2012-01-01

EXECUTIVE SUMMARY Conflict in cyberspace is difficult to analyze; methods developed for other dimensions of conflict, such as land warfare , war at sea...and missile warfare , do not adequately address cyber conflict. A characteristic that distinguishes cyber conflict is that actors do not know the...strategic and policy guidance. To analyze the strategic decisions involved in cyber conflict, we use a game theoretic framework—we view cyber warfare as a

Ag2S atomic switch-based `tug of war' for decision making

NASA Astrophysics Data System (ADS)

Lutz, C.; Hasegawa, T.; Chikyow, T.

2016-07-01

For a computing process such as making a decision, a software controlled chip of several transistors is necessary. Inspired by how a single cell amoeba decides its movements, the theoretical `tug of war' computing model was proposed but not yet implemented in an analogue device suitable for integrated circuits. Based on this model, we now developed a new electronic element for decision making processes, which will have no need for prior programming. The devices are based on the growth and shrinkage of Ag filaments in α-Ag2+δS gap-type atomic switches. Here we present the adapted device design and the new materials. We demonstrate the basic `tug of war' operation by IV-measurements and Scanning Electron Microscopy (SEM) observation. These devices could be the base for a CMOS-free new computer architecture.For a computing process such as making a decision, a software controlled chip of several transistors is necessary. Inspired by how a single cell amoeba decides its movements, the theoretical `tug of war' computing model was proposed but not yet implemented in an analogue device suitable for integrated circuits. Based on this model, we now developed a new electronic element for decision making processes, which will have no need for prior programming. The devices are based on the growth and shrinkage of Ag filaments in α-Ag2+δS gap-type atomic switches. Here we present the adapted device design and the new materials. We demonstrate the basic `tug of war' operation by IV-measurements and Scanning Electron Microscopy (SEM) observation. These devices could be the base for a CMOS-free new computer architecture. Electronic supplementary information (ESI) available. See DOI: 10.1039/c6nr00690f

An Analysis of Machine- and Human-Analytics in Classification.

PubMed

Tam, Gary K L; Kothari, Vivek; Chen, Min

2017-01-01

In this work, we present a study that traces the technical and cognitive processes in two visual analytics applications to a common theoretic model of soft knowledge that may be added into a visual analytics process for constructing a decision-tree model. Both case studies involved the development of classification models based on the "bag of features" approach. Both compared a visual analytics approach using parallel coordinates with a machine-learning approach using information theory. Both found that the visual analytics approach had some advantages over the machine learning approach, especially when sparse datasets were used as the ground truth. We examine various possible factors that may have contributed to such advantages, and collect empirical evidence for supporting the observation and reasoning of these factors. We propose an information-theoretic model as a common theoretic basis to explain the phenomena exhibited in these two case studies. Together we provide interconnected empirical and theoretical evidence to support the usefulness of visual analytics.

Extensions to regret-based decision curve analysis: an application to hospice referral for terminal patients.

PubMed

Tsalatsanis, Athanasios; Barnes, Laura E; Hozo, Iztok; Djulbegovic, Benjamin

2011-12-23

Despite the well documented advantages of hospice care, most terminally ill patients do not reap the maximum benefit from hospice services, with the majority of them receiving hospice care either prematurely or delayed. Decision systems to improve the hospice referral process are sorely needed. We present a novel theoretical framework that is based on well-established methodologies of prognostication and decision analysis to assist with the hospice referral process for terminally ill patients. We linked the SUPPORT statistical model, widely regarded as one of the most accurate models for prognostication of terminally ill patients, with the recently developed regret based decision curve analysis (regret DCA). We extend the regret DCA methodology to consider harms associated with the prognostication test as well as harms and effects of the management strategies. In order to enable patients and physicians in making these complex decisions in real-time, we developed an easily accessible web-based decision support system available at the point of care. The web-based decision support system facilitates the hospice referral process in three steps. First, the patient or surrogate is interviewed to elicit his/her personal preferences regarding the continuation of life-sustaining treatment vs. palliative care. Then, regret DCA is employed to identify the best strategy for the particular patient in terms of threshold probability at which he/she is indifferent between continuation of treatment and of hospice referral. Finally, if necessary, the probabilities of survival and death for the particular patient are computed based on the SUPPORT prognostication model and contrasted with the patient's threshold probability. The web-based design of the CDSS enables patients, physicians, and family members to participate in the decision process from anywhere internet access is available. We present a theoretical framework to facilitate the hospice referral process. Further rigorous clinical evaluation including testing in a prospective randomized controlled trial is required and planned.

Extensions to Regret-based Decision Curve Analysis: An application to hospice referral for terminal patients

PubMed Central

2011-01-01

Background Despite the well documented advantages of hospice care, most terminally ill patients do not reap the maximum benefit from hospice services, with the majority of them receiving hospice care either prematurely or delayed. Decision systems to improve the hospice referral process are sorely needed. Methods We present a novel theoretical framework that is based on well-established methodologies of prognostication and decision analysis to assist with the hospice referral process for terminally ill patients. We linked the SUPPORT statistical model, widely regarded as one of the most accurate models for prognostication of terminally ill patients, with the recently developed regret based decision curve analysis (regret DCA). We extend the regret DCA methodology to consider harms associated with the prognostication test as well as harms and effects of the management strategies. In order to enable patients and physicians in making these complex decisions in real-time, we developed an easily accessible web-based decision support system available at the point of care. Results The web-based decision support system facilitates the hospice referral process in three steps. First, the patient or surrogate is interviewed to elicit his/her personal preferences regarding the continuation of life-sustaining treatment vs. palliative care. Then, regret DCA is employed to identify the best strategy for the particular patient in terms of threshold probability at which he/she is indifferent between continuation of treatment and of hospice referral. Finally, if necessary, the probabilities of survival and death for the particular patient are computed based on the SUPPORT prognostication model and contrasted with the patient's threshold probability. The web-based design of the CDSS enables patients, physicians, and family members to participate in the decision process from anywhere internet access is available. Conclusions We present a theoretical framework to facilitate the hospice referral process. Further rigorous clinical evaluation including testing in a prospective randomized controlled trial is required and planned. PMID:22196308

The tell-tale look: viewing time, preferences, and prices.

PubMed

Gunia, Brian C; Murnighan, J Keith

2015-01-01

Even the simplest choices can prompt decision-makers to balance their preferences against other, more pragmatic considerations like price. Thus, discerning people's preferences from their decisions creates theoretical, empirical, and practical challenges. The current paper addresses these challenges by highlighting some specific circumstances in which the amount of time that people spend examining potential purchase items (i.e., viewing time) can in fact reveal their preferences. Our model builds from the gazing literature, in a purchasing context, to propose that the informational value of viewing time depends on prices. Consistent with the model's predictions, four studies show that when prices are absent or moderate, viewing time provides a signal that is consistent with a person's preferences and purchase intentions. When prices are extreme or consistent with a person's preferences, however, viewing time is a less reliable predictor of either. Thus, our model highlights a price-contingent "viewing bias," shedding theoretical, empirical, and practical light on the psychology of preferences and visual attention, and identifying a readily observable signal of preference.

Exploring stop-go decision zones at rural high-speed intersections with flashing green signal and insufficient yellow time in China.

PubMed

Tang, Keshuang; Xu, Yanqing; Wang, Fen; Oguchi, Takashi

2016-10-01

The objective of this study is to empirically analyze and model the stop-go decision behavior of drivers at rural high-speed intersections in China, where a flashing green signal of 3s followed by a yellow signal of 3s is commonly applied to end a green phase. 1, 186 high-resolution vehicle trajectories were collected at four typical high-speed intersection approaches in Shanghai and used for the identification of actual stop-go decision zones and the modeling of stop-go decision behavior. Results indicate that the presence of flashing green significantly changed the theoretical decision zones based on the conventional Dilemma Zone theory. The actual stop-go decision zones at the study intersections were thus formulated and identified based on the empirical data. Binary Logistic model and Fuzzy Logic model were then developed to further explore the impacts of flashing green on the stop-go behavior of drivers. It was found that the Fuzzy Logic model could produce comparably good estimation results as compared to the traditional Binary Logistic models. The findings of this study could contribute the development of effective dilemma zone protection strategies, the improvement of stop-go decision model embedded in the microscopic traffic simulation software and the proper design of signal change and clearance intervals at high-speed intersections in China. Copyright © 2016 Elsevier Ltd. All rights reserved.

Partial Planning Reinforcement Learning

DTIC Science & Technology

2012-08-31

Research Office P.O. Box 12211 Research Triangle Park, NC 27709-2211 15. SUBJECT TERMS Reinforcement Learning, Bayesian Optimization, Active ... Learning , Action Model Learning, Decision Theoretic Assistance Prasad Tadepalli, Alan Fern Oregon State University Office of Sponsored Programs Oregon State

Dual Processes in Decision Making and Developmental Neuroscience: A Fuzzy-Trace Model.

PubMed

Reyna, Valerie F; Brainerd, Charles J

2011-09-01

From Piaget to the present, traditional and dual-process theories have predicted improvement in reasoning from childhood to adulthood, and improvement has been observed. However, developmental reversals-that reasoning biases emerge with development -have also been observed in a growing list of paradigms. We explain how fuzzy-trace theory predicts both improvement and developmental reversals in reasoning and decision making. Drawing on research on logical and quantitative reasoning, as well as on risky decision making in the laboratory and in life, we illustrate how the same small set of theoretical principles apply to typical neurodevelopment, encompassing childhood, adolescence, and adulthood, and to neurological conditions such as autism and Alzheimer's disease. For example, framing effects-that risk preferences shift when the same decisions are phrases in terms of gains versus losses-emerge in early adolescence as gist-based intuition develops. In autistic individuals, who rely less on gist-based intuition and more on verbatim-based analysis, framing biases are attenuated (i.e., they outperform typically developing control subjects). In adults, simple manipulations based on fuzzy-trace theory can make framing effects appear and disappear depending on whether gist-based intuition or verbatim-based analysis is induced. These theoretical principles are summarized and integrated in a new mathematical model that specifies how dual modes of reasoning combine to produce predictable variability in performance. In particular, we show how the most popular and extensively studied model of decision making-prospect theory-can be derived from fuzzy-trace theory by combining analytical (verbatim-based) and intuitive (gist-based) processes.

Dual Processes in Decision Making and Developmental Neuroscience: A Fuzzy-Trace Model

PubMed Central

Reyna, Valerie F.; Brainerd, Charles J.

2011-01-01

From Piaget to the present, traditional and dual-process theories have predicted improvement in reasoning from childhood to adulthood, and improvement has been observed. However, developmental reversals—that reasoning biases emerge with development —have also been observed in a growing list of paradigms. We explain how fuzzy-trace theory predicts both improvement and developmental reversals in reasoning and decision making. Drawing on research on logical and quantitative reasoning, as well as on risky decision making in the laboratory and in life, we illustrate how the same small set of theoretical principles apply to typical neurodevelopment, encompassing childhood, adolescence, and adulthood, and to neurological conditions such as autism and Alzheimer's disease. For example, framing effects—that risk preferences shift when the same decisions are phrases in terms of gains versus losses—emerge in early adolescence as gist-based intuition develops. In autistic individuals, who rely less on gist-based intuition and more on verbatim-based analysis, framing biases are attenuated (i.e., they outperform typically developing control subjects). In adults, simple manipulations based on fuzzy-trace theory can make framing effects appear and disappear depending on whether gist-based intuition or verbatim-based analysis is induced. These theoretical principles are summarized and integrated in a new mathematical model that specifies how dual modes of reasoning combine to produce predictable variability in performance. In particular, we show how the most popular and extensively studied model of decision making—prospect theory—can be derived from fuzzy-trace theory by combining analytical (verbatim-based) and intuitive (gist-based) processes. PMID:22096268

From Social Network (Centralized vs. Decentralized) to Collective Decision-Making (Unshared vs. Shared Consensus)

PubMed Central

Sueur, Cédric; Deneubourg, Jean-Louis; Petit, Odile

2012-01-01

Relationships we have with our friends, family, or colleagues influence our personal decisions, as well as decisions we make together with others. As in human beings, despotism and egalitarian societies seem to also exist in animals. While studies have shown that social networks constrain many phenomena from amoebae to primates, we still do not know how consensus emerges from the properties of social networks in many biological systems. We created artificial social networks that represent the continuum from centralized to decentralized organization and used an agent-based model to make predictions about the patterns of consensus and collective movements we observed according to the social network. These theoretical results showed that different social networks and especially contrasted ones – star network vs. equal network - led to totally different patterns. Our model showed that, by moving from a centralized network to a decentralized one, the central individual seemed to lose its leadership in the collective movement's decisions. We, therefore, showed a link between the type of social network and the resulting consensus. By comparing our theoretical data with data on five groups of primates, we confirmed that this relationship between social network and consensus also appears to exist in animal societies. PMID:22393416

Other People’s Money: The Role of Reciprocity and Social Uncertainty in Decisions for Others

PubMed Central

2017-01-01

Many important decisions are taken not by the person who will ultimately gain or lose from the outcome, but on their behalf, by somebody else. We examined economic decision-making about risk and time in situations in which deciders chose for others who also chose for them. We propose that this unique setting, which has not been studied before, elicits perception of reciprocity that prompts a unique bias in preferences. We found that decision-makers are less patient (more discounting), and more risk averse for losses than gains, with other peoples’ money, especially when their choices for others are more uncertain. Those results were derived by exploiting a computational modeling framework that has been shown to account for the underlying psychological and neural decision processes. We propose a novel theoretical mechanism—precautionary preferences under social uncertainty, which explains the findings. Implications for future research and alternative models are also discussed. PMID:29456782

Technology diffusion and environmental regulation: Evidence from electric power plants under the Clean Air Act

NASA Astrophysics Data System (ADS)

Frey, Elaine F.

Even though environmental policy can greatly affect the path of technology diffusion, the economics literature contains limited empirical evidence of this relationship. My research will contribute to the available evidence by providing insight into the technology adoption decisions of electric generating firms. Since policies are often evaluated based on the incentives they provide to promote adoption of new technologies, it is important that policy makers understand the relationship between technological diffusion and regulation structure to make informed decisions. Lessons learned from this study can be used to guide future policies such as those directed to mitigate climate change. I first explore the diffusion of scrubbers, a sulfur dioxide (SO 2) abatement technology, in response to federal market-based regulations and state command-and-control regulations. I develop a simple theoretical model to describe the adoption decisions of scrubbers and use a survival model to empirically test the theoretical model. I find that power plants with strict command-and-control regulations have a high probability of installing a scrubber. These findings suggest that although market-based regulations have encouraged diffusion, many scrubbers have been installed because of state regulatory pressure. Although tradable permit systems are thought to give firms more flexibility in choosing abatement technologies, I show that interactions between a permit system and pre-existing command-and-control regulations can limit that flexibility. In a separate analysis, I explore the diffusion of combined cycle (CC) generating units, which are natural gas-fired generating units that are cleaner and more efficient than alternative generating units. I model the decision to consider adoption of a CC generating unit and the extent to which the technology is adopted in response to environmental regulations imposed on new sources of pollutants. To accomplish this, I use a zero-inflated Poisson model and focus on both the decision to adopt a CC unit at an existing power plant as well as the firm-level decision to adopt a CC unit in either a new or an existing power plant. Evidence from this empirical investigation shows that environmental regulation has a significant effect on both the decision to consider adoption as well as the extent of adoption.

Core competencies for shared decision making training programs: insights from an international, interdisciplinary working group.

PubMed

Légaré, France; Moumjid-Ferdjaoui, Nora; Drolet, Renée; Stacey, Dawn; Härter, Martin; Bastian, Hilda; Beaulieu, Marie-Dominique; Borduas, Francine; Charles, Cathy; Coulter, Angela; Desroches, Sophie; Friedrich, Gwendolyn; Gafni, Amiram; Graham, Ian D; Labrecque, Michel; LeBlanc, Annie; Légaré, Jean; Politi, Mary; Sargeant, Joan; Thomson, Richard

2013-01-01

Shared decision making is now making inroads in health care professionals' continuing education curriculum, but there is no consensus on what core competencies are required by clinicians for effectively involving patients in health-related decisions. Ready-made programs for training clinicians in shared decision making are in high demand, but existing programs vary widely in their theoretical foundations, length, and content. An international, interdisciplinary group of 25 individuals met in 2012 to discuss theoretical approaches to making health-related decisions, compare notes on existing programs, take stock of stakeholders concerns, and deliberate on core competencies. This article summarizes the results of those discussions. Some participants believed that existing models already provide a sufficient conceptual basis for developing and implementing shared decision making competency-based training programs on a wide scale. Others argued that this would be premature as there is still no consensus on the definition of shared decision making or sufficient evidence to recommend specific competencies for implementing shared decision making. However, all participants agreed that there were 2 broad types of competencies that clinicians need for implementing shared decision making: relational competencies and risk communication competencies. Further multidisciplinary research could broaden and deepen our understanding of core competencies for shared decision making training. Copyright © 2013 The Alliance for Continuing Education in the Health Professions, the Society for Academic Continuing Medical Education, and the Council on CME, Association for Hospital Medical Education.

(Fish) Food for Thought: Authority Shifts in the Interaction between Mathematics and Reality

ERIC Educational Resources Information Center

Peled, Irit

2010-01-01

This theoretical paper explores the decision-making process involved in modelling and mathematizing situations during problem solving. Specifically, it focuses on the authority behind these choices (i.e., what or who determines the chosen mathematical models). We show that different types of situations involve different sources of authority,…

Assessing Intelligence in Children and Youth Living in the Netherlands

ERIC Educational Resources Information Center

Hurks, Petra P. M.; Bakker, Helen

2016-01-01

In this article, we briefly describe the history of intelligence test use with children and youth in the Netherlands, explain which models of intelligence guide decisions about test use, and detail how intelligence tests are currently being used in Dutch school settings. Empirically supported and theoretical models studying the structure of human…

The Evidence Base for Gypsy and Traveller Site Planning: A Story of Complexity and Tension

ERIC Educational Resources Information Center

Niner, Pat; Brown, Philip

2011-01-01

The linear technical-rational model has been heavily criticised as theoretically, politically and practically inadequate. The example of accommodation needs assessment as evidence for highly contentious decisions on Gypsy and Traveller caravan site provision suggests, however, that the technical-rational model has great value in coping with…

The decision of out-of-home placement in residential care after parental neglect: Empirically testing a psychosocial model.

PubMed

Rodrigues, Leonor; Calheiros, Manuela; Pereira, Cícero

2015-11-01

Out-of-home placement decisions in residential care are complex, ambiguous and full of uncertainty, especially in cases of parental neglect. Literature on this topic is so far unable to understand and demonstrate the source of errors involved in those decisions and still fails to focus on professional's decision making process. Therefore, this work intends to test a socio-psychological model of decision-making that is a more integrated, dualistic and ecological version of the Theory of Planned Behavior's model. It describes the process through which the decision maker takes into account personal, contextual and social factors of the Decision-Making Ecology in the definition of his/her decision threshold. One hundred and ninety-five professionals from different Children and Youth Protection Units, throughout the Portuguese territory, participated in this online study. After reading a vignette of a (psychological and physical) neglect case toward a one-year-old child, participants were presented with a group of questions that measured worker's assessment of risk, intention, attitude, subjective norm, behavior control and beliefs toward residential care placement decision, as well as worker's behavior experience, emotions and family/child-related-values involved in that decision. A set of structural equation modeling analyses have proven the good fit of the proposed model. The intention to propose a residential care placement decision was determined by cognitive, social, affective, value-laden and experience variables and the perceived risk. Altogether our model explained 61% of professional's decision toward a parental neglect case. The theoretical and practical implications of these results are discussed, namely the importance of raising awareness about the existence of these biased psychosocial determinants. Copyright © 2015 Elsevier Ltd. All rights reserved.

Group decisions in biodiversity conservation: implications from game theory.

PubMed

Frank, David M; Sarkar, Sahotra

2010-05-27

Decision analysis and game theory have proved useful tools in various biodiversity conservation planning and modeling contexts. This paper shows how game theory may be used to inform group decisions in biodiversity conservation scenarios by modeling conflicts between stakeholders to identify Pareto-inefficient Nash equilibria. These are cases in which each agent pursuing individual self-interest leads to a worse outcome for all, relative to other feasible outcomes. Three case studies from biodiversity conservation contexts showing this feature are modeled to demonstrate how game-theoretical representation can inform group decision-making. The mathematical theory of games is used to model three biodiversity conservation scenarios with Pareto-inefficient Nash equilibria: (i) a two-agent case involving wild dogs in South Africa; (ii) a three-agent raptor and grouse conservation scenario from the United Kingdom; and (iii) an n-agent fish and coral conservation scenario from the Philippines. In each case there is reason to believe that traditional mechanism-design solutions that appeal to material incentives may be inadequate, and the game-theoretical analysis recommends a resumption of further deliberation between agents and the initiation of trust--and confidence--building measures. Game theory can and should be used as a normative tool in biodiversity conservation contexts: identifying scenarios with Pareto-inefficient Nash equilibria enables constructive action in order to achieve (closer to) optimal conservation outcomes, whether by policy solutions based on mechanism design or otherwise. However, there is mounting evidence that formal mechanism-design solutions may backfire in certain cases. Such scenarios demand a return to group deliberation and the creation of reciprocal relationships of trust.

Toward a Model of Human Information Processing for Decision-Making and Skill Acquisition in Laparoscopic Colorectal Surgery.

PubMed

White, Eoin J; McMahon, Muireann; Walsh, Michael T; Coffey, J Calvin; O Sullivan, Leonard

To create a human information-processing model for laparoscopic surgery based on already established literature and primary research to enhance laparoscopic surgical education in this context. We reviewed the literature for information-processing models most relevant to laparoscopic surgery. Our review highlighted the necessity for a model that accounts for dynamic environments, perception, allocation of attention resources between the actions of both hands of an operator, and skill acquisition and retention. The results of the literature review were augmented through intraoperative observations of 7 colorectal surgical procedures, supported by laparoscopic video analysis of 12 colorectal procedures. The Wickens human information-processing model was selected as the most relevant theoretical model to which we make adaptions for this specific application. We expanded the perception subsystem of the model to involve all aspects of perception during laparoscopic surgery. We extended the decision-making system to include dynamic decision-making to account for case/patient-specific and surgeon-specific deviations. The response subsystem now includes dual-task performance and nontechnical skills, such as intraoperative communication. The memory subsystem is expanded to include skill acquisition and retention. Surgical decision-making during laparoscopic surgery is the result of a highly complex series of processes influenced not only by the operator's knowledge, but also patient anatomy and interaction with the surgical team. Newer developments in simulation-based education must focus on the theoretically supported elements and events that underpin skill acquisition and affect the cognitive abilities of novice surgeons. The proposed human information-processing model builds on established literature regarding information processing, accounting for a dynamic environment of laparoscopic surgery. This revised model may be used as a foundation for a model describing robotic surgery. Copyright © 2017 Association of Program Directors in Surgery. Published by Elsevier Inc. All rights reserved.

A social discounting model based on Tsallis’ statistics

NASA Astrophysics Data System (ADS)

Takahashi, Taiki

2010-09-01

Social decision making (e.g. social discounting and social preferences) has been attracting attention in economics, econophysics, social physics, behavioral psychology, and neuroeconomics. This paper proposes a novel social discounting model based on the deformed algebra developed in the Tsallis’ non-extensive thermostatistics. Furthermore, it is suggested that this model can be utilized to quantify the degree of consistency in social discounting in humans and analyze the relationships between behavioral tendencies in social discounting and other-regarding economic decision making under game-theoretic conditions. Future directions in the application of the model to studies in econophysics, neuroeconomics, and social physics, as well as real-world problems such as the supply of live organ donations, are discussed.

Operational Plan Ontology Model for Interconnection and Interoperability

NASA Astrophysics Data System (ADS)

Long, F.; Sun, Y. K.; Shi, H. Q.

2017-03-01

Aiming at the assistant decision-making system’s bottleneck of processing the operational plan data and information, this paper starts from the analysis of the problem of traditional expression and the technical advantage of ontology, and then it defines the elements of the operational plan ontology model and determines the basis of construction. Later, it builds up a semi-knowledge-level operational plan ontology model. Finally, it probes into the operational plan expression based on the operational plan ontology model and the usage of the application software. Thus, this paper has the theoretical significance and application value in the improvement of interconnection and interoperability of the operational plan among assistant decision-making systems.

A Computational Approach to Characterizing the Impact of Social Influence on Individuals’ Vaccination Decision Making

PubMed Central

Xia, Shang; Liu, Jiming

2013-01-01

In modeling individuals vaccination decision making, existing studies have typically used the payoff-based (e.g., game-theoretical) approaches that evaluate the risks and benefits of vaccination. In reality, whether an individual takes vaccine or not is also influenced by the decisions of others, i.e., due to the impact of social influence. In this regard, we present a dual-perspective view on individuals decision making that incorporates both the cost analysis of vaccination and the impact of social influence. In doing so, we consider a group of individuals making their vaccination decisions by both minimizing the associated costs and evaluating the decisions of others. We apply social impact theory (SIT) to characterize the impact of social influence with respect to individuals interaction relationships. By doing so, we propose a novel modeling framework that integrates an extended SIT-based characterization of social influence with a game-theoretical analysis of cost minimization. We consider the scenario of voluntary vaccination against an influenza-like disease through a series of simulations. We investigate the steady state of individuals’ decision making, and thus, assess the impact of social influence by evaluating the coverage of vaccination for infectious diseases control. Our simulation results suggest that individuals high conformity to social influence will increase the vaccination coverage if the cost of vaccination is low, and conversely, will decrease it if the cost is high. Interestingly, if individuals are social followers, the resulting vaccination coverage would converge to a certain level, depending on individuals’ initial level of vaccination willingness rather than the associated costs. We conclude that social influence will have an impact on the control of an infectious disease as they can affect the vaccination coverage. In this respect, our work can provide a means for modeling the impact of social influence as well as for estimating the effectiveness of a voluntary vaccination program. PMID:23585835

A computational approach to characterizing the impact of social influence on individuals' vaccination decision making.

PubMed

Xia, Shang; Liu, Jiming

2013-01-01

In modeling individuals vaccination decision making, existing studies have typically used the payoff-based (e.g., game-theoretical) approaches that evaluate the risks and benefits of vaccination. In reality, whether an individual takes vaccine or not is also influenced by the decisions of others, i.e., due to the impact of social influence. In this regard, we present a dual-perspective view on individuals decision making that incorporates both the cost analysis of vaccination and the impact of social influence. In doing so, we consider a group of individuals making their vaccination decisions by both minimizing the associated costs and evaluating the decisions of others. We apply social impact theory (SIT) to characterize the impact of social influence with respect to individuals interaction relationships. By doing so, we propose a novel modeling framework that integrates an extended SIT-based characterization of social influence with a game-theoretical analysis of cost minimization. We consider the scenario of voluntary vaccination against an influenza-like disease through a series of simulations. We investigate the steady state of individuals' decision making, and thus, assess the impact of social influence by evaluating the coverage of vaccination for infectious diseases control. Our simulation results suggest that individuals high conformity to social influence will increase the vaccination coverage if the cost of vaccination is low, and conversely, will decrease it if the cost is high. Interestingly, if individuals are social followers, the resulting vaccination coverage would converge to a certain level, depending on individuals' initial level of vaccination willingness rather than the associated costs. We conclude that social influence will have an impact on the control of an infectious disease as they can affect the vaccination coverage. In this respect, our work can provide a means for modeling the impact of social influence as well as for estimating the effectiveness of a voluntary vaccination program.

Neural Underpinnings of Decision Strategy Selection: A Review and a Theoretical Model.

PubMed

Wichary, Szymon; Smolen, Tomasz

2016-01-01

In multi-attribute choice, decision makers use decision strategies to arrive at the final choice. What are the neural mechanisms underlying decision strategy selection? The first goal of this paper is to provide a literature review on the neural underpinnings and cognitive models of decision strategy selection and thus set the stage for a neurocognitive model of this process. The second goal is to outline such a unifying, mechanistic model that can explain the impact of noncognitive factors (e.g., affect, stress) on strategy selection. To this end, we review the evidence for the factors influencing strategy selection, the neural basis of strategy use and the cognitive models of this process. We also present the Bottom-Up Model of Strategy Selection (BUMSS). The model assumes that the use of the rational Weighted Additive strategy and the boundedly rational heuristic Take The Best can be explained by one unifying, neurophysiologically plausible mechanism, based on the interaction of the frontoparietal network, orbitofrontal cortex, anterior cingulate cortex and the brainstem nucleus locus coeruleus. According to BUMSS, there are three processes that form the bottom-up mechanism of decision strategy selection and lead to the final choice: (1) cue weight computation, (2) gain modulation, and (3) weighted additive evaluation of alternatives. We discuss how these processes might be implemented in the brain, and how this knowledge allows us to formulate novel predictions linking strategy use and neural signals.

Agent-Centric Approach for Cybersecurity Decision-Support with Partial Observability

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tipireddy, Ramakrishna; Chatterjee, Samrat; Paulson, Patrick R.

Generating automated cyber resilience policies for real-world settings is a challenging research problem that must account for uncertainties in system state over time and dynamics between attackers and defenders. In addition to understanding attacker and defender motives and tools, and identifying “relevant” system and attack data, it is also critical to develop rigorous mathematical formulations representing the defender’s decision-support problem under uncertainty. Game-theoretic approaches involving cyber resource allocation optimization with Markov decision processes (MDP) have been previously proposed in the literature. Moreover, advancements in reinforcement learning approaches have motivated the development of partially observable stochastic games (POSGs) in various multi-agentmore » problem domains with partial information. Recent advances in cyber-system state space modeling have also generated interest in potential applicability of POSGs for cybersecurity. However, as is the case in strategic card games such as poker, research challenges using game-theoretic approaches for practical cyber defense applications include: 1) solving for equilibrium and designing efficient algorithms for large-scale, general problems; 2) establishing mathematical guarantees that equilibrium exists; 3) handling possible existence of multiple equilibria; and 4) exploitation of opponent weaknesses. Inspired by advances in solving strategic card games while acknowledging practical challenges associated with the use of game-theoretic approaches in cyber settings, this paper proposes an agent-centric approach for cybersecurity decision-support with partial system state observability.« less

Intelligence moderates neural responses to monetary reward and punishment.

PubMed

Hawes, Daniel R; DeYoung, Colin G; Gray, Jeremy R; Rustichini, Aldo

2014-05-01

The relations between intelligence (IQ) and neural responses to monetary gains and losses were investigated in a simple decision task. In 94 healthy adults, typical responses of striatal blood oxygen level-dependent (BOLD) signal after monetary reward and punishment were weaker for subjects with higher IQ. IQ-moderated differential responses to gains and losses were also found for regions in the medial prefrontal cortex, posterior cingulate cortex, and left inferior frontal cortex. These regions have previously been identified with the subjective utility of monetary outcomes. Analysis of subjects' behavior revealed a correlation between IQ and the extent to which choices were related to experienced decision outcomes in preceding trials. Specifically, higher IQ predicted behavior to be more strongly correlated with an extended period of previously experienced decision outcomes, whereas lower IQ predicted behavior to be correlated exclusively to the most recent decision outcomes. We link these behavioral and imaging findings to a theoretical model capable of describing a role for intelligence during the evaluation of rewards generated by unknown probabilistic processes. Our results demonstrate neural differences in how people of different intelligence respond to experienced monetary rewards and punishments. Our theoretical discussion offers a functional description for how these individual differences may be linked to choice behavior. Together, our results and model support the hypothesis that observed correlations between intelligence and preferences may be rooted in the way decision outcomes are experienced ex post, rather than deriving exclusively from how choices are evaluated ex ante.

Classification images reveal decision variables and strategies in forced choice tasks

PubMed Central

Pritchett, Lisa M.; Murray, Richard F.

2015-01-01

Despite decades of research, there is still uncertainty about how people make simple decisions about perceptual stimuli. Most theories assume that perceptual decisions are based on decision variables, which are internal variables that encode task-relevant information. However, decision variables are usually considered to be theoretical constructs that cannot be measured directly, and this often makes it difficult to test theories of perceptual decision making. Here we show how to measure decision variables on individual trials, and we use these measurements to test theories of perceptual decision making more directly than has previously been possible. We measure classification images, which are estimates of templates that observers use to extract information from stimuli. We then calculate the dot product of these classification images with the stimuli to estimate observers' decision variables. Finally, we reconstruct each observer's “decision space,” a map that shows the probability of the observer’s responses for all values of the decision variables. We use this method to examine decision strategies in two-alternative forced choice (2AFC) tasks, for which there are several competing models. In one experiment, the resulting decision spaces support the difference model, a classic theory of 2AFC decisions. In a second experiment, we find unexpected decision spaces that are not predicted by standard models of 2AFC decisions, and that suggest intrinsic uncertainty or soft thresholding. These experiments give new evidence regarding observers’ strategies in 2AFC tasks, and they show how measuring decision variables can answer long-standing questions about perceptual decision making. PMID:26015584

A decision-theoretic approach to the display of information for time-critical decisions: The Vista project

NASA Technical Reports Server (NTRS)

Horvitz, Eric; Ruokangas, Corinne; Srinivas, Sampath; Barry, Matthew

1993-01-01

We describe a collaborative research and development effort between the Palo Alto Laboratory of the Rockwell Science Center, Rockwell Space Operations Company, and the Propulsion Systems Section of NASA JSC to design computational tools that can manage the complexity of information displayed to human operators in high-stakes, time-critical decision contexts. We shall review an application from NASA Mission Control and describe how we integrated a probabilistic diagnostic model and a time-dependent utility model, with techniques for managing the complexity of computer displays. Then, we shall describe the behavior of VPROP, a system constructed to demonstrate promising display-management techniques. Finally, we shall describe our current research directions on the Vista 2 follow-on project.

Cognitive continuum theory in interprofessional healthcare: A critical analysis.

PubMed

Parker-Tomlin, Michelle; Boschen, Mark; Morrissey, Shirley; Glendon, Ian

2017-07-01

Effective clinical decision making is among the most important skills required by healthcare practitioners. Making sound decisions while working collaboratively in interprofessional healthcare teams is essential for modern healthcare planning, successful interventions, and patient care. The cognitive continuum theory (CCT) is a model of human judgement and decision making aimed at orienting decision-making processes. CCT has the potential to improve both individual health practitioner, and interprofessional team understanding about, and communication of, clinical decision-making processes. Examination of the current application of CCT indicates that this theory could strengthen interprofessional team clinical decision making (CDM). However, further research is needed before extending the use of this theoretical framework to a wider range of interprofessional healthcare team processes. Implications for research, education, practice, and policy are addressed.

How Costs Influence Decision Values for Mixed Outcomes

PubMed Central

Talmi, Deborah; Pine, Alex

2012-01-01

The things that we hold dearest often require a sacrifice, as epitomized in the maxim “no pain, no gain.” But how is the subjective value of outcomes established when they consist of mixtures of costs and benefits? We describe theoretical models for the integration of costs and benefits into a single value, drawing on both the economic and the empirical literatures, with the goal of rendering them accessible to the neuroscience community. We propose two key assays that go beyond goodness of fit for deciding between the dominant additive model and four varieties of interactive models. First, how they model decisions between costs when reward is not on offer; and second, whether they predict changes in reward sensitivity when costs are added to outcomes, and in what direction. We provide a selective review of relevant neurobiological work from a computational perspective, focusing on those studies that illuminate the underlying valuation mechanisms. Cognitive neuroscience has great potential to decide which of the theoretical models is actually employed by our brains, but empirical work has yet to fully embrace this challenge. We hope that future research improves our understanding of how our brain decides whether mixed outcomes are worthwhile. PMID:23112758

Neuroeconomics: cross-currents in research on decision-making.

PubMed

Sanfey, Alan G; Loewenstein, George; McClure, Samuel M; Cohen, Jonathan D

2006-03-01

Despite substantial advances, the question of how we make decisions and judgments continues to pose important challenges for scientific research. Historically, different disciplines have approached this problem using different techniques and assumptions, with few unifying efforts made. However, the field of neuroeconomics has recently emerged as an inter-disciplinary effort to bridge this gap. Research in neuroscience and psychology has begun to investigate neural bases of decision predictability and value, central parameters in the economic theory of expected utility. Economics, in turn, is being increasingly influenced by a multiple-systems approach to decision-making, a perspective strongly rooted in psychology and neuroscience. The integration of these disparate theoretical approaches and methodologies offers exciting potential for the construction of more accurate models of decision-making.

Individual Confidence-Weighting and Group Decision-Making.

PubMed

Marshall, James A R; Brown, Gavin; Radford, Andrew N

2017-09-01

Group-living species frequently pool individual information so as to reach consensus decisions such as when and where to move, or whether a predator is present. Such opinion-pooling has been demonstrated empirically, and theoretical models have been proposed to explain why group decisions are more reliable than individual decisions. Behavioural ecology theory frequently assumes that all individuals have equal decision-making abilities, but decision theory relaxes this assumption and has been tested in human groups. We summarise relevant theory and argue for its applicability to collective animal decisions. We consider selective pressure on confidence-weighting in groups of related and unrelated individuals. We also consider which species and behaviours may provide evidence of confidence-weighting, paying particular attention to the sophisticated vocal communication of cooperative breeders. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

[Interoception and decision-making].

PubMed

Ohira, Hideki

2015-02-01

We sometimes make decisions relying not necessarily on deliberative thoughts but on intuitive and emotional processes in uncertain situations. The somatic marker hypothesis proposed by Damasio argued that interoception, which means bodily responses such as sympathetic activity, can be represented in the insula and anterior cingulate cortex and can play critical roles in decision-making. Though this hypothesis has been criticized in its theoretical and empirical aspects, recent studies are expanding the hypothesis to elucidate multiple bodily responses including autonomic, endocrine, and immune activities that affect decision-making. In addition, cumulative findings suggest that the anterior insula where the inner model of interoception is represented can act as an interface between the brain and body in decision-making. This article aims to survey recent findings on the brain-body interplays underlying decision-making, and to propose hypotheses on the significance of the body in decision-making.

An economic analysis of harvest behavior: integrating forest and ownership characteristics

Treesearch

Donald F. Dennis

1989-01-01

This study provides insight into the determinants of timber supply from private forests through development of both theoretical and empirical models of harvest behavior. A microeconomic model encompasses the multiple objective nature of private ownership by examining the harvest decision for landowners who derive utility from forest amenities and from income used for...

Modelling emergency decisions: recognition-primed decision making. The literature in relation to an ophthalmic critical incident.

PubMed

Bond, Susan; Cooper, Simon

2006-08-01

To review and reflect on the literature on recognition-primed decision (RPD) making and influences on emergency decisions with particular reference to an ophthalmic critical incident involving the sub-arachnoid spread of local anaesthesia following the peribulbar injection. This paper critics the literature on recognition-primed decision making, with particular reference to emergency situations. It illustrates the findings by focussing on an ophthalmic critical incident. Systematic literature review with critical incident reflection. Medline, CINAHL and PsychINFO databases were searched for papers on recognition-primed decision making (1996-2004) followed by the 'snowball method'. Studies were selected in accordance with preset criteria. A total of 12 papers were included identifying the recognition-primed decision making as a good theoretical description of acute emergency decisions. In addition, cognitive resources, situational awareness, stress, team support and task complexity were identified as influences on the decision process. Recognition-primed decision-making theory describes the decision processes of experts in time-bound emergency situations and is the foundation for a model of emergency decision making (Fig. 2). Decision theory and models, in this case related to emergency situations, inform practice and enhance clinical effectiveness. The critical incident described highlights the need for nurses to have a comprehensive and in-depth understanding of anaesthetic techniques as well as an ability to manage and resuscitate patients autonomously. In addition, it illustrates how the critical incidents should influence the audit cycle with improvements in patient safety.

Lung Cancer Screening Participation: Developing a Conceptual Model to Guide Research

PubMed Central

Carter-Harris, Lisa; Davis, Lorie L.; Rawl, Susan M.

2017-01-01

Purpose To describe the development of a conceptual model to guide research focused on lung cancer screening participation from the perspective of the individual in the decision-making process. Methods Based on a comprehensive review of empirical and theoretical literature, a conceptual model was developed linking key psychological variables (stigma, medical mistrust, fatalism, worry, and fear) to the health belief model and precaution adoption process model. Results Proposed model concepts have been examined in prior research of either lung or other cancer screening behavior. To date, a few studies have explored a limited number of variables that influence screening behavior in lung cancer specifically. Therefore, relationships among concepts in the model have been proposed and future research directions presented. Conclusion This proposed model is an initial step to support theoretically based research. As lung cancer screening becomes more widely implemented, it is critical to theoretically guide research to understand variables that may be associated with lung cancer screening participation. Findings from future research guided by the proposed conceptual model can be used to refine the model and inform tailored intervention development. PMID:28304262

Lung Cancer Screening Participation: Developing a Conceptual Model to Guide Research.

PubMed

Carter-Harris, Lisa; Davis, Lorie L; Rawl, Susan M

2016-11-01

To describe the development of a conceptual model to guide research focused on lung cancer screening participation from the perspective of the individual in the decision-making process. Based on a comprehensive review of empirical and theoretical literature, a conceptual model was developed linking key psychological variables (stigma, medical mistrust, fatalism, worry, and fear) to the health belief model and precaution adoption process model. Proposed model concepts have been examined in prior research of either lung or other cancer screening behavior. To date, a few studies have explored a limited number of variables that influence screening behavior in lung cancer specifically. Therefore, relationships among concepts in the model have been proposed and future research directions presented. This proposed model is an initial step to support theoretically based research. As lung cancer screening becomes more widely implemented, it is critical to theoretically guide research to understand variables that may be associated with lung cancer screening participation. Findings from future research guided by the proposed conceptual model can be used to refine the model and inform tailored intervention development.

A normative inference approach for optimal sample sizes in decisions from experience

PubMed Central

Ostwald, Dirk; Starke, Ludger; Hertwig, Ralph

2015-01-01

“Decisions from experience” (DFE) refers to a body of work that emerged in research on behavioral decision making over the last decade. One of the major experimental paradigms employed to study experience-based choice is the “sampling paradigm,” which serves as a model of decision making under limited knowledge about the statistical structure of the world. In this paradigm respondents are presented with two payoff distributions, which, in contrast to standard approaches in behavioral economics, are specified not in terms of explicit outcome-probability information, but by the opportunity to sample outcomes from each distribution without economic consequences. Participants are encouraged to explore the distributions until they feel confident enough to decide from which they would prefer to draw from in a final trial involving real monetary payoffs. One commonly employed measure to characterize the behavior of participants in the sampling paradigm is the sample size, that is, the number of outcome draws which participants choose to obtain from each distribution prior to terminating sampling. A natural question that arises in this context concerns the “optimal” sample size, which could be used as a normative benchmark to evaluate human sampling behavior in DFE. In this theoretical study, we relate the DFE sampling paradigm to the classical statistical decision theoretic literature and, under a probabilistic inference assumption, evaluate optimal sample sizes for DFE. In our treatment we go beyond analytically established results by showing how the classical statistical decision theoretic framework can be used to derive optimal sample sizes under arbitrary, but numerically evaluable, constraints. Finally, we critically evaluate the value of deriving optimal sample sizes under this framework as testable predictions for the experimental study of sampling behavior in DFE. PMID:26441720

Using sense-making theory to aid understanding of the recognition, assessment and management of pain in patients with dementia in acute hospital settings.

PubMed

Dowding, Dawn; Lichtner, Valentina; Allcock, Nick; Briggs, Michelle; James, Kirstin; Keady, John; Lasrado, Reena; Sampson, Elizabeth L; Swarbrick, Caroline; José Closs, S

2016-01-01

The recognition, assessment and management of pain in hospital settings is suboptimal, and is a particular challenge in patients with dementia. The existing process guiding pain assessment and management in clinical settings is based on the assumption that nurses follow a sequential linear approach to decision making. In this paper we re-evaluate this theoretical assumption drawing on findings from a study of pain recognition, assessment and management in patients with dementia. To provide a revised conceptual model of pain recognition, assessment and management based on sense-making theories of decision making. The research we refer to is an exploratory ethnographic study using nested case sites. Patients with dementia (n=31) were the unit of data collection, nested in 11 wards (vascular, continuing care, stroke rehabilitation, orthopaedic, acute medicine, care of the elderly, elective and emergency surgery), located in four NHS hospital organizations in the UK. Data consisted of observations of patients at bedside (170h in total); observations of the context of care; audits of patient hospital records; documentary analysis of artefacts; semi-structured interviews (n=56) and informal open conversations with staff and carers (family members). Existing conceptualizations of pain recognition, assessment and management do not fully explain how the decision process occurs in clinical practice. Our research indicates that pain recognition, assessment and management is not an individual cognitive activity; rather it is carried out by groups of individuals over time and within a specific organizational culture or climate, which influences both health care professional and patient behaviour. We propose a revised theoretical model of decision making related to pain assessment and management for patients with dementia based on theories of sense-making, which is reflective of the reality of clinical decision making in acute hospital wards. The revised model recognizes the salience of individual cognition as well as acknowledging that decisions are constructed through social interaction and organizational context. The model will be used in further research to develop decision support interventions to assist with the assessment and management of patients with dementia in acute hospital settings. Copyright © 2015. Published by Elsevier Ltd.

Multistable binary decision making on networks

NASA Astrophysics Data System (ADS)

Lucas, Andrew; Lee, Ching Hua

2013-03-01

We propose a simple model for a binary decision making process on a graph, motivated by modeling social decision making with cooperative individuals. The model is similar to a random field Ising model or fiber bundle model, but with key differences in behavior on heterogeneous networks. For many types of disorder and interactions between the nodes, we predict with mean field theory discontinuous phase transitions that are largely independent of network structure. We show how these phase transitions can also be understood by studying microscopic avalanches and describe how network structure enhances fluctuations in the distribution of avalanches. We suggest theoretically the existence of a “glassy” spectrum of equilibria associated with a typical phase, even on infinite graphs, so long as the first moment of the degree distribution is finite. This behavior implies that the model is robust against noise below a certain scale and also that phase transitions can switch from discontinuous to continuous on networks with too few edges. Numerical simulations suggest that our theory is accurate.

Aircraft accident investigation: the decision-making in initial action scenario.

PubMed

Barreto, Marcia M; Ribeiro, Selma L O

2012-01-01

In the complex aeronautical environment, the efforts in terms of operational safety involve the adoption of proactive and reactive measures. The process of investigation begins right after the occurrence of the aeronautical accident, through the initial action. Thus, it is in the crisis scenario, that the person responsible for the initial action makes decisions and gathers the necessary information for the subsequent phases of the investigation process. Within this scenario, which is a natural environment, researches have shown the fragility of rational models of decision making. The theoretical perspective of naturalistic decision making constitutes a breakthrough in the understanding of decision problems demanded by real world. The proposal of this study was to verify if the initial action, after the occurrence of an accident, and the decision-making strategies, used by the investigators responsible for this activity, are characteristic of the naturalistic decision making theoretical approach. To attend the proposed objective a descriptive research was undertaken with a sample of professionals that work in this activity. The data collected through individual interviews were analyzed and the results demonstrated that the initial action environment, which includes restricted time, dynamic conditions, the presence of multiple actors, stress and insufficient information is characteristic of the naturalistic decision making. They also demonstrated that, when the investigators make their decisions, they use their experience and the mental simulation, intuition, improvisation, metaphors and analogues cases, as strategies, all of them related to the naturalistic approach of decision making, in order to satisfy the needs of the situation and reach the objectives of the initial action in the accident scenario.

Analysis of the decision-making process leading to appendectomy: a grounded theory study.

PubMed

Larsson, Gerry; Weibull, Henrik; Larsson, Bodil Wilde

2004-11-01

The aim was to develop a theoretical understanding of the decision-making process leading to appendectomy. A qualitative interview study was performed in the grounded theory tradition using the constant comparative method to analyze data. The study setting was one county hospital and two local hospitals in Sweden, where 11 surgeons and 15 surgical nurses were interviewed. A model was developed which suggests that surgeons' decision making regarding appendectomy is formed by the interplay between their medical assessment of the patient's condition and a set of contextual characteristics. The latter consist of three interacting factors: (1) organizational conditions, (2) the professional actors' individual characteristics and interaction, and (3) the personal characteristics of the patient and his or her family or relatives. In case the outcome of medical assessment is ambiguous, the risk evaluation and final decision will be influenced by an interaction of the contextual characteristics. It was concluded that, compared to existing, rational models of decision making, the model presented identified potentially important contextual characteristics and an outline on when they come into play.

Bringing a humanistic approach to cancer clinical trials

PubMed Central

Arai, Roberto Jun; Longo, Elaine Santana; Sponton, Maria Helena; Del Pilar Estevez Diz, Maria

2017-01-01

In this article, we describe some practical aspects that promote the humanisation of clinical research. Actions are not limited to improving the communication skills of medical staff but also include maintenance of care continuity, accessible written information, and application of theoretic models such as shared decision-making and management of stress in decision-making under uncertainty. We believe that a comprehensive strategy will increase patients’ motivation to participate in and adhere to clinical research. PMID:28596804

A Proposed Theoretical Model Using the Work of Thomas Kuhn, David Ausubel, and Mauritz Johnson as a Basis for Curriculum and Instruction Decisions in Science Education.

ERIC Educational Resources Information Center

Bowen, Barbara Lynn

This study presents a holistic framework which can be used as a basis for decision-making at various points in the curriculum-instruction development process as described by Johnson in a work published in 1967. The proposed framework has conceptual bases in the work of Thomas S. Kuhn and David P. Ausubel and utilizes the work of several perceptual…

Psychophysical Laws and the Superorganism.

PubMed

Reina, Andreagiovanni; Bose, Thomas; Trianni, Vito; Marshall, James A R

2018-03-12

Through theoretical analysis, we show how a superorganism may react to stimulus variations according to psychophysical laws observed in humans and other animals. We investigate an empirically-motivated honeybee house-hunting model, which describes a value-sensitive decision process over potential nest-sites, at the level of the colony. In this study, we show how colony decision time increases with the number of available nests, in agreement with the Hick-Hyman law of psychophysics, and decreases with mean nest quality, in agreement with Piéron's law. We also show that colony error rate depends on mean nest quality, and difference in quality, in agreement with Weber's law. Psychophysical laws, particularly Weber's law, have been found in diverse species, including unicellular organisms. Our theoretical results predict that superorganisms may also exhibit such behaviour, suggesting that these laws arise from fundamental mechanisms of information processing and decision-making. Finally, we propose a combined psychophysical law which unifies Hick-Hyman's law and Piéron's law, traditionally studied independently; this unified law makes predictions that can be empirically tested.

Seven Basic Steps to Solving Ethical Dilemmas in Special Education: A Decision-Making Framework

ERIC Educational Resources Information Center

Stockall, Nancy; Dennis, Lindsay R.

2015-01-01

This article presents a seven-step framework for decision making to solve ethical issues in special education. The authors developed the framework from the existing literature and theoretical frameworks of justice, critique, care, and professionalism. The authors briefly discuss each theoretical framework and then describe the decision-making…

Health versus money. Value judgments in the perspective of decision analysis.

PubMed

Thompson, M S

1983-01-01

An important, but largely uninvestigated, value trade-off balances marginal nonhealth consumption against marginal medical care. Benefit-cost analysts have traditionally, if not fully satisfactorily, dealt with this issue by valuing health gains by their effects on productivity. Cost-effectiveness analysts compare monetary and health effects and leave their relative valuations to decision makers. A decision-analytic model using the satisfaction or utility gained from nonhealth consumption and the level of health enables one to calculate willingness to pay--a theoretically superior way of assigning monetary values to effects for benefit-cost analysis-and to determine minimally acceptable cost-effectiveness ratios. Examples show how a decision-analytic model of utility can differentiate medical actions so essential that failure to take them would be considered negligent from actions so expensive as to be unjustifiable, and can help to determine optimal legal arrangements for compensation for medical malpractice.

A new framework for modeling decisions about changing information: The Piecewise Linear Ballistic Accumulator model

PubMed Central

Heathcote, Andrew

2016-01-01

In the real world, decision making processes must be able to integrate non-stationary information that changes systematically while the decision is in progress. Although theories of decision making have traditionally been applied to paradigms with stationary information, non-stationary stimuli are now of increasing theoretical interest. We use a random-dot motion paradigm along with cognitive modeling to investigate how the decision process is updated when a stimulus changes. Participants viewed a cloud of moving dots, where the motion switched directions midway through some trials, and were asked to determine the direction of motion. Behavioral results revealed a strong delay effect: after presentation of the initial motion direction there is a substantial time delay before the changed motion information is integrated into the decision process. To further investigate the underlying changes in the decision process, we developed a Piecewise Linear Ballistic Accumulator model (PLBA). The PLBA is efficient to simulate, enabling it to be fit to participant choice and response-time distribution data in a hierarchal modeling framework using a non-parametric approximate Bayesian algorithm. Consistent with behavioral results, PLBA fits confirmed the presence of a long delay between presentation and integration of new stimulus information, but did not support increased response caution in reaction to the change. We also found the decision process was not veridical, as symmetric stimulus change had an asymmetric effect on the rate of evidence accumulation. Thus, the perceptual decision process was slow to react to, and underestimated, new contrary motion information. PMID:26760448

Essays on the Role of Noncognitive Skills in Decision-Making

ERIC Educational Resources Information Center

McGee, Andrew Dunstan

2010-01-01

While "ability" has long featured prominently in economic models and empirical studies of labor markets, economists have only recently begun to consider how personality and attitudes--noncognitive factors--influence behavior both from a theoretical and empirical standpoint. This dissertation incorporates noncognitive factors into…

Four Mechanistic Models of Peer Influence on Adolescent Cannabis Use.

PubMed

Caouette, Justin D; Feldstein Ewing, Sarah W

2017-06-01

Most adolescents begin exploring cannabis in peer contexts, but the neural mechanisms that underlie peer influence on adolescent cannabis use are still unknown. This theoretical overview elucidates the intersecting roles of neural function and peer factors in cannabis use in adolescents. Novel paradigms using functional magnetic resonance imaging (fMRI) in adolescents have identified distinct neural mechanisms of risk decision-making and incentive processing in peer contexts, centered on reward-motivation and affect regulatory neural networks; these findings inform a theoretical model of peer-driven cannabis use decisions in adolescents. We propose four "mechanistic profiles" of social facilitation of cannabis use in adolescents: (1) peer influence as the primary driver of use; (2) cannabis exploration as the primary driver, which may be enhanced in peer contexts; (3) social anxiety; and (4) negative peer experiences. Identification of "neural targets" involved in motivating cannabis use may inform clinicians about which treatment strategies work best in adolescents with cannabis use problems, and via which social and neurocognitive processes.

Toward a Concept of Operations for Aviation Weather Information Implementation in the Evolving National Airspace System

NASA Technical Reports Server (NTRS)

McAdaragh, Raymon M.

2002-01-01

The capacity of the National Airspace System is being stressed due to the limits of current technologies. Because of this, the FAA and NASA are working to develop new technologies to increase the system's capacity which enhancing safety. Adverse weather has been determined to be a major factor in aircraft accidents and fatalities and the FAA and NASA have developed programs to improve aviation weather information technologies and communications for system users The Aviation Weather Information Element of the Weather Accident Prevention Project of NASA's Aviation Safety Program is currently working to develop these technologies in coordination with the FAA and industry. This paper sets forth a theoretical approach to implement these new technologies while addressing the National Airspace System (NAS) as an evolving system with Weather Information as one of its subSystems. With this approach in place, system users will be able to acquire the type of weather information that is needed based upon the type of decision-making situation and condition that is encountered. The theoretical approach addressed in this paper takes the form of a model for weather information implementation. This model addresses the use of weather information in three decision-making situations, based upon the system user's operational perspective. The model also addresses two decision-making conditions, which are based upon the need for collaboration due to the level of support offered by the weather information provided by each new product or technology. The model is proposed for use in weather information implementation in order to provide a systems approach to the NAS. Enhancements to the NAS collaborative decision-making capabilities are also suggested.

The time course of saccadic decision making: dynamic field theory.

PubMed

Wilimzig, Claudia; Schneider, Stefan; Schöner, Gregor

2006-10-01

Making a saccadic eye movement involves two decisions, the decision to initiate the saccade and the selection of the visual target of the saccade. Here we provide a theoretical account for the time-courses of these two processes, whose instabilities are the basis of decision making. We show how the cross-over from spatial averaging for fast saccades to selection for slow saccades arises from the balance between excitatory and inhibitory processes. Initiating a saccade involves overcoming fixation, as can be observed in the countermanding paradigm, which we model accounting both for the temporal evolution of the suppression probability and its dependence on fixation activity. The interaction between the two forms of decision making is demonstrated by predicting how the cross-over from averaging to selection depends on the fixation stimulus in gap-step-overlap paradigms. We discuss how the activation dynamics of our model may be mapped onto neuronal structures including the motor map and the fixation cells in superior colliculus.

[Decision-making process and health management councils: theoretical approaches].

PubMed

Wendhausen, Agueda; Cardoso, Sandra de Mello

2007-01-01

With the institutionalization of participation in health, through conferences and management councils at national, state, municipal and local levels, a process of democratization is initiated in the health area. However, in relation to the health councils in particular, there is still much to be done, including improving the quality of the decision-making process. This work aims to place the decision-making process in its theoretical context in terms of participatory democracy, elements which make up, factors which influence its development, and finally, to explore some possibilities of this theoretical basis to analyze the practices of the health councils in the area of health. It is hoped that it will make a theoretical contribution to the analyses carried out in this area, in order to provide a decision-making process that is more inclusive in terms of participation.

Bayesian averaging over Decision Tree models for trauma severity scoring.

PubMed

Schetinin, V; Jakaite, L; Krzanowski, W

2018-01-01

Health care practitioners analyse possible risks of misleading decisions and need to estimate and quantify uncertainty in predictions. We have examined the "gold" standard of screening a patient's conditions for predicting survival probability, based on logistic regression modelling, which is used in trauma care for clinical purposes and quality audit. This methodology is based on theoretical assumptions about data and uncertainties. Models induced within such an approach have exposed a number of problems, providing unexplained fluctuation of predicted survival and low accuracy of estimating uncertainty intervals within which predictions are made. Bayesian method, which in theory is capable of providing accurate predictions and uncertainty estimates, has been adopted in our study using Decision Tree models. Our approach has been tested on a large set of patients registered in the US National Trauma Data Bank and has outperformed the standard method in terms of prediction accuracy, thereby providing practitioners with accurate estimates of the predictive posterior densities of interest that are required for making risk-aware decisions. Copyright © 2017 Elsevier B.V. All rights reserved.

Modeling Opponents in Adversarial Risk Analysis.

PubMed

Rios Insua, David; Banks, David; Rios, Jesus

2016-04-01

Adversarial risk analysis has been introduced as a framework to deal with risks derived from intentional actions of adversaries. The analysis supports one of the decisionmakers, who must forecast the actions of the other agents. Typically, this forecast must take account of random consequences resulting from the set of selected actions. The solution requires one to model the behavior of the opponents, which entails strategic thinking. The supported agent may face different kinds of opponents, who may use different rationality paradigms, for example, the opponent may behave randomly, or seek a Nash equilibrium, or perform level-k thinking, or use mirroring, or employ prospect theory, among many other possibilities. We describe the appropriate analysis for these situations, and also show how to model the uncertainty about the rationality paradigm used by the opponent through a Bayesian model averaging approach, enabling a fully decision-theoretic solution. We also show how as we observe an opponent's decision behavior, this approach allows learning about the validity of each of the rationality models used to predict his decision by computing the models' (posterior) probabilities, which can be understood as a measure of their validity. We focus on simultaneous decision making by two agents. © 2015 Society for Risk Analysis.

Testing a theoretical model of clinical nurses' intent to stay.

PubMed

Cowden, Tracy L; Cummings, Greta G

2015-01-01

Published theoretical models of nurses' intent to stay (ITS) report inconsistent outcomes, and not all hypothesized models have been adequately tested. Research has focused on cognitive rather than emotional determinants of nurses' ITS. The aim of this study was to empirically verify a complex theoretical model of nurses' ITS that includes both affective and cognitive determinants and to explore the influence of relational leadership on staff nurses' ITS. The study was a correlational, mixed-method, nonexperimental design. A subsample of the Quality Work Environment Study survey data 2009 (n = 415 nurses) was used to test our theoretical model of clinical nurses' ITS as a structural equation model. The model explained 63% of variance in ITS. Organizational commitment, empowerment, and desire to stay were the model concepts with the strongest effects on nurses' ITS. Leadership practices indirectly influenced ITS. How nurses evaluate and respond to their work environment is both an emotional and rational process. Health care organizations need to be cognizant of the influence that nurses' feelings and views of their work setting have on their intention decisions and integrate that knowledge into the development of retention strategies. Leadership practices play an important role in staff nurses' perceptions of the workplace. Identifying the mechanisms by which leadership influences staff nurses' intentions to stay presents additional focus areas for developing retention strategies.

The Effects of Taxes on the Supply of Labor: with Special Reference to Income Maintenance Programs.

ERIC Educational Resources Information Center

Boskin, Michael Jay

The study builds a theoretical model of the interdependence of the labor supply decisions of family members and applies it to data from the 1967 survey of Economic Opportunity to estimate labor supply curves for population subgroups. The three relevant variables measured are labor supply, wages, and income. The model gives an estimate of the…

Risk-Based Decision Making in a Scientific Issue: A Study of Teachers Discussing a Dilemma through a Microworld

ERIC Educational Resources Information Center

Levinson, Ralph; Kent, Phillip; Pratt, David; Kapadia, Ramesh; Yogui, Cristina

2012-01-01

Risk has now become a feature of science curricula in many industrialized countries. While risk is conceptualized within a number of different theoretical frameworks, the predominant model used in examination specifications is a utility model in which risk calculations are deemed to be objective through technical expert assessment and where the…

Classifying clinical decision making: interpreting nursing intuition, heuristics and medical diagnosis.

PubMed

Buckingham, C D; Adams, A

2000-10-01

This is the second of two linked papers exploring decision making in nursing. The first paper, 'Classifying clinical decision making: a unifying approach' investigated difficulties with applying a range of decision-making theories to nursing practice. This is due to the diversity of terminology and theoretical concepts used, which militate against nurses being able to compare the outcomes of decisions analysed within different frameworks. It is therefore problematic for nurses to assess how good their decisions are, and where improvements can be made. However, despite the range of nomenclature, it was argued that there are underlying similarities between all theories of decision processes and that these should be exposed through integration within a single explanatory framework. A proposed solution was to use a general model of psychological classification to clarify and compare terms, concepts and processes identified across the different theories. The unifying framework of classification was described and this paper operationalizes it to demonstrate how different approaches to clinical decision making can be re-interpreted as classification behaviour. Particular attention is focused on classification in nursing, and on re-evaluating heuristic reasoning, which has been particularly prone to theoretical and terminological confusion. Demonstrating similarities in how different disciplines make decisions should promote improved multidisciplinary collaboration and a weakening of clinical elitism, thereby enhancing organizational effectiveness in health care and nurses' professional status. This is particularly important as nurses' roles continue to expand to embrace elements of managerial, medical and therapeutic work. Analysing nurses' decisions as classification behaviour will also enhance clinical effectiveness, and assist in making nurses' expertise more visible. In addition, the classification framework explodes the myth that intuition, traditionally associated with nurses' decision making, is less rational and scientific than other approaches.

Model of the best-of-N nest-site selection process in honeybees.

PubMed

Reina, Andreagiovanni; Marshall, James A R; Trianni, Vito; Bose, Thomas

2017-05-01

The ability of a honeybee swarm to select the best nest site plays a fundamental role in determining the future colony's fitness. To date, the nest-site selection process has mostly been modeled and theoretically analyzed for the case of binary decisions. However, when the number of alternative nests is larger than two, the decision-process dynamics qualitatively change. In this work, we extend previous analyses of a value-sensitive decision-making mechanism to a decision process among N nests. First, we present the decision-making dynamics in the symmetric case of N equal-quality nests. Then, we generalize our findings to a best-of-N decision scenario with one superior nest and N-1 inferior nests, previously studied empirically in bees and ants. Whereas previous binary models highlighted the crucial role of inhibitory stop-signaling, the key parameter in our new analysis is the relative time invested by swarm members in individual discovery and in signaling behaviors. Our new analysis reveals conflicting pressures on this ratio in symmetric and best-of-N decisions, which could be solved through a time-dependent signaling strategy. Additionally, our analysis suggests how ecological factors determining the density of suitable nest sites may have led to selective pressures for an optimal stable signaling ratio.

Model of the best-of-N nest-site selection process in honeybees

NASA Astrophysics Data System (ADS)

Reina, Andreagiovanni; Marshall, James A. R.; Trianni, Vito; Bose, Thomas

2017-05-01

The ability of a honeybee swarm to select the best nest site plays a fundamental role in determining the future colony's fitness. To date, the nest-site selection process has mostly been modeled and theoretically analyzed for the case of binary decisions. However, when the number of alternative nests is larger than two, the decision-process dynamics qualitatively change. In this work, we extend previous analyses of a value-sensitive decision-making mechanism to a decision process among N nests. First, we present the decision-making dynamics in the symmetric case of N equal-quality nests. Then, we generalize our findings to a best-of-N decision scenario with one superior nest and N -1 inferior nests, previously studied empirically in bees and ants. Whereas previous binary models highlighted the crucial role of inhibitory stop-signaling, the key parameter in our new analysis is the relative time invested by swarm members in individual discovery and in signaling behaviors. Our new analysis reveals conflicting pressures on this ratio in symmetric and best-of-N decisions, which could be solved through a time-dependent signaling strategy. Additionally, our analysis suggests how ecological factors determining the density of suitable nest sites may have led to selective pressures for an optimal stable signaling ratio.

Neural Underpinnings of Decision Strategy Selection: A Review and a Theoretical Model

PubMed Central

Wichary, Szymon; Smolen, Tomasz

2016-01-01

In multi-attribute choice, decision makers use decision strategies to arrive at the final choice. What are the neural mechanisms underlying decision strategy selection? The first goal of this paper is to provide a literature review on the neural underpinnings and cognitive models of decision strategy selection and thus set the stage for a neurocognitive model of this process. The second goal is to outline such a unifying, mechanistic model that can explain the impact of noncognitive factors (e.g., affect, stress) on strategy selection. To this end, we review the evidence for the factors influencing strategy selection, the neural basis of strategy use and the cognitive models of this process. We also present the Bottom-Up Model of Strategy Selection (BUMSS). The model assumes that the use of the rational Weighted Additive strategy and the boundedly rational heuristic Take The Best can be explained by one unifying, neurophysiologically plausible mechanism, based on the interaction of the frontoparietal network, orbitofrontal cortex, anterior cingulate cortex and the brainstem nucleus locus coeruleus. According to BUMSS, there are three processes that form the bottom-up mechanism of decision strategy selection and lead to the final choice: (1) cue weight computation, (2) gain modulation, and (3) weighted additive evaluation of alternatives. We discuss how these processes might be implemented in the brain, and how this knowledge allows us to formulate novel predictions linking strategy use and neural signals. PMID:27877103

Computerised decision support in physical activity interventions: A systematic literature review.

PubMed

Triantafyllidis, Andreas; Filos, Dimitris; Claes, Jomme; Buys, Roselien; Cornelissen, Véronique; Kouidi, Evangelia; Chouvarda, Ioanna; Maglaveras, Nicos

2018-03-01

The benefits of regular physical activity for health and quality of life are unarguable. New information, sensing and communication technologies have the potential to play a critical role in computerised decision support and coaching for physical activity. We provide a literature review of recent research in the development of physical activity interventions employing computerised decision support, their feasibility and effectiveness in healthy and diseased individuals, and map out challenges and future research directions. We searched the bibliographic databases of PubMed and Scopus to identify physical activity interventions with computerised decision support utilised in a real-life context. Studies were synthesized according to the target user group, the technological format (e.g., web-based or mobile-based) and decision-support features of the intervention, the theoretical model for decision support in health behaviour change, the study design, the primary outcome, the number of participants and their engagement with the intervention, as well as the total follow-up duration. From the 24 studies included in the review, the highest percentage (n = 7, 29%) targeted sedentary healthy individuals followed by patients with prediabetes/diabetes (n = 4, 17%) or overweight individuals (n = 4, 17%). Most randomized controlled trials reported significantly positive effects of the interventions, i.e., increase in physical activity (n = 7, 100%) for 7 studies assessing physical activity measures, weight loss (n = 3, 75%) for 4 studies assessing diet, and reductions in glycosylated hemoglobin (n = 2, 66%) for 3 studies assessing glycose concentration. Accelerometers/pedometers were used in almost half of the studies (n = 11, 46%). Most adopted decision support features included personalised goal-setting (n = 16, 67%) and motivational feedback sent to the users (n = 15, 63%). Fewer adopted features were integration with electronic health records (n = 3, 13%) and alerts sent to caregivers (n = 4, 17%). Theoretical models of decision support in health behaviour to drive the development of the intervention were not reported in most studies (n = 14, 58%). Interventions employing computerised decision support have the potential to promote physical activity and result in health benefits for both diseased and healthy individuals, and help healthcare providers to monitor patients more closely. Objectively measured activity through sensing devices, integration with clinical systems used by healthcare providers and theoretical frameworks for health behaviour change need to be employed in a larger scale in future studies in order to realise the development of evidence-based computerised systems for physical activity monitoring and coaching. Copyright © 2017 Elsevier B.V. All rights reserved.

Communication nonaccommodation in family conversations about end-of-life health decisions.

PubMed

Scott, Allison M; Caughlin, John P

2015-01-01

Furthering our understanding of how communication can improve end-of-life decision making requires a shift in focus from whether people talk to how people talk about end-of-life health decisions. This study used communication accommodation theory to examine the extent to which communication nonaccommodation distinguished more from less successful end-of-life conversations among family members. We analyzed elicited conversations about end-of-life health decisions from 121 older parent/adult child dyads using outside ratings of communication over- and underaccommodation and self-reported conversational outcomes. Results of multilevel linear modeling revealed that outside ratings of underaccommodation predicted self-reported and partner-reported uncertainty, and ratings of overaccommodation predicted self-reported decision-making efficacy and change in concordance accuracy. We discuss the methodological, theoretical, and practical implications of these findings.

Visual Perceptual Learning and Models.

PubMed

Dosher, Barbara; Lu, Zhong-Lin

2017-09-15

Visual perceptual learning through practice or training can significantly improve performance on visual tasks. Originally seen as a manifestation of plasticity in the primary visual cortex, perceptual learning is more readily understood as improvements in the function of brain networks that integrate processes, including sensory representations, decision, attention, and reward, and balance plasticity with system stability. This review considers the primary phenomena of perceptual learning, theories of perceptual learning, and perceptual learning's effect on signal and noise in visual processing and decision. Models, especially computational models, play a key role in behavioral and physiological investigations of the mechanisms of perceptual learning and for understanding, predicting, and optimizing human perceptual processes, learning, and performance. Performance improvements resulting from reweighting or readout of sensory inputs to decision provide a strong theoretical framework for interpreting perceptual learning and transfer that may prove useful in optimizing learning in real-world applications.

The Influence of Information Acquisition on the Complex Dynamics of Market Competition

NASA Astrophysics Data System (ADS)

Guo, Zhanbing; Ma, Junhai

In this paper, we build a dynamical game model with three bounded rational players (firms) to study the influence of information on the complex dynamics of market competition, where useful information is about rival’s real decision. In this dynamical game model, one information-sharing team is composed of two firms, they acquire and share the information about their common competitor, however, they make their own decisions separately, where the amount of information acquired by this information-sharing team will determine the estimation accuracy about the rival’s real decision. Based on this dynamical game model and some creative 3D diagrams, the influence of the amount of information on the complex dynamics of market competition such as local dynamics, global dynamics and profits is studied. These results have significant theoretical and practical values to realize the influence of information.

The impact of stakeholder involvement in hospital policy decision-making: a study of the hospital's business processes.

PubMed

Malfait, Simon; Van Hecke, Ann; Hellings, Johan; De Bodt, Griet; Eeckloo, Kristof

2017-02-01

In many health care systems, strategies are currently deployed to engage patients and other stakeholders in decisions affecting hospital services. In this paper, a model for stakeholder involvement is presented and evaluated in three Flemish hospitals. In the model, a stakeholder committee advises the hospital's board of directors on themes of strategic importance. To study the internal hospital's decision processes in order to identify the impact of a stakeholder involvement committee on strategic themes in the hospital decision processes. A retrospective analysis of the decision processes was conducted in three hospitals that implemented a stakeholder committee. The analysis consisted of process and outcome evaluation. Fifteen themes were discussed in the stakeholder committees, whereof 11 resulted in a considerable change. None of these were on a strategic level. The theoretical model was not applied as initially developed, but was altered by each hospital. Consequentially, the decision processes differed between the hospitals. Despite alternation of the model, the stakeholder committee showed a meaningful impact in all hospitals on the operational level. As a result of the differences in decision processes, three factors could be identified as facilitators for success: (1) a close interaction with the board of executives, (2) the inclusion of themes with a more practical and patient-oriented nature, and (3) the elaboration of decisions on lower echelons of the organization. To effectively influence the organization's public accountability, hospitals should involve stakeholders in the decision-making process of the organization. The model of a stakeholder committee was not applied as initially developed and did not affect the strategic decision-making processes in the involved hospitals. Results show only impact at the operational level in the participating hospitals. More research is needed connecting stakeholder involvement with hospital governance.

Emergent collective decision-making: Control, model and behavior

NASA Astrophysics Data System (ADS)

Shen, Tian

In this dissertation we study emergent collective decision-making in social groups with time-varying interactions and heterogeneously informed individuals. First we analyze a nonlinear dynamical systems model motivated by animal collective motion with heterogeneously informed subpopulations, to examine the role of uninformed individuals. We find through formal analysis that adding uninformed individuals in a group increases the likelihood of a collective decision. Secondly, we propose a model for human shared decision-making with continuous-time feedback and where individuals have little information about the true preferences of other group members. We study model equilibria using bifurcation analysis to understand how the model predicts decisions based on the critical threshold parameters that represent an individual's tradeoff between social and environmental influences. Thirdly, we analyze continuous-time data of pairs of human subjects performing an experimental shared tracking task using our second proposed model in order to understand transient behavior and the decision-making process. We fit the model to data and show that it reproduces a wide range of human behaviors surprisingly well, suggesting that the model may have captured the mechanisms of observed behaviors. Finally, we study human behavior from a game-theoretic perspective by modeling the aforementioned tracking task as a repeated game with incomplete information. We show that the majority of the players are able to converge to playing Nash equilibrium strategies. We then suggest with simulations that the mean field evolution of strategies in the population resemble replicator dynamics, indicating that the individual strategies may be myopic. Decisions form the basis of control and problems involving deciding collectively between alternatives are ubiquitous in nature and in engineering. Understanding how multi-agent systems make decisions among alternatives also provides insight for designing decentralized control laws for engineering applications from mobile sensor networks for environmental monitoring to collective construction robots. With this dissertation we hope to provide additional methodology and mathematical models for understanding the behavior and control of collective decision-making in multi-agent systems.

Swarm intelligence: when uncertainty meets conflict.

PubMed

Conradt, Larissa; List, Christian; Roper, Timothy J

2013-11-01

Good decision making is important for the survival and fitness of stakeholders, but decisions usually involve uncertainty and conflict. We know surprisingly little about profitable decision-making strategies in conflict situations. On the one hand, sharing decisions with others can pool information and decrease uncertainty (swarm intelligence). On the other hand, sharing decisions can hand influence to individuals whose goals conflict. Thus, when should an animal share decisions with others? Using a theoretical model, we show that, contrary to intuition, decision sharing by animals with conflicting goals often increases individual gains as well as decision accuracy. Thus, conflict-far from hampering effective decision making-can improve decision outcomes for all stakeholders, as long as they share large-scale goals. In contrast, decisions shared by animals without conflict were often surprisingly poor. The underlying mechanism is that animals with conflicting goals are less correlated in individual choice errors. These results provide a strong argument in the interest of all stakeholders for not excluding other (e.g., minority) factions from collective decisions. The observed benefits of including diverse factions among the decision makers could also be relevant to human collective decision making.

Decentralised water systems: emotional influences on resource decision making.

PubMed

Mankad, Aditi

2012-09-01

The study of emotion has gathered momentum in the field of environmental science, specifically in the context of community resource decision-making. Of particular interest in this review is the potential influence of emotion, risk and threat perception on individuals' decisions to acceptance and adopt decentralised water systems, such as rainwater tanks and greywater systems. The role of message framing is also considered in detail, as well as the influences that different types of framing can have on decision making. These factors are considered as possible predictors for analysing community acceptance of decentralised water in urban environments. Concepts believed to be influenced by emotion, such as trust and framing, are also discussed as potentially meaningful contributors to an overall model of community acceptance of decentralised water. Recommendations are made for how emotion-based concepts, such as risk and threat, can be targeted to facilitate widespread adoption of decentralised systems and how researchers can explore different types of emotions that influence decision making in distinct ways. This review is an important theoretical step in advancing the psycho-social understanding of acceptance and adoption of on-site water sources. Avenues for future research are recommended, including the need for greater theoretical development to encourage future social science research on decentralised systems. Crown Copyright © 2012. Published by Elsevier Ltd. All rights reserved.

Association of information satisfaction, psychological distress and monitoring coping style with post-decision regret following breast reconstruction.

PubMed

Sheehan, Joanne; Sherman, Kerry A; Lam, Thomas; Boyages, John

2007-04-01

Little is known of the psychosocial factors associated with decision regret in the context of breast reconstruction following mastectomy for breast cancer treatment. Moreover, there is a paucity of theoretically-based research in the area of post-decision regret. Adopting the theoretical framework of the Monitoring Process Model (Cancer 1995;76(1):167-177), the current study assessed the role of information satisfaction, current psychological distress and the moderating effect of monitoring coping style to the experience of regret over the decision to undergo reconstructive surgery. Women (N=123) diagnosed with breast cancer who had undergone immediate or delayed breast reconstruction following mastectomy participated in the study. The majority of participants (52.8%, n=65) experienced no decision regret, 27.6% experienced mild regret and 19.5% moderate to strong regret. Bivariate analyses indicated that decision regret was associated with low satisfaction with preparatory information, depression, anxiety and stress. Multinominal logistic regression analysis showed, controlling for mood state and time since last reconstructive procedure, that lower satisfaction with information and increased depression were associated with increased likelihood of experiencing regret. Monitoring coping style moderated the association between anxiety and regret (beta=-0.10, OR=0.91, p=0.01), whereby low monitors who were highly anxious had a greater likelihood of experiencing regret than highly anxious high monitors. Copyright (c) 2006 John Wiley & Sons, Ltd.

A Theoretical Foundation for the Study of Inferential Error in Decision-Making Groups.

ERIC Educational Resources Information Center

Gouran, Dennis S.

To provide a theoretical base for investigating the influence of inferential error on group decision making, current literature on both inferential error and decision making is reviewed and applied to the Watergate incident. Although groups tend to make fewer inferential errors because members' inferences are generally not biased in the same…

Convergence to consensus in heterogeneous groups and the emergence of informal leadership.

PubMed

Gavrilets, Sergey; Auerbach, Jeremy; van Vugt, Mark

2016-07-14

When group cohesion is essential, groups must have efficient strategies in place for consensus decision-making. Recent theoretical work suggests that shared decision-making is often the most efficient way for dealing with both information uncertainty and individual variation in preferences. However, some animal and most human groups make collective decisions through particular individuals, leaders, that have a disproportionate influence on group decision-making. To address this discrepancy between theory and data, we study a simple, but general, model that explicitly focuses on the dynamics of consensus building in groups composed by individuals who are heterogeneous in preferences, certain personality traits (agreeability and persuasiveness), reputation, and social networks. We show that within-group heterogeneity can significantly delay democratic consensus building as well as give rise to the emergence of informal leaders, i.e. individuals with a disproportionately large impact on group decisions. Our results thus imply strong benefits of leadership particularly when groups experience time pressure and significant conflict of interest between members (due to various between-individual differences). Overall, our models shed light on why leadership and decision-making hierarchies are widespread, especially in human groups.

A Design Pattern for Decentralised Decision Making

PubMed Central

Valentini, Gabriele; Fernández-Oto, Cristian; Dorigo, Marco

2015-01-01

The engineering of large-scale decentralised systems requires sound methodologies to guarantee the attainment of the desired macroscopic system-level behaviour given the microscopic individual-level implementation. While a general-purpose methodology is currently out of reach, specific solutions can be given to broad classes of problems by means of well-conceived design patterns. We propose a design pattern for collective decision making grounded on experimental/theoretical studies of the nest-site selection behaviour observed in honeybee swarms (Apis mellifera). The way in which honeybee swarms arrive at consensus is fairly well-understood at the macroscopic level. We provide formal guidelines for the microscopic implementation of collective decisions to quantitatively match the macroscopic predictions. We discuss implementation strategies based on both homogeneous and heterogeneous multiagent systems, and we provide means to deal with spatial and topological factors that have a bearing on the micro-macro link. Finally, we exploit the design pattern in two case studies that showcase the viability of the approach. Besides engineering, such a design pattern can prove useful for a deeper understanding of decision making in natural systems thanks to the inclusion of individual heterogeneities and spatial factors, which are often disregarded in theoretical modelling. PMID:26496359

Collaborative deliberation: a model for patient care.

PubMed

Elwyn, Glyn; Lloyd, Amy; May, Carl; van der Weijden, Trudy; Stiggelbout, Anne; Edwards, Adrian; Frosch, Dominick L; Rapley, Tim; Barr, Paul; Walsh, Thom; Grande, Stuart W; Montori, Victor; Epstein, Ronald

2014-11-01

Existing theoretical work in decision making and behavior change has focused on how individuals arrive at decisions or form intentions. Less attention has been given to theorizing the requirements that might be necessary for individuals to work collaboratively to address difficult decisions, consider new alternatives, or change behaviors. The goal of this work was to develop, as a forerunner to a middle range theory, a conceptual model that considers the process of supporting patients to consider alternative health care options, in collaboration with clinicians, and others. Theory building among researchers with experience and expertise in clinician-patient communication, using an iterative cycle of discussions. We developed a model composed of five inter-related propositions that serve as a foundation for clinical communication processes that honor the ethical principles of respecting individual agency, autonomy, and an empathic approach to practice. We named the model 'collaborative deliberation.' The propositions describe: (1) constructive interpersonal engagement, (2) recognition of alternative actions, (3) comparative learning, (4) preference construction and elicitation, and (5) preference integration. We believe the model underpins multiple suggested approaches to clinical practice that take the form of patient centered care, motivational interviewing, goal setting, action planning, and shared decision making. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Revisiting the evidence for collapsing boundaries and urgency signals in perceptual decision-making.

PubMed

Hawkins, Guy E; Forstmann, Birte U; Wagenmakers, Eric-Jan; Ratcliff, Roger; Brown, Scott D

2015-02-11

For nearly 50 years, the dominant account of decision-making holds that noisy information is accumulated until a fixed threshold is crossed. This account has been tested extensively against behavioral and neurophysiological data for decisions about consumer goods, perceptual stimuli, eyewitness testimony, memories, and dozens of other paradigms, with no systematic misfit between model and data. Recently, the standard model has been challenged by alternative accounts that assume that less evidence is required to trigger a decision as time passes. Such "collapsing boundaries" or "urgency signals" have gained popularity in some theoretical accounts of neurophysiology. Nevertheless, evidence in favor of these models is mixed, with support coming from only a narrow range of decision paradigms compared with a long history of support from dozens of paradigms for the standard theory. We conducted the first large-scale analysis of data from humans and nonhuman primates across three distinct paradigms using powerful model-selection methods to compare evidence for fixed versus collapsing bounds. Overall, we identified evidence in favor of the standard model with fixed decision boundaries. We further found that evidence for static or dynamic response boundaries may depend on specific paradigms or procedures, such as the extent of task practice. We conclude that the difficulty of selecting between collapsing and fixed bounds models has received insufficient attention in previous research, calling into question some previous results. Copyright © 2015 the authors 0270-6474/15/352476-09$15.00/0.

The Effects of Evidence Bounds on Decision-Making: Theoretical and Empirical Developments

PubMed Central

Zhang, Jiaxiang

2012-01-01

Converging findings from behavioral, neurophysiological, and neuroimaging studies suggest an integration-to-boundary mechanism governing decision formation and choice selection. This mechanism is supported by sequential sampling models of choice decisions, which can implement statistically optimal decision strategies for selecting between multiple alternative options on the basis of sensory evidence. This review focuses on recent developments in understanding the evidence boundary, an important component of decision-making raised by experimental findings and models. The article starts by reviewing the neurobiology of perceptual decisions and several influential sequential sampling models, in particular the drift-diffusion model, the Ornstein–Uhlenbeck model and the leaky-competing-accumulator model. In the second part, the article examines how the boundary may affect a model’s dynamics and performance and to what extent it may improve a model’s fits to experimental data. In the third part, the article examines recent findings that support the presence and site of boundaries in the brain. The article considers two questions: (1) whether the boundary is a spontaneous property of neural integrators, or is controlled by dedicated neural circuits; (2) if the boundary is variable, what could be the driving factors behind boundary changes? The review brings together studies using different experimental methods in seeking answers to these questions, highlights psychological and physiological factors that may be associated with the boundary and its changes, and further considers the evidence boundary as a generic mechanism to guide complex behavior. PMID:22870070

Acting Irrationally to Improve Performance in Stochastic Worlds

NASA Astrophysics Data System (ADS)

Belavkin, Roman V.

Despite many theories and algorithms for decision-making, after estimating the utility function the choice is usually made by maximising its expected value (the max EU principle). This traditional and 'rational' conclusion of the decision-making process is compared in this paper with several 'irrational' techniques that make choice in Monte-Carlo fashion. The comparison is made by evaluating the performance of simple decision-theoretic agents in stochastic environments. It is shown that not only the random choice strategies can achieve performance comparable to the max EU method, but under certain conditions the Monte-Carlo choice methods perform almost two times better than the max EU. The paper concludes by quoting evidence from recent cognitive modelling works as well as the famous decision-making paradoxes.

Shared decision making in senior medical students: results from a national survey.

PubMed

Zeballos-Palacios, Claudia; Quispe, Renato; Mongilardi, Nicole; Diaz-Arocutipa, Carlos; Mendez-Davalos, Carlos; Lizarraga, Natalia; Paz, Aldo; Montori, Victor M; Malaga, German

2015-05-01

To explore perceptions and experiences of Peruvian medical students about observed, preferred, and feasible decision-making approaches. We surveyed senior medical students from 19 teaching hospitals in 4 major cities in Peru. The self-administered questionnaire collected demographic information, current approach, exposure to role models for and training in shared decision making, and perceptions of the pertinence and feasibility of the different decision-making approaches in general as well as in challenging scenarios. A total of 327 senior medical students (51% female) were included. The mean age was 25 years. Among all respondents, 2% reported receiving both theoretical and practical training in shared decision making. While 46% of students identified their current decision-making approach as clinician-as-perfect-agent, 50% of students identified their teachers with the paternalistic approach. Remarkably, 53% of students thought shared decision making should be the preferred approach and 50% considered it feasible in Peru. Among the 10 challenging scenarios, shared decision making reached a plurality (40%) in only one scenario (terminally ill patients). Despite limited exposure and training, Peruvian medical students aspire to practice shared decision making but their current attitude reflects the less participatory approaches they see role modeled by their teachers. © The Author(s) 2015.

Factors Related to Organizational Turnover Intentions of Louisiana Cooperative Extension Service Agents.

ERIC Educational Resources Information Center

Carter, Carolyn G.; And Others

The relationship between employee turnover intentions and various predictors of turnover are examined in this study based on the theoretical framework of March and Simon's (1958) "decision to participate" model. Specifically, the predictors include desirability of movement (organizational commitment), ease of movement, job satisfaction,…

Student Observations: Introducing iPads into University Classrooms

ERIC Educational Resources Information Center

Wardley, Leslie J.; Mang, Colin F.

2016-01-01

This paper explores the growing trend of using mobile technology in university classrooms, exploring the use of tablets in particular, to identify learning benefits faced by students. Students, acting on their efficacy beliefs, make decisions regarding technology's influence in improving their education. We construct a theoretical model in which…

School System Simulation: An Effective Model for Educational Leaders.

ERIC Educational Resources Information Center

Nelson, Jorge O.

This study reviews the literature regarding the theoretical rationale for creating a computer-based school system simulation for educational leaders' use in problem solving and decision making. Like all social systems, educational systems are so complex that individuals are hard-pressed to consider all interrelated parts as a totality. A…

Analysis of decision fusion algorithms in handling uncertainties for integrated health monitoring systems

NASA Astrophysics Data System (ADS)

Zein-Sabatto, Saleh; Mikhail, Maged; Bodruzzaman, Mohammad; DeSimio, Martin; Derriso, Mark; Behbahani, Alireza

2012-06-01

It has been widely accepted that data fusion and information fusion methods can improve the accuracy and robustness of decision-making in structural health monitoring systems. It is arguably true nonetheless, that decision-level is equally beneficial when applied to integrated health monitoring systems. Several decisions at low-levels of abstraction may be produced by different decision-makers; however, decision-level fusion is required at the final stage of the process to provide accurate assessment about the health of the monitored system as a whole. An example of such integrated systems with complex decision-making scenarios is the integrated health monitoring of aircraft. Thorough understanding of the characteristics of the decision-fusion methodologies is a crucial step for successful implementation of such decision-fusion systems. In this paper, we have presented the major information fusion methodologies reported in the literature, i.e., probabilistic, evidential, and artificial intelligent based methods. The theoretical basis and characteristics of these methodologies are explained and their performances are analyzed. Second, candidate methods from the above fusion methodologies, i.e., Bayesian, Dempster-Shafer, and fuzzy logic algorithms are selected and their applications are extended to decisions fusion. Finally, fusion algorithms are developed based on the selected fusion methods and their performance are tested on decisions generated from synthetic data and from experimental data. Also in this paper, a modeling methodology, i.e. cloud model, for generating synthetic decisions is presented and used. Using the cloud model, both types of uncertainties; randomness and fuzziness, involved in real decision-making are modeled. Synthetic decisions are generated with an unbiased process and varying interaction complexities among decisions to provide for fair performance comparison of the selected decision-fusion algorithms. For verification purposes, implementation results of the developed fusion algorithms on structural health monitoring data collected from experimental tests are reported in this paper.

Theoretical Models of Participation in Adult Education: The Need for an Integrated Model

ERIC Educational Resources Information Center

Boeren, E.; Nicaise, I.; Baert, H.

2010-01-01

The European Union has set a goal that by 2010, 12.5% of the working age population should be taking part in lifelong learning. This participation rate has not yet been achieved in many countries. A partial explanation is the fact that the decision to participate depends on a variety of factors at three levels: the individual; the educational…

Entry and Exit.

DTIC Science & Technology

1987-03-01

1. Introduction R Analyses of industrial competition have attained a new vigor with the application of game -theoretic methods. The process of... competition is represented in models that reflect genuine struggles for entry, market power, and continuing survival. Dynamics and informational effects are...presents a few of the models developed recently to study competitive processes that affect a firm’s entry into a market , and the decision to exit. The

A structured analysis of uncertainty surrounding modeled impacts of groundwater-extraction rules

NASA Astrophysics Data System (ADS)

Guillaume, Joseph H. A.; Qureshi, M. Ejaz; Jakeman, Anthony J.

2012-08-01

Integrating economic and groundwater models for groundwater-management can help improve understanding of trade-offs involved between conflicting socioeconomic and biophysical objectives. However, there is significant uncertainty in most strategic decision-making situations, including in the models constructed to represent them. If not addressed, this uncertainty may be used to challenge the legitimacy of the models and decisions made using them. In this context, a preliminary uncertainty analysis was conducted of a dynamic coupled economic-groundwater model aimed at assessing groundwater extraction rules. The analysis demonstrates how a variety of uncertainties in such a model can be addressed. A number of methods are used including propagation of scenarios and bounds on parameters, multiple models, block bootstrap time-series sampling and robust linear regression for model calibration. These methods are described within the context of a theoretical uncertainty management framework, using a set of fundamental uncertainty management tasks and an uncertainty typology.

Using Covert Response Activation to Test Latent Assumptions of Formal Decision-Making Models in Humans.

PubMed

Servant, Mathieu; White, Corey; Montagnini, Anna; Burle, Borís

2015-07-15

Most decisions that we make build upon multiple streams of sensory evidence and control mechanisms are needed to filter out irrelevant information. Sequential sampling models of perceptual decision making have recently been enriched by attentional mechanisms that weight sensory evidence in a dynamic and goal-directed way. However, the framework retains the longstanding hypothesis that motor activity is engaged only once a decision threshold is reached. To probe latent assumptions of these models, neurophysiological indices are needed. Therefore, we collected behavioral and EMG data in the flanker task, a standard paradigm to investigate decisions about relevance. Although the models captured response time distributions and accuracy data, EMG analyses of response agonist muscles challenged the assumption of independence between decision and motor processes. Those analyses revealed covert incorrect EMG activity ("partial error") in a fraction of trials in which the correct response was finally given, providing intermediate states of evidence accumulation and response activation at the single-trial level. We extended the models by allowing motor activity to occur before a commitment to a choice and demonstrated that the proposed framework captured the rate, latency, and EMG surface of partial errors, along with the speed of the correction process. In return, EMG data provided strong constraints to discriminate between competing models that made similar behavioral predictions. Our study opens new theoretical and methodological avenues for understanding the links among decision making, cognitive control, and motor execution in humans. Sequential sampling models of perceptual decision making assume that sensory information is accumulated until a criterion quantity of evidence is obtained, from where the decision terminates in a choice and motor activity is engaged. The very existence of covert incorrect EMG activity ("partial error") during the evidence accumulation process challenges this longstanding assumption. In the present work, we use partial errors to better constrain sequential sampling models at the single-trial level. Copyright © 2015 the authors 0270-6474/15/3510371-15$15.00/0.

Separating Decision and Encoding Noise in Signal Detection Tasks

PubMed Central

Cabrera, Carlos Alexander; Lu, Zhong-Lin; Dosher, Barbara Anne

2015-01-01

In this paper we develop an extension to the Signal Detection Theory (SDT) framework to separately estimate internal noise arising from representational and decision processes. Our approach constrains SDT models with decision noise by combining a multi-pass external noise paradigm with confidence rating responses. In a simulation study we present evidence that representation and decision noise can be separately estimated over a range of representative underlying representational and decision noise level configurations. These results also hold across a number of decision rules and show resilience to rule miss-specification. The new theoretical framework is applied to a visual detection confidence-rating task with three and five response categories. This study compliments and extends the recent efforts of researchers (Benjamin, Diaz, & Wee, 2009; Mueller & Weidemann, 2008; Rosner & Kochanski, 2009, Kellen, Klauer, & Singmann, 2012) to separate and quantify underlying sources of response variability in signal detection tasks. PMID:26120907

Towards an internal model in pilot training.

PubMed

Braune, R J; Trollip, S R

1982-10-01

Optimal decision making requires an information seeking behavior which reflects the comprehension of the overall system dynamics. Research in the area of human monitors in man-machine systems supports the notion of an internal model with built-in expectancies. It is doubtful that the current approach to pilot training helps develop this internal model in the most efficient way. But this is crucial since the role of the pilot is changing to a systems' manager and decision maker. An extension of the behavioral framework of pilot training might help to prepare the pilot better for the increasingly complex flight environment. This extension is based on the theoretical model of schema theory, which evolved out of psychological research. The technological advances in aircraft simulators and in-flight performance measurement devices allow investigation of the still-unresolved issues.

Discriminating evidence accumulation from urgency signals in speeded decision making.

PubMed

Hawkins, Guy E; Wagenmakers, Eric-Jan; Ratcliff, Roger; Brown, Scott D

2015-07-01

The dominant theoretical paradigm in explaining decision making throughout both neuroscience and cognitive science is known as “evidence accumulation”--The core idea being that decisions are reached by a gradual accumulation of noisy information. Although this notion has been supported by hundreds of experiments over decades of study, a recent theory proposes that the fundamental assumption of evidence accumulation requires revision. The "urgency gating" model assumes decisions are made without accumulating evidence, using only moment-by-moment information. Under this assumption, the successful history of evidence accumulation models is explained by asserting that the two models are mathematically identical in standard experimental procedures. We demonstrate that this proof of equivalence is incorrect, and that the models are not identical, even when both models are augmented with realistic extra assumptions. We also demonstrate that the two models can be perfectly distinguished in realistic simulated experimental designs, and in two real data sets; the evidence accumulation model provided the best account for one data set, and the urgency gating model for the other. A positive outcome is that the opposing modeling approaches can be fruitfully investigated without wholesale change to the standard experimental paradigms. We conclude that future research must establish whether the urgency gating model enjoys the same empirical support in the standard experimental paradigms that evidence accumulation models have gathered over decades of study. Copyright © 2015 the American Physiological Society.

Clinical decision-making to facilitate appropriate patient management in chiropractic practice: 'the 3-questions model'.

PubMed

Amorin-Woods, Lyndon G; Parkin-Smith, Gregory F

2012-03-14

A definitive diagnosis in chiropractic clinical practice is frequently elusive, yet decisions around management are still necessary. Often, a clinical impression is made after the exclusion of serious illness or injury, and care provided within the context of diagnostic uncertainty. Rather than focussing on labelling the condition, the clinician may choose to develop a defendable management plan since the response to treatment often clarifies the diagnosis. This paper explores the concept and elements of defensive problem-solving practice, with a view to developing a model of agile, pragmatic decision-making amenable to real-world application. A theoretical framework that reflects the elements of this approach will be offered in order to validate the potential of a so called '3-Questions Model'; Clinical decision-making is considered to be a key characteristic of any modern healthcare practitioner. It is, thus, prudent for chiropractors to re-visit the concept of defensible practice with a view to facilitate capable clinical decision-making and competent patient examination skills. In turn, the perception of competence and trustworthiness of chiropractors within the wider healthcare community helps integration of chiropractic services into broader healthcare settings.

Love as a regulative ideal in surrogate decision making.

PubMed

Stonestreet, Erica Lucast

2014-10-01

This discussion aims to give a normative theoretical basis for a "best judgment" model of surrogate decision making rooted in a regulative ideal of love. Currently, there are two basic models of surrogate decision making for incompetent patients: the "substituted judgment" model and the "best interests" model. The former draws on the value of autonomy and responds with respect; the latter draws on the value of welfare and responds with beneficence. It can be difficult to determine which of these two models is more appropriate for a given patient, and both approaches may seem inadequate for a surrogate who loves the patient. The proposed "best judgment" model effectively draws on the values incorporated in each of the traditional standards, but does so because these values are important to someone who loves a patient, since love responds to the patient as the specific person she is. © The Author 2014. Published by Oxford University Press, on behalf of the Journal of Medicine and Philosophy Inc. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Philosophical Foundations for Curriculum Decision: A Reflective Analysis

ERIC Educational Resources Information Center

Belbase, Shashidhar

2011-01-01

This paper discusses the author's curriculum experiences under different philosophical, epistemological and theoretical backdrops. The analysis of different perspectives bridges epistemological and philosophical/theoretical lenses to my understanding of curriculum and different curricular decisions. This praxeological experience as a student and…

Five reasons not to use numerical models in water resource management (Arne Richter Award Lecture for OYS)

NASA Astrophysics Data System (ADS)

Pianosi, Francesca

2015-04-01

Sustainable water resource management in a quickly changing world poses new challenges to hydrology and decision sciences. Systems analysis can contribute to promote sustainable practices by providing the theoretical background and the operational tools for an objective and transparent appraisal of policy options for water resource systems (WRS) management. Traditionally, limited availability of data and computing resources imposed to use oversimplified WRS models, with little consideration of modeling uncertainties and of the non-stationarity and feedbacks between WRS drivers, and a priori aggregation of costs and benefits. Nowadays we increasingly recognize the inadequacy of these simplifications, and consider them among the reasons for the limited use of model-generated information in actual decision-making processes. On the other hand, fast-growing availability of data and computing resources are opening up unprecedented possibilities in the way we build and apply numerical models. In this talk I will discuss my experiences and ideas on how we can exploit this potential to improve model-informed decision-making while facing the challenges of uncertainty, non-stationarity, feedbacks and conflicting objectives. In particular, through practical examples of WRS design and operation problems, my talk will aim at stimulating discussion about the impact of uncertainty on decisions: can inaccurate and imprecise predictions still carry valuable information for decision-making? Does uncertainty in predictions necessarily limit our ability to make 'good' decisions? Or can uncertainty even be of help for decision-making, for instance by reducing the projected conflict between competing water use? Finally, I will also discuss how the traditionally separate disciplines of numerical modelling, optimization, and uncertainty and sensitivity analysis have in my experience been just different facets of the same 'systems approach'.

Network approaches for expert decisions in sports.

PubMed

Glöckner, Andreas; Heinen, Thomas; Johnson, Joseph G; Raab, Markus

2012-04-01

This paper focuses on a model comparison to explain choices based on gaze behavior via simulation procedures. We tested two classes of models, a parallel constraint satisfaction (PCS) artificial neuronal network model and an accumulator model in a handball decision-making task from a lab experiment. Both models predict action in an option-generation task in which options can be chosen from the perspective of a playmaker in handball (i.e., passing to another player or shooting at the goal). Model simulations are based on a dataset of generated options together with gaze behavior measurements from 74 expert handball players for 22 pieces of video footage. We implemented both classes of models as deterministic vs. probabilistic models including and excluding fitted parameters. Results indicated that both classes of models can fit and predict participants' initially generated options based on gaze behavior data, and that overall, the classes of models performed about equally well. Early fixations were thereby particularly predictive for choices. We conclude that the analyses of complex environments via network approaches can be successfully applied to the field of experts' decision making in sports and provide perspectives for further theoretical developments. Copyright © 2011 Elsevier B.V. All rights reserved.

Model-theoretic framework for sensor data fusion

NASA Astrophysics Data System (ADS)

Zavoleas, Kyriakos P.; Kokar, Mieczyslaw M.

1993-09-01

The main goal of our research in sensory data fusion (SDF) is the development of a systematic approach (a methodology) to designing systems for interpreting sensory information and for reasoning about the situation based upon this information and upon available data bases and knowledge bases. To achieve such a goal, two kinds of subgoals have been set: (1) develop a theoretical framework in which rational design/implementation decisions can be made, and (2) design a prototype SDF system along the lines of the framework. Our initial design of the framework has been described in our previous papers. In this paper we concentrate on the model-theoretic aspects of this framework. We postulate that data are embedded in data models, and information processing mechanisms are embedded in model operators. The paper is devoted to analyzing the classes of model operators and their significance in SDF. We investigate transformation abstraction and fusion operators. A prototype SDF system, fusing data from range and intensity sensors, is presented, exemplifying the structures introduced. Our framework is justified by the fact that it provides modularity, traceability of information flow, and a basis for a specification language for SDF.

Portfolio theory and the alternative decision rule of cost-effectiveness analysis: theoretical and practical considerations.

PubMed

Sendi, Pedram; Al, Maiwenn J; Gafni, Amiram; Birch, Stephen

2004-05-01

Bridges and Terris (Soc. Sci. Med. (2004)) critique our paper on the alternative decision rule of economic evaluation in the presence of uncertainty and constrained resources within the context of a portfolio of health care programs (Sendi et al. Soc. Sci. Med. 57 (2003) 2207). They argue that by not adopting a formal portfolio theory approach we overlook the optimal solution. We show that these arguments stem from a fundamental misunderstanding of the alternative decision rule of economic evaluation. In particular, the portfolio theory approach advocated by Bridges and Terris is based on the same theoretical assumptions that the alternative decision rule set out to relax. Moreover, Bridges and Terris acknowledge that the proposed portfolio theory approach may not identify the optimal solution to resource allocation problems. Hence, it provides neither theoretical nor practical improvements to the proposed alternative decision rule.

The Role of Government Policies in the Adoption of Conservation Tillage in China: A Theoretical Model

NASA Astrophysics Data System (ADS)

Ding, Ya

2018-01-01

In recent years, many areas of China have been facing increasing problems of soil erosion and land degradation. Conservation tillage, with both economic and ecological benefits, provides a good avenue for Chinese farmers to conserve land as well as secure food production. However, the adoption rate of conservation tillage systems is very low in China. In this paper, the author constructs a theoretical model to explain a farmer’s adoption decision of conservation tillage. The goal is to investigate potential reasons behind the low adoption rate and explores alternative policy tools that can help improve a farmer’s incentive to adopt conservation tillage in China.

Doing what's right: A grounded theory of ethical decision-making in occupational therapy.

PubMed

VanderKaay, Sandra; Letts, Lori; Jung, Bonny; Moll, Sandra E

2018-04-20

Ethical decision-making is an important aspect of reasoning in occupational therapy practice. However, the process of ethical decision-making within the broader context of reasoning is yet to be clearly explicated. The purpose of this study was to advance a theoretical understanding of the process by which occupational therapists make ethical decisions in day-to-day practice. A constructivist grounded theory approach was adopted, incorporating in-depth semi-structured interviews with 18 occupational therapists from a range of practice settings and years of experience. Initially, participants nominated as key informants who were able to reflect on their decision-making processes were recruited. Theoretical sampling informed subsequent stages of data collection. Participants were asked to describe their process of ethical decision-making using scenarios from clinical practice. Interview transcripts were analyzed using a systematic process of initial then focused coding, and theoretical categorization to construct a theory regarding the process of ethical decision-making. An ethical decision-making prism was developed to capture three main processes: Considering the Fundamental Checklist, Consulting Others, and Doing What's Right. Ethical decision-making appeared to be an inductive and dialectical process with the occupational therapist at its core. Study findings advance our understanding of ethical decision-making in day-to-day clinical practice.

A dataset of human decision-making in teamwork management.

PubMed

Yu, Han; Shen, Zhiqi; Miao, Chunyan; Leung, Cyril; Chen, Yiqiang; Fauvel, Simon; Lin, Jun; Cui, Lizhen; Pan, Zhengxiang; Yang, Qiang

2017-01-17

Today, most endeavours require teamwork by people with diverse skills and characteristics. In managing teamwork, decisions are often made under uncertainty and resource constraints. The strategies and the effectiveness of the strategies different people adopt to manage teamwork under different situations have not yet been fully explored, partially due to a lack of detailed large-scale data. In this paper, we describe a multi-faceted large-scale dataset to bridge this gap. It is derived from a game simulating complex project management processes. It presents the participants with different conditions in terms of team members' capabilities and task characteristics for them to exhibit their decision-making strategies. The dataset contains detailed data reflecting the decision situations, decision strategies, decision outcomes, and the emotional responses of 1,144 participants from diverse backgrounds. To our knowledge, this is the first dataset simultaneously covering these four facets of decision-making. With repeated measurements, the dataset may help establish baseline variability of decision-making in teamwork management, leading to more realistic decision theoretic models and more effective decision support approaches.

A dataset of human decision-making in teamwork management

PubMed Central

Yu, Han; Shen, Zhiqi; Miao, Chunyan; Leung, Cyril; Chen, Yiqiang; Fauvel, Simon; Lin, Jun; Cui, Lizhen; Pan, Zhengxiang; Yang, Qiang

2017-01-01

Today, most endeavours require teamwork by people with diverse skills and characteristics. In managing teamwork, decisions are often made under uncertainty and resource constraints. The strategies and the effectiveness of the strategies different people adopt to manage teamwork under different situations have not yet been fully explored, partially due to a lack of detailed large-scale data. In this paper, we describe a multi-faceted large-scale dataset to bridge this gap. It is derived from a game simulating complex project management processes. It presents the participants with different conditions in terms of team members’ capabilities and task characteristics for them to exhibit their decision-making strategies. The dataset contains detailed data reflecting the decision situations, decision strategies, decision outcomes, and the emotional responses of 1,144 participants from diverse backgrounds. To our knowledge, this is the first dataset simultaneously covering these four facets of decision-making. With repeated measurements, the dataset may help establish baseline variability of decision-making in teamwork management, leading to more realistic decision theoretic models and more effective decision support approaches. PMID:28094787

A dataset of human decision-making in teamwork management

NASA Astrophysics Data System (ADS)

Yu, Han; Shen, Zhiqi; Miao, Chunyan; Leung, Cyril; Chen, Yiqiang; Fauvel, Simon; Lin, Jun; Cui, Lizhen; Pan, Zhengxiang; Yang, Qiang

2017-01-01

Today, most endeavours require teamwork by people with diverse skills and characteristics. In managing teamwork, decisions are often made under uncertainty and resource constraints. The strategies and the effectiveness of the strategies different people adopt to manage teamwork under different situations have not yet been fully explored, partially due to a lack of detailed large-scale data. In this paper, we describe a multi-faceted large-scale dataset to bridge this gap. It is derived from a game simulating complex project management processes. It presents the participants with different conditions in terms of team members' capabilities and task characteristics for them to exhibit their decision-making strategies. The dataset contains detailed data reflecting the decision situations, decision strategies, decision outcomes, and the emotional responses of 1,144 participants from diverse backgrounds. To our knowledge, this is the first dataset simultaneously covering these four facets of decision-making. With repeated measurements, the dataset may help establish baseline variability of decision-making in teamwork management, leading to more realistic decision theoretic models and more effective decision support approaches.

Representation of People's Decisions in Health Information Systems. A Complementary Approach for Understanding Health Care Systems and Population Health.

PubMed

Gonzalez Bernaldo de Quiros, Fernan; Dawidowski, Adriana R; Figar, Silvana

2017-02-01

In this study, we aimed: 1) to conceptualize the theoretical challenges facing health information systems (HIS) to represent patients' decisions about health and medical treatments in everyday life; 2) to suggest approaches for modeling these processes. The conceptualization of the theoretical and methodological challenges was discussed in 2015 during a series of interdisciplinary meetings attended by health informatics staff, epidemiologists and health professionals working in quality management and primary and secondary prevention of chronic diseases of the Hospital Italiano de Buenos Aires, together with sociologists, anthropologists and e-health stakeholders. HIS are facing the need and challenge to represent social human processes based on constructivist and complexity theories, which are the current frameworks of human sciences for understanding human learning and socio-cultural changes. Computer systems based on these theories can model processes of social construction of concrete and subjective entities and the interrelationships between them. These theories could be implemented, among other ways, through the mapping of health assets, analysis of social impact through community trials and modeling of complexity with system simulation tools. This analysis suggested the need to complement the traditional linear causal explanations of disease onset (and treatments) that are the bases for models of analysis of HIS with constructivist and complexity frameworks. Both may enlighten the complex interrelationships among patients, health services and the health system. The aim of this strategy is to clarify people's decision making processes to improve the efficiency, quality and equity of the health services and the health system.

Testing the hierarchy of effects model: ParticipACTION's serial mass communication campaigns on physical activity in Canada.

PubMed

Craig, C L; Bauman, A; Reger-Nash, B

2010-03-01

The hierarchy of effects (HOE) model is often used in planning mass-reach communication campaigns to promote health, but has rarely been empirically tested. This paper examines Canada's 30 year ParticipACTION campaign to promote physical activity (PA). A cohort from the nationally representative 1981 Canada Fitness Survey was followed up in 1988 and 2002-2004. Modelling of these data tested whether the mechanisms of campaign effects followed the theoretical framework proposed in the HOE. Campaign awareness was measured in 1981. Outcome expectancy, attitudes, decision balance and future intention were asked in 1988. PA was assessed at all time points. Logistic regression was used to sequentially test mediating and moderating variables adjusting for age, sex and education. No selection bias was observed; however, relatively fewer respondents than non-respondents smoked or were underweight at baseline. Among those inactive at baseline, campaign awareness predicted outcome expectancy which in turn predicted positive attitude to PA. Positive attitudes predicted high decision balance, which predicted future intention. Future intention mediated the relationship between decision balance and sufficient activity. Among those sufficiently active at baseline, awareness was unrelated to outcome expectancy and inversely related to positive attitude. These results lend support to the HOE model, in that the effects of ParticipACTION's serial mass media campaigns were consistent with the sequential rollout of its messages, which in turn was associated with achieving an active lifestyle among those initially insufficiently active. This provides support to an often-used theoretical framework for designing health promotion media campaigns.

Kernel-Based Approximate Dynamic Programming Using Bellman Residual Elimination

DTIC Science & Technology

2010-02-01

framework is the ability to utilize stochastic system models, thereby allowing the system to make sound decisions even if there is randomness in the system ...approximate policy when a system model is unavailable. We present theoretical analysis of all BRE algorithms proving convergence to the optimal policy in...policies based on MDPs is that there may be parameters of the system model that are poorly known and/or vary with time as the system operates. System

What is adaptive about adaptive decision making? A parallel constraint satisfaction account.

PubMed

Glöckner, Andreas; Hilbig, Benjamin E; Jekel, Marc

2014-12-01

There is broad consensus that human cognition is adaptive. However, the vital question of how exactly this adaptivity is achieved has remained largely open. Herein, we contrast two frameworks which account for adaptive decision making, namely broad and general single-mechanism accounts vs. multi-strategy accounts. We propose and fully specify a single-mechanism model for decision making based on parallel constraint satisfaction processes (PCS-DM) and contrast it theoretically and empirically against a multi-strategy account. To achieve sufficiently sensitive tests, we rely on a multiple-measure methodology including choice, reaction time, and confidence data as well as eye-tracking. Results show that manipulating the environmental structure produces clear adaptive shifts in choice patterns - as both frameworks would predict. However, results on the process level (reaction time, confidence), in information acquisition (eye-tracking), and from cross-predicting choice consistently corroborate single-mechanisms accounts in general, and the proposed parallel constraint satisfaction model for decision making in particular. Copyright © 2014 Elsevier B.V. All rights reserved.

Distinction between Externally vs. Internally Guided Decision-Making: Operational Differences, Meta-Analytical Comparisons and Their Theoretical Implications

PubMed Central

Nakao, Takashi; Ohira, Hideki; Northoff, Georg

2012-01-01

Most experimental studies of decision-making have specifically examined situations in which a single less-predictable correct answer exists (externally guided decision-making under uncertainty). Along with such externally guided decision-making, there are instances of decision-making in which no correct answer based on external circumstances is available for the subject (internally guided decision-making). Such decisions are usually made in the context of moral decision-making as well as in preference judgment, where the answer depends on the subject’s own, i.e., internal, preferences rather than on external, i.e., circumstantial, criteria. The neuronal and psychological mechanisms that allow guidance of decisions based on more internally oriented criteria in the absence of external ones remain unclear. This study was undertaken to compare decision-making of these two kinds empirically and theoretically. First, we reviewed studies of decision-making to clarify experimental–operational differences between externally guided and internally guided decision-making. Second, using multi-level kernel density analysis, a whole-brain-based quantitative meta-analysis of neuroimaging studies was performed. Our meta-analysis revealed that the neural network used predominantly for internally guided decision-making differs from that for externally guided decision-making under uncertainty. This result suggests that studying only externally guided decision-making under uncertainty is insufficient to account for decision-making processes in the brain. Finally, based on the review and results of the meta-analysis, we discuss the differences and relations between decision-making of these two types in terms of their operational, neuronal, and theoretical characteristics. PMID:22403525

Information Presentation in Decision and Risk Analysis: Answered, Partly Answered, and Unanswered Questions.

PubMed

Keller, L Robin; Wang, Yitong

2017-06-01

For the last 30 years, researchers in risk analysis, decision analysis, and economics have consistently proven that decisionmakers employ different processes for evaluating and combining anticipated and actual losses, gains, delays, and surprises. Although rational models generally prescribe a consistent response, people's heuristic processes will sometimes lead them to be inconsistent in the way they respond to information presented in theoretically equivalent ways. We point out several promising future research directions by listing and detailing a series of answered, partly answered, and unanswered questions. © 2016 Society for Risk Analysis.

A Decision Model for Supporting Task Allocation Processes in Global Software Development

NASA Astrophysics Data System (ADS)

Lamersdorf, Ansgar; Münch, Jürgen; Rombach, Dieter

Today, software-intensive systems are increasingly being developed in a globally distributed way. However, besides its benefit, global development also bears a set of risks and problems. One critical factor for successful project management of distributed software development is the allocation of tasks to sites, as this is assumed to have a major influence on the benefits and risks. We introduce a model that aims at improving management processes in globally distributed projects by giving decision support for task allocation that systematically regards multiple criteria. The criteria and causal relationships were identified in a literature study and refined in a qualitative interview study. The model uses existing approaches from distributed systems and statistical modeling. The article gives an overview of the problem and related work, introduces the empirical and theoretical foundations of the model, and shows the use of the model in an example scenario.

Theoretical Approaches to Moral/Citizenship Education.

ERIC Educational Resources Information Center

Heslep, Robert D.

Four theoretical approaches to moral/citizenship education are described and compared. Positive and negative aspects of the cognitive-decision, developmental, prosocial, and values approaches are discussed and ways of relating the four approaches to each other are suggested. The first approach, cognitive-decision, is distinctive for its…

Inductive reasoning 2.0.

PubMed

Hayes, Brett K; Heit, Evan

2018-05-01

Inductive reasoning entails using existing knowledge to make predictions about novel cases. The first part of this review summarizes key inductive phenomena and critically evaluates theories of induction. We highlight recent theoretical advances, with a special emphasis on the structured statistical approach, the importance of sampling assumptions in Bayesian models, and connectionist modeling. A number of new research directions in this field are identified including comparisons of inductive and deductive reasoning, the identification of common core processes in induction and memory tasks and induction involving category uncertainty. The implications of induction research for areas as diverse as complex decision-making and fear generalization are discussed. This article is categorized under: Psychology > Reasoning and Decision Making Psychology > Learning. © 2017 Wiley Periodicals, Inc.

The Role of Evaluative Metadata in an Online Teacher Resource Exchange

ERIC Educational Resources Information Center

Abramovich, Samuel; Schunn, Christian D.; Correnti, Richard J.

2013-01-01

A large-scale online teacher resource exchange is studied to examine the ways in which metadata influence teachers' selection of resources. A hierarchical linear modeling approach was used to tease apart the simultaneous effects of resource features and author features. From a decision heuristics theoretical perspective, teachers appear to…

Modulation of Additive and Interactive Effects in Lexical Decision by Trial History

ERIC Educational Resources Information Center

Masson, Michael E. J.; Kliegl, Reinhold

2013-01-01

Additive and interactive effects of word frequency, stimulus quality, and semantic priming have been used to test theoretical claims about the cognitive architecture of word-reading processes. Additive effects among these factors have been taken as evidence for discrete-stage models of word reading. We present evidence from linear mixed-model…

Cooperative Game Theoretic Models for Decision-Making in Contexts of Library Cooperation.

ERIC Educational Resources Information Center

Hayes, Robert M.

2003-01-01

Presents a brief summary of Cooperative Economic Game Theory, followed by a summary of specific measures identified by Nash, Shapley, and Harsanyi. Reviews contexts in which negotiation and cooperation among libraries is of special economic importance, and for two of these contexts-cooperative acquisitions and cooperative automation-illustrates…

Policy capturing as a method of quantifying the determinants of landscape preference

Treesearch

Dennis B. Propst

1979-01-01

Policy Capturing, a potential methodology for evaluating landscape preference, was described and tested. This methodology results in a mathematical model that theoretically represents the human decision-making process. Under experimental conditions, judges were asked to express their preferences for scenes of the Blue Ridge Parkway. An equation which "captures,...

Steps to Promote Open and Authentic Dialogue between Teachers and School Management

ERIC Educational Resources Information Center

Klein, Joseph

2017-01-01

Purpose: School principals must determine educational policies and make information-based decisions. Teachers have authentic information that they do not transmit in full to the principals. A theoretical model was tested that explains the factors behind this disconnection in communication. Design: Four hundred and forty-five teachers completed…

Graduate School Choice: An Examination of Individual and Institutional Effects

ERIC Educational Resources Information Center

English, David Judson

2012-01-01

While significant scholarly attention focuses on the development and testing of theoretically grounded models of the college choice process at the undergraduate level, far less research explores the area of graduate school enrollments. Graduate school choice, which is defined for the purposes of this paper as the decision to pursue any…

Designing a Citizen Involvement Program: A Guidebook for Involving Citizens in the Resolution of Environmental Issues.

ERIC Educational Resources Information Center

Howell, Robert E.; And Others

A model and supportive materials are presented for design and implementation of a program for involving citizens in decision-making concerning significant environmental issues. Chapter topics include: why citizen involvement? (potential benefits of the process); theoretical basis for citizen involvement (three fundamental perspectives underlying…

Information Centralization of Organization Information Structures via Reports of Exceptions.

ERIC Educational Resources Information Center

Moskowitz, Herbert; Murnighan, John Keith

A team theoretic model that establishes a criterion (decision rule) for a financial institution branch to report exceptional loan requests to headquarters for action was compared to such choices made by graduate industrial management students acting as financial vice-presidents. Results showed that the loan size criterion specified by subjects was…

Scaling Up Decision Theoretic Planning to Planetary Rover Problems

NASA Technical Reports Server (NTRS)

Meuleau, Nicolas; Dearden, Richard; Washington, Rich

2004-01-01

Because of communication limits, planetary rovers must operate autonomously during consequent durations. The ability to plan under uncertainty is one of the main components of autonomy. Previous approaches to planning under uncertainty in NASA applications are not able to address the challenges of future missions, because of several apparent limits. On another side, decision theory provides a solid principle framework for reasoning about uncertainty and rewards. Unfortunately, there are several obstacles to a direct application of decision-theoretic techniques to the rover domain. This paper focuses on the issues of structure and concurrency, and continuous state variables. We describes two techniques currently under development that address specifically these issues and allow scaling-up decision theoretic solution techniques to planetary rover planning problems involving a small number of goals.

Four Mechanistic Models of Peer Influence on Adolescent Cannabis Use

PubMed Central

Caouette, Justin D.; Feldstein Ewing, Sarah W.

2017-01-01

Purpose of review Most adolescents begin exploring cannabis in peer contexts, but the neural mechanisms that underlie peer influence on adolescent cannabis use are still unknown. This theoretical overview elucidates the intersecting roles of neural function and peer factors in cannabis use in adolescents. Recent findings Novel paradigms using functional magnetic resonance imaging (fMRI) in adolescents have identified distinct neural mechanisms of risk decision-making and incentive processing in peer contexts, centered on reward-motivation and affect regulatory neural networks; these findings inform a theoretical model of peer-driven cannabis use decisions in adolescents. Summary We propose four “mechanistic profiles” of social facilitation of cannabis use in adolescents: (1) peer influence as the primary driver of use; (2) cannabis exploration as the primary driver, which may be enhanced in peer contexts; (3) social anxiety; and (4) negative peer experiences. Identification of “neural targets” involved in motivating cannabis use may inform clinicians about which treatment strategies work best in adolescents with cannabis use problems, and via which social and neurocognitive processes. PMID:29104847

The Tell-Tale Look: Viewing Time, Preferences, and Prices

PubMed Central

Gunia, Brian C.; Murnighan, J. Keith

2015-01-01

Even the simplest choices can prompt decision-makers to balance their preferences against other, more pragmatic considerations like price. Thus, discerning people’s preferences from their decisions creates theoretical, empirical, and practical challenges. The current paper addresses these challenges by highlighting some specific circumstances in which the amount of time that people spend examining potential purchase items (i.e., viewing time) can in fact reveal their preferences. Our model builds from the gazing literature, in a purchasing context, to propose that the informational value of viewing time depends on prices. Consistent with the model’s predictions, four studies show that when prices are absent or moderate, viewing time provides a signal that is consistent with a person’s preferences and purchase intentions. When prices are extreme or consistent with a person’s preferences, however, viewing time is a less reliable predictor of either. Thus, our model highlights a price-contingent “viewing bias,” shedding theoretical, empirical, and practical light on the psychology of preferences and visual attention, and identifying a readily observable signal of preference. PMID:25581382

Social cycling and conditional responses in the Rock-Paper-Scissors game

PubMed Central

Wang, Zhijian; Xu, Bin; Zhou, Hai-Jun

2014-01-01

How humans make decisions in non-cooperative strategic interactions is a big question. For the fundamental Rock-Paper-Scissors (RPS) model game system, classic Nash equilibrium (NE) theory predicts that players randomize completely their action choices to avoid being exploited, while evolutionary game theory of bounded rationality in general predicts persistent cyclic motions, especially in finite populations. However as empirical studies have been relatively sparse, it is still a controversial issue as to which theoretical framework is more appropriate to describe decision-making of human subjects. Here we observe population-level persistent cyclic motions in a laboratory experiment of the discrete-time iterated RPS game under the traditional random pairwise-matching protocol. This collective behavior contradicts with the NE theory but is quantitatively explained, without any adjustable parameter, by a microscopic model of win-lose-tie conditional response. Theoretical calculations suggest that if all players adopt the same optimized conditional response strategy, their accumulated payoff will be much higher than the reference value of the NE mixed strategy. Our work demonstrates the feasibility of understanding human competition behaviors from the angle of non-equilibrium statistical physics. PMID:25060115

Cognitive engineering models in space systems

NASA Technical Reports Server (NTRS)

Mitchell, Christine M.

1992-01-01

NASA space systems, including mission operations on the ground and in space, are complex, dynamic, predominantly automated systems in which the human operator is a supervisory controller. The human operator monitors and fine-tunes computer-based control systems and is responsible for ensuring safe and efficient system operation. In such systems, the potential consequences of human mistakes and errors may be very large, and low probability of such events is likely. Thus, models of cognitive functions in complex systems are needed to describe human performance and form the theoretical basis of operator workstation design, including displays, controls, and decision support aids. The operator function model represents normative operator behavior-expected operator activities given current system state. The extension of the theoretical structure of the operator function model and its application to NASA Johnson mission operations and space station applications is discussed.

Evidence accumulation detected in BOLD signal using slow perceptual decision making.

PubMed

Krueger, Paul M; van Vugt, Marieke K; Simen, Patrick; Nystrom, Leigh; Holmes, Philip; Cohen, Jonathan D

2017-04-01

We assessed whether evidence accumulation could be observed in the BOLD signal during perceptual decision making. This presents a challenge since the hemodynamic response is slow, while perceptual decisions are typically fast. Guided by theoretical predictions of the drift diffusion model, we slowed down decisions by penalizing participants for incorrect responses. Second, we distinguished BOLD activity related to stimulus detection (modeled using a boxcar) from activity related to integration (modeled using a ramp) by minimizing the collinearity of GLM regressors. This was achieved by dissecting a boxcar into its two most orthogonal components: an "up-ramp" and a "down-ramp." Third, we used a control condition in which stimuli and responses were similar to the experimental condition, but that did not engage evidence accumulation of the stimuli. The results revealed an absence of areas in parietal cortex that have been proposed to drive perceptual decision making but have recently come into question; and newly identified regions that are candidates for involvement in evidence accumulation. Previous fMRI studies have either used fast perceptual decision making, which precludes the measurement of evidence accumulation, or slowed down responses by gradually revealing stimuli. The latter approach confounds perceptual detection with evidence accumulation because accumulation is constrained by perceptual input. We slowed down the decision making process itself while leaving perceptual information intact. This provided a more sensitive and selective observation of brain regions associated with the evidence accumulation processes underlying perceptual decision making than previous methods. Copyright © 2017 Elsevier B.V. All rights reserved.

Acquisition and production of skilled behavior in dynamic decision-making tasks

NASA Technical Reports Server (NTRS)

Kirlik, Alex

1993-01-01

Summaries of the four projects completed during the performance of this research are included. The four projects described are: Perceptual Augmentation Aiding for Situation Assessment, Perceptual Augmentation Aiding for Dynamic Decision-Making and Control, Action Advisory Aiding for Dynamic Decision-Making and Control, and Display Design to Support Time-Constrained Route Optimization. Papers based on each of these projects are currently in preparation. The theoretical framework upon which the first three projects are based, Ecological Task Analysis, was also developed during the performance of this research, and is described in a previous report. A project concerned with modeling strategies in human control of a dynamic system was also completed during the performance of this research.

A new approach to hazardous materials transportation risk analysis: decision modeling to identify critical variables.

PubMed

Clark, Renee M; Besterfield-Sacre, Mary E

2009-03-01

We take a novel approach to analyzing hazardous materials transportation risk in this research. Previous studies analyzed this risk from an operations research (OR) or quantitative risk assessment (QRA) perspective by minimizing or calculating risk along a transport route. Further, even though the majority of incidents occur when containers are unloaded, the research has not focused on transportation-related activities, including container loading and unloading. In this work, we developed a decision model of a hazardous materials release during unloading using actual data and an exploratory data modeling approach. Previous studies have had a theoretical perspective in terms of identifying and advancing the key variables related to this risk, and there has not been a focus on probability and statistics-based approaches for doing this. Our decision model empirically identifies the critical variables using an exploratory methodology for a large, highly categorical database involving latent class analysis (LCA), loglinear modeling, and Bayesian networking. Our model identified the most influential variables and countermeasures for two consequences of a hazmat incident, dollar loss and release quantity, and is one of the first models to do this. The most influential variables were found to be related to the failure of the container. In addition to analyzing hazmat risk, our methodology can be used to develop data-driven models for strategic decision making in other domains involving risk.

Convergence to consensus in heterogeneous groups and the emergence of informal leadership

PubMed Central

Gavrilets, Sergey; Auerbach, Jeremy; van Vugt, Mark

2016-01-01

When group cohesion is essential, groups must have efficient strategies in place for consensus decision-making. Recent theoretical work suggests that shared decision-making is often the most efficient way for dealing with both information uncertainty and individual variation in preferences. However, some animal and most human groups make collective decisions through particular individuals, leaders, that have a disproportionate influence on group decision-making. To address this discrepancy between theory and data, we study a simple, but general, model that explicitly focuses on the dynamics of consensus building in groups composed by individuals who are heterogeneous in preferences, certain personality traits (agreeability and persuasiveness), reputation, and social networks. We show that within-group heterogeneity can significantly delay democratic consensus building as well as give rise to the emergence of informal leaders, i.e. individuals with a disproportionately large impact on group decisions. Our results thus imply strong benefits of leadership particularly when groups experience time pressure and significant conflict of interest between members (due to various between-individual differences). Overall, our models shed light on why leadership and decision-making hierarchies are widespread, especially in human groups. PMID:27412692

Understanding the Role of Numeracy in Health: Proposed Theoretical Framework and Practical Insights

PubMed Central

Lipkus, Isaac M.; Peters, Ellen

2009-01-01

Numeracy, that is how facile people are with mathematical concepts and their applications, is gaining importance in medical decision making and risk communication. This paper proposes six critical functions of health numeracy. These functions are integrated into a theoretical framework on health numeracy that has implications for risk-communication and medical-decision-making processes. We examine practical underpinnings for targeted interventions aimed at improving such processes as a function of health numeracy. It is hoped that the proposed functions and theoretical framework will spur more research to determine how an understanding of health numeracy can lead to more effective communication and decision outcomes. PMID:19834054

Recognition and source memory as multivariate decision processes.

PubMed

Banks, W P

2000-07-01

Recognition memory, source memory, and exclusion performance are three important domains of study in memory, each with its own findings, it specific theoretical developments, and its separate research literature. It is proposed here that results from all three domains can be treated with a single analytic model. This article shows how to generate a comprehensive memory representation based on multidimensional signal detection theory and how to make predictions for each of these paradigms using decision axes drawn through the space. The detection model is simpler than the comparable multinomial model, it is more easily generalizable, and it does not make threshold assumptions. An experiment using the same memory set for all three tasks demonstrates the analysis and tests the model. The results show that some seemingly complex relations between the paradigms derive from an underlying simplicity of structure.

When is rational to order a diagnostic test, or prescribe treatment: the threshold model as an explanation of practice variation.

PubMed

Djulbegovic, Benjamin; van den Ende, Jef; Hamm, Robert M; Mayrhofer, Thomas; Hozo, Iztok; Pauker, Stephen G

2015-05-01

The threshold model represents an important advance in the field of medical decision-making. It is a linchpin between evidence (which exists on the continuum of credibility) and decision-making (which is a categorical exercise - we decide to act or not act). The threshold concept is closely related to the question of rational decision-making. When should the physician act, that is order a diagnostic test, or prescribe treatment? The threshold model embodies the decision theoretic rationality that says the most rational decision is to prescribe treatment when the expected treatment benefit outweighs its expected harms. However, the well-documented large variation in the way physicians order diagnostic tests or decide to administer treatments is consistent with a notion that physicians' individual action thresholds vary. We present a narrative review summarizing the existing literature on physicians' use of a threshold strategy for decision-making. We found that the observed variation in decision action thresholds is partially due to the way people integrate benefits and harms. That is, explanation of variation in clinical practice can be reduced to a consideration of thresholds. Limited evidence suggests that non-expected utility threshold (non-EUT) models, such as regret-based and dual-processing models, may explain current medical practice better. However, inclusion of costs and recognition of risk attitudes towards uncertain treatment effects and comorbidities may improve the explanatory and predictive value of the EUT-based threshold models. The decision when to act is closely related to the question of rational choice. We conclude that the medical community has not yet fully defined criteria for rational clinical decision-making. The traditional notion of rationality rooted in EUT may need to be supplemented by reflective rationality, which strives to integrate all aspects of medical practice - medical, humanistic and socio-economic - within a coherent reasoning system. © 2015 Stichting European Society for Clinical Investigation Journal Foundation.

Computing by robust transience: How the fronto-parietal network performs sequential category-based decisions

PubMed Central

Chaisangmongkon, Warasinee; Swaminathan, Sruthi K.; Freedman, David J.; Wang, Xiao-Jing

2017-01-01

Summary Decision making involves dynamic interplay between internal judgements and external perception, which has been investigated in delayed match-to-category (DMC) experiments. Our analysis of neural recordings shows that, during DMC tasks, LIP and PFC neurons demonstrate mixed, time-varying, and heterogeneous selectivity, but previous theoretical work has not established the link between these neural characteristics and population-level computations. We trained a recurrent network model to perform DMC tasks and found that the model can remarkably reproduce key features of neuronal selectivity at the single-neuron and population levels. Analysis of the trained networks elucidates that robust transient trajectories of the neural population are the key driver of sequential categorical decisions. The directions of trajectories are governed by network self-organized connectivity, defining a ‘neural landscape’, consisting of a task-tailored arrangement of slow states and dynamical tunnels. With this model, we can identify functionally-relevant circuit motifs and generalize the framework to solve other categorization tasks. PMID:28334612

Price Strategies between a Dominant Retailer and Manufacturers

NASA Astrophysics Data System (ADS)

Cho, Hsun Jung; Mak, Hou Kit

2009-08-01

Supply chain-related game theoretical applications have been discussed for decades. This research accounts for the emergence of a dominant retailer, and the retailer Stackelberg pricing models of distribution channels. Research in the channel pricing game may use different definitions of pricing decision variables. In this research, we pay attentions to the retailer Stackelberg pricing game, and discuss the effects when choosing different decision variables. According the literature it was shown that the strategies between channel members depend critically on the form of the demand function. Two different demand forms—linear and non-linear—will be considered in our numerical example respectively. Our major finding is the outcomes are not relative to manufacturers' pricing decisions but to the retailer's pricing decision and choosing percentage margin as retailer's decision variable is the best strategy for the retailer but worst for manufacturers. The numerical results show that it is consistence between linear and non-linear demand form.

Perceptual Decision Making in Rodents, Monkeys, and Humans.

PubMed

Hanks, Timothy D; Summerfield, Christopher

2017-01-04

Perceptual decision making is the process by which animals detect, discriminate, and categorize information from the senses. Over the past two decades, understanding how perceptual decisions are made has become a central theme in the neurosciences. Exceptional progress has been made by recording from single neurons in the cortex of the macaque monkey and using computational models from mathematical psychology to relate these neural data to behavior. More recently, however, the range of available techniques and paradigms has dramatically broadened, and researchers have begun to harness new approaches to explore how rodents and humans make perceptual decisions. The results have illustrated some striking convergences with findings from the monkey, but also raised new questions and provided new theoretical insights. In this review, we summarize key findings, and highlight open challenges, for understanding perceptual decision making in rodents, monkeys, and humans. Copyright © 2017 Elsevier Inc. All rights reserved.

Decision-theoretic methodology for reliability and risk allocation in nuclear power plants

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cho, N.Z.; Papazoglou, I.A.; Bari, R.A.

1985-01-01

This paper describes a methodology for allocating reliability and risk to various reactor systems, subsystems, components, operations, and structures in a consistent manner, based on a set of global safety criteria which are not rigid. The problem is formulated as a multiattribute decision analysis paradigm; the multiobjective optimization, which is performed on a PRA model and reliability cost functions, serves as the guiding principle for reliability and risk allocation. The concept of noninferiority is used in the multiobjective optimization problem. Finding the noninferior solution set is the main theme of the current approach. The assessment of the decision maker's preferencesmore » could then be performed more easily on the noninferior solution set. Some results of the methodology applications to a nontrivial risk model are provided and several outstanding issues such as generic allocation and preference assessment are discussed.« less

Modulation of additive and interactive effects in lexical decision by trial history.

PubMed

Masson, Michael E J; Kliegl, Reinhold

2013-05-01

Additive and interactive effects of word frequency, stimulus quality, and semantic priming have been used to test theoretical claims about the cognitive architecture of word-reading processes. Additive effects among these factors have been taken as evidence for discrete-stage models of word reading. We present evidence from linear mixed-model analyses applied to 2 lexical decision experiments indicating that apparent additive effects can be the product of aggregating over- and underadditive interaction effects that are modulated by recent trial history, particularly the lexical status and stimulus quality of the previous trial's target. Even a simple practice effect expressed as improved response speed across trials was powerfully modulated by the nature of the previous target item. These results suggest that additivity and interaction between factors may reflect trial-to-trial variation in stimulus representations and decision processes rather than fundamental differences in processing architecture.

On the continuous differentiability of inter-spike intervals of synaptically connected cortical spiking neurons in a neuronal network.

PubMed

Kumar, Gautam; Kothare, Mayuresh V

2013-12-01

We derive conditions for continuous differentiability of inter-spike intervals (ISIs) of spiking neurons with respect to parameters (decision variables) of an external stimulating input current that drives a recurrent network of synaptically connected neurons. The dynamical behavior of individual neurons is represented by a class of discontinuous single-neuron models. We report here that ISIs of neurons in the network are continuously differentiable with respect to decision variables if (1) a continuously differentiable trajectory of the membrane potential exists between consecutive action potentials with respect to time and decision variables and (2) the partial derivative of the membrane potential of spiking neurons with respect to time is not equal to the partial derivative of their firing threshold with respect to time at the time of action potentials. Our theoretical results are supported by showing fulfillment of these conditions for a class of known bidimensional spiking neuron models.

A Practical Approach to Address Uncertainty in Stakeholder Deliberations.

PubMed

Gregory, Robin; Keeney, Ralph L

2017-03-01

This article addresses the difficulties of incorporating uncertainty about consequence estimates as part of stakeholder deliberations involving multiple alternatives. Although every prediction of future consequences necessarily involves uncertainty, a large gap exists between common practices for addressing uncertainty in stakeholder deliberations and the procedures of prescriptive decision-aiding models advanced by risk and decision analysts. We review the treatment of uncertainty at four main phases of the deliberative process: with experts asked to describe possible consequences of competing alternatives, with stakeholders who function both as individuals and as members of coalitions, with the stakeholder committee composed of all stakeholders, and with decisionmakers. We develop and recommend a model that uses certainty equivalents as a theoretically robust and practical approach for helping diverse stakeholders to incorporate uncertainties when evaluating multiple-objective alternatives as part of public policy decisions. © 2017 Society for Risk Analysis.

Implicit Theoretical Leadership Frameworks of Higher Education Administrators.

ERIC Educational Resources Information Center

Lees, Kimberly; And Others

Colleges and universities have a unique organizational culture that influences the decision-making processes used by leaders of higher education. This paper presents findings of a study that attempted to identify the theoretical frameworks that administrators of higher education use to guide their decision-making processes. The following…

Perception, Action, and Cognition of Football Referees in Extreme Temperatures: Impact on Decision Performance.

PubMed

Gaoua, Nadia; de Oliveira, Rita F; Hunter, Steve

2017-01-01

Different professional domains require high levels of physical performance alongside fast and accurate decision-making. Construction workers, police officers, firefighters, elite sports men and women, the military and emergency medical professionals are often exposed to hostile environments with limited options for behavioral coping strategies. In this (mini) review we use football refereeing as an example to discuss the combined effect of intense physical activity and extreme temperatures on decision-making and suggest an explicative model. In professional football competitions can be played in temperatures ranging from -5°C in Norway to 30°C in Spain for example. Despite these conditions, the referee's responsibility is to consistently apply the laws fairly and uniformly, and to ensure the rules are followed without waning or adversely influencing the competitiveness of the play. However, strenuous exercise in extreme environments imposes increased physiological and psychological stress that can affect decision-making. Therefore, the physical exertion required to follow the game and the thermal strain from the extreme temperatures may hinder the ability of referees to make fast and accurate decisions. Here, we review literature on the physical and cognitive requirements of football refereeing and how extreme temperatures may affect referees' decisions. Research suggests that both hot and cold environments have a negative impact on decision-making but data specific to decision-making is still lacking. A theoretical model of decision-making under the constraint of intense physical activity and thermal stress is suggested. Future naturalistic studies are needed to validate this model and provide clear recommendations for mitigating strategies.

Perception, Action, and Cognition of Football Referees in Extreme Temperatures: Impact on Decision Performance

PubMed Central

Gaoua, Nadia; de Oliveira, Rita F.; Hunter, Steve

2017-01-01

Different professional domains require high levels of physical performance alongside fast and accurate decision-making. Construction workers, police officers, firefighters, elite sports men and women, the military and emergency medical professionals are often exposed to hostile environments with limited options for behavioral coping strategies. In this (mini) review we use football refereeing as an example to discuss the combined effect of intense physical activity and extreme temperatures on decision-making and suggest an explicative model. In professional football competitions can be played in temperatures ranging from -5°C in Norway to 30°C in Spain for example. Despite these conditions, the referee’s responsibility is to consistently apply the laws fairly and uniformly, and to ensure the rules are followed without waning or adversely influencing the competitiveness of the play. However, strenuous exercise in extreme environments imposes increased physiological and psychological stress that can affect decision-making. Therefore, the physical exertion required to follow the game and the thermal strain from the extreme temperatures may hinder the ability of referees to make fast and accurate decisions. Here, we review literature on the physical and cognitive requirements of football refereeing and how extreme temperatures may affect referees’ decisions. Research suggests that both hot and cold environments have a negative impact on decision-making but data specific to decision-making is still lacking. A theoretical model of decision-making under the constraint of intense physical activity and thermal stress is suggested. Future naturalistic studies are needed to validate this model and provide clear recommendations for mitigating strategies. PMID:28912742

Emotions and Decisions: Beyond Conceptual Vagueness and the Rationality Muddle.

PubMed

Volz, Kirsten G; Hertwig, Ralph

2016-01-01

For centuries, decision scholars paid little attention to emotions: Decisions were modeled in normative and descriptive frameworks with little regard for affective processes. Recently, however, an "emotions revolution" has taken place, particularly in the neuroscientific study of decision making, putting emotional processes on an equal footing with cognitive ones. Yet disappointingly little theoretical progress has been made. The concepts and processes discussed often remain vague, and conclusions about the implications of emotions for rationality are contradictory and muddled. We discuss three complementary ways to move the neuroscientific study of emotion and decision making from agenda setting to theory building. The first is to use reverse inference as a hypothesis-discovery rather than a hypothesis-testing tool, unless its utility can be systematically quantified (e.g., through meta-analysis). The second is to capitalize on the conceptual inventory advanced by the behavioral science of emotions, testing those concepts and unveiling the underlying processes. The third is to model the interplay between emotions and decisions, harnessing existing cognitive frameworks of decision making and mapping emotions onto the postulated computational processes. To conclude, emotions (like cognitive strategies) are not rational or irrational per se: How (un)reasonable their influence is depends on their fit with the environment. © The Author(s) 2015.

The Sacramento-San Joaquin Delta Conflict: Strategic Insights for California's Policymakers

NASA Astrophysics Data System (ADS)

Moazezi, M. R.

2013-12-01

The Sacramento-San Joaquin Delta - a major water supply source in California and a unique habitat for many native and invasive species--is on the verge of collapse due to a prolonged conflict over how to manage the Delta. There is an urgent need to expedite the resolution of this conflict because the continuation of the status quo would leave irreversible environmental consequences for the entire state. In this paper a systematic technique is proposed for providing strategic insights into the Sacramento-San Joaquin Delta conflict. Game theory framework is chosen to systematically analyze behavioral characteristics of decision makers as well as their options in the conflict with respect to their preferences using a formal mathematical language. The Graph Model for Conflict Resolution (GMCR), a recent game-theoretic technique, is applied to model and analyze the Delta conflict in order to better understand the options, preferences, and behavioral characteristics of the major decision makers. GMCR II as a decision support system tool based on GMCR concept is used to facilitate the analysis of the problem through a range of non-cooperative game theoretic stability definitions. Furthermore, coalition analysis is conducted to analyze the potential for forming partial coalitions among decision makers, and to investigate how forming a coalition can influence the conflict resolution process. This contribution shows that involvement of the State of California is necessary for developing an environmental-friendly resolution for the Delta conflict. It also indicates that this resolution is only achievable through improving the fragile levee systems and constructing a new water export facility.

Purchasing and Using Personal Emergency Response Systems (PERS): how decisions are made by community-dwelling seniors in Canada.

PubMed

McKenna, Alexandra C; Kloseck, Marita; Crilly, Richard; Polgar, Jan

2015-07-11

As the demographic of older people continues to grow, health services that support independence among community-dwelling seniors have become increasingly important. Personal Emergency Response Systems (PERS) are medical alert systems, designed to serve as a safety net for seniors living alone. Health care professionals often recommend that seniors in danger of falls or other medical emergencies obtain a PERS. The purpose of the study was to investigate the experience of seniors living with and using a PERS in their daily lives, using a qualitative grounded theory approach. Five focus groups and 10 semi-structured interviews, with a total of 30 participants, were completed using a grounded theory approach. All participants were PERS subscribers over the age of 80, living alone in a naturally occurring retirement community (NORC) with high health service utilization in a major urban centre in Ontario. Constant comparative analysis was used to develop themes and ultimately a model of why and how seniors obtain and use the PERS. Two core themes, unpredictability and decision-making around PERS activation, emerged as major features of the theoretical model. Being able to get help and the psychological value of PERS informed the context of living with a PERS. A number of theoretical conclusions related to unpredictability and the decision-making process around activating PERS were generated.

Decision making generalized by a cumulative probability weighting function

NASA Astrophysics Data System (ADS)

dos Santos, Lindomar Soares; Destefano, Natália; Martinez, Alexandre Souto

2018-01-01

Typical examples of intertemporal decision making involve situations in which individuals must choose between a smaller reward, but more immediate, and a larger one, delivered later. Analogously, probabilistic decision making involves choices between options whose consequences differ in relation to their probability of receiving. In Economics, the expected utility theory (EUT) and the discounted utility theory (DUT) are traditionally accepted normative models for describing, respectively, probabilistic and intertemporal decision making. A large number of experiments confirmed that the linearity assumed by the EUT does not explain some observed behaviors, as nonlinear preference, risk-seeking and loss aversion. That observation led to the development of new theoretical models, called non-expected utility theories (NEUT), which include a nonlinear transformation of the probability scale. An essential feature of the so-called preference function of these theories is that the probabilities are transformed by decision weights by means of a (cumulative) probability weighting function, w(p) . We obtain in this article a generalized function for the probabilistic discount process. This function has as particular cases mathematical forms already consecrated in the literature, including discount models that consider effects of psychophysical perception. We also propose a new generalized function for the functional form of w. The limiting cases of this function encompass some parametric forms already proposed in the literature. Far beyond a mere generalization, our function allows the interpretation of probabilistic decision making theories based on the assumption that individuals behave similarly in the face of probabilities and delays and is supported by phenomenological models.

Vista goes online: Decision-analytic systems for real-time decision-making in mission control

NASA Technical Reports Server (NTRS)

Barry, Matthew; Horvitz, Eric; Ruokangas, Corinne; Srinivas, Sampath

1994-01-01

The Vista project has centered on the use of decision-theoretic approaches for managing the display of critical information relevant to real-time operations decisions. The Vista-I project originally developed a prototype of these approaches for managing flight control displays in the Space Shuttle Mission Control Center (MCC). The follow-on Vista-II project integrated these approaches in a workstation program which currently is being certified for use in the MCC. To our knowledge, this will be the first application of automated decision-theoretic reasoning techniques for real-time spacecraft operations. We shall describe the development and capabilities of the Vista-II system, and provide an overview of the use of decision-theoretic reasoning techniques to the problems of managing the complexity of flight controller displays. We discuss the relevance of the Vista techniques within the MCC decision-making environment, focusing on the problems of detecting and diagnosing spacecraft electromechanical subsystems component failures with limited information, and the problem of determining what control actions should be taken in high-stakes, time-critical situations in response to a diagnosis performed under uncertainty. Finally, we shall outline our current research directions for follow-on projects.

Model-Checking with Edge-Valued Decision Diagrams

NASA Technical Reports Server (NTRS)

Roux, Pierre; Siminiceanu, Radu I.

2010-01-01

We describe an algebra of Edge-Valued Decision Diagrams (EVMDDs) to encode arithmetic functions and its implementation in a model checking library along with state-of-the-art algorithms for building the transition relation and the state space of discrete state systems. We provide efficient algorithms for manipulating EVMDDs and give upper bounds of the theoretical time complexity of these algorithms for all basic arithmetic and relational operators. We also demonstrate that the time complexity of the generic recursive algorithm for applying a binary operator on EVMDDs is no worse than that of Multi-Terminal Decision Diagrams. We have implemented a new symbolic model checker with the intention to represent in one formalism the best techniques available at the moment across a spectrum of existing tools: EVMDDs for encoding arithmetic expressions, identity-reduced MDDs for representing the transition relation, and the saturation algorithm for reachability analysis. We compare our new symbolic model checking EVMDD library with the widely used CUDD package and show that, in many cases, our tool is several orders of magnitude faster than CUDD.

Probabilistic, Decision-theoretic Disease Surveillance and Control

PubMed Central

Wagner, Michael; Tsui, Fuchiang; Cooper, Gregory; Espino, Jeremy U.; Harkema, Hendrik; Levander, John; Villamarin, Ricardo; Voorhees, Ronald; Millett, Nicholas; Keane, Christopher; Dey, Anind; Razdan, Manik; Hu, Yang; Tsai, Ming; Brown, Shawn; Lee, Bruce Y.; Gallagher, Anthony; Potter, Margaret

2011-01-01

The Pittsburgh Center of Excellence in Public Health Informatics has developed a probabilistic, decision-theoretic system for disease surveillance and control for use in Allegheny County, PA and later in Tarrant County, TX. This paper describes the software components of the system and its knowledge bases. The paper uses influenza surveillance to illustrate how the software components transform data collected by the healthcare system into population level analyses and decision analyses of potential outbreak-control measures. PMID:23569617

Wildfire risk management on a landscape with public and private ownership: Who pays for protection?

Treesearch

Gwenlyn Busby; Heidi J. Albers

2010-01-01

Wildfire, like many natural hazards, affects large landscapes with many landowners and the risk individual owners face depends on both individual and collective protective actions. In this study, we develop a spatially explicit game theoretic model to examine the strategic interaction between landowners' hazard mitigation decisions on a landscape with public and...

Theory and Evidence of Switching Costs in the Market for College Textbooks

ERIC Educational Resources Information Center

McMahan, Chris

2013-01-01

This dissertation develops and estimates a model of switching costs in the market for college textbooks. First, in a theoretical setting, this paper characterizes the professor's adoption decision, which includes a trade-off between time and course quality. The professor faces a time cost when he switches textbooks. This switching cost leads…

A Note on the Treatment of Uncertainty in Economics and Finance

ERIC Educational Resources Information Center

Carilli, Anthony M.; Dempster, Gregory M.

2003-01-01

The treatment of uncertainty in the business classroom has been dominated by the application of risk theory to the utility-maximization framework. Nonetheless, the relevance of the standard risk model as a positive description of economic decision making often has been called into question in theoretical work. In this article, the authors offer an…

Methods of the Development Strategy of Service Companies: Logistical Approach

ERIC Educational Resources Information Center

Toymentseva, Irina A.; Karpova, Natalya P.; Toymentseva, Angelina A.; Chichkina, Vera D.; Efanov, Andrey V.

2016-01-01

The urgency of the analyzed issue is due to lack of attention of heads of service companies to the theory and methodology of strategic management, methods and models of management decision-making in times of economic instability. The purpose of the article is to develop theoretical positions and methodical recommendations on the formation of the…

Cultural Modelling: Literature review

DTIC Science & Technology

2006-09-01

of mood and/or emotions. Our review did show some evidence that artificial intelligence research has tended to depict human decision making as...pp. 72-79). The Society for the Study of Artificial Intelligence and the Simulation of Behaviour (AISB). Halfill, T., Sundstrom, E., Nielsen, T. M...M. & Thagard, P. (2005). Changing personalities: Towards realistic virtual characters. Journal of Experimental & Theoretical Artificial Intelligence

Evidence-Based Administration for Decision Making in the Framework of Knowledge Strategic Management

ERIC Educational Resources Information Center

Del Junco, Julio Garcia; Zaballa, Rafael De Reyna; de Perea, Juan Garcia Alvarez

2010-01-01

Purpose: This paper seeks to present a model based on evidence-based administration (EBA), which aims to facilitate the creation, transformation and diffusion of knowledge in learning organizations. Design/methodology/approach: A theoretical framework is proposed based on EBA and the case method. Accordingly, an empirical study was carried out in…

Engineering education as a complex system

NASA Astrophysics Data System (ADS)

Gattie, David K.; Kellam, Nadia N.; Schramski, John R.; Walther, Joachim

2011-12-01

This paper presents a theoretical basis for cultivating engineering education as a complex system that will prepare students to think critically and make decisions with regard to poorly understood, ill-structured issues. Integral to this theoretical basis is a solution space construct developed and presented as a benchmark for evaluating problem-solving orientations that emerge within students' thinking as they progress through an engineering curriculum. It is proposed that the traditional engineering education model, while analytically rigorous, is characterised by properties that, although necessary, are insufficient for preparing students to address complex issues of the twenty-first century. A Synthesis and Design Studio model for engineering education is proposed, which maintains the necessary rigor of analysis within a uniquely complex yet sufficiently structured learning environment.

Investigating Miranda waiver decisions: An examination of the rational consequences.

PubMed

Blackwood, Hayley L; Rogers, Richard; Steadham, Jennifer A; Fiduccia, Chelsea E

2015-01-01

Millions of custodial suspects waive their Miranda rights each year without the benefit of legal counsel. Miranda understanding, appreciation, and reasoning abilities are essential to courts' acceptance of Miranda waivers (Grisso, 2003; Rogers & Shuman, 2005). The question posed to forensic psychologists and psychiatrists in the disputed Miranda waivers is whether a particular waiver decision was knowing, intelligent, and voluntary. Despite the remarkable development of Miranda research in recent decades, studies have generally focused on understanding and appreciation of Miranda rights, but with comparatively minimal emphasis on Miranda reasoning and attendant waiver decisions. Research on defendants' decisional capacities constitutes a critical step in further developing theoretical and clinical models for Miranda waiver decisions. The current study evaluated Miranda waiver decisions for 80 pretrial defendants from two Oklahoma jails to study systematically how rational decision abilities affect defendants' personal waiver decisions. In stark contrast to what was expected, many defendants were able to identify a rational decisional process in their own legal cases, yet cast such reasoning aside and chose a completely contradictory Miranda waiver decision. Published by Elsevier Ltd.

An Integrated Psychosocial Model of Relatives' Decision About Deceased Organ Donation (IMROD): Joining Pieces of the Puzzle

PubMed Central

López, Jorge S.; Soria-Oliver, Maria; Aramayona, Begoña; García-Sánchez, Rubén; Martínez, José M.; Martín, María J.

2018-01-01

Organ transplantation remains currently limited because the demand for organs far exceeds the supply. Though organ procurement is a complex process involving social, organizational, and clinical factors, one of the most relevant limitations of organ availability is family refusal to donate organs of a deceased relative. In the past decades, a remarkable corpus of evidence about the factors conditioning relatives' consent has been generated. However, research in the field has been carried out mainly by means of merely empirical approaches, and only partial attempts have been made to integrate the existing empirical evidence within conceptual and theoretically based frameworks. Accordingly, this work articulates the proposal of an Integrated Psychosocial Model of Relatives' Organ Donation (IMROD) which offers a systematic view of the factors and psychosocial processes involved in family decision and their interrelations. Relatives' experience is conceptualized as a decision process about the possibility of vicariously performing an altruistic behavior that takes place under one of the most stressful experiences of one's lifetime and in the context of interaction with different healthcare professionals. Drawing on this, in the proposed model, the influence of the implied factors and their interrelations/interactions are structured and interpreted according to their theoretically based relation with processes like rational/heuristic decision-making, uncertainty, stress, bereavement, emotional reactions, sense of reciprocity, sense of freedom to decide, and attitudes/intentions toward one's own and the deceased's organ donation. Our model also develops a processual perspective and suggests different decisional scenarios that may be reached as a result of the combinations of the considered factors. Each of these scenarios may imply different balances between factors that enhance or hinder donation, such as different levels of uncertainty and potential decisional conflict. Throughout our work, current controversial or inconsistent results are discussed and interpreted on the basis of the relationships that are posited in the proposed model. Finally, we suggest that the structure of the relationships and interactions contained in our model can be used by future research to guide the formulation of hypotheses and the interpretation of results. In this sense, specific guidelines and research questions are also proposed. PMID:29692744

An Integrated Psychosocial Model of Relatives' Decision About Deceased Organ Donation (IMROD): Joining Pieces of the Puzzle.

PubMed

López, Jorge S; Soria-Oliver, Maria; Aramayona, Begoña; García-Sánchez, Rubén; Martínez, José M; Martín, María J

2018-01-01

Organ transplantation remains currently limited because the demand for organs far exceeds the supply. Though organ procurement is a complex process involving social, organizational, and clinical factors, one of the most relevant limitations of organ availability is family refusal to donate organs of a deceased relative. In the past decades, a remarkable corpus of evidence about the factors conditioning relatives' consent has been generated. However, research in the field has been carried out mainly by means of merely empirical approaches, and only partial attempts have been made to integrate the existing empirical evidence within conceptual and theoretically based frameworks. Accordingly, this work articulates the proposal of an Integrated Psychosocial Model of Relatives' Organ Donation (IMROD) which offers a systematic view of the factors and psychosocial processes involved in family decision and their interrelations. Relatives' experience is conceptualized as a decision process about the possibility of vicariously performing an altruistic behavior that takes place under one of the most stressful experiences of one's lifetime and in the context of interaction with different healthcare professionals. Drawing on this, in the proposed model, the influence of the implied factors and their interrelations/interactions are structured and interpreted according to their theoretically based relation with processes like rational/heuristic decision-making, uncertainty, stress, bereavement, emotional reactions, sense of reciprocity, sense of freedom to decide, and attitudes/intentions toward one's own and the deceased's organ donation. Our model also develops a processual perspective and suggests different decisional scenarios that may be reached as a result of the combinations of the considered factors. Each of these scenarios may imply different balances between factors that enhance or hinder donation, such as different levels of uncertainty and potential decisional conflict. Throughout our work, current controversial or inconsistent results are discussed and interpreted on the basis of the relationships that are posited in the proposed model. Finally, we suggest that the structure of the relationships and interactions contained in our model can be used by future research to guide the formulation of hypotheses and the interpretation of results. In this sense, specific guidelines and research questions are also proposed.

Theoretical aspects of cellular decision-making and information-processing.

PubMed

Kobayashi, Tetsuya J; Kamimura, Atsushi

2012-01-01

Microscopic biological processes have extraordinary complexity and variety at the sub-cellular, intra-cellular, and multi-cellular levels. In dealing with such complex phenomena, conceptual and theoretical frameworks are crucial, which enable us to understand seemingly different intra- and inter-cellular phenomena from unified viewpoints. Decision-making is one such concept that has attracted much attention recently. Since a number of cellular behavior can be regarded as processes to make specific actions in response to external stimuli, decision-making can cover and has been used to explain a broad range of different cellular phenomena [Balázsi et al. (Cell 144(6):910, 2011), Zeng et al. (Cell 141(4):682, 2010)]. Decision-making is also closely related to cellular information-processing because appropriate decisions cannot be made without exploiting the information that the external stimuli contain. Efficiency of information transduction and processing by intra-cellular networks determines the amount of information obtained, which in turn limits the efficiency of subsequent decision-making. Furthermore, information-processing itself can serve as another concept that is crucial for understanding of other biological processes than decision-making. In this work, we review recent theoretical developments on cellular decision-making and information-processing by focusing on the relation between these two concepts.

Modeling and optimum time performance for concurrent processing

NASA Technical Reports Server (NTRS)

Mielke, Roland R.; Stoughton, John W.; Som, Sukhamoy

1988-01-01

The development of a new graph theoretic model for describing the relation between a decomposed algorithm and its execution in a data flow environment is presented. Called ATAMM, the model consists of a set of Petri net marked graphs useful for representing decision-free algorithms having large-grained, computationally complex primitive operations. Performance time measures which determine computing speed and throughput capacity are defined, and the ATAMM model is used to develop lower bounds for these times. A concurrent processing operating strategy for achieving optimum time performance is presented and illustrated by example.

Constructor theory of probability

PubMed Central

2016-01-01

Unitary quantum theory, having no Born Rule, is non-probabilistic. Hence the notorious problem of reconciling it with the unpredictability and appearance of stochasticity in quantum measurements. Generalizing and improving upon the so-called ‘decision-theoretic approach’, I shall recast that problem in the recently proposed constructor theory of information—where quantum theory is represented as one of a class of superinformation theories, which are local, non-probabilistic theories conforming to certain constructor-theoretic conditions. I prove that the unpredictability of measurement outcomes (to which constructor theory gives an exact meaning) necessarily arises in superinformation theories. Then I explain how the appearance of stochasticity in (finitely many) repeated measurements can arise under superinformation theories. And I establish sufficient conditions for a superinformation theory to inform decisions (made under it) as if it were probabilistic, via a Deutsch–Wallace-type argument—thus defining a class of decision-supporting superinformation theories. This broadens the domain of applicability of that argument to cover constructor-theory compliant theories. In addition, in this version some of the argument's assumptions, previously construed as merely decision-theoretic, follow from physical properties expressed by constructor-theoretic principles. PMID:27616914

Bayesian accounts of covert selective attention: A tutorial review.

PubMed

Vincent, Benjamin T

2015-05-01

Decision making and optimal observer models offer an important theoretical approach to the study of covert selective attention. While their probabilistic formulation allows quantitative comparison to human performance, the models can be complex and their insights are not always immediately apparent. Part 1 establishes the theoretical appeal of the Bayesian approach, and introduces the way in which probabilistic approaches can be applied to covert search paradigms. Part 2 presents novel formulations of Bayesian models of 4 important covert attention paradigms, illustrating optimal observer predictions over a range of experimental manipulations. Graphical model notation is used to present models in an accessible way and Supplementary Code is provided to help bridge the gap between model theory and practical implementation. Part 3 reviews a large body of empirical and modelling evidence showing that many experimental phenomena in the domain of covert selective attention are a set of by-products. These effects emerge as the result of observers conducting Bayesian inference with noisy sensory observations, prior expectations, and knowledge of the generative structure of the stimulus environment.

Implementation of a participatory management model: analysis from a political perspective.

PubMed

Bernardes, Andrea; G Cummings, Greta; Gabriel, Carmen Silvia; Martinez Évora, Yolanda Dora; Gomes Maziero, Vanessa; Coleman-Miller, Glenda

2015-10-01

To analyse experiences of managers and nursing staff in the implementation of participatory management, specifically processes of decision-making, communication and power in a Canadian hospital. Implementing a Participatory Management Model involves change because it is focused on the needs of patients and encourages decentralisation of power and shared decisions. The study design is qualitative using observational sessions and content analysis for data analysis. We used Bolman and Deal's four-frame theoretical framework to interpret our findings. Participatory management led to advances in care, because it allowed for more dialogue and shared decision making. However, the biggest challenge has been that all major changes are still being decided centrally by the provincial executive board. Managers and directors are facing difficulties related to this change process, such as the resistance to change by some employees and limited input to decision-making affecting their areas of responsibility; however, they and their teams are working to utilise the values and principles underlying participatory management in their daily work practices. Innovative management models encourage accountability, increased motivation and satisfaction of nursing staff, and improve the quality of care. © 2014 John Wiley & Sons Ltd.

Defending Against Advanced Persistent Threats Using Game-Theory.

PubMed

Rass, Stefan; König, Sandra; Schauer, Stefan

2017-01-01

Advanced persistent threats (APT) combine a variety of different attack forms ranging from social engineering to technical exploits. The diversity and usual stealthiness of APT turns them into a central problem of contemporary practical system security, since information on attacks, the current system status or the attacker's incentives is often vague, uncertain and in many cases even unavailable. Game theory is a natural approach to model the conflict between the attacker and the defender, and this work investigates a generalized class of matrix games as a risk mitigation tool for an advanced persistent threat (APT) defense. Unlike standard game and decision theory, our model is tailored to capture and handle the full uncertainty that is immanent to APTs, such as disagreement among qualitative expert risk assessments, unknown adversarial incentives and uncertainty about the current system state (in terms of how deeply the attacker may have penetrated into the system's protective shells already). Practically, game-theoretic APT models can be derived straightforwardly from topological vulnerability analysis, together with risk assessments as they are done in common risk management standards like the ISO 31000 family. Theoretically, these models come with different properties than classical game theoretic models, whose technical solution presented in this work may be of independent interest.

Probative value of absolute and relative judgments in eyewitness identification.

PubMed

Clark, Steven E; Erickson, Michael A; Breneman, Jesse

2011-10-01

It is well-accepted that eyewitness identification decisions based on relative judgments are less accurate than identification decisions based on absolute judgments. However, the theoretical foundation for this view has not been established. In this study relative and absolute judgments were compared through simulations of the WITNESS model (Clark, Appl Cogn Psychol 17:629-654, 2003) to address the question: Do suspect identifications based on absolute judgments have higher probative value than suspect identifications based on relative judgments? Simulations of the WITNESS model showed a consistent advantage for absolute judgments over relative judgments for suspect-matched lineups. However, simulations of same-foils lineups showed a complex interaction based on the accuracy of memory and the similarity relationships among lineup members.

Optimal indolence: a normative microscopic approach to work and leisure

PubMed Central

Niyogi, Ritwik K.; Breton, Yannick-Andre; Solomon, Rebecca B.; Conover, Kent; Shizgal, Peter; Dayan, Peter

2014-01-01

Dividing limited time between work and leisure when both have their attractions is a common everyday decision. We provide a normative control-theoretic treatment of this decision that bridges economic and psychological accounts. We show how our framework applies to free-operant behavioural experiments in which subjects are required to work (depressing a lever) for sufficient total time (called the price) to receive a reward. When the microscopic benefit-of-leisure increases nonlinearly with duration, the model generates behaviour that qualitatively matches various microfeatures of subjects’ choices, including the distribution of leisure bout durations as a function of the pay-off. We relate our model to traditional accounts by deriving macroscopic, molar, quantities from microscopic choices. PMID:24284898

Computing an optimal time window of audiovisual integration in focused attention tasks: illustrated by studies on effect of age and prior knowledge.

PubMed

Colonius, Hans; Diederich, Adele

2011-07-01

The concept of a "time window of integration" holds that information from different sensory modalities must not be perceived too far apart in time in order to be integrated into a multisensory perceptual event. Empirical estimates of window width differ widely, however, ranging from 40 to 600 ms depending on context and experimental paradigm. Searching for theoretical derivation of window width, Colonius and Diederich (Front Integr Neurosci 2010) developed a decision-theoretic framework using a decision rule that is based on the prior probability of a common source, the likelihood of temporal disparities between the unimodal signals, and the payoff for making right or wrong decisions. Here, this framework is extended to the focused attention task where subjects are asked to respond to signals from a target modality only. Evoking the framework of the time-window-of-integration (TWIN) model, an explicit expression for optimal window width is obtained. The approach is probed on two published focused attention studies. The first is a saccadic reaction time study assessing the efficiency with which multisensory integration varies as a function of aging. Although the window widths for young and older adults differ by nearly 200 ms, presumably due to their different peripheral processing speeds, neither of them deviates significantly from the optimal values. In the second study, head saccadic reactions times to a perfectly aligned audiovisual stimulus pair had been shown to depend on the prior probability of spatial alignment. Intriguingly, they reflected the magnitude of the time-window widths predicted by our decision-theoretic framework, i.e., a larger time window is associated with a higher prior probability.

Knowledge translation strategies to improve the use of evidence in public health decision making in local government: intervention design and implementation plan

PubMed Central

2013-01-01

Background Knowledge translation strategies are an approach to increase the use of evidence within policy and practice decision-making contexts. In clinical and health service contexts, knowledge translation strategies have focused on individual behavior change, however the multi-system context of public health requires a multi-level, multi-strategy approach. This paper describes the design of and implementation plan for a knowledge translation intervention for public health decision making in local government. Methods Four preliminary research studies contributed findings to the design of the intervention: a systematic review of knowledge translation intervention effectiveness research, a scoping study of knowledge translation perspectives and relevant theory literature, a survey of the local government public health workforce, and a study of the use of evidence-informed decision-making for public health in local government. A logic model was then developed to represent the putative pathways between intervention inputs, processes, and outcomes operating between individual-, organizational-, and system-level strategies. This formed the basis of the intervention plan. Results The systematic and scoping reviews identified that effective and promising strategies to increase access to research evidence require an integrated intervention of skill development, access to a knowledge broker, resources and tools for evidence-informed decision making, and networking for information sharing. Interviews and survey analysis suggested that the intervention needs to operate at individual and organizational levels, comprising workforce development, access to evidence, and regular contact with a knowledge broker to increase access to intervention evidence; develop skills in appraisal and integration of evidence; strengthen networks; and explore organizational factors to build organizational cultures receptive to embedding evidence in practice. The logic model incorporated these inputs and strategies with a set of outcomes to measure the intervention’s effectiveness based on the theoretical frameworks, evaluation studies, and decision-maker experiences. Conclusion Documenting the design of and implementation plan for this knowledge translation intervention provides a transparent, theoretical, and practical approach to a complex intervention. It provides significant insights into how practitioners might engage with evidence in public health decision making. While this intervention model was designed for the local government context, it is likely to be applicable and generalizable across sectors and settings. Trial registration Australia New Zealand Clinical Trials Register ACTRN12609000953235. PMID:24107358

Pilot interaction with automated airborne decision making systems

NASA Technical Reports Server (NTRS)

Rouse, W. B.; Chu, Y. Y.; Greenstein, J. S.; Walden, R. S.

1976-01-01

An investigation was made of interaction between a human pilot and automated on-board decision making systems. Research was initiated on the topic of pilot problem solving in automated and semi-automated flight management systems and attempts were made to develop a model of human decision making in a multi-task situation. A study was made of allocation of responsibility between human and computer, and discussed were various pilot performance parameters with varying degrees of automation. Optimal allocation of responsibility between human and computer was considered and some theoretical results found in the literature were presented. The pilot as a problem solver was discussed. Finally the design of displays, controls, procedures, and computer aids for problem solving tasks in automated and semi-automated systems was considered.

Understanding the Hows and Whys of Decision-Making: From Expected Utility to Divisive Normalization.

PubMed

Glimcher, Paul

2014-01-01

Over the course of the last century, economists and ethologists have built detailed models from first principles of how humans and animals should make decisions. Over the course of the last few decades, psychologists and behavioral economists have gathered a wealth of data at variance with the predictions of these economic models. This has led to the development of highly descriptive models that can often predict what choices people or animals will make but without offering any insight into why people make the choices that they do--especially when those choices reduce a decision-maker's well-being. Over the course of the last two decades, neurobiologists working with economists and psychologists have begun to use our growing understanding of how the nervous system works to develop new models of how the nervous system makes decisions. The result, a growing revolution at the interdisciplinary border of neuroscience, psychology, and economics, is a new field called Neuroeconomics. Emerging neuroeconomic models stand to revolutionize our understanding of human and animal choice behavior by combining fundamental properties of neurobiological representation with decision-theoretic analyses. In this overview, one class of these models, based on the widely observed neural computation known as divisive normalization, is presented in detail. The work demonstrates not only that a discrete class of computation widely observed in the nervous system is fundamentally ubiquitous, but how that computation shapes behaviors ranging from visual perception to financial decision-making. It also offers the hope of reconciling economic analysis of what choices we should make with psychological observations of the choices we actually do make. Copyright © 2014 Cold Spring Harbor Laboratory Press; all rights reserved.

A Probabilistic, Dynamic, and Attribute-wise Model of Intertemporal Choice

PubMed Central

Dai, Junyi; Busemeyer, Jerome R.

2014-01-01

Most theoretical and empirical research on intertemporal choice assumes a deterministic and static perspective, leading to the widely adopted delay discounting models. As a form of preferential choice, however, intertemporal choice may be generated by a stochastic process that requires some deliberation time to reach a decision. We conducted three experiments to investigate how choice and decision time varied as a function of manipulations designed to examine the delay duration effect, the common difference effect, and the magnitude effect in intertemporal choice. The results, especially those associated with the delay duration effect, challenged the traditional deterministic and static view and called for alternative approaches. Consequently, various static or dynamic stochastic choice models were explored and fit to the choice data, including alternative-wise models derived from the traditional exponential or hyperbolic discount function and attribute-wise models built upon comparisons of direct or relative differences in money and delay. Furthermore, for the first time, dynamic diffusion models, such as those based on decision field theory, were also fit to the choice and response time data simultaneously. The results revealed that the attribute-wise diffusion model with direct differences, power transformations of objective value and time, and varied diffusion parameter performed the best and could account for all three intertemporal effects. In addition, the empirical relationship between choice proportions and response times was consistent with the prediction of diffusion models and thus favored a stochastic choice process for intertemporal choice that requires some deliberation time to make a decision. PMID:24635188

Many faces of rationality: Implications of the great rationality debate for clinical decision-making.

PubMed

Djulbegovic, Benjamin; Elqayam, Shira

2017-10-01

Given that more than 30% of healthcare costs are wasted on inappropriate care, suboptimal care is increasingly connected to the quality of medical decisions. It has been argued that personal decisions are the leading cause of death, and 80% of healthcare expenditures result from physicians' decisions. Therefore, improving healthcare necessitates improving medical decisions, ie, making decisions (more) rational. Drawing on writings from The Great Rationality Debate from the fields of philosophy, economics, and psychology, we identify core ingredients of rationality commonly encountered across various theoretical models. Rationality is typically classified under umbrella of normative (addressing the question how people "should" or "ought to" make their decisions) and descriptive theories of decision-making (which portray how people actually make their decisions). Normative theories of rational thought of relevance to medicine include epistemic theories that direct practice of evidence-based medicine and expected utility theory, which provides the basis for widely used clinical decision analyses. Descriptive theories of rationality of direct relevance to medical decision-making include bounded rationality, argumentative theory of reasoning, adaptive rationality, dual processing model of rationality, regret-based rationality, pragmatic/substantive rationality, and meta-rationality. For the first time, we provide a review of wide range of theories and models of rationality. We showed that what is "rational" behaviour under one rationality theory may be irrational under the other theory. We also showed that context is of paramount importance to rationality and that no one model of rationality can possibly fit all contexts. We suggest that in context-poor situations, such as policy decision-making, normative theories based on expected utility informed by best research evidence may provide the optimal approach to medical decision-making, whereas in the context-rich circumstances other types of rationality, informed by human cognitive architecture and driven by intuition and emotions such as the aim to minimize regret, may provide better solution to the problem at hand. The choice of theory under which we operate is important as it determines both policy and our individual decision-making. © 2017 The Authors Journal of Evaluation in Clinical Practice Published by John Wiley & Sons Ltd.

A behavior model for blood donors and marketing strategies to retain and attract them

PubMed Central

Aldamiz-echevarria, Covadonga; Aguirre-Garcia, Maria Soledad

2014-01-01

Objective analyze and propose a theoretical model that describes blood donor decisions to help staff working in blood banks (nurses and others) in their efforts to capture and retain donors. Methods analysis of several studies on the motivations to give blood in Spain over the last six years, as well as past literature on the topic, the authors' experiences in the last 25 years in over 15 Non Governmental Organizations with different levels of responsibilities, their experiences as blood donors and the informal interviews developed during those 25 years. Results a model is proposed with different internal and external factors that influence blood donation, as well as the different stages of the decision-making process. Conclusion the knowledge of the donation process permits the development of marketing strategies that help to increase donors and donations. PMID:25029059

A behavior model for blood donors and marketing strategies to retain and attract them.

PubMed

Aldamiz-Echevarria, Covadonga; Aguirre-Garcia, Maria Soledad

2014-01-01

analyze and propose a theoretical model that describes blood donor decisions to help staff working in blood banks (nurses and others) in their efforts to capture and retain donors. analysis of several studies on the motivations to give blood in Spain over the last six years, as well as past literature on the topic, the authors' experiences in the last 25 years in over 15 Non Governmental Organizations with different levels of responsibilities, their experiences as blood donors and the informal interviews developed during those 25 years. a model is proposed with different internal and external factors that influence blood donation, as well as the different stages of the decision-making process. the knowledge of the donation process permits the development of marketing strategies that help to increase donors and donations.

Household social characteristics of the demand for alcoholic beverages among Spanish students.

PubMed

Gil-Lacruz, Ana Isabel; Gil-Lacruz, Marta

2013-03-01

This paper studies how household social capital affects adolescents' demand for alcoholic drinks. To that end, we focus on a theoretical framework that combines elements from the Model of Rational Addiction and the Model of Social Economics. For the empirical framework, we use a simultaneous Type II Tobit model, with data drawn from the Spanish National Survey on Drug Use in the School Population (2000, 2002, and 2004). The sample is comprised of 12,627 students aged 17 years old. Our results confirm that parents' decisions about drinking are even more decisive in their children's behavior than socioeconomic variables, such as parents' educative levels or working status. Parental responsibilities go beyond the endowment of health and educational goods and services; so, these results suggest the importance of designing family-drug use prevention programs. The study's limitations are noted.

Neuromorphic Implementation of Attractor Dynamics in a Two-Variable Winner-Take-All Circuit with NMDARs: A Simulation Study

PubMed Central

You, Hongzhi; Wang, Da-Hui

2017-01-01

Neural networks configured with winner-take-all (WTA) competition and N-methyl-D-aspartate receptor (NMDAR)-mediated synaptic dynamics are endowed with various dynamic characteristics of attractors underlying many cognitive functions. This paper presents a novel method for neuromorphic implementation of a two-variable WTA circuit with NMDARs aimed at implementing decision-making, working memory and hysteresis in visual perceptions. The method proposed is a dynamical system approach of circuit synthesis based on a biophysically plausible WTA model. Notably, slow and non-linear temporal dynamics of NMDAR-mediated synapses was generated. Circuit simulations in Cadence reproduced ramping neural activities observed in electrophysiological recordings in experiments of decision-making, the sustained activities observed in the prefrontal cortex during working memory, and classical hysteresis behavior during visual discrimination tasks. Furthermore, theoretical analysis of the dynamical system approach illuminated the underlying mechanisms of decision-making, memory capacity and hysteresis loops. The consistence between the circuit simulations and theoretical analysis demonstrated that the WTA circuit with NMDARs was able to capture the attractor dynamics underlying these cognitive functions. Their physical implementations as elementary modules are promising for assembly into integrated neuromorphic cognitive systems. PMID:28223913

Neuromorphic Implementation of Attractor Dynamics in a Two-Variable Winner-Take-All Circuit with NMDARs: A Simulation Study.

PubMed

You, Hongzhi; Wang, Da-Hui

2017-01-01

Neural networks configured with winner-take-all (WTA) competition and N-methyl-D-aspartate receptor (NMDAR)-mediated synaptic dynamics are endowed with various dynamic characteristics of attractors underlying many cognitive functions. This paper presents a novel method for neuromorphic implementation of a two-variable WTA circuit with NMDARs aimed at implementing decision-making, working memory and hysteresis in visual perceptions. The method proposed is a dynamical system approach of circuit synthesis based on a biophysically plausible WTA model. Notably, slow and non-linear temporal dynamics of NMDAR-mediated synapses was generated. Circuit simulations in Cadence reproduced ramping neural activities observed in electrophysiological recordings in experiments of decision-making, the sustained activities observed in the prefrontal cortex during working memory, and classical hysteresis behavior during visual discrimination tasks. Furthermore, theoretical analysis of the dynamical system approach illuminated the underlying mechanisms of decision-making, memory capacity and hysteresis loops. The consistence between the circuit simulations and theoretical analysis demonstrated that the WTA circuit with NMDARs was able to capture the attractor dynamics underlying these cognitive functions. Their physical implementations as elementary modules are promising for assembly into integrated neuromorphic cognitive systems.

Probabilistic learning and inference in schizophrenia

PubMed Central

Averbeck, Bruno B.; Evans, Simon; Chouhan, Viraj; Bristow, Eleanor; Shergill, Sukhwinder S.

2010-01-01

Patients with schizophrenia make decisions on the basis of less evidence when required to collect information to make an inference, a behavior often called jumping to conclusions. The underlying basis for this behaviour remains controversial. We examined the cognitive processes underpinning this finding by testing subjects on the beads task, which has been used previously to elicit jumping to conclusions behaviour, and a stochastic sequence learning task, with a similar decision theoretic structure. During the sequence learning task, subjects had to learn a sequence of button presses, while receiving noisy feedback on their choices. We fit a Bayesian decision making model to the sequence task and compared model parameters to the choice behavior in the beads task in both patients and healthy subjects. We found that patients did show a jumping to conclusions style; and those who picked early in the beads task tended to learn less from positive feedback in the sequence task. This favours the likelihood of patients selecting early because they have a low threshold for making decisions, and that they make choices on the basis of relatively little evidence. PMID:20810252

Probabilistic learning and inference in schizophrenia.

PubMed

Averbeck, Bruno B; Evans, Simon; Chouhan, Viraj; Bristow, Eleanor; Shergill, Sukhwinder S

2011-04-01

Patients with schizophrenia make decisions on the basis of less evidence when required to collect information to make an inference, a behavior often called jumping to conclusions. The underlying basis for this behavior remains controversial. We examined the cognitive processes underpinning this finding by testing subjects on the beads task, which has been used previously to elicit jumping to conclusions behavior, and a stochastic sequence learning task, with a similar decision theoretic structure. During the sequence learning task, subjects had to learn a sequence of button presses, while receiving a noisy feedback on their choices. We fit a Bayesian decision making model to the sequence task and compared model parameters to the choice behavior in the beads task in both patients and healthy subjects. We found that patients did show a jumping to conclusions style; and those who picked early in the beads task tended to learn less from positive feedback in the sequence task. This favours the likelihood of patients selecting early because they have a low threshold for making decisions, and that they make choices on the basis of relatively little evidence. Published by Elsevier B.V.

Shame in decision making under risk conditions: Understanding the effect of transparency.

PubMed

Bonavia, Tomas; Brox-Ponce, Josué

2018-01-01

The role played by the emotion of shame in the area of decision-making in situations of risk has hardly been studied. In this article, we show how the socio-moral emotions and the anticipated feeling of shame associated with different options can determine our decisions, even overriding the cognitive choice tendency proposed by the certainty effect. To do so, we carried out an experiment with university students as participants, dividing them into four experimental conditions. Our findings suggest that people avoid making unethical decisions, both when these decisions are made public to others and when they remain in the private sphere. This result seems to indicate that the main factor in not making unethical decisions is related to the need to avoid transgressing an internal moral standard of behavior, and that the role of transparency is less relevant than expected. However, we propose that, although the effect of transparency is limited in reducing unethical economic decisions, it should continue to be taken into account in theoretical models that address the reasons people behave unethically.

Shame in decision making under risk conditions: Understanding the effect of transparency

PubMed Central

2018-01-01

The role played by the emotion of shame in the area of decision-making in situations of risk has hardly been studied. In this article, we show how the socio-moral emotions and the anticipated feeling of shame associated with different options can determine our decisions, even overriding the cognitive choice tendency proposed by the certainty effect. To do so, we carried out an experiment with university students as participants, dividing them into four experimental conditions. Our findings suggest that people avoid making unethical decisions, both when these decisions are made public to others and when they remain in the private sphere. This result seems to indicate that the main factor in not making unethical decisions is related to the need to avoid transgressing an internal moral standard of behavior, and that the role of transparency is less relevant than expected. However, we propose that, although the effect of transparency is limited in reducing unethical economic decisions, it should continue to be taken into account in theoretical models that address the reasons people behave unethically. PMID:29444107

Exploring the association between insecure attachment styles and adolescent autonomy in family decision making: a differentiated approach.

PubMed

Van Petegem, Stijn; Beyers, Wim; Brenning, Katrijn; Vansteenkiste, Maarten

2013-12-01

The present investigation focuses on the associations between adolescents' insecure attachment styles (i.e., anxiety and avoidance) and their autonomous functioning in family decision making. In line with recent insights in the construct of adolescent autonomy, we combined two perspectives on autonomy, differentiating between the degree of independent versus dependent functioning and the self-endorsed and pressuring motives underlying (in)dependent functioning. A longitudinal sample of 327 adolescents (age range = 13-20 years; 64 % girls) completed questionnaires on attachment to the mother and father and on both autonomy operationalisations on two measurement moments spanning a 1-year interval. Structural equation modeling showed that attachment avoidance generally was unrelated to the degree of independent decision making and the motives underlying independent decision making, but related to more pressuring motives for dependent decision making. Anxiety, on the other hand, was associated with a lower degree of independent decision making as well as with more pressuring motives for both independent and dependent decision making. Cross-lagged paths were generally in line with these findings. Theoretical implications are outlined in the discussion.

Web-services-based spatial decision support system to facilitate nuclear waste siting

NASA Astrophysics Data System (ADS)

Huang, L. Xinglai; Sheng, Grant

2006-10-01

The availability of spatial web services enables data sharing among managers, decision and policy makers and other stakeholders in much simpler ways than before and subsequently has created completely new opportunities in the process of spatial decision making. Though generally designed for a certain problem domain, web-services-based spatial decision support systems (WSDSS) can provide a flexible problem-solving environment to explore the decision problem, understand and refine problem definition, and generate and evaluate multiple alternatives for decision. This paper presents a new framework for the development of a web-services-based spatial decision support system. The WSDSS is comprised of distributed web services that either have their own functions or provide different geospatial data and may reside in different computers and locations. WSDSS includes six key components, namely: database management system, catalog, analysis functions and models, GIS viewers and editors, report generators, and graphical user interfaces. In this study, the architecture of a web-services-based spatial decision support system to facilitate nuclear waste siting is described as an example. The theoretical, conceptual and methodological challenges and issues associated with developing web services-based spatial decision support system are described.

Dynamic decision making for dam-break emergency management - Part 1: Theoretical framework

NASA Astrophysics Data System (ADS)

Peng, M.; Zhang, L. M.

2013-02-01

An evacuation decision for dam breaks is a very serious issue. A late decision may lead to loss of lives and properties, but a very early evacuation will incur unnecessary expenses. This paper presents a risk-based framework of dynamic decision making for dam-break emergency management (DYDEM). The dam-break emergency management in both time scale and space scale is introduced first to define the dynamic decision problem. The probability of dam failure is taken as a stochastic process and estimated using a time-series analysis method. The flood consequences are taken as functions of warning time and evaluated with a human risk analysis model (HURAM) based on Bayesian networks. A decision criterion is suggested to decide whether to evacuate the population at risk (PAR) or to delay the decision. The optimum time for evacuating the PAR is obtained by minimizing the expected total loss, which integrates the time-related probabilities and flood consequences. When a delayed decision is chosen, the decision making can be updated with available new information. A specific dam-break case study is presented in a companion paper to illustrate the application of this framework to complex dam-breaching problems.

The construct-behavior gap in behavioral decision research: A challenge beyond replicability.

PubMed

Regenwetter, Michel; Robinson, Maria M

2017-10-01

Behavioral decision research compares theoretical constructs like preferences to behavior such as observed choices. Three fairly common links from constructs to behavior are (1) to tally, across participants and decision problems, the number of choices consistent with one predicted pattern of pairwise preferences; (2) to compare what most people choose in each decision problem against a predicted preference pattern; or (3) to enumerate the decision problems in which two experimental conditions generate a 1-sided significant difference in choice frequency 'consistent' with the theory. Although simple, these theoretical links are heuristics. They are subject to well-known reasoning fallacies, most notably the fallacy of sweeping generalization and the fallacy of composition. No amount of replication can alleviate these fallacies. On the contrary, reiterating logically inconsistent theoretical reasoning over and again across studies obfuscates science. As a case in point, we consider pairwise choices among simple lotteries and the hypotheses of overweighting or underweighting of small probabilities, as well as the description-experience gap. We discuss ways to avoid reasoning fallacies in bridging the conceptual gap between hypothetical constructs, such as, for example, "overweighting" to observable pairwise choice data. Although replication is invaluable, successful replication of hard-to-interpret results is not. Behavioral decision research stands to gain much theoretical and empirical clarity by spelling out precise and formally explicit theories of how hypothetical constructs translate into observable behavior. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

The Scenario Approach to the Development of Regional Waste Management Systems (Implementation Experience in the Regions of Russia)

ERIC Educational Resources Information Center

Fomin, Eugene P.; Alekseev, Audrey A.; Fomina, Natalia E.; Dorozhkin, Vladimir E.

2016-01-01

The article illustrates a theoretical approach to scenario modeling of economic indicators of regional waste management system. The method includes a three-iterative algorithm that allows the executive authorities and investors to take a decision on logistics, bulk, technological and economic parameters of the formation of the regional long-term…

Imitation dynamics of vaccine decision-making behaviours based on the game theory.

PubMed

Yang, Junyuan; Martcheva, Maia; Chen, Yuming

2016-01-01

Based on game theory, we propose an age-structured model to investigate the imitation dynamics of vaccine uptake. We first obtain the existence and local stability of equilibria. We show that Hopf bifurcation can occur. We also establish the global stability of the boundary equilibria and persistence of the disease. The theoretical results are supported by numerical simulations.

Toward theoretical understanding of the fertility preservation decision-making process: examining information processing among young women with cancer.

PubMed

Hershberger, Patricia E; Finnegan, Lorna; Altfeld, Susan; Lake, Sara; Hirshfeld-Cytron, Jennifer

2013-01-01

Young women with cancer now face the complex decision about whether to undergo fertility preservation. Yet little is known about how these women process information involved in making this decision. The purpose of this article is to expand theoretical understanding of the decision-making process by examining aspects of information processing among young women diagnosed with cancer. Using a grounded theory approach, 27 women with cancer participated in individual, semistructured interviews. Data were coded and analyzed using constant-comparison techniques that were guided by 5 dimensions within the Contemplate phase of the decision-making process framework. In the first dimension, young women acquired information primarily from clinicians and Internet sources. Experiential information, often obtained from peers, occurred in the second dimension. Preferences and values were constructed in the third dimension as women acquired factual, moral, and ethical information. Women desired tailored, personalized information that was specific to their situation in the fourth dimension; however, women struggled with communicating these needs to clinicians. In the fifth dimension, women offered detailed descriptions of clinician behaviors that enhance or impede decisional debriefing. Better understanding of theoretical underpinnings surrounding women's information processes can facilitate decision support and improve clinical care.

Midwives׳ clinical reasoning during second stage labour: Report on an interpretive study.

PubMed

Jefford, Elaine; Fahy, Kathleen

2015-05-01

clinical reasoning was once thought to be the exclusive domain of medicine - setting it apart from 'non-scientific' occupations like midwifery. Poor assessment, clinical reasoning and decision-making skills are well known contributors to adverse outcomes in maternity care. Midwifery decision-making models share a common deficit: they are insufficiently detailed to guide reasoning processes for midwives in practice. For these reasons we wanted to explore if midwives actively engaged in clinical reasoning processes within their clinical practice and if so to what extent. The study was conducted using post structural, feminist methodology. to what extent do midwives engage in clinical reasoning processes when making decisions in the second stage labour? twenty-six practising midwives were interviewed. Feminist interpretive analysis was conducted by two researchers guided by the steps of a model of clinical reasoning process. Six narratives were excluded from analysis because they did not sufficiently address the research question. The midwives narratives were prepared via data reduction. A theoretically informed analysis and interpretation was conducted. using a feminist, interpretive approach we created a model of midwifery clinical reasoning grounded in the literature and consistent with the data. Thirteen of the 20 participant narratives demonstrate analytical clinical reasoning abilities but only nine completed the process and implemented the decision. Seven midwives used non-analytical decision-making without adequately checking against assessment data. over half of the participants demonstrated the ability to use clinical reasoning skills. Less than half of the midwives demonstrated clinical reasoning as their way of making decisions. The new model of Midwifery Clinical Reasoning includes 'intuition' as a valued way of knowing. Using intuition, however, should not replace clinical reasoning which promotes through decision-making can be made transparent and be consensually validated. Copyright © 2015 Elsevier Ltd. All rights reserved.

Regulator Loss Functions and Hierarchical Modeling for Safety Decision Making.

PubMed

Hatfield, Laura A; Baugh, Christine M; Azzone, Vanessa; Normand, Sharon-Lise T

2017-07-01

Regulators must act to protect the public when evidence indicates safety problems with medical devices. This requires complex tradeoffs among risks and benefits, which conventional safety surveillance methods do not incorporate. To combine explicit regulator loss functions with statistical evidence on medical device safety signals to improve decision making. In the Hospital Cost and Utilization Project National Inpatient Sample, we select pediatric inpatient admissions and identify adverse medical device events (AMDEs). We fit hierarchical Bayesian models to the annual hospital-level AMDE rates, accounting for patient and hospital characteristics. These models produce expected AMDE rates (a safety target), against which we compare the observed rates in a test year to compute a safety signal. We specify a set of loss functions that quantify the costs and benefits of each action as a function of the safety signal. We integrate the loss functions over the posterior distribution of the safety signal to obtain the posterior (Bayes) risk; the preferred action has the smallest Bayes risk. Using simulation and an analysis of AMDE data, we compare our minimum-risk decisions to a conventional Z score approach for classifying safety signals. The 2 rules produced different actions for nearly half of hospitals (45%). In the simulation, decisions that minimize Bayes risk outperform Z score-based decisions, even when the loss functions or hierarchical models are misspecified. Our method is sensitive to the choice of loss functions; eliciting quantitative inputs to the loss functions from regulators is challenging. A decision-theoretic approach to acting on safety signals is potentially promising but requires careful specification of loss functions in consultation with subject matter experts.

Towards a neuro-computational account of prism adaptation.

PubMed

Petitet, Pierre; O'Reilly, Jill X; O'Shea, Jacinta

2017-12-14

Prism adaptation has a long history as an experimental paradigm used to investigate the functional and neural processes that underlie sensorimotor control. In the neuropsychology literature, prism adaptation behaviour is typically explained by reference to a traditional cognitive psychology framework that distinguishes putative functions, such as 'strategic control' versus 'spatial realignment'. This theoretical framework lacks conceptual clarity, quantitative precision and explanatory power. Here, we advocate for an alternative computational framework that offers several advantages: 1) an algorithmic explanatory account of the computations and operations that drive behaviour; 2) expressed in quantitative mathematical terms; 3) embedded within a principled theoretical framework (Bayesian decision theory, state-space modelling); 4) that offers a means to generate and test quantitative behavioural predictions. This computational framework offers a route towards mechanistic neurocognitive explanations of prism adaptation behaviour. Thus it constitutes a conceptual advance compared to the traditional theoretical framework. In this paper, we illustrate how Bayesian decision theory and state-space models offer principled explanations for a range of behavioural phenomena in the field of prism adaptation (e.g. visual capture, magnitude of visual versus proprioceptive realignment, spontaneous recovery and dynamics of adaptation memory). We argue that this explanatory framework can advance understanding of the functional and neural mechanisms that implement prism adaptation behaviour, by enabling quantitative tests of hypotheses that go beyond merely descriptive mapping claims that 'brain area X is (somehow) involved in psychological process Y'. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

A conceptual review of decision making in social dilemmas: applying a logic of appropriateness.

PubMed

Weber, J Mark; Kopelman, Shirli; Messick, David M

2004-01-01

Despite decades of experimental social dilemma research, "theoretical integration has proven elusive" (Smithson & Foddy, 1999, p. 14). To advance a theory of decision making in social dilemmas, this article provides a conceptual review of the literature that applies a "logic of appropriateness" (March, 1994) framework. The appropriateness framework suggests that people making decisions ask themselves (explicitly or implicitly), "What does a person like me do in a situation like this? " This question identifies 3 significant factors: recognition and classification of the kind of situation encountered, the identity of the individual making the decision, and the application of rules or heuristics in guiding behavioral choice. In contrast with dominant rational choice models, the appropriateness framework proposed accommodates the inherently social nature of social dilemmas, and the role of rule and heuristic based processing. Implications for the interpretation of past findings and the direction of future research are discussed.

Cortical topography of intracortical inhibition influences the speed of decision making.

PubMed

Wilimzig, Claudia; Ragert, Patrick; Dinse, Hubert R

2012-02-21

The neocortex contains orderly topographic maps; however, their functional role remains controversial. Theoretical studies have suggested a role in minimizing computational costs, whereas empirical studies have focused on spatial localization. Using a tactile multiple-choice reaction time (RT) task before and after the induction of perceptual learning through repetitive sensory stimulation, we extend the framework of cortical topographies by demonstrating that the topographic arrangement of intracortical inhibition contributes to the speed of human perceptual decision-making processes. RTs differ among fingers, displaying an inverted U-shaped function. Simulations using neural fields show the inverted U-shaped RT distribution as an emergent consequence of lateral inhibition. Weakening inhibition through learning shortens RTs, which is modeled through topographically reorganized inhibition. Whereas changes in decision making are often regarded as an outcome of higher cortical areas, our data show that the spatial layout of interaction processes within representational maps contributes to selection and decision-making processes.

Cortical topography of intracortical inhibition influences the speed of decision making

PubMed Central

Wilimzig, Claudia; Ragert, Patrick; Dinse, Hubert R.

2012-01-01

The neocortex contains orderly topographic maps; however, their functional role remains controversial. Theoretical studies have suggested a role in minimizing computational costs, whereas empirical studies have focused on spatial localization. Using a tactile multiple-choice reaction time (RT) task before and after the induction of perceptual learning through repetitive sensory stimulation, we extend the framework of cortical topographies by demonstrating that the topographic arrangement of intracortical inhibition contributes to the speed of human perceptual decision-making processes. RTs differ among fingers, displaying an inverted U-shaped function. Simulations using neural fields show the inverted U-shaped RT distribution as an emergent consequence of lateral inhibition. Weakening inhibition through learning shortens RTs, which is modeled through topographically reorganized inhibition. Whereas changes in decision making are often regarded as an outcome of higher cortical areas, our data show that the spatial layout of interaction processes within representational maps contributes to selection and decision-making processes. PMID:22315409

Local Choices: Rationality and the Contextuality of Decision-Making

PubMed Central

Vlaev, Ivo

2018-01-01

Rational explanation is ubiquitous in psychology and social sciences, ranging from rational analysis, expectancy-value theories, ideal observer models, mental logic to probabilistic frameworks, rational choice theory, and informal “folk psychological” explanation. However, rational explanation appears to be challenged by apparently systematic irrationality observed in psychological experiments, especially in the field of judgement and decision-making (JDM). Here, it is proposed that the experimental results require not that rational explanation should be rejected, but that rational explanation is local, i.e., within a context. Thus, rational models need to be supplemented with a theory of contextual shifts. We review evidence in JDM that patterns of choices are often consistent within contexts, but unstable between contexts. We also demonstrate that for a limited, though reasonably broad, class of decision-making domains, recent theoretical models can be viewed as providing theories of contextual shifts. It is argued that one particular significant source of global inconsistency arises from a cognitive inability to represent absolute magnitudes, whether for perceptual variables, utilities, payoffs, or probabilities. This overall argument provides a fresh perspective on the scope and limits of human rationality. PMID:29301289

Local Choices: Rationality and the Contextuality of Decision-Making.

PubMed

Vlaev, Ivo

2018-01-02

Rational explanation is ubiquitous in psychology and social sciences, ranging from rational analysis, expectancy-value theories, ideal observer models, mental logic to probabilistic frameworks, rational choice theory, and informal "folk psychological" explanation. However, rational explanation appears to be challenged by apparently systematic irrationality observed in psychological experiments, especially in the field of judgement and decision-making (JDM). Here, it is proposed that the experimental results require not that rational explanation should be rejected, but that rational explanation is local , i.e., within a context. Thus, rational models need to be supplemented with a theory of contextual shifts. We review evidence in JDM that patterns of choices are often consistent within contexts, but unstable between contexts. We also demonstrate that for a limited, though reasonably broad, class of decision-making domains, recent theoretical models can be viewed as providing theories of contextual shifts. It is argued that one particular significant source of global inconsistency arises from a cognitive inability to represent absolute magnitudes, whether for perceptual variables, utilities, payoffs, or probabilities. This overall argument provides a fresh perspective on the scope and limits of human rationality.

A three-way approach for protein function classification

PubMed Central

2017-01-01

The knowledge of protein functions plays an essential role in understanding biological cells and has a significant impact on human life in areas such as personalized medicine, better crops and improved therapeutic interventions. Due to expense and inherent difficulty of biological experiments, intelligent methods are generally relied upon for automatic assignment of functions to proteins. The technological advancements in the field of biology are improving our understanding of biological processes and are regularly resulting in new features and characteristics that better describe the role of proteins. It is inevitable to neglect and overlook these anticipated features in designing more effective classification techniques. A key issue in this context, that is not being sufficiently addressed, is how to build effective classification models and approaches for protein function prediction by incorporating and taking advantage from the ever evolving biological information. In this article, we propose a three-way decision making approach which provides provisions for seeking and incorporating future information. We considered probabilistic rough sets based models such as Game-Theoretic Rough Sets (GTRS) and Information-Theoretic Rough Sets (ITRS) for inducing three-way decisions. An architecture of protein functions classification with probabilistic rough sets based three-way decisions is proposed and explained. Experiments are carried out on Saccharomyces cerevisiae species dataset obtained from Uniprot database with the corresponding functional classes extracted from the Gene Ontology (GO) database. The results indicate that as the level of biological information increases, the number of deferred cases are reduced while maintaining similar level of accuracy. PMID:28234929

Bayesian randomized clinical trials: From fixed to adaptive design.

PubMed

Yin, Guosheng; Lam, Chi Kin; Shi, Haolun

2017-08-01

Randomized controlled studies are the gold standard for phase III clinical trials. Using α-spending functions to control the overall type I error rate, group sequential methods are well established and have been dominating phase III studies. Bayesian randomized design, on the other hand, can be viewed as a complement instead of competitive approach to the frequentist methods. For the fixed Bayesian design, the hypothesis testing can be cast in the posterior probability or Bayes factor framework, which has a direct link to the frequentist type I error rate. Bayesian group sequential design relies upon Bayesian decision-theoretic approaches based on backward induction, which is often computationally intensive. Compared with the frequentist approaches, Bayesian methods have several advantages. The posterior predictive probability serves as a useful and convenient tool for trial monitoring, and can be updated at any time as the data accrue during the trial. The Bayesian decision-theoretic framework possesses a direct link to the decision making in the practical setting, and can be modeled more realistically to reflect the actual cost-benefit analysis during the drug development process. Other merits include the possibility of hierarchical modeling and the use of informative priors, which would lead to a more comprehensive utilization of information from both historical and longitudinal data. From fixed to adaptive design, we focus on Bayesian randomized controlled clinical trials and make extensive comparisons with frequentist counterparts through numerical studies. Copyright © 2017 Elsevier Inc. All rights reserved.

Anger as a moderator of safer sex motivation among low-income urban women.

PubMed

Schroder, Kerstin E E; Carey, Michael P

2005-10-01

Theoretical models suggest that both HIV knowledge and HIV risk perception inform rational decision making and, thus, predict safer sex motivation and behavior. However, the amount of variance explained by knowledge and risk perception is typically small. In this cross-sectional study, we investigated whether the predictive power of HIV knowledge and HIV risk perception on safer sex motivation is affected by trait anger. We hypothesized that anger may disrupt rational decision making, distorting the effects of both HIV knowledge and risk perception on safer sex intentions. Data from 232 low-income, urban women at risk for HIV infection were used to test a path model with past sexual risk behavior, HIV knowledge, and HIV risk perception as predictors of safer sex intentions. Moderator effects of anger on safer sex intentions were tested by simultaneous group comparisons between high-anger and low-anger women (median split). The theoretically expected "rational pattern" was found among low-anger women only, including (a) a positive effect of knowledge on safer sex intentions, and (b) buffer (inhibitor) effects of HIV knowledge and HIV risk perception on the negative path leading from past risk behavior to safer sex intentions. Among high-anger women, an "irrational pattern" emerged, with no effects of HIV knowledge and negative effects of both past risk behavior and HIV risk perception on safer sex intentions. In sum, the results suggest that rational knowledge- and risk-based decisions regarding safer sex may be limited to low-anger women.

Anger as a Moderator of Safer Sex Motivation among Low Income Urban Women

PubMed Central

Carey, Michael P.

2005-01-01

Theoretical models suggest that both HIV knowledge and HIV risk perception inform rational decision-making and, thus, predict safer sex motivation and behavior. However, the amount of variance explained by knowledge and risk perception is typically small. In this cross-sectional study, we investigated whether the predictive power of HIV knowledge and HIV risk perception on safer sex motivation is affected by trait anger. We hypothesized that anger may disrupt rational-decision making, distorting the effects of both HIV knowledge and risk perception on safer sex intentions. Data from 232 low-income, urban women at risk for HIV infection were used to test a path model with past sexual risk behavior, HIV knowledge, and HIV risk perception as predictors of safer sex intentions. Moderator effects of anger on safer sex intentions were tested by simultaneous group comparisons between high-anger and low-anger women (median-split). The theoretically expected “rational pattern” was found among low-anger women only, including (a) a positive effect of knowledge on safer sex intentions, and (b) buffer (inhibitor) effects of HIV knowledge and HIV risk perception on the negative path leading from past risk behavior to safer sex intentions. Among high-anger women, an “irrational pattern” emerged, with no effects of HIV knowledge and negative effects of both past risk behavior and HIV risk perception on safer sex intentions. In sum, the results suggest that rational knowledge and risk-based decisions regarding safer sex may be limited to low-anger women. PMID:16247592

A three-way approach for protein function classification.

PubMed

Ur Rehman, Hafeez; Azam, Nouman; Yao, JingTao; Benso, Alfredo

2017-01-01

The knowledge of protein functions plays an essential role in understanding biological cells and has a significant impact on human life in areas such as personalized medicine, better crops and improved therapeutic interventions. Due to expense and inherent difficulty of biological experiments, intelligent methods are generally relied upon for automatic assignment of functions to proteins. The technological advancements in the field of biology are improving our understanding of biological processes and are regularly resulting in new features and characteristics that better describe the role of proteins. It is inevitable to neglect and overlook these anticipated features in designing more effective classification techniques. A key issue in this context, that is not being sufficiently addressed, is how to build effective classification models and approaches for protein function prediction by incorporating and taking advantage from the ever evolving biological information. In this article, we propose a three-way decision making approach which provides provisions for seeking and incorporating future information. We considered probabilistic rough sets based models such as Game-Theoretic Rough Sets (GTRS) and Information-Theoretic Rough Sets (ITRS) for inducing three-way decisions. An architecture of protein functions classification with probabilistic rough sets based three-way decisions is proposed and explained. Experiments are carried out on Saccharomyces cerevisiae species dataset obtained from Uniprot database with the corresponding functional classes extracted from the Gene Ontology (GO) database. The results indicate that as the level of biological information increases, the number of deferred cases are reduced while maintaining similar level of accuracy.

An asymmetric parental investment conflict with continuous strategy sets.

PubMed

Yaniv, Osnat

2005-12-07

In the parental investment conflict each of the sexes decides how much to invest in its brood, where its decision influences both sexes' fitness. In nature, each species is usually characterized by a common parental care pattern, male-only care, female-only care or biparental care. A possible way for understanding the factors that have led each species to adopt its unique parental care pattern is to analyse a male's and a female's decision process using a game-theoretical model. This paper suggests a two-stage game-theoretical model with two types of players, male and female. During the game each parent makes three decisions. The interval between the beginning of the game, i.e. after mating and having offspring, and the moment a parent starts to care for them is a random variable. Thus, in the first stage a parent chooses the cumulative probability distribution of this interval, and its amount of parental care. In the second stage the other parent chooses its probability for cooperation. It is assumed that as long as parental care is not provided the offspring are at risk, and that parental caring accrues a different cost for each sex. We compute the Evolutionary Stable Strategies (ESS) under payoff-relevant asymmetry, and show that uniparental and biparental care are possible ESS. We also characterize cases where the sex having the lower cost "forces" the sex having the higher cost to care and vice versa.

Discrete Choice Experiments: A Guide to Model Specification, Estimation and Software.

PubMed

Lancsar, Emily; Fiebig, Denzil G; Hole, Arne Risa

2017-07-01

We provide a user guide on the analysis of data (including best-worst and best-best data) generated from discrete-choice experiments (DCEs), comprising a theoretical review of the main choice models followed by practical advice on estimation and post-estimation. We also provide a review of standard software. In providing this guide, we endeavour to not only provide guidance on choice modelling but to do so in a way that provides a 'way in' for researchers to the practicalities of data analysis. We argue that choice of modelling approach depends on the research questions, study design and constraints in terms of quality/quantity of data and that decisions made in relation to analysis of choice data are often interdependent rather than sequential. Given the core theory and estimation of choice models is common across settings, we expect the theoretical and practical content of this paper to be useful to researchers not only within but also beyond health economics.

Are groups more rational than individuals? A review of interactive decision making in groups.

PubMed

Kugler, Tamar; Kausel, Edgar E; Kocher, Martin G

2012-07-01

Many decisions are interactive; the outcome of one party depends not only on its decisions or on acts of nature but also on the decisions of others. Standard game theory assumes that individuals are rational, self-interested decision makers-that is, decision makers are selfish, perfect calculators, and flawless executors of their strategies. A myriad of studies shows that these assumptions are problematic, at least when examining decisions made by individuals. In this article, we review the literature of the last 25 years on decision making by groups. Researchers have compared the strategic behavior of groups and individuals in many games: prisoner's dilemma, dictator, ultimatum, trust, centipede and principal-agent games, among others. Our review suggests that results are quite consistent in revealing that group decisions are closer to the game-theoretic assumption of rationality than individual decisions. Given that many real-world decisions are made by groups, it is possible to argue that standard game theory is a better descriptive model than previously believed by experimental researchers. We conclude by discussing future research avenues in this area. WIREs Cogn Sci 2012, 3:471-482. doi: 10.1002/wcs.1184 For further resources related to this article, please visit the WIREs website. Copyright © 2012 John Wiley & Sons, Ltd.

Striatal activation reflects urgency in perceptual decision making.

PubMed

van Maanen, Leendert; Fontanesi, Laura; Hawkins, Guy E; Forstmann, Birte U

2016-10-01

Deciding between multiple courses of action often entails an increasing need to do something as time passes - a sense of urgency. This notion of urgency is not incorporated in standard theories of speeded decision making that assume information is accumulated until a critical fixed threshold is reached. Yet, it is hypothesized in novel theoretical models of decision making. In two experiments, we investigated the behavioral and neural evidence for an "urgency signal" in human perceptual decision making. Experiment 1 found that as the duration of the decision making process increased, participants made a choice based on less evidence for the selected option. Experiment 2 replicated this finding, and additionally found that variability in this effect across participants covaried with activation in the striatum. We conclude that individual differences in susceptibility to urgency are reflected by striatal activation. By dynamically updating a response threshold, the striatum is involved in signaling urgency in humans. Copyright © 2016 Elsevier Inc. All rights reserved.

Calculating the social cost of illegal drugs: a theoretical approach.

PubMed

Diomidous, Marianna; Zimeras, Stelios; Mechili, Aggelos

2013-01-01

The use of illegal drugs generates a wide range of social harms depending on various ways, according to the policy definition of the problem. The challenge is the way to model the impact of illegal drugs use during a long time period considering the factors that affects the process. Based on these models, estimation could be measured and prediction could be achieved. The illegal drugs use might affect the economic and social structure of the public system leading to direct and effective decisions to overcome the problematic. For that reason, calculation of social cost related to the use of illegal could be introduced over time (t) as a proposed social measure to define the variability of social indicator on society. In this work, a theoretical approach for the calculation of social cost of illegal drugs is proposed and models over time are defined.

Delivering patient decision aids on the Internet: definitions, theories, current evidence, and emerging research areas

PubMed Central

2013-01-01

Background In 2005, the International Patient Decision Aids Standards Collaboration identified twelve quality dimensions to guide assessment of patient decision aids. One dimension—the delivery of patient decision aids on the Internet—is relevant when the Internet is used to provide some or all components of a patient decision aid. Building on the original background chapter, this paper provides an updated definition for this dimension, outlines a theoretical rationale, describes current evidence, and discusses emerging research areas. Methods An international, multidisciplinary panel of authors examined the relevant theoretical literature and empirical evidence through 2012. Results The updated definition distinguishes Internet-delivery of patient decision aids from online health information and clinical practice guidelines. Theories in cognitive psychology, decision psychology, communication, and education support the value of Internet features for providing interactive information and deliberative support. Dissemination and implementation theories support Internet-delivery for providing the right information (rapidly updated), to the right person (tailored), at the right time (the appropriate point in the decision making process). Additional efforts are needed to integrate the theoretical rationale and empirical evidence from health technology perspectives, such as consumer health informatics, user experience design, and human-computer interaction. Despite Internet usage ranging from 74% to 85% in developed countries and 80% of users searching for health information, it is unknown how many individuals specifically seek patient decision aids on the Internet. Among the 86 randomized controlled trials in the 2011 Cochrane Collaboration’s review of patient decision aids, only four studies focused on Internet-delivery. Given the limited number of published studies, this paper particularly focused on identifying gaps in the empirical evidence base and identifying emerging areas of research. Conclusions As of 2012, the updated theoretical rationale and emerging evidence suggest potential benefits to delivering patient decision aids on the Internet. However, additional research is needed to identify best practices and quality metrics for Internet-based development, evaluation, and dissemination, particularly in the areas of interactivity, multimedia components, socially-generated information, and implementation strategies. PMID:24625064

A Novel Methodology for Charging Station Deployment

NASA Astrophysics Data System (ADS)

Sun, Zhonghao; Zhao, Yunwei; He, Yueying; Li, Mingzhe

2018-02-01

Lack of charging stations has been a main obstacle to the promotion of electric vehicles. This paper studies deploying charging stations in traffic networks considering grid constraints to balance the charging demand and grid stability. First, we propose a statistical model for charging demand. Then we combine the charging demand model with power grid constraints and give the formulation of the charging station deployment problem. Finally, we propose a theoretical solution for the problem by transforming it to a Markov Decision Process.

A framework for designing and analyzing binary decision-making strategies in cellular systems†

PubMed Central

Porter, Joshua R.; Andrews, Burton W.; Iglesias, Pablo A.

2015-01-01

Cells make many binary (all-or-nothing) decisions based on noisy signals gathered from their environment and processed through noisy decision-making pathways. Reducing the effect of noise to improve the fidelity of decision-making comes at the expense of increased complexity, creating a tradeoff between performance and metabolic cost. We present a framework based on rate distortion theory, a branch of information theory, to quantify this tradeoff and design binary decision-making strategies that balance low cost and accuracy in optimal ways. With this framework, we show that several observed behaviors of binary decision-making systems, including random strategies, hysteresis, and irreversibility, are optimal in an information-theoretic sense for various situations. This framework can also be used to quantify the goals around which a decision-making system is optimized and to evaluate the optimality of cellular decision-making systems by a fundamental information-theoretic criterion. As proof of concept, we use the framework to quantify the goals of the externally triggered apoptosis pathway. PMID:22370552

Testing Ecological Theories of Offender Spatial Decision Making Using a Discrete Choice Model.

PubMed

Johnson, Shane D; Summers, Lucia

2015-04-01

Research demonstrates that crime is spatially concentrated. However, most research relies on information about where crimes occur, without reference to where offenders reside. This study examines how the characteristics of neighborhoods and their proximity to offender home locations affect offender spatial decision making. Using a discrete choice model and data for detected incidents of theft from vehicles (TFV) , we test predictions from two theoretical perspectives-crime pattern and social disorganization theories. We demonstrate that offenders favor areas that are low in social cohesion and closer to their home, or other age-related activity nodes. For adult offenders, choices also appear to be influenced by how accessible a neighborhood is via the street network. The implications for criminological theory and crime prevention are discussed.

Testing Ecological Theories of Offender Spatial Decision Making Using a Discrete Choice Model

PubMed Central

Summers, Lucia

2015-01-01

Research demonstrates that crime is spatially concentrated. However, most research relies on information about where crimes occur, without reference to where offenders reside. This study examines how the characteristics of neighborhoods and their proximity to offender home locations affect offender spatial decision making. Using a discrete choice model and data for detected incidents of theft from vehicles (TFV), we test predictions from two theoretical perspectives—crime pattern and social disorganization theories. We demonstrate that offenders favor areas that are low in social cohesion and closer to their home, or other age-related activity nodes. For adult offenders, choices also appear to be influenced by how accessible a neighborhood is via the street network. The implications for criminological theory and crime prevention are discussed. PMID:25866412

Vehicular headways on signalized intersections: theory, models, and reality

NASA Astrophysics Data System (ADS)

Krbálek, Milan; Šleis, Jiří

2015-01-01

We discuss statistical properties of vehicular headways measured on signalized crossroads. On the basis of mathematical approaches, we formulate theoretical and empirically inspired criteria for the acceptability of theoretical headway distributions. Sequentially, the multifarious families of statistical distributions (commonly used to fit real-road headway statistics) are confronted with these criteria, and with original empirical time clearances gauged among neighboring vehicles leaving signal-controlled crossroads after a green signal appears. Using three different numerical schemes, we demonstrate that an arrangement of vehicles on an intersection is a consequence of the general stochastic nature of queueing systems, rather than a consequence of traffic rules, driver estimation processes, or decision-making procedures.

The Role of Dysfunctional Myths in a Decision-Making Process under Bounded Rationality: A Complex Dynamical Systems Perspective.

PubMed

Stamovlasis, Dimitrios; Vaiopoulou, Julie

2017-07-01

The present study examines the factors influencing a decision-making process, with specific focus on the role of dysfunctional myths (DM). DM are thoughts or beliefs that are rather irrational, however influential to people's decisions. In this paper a decision-making process regarding the career choice of university students majoring in natural sciences and education (N=496) is examined by analyzing survey data taken via Career Decision Making Difficulties Questionnaire (CDDQ). The difficulty of making the choice and the certainty about one's decision were the state variables, while the independent variables were factors related to the lack of information or knowledge needed, which actually reflect a bounded rationality. Cusp catastrophe analysis, based on both least squares and maximum likelihood procedures, showed that the nonlinear models predicting the two state variables were superior to linear alternatives. Factors related to lack of knowledge about the steps involved in the process of career decision-making, lack of information about the various occupations, lack of information about self and lack of motivation acted as asymmetry, while dysfunctional myths acted as bifurcation factor for both state variables. The catastrophe model, grounded in empirical data, revealed a unique role for DM and a better interpretation within the context of complexity and the notion of bounded rationality. The analysis opens the nonlinear dynamical systems (NDS) perspective in studying decision-making processes. Theoretical and practical implications are discussed.

Evaluation of nursing practice: process and critique.

PubMed

Braunstein, M S

1998-01-01

This article describes the difficulties in conducting clinical trials to evaluate nursing practice models. Suggestions are offered for strengthening the process. A clinical trial of a nursing practice model based on a synthesis of Aristotelian theory with Rogers' science is described. The rationale for decisions regarding the research procedures used in presented. Methodological limitations of the study design and the specifications of the practice model are examined. It is concluded that clear specification of theoretical relationships within a practice model and clear identification of key intervening variables will enable researchers to better connect the treatment with the outcome.

Theory of choice in bandit, information sampling and foraging tasks.

PubMed

Averbeck, Bruno B

2015-03-01

Decision making has been studied with a wide array of tasks. Here we examine the theoretical structure of bandit, information sampling and foraging tasks. These tasks move beyond tasks where the choice in the current trial does not affect future expected rewards. We have modeled these tasks using Markov decision processes (MDPs). MDPs provide a general framework for modeling tasks in which decisions affect the information on which future choices will be made. Under the assumption that agents are maximizing expected rewards, MDPs provide normative solutions. We find that all three classes of tasks pose choices among actions which trade-off immediate and future expected rewards. The tasks drive these trade-offs in unique ways, however. For bandit and information sampling tasks, increasing uncertainty or the time horizon shifts value to actions that pay-off in the future. Correspondingly, decreasing uncertainty increases the relative value of actions that pay-off immediately. For foraging tasks the time-horizon plays the dominant role, as choices do not affect future uncertainty in these tasks.

The Effect of Expected Value on Attraction Effect Preference Reversals

PubMed Central

Warren, Paul A.; El‐Deredy, Wael; Howes, Andrew

2016-01-01

Abstract The attraction effect shows that adding a third alternative to a choice set can alter preference between the original two options. For over 30 years, this simple demonstration of context dependence has been taken as strong evidence against a class of parsimonious value‐maximising models that evaluate alternatives independently from one another. Significantly, however, in previous demonstrations of the attraction effect alternatives are approximately equally valuable, so there was little consequence to the decision maker irrespective of which alternative was selected. Here we vary the difference in expected value between alternatives and provide the first demonstration that, although extinguished with large differences, this theoretically important effect persists when choice between alternatives has a consequence. We use this result to clarify the implications of the attraction effect, arguing that although it robustly violates the assumptions of value‐maximising models, it does not eliminate the possibility that human decision making is optimal. © 2016 The Authors Journal of Behavioral Decision Making Published by John Wiley & Sons Ltd. PMID:29081595

The Effect of Expected Value on Attraction Effect Preference Reversals.

PubMed

Farmer, George D; Warren, Paul A; El-Deredy, Wael; Howes, Andrew

2017-10-01

The attraction effect shows that adding a third alternative to a choice set can alter preference between the original two options. For over 30 years, this simple demonstration of context dependence has been taken as strong evidence against a class of parsimonious value-maximising models that evaluate alternatives independently from one another. Significantly, however, in previous demonstrations of the attraction effect alternatives are approximately equally valuable, so there was little consequence to the decision maker irrespective of which alternative was selected. Here we vary the difference in expected value between alternatives and provide the first demonstration that, although extinguished with large differences, this theoretically important effect persists when choice between alternatives has a consequence. We use this result to clarify the implications of the attraction effect, arguing that although it robustly violates the assumptions of value-maximising models, it does not eliminate the possibility that human decision making is optimal. © 2016 The Authors Journal of Behavioral Decision Making Published by John Wiley & Sons Ltd.

A critical narrative analysis of shared decision-making in acute inpatient mental health care.

PubMed

Stacey, Gemma; Felton, Anne; Morgan, Alastair; Stickley, Theo; Willis, Martin; Diamond, Bob; Houghton, Philip; Johnson, Beverley; Dumenya, John

2016-01-01

Shared decision-making (SDM) is a high priority in healthcare policy and is complementary to the recovery philosophy in mental health care. This agenda has been operationalised within the Values-Based Practice (VBP) framework, which offers a theoretical and practical model to promote democratic interprofessional approaches to decision-making. However, these are limited by a lack of recognition of the implications of power implicit within the mental health system. This study considers issues of power within the context of decision-making and examines to what extent decisions about patients' care on acute in-patient wards are perceived to be shared. Focus groups were conducted with 46 mental health professionals, service users, and carers. The data were analysed using the framework of critical narrative analysis (CNA). The findings of the study suggested each group constructed different identity positions, which placed them as inside or outside of the decision-making process. This reflected their view of themselves as best placed to influence a decision on behalf of the service user. In conclusion, the discourse of VBP and SDM needs to take account of how differentials of power and the positioning of speakers affect the context in which decisions take place.

The reciprocal dynamic model of career decision ambiguity tolerance with career indecision: A longitudinal three-wave investigation.

PubMed

Xu, Hui; Tracey, Terence J G

2017-10-01

The current study investigated the dynamic interplay of career decision ambiguity tolerance and career indecision over 3 assessment times in a sample of college students (n = 583). While the previous research has repeatedly shown an association of career decision ambiguity tolerance with career indecision, the direction of this association has not been adequately assessed with longitudinal investigation. It was hypothesized in this study that there is a reciprocal pattern of career decision ambiguity tolerance leading to subsequent career indecision and career indecision leading to subsequent career decision ambiguity tolerance. Using a cross-lagged panel design, this study found support for the reciprocal pattern that aversion to ambiguity led to increased negative affect and choice anxiety in career decision making, while negative affect and choice anxiety led to increased aversion to ambiguity. Additionally, this study revealed that aversion led to decreased readiness for career decision making and readiness for career decision making led to increased interests in new information. The key findings were discussed with respect to the theoretical and clinical implications for career counseling along with limitations and suggestions for future research. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

An exploration of clinical decision making in mental health triage.

PubMed

Sands, Natisha

2009-08-01

Mental health (MH) triage is a specialist area of clinical nursing practice that involves complex decision making. The discussion in this article draws on the findings of a Ph.D. study that involved a statewide investigation of the scope of MH triage nursing practice in Victoria, Australia. Although the original Ph.D. study investigated a number of core practices in MH triage, the focus of the discussion in this article is specifically on the findings related to clinical decision making in MH triage, which have not previously been published. The study employed an exploratory descriptive research design that used mixed data collection methods including a survey questionnaire (n = 139) and semistructured interviews (n = 21). The study findings related to decision making revealed a lack of empirically tested evidence-based decision-making frameworks currently in use to support MH triage nursing practice. MH triage clinicians in Australia rely heavily on clinical experience to underpin decision making and have little of knowledge of theoretical models for practice, such as methodologies for rating urgency. A key recommendation arising from the study is the need to develop evidence-based decision-making frameworks such as clinical guidelines to inform and support MH triage clinical decision making.

Transforming clinical practice guidelines and clinical pathways into fast-and-frugal decision trees to improve clinical care strategies.

PubMed

Djulbegovic, Benjamin; Hozo, Iztok; Dale, William

2018-02-27

Contemporary delivery of health care is inappropriate in many ways, largely due to suboptimal Q5 decision-making. A typical approach to improve practitioners' decision-making is to develop evidence-based clinical practice guidelines (CPG) by guidelines panels, who are instructed to use their judgments to derive practice recommendations. However, mechanisms for the formulation of guideline judgments remains a "black-box" operation-a process with defined inputs and outputs but without sufficient knowledge of its internal workings. Increased explicitness and transparency in the process can be achieved by implementing CPG as clinical pathways (CPs) (also known as clinical algorithms or flow-charts). However, clinical recommendations thus derived are typically ad hoc and developed by experts in a theory-free environment. As any recommendation can be right (true positive or negative), or wrong (false positive or negative), the lack of theoretical structure precludes the quantitative assessment of the management strategies recommended by CPGs/CPs. To realize the full potential of CPGs/CPs, they need to be placed on more solid theoretical grounds. We believe this potential can be best realized by converting CPGs/CPs within the heuristic theory of decision-making, often implemented as fast-and-frugal (FFT) decision trees. This is possible because FFT heuristic strategy of decision-making can be linked to signal detection theory, evidence accumulation theory, and a threshold model of decision-making, which, in turn, allows quantitative analysis of the accuracy of clinical management strategies. Fast-and-frugal provides a simple and transparent, yet solid and robust, methodological framework connecting decision science to clinical care, a sorely needed missing link between CPGs/CPs and patient outcomes. We therefore advocate that all guidelines panels express their recommendations as CPs, which in turn should be converted into FFTs to guide clinical care. © 2018 John Wiley & Sons, Ltd.

A sequential sampling account of response bias and speed-accuracy tradeoffs in a conflict detection task.

PubMed

Vuckovic, Anita; Kwantes, Peter J; Humphreys, Michael; Neal, Andrew

2014-03-01

Signal Detection Theory (SDT; Green & Swets, 1966) is a popular tool for understanding decision making. However, it does not account for the time taken to make a decision, nor why response bias might change over time. Sequential sampling models provide a way of accounting for speed-accuracy trade-offs and response bias shifts. In this study, we test the validity of a sequential sampling model of conflict detection in a simulated air traffic control task by assessing whether two of its key parameters respond to experimental manipulations in a theoretically consistent way. Through experimental instructions, we manipulated participants' response bias and the relative speed or accuracy of their responses. The sequential sampling model was able to replicate the trends in the conflict responses as well as response time across all conditions. Consistent with our predictions, manipulating response bias was associated primarily with changes in the model's Criterion parameter, whereas manipulating speed-accuracy instructions was associated with changes in the Threshold parameter. The success of the model in replicating the human data suggests we can use the parameters of the model to gain an insight into the underlying response bias and speed-accuracy preferences common to dynamic decision-making tasks. © 2013 American Psychological Association

Proposing a Formalised Model for Mindful Information Systems Offshoring

NASA Astrophysics Data System (ADS)

Costello, Gabriel J.; Coughlan, Chris; Donnellan, Brian; Gadatsch, Andreas

The central thesis of this chapter is that mathematical economics can provide a novel approach to the examination of offshoring business decisions and provide an impetus for future research in the area. A growing body of research indicates that projected cost savings from IT offshoring projects are not being met. Furthermore, evidence suggests that decision-making processes have been more emotional than rational, and that many offshoring arrangements have been rushed into without adequate analysis of the true costs involved. Building on the concept of mindfulness and mindlessness introduced to the IS literature by Swanson and Ramiller, a cost equation is developed using “deductive reasoning rather than inductive study” in the tradition of mathematical economics. The model endeavours to capture a wide range of both the quantitative and qualitative parameters. Although the economic model is illustrated against the background of a European scenario, the theoretical framework is generic and applicable to organisations in any global location.

The role of political affiliation in employment decisions: A model and research agenda.

PubMed

Roth, Philip L; Goldberg, Caren B; Thatcher, Jason B

2017-09-01

Organizational researchers have studied how individuals identify with groups and organizations and how this affiliation influences behavior for decades (e.g., Tajfel, 1982). Interestingly, investigation into political affiliation and political affiliation similarity in the organizational sciences is extremely rare. This is striking, given the deep political divides that exist between groups of individuals described in the political science literature. We draw from theories based on similarity, organizational identification, and person-environment fit, as well as theoretical notions related to individuating information, to develop a model, the political affiliation model (PAM), which describes the implications of political affiliation and political similarity for employment decisions. We set forth a number of propositions based on PAM, to spur future research in the organizational sciences for a timely topic which has received little attention. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Coaching and guidance with patient decision aids: A review of theoretical and empirical evidence

PubMed Central

2013-01-01

Background Coaching and guidance are structured approaches that can be used within or alongside patient decision aids (PtDAs) to facilitate the process of decision making. Coaching is provided by an individual, and guidance is embedded within the decision support materials. The purpose of this paper is to: a) present updated definitions of the concepts “coaching” and “guidance”; b) present an updated summary of current theoretical and empirical insights into the roles played by coaching/guidance in the context of PtDAs; and c) highlight emerging issues and research opportunities in this aspect of PtDA design. Methods We identified literature published since 2003 on shared decision making theoretical frameworks inclusive of coaching or guidance. We also conducted a sub-analysis of randomized controlled trials included in the 2011 Cochrane Collaboration Review of PtDAs with search results updated to December 2010. The sub-analysis was conducted on the characteristics of coaching and/or guidance included in any trial of PtDAs and trials that allowed the impact of coaching and/or guidance with PtDA to be compared to another intervention or usual care. Results Theoretical evidence continues to justify the use of coaching and/or guidance to better support patients in the process of thinking about a decision and in communicating their values/preferences with others. In 98 randomized controlled trials of PtDAs, 11 trials (11.2%) included coaching and 63 trials (64.3%) provided guidance. Compared to usual care, coaching provided alongside a PtDA improved knowledge and decreased mean costs. The impact on some other outcomes (e.g., participation in decision making, satisfaction, option chosen) was more variable, with some trials showing positive effects and other trials reporting no differences. For values-choice agreement, decisional conflict, adherence, and anxiety there were no differences between groups. None of these outcomes were worse when patients were exposed to decision coaching alongside a PtDA. No trials evaluated the effect of guidance provided within PtDAs. Conclusions Theoretical evidence continues to justify the use of coaching and/or guidance to better support patients to participate in decision making. However, there are few randomized controlled trials that have compared the effectiveness of coaching used alongside PtDAs to PtDAs without coaching, and no trials have compared the PtDAs with guidance to those without guidance. PMID:24624995

Location Dynamics of Foreign Banking in Shanghai from 1990 TO 2009

NASA Astrophysics Data System (ADS)

Feng, Xiaobing; Kim, Beom Jun

This study examined the determinants of foreign bank location decisions in Shanghai markets over the period of 1990 to 2009. The growing foreign presence in Shanghai was found to be related to two different policy regimes: Pudong development area foreign enterprise clustering period after China opened Pudong, and "deposit-loan-match principle" implementing period after China joined WTO. The current location pattern was found to be correlated to deposit potential in each district. It is evident that the foreign bank location decisions were influenced by those of domestic banks while the reverse did not hold. These findings provide a valuable platform for theoretical modeling and further analysis.

The database search problem: a question of rational decision making.

PubMed

Gittelson, S; Biedermann, A; Bozza, S; Taroni, F

2012-10-10

This paper applies probability and decision theory in the graphical interface of an influence diagram to study the formal requirements of rationality which justify the individualization of a person found through a database search. The decision-theoretic part of the analysis studies the parameters that a rational decision maker would use to individualize the selected person. The modeling part (in the form of an influence diagram) clarifies the relationships between this decision and the ingredients that make up the database search problem, i.e., the results of the database search and the different pairs of propositions describing whether an individual is at the source of the crime stain. These analyses evaluate the desirability associated with the decision of 'individualizing' (and 'not individualizing'). They point out that this decision is a function of (i) the probability that the individual in question is, in fact, at the source of the crime stain (i.e., the state of nature), and (ii) the decision maker's preferences among the possible consequences of the decision (i.e., the decision maker's loss function). We discuss the relevance and argumentative implications of these insights with respect to recent comments in specialized literature, which suggest points of view that are opposed to the results of our study. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

A conversation-based process tracing method for use with naturalistic decisions: an evaluation study.

PubMed

Williamson, J; Ranyard, R; Cuthbert, L

2000-05-01

This study is an evaluation of a process tracing method developed for naturalistic decisions, in this case a consumer choice task. The method is based on Huber et al.'s (1997) Active Information Search (AIS) technique, but develops it by providing spoken rather than written answers to respondents' questions, and by including think aloud instructions. The technique is used within a conversation-based situation, rather than the respondent thinking aloud 'into an empty space', as is conventionally the case in think aloud techniques. The method results in a concurrent verbal protocol as respondents make their decisions, and a retrospective report in the form of a post-decision summary. The method was found to be virtually non-reactive in relation to think aloud, although the variable of Preliminary Attribute Elicitation showed some evidence of reactivity. This was a methodological evaluation, and as such the data reported are essentially descriptive. Nevertheless, the data obtained indicate that the method is capable of producing information about decision processes which could have theoretical importance in terms of evaluating models of decision-making.

Testing take-the-best in new and changing environments.

PubMed

Lee, Michael D; Blanco, Gabrielle; Bo, Nikole

2017-08-01

Take-the-best is a decision-making strategy that chooses between alternatives, by searching the cues representing the alternatives in order of cue validity, and choosing the alternative with the first discriminating cue. Theoretical support for take-the-best comes from the "fast and frugal" approach to modeling cognition, which assumes decision-making strategies need to be fast to cope with a competitive world, and be simple to be robust to uncertainty and environmental change. We contribute to the empirical evaluation of take-the-best in two ways. First, we generate four new environments-involving bridge lengths, hamburger prices, theme park attendances, and US university rankings-supplementing the relatively limited number of naturally cue-based environments previously considered. We find that take-the-best is as accurate as rival decision strategies that use all of the available cues. Secondly, we develop 19 new data sets characterizing the change in cities and their populations in four countries. We find that take-the-best maintains its accuracy and limited search as the environments change, even if cue validities learned in one environment are used to make decisions in another. Once again, we find that take-the-best is as accurate as rival strategies that use all of the cues. We conclude that these new evaluations support the theoretical claims of the accuracy, frugality, and robustness for take-the-best, and that the new data sets provide a valuable resource for the more general study of the relationship between effective decision-making strategies and the environments in which they operate.

Traces of Civil Economy in Early Modern Franciscan Economic Thought: An Education Essay for Civilisation and Integral Human Development

ERIC Educational Resources Information Center

Zamagni, Stefano

2017-01-01

After a brief historical reconstruction of the emergence of the market economy as a model of social order in Europe, dating back to the eleventh century--the century of the commercial revolution--the paper focuses on the decisive contribution of the Franciscan school of thought to furnish the theoretical infrastructure of the new mode of…

Technology assessment: What should it be?

NASA Technical Reports Server (NTRS)

Black, G.

1975-01-01

The necessity of uncovering unsuspected relationships in proposed actions is discussed along with the feasibility of using decision theoretical models to cope with problems of uncertainty in the future-oriented analyses characteristic of assessments. It is shown that it is necessary to integrate the results of technology assessment with other program analyses and that results of technology assessment be supplied in a form that permits integration with other information.

Factors Associated with Physicians' Choice of a Career in Research: A Retrospective Report 15 Years after Medical School Graduation

ERIC Educational Resources Information Center

Krupat, Edward; Camargo, Carlos A., Jr.; Strewler, Gordon J.; Espinola, Janice A.; Fleenor, Thomas J., Jr.; Dienstag, Jules L.

2017-01-01

Relatively little is known regarding factors associated with the choice of a research career among practicing physicians, and most investigations of this issue have been conducted in the absence of a theoretical/conceptual model. Therefore we designed a survey to identify the determinants of decisions to pursue a biomedical research career based…

Applying a family systems lens to proxy decision making in clinical practice and research.

PubMed

Rolland, John S; Emanuel, Linda L; Torke, Alexia M

2017-03-01

When patients are incapacitated and face serious illness, family members must make medical decisions for the patient. Medical decision sciences give only modest attention to the relationships among patients and their family members, including impact that these relationships have on the decision-making process. A review of the literature reveals little effort to systematically apply a theoretical framework to the role of family interactions in proxy decision making. A family systems perspective can provide a useful lens through which to understand the dynamics of proxy decision making. This article considers the mutual impact of family systems on the processes and outcomes of proxy decision making. The article first reviews medical decision science's evolution and focus on proxy decision making and then reviews a family systems approach, giving particular attention to Rolland's Family Systems Illness Model. A case illustrates how clinical practice and how research would benefit from bringing family systems thinking to proxy decisions. We recommend including a family systems approach in medical decision science research and clinical practices around proxy decisions making. We propose that clinical decisions could be less conflicted and less emotionally troubling for families and clinicians if family systems approaches were included. This perspective opens new directions for research and novel approaches to clinical care. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Merging Theoretical Models and Therapy Approaches in the Context of Internet Gaming Disorder: A Personal Perspective.

PubMed

Young, Kimberly S; Brand, Matthias

2017-01-01

Although, it is not yet officially recognized as a clinical entity which is diagnosable, Internet Gaming Disorder (IGD) has been included in section III for further study in the DSM-5 by the American Psychiatric Association (APA, 2013). This is important because there is increasing evidence that people of all ages, in particular teens and young adults, are facing very real and sometimes very severe consequences in daily life resulting from an addictive use of online games. This article summarizes general aspects of IGD including diagnostic criteria and arguments for the classification as an addictive disorder including evidence from neurobiological studies. Based on previous theoretical considerations and empirical findings, this paper examines the use of one recently proposed model, the Interaction of Person-Affect-Cognition-Execution (I-PACE) model, for inspiring future research and for developing new treatment protocols for IGD. The I-PACE model is a theoretical framework that explains symptoms of Internet addiction by looking at interactions between predisposing factors, moderators, and mediators in combination with reduced executive functioning and diminished decision making. Finally, the paper discusses how current treatment protocols focusing on Cognitive-Behavioral Therapy for Internet addiction (CBT-IA) fit with the processes hypothesized in the I-PACE model.

Merging Theoretical Models and Therapy Approaches in the Context of Internet Gaming Disorder: A Personal Perspective

PubMed Central

Young, Kimberly S.; Brand, Matthias

2017-01-01

Although, it is not yet officially recognized as a clinical entity which is diagnosable, Internet Gaming Disorder (IGD) has been included in section III for further study in the DSM-5 by the American Psychiatric Association (APA, 2013). This is important because there is increasing evidence that people of all ages, in particular teens and young adults, are facing very real and sometimes very severe consequences in daily life resulting from an addictive use of online games. This article summarizes general aspects of IGD including diagnostic criteria and arguments for the classification as an addictive disorder including evidence from neurobiological studies. Based on previous theoretical considerations and empirical findings, this paper examines the use of one recently proposed model, the Interaction of Person-Affect-Cognition-Execution (I-PACE) model, for inspiring future research and for developing new treatment protocols for IGD. The I-PACE model is a theoretical framework that explains symptoms of Internet addiction by looking at interactions between predisposing factors, moderators, and mediators in combination with reduced executive functioning and diminished decision making. Finally, the paper discusses how current treatment protocols focusing on Cognitive-Behavioral Therapy for Internet addiction (CBT-IA) fit with the processes hypothesized in the I-PACE model. PMID:29104555

Defending Against Advanced Persistent Threats Using Game-Theory

PubMed Central

König, Sandra; Schauer, Stefan

2017-01-01

Advanced persistent threats (APT) combine a variety of different attack forms ranging from social engineering to technical exploits. The diversity and usual stealthiness of APT turns them into a central problem of contemporary practical system security, since information on attacks, the current system status or the attacker’s incentives is often vague, uncertain and in many cases even unavailable. Game theory is a natural approach to model the conflict between the attacker and the defender, and this work investigates a generalized class of matrix games as a risk mitigation tool for an advanced persistent threat (APT) defense. Unlike standard game and decision theory, our model is tailored to capture and handle the full uncertainty that is immanent to APTs, such as disagreement among qualitative expert risk assessments, unknown adversarial incentives and uncertainty about the current system state (in terms of how deeply the attacker may have penetrated into the system’s protective shells already). Practically, game-theoretic APT models can be derived straightforwardly from topological vulnerability analysis, together with risk assessments as they are done in common risk management standards like the ISO 31000 family. Theoretically, these models come with different properties than classical game theoretic models, whose technical solution presented in this work may be of independent interest. PMID:28045922

Naturalistic Decision Making in Power Grid Operations: Implications for Dispatcher Training and Usability Testing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Greitzer, Frank L.; Podmore, Robin

2008-11-17

The focus of the present study is on improved training approaches to accelerate learning and improved methods for analyzing effectiveness of tools within a high-fidelity power grid simulated environment. A theory-based model has been developed to document and understand the mental processes that an expert power system operator uses when making critical decisions. The theoretical foundation for the method is based on the concepts of situation awareness, the methods of cognitive task analysis, and the naturalistic decision making (NDM) approach of Recognition Primed Decision Making. The method has been systematically explored and refined as part of a capability demonstration ofmore » a high-fidelity real-time power system simulator under normal and emergency conditions. To examine NDM processes, we analyzed transcripts of operator-to-operator conversations during the simulated scenario to reveal and assess NDM-based performance criteria. The results of the analysis indicate that the proposed framework can be used constructively to map or assess the Situation Awareness Level of the operators at each point in the scenario. We can also identify the mental models and mental simulations that the operators employ at different points in the scenario. This report documents the method, describes elements of the model, and provides appendices that document the simulation scenario and the associated mental models used by operators in the scenario.« less

Modelling ADHD: A review of ADHD theories through their predictions for computational models of decision-making and reinforcement learning.

PubMed

Ziegler, Sigurd; Pedersen, Mads L; Mowinckel, Athanasia M; Biele, Guido

2016-12-01

Attention deficit hyperactivity disorder (ADHD) is characterized by altered decision-making (DM) and reinforcement learning (RL), for which competing theories propose alternative explanations. Computational modelling contributes to understanding DM and RL by integrating behavioural and neurobiological findings, and could elucidate pathogenic mechanisms behind ADHD. This review of neurobiological theories of ADHD describes predictions for the effect of ADHD on DM and RL as described by the drift-diffusion model of DM (DDM) and a basic RL model. Empirical studies employing these models are also reviewed. While theories often agree on how ADHD should be reflected in model parameters, each theory implies a unique combination of predictions. Empirical studies agree with the theories' assumptions of a lowered DDM drift rate in ADHD, while findings are less conclusive for boundary separation. The few studies employing RL models support a lower choice sensitivity in ADHD, but not an altered learning rate. The discussion outlines research areas for further theoretical refinement in the ADHD field. Copyright © 2016 Elsevier Ltd. All rights reserved.

Distributive justice and infertility treatment in Canada.

PubMed

Nisker, Jeff

2008-05-01

An exploration of distributive justice in Canadian infertility treatment requires the integration of ethical, clinical, and economic principles. In 1971, American philosopher John Rawls proposed a theoretical model for fair decision-making in which "rational" and "self-interested" citizens are behind a "veil of ignorance" with respect to both their own position and the position of other decision-makers. Rawls proposed that these self-interested decision-makers, fearing that they are among the least advantaged persons who could be affected by the decision, will agree only upon rules that encode equality of opportunity and that bestow the greatest benefit on the least advantaged citizens. Regarding health policy decision-making, Rawls' model is best illustrated by Canadian philosopher Warren Bourgeois in his panel of "volunteers." These rational and self-interested volunteers receive an amnestic drug that renders them unaware of their health, social, and financial position, but they know that they are representative of diverse spheres of citizens whose well-being will be affected by their decision. After describing fair decision-making, Bourgeois considers the lack of a distributive justice imperative in Canada's Assisted Human Reproduction Act, in contrast to legislation in European nations and Australia, summarizes the economic and clinical considerations that must be provided to the decision-makers behind the "veil of ignorance" for fair decisions to occur, and considers altruism in relation to equality of access. He concludes by noting that among countries with legislation governing assisted reproduction Canada is alone in having legislation that is void of distributive justice in providing access to clinically appropriate infertility care.

Toward theoretical understanding of the fertility preservation decision-making process: Examining information processing among young women with cancer

PubMed Central

Hershberger, Patricia E.; Finnegan, Lorna; Altfeld, Susan; Lake, Sara; Hirshfeld-Cytron, Jennifer

2014-01-01

Background Young women with cancer now face the complex decision about whether to undergo fertility preservation. Yet little is known about how these women process information involved in making this decision. Objective The purpose of this paper is to expand theoretical understanding of the decision-making process by examining aspects of information processing among young women diagnosed with cancer. Methods Using a grounded theory approach, 27 women with cancer participated in individual, semi-structured interviews. Data were coded and analyzed using constant-comparison techniques that were guided by five dimensions within the Contemplate phase of the decision-making process framework. Results In the first dimension, young women acquired information primarily from clinicians and Internet sources. Experiential information, often obtained from peers, occurred in the second dimension. Preferences and values were constructed in the third dimension as women acquired factual, moral, and ethical information. Women desired tailored, personalized information that was specific to their situation in the fourth dimension; however, women struggled with communicating these needs to clinicians. In the fifth dimension, women offered detailed descriptions of clinician behaviors that enhance or impede decisional debriefing. Conclusion Better understanding of theoretical underpinnings surrounding women’s information processes can facilitate decision support and improve clinical care. PMID:24552086

Decision-Making Under Risk: Integrating Perspectives From Biology, Economics, and Psychology.

PubMed

Mishra, Sandeep

2014-08-01

Decision-making under risk has been variably characterized and examined in many different disciplines. However, interdisciplinary integration has not been forthcoming. Classic theories of decision-making have not been amply revised in light of greater empirical data on actual patterns of decision-making behavior. Furthermore, the meta-theoretical framework of evolution by natural selection has been largely ignored in theories of decision-making under risk in the human behavioral sciences. In this review, I critically examine four of the most influential theories of decision-making from economics, psychology, and biology: expected utility theory, prospect theory, risk-sensitivity theory, and heuristic approaches. I focus especially on risk-sensitivity theory, which offers a framework for understanding decision-making under risk that explicitly involves evolutionary considerations. I also review robust empirical evidence for individual differences and environmental/situational factors that predict actual risky decision-making that any general theory must account for. Finally, I offer steps toward integrating various theoretical perspectives and empirical findings on risky decision-making. © 2014 by the Society for Personality and Social Psychology, Inc.

Why, When, and How to Take into Account the Uncertainty Involved in Career Decisions.

ERIC Educational Resources Information Center

Gati, Itamar

1990-01-01

Theoretically analyzes career decisions under uncertainty, when career decision maker ranks options rather than choosing best one. Found that how decisions were framed affected ranking of options and quality of decisions. Analysis showed that the rank order of options in optimal ranking always coincided with the rank order of the options by their…

Cognitive control predicts use of model-based reinforcement learning.

PubMed

Otto, A Ross; Skatova, Anya; Madlon-Kay, Seth; Daw, Nathaniel D

2015-02-01

Accounts of decision-making and its neural substrates have long posited the operation of separate, competing valuation systems in the control of choice behavior. Recent theoretical and experimental work suggest that this classic distinction between behaviorally and neurally dissociable systems for habitual and goal-directed (or more generally, automatic and controlled) choice may arise from two computational strategies for reinforcement learning (RL), called model-free and model-based RL, but the cognitive or computational processes by which one system may dominate over the other in the control of behavior is a matter of ongoing investigation. To elucidate this question, we leverage the theoretical framework of cognitive control, demonstrating that individual differences in utilization of goal-related contextual information--in the service of overcoming habitual, stimulus-driven responses--in established cognitive control paradigms predict model-based behavior in a separate, sequential choice task. The behavioral correspondence between cognitive control and model-based RL compellingly suggests that a common set of processes may underpin the two behaviors. In particular, computational mechanisms originally proposed to underlie controlled behavior may be applicable to understanding the interactions between model-based and model-free choice behavior.

Computational mate choice: theory and empirical evidence.

PubMed

Castellano, Sergio; Cadeddu, Giorgia; Cermelli, Paolo

2012-06-01

The present review is based on the thesis that mate choice results from information-processing mechanisms governed by computational rules and that, to understand how females choose their mates, we should identify which are the sources of information and how they are used to make decisions. We describe mate choice as a three-step computational process and for each step we present theories and review empirical evidence. The first step is a perceptual process. It describes the acquisition of evidence, that is, how females use multiple cues and signals to assign an attractiveness value to prospective mates (the preference function hypothesis). The second step is a decisional process. It describes the construction of the decision variable (DV), which integrates evidence (private information by direct assessment), priors (public information), and value (perceived utility) of prospective mates into a quantity that is used by a decision rule (DR) to produce a choice. We make the assumption that females are optimal Bayesian decision makers and we derive a formal model of DV that can explain the effects of preference functions, mate copying, social context, and females' state and condition on the patterns of mate choice. The third step of mating decision is a deliberative process that depends on the DRs. We identify two main categories of DRs (absolute and comparative rules), and review the normative models of mate sampling tactics associated to them. We highlight the limits of the normative approach and present a class of computational models (sequential-sampling models) that are based on the assumption that DVs accumulate noisy evidence over time until a decision threshold is reached. These models force us to rethink the dichotomy between comparative and absolute decision rules, between discrimination and recognition, and even between rational and irrational choice. Since they have a robust biological basis, we think they may represent a useful theoretical tool for behavioural ecologist interested in integrating proximate and ultimate causes of mate choice. Copyright © 2012 Elsevier B.V. All rights reserved.

On the use of Bayesian decision theory for issuing natural hazard warnings

NASA Astrophysics Data System (ADS)

Economou, T.; Stephenson, D. B.; Rougier, J. C.; Neal, R. A.; Mylne, K. R.

2016-10-01

Warnings for natural hazards improve societal resilience and are a good example of decision-making under uncertainty. A warning system is only useful if well defined and thus understood by stakeholders. However, most operational warning systems are heuristic: not formally or transparently defined. Bayesian decision theory provides a framework for issuing warnings under uncertainty but has not been fully exploited. Here, a decision theoretic framework is proposed for hazard warnings. The framework allows any number of warning levels and future states of nature, and a mathematical model for constructing the necessary loss functions for both generic and specific end-users is described. The approach is illustrated using one-day ahead warnings of daily severe precipitation over the UK, and compared to the current decision tool used by the UK Met Office. A probability model is proposed to predict precipitation, given ensemble forecast information, and loss functions are constructed for two generic stakeholders: an end-user and a forecaster. Results show that the Met Office tool issues fewer high-level warnings compared with our system for the generic end-user, suggesting the former may not be suitable for risk averse end-users. In addition, raw ensemble forecasts are shown to be unreliable and result in higher losses from warnings.

On the use of Bayesian decision theory for issuing natural hazard warnings.

PubMed

Economou, T; Stephenson, D B; Rougier, J C; Neal, R A; Mylne, K R

2016-10-01

Warnings for natural hazards improve societal resilience and are a good example of decision-making under uncertainty. A warning system is only useful if well defined and thus understood by stakeholders. However, most operational warning systems are heuristic: not formally or transparently defined. Bayesian decision theory provides a framework for issuing warnings under uncertainty but has not been fully exploited. Here, a decision theoretic framework is proposed for hazard warnings. The framework allows any number of warning levels and future states of nature, and a mathematical model for constructing the necessary loss functions for both generic and specific end-users is described. The approach is illustrated using one-day ahead warnings of daily severe precipitation over the UK, and compared to the current decision tool used by the UK Met Office. A probability model is proposed to predict precipitation, given ensemble forecast information, and loss functions are constructed for two generic stakeholders: an end-user and a forecaster. Results show that the Met Office tool issues fewer high-level warnings compared with our system for the generic end-user, suggesting the former may not be suitable for risk averse end-users. In addition, raw ensemble forecasts are shown to be unreliable and result in higher losses from warnings.

On the use of Bayesian decision theory for issuing natural hazard warnings

PubMed Central

Stephenson, D. B.; Rougier, J. C.; Neal, R. A.; Mylne, K. R.

2016-01-01

Warnings for natural hazards improve societal resilience and are a good example of decision-making under uncertainty. A warning system is only useful if well defined and thus understood by stakeholders. However, most operational warning systems are heuristic: not formally or transparently defined. Bayesian decision theory provides a framework for issuing warnings under uncertainty but has not been fully exploited. Here, a decision theoretic framework is proposed for hazard warnings. The framework allows any number of warning levels and future states of nature, and a mathematical model for constructing the necessary loss functions for both generic and specific end-users is described. The approach is illustrated using one-day ahead warnings of daily severe precipitation over the UK, and compared to the current decision tool used by the UK Met Office. A probability model is proposed to predict precipitation, given ensemble forecast information, and loss functions are constructed for two generic stakeholders: an end-user and a forecaster. Results show that the Met Office tool issues fewer high-level warnings compared with our system for the generic end-user, suggesting the former may not be suitable for risk averse end-users. In addition, raw ensemble forecasts are shown to be unreliable and result in higher losses from warnings. PMID:27843399

Using a modified technology acceptance model to evaluate healthcare professionals' adoption of a new telemonitoring system.

PubMed

Gagnon, Marie Pierre; Orruño, Estibalitz; Asua, José; Abdeljelil, Anis Ben; Emparanza, José

2012-01-01

To examine the factors that could influence the decision of healthcare professionals to use a telemonitoring system. A questionnaire, based on the Technology Acceptance Model (TAM), was developed. A panel of experts in technology assessment evaluated the face and content validity of the instrument. Two hundred and thirty-four questionnaires were distributed among nurses and doctors of the cardiology, pulmonology, and internal medicine departments of a tertiary hospital. Cronbach alpha was calculated to measure the internal consistency of the questionnaire items. Construct validity was evaluated using interitem correlation analysis. Logistic regression analysis was performed to test the theoretical model. Adjusted odds ratios (ORs) and their 95% confidence intervals (CIs) were computed. A response rate of 39.7% was achieved. With the exception of one theoretical construct (Habit) that corresponds to behaviors that become automatized, Cronbach alpha values were acceptably high for the remaining constructs. Theoretical variables were well correlated with each other and with the dependent variable. The original TAM was good at predicting telemonitoring usage intention, Perceived Usefulness being the only significant predictor (OR: 5.28, 95% CI: 2.12-13.11). The model was still significant and more powerful when the other theoretical variables were added. However, the only significant predictor in the modified model was Facilitators (OR: 4.96, 95% CI: 1.59-15.55). The TAM is a good predictive model of healthcare professionals' intention to use telemonitoring. However, the perception of facilitators is the most important variable to consider for increasing doctors' and nurses' intention to use the new technology.

A Monte-Carlo game theoretic approach for Multi-Criteria Decision Making under uncertainty

NASA Astrophysics Data System (ADS)

Madani, Kaveh; Lund, Jay R.

2011-05-01

Game theory provides a useful framework for studying Multi-Criteria Decision Making problems. This paper suggests modeling Multi-Criteria Decision Making problems as strategic games and solving them using non-cooperative game theory concepts. The suggested method can be used to prescribe non-dominated solutions and also can be used as a method to predict the outcome of a decision making problem. Non-cooperative stability definitions for solving the games allow consideration of non-cooperative behaviors, often neglected by other methods which assume perfect cooperation among decision makers. To deal with the uncertainty in input variables a Monte-Carlo Game Theory (MCGT) approach is suggested which maps the stochastic problem into many deterministic strategic games. The games are solved using non-cooperative stability definitions and the results include possible effects of uncertainty in input variables on outcomes. The method can handle multi-criteria multi-decision-maker problems with uncertainty. The suggested method does not require criteria weighting, developing a compound decision objective, and accurate quantitative (cardinal) information as it simplifies the decision analysis by solving problems based on qualitative (ordinal) information, reducing the computational burden substantially. The MCGT method is applied to analyze California's Sacramento-San Joaquin Delta problem. The suggested method provides insights, identifies non-dominated alternatives, and predicts likely decision outcomes.

A game-theoretical approach to multimedia social networks security.

PubMed

Liu, Enqiang; Liu, Zengliang; Shao, Fei; Zhang, Zhiyong

2014-01-01

The contents access and sharing in multimedia social networks (MSNs) mainly rely on access control models and mechanisms. Simple adoptions of security policies in the traditional access control model cannot effectively establish a trust relationship among parties. This paper proposed a novel two-party trust architecture (TPTA) to apply in a generic MSN scenario. According to the architecture, security policies are adopted through game-theoretic analyses and decisions. Based on formalized utilities of security policies and security rules, the choice of security policies in content access is described as a game between the content provider and the content requester. By the game method for the combination of security policies utility and its influences on each party's benefits, the Nash equilibrium is achieved, that is, an optimal and stable combination of security policies, to establish and enhance trust among stakeholders.

A Game-Theoretical Approach to Multimedia Social Networks Security

PubMed Central

Liu, Enqiang; Liu, Zengliang; Shao, Fei; Zhang, Zhiyong

2014-01-01

The contents access and sharing in multimedia social networks (MSNs) mainly rely on access control models and mechanisms. Simple adoptions of security policies in the traditional access control model cannot effectively establish a trust relationship among parties. This paper proposed a novel two-party trust architecture (TPTA) to apply in a generic MSN scenario. According to the architecture, security policies are adopted through game-theoretic analyses and decisions. Based on formalized utilities of security policies and security rules, the choice of security policies in content access is described as a game between the content provider and the content requester. By the game method for the combination of security policies utility and its influences on each party's benefits, the Nash equilibrium is achieved, that is, an optimal and stable combination of security policies, to establish and enhance trust among stakeholders. PMID:24977226

The Regulatory Capacity of Bivalent Genes—A Theoretical Approach

PubMed Central

Thalheim, Torsten; Herberg, Maria; Loeffler, Markus; Galle, Joerg

2017-01-01

Bivalent genes are frequently associated with developmental and lineage specification processes. Resolving their bivalency enables fast changes in their expression, which potentially can trigger cell fate decisions. Here, we provide a theoretical model of bivalency that allows for predictions on the occurrence, stability and regulatory capacity of this prominent modification state. We suggest that bivalency enables balanced gene expression heterogeneity that constitutes a prerequisite of robust lineage priming in somatic stem cells. Moreover, we demonstrate that interactions between the histone and DNA methylation machineries together with the proliferation activity control the stability of the bivalent state and can turn it into an unmodified state. We suggest that deregulation of these interactions underlies cell transformation processes as associated with acute myeloid leukemia (AML) and provide a model of AML blast formation following deregulation of the Ten-eleven Translocation (TET) pathway. PMID:28513551

Probability Weighting Functions Derived from Hyperbolic Time Discounting: Psychophysical Models and Their Individual Level Testing.

PubMed

Takemura, Kazuhisa; Murakami, Hajime

2016-01-01

A probability weighting function (w(p)) is considered to be a nonlinear function of probability (p) in behavioral decision theory. This study proposes a psychophysical model of probability weighting functions derived from a hyperbolic time discounting model and a geometric distribution. The aim of the study is to show probability weighting functions from the point of view of waiting time for a decision maker. Since the expected value of a geometrically distributed random variable X is 1/p, we formulized the probability weighting function of the expected value model for hyperbolic time discounting as w(p) = (1 - k log p)(-1). Moreover, the probability weighting function is derived from Loewenstein and Prelec's (1992) generalized hyperbolic time discounting model. The latter model is proved to be equivalent to the hyperbolic-logarithmic weighting function considered by Prelec (1998) and Luce (2001). In this study, we derive a model from the generalized hyperbolic time discounting model assuming Fechner's (1860) psychophysical law of time and a geometric distribution of trials. In addition, we develop median models of hyperbolic time discounting and generalized hyperbolic time discounting. To illustrate the fitness of each model, a psychological experiment was conducted to assess the probability weighting and value functions at the level of the individual participant. The participants were 50 university students. The results of individual analysis indicated that the expected value model of generalized hyperbolic discounting fitted better than previous probability weighting decision-making models. The theoretical implications of this finding are discussed.

A Conceptual Model for Increasing Use of Electronic Medical Records by Primary Care Physicians Through End-User Support.

PubMed

Randhawa, Gurprit K

2017-01-01

A conceptual model for exploring the relationship between end-user support (EUS) and electronic medical record (EMR) use by primary care physicians is presented. The model was developed following a review of conceptual and theoretical frameworks related to technology adoption/use and EUS. The model includes (a) one core construct (facilitating conditions), (b) four antecedents and one postcedent of facilitating conditions, and (c) four moderators. EMR use behaviour is the key outcome of the model. The proposed conceptual model should be tested. The model may be used to inform planning and decision-making for EMR implementations to increase EMR use for benefits realization.

Dynamic remapping decisions in multi-phase parallel computations

NASA Technical Reports Server (NTRS)

Nicol, D. M.; Reynolds, P. F., Jr.

1986-01-01

The effectiveness of any given mapping of workload to processors in a parallel system is dependent on the stochastic behavior of the workload. Program behavior is often characterized by a sequence of phases, with phase changes occurring unpredictably. During a phase, the behavior is fairly stable, but may become quite different during the next phase. Thus a workload assignment generated for one phase may hinder performance during the next phase. We consider the problem of deciding whether to remap a paralled computation in the face of uncertainty in remapping's utility. Fundamentally, it is necessary to balance the expected remapping performance gain against the delay cost of remapping. This paper treats this problem formally by constructing a probabilistic model of a computation with at most two phases. We use stochastic dynamic programming to show that the remapping decision policy which minimizes the expected running time of the computation has an extremely simple structure: the optimal decision at any step is followed by comparing the probability of remapping gain against a threshold. This theoretical result stresses the importance of detecting a phase change, and assessing the possibility of gain from remapping. We also empirically study the sensitivity of optimal performance to imprecise decision threshold. Under a wide range of model parameter values, we find nearly optimal performance if remapping is chosen simply when the gain probability is high. These results strongly suggest that except in extreme cases, the remapping decision problem is essentially that of dynamically determining whether gain can be achieved by remapping after a phase change; precise quantification of the decision model parameters is not necessary.

Misery is not Miserly: Sad and Self-Focused Individuals Spend More

PubMed Central

Cryder, Cynthia E.; Lerner, Jennifer S; Gross, James J.; Dahl, Ronald E.

2014-01-01

Misery is not miserly: sadness increases the amount of money decision makers give up to acquire a commodity (Lerner, Small, & Loewenstein, 2004). The present research investigated when and why the “misery-is-not-miserly” effect occurs. Drawing on William James’s (1890) concept of the material self, we tested a model specifying relationships among sadness, self-focus, and the amount of money decision makers spend. Consistent with our Jamesian hypothesis, results revealed that self-focus both moderates and mediates the effect of sadness on spending. Results were consistent across males and females. Because the study used real commodities and real money, results hold implications for everyday decisions. They also hold implications for theoretical development. Economic theories of spending may benefit from incorporating psychological theories – specifically theories of emotion and the self. PMID:18578840

Optimal behaviour can violate the principle of regularity.

PubMed

Trimmer, Pete C

2013-07-22

Understanding decisions is a fundamental aim of behavioural ecology, psychology and economics. The regularity axiom of utility theory holds that a preference between options should be maintained when other options are made available. Empirical studies have shown that animals violate regularity but this has not been understood from a theoretical perspective, such decisions have therefore been labelled as irrational. Here, I use models of state-dependent behaviour to demonstrate that choices can violate regularity even when behavioural strategies are optimal. I also show that the range of conditions over which regularity should be violated can be larger when options do not always persist into the future. Consequently, utility theory--based on axioms, including transitivity, regularity and the independence of irrelevant alternatives--is undermined, because even alternatives that are never chosen by an animal (in its current state) can be relevant to a decision.

Theoretical aspects and modelling of cellular decision making, cell killing and information-processing in photodynamic therapy of cancer.

PubMed

Gkigkitzis, Ioannis

2013-01-01

The aim of this report is to provide a mathematical model of the mechanism for making binary fate decisions about cell death or survival, during and after Photodynamic Therapy (PDT) treatment, and to supply the logical design for this decision mechanism as an application of rate distortion theory to the biochemical processing of information by the physical system of a cell. Based on system biology models of the molecular interactions involved in the PDT processes previously established, and regarding a cellular decision-making system as a noisy communication channel, we use rate distortion theory to design a time dependent Blahut-Arimoto algorithm where the input is a stimulus vector composed of the time dependent concentrations of three PDT related cell death signaling molecules and the output is a cell fate decision. The molecular concentrations are determined by a group of rate equations. The basic steps are: initialize the probability of the cell fate decision, compute the conditional probability distribution that minimizes the mutual information between input and output, compute the cell probability of cell fate decision that minimizes the mutual information and repeat the last two steps until the probabilities converge. Advance to the next discrete time point and repeat the process. Based on the model from communication theory described in this work, and assuming that the activation of the death signal processing occurs when any of the molecular stimulants increases higher than a predefined threshold (50% of the maximum concentrations), for 1800s of treatment, the cell undergoes necrosis within the first 30 minutes with probability range 90.0%-99.99% and in the case of repair/survival, it goes through apoptosis within 3-4 hours with probability range 90.00%-99.00%. Although, there is no experimental validation of the model at this moment, it reproduces some patterns of survival ratios of predicted experimental data. Analytical modeling based on cell death signaling molecules has been shown to be an independent and useful tool for prediction of cell surviving response to PDT. The model can be adjusted to provide important insights for cellular response to other treatments such as hyperthermia, and diseases such as neurodegeneration.

Strategic Decision-Making by Deans in Academic Health Centers: A Framework Analysis

ERIC Educational Resources Information Center

Keeney, Brianne

2012-01-01

This study examines strategic decision-making at the college level in relation to seven theoretical frames. Strategic decisions are those made by top executives, have wide-ranging influence throughout the organization, affect the long-term future of the organization, and are connected to the external environment. The seven decision-making frames…

How High School Students Construct Decision-Making Strategies for Choosing Colleges

ERIC Educational Resources Information Center

Govan, George V.; Patrick, Sondra; Yen, Cherng-Jyn

2006-01-01

This study examined how high school seniors construct decision-making strategies for choosing a college to attend. To comprehend their decision-making strategies, we chose to examine this process through the theoretical lens of bounded rationality, which brings to light the complexity in constructing a college choice decision-making strategy…

Defining the doula's role: fostering relational autonomy.

PubMed

Meadow, Sandra L

2015-12-01

Training organizations as well as academic and popular literature provide ambiguous or ethically contentious characterizations of the role of the birth doula, a non-clinical role assisting women in pregnancy and birth with information and physical and emotional support. Doulas have been criticized for attempting to impose their own agendas on their clients and for interfering with the relationship between women and their medical caregivers. To develop a theoretically grounded model of the birth doula's role to guide constructive practice and refute some training organizations' and doulas' adoption of an active 'advocacy' role with clients that can lead to inappropriate practices. Apply the theoretical framework of relational autonomy to the components of the work that doulas perform with their clients. The conceptual framework of relational autonomy recognizes the social context in which women make choices about their care in pregnancy and birth, instead of assuming that autonomy is exercised in isolation. To support this understanding of autonomy, a relational model emphasizes women's skills development, self-confidence and recognition of the social context for decisions. Highlighting these aspects of exercising autonomy reduces the potential for the doula to seek to influence her client. The doula's role is reframed as one of facilitating patient engagement and shared decision-making. © 2014 John Wiley & Sons Ltd.

Should cell-free DNA testing be used to target antenatal rhesus immune globulin administration?

PubMed

Ma, Kimberly K; Rodriguez, Maria I; Cheng, Yvonne W; Norton, Mary E; Caughey, Aaron B

2016-01-01

To compare the rates of alloimmunization with the use of cell-free DNA (cfDNA) screening to target antenatal rhesus immune globulin (RhIG) prenatally, versus routine administration of RhIG in rhesus D (RhD)-negative pregnant women in a theoretic cohort using a decision-analytic model. A decision-analytic model compared cfDNA testing to routine antenatal RhIG administration. The primary outcome was maternal sensitization to RhD antigen. Sensitivity and specificity of cfDNA testing were assumed to be 99.8% and 95.3%, respectively. Univariate and bivariate sensitivity analyses, Monte Carlo simulation, and threshold analyses were performed. In a cohort of 10,000 RhD-negative women, 22.6 sensitizations would occur with utilization of cfDNA, while 20 sensitizations would occur with routine RhIG. Only when the sensitivity of the cfDNA test reached 100%, the rate of sensitization was equal for both cfDNA and RhIG. Otherwise, routine RhIG minimized the rate of sensitization, especially given RhIG is readily available in the United States. Adoption of cfDNA testing would result in a 13.0% increase in sensitization among RhD-negative women in a theoretical cohort taking into account the ethnic diversity of the United States' population.

Complacency and bias in human use of automation: an attentional integration.

PubMed

Parasuraman, Raja; Manzey, Dietrich H

2010-06-01

Our aim was to review empirical studies of complacency and bias in human interaction with automated and decision support systems and provide an integrated theoretical model for their explanation. Automation-related complacency and automation bias have typically been considered separately and independently. Studies on complacency and automation bias were analyzed with respect to the cognitive processes involved. Automation complacency occurs under conditions of multiple-task load, when manual tasks compete with the automated task for the operator's attention. Automation complacency is found in both naive and expert participants and cannot be overcome with simple practice. Automation bias results in making both omission and commission errors when decision aids are imperfect. Automation bias occurs in both naive and expert participants, cannot be prevented by training or instructions, and can affect decision making in individuals as well as in teams. While automation bias has been conceived of as a special case of decision bias, our analysis suggests that it also depends on attentional processes similar to those involved in automation-related complacency. Complacency and automation bias represent different manifestations of overlapping automation-induced phenomena, with attention playing a central role. An integrated model of complacency and automation bias shows that they result from the dynamic interaction of personal, situational, and automation-related characteristics. The integrated model and attentional synthesis provides a heuristic framework for further research on complacency and automation bias and design options for mitigating such effects in automated and decision support systems.

I-DECIDE: An Online Intervention Drawing on the Psychosocial Readiness Model for Women Experiencing Domestic Violence.

PubMed

Tarzia, Laura; Murray, Elizabeth; Humphreys, Cathy; Glass, Nancy; Taft, Angela; Valpied, Jodie; Hegarty, Kelsey

2016-01-01

Domestic violence (DV) perpetrated by men against women is a pervasive global problem with significant physical and emotional consequences. Although some face-to-face interventions in health care settings have shown promise, there are barriers to disclosure to health care practitioners and women may not be ready to access or accept help, reducing uptake. Similar to the mental health field, interventions from clinical practice can be adapted to be delivered by technology. This article outlines the theoretical and conceptual development of I-DECIDE, an online healthy relationship tool and safety decision aid for women experiencing DV. The article explores the use of the Psychosocial Readiness Model (PRM) as a theoretical framework for the intervention and evaluation. This is a theoretical article drawing on current theory and literature around health care and online interventions for DV. The article argues that the Internet as a method of intervention delivery for DV might overcome many of the barriers present in health care settings. Using the PRM as a framework for an online DV intervention may help women on a pathway to safety and well-being for themselves and their children. This hypothesis will be tested in a randomized, controlled trial in 2015/2016. This article highlights the importance of using a theoretical model in intervention development and evaluation. Copyright © 2016 Jacobs Institute of Women's Health. Published by Elsevier Inc. All rights reserved.

Human Factors of CC-130 Operations. Volume 5: Human Factors in Decision Making

DTIC Science & Technology

1998-02-01

known about human information processing and decision making. Topics for HFDM training come directly from this theoretical framework . The proposed...The proposed training can be distinguished from other approaches with similar goals (either explicit or implicit) by its base within a theoretical ... framework of human information processing. The differences lie less in the content than in the way the material is organized and shaped by theory. The

Punishment in the form of shared cost promotes altruism in the cooperative dilemma games.

PubMed

Zhang, Chunyan; Zhu, Yuying; Chen, Zengqiang; Zhang, Jianlei

2017-05-07

One phenomenon or social institution often observed in multi-agent interactions is the altruistic punishment, i.e. the punishment of unfair behavior by others at a personal cost. Inspired by the works focusing on punishment and the intricate mechanism behind it, we theoretically study the strategy evolution in the framework of two-strategy game models with the punishment on defectors, moreover, the cost of punishing will be evenly shared among the cooperators. Theoretical computations suggest that larger punishment on defectors or smaller punishment cost incurred by cooperators will enhance the fixation of altruistic cooperation in the population. Through the replicate dynamics, the group size of the randomly selected individuals from the sufficiently large population will notably affect the strategy evolution in populations nested within a dilemma. By theoretical modeling the concept of shared cost for punishment from one point of view, our findings underscore the importance of punishment with shared cost as a factor in real-life decisions in an evolutionary game context. Copyright © 2017 Elsevier Ltd. All rights reserved.

Heuristic use of perceptual evidence leads to dissociation between performance and metacognitive sensitivity.

PubMed

Maniscalco, Brian; Peters, Megan A K; Lau, Hakwan

2016-04-01

Zylberberg et al. [Zylberberg, Barttfeld, & Sigman (Frontiers in Integrative Neuroscience, 6; 79, 2012), Frontiers in Integrative Neuroscience 6:79] found that confidence decisions, but not perceptual decisions, are insensitive to evidence against a selected perceptual choice. We present a signal detection theoretic model to formalize this insight, which gave rise to a counter-intuitive empirical prediction: that depending on the observer's perceptual choice, increasing task performance can be associated with decreasing metacognitive sensitivity (i.e., the trial-by-trial correspondence between confidence and accuracy). The model also provides an explanation as to why metacognitive sensitivity tends to be less than optimal in actual subjects. These predictions were confirmed robustly in a psychophysics experiment. In a second experiment we found that, in at least some subjects, the effects were replicated even under performance feedback designed to encourage optimal behavior. However, some subjects did show improvement under feedback, suggesting the tendency to ignore evidence against a selected perceptual choice may be a heuristic adopted by the perceptual decision-making system, rather than reflecting inherent biological limitations. We present a Bayesian modeling framework that explains why this heuristic strategy may be advantageous in real-world contexts.

Lateralization is predicted by reduced coupling from the left to right prefrontal cortex during semantic decisions on written words.

PubMed

Seghier, Mohamed L; Josse, Goulven; Leff, Alexander P; Price, Cathy J

2011-07-01

Over 90% of people activate the left hemisphere more than the right hemisphere for language processing. Here, we show that the degree to which language is left lateralized is inversely related to the degree to which left frontal regions drive activity in homotopic right frontal regions. Lateralization was assessed in 60 subjects using functional magnetic resonance imaging (fMRI) activation for semantic decisions on verbal (written words) and nonverbal (pictures of objects) stimuli. Regional interactions between left and right ventral and dorsal frontal regions were assessed using dynamic causal modeling (DCM), random-effects Bayesian model selection at the family level, and Bayesian model averaging at the connection level. We found that 1) semantic decisions on words and pictures modulated interhemispheric coupling between the left and right dorsal frontal regions, 2) activation was more left lateralized for words than pictures, and 3) for words only, left lateralization was greater when the coupling from the left to right dorsal frontal cortex was reduced. These results have theoretical implications for understanding how left and right hemispheres communicate with one another during the processing of lateralized functions.

A meta-ethnography and theory of parental ethical decision making in the neonatal intensive care unit.

PubMed

Rosenthal, Sara A; Nolan, Marie T

2013-07-01

To synthesize the existing qualitative literature about parent ethical decision making in the neonatal intensive care unit (NICU) and to investigate the potential impact of culture on parents' decision making experiences. PubMed, CINAHL plus, and PsychInfo using the search terms parental decision making, culture, race, decision making, and parental decisions. Qualitative research studies investigating decision making for infants in the NICU from the parents' perspective were included. Studies involving older pediatric populations were excluded. Ten primary qualitative research articles were included. The primary author read all manuscripts and tabulated themes related to parents' ethical decision making. Study findings were synthesized using meta-ethnography involving translating concepts of separate studies into one another, exploring contradictions, and organizing these concepts into new theories. Key themes included parent involvement in decision making, parental role, necessity of good information, need for communication, desire for hope and compassion conveyed by providers, decision making satisfaction, and trust in caregiving team. A preliminary theoretical framework of ethical parent decision making was modeled based on the proposed relationships between the themes. Parent preferences for their involvement in decision making, their perceptions of communication with providers, and their relationships with providers are all important factors in the experience of making decisions for their infants. Needs of parents were the same regardless the ethnic or racial diversity of study participants. © 2013 AWHONN, the Association of Women's Health, Obstetric and Neonatal Nurses.

An Astrosociological Perspective on Space-Capable vs. Spacefaring Societies

NASA Astrophysics Data System (ADS)

Pass, J.

As with any academic field, astrosociology allows for an endless number of competing theoretical models and hypotheses. One possible theoretical model is presented here that starts with the premise that even the most advanced societies today are extremely far from achieving a spacefaring status. The most advanced nation states are, in fact, space-capable societies because they have the capacity to send cargo and humans into low Earth orbit and beyond. However, their social structures and cultures lack fundamental characteristics that would allow for their designation as spacefaring societies. This article describes the characteristics of a theoretical spacefaring society and argues that getting there from our current status as space-capable societies is a long and arduous process, and it is not a definite outcome whatsoever. While a continuum is offered, it represents an imprecise path that can retrograde or fall apart at any time. Thus, this theoretical model provides one possible series of an unfolding of events that result in the creation of characteristics of the social fabric that may result in movement along the continuum toward a spacefaring society. Movement along the continuum results in an accumulation of coordinated spacefaring characteristics for a given society. Simultaneously, strictly terrestrial characteristics disappear or transform themselves into hybrid forms that include spacefaring features. This exercise demonstrates that this theoretical exercise has a number of benefits for astrosociologists conducting research in the area of spacefaring theory. Moreover, it makes the case for the idea that the study of the theoretical transformation from a space-capable to a spacefaring society includes implications for current and future 1) space policy in the public sector and 2) corporate decision-making related to space in the private sector.

How Accumulated Real Life Stress Experience and Cognitive Speed Interact on Decision-Making Processes

PubMed Central

Friedel, Eva; Sebold, Miriam; Kuitunen-Paul, Sören; Nebe, Stephan; Veer, Ilya M.; Zimmermann, Ulrich S.; Schlagenhauf, Florian; Smolka, Michael N.; Rapp, Michael; Walter, Henrik; Heinz, Andreas

2017-01-01

Rationale: Advances in neurocomputational modeling suggest that valuation systems for goal-directed (deliberative) on one side, and habitual (automatic) decision-making on the other side may rely on distinct computational strategies for reinforcement learning, namely model-free vs. model-based learning. As a key theoretical difference, the model-based system strongly demands cognitive functions to plan actions prospectively based on an internal cognitive model of the environment, whereas valuation in the model-free system relies on rather simple learning rules from operant conditioning to retrospectively associate actions with their outcomes and is thus cognitively less demanding. Acute stress reactivity is known to impair model-based but not model-free choice behavior, with higher working memory capacity protecting the model-based system from acute stress. However, it is not clear which impact accumulated real life stress has on model-free and model-based decision systems and how this influence interacts with cognitive abilities. Methods: We used a sequential decision-making task distinguishing relative contributions of both learning strategies to choice behavior, the Social Readjustment Rating Scale questionnaire to assess accumulated real life stress, and the Digit Symbol Substitution Test to test cognitive speed in 95 healthy subjects. Results: Individuals reporting high stress exposure who had low cognitive speed showed reduced model-based but increased model-free behavioral control. In contrast, subjects exposed to accumulated real life stress with high cognitive speed displayed increased model-based performance but reduced model-free control. Conclusion: These findings suggest that accumulated real life stress exposure can enhance reliance on cognitive speed for model-based computations, which may ultimately protect the model-based system from the detrimental influences of accumulated real life stress. The combination of accumulated real life stress exposure and slower information processing capacities, however, might favor model-free strategies. Thus, the valence and preference of either system strongly depends on stressful experiences and individual cognitive capacities. PMID:28642696

How Accumulated Real Life Stress Experience and Cognitive Speed Interact on Decision-Making Processes.

PubMed

Friedel, Eva; Sebold, Miriam; Kuitunen-Paul, Sören; Nebe, Stephan; Veer, Ilya M; Zimmermann, Ulrich S; Schlagenhauf, Florian; Smolka, Michael N; Rapp, Michael; Walter, Henrik; Heinz, Andreas

2017-01-01

Rationale: Advances in neurocomputational modeling suggest that valuation systems for goal-directed (deliberative) on one side, and habitual (automatic) decision-making on the other side may rely on distinct computational strategies for reinforcement learning, namely model-free vs. model-based learning. As a key theoretical difference, the model-based system strongly demands cognitive functions to plan actions prospectively based on an internal cognitive model of the environment, whereas valuation in the model-free system relies on rather simple learning rules from operant conditioning to retrospectively associate actions with their outcomes and is thus cognitively less demanding. Acute stress reactivity is known to impair model-based but not model-free choice behavior, with higher working memory capacity protecting the model-based system from acute stress. However, it is not clear which impact accumulated real life stress has on model-free and model-based decision systems and how this influence interacts with cognitive abilities. Methods: We used a sequential decision-making task distinguishing relative contributions of both learning strategies to choice behavior, the Social Readjustment Rating Scale questionnaire to assess accumulated real life stress, and the Digit Symbol Substitution Test to test cognitive speed in 95 healthy subjects. Results: Individuals reporting high stress exposure who had low cognitive speed showed reduced model-based but increased model-free behavioral control. In contrast, subjects exposed to accumulated real life stress with high cognitive speed displayed increased model-based performance but reduced model-free control. Conclusion: These findings suggest that accumulated real life stress exposure can enhance reliance on cognitive speed for model-based computations, which may ultimately protect the model-based system from the detrimental influences of accumulated real life stress. The combination of accumulated real life stress exposure and slower information processing capacities, however, might favor model-free strategies. Thus, the valence and preference of either system strongly depends on stressful experiences and individual cognitive capacities.

Risk taking and adult attention deficit/hyperactivity disorder: A gap between real life behavior and experimental decision making.

PubMed

Pollak, Yehuda; Shalit, Reut; Aran, Adi

2018-01-01

Adults with attention deficit/hyperactivity disorder (ADHD) are prone to suboptimal decision making and risk taking. The aim of this study was to test performance on a theoretically-based probabilistic decision making task in well-characterized adults with and without ADHD, and examine the relation between experimental risk taking and history of real-life risk-taking behavior, defined as cigarette, alcohol, and street drug use. University students with and without ADHD completed a modified version of the Cambridge Gambling Test, in which they had to choose between alternatives varied by level of risk, and reported their history of substance use. Both groups showed similar patterns of risk taking on the experimental decision making task, suggesting that ADHD is not linked to low sensitivity to risk. Past and present substance use was more prevalent in adults with ADHD. These finding question the validity of experimental probabilistic decision making task as a valid model for ADHD-related risk-taking behavior. Copyright © 2017 Elsevier B.V. All rights reserved.

Authors' response: the primacy of conscious decision making.

PubMed

Shanks, David R; Newell, Ben R

2014-02-01

The target article sought to question the common belief that our decisions are often biased by unconscious influences. While many commentators offer additional support for this perspective, others question our theoretical assumptions, empirical evaluations, and methodological criteria. We rebut in particular the starting assumption that all decision making is unconscious, and that the onus should be on researchers to prove conscious influences. Further evidence is evaluated in relation to the core topics we reviewed (multiple-cue judgment, deliberation without attention, and decisions under uncertainty), as well as priming effects. We reiterate a key conclusion from the target article, namely, that it now seems to be generally accepted that awareness should be operationally defined as reportable knowledge, and that such knowledge can only be evaluated by careful and thorough probing. We call for future research to pay heed to the different ways in which awareness can intervene in decision making (as identified in our lens model analysis) and to employ suitable methodology in the assessment of awareness, including the requirements that awareness assessment must be reliable, relevant, immediate, and sensitive.

Sensation Seeking and Impulsivity: Combined Associations with Risky Sexual Behavior in a Large Sample of Young Adults

PubMed Central

Charnigo, Richard; Noar, Seth M.; Garnett, Christopher; Crosby, Richard; Palmgreen, Philip; Zimmerman, Rick S.

2015-01-01

Although prior studies have shown that sensation seeking and impulsive decision-making are related to sexual risk-taking, it is still unclear whether these personality traits operate independently or synergistically. The purpose of this study was to elucidate the joint contribution of these personality traits to HIV and sexually transmitted disease (STD) risk behaviors using data from a large sample of sexually active young adults (N = 2,386). Regression modeling indicated that both sensation seeking and impulsive decision-making were consistently associated with sexual risk behaviors across 11 risk-related outcomes. Results further indicated that sensation seeking and impulsive decision-making operated synergistically with respect to the outcome variables of sex acts using drugs, acts with a partner using alcohol, and acts with a partner using drugs. In contrast to this, sensation seeking and impulsive decision-making operated independently with respect to the other sexual risk outcomes. Theoretical implications, as well as implications for HIV/STD prevention among high sensation seekers and impulsive decision-makers, are discussed. PMID:22456443

An Agent-Based Model of Private Woodland Owner Management Behavior Using Social Interactions, Information Flow, and Peer-To-Peer Networks

PubMed Central

Huff, Emily Silver; Leahy, Jessica E.; Hiebeler, David; Weiskittel, Aaron R.; Noblet, Caroline L.

2015-01-01

Privately owned woodlands are an important source of timber and ecosystem services in North America and worldwide. Impacts of management on these ecosystems and timber supply from these woodlands are difficult to estimate because complex behavioral theory informs the owner’s management decisions. The decision-making environment consists of exogenous market factors, internal cognitive processes, and social interactions with fellow landowners, foresters, and other rural community members. This study seeks to understand how social interactions, information flow, and peer-to-peer networks influence timber harvesting behavior using an agent-based model. This theoretical model includes forested polygons in various states of ‘harvest readiness’ and three types of agents: forest landowners, foresters, and peer leaders (individuals trained in conservation who use peer-to-peer networking). Agent rules, interactions, and characteristics were parameterized with values from existing literature and an empirical survey of forest landowner attitudes, intentions, and demographics. The model demonstrates that as trust in foresters and peer leaders increases, the percentage of the forest that is harvested sustainably increases. Furthermore, peer leaders can serve to increase landowner trust in foresters. Model output and equations will inform forest policy and extension/outreach efforts. The model also serves as an important testing ground for new theories of landowner decision making and behavior. PMID:26562429

An integrative review of in-class activities that enable active learning in college science classroom settings

NASA Astrophysics Data System (ADS)

Arthurs, Leilani A.; Kreager, Bailey Zo

2017-10-01

Engaging students in active learning is linked to positive learning outcomes. This study aims to synthesise the peer-reviewed literature about 'active learning' in college science classroom settings. Using the methodology of an integrative literature review, 337 articles archived in the Educational Resources Information Center (ERIC) are examined. Four categories of in-class activities emerge: (i) individual non-polling activities, (ii) in-class polling activities, (iii) whole-class discussion or activities, and (iv) in-class group activities. Examining the collection of identified in-class activities through the lens of a theoretical framework informed by constructivism and social interdependence theory, we synthesise the reviewed literature to propose the active learning strategies (ALSs) model and the instructional decisions to enable active learning (IDEAL) theory. The ALS model characterises in-class activities in terms of the degrees to which they are designed to promote (i) peer interaction and (ii) social interdependence. The IDEAL theory includes the ALS model and provides a framework for conceptualising different levels of the general concept 'active learning' and how these levels connect to instructional decision-making about using in-class activities. The proposed ALS model and IDEAL theory can be utilised to inform instructional decision-making and future research about active learning in college science courses.

What lies behind crop decisions?Coming to terms with revealing farmers' preferences

NASA Astrophysics Data System (ADS)

Gomez, C.; Gutierrez, C.; Pulido-Velazquez, M.; López Nicolás, A.

2016-12-01

The paper offers a fully-fledged applied revealed preference methodology to screen and represent farmers' choices as the solution of an optimal program involving trade-offs among the alternative welfare outcomes of crop decisions such as profits, income security and management easiness. The recursive two-stage method is proposed as an alternative to cope with the methodological problems inherent to common practice positive mathematical program methodologies (PMP). Differently from PMP, in the model proposed in this paper, the non-linear costs that are required for both calibration and smooth adjustment are not at odds with the assumptions of linear Leontief technologies and fixed crop prices and input costs. The method frees the model from ad-hoc assumptions about costs and then recovers the potential of economic analysis as a means to understand the rationale behind observed and forecasted farmers' decisions and then to enhance the potential of the model to support policy making in relevant domains such as agricultural policy, water management, risk management and climate change adaptation. After the introduction, where the methodological drawbacks and challenges are set up, section two presents the theoretical model, section three develops its empirical application and presents its implementation to a Spanish irrigation district and finally section four concludes and makes suggestions for further research.

Bayesian methods to estimate urban growth potential

USGS Publications Warehouse

Smith, Jordan W.; Smart, Lindsey S.; Dorning, Monica; Dupéy, Lauren Nicole; Méley, Andréanne; Meentemeyer, Ross K.

2017-01-01

Urban growth often influences the production of ecosystem services. The impacts of urbanization on landscapes can subsequently affect landowners’ perceptions, values and decisions regarding their land. Within land-use and land-change research, very few models of dynamic landscape-scale processes like urbanization incorporate empirically-grounded landowner decision-making processes. Very little attention has focused on the heterogeneous decision-making processes that aggregate to influence broader-scale patterns of urbanization. We examine the land-use tradeoffs faced by individual landowners in one of the United States’ most rapidly urbanizing regions − the urban area surrounding Charlotte, North Carolina. We focus on the land-use decisions of non-industrial private forest owners located across the region’s development gradient. A discrete choice experiment is used to determine the critical factors influencing individual forest owners’ intent to sell their undeveloped properties across a series of experimentally varied scenarios of urban growth. Data are analyzed using a hierarchical Bayesian approach. The estimates derived from the survey data are used to modify a spatially-explicit trend-based urban development potential model, derived from remotely-sensed imagery and observed changes in the region’s socioeconomic and infrastructural characteristics between 2000 and 2011. This modeling approach combines the theoretical underpinnings of behavioral economics with spatiotemporal data describing a region’s historical development patterns. By integrating empirical social preference data into spatially-explicit urban growth models, we begin to more realistically capture processes as well as patterns that drive the location, magnitude and rates of urban growth.

A cognitive-behavioral model of Internet gaming disorder: theoretical underpinnings and clinical implications.

PubMed

Dong, Guangheng; Potenza, Marc N

2014-11-01

Cognitive contributions to the behaviors observed in substance and non-substance addictions have been investigated and characterized. Based on models of drug addictions and the extant literature on Internet gaming disorder (IGD), we propose a cognitive-behavioral model for conceptualizing IGD. The model focuses on three domains and their roles in addictive behaviors. The three domains include motivational drives related to reward-seeking and stress-reduction, behavioral control relating to executive inhibition, and decision-making that involves weighing the pros and cons of engaging in motivated behaviors. Based on this model, we propose how behavioral therapies might target these domains in the treatment of IGD. Copyright © 2014 Elsevier Ltd. All rights reserved.

Hierarchical Bayesian analysis of outcome- and process-based social preferences and beliefs in Dictator Games and sequential Prisoner's Dilemmas.

PubMed

Aksoy, Ozan; Weesie, Jeroen

2014-05-01

In this paper, using a within-subjects design, we estimate the utility weights that subjects attach to the outcome of their interaction partners in four decision situations: (1) binary Dictator Games (DG), second player's role in the sequential Prisoner's Dilemma (PD) after the first player (2) cooperated and (3) defected, and (4) first player's role in the sequential Prisoner's Dilemma game. We find that the average weights in these four decision situations have the following order: (1)>(2)>(4)>(3). Moreover, the average weight is positive in (1) but negative in (2), (3), and (4). Our findings indicate the existence of strong negative and small positive reciprocity for the average subject, but there is also high interpersonal variation in the weights in these four nodes. We conclude that the PD frame makes subjects more competitive than the DG frame. Using hierarchical Bayesian modeling, we simultaneously analyze beliefs of subjects about others' utility weights in the same four decision situations. We compare several alternative theoretical models on beliefs, e.g., rational beliefs (Bayesian-Nash equilibrium) and a consensus model. Our results on beliefs strongly support the consensus effect and refute rational beliefs: there is a strong relationship between own preferences and beliefs and this relationship is relatively stable across the four decision situations. Copyright © 2014 Elsevier Inc. All rights reserved.

Theoretical life history responses of juvenile Oncorhynchus mykiss to changes in food availability using a dynamic state-dependent approach

USGS Publications Warehouse

Romine, Jason G.; Benjamin, Joseph R.; Perry, Russell W.; Casal, Lynne; Connolly, Patrick J.; Sauter, Sally S.

2013-01-01

Marine subsidies can play an important role in the growth, survival, and migratory behavior of rearing juvenile salmonids. Availability of high-energy, marine-derived food sources during critical decision windows may influence the timing of emigration or the decision to forego emigration completely and remain in the freshwater environment. Increasing growth and growth rate during these decision windows may result in an altered juvenile population structure, which will ultimately affect the adult population age-structure. We used a state dependent model to understand how the juvenile Oncorhynchus mykiss population structure may respond to increased availability of salmon eggs in their diet during critical decision windows. Our models predicted an increase in smolt production until coho salmon eggs comprised more than 50 percent of juvenile O. mykiss diet at the peak of the spawning run. At higher-than intermediate levels of egg consumption, smolt production decreased owing to increasing numbers of fish adopting a resident life-history strategy. Additionally, greater growth rates decreased the number of age-3 smolts and increased the number of age-2 smolts. Increased growth rates with higher egg consumption also decreased the age at which fish adopted the resident pathway. Our models suggest that the introduction of a high-energy food source during critical periods of the year could be sufficient to increase smolt production.

The process of trying to quit smoking from the perspective of patients with chronic obstructive pulmonary disease.

PubMed

Lundh, Lena; Hylander, Ingrid; Törnkvist, Lena

2012-09-01

To investigate why some patients with chronic obstructive pulmonary disease (COPD) have difficulty quitting smoking and to develop a theoretical model that describes their perspectives on these difficulties. Grounded theory method was used from the selection of participants to the analyses of semi-structured interviews with 14 patients with COPD. Four additional interviews were conducted to ensure relevance. The analysis resulted in a theoretical model that illustrates the process of 'Patients with COPD trying to quit smoking'. The model illuminates factors related to the decision to try to quit smoking, including pressure-filled mental states and constructive or destructive pressure-relief strategies. The constructive strategies lead either to success in quitting or to continuing to try to quit. The destructive strategies can lead to losing hope and becoming resigned to continuing to smoke. The theoretical model 'Patients trying to quit smoking' contributes to a better understanding of the pressure-filled mental states and destructive strategies experienced by some patients with COPD in the process of trying to quit. This better understanding can help nurses individualise counselling. Moreover, patients' own awareness of these states and strategies may facilitate their efforts to quit. The information in the model can also be used as a supplement to methods such as motivational interviewing (MI). © 2011 The Authors. Scandinavian Journal of Caring Sciences © 2011 Nordic College of Caring Science.

[Risk, uncertainty and ignorance in medicine].

PubMed

Rørtveit, G; Strand, R

2001-04-30

Exploration of healthy patients' risk factors for disease has become a major medical activity. The rationale behind primary prevention through exploration and therapeutic risk reduction is not separated from the theoretical assumption that every form of uncertainty can be expressed as risk. Distinguishing "risk" (as quantitative probabilities in a known sample space), "strict uncertainty" (when the sample space is known, but probabilities of events cannot be quantified) and "ignorance" (when the sample space is not fully known), a typical clinical situation (primary risk of coronary disease) is analysed. It is shown how strict uncertainty and sometimes ignorance can be present, in which case the orthodox decision theoretical rationale for treatment breaks down. For use in such cases, a different ideal model of rationality is proposed, focusing on the patient's considered reasons. This model has profound implications for the current understanding of medical professionalism as well as for the design of clinical guidelines.

Vaccination, herd behavior, and herd immunity.

PubMed

Cohen, Matan J; Brezis, Mayer; Block, Colin; Diederich, Adele; Chinitz, David

2013-11-01

During the 2009 outbreak of novel influenza AH1N1, insufficient data were available to adequately inform decision makers about benefits and risks of vaccination and disease. We hypothesized that individuals would opt to mimic their peers, having no better decision anchor. We used Game Theory, decision analysis, and transmission models to simulate the impact of subjective risks and preference estimates on vaccination behavior. We asked 95 students to provide estimates of risk and health state valuations with regard to AH1N1 infection, complications, and expectations of vaccine benefits and risks. These estimates were included in a sequential chain of models: a dynamic epidemic model, a decision tree, and a population-level model. Additionally, participants' intentions to vaccinate or not at varying vaccination rates were documented. The model showed that at low vaccination rates, vaccination dominated. When vaccination rates increased above 78%, nonvaccination was the dominant strategy. We found that vaccination intentions did not correspond to the shift in strategy dominance and segregated to 3 types of intentions: regardless of what others do 29/95 (31%) intended to vaccinate while 27/95 (28%) did not; among 39 of 95 (41%) intention was positively associated with putative vaccination rates. Some people conform to the majority's choice, either shifting epidemic dynamics toward herd immunity or, conversely, limiting societal goals. Policy leaders should use models carefully, noting their limitations and theoretical assumptions. Behavior drivers were not explicitly explored in this study, and the discrepant results beg further investigation. Models including real subjective perceptions with empiric or subjective probabilities can provide insight into deviations from expected rational behavior and suggest interventions in order to provide better population outcomes.

Science of Decision Making: A Data-Modeling Approach

DTIC Science & Technology

2013-10-01

were separated on a capillary column using the Dionex UltiMate 3000 (Sunnyvale, CA). The resolved peptides were then sprayed into a linear ion trap...database (3–5). These algorithms assign a peptide sequence, along with a matching score of the experimental ion product mass spectrum, to a theoretical ion ...Bacterial Sample Processing Samples were prepared for liquid chromatography (LC) tandem MS (LC– MS/MS) in a similar manner to that previously reported

Information needs and preferences of low and high literacy consumers for decisions about colorectal cancer screening: utilizing a linguistic model

PubMed Central

Smith, Sian K; Trevena, Lyndal; Nutbeam, Don; Barratt, Alexandra; McCaffery, Kirsten J

2008-01-01

Abstract Context  The use of written decision aids (DAs) in clinical practice has proliferated. However, few DAs have been developed for low literacy users, despite this group having low knowledge about healthcare and lacking involvement in health decisions. Objective  To explore the information needs and understanding of adults with varying literacy in relation to colorectal cancer screening, and to consider their responses to two versions of a decision aid. Participants  Thirty‐three men and women aged 45–74 years were recruited from Adult Basic Education classes (n = 17) and University Continuing Education programs (n = 16). Methods  We used qualitative methods (in‐depth, semi‐structured interviews) to compare and contrast the views of adults with lower and higher literacy levels, to gain a better understanding of how people with lower literacy value and interpret specific DA content and components; and determine whether needs and preferences are specific to lower literacy groups or generic across the broad literacy spectrum. Results  Regardless of literacy perspective, participants’ interpretations of the DA were shaped by their prior knowledge and expectations, as well as their values and preferences. This influenced perceptions of the DAs role in supporting informed decision making. A linguistic theoretical model was applied to interpret the findings. This facilitated considerations beyond the traditional focus on the readability of materials. Conclusion  Decision aids developers may find it useful to apply alternative approaches (linguistic) when creating DAs for consumers of varying literacy. PMID:18494957

Combining statistical inference and decisions in ecology

USGS Publications Warehouse

Williams, Perry J.; Hooten, Mevin B.

2016-01-01

Statistical decision theory (SDT) is a sub-field of decision theory that formally incorporates statistical investigation into a decision-theoretic framework to account for uncertainties in a decision problem. SDT provides a unifying analysis of three types of information: statistical results from a data set, knowledge of the consequences of potential choices (i.e., loss), and prior beliefs about a system. SDT links the theoretical development of a large body of statistical methods including point estimation, hypothesis testing, and confidence interval estimation. The theory and application of SDT have mainly been developed and published in the fields of mathematics, statistics, operations research, and other decision sciences, but have had limited exposure in ecology. Thus, we provide an introduction to SDT for ecologists and describe its utility for linking the conventionally separate tasks of statistical investigation and decision making in a single framework. We describe the basic framework of both Bayesian and frequentist SDT, its traditional use in statistics, and discuss its application to decision problems that occur in ecology. We demonstrate SDT with two types of decisions: Bayesian point estimation, and an applied management problem of selecting a prescribed fire rotation for managing a grassland bird species. Central to SDT, and decision theory in general, are loss functions. Thus, we also provide basic guidance and references for constructing loss functions for an SDT problem.

Deciding Where to Turn: A Qualitative Investigation of College Students' Helpseeking Decisions After Sexual Assault.

PubMed

DeLoveh, Heidi L M; Cattaneo, Lauren Bennett

2017-03-01

Sexual assault is a widespread problem on college campuses that has been the subject of substantial attention in recent years (Ali, 2011; Krebs, Lindquist, Berzofsky, Shook-Sa, & Peterson, 2016). Resources designed to address the problem exist, but there is evidence that they are underutilized by survivors (Campbell, 2008). The current study used grounded theory to explore how sexual assault survivors make decisions about helpseeking. In-depth interviews were conducted with 14 college sexual assault survivors to develop a theoretical model for their decision-making process. The resulting model, Deciding Where to Turn, suggests that survivors engage in three key decision points: determining if there is a problem related to the sexual assault (Do I Need Help), considering options (What Can I Do), and weighing the consequences of these options (What Will I Do). This process results in one of four behavioral choices: cope on one's own, seek support from friends/family, seek support from formal resources, or covert helpseeking, where needs are met without disclosure. Deciding Where to Turn contributes to the literature by providing a framework for understanding helpseeking decisions after sexual assault, highlighting the need to match reactions to survivor perceptions. The concept of covert helpseeking in particular adds to the way researchers and practitioners think about helpseeking. Research and practice implications are discussed. © Society for Community Research and Action 2017.

Don't tell on me: Experimental evidence of asymmetric information in transnational households*

PubMed Central

Ambler, Kate

2014-01-01

Although most theoretical models of household decision making assume perfect information, empirical studies suggest that information asymmetries can have large impacts on resource allocation. I demonstrate the importance of these asymmetries in transnational households, where physical distance between family members can make information barriers especially acute. I implement an experiment among migrants in Washington, DC, and their families in El Salvador that examines how information asymmetries can have strategic and inadvertent impacts on remittance decisions. Migrants make an incentivized decision over how much of a cash windfall to remit, and recipients decide how they will spend a remittance. Migrants strategically send home less when their choice is not revealed to recipients. Recipients make spending choices closer to migrants' preferences when the migrants' preferences are shared, regardless of whether or not the spending choices are revealed to the migrants, suggesting that recipients' choices are inadvertently affected by imperfect information. PMID:25558123

The affective regulation of cognitive priming.

PubMed

Storbeck, Justin; Clore, Gerald L

2008-04-01

Semantic and affective priming are classic effects observed in cognitive and social psychology, respectively. The authors discovered that affect regulates such priming effects. In Experiment 1, positive and negative moods were induced before one of three priming tasks; evaluation, categorization, or lexical decision. As predicted, positive affect led to both affective priming (evaluation task) and semantic priming (category and lexical decision tasks). However, negative affect inhibited such effects. In Experiment 2, participants in their natural affective state completed the same priming tasks as in Experiment 1. As expected, affective priming (evaluation task) and category priming (categorization and lexical decision tasks) were observed in such resting affective states. Hence, the authors conclude that negative affect inhibits semantic and affective priming. These results support recent theoretical models, which suggest that positive affect promotes associations among strong and weak concepts, and that negative affect impairs such associations (Clore & Storbeck, 2006; Kuhl, 2000). (Copyright) 2008 APA.

Don't tell on me: Experimental evidence of asymmetric information in transnational households.

PubMed

Ambler, Kate

2015-03-01

Although most theoretical models of household decision making assume perfect information, empirical studies suggest that information asymmetries can have large impacts on resource allocation. I demonstrate the importance of these asymmetries in transnational households, where physical distance between family members can make information barriers especially acute. I implement an experiment among migrants in Washington, DC, and their families in El Salvador that examines how information asymmetries can have strategic and inadvertent impacts on remittance decisions. Migrants make an incentivized decision over how much of a cash windfall to remit, and recipients decide how they will spend a remittance. Migrants strategically send home less when their choice is not revealed to recipients. Recipients make spending choices closer to migrants' preferences when the migrants' preferences are shared, regardless of whether or not the spending choices are revealed to the migrants, suggesting that recipients' choices are inadvertently affected by imperfect information.

Optimal behaviour can violate the principle of regularity

PubMed Central

Trimmer, Pete C.

2013-01-01

Understanding decisions is a fundamental aim of behavioural ecology, psychology and economics. The regularity axiom of utility theory holds that a preference between options should be maintained when other options are made available. Empirical studies have shown that animals violate regularity but this has not been understood from a theoretical perspective, such decisions have therefore been labelled as irrational. Here, I use models of state-dependent behaviour to demonstrate that choices can violate regularity even when behavioural strategies are optimal. I also show that the range of conditions over which regularity should be violated can be larger when options do not always persist into the future. Consequently, utility theory—based on axioms, including transitivity, regularity and the independence of irrelevant alternatives—is undermined, because even alternatives that are never chosen by an animal (in its current state) can be relevant to a decision. PMID:23740781

Understanding surgery choices for breast cancer: how might the Theory of Planned Behaviour and the Common Sense Model contribute to decision support interventions?

PubMed Central

Sivell, Stephanie; Edwards, Adrian; Elwyn, Glyn; Manstead, Antony S. R.

2010-01-01

Abstract Objective  To describe the evidence about factors influencing breast cancer patients’ surgery choices and the implications for designing decision support in reference to an extended Theory of Planned Behaviour (TPB) and the Common Sense Model of Illness Representations (CSM). Background  A wide range of factors are known to influence the surgery choices of women diagnosed with early breast cancer facing the choice of mastectomy or breast conservation surgery with radiotherapy. However, research does not always reflect the complexities of decision making and is often atheoretical. A theoretical approach, as provided by the CSM and the TPB, could help to identify and tailor support by focusing on patients’ representations of their breast cancer and predicting surgery choices. Design  Literature search and narrative synthesis of data. Synthesis  Twenty‐six studies reported women’s surgery choices to be influenced by perceived clinical outcomes of surgery, appearance and body image, treatment concerns, involvement in decision making and preferences of clinicians. These factors can be mapped onto the key constructs of both the TPB and CSM and used to inform the design and development of decision support interventions to ensure accurate information is provided in areas most important to patients. Conclusions  The TPB and CSM have the potential to inform the design of decision support for breast cancer patients, with accurate and clear information that avoids leading patients to make decisions they may come to regret. Further research is needed examining how the components of the extended TPB and CSM account for patients’ surgery choices. PMID:20579123

Neural mechanisms of human perceptual choice under focused and divided attention.

PubMed

Wyart, Valentin; Myers, Nicholas E; Summerfield, Christopher

2015-02-25

Perceptual decisions occur after the evaluation and integration of momentary sensory inputs, and dividing attention between spatially disparate sources of information impairs decision performance. However, it remains unknown whether dividing attention degrades the precision of sensory signals, precludes their conversion into decision signals, or dampens the integration of decision information toward an appropriate response. Here we recorded human electroencephalographic (EEG) activity while participants categorized one of two simultaneous and independent streams of visual gratings according to their average tilt. By analyzing trial-by-trial correlations between EEG activity and the information offered by each sample, we obtained converging behavioral and neural evidence that dividing attention between left and right visual fields does not dampen the encoding of sensory or decision information. Under divided attention, momentary decision information from both visual streams was encoded in slow parietal signals without interference but was lost downstream during their integration as reflected in motor mu- and beta-band (10-30 Hz) signals, resulting in a "leaky" accumulation process that conferred greater behavioral influence to more recent samples. By contrast, sensory inputs that were explicitly cued as irrelevant were not converted into decision signals. These findings reveal that a late cognitive bottleneck on information integration limits decision performance under divided attention, and places new capacity constraints on decision-theoretic models of information integration under cognitive load. Copyright © 2015 the authors 0270-6474/15/353485-14$15.00/0.

Neural mechanisms of human perceptual choice under focused and divided attention

PubMed Central

Wyart, Valentin; Myers, Nicholas E.; Summerfield, Christopher

2015-01-01

Perceptual decisions occur after evaluation and integration of momentary sensory inputs, and dividing attention between spatially disparate sources of information impairs decision performance. However, it remains unknown whether dividing attention degrades the precision of sensory signals, precludes their conversion into decision signals, or dampens the integration of decision information towards an appropriate response. Here we recorded human electroencephalographic (EEG) activity whilst participants categorised one of two simultaneous and independent streams of visual gratings according to their average tilt. By analyzing trial-by-trial correlations between EEG activity and the information offered by each sample, we obtained converging behavioural and neural evidence that dividing attention between left and right visual fields does not dampen the encoding of sensory or decision information. Under divided attention, momentary decision information from both visual streams was encoded in slow parietal signals without interference but was lost downstream during their integration as reflected in motor mu- and beta-band (10–30 Hz) signals, resulting in a ‘leaky’ accumulation process which conferred greater behavioural influence to more recent samples. By contrast, sensory inputs that were explicitly cued as irrelevant were not converted into decision signals. These findings reveal that a late cognitive bottleneck on information integration limits decision performance under divided attention, and place new capacity constraints on decision-theoretic models of information integration under cognitive load. PMID:25716848

Collaborative, Sequential and Isolated Decisions in Design

NASA Technical Reports Server (NTRS)

Lewis, Kemper; Mistree, Farrokh

1997-01-01

The Massachusetts Institute of Technology (MIT) Commission on Industrial Productivity, in their report Made in America, found that six recurring weaknesses were hampering American manufacturing industries. The two weaknesses most relevant to product development were 1) technological weakness in development and production, and 2) failures in cooperation. The remedies to these weaknesses are considered the essential twin pillars of CE: 1) improved development process, and 2) closer cooperation. In the MIT report, it is recognized that total cooperation among teams in a CE environment is rare in American industry, while the majority of the design research in mathematically modeling CE has assumed total cooperation. In this paper, we present mathematical constructs, based on game theoretic principles, to model degrees of collaboration characterized by approximate cooperation, sequential decision making and isolation. The design of a pressure vessel and a passenger aircraft are included as illustrative examples.

Dynamic Resource Allocation in Disaster Response: Tradeoffs in Wildfire Suppression

PubMed Central

Petrovic, Nada; Alderson, David L.; Carlson, Jean M.

2012-01-01

Challenges associated with the allocation of limited resources to mitigate the impact of natural disasters inspire fundamentally new theoretical questions for dynamic decision making in coupled human and natural systems. Wildfires are one of several types of disaster phenomena, including oil spills and disease epidemics, where (1) the disaster evolves on the same timescale as the response effort, and (2) delays in response can lead to increased disaster severity and thus greater demand for resources. We introduce a minimal stochastic process to represent wildfire progression that nonetheless accurately captures the heavy tailed statistical distribution of fire sizes observed in nature. We then couple this model for fire spread to a series of response models that isolate fundamental tradeoffs both in the strength and timing of response and also in division of limited resources across multiple competing suppression efforts. Using this framework, we compute optimal strategies for decision making scenarios that arise in fire response policy. PMID:22514605

Stability and Hopf bifurcation for a business cycle model with expectation and delay

NASA Astrophysics Data System (ADS)

Liu, Xiangdong; Cai, Wenli; Lu, Jiajun; Wang, Yangyang

2015-08-01

According to rational expectation hypothesis, the government will take into account the future capital stock in the process of investment decision. By introducing anticipated capital stock into an economic model with investment delay, we construct a mixed functional differential system including delay and advanced variables. The system is converted to the one containing only delay by variable substitution. The equilibrium point of the system is obtained and its dynamical characteristics such as stability, Hopf bifurcation and its stability and direction are investigated by using the related theories of nonlinear dynamics. We carry out some numerical simulations to confirm these theoretical conclusions. The results indicate that both capital stock's anticipation and investment lag are the certain factors leading to the occurrence of cyclical fluctuations in the macroeconomic system. Moreover, the level of economic fluctuation can be dampened to some extent if investment decisions are made by the reasonable short-term forecast on capital stock.

Averting Behavior Framework for Perceived Risk of Yersinia enterocolitica Infections.

PubMed

Aziz, Sonia N; Aziz, Khwaja M S

2012-01-01

The focus of this research is to present a theoretical model of averting actions that households take to avoid exposure to Yersinia enterocolitica in contaminated food. The cost of illness approach only takes into account the value of a cure, while the averting behavior approach can estimate the value of preventing the illness. The household, rather than the individual, is the unit of analysis in this model, where one household member is primarily responsible for procuring uncontaminated food for their family. Since children are particularly susceptible and live with parents who are primary decision makers for sustenance, the designated household head makes the choices that are investigated in this paper. This model uses constrained optimization to characterize activities that may offer protection from exposure to Yersinia enterocolitica contaminated food. A representative household decision maker is assumed to allocate family resources to maximize utility of an altruistic parent, an assumption used in most research involving economics of the family.

Professional responsibility and decision-making in the context of a disease-focused model of nursing care: The difficulties experienced by Spanish nurses.

PubMed

Rodrigo, Olga; Caïs, Jordi; Monforte-Royo, Cristina

2017-10-01

When, in 1977, nurse education in Spain was transferred to universities a more patient-centred, the Anglo-American philosophy of care was introduced into a context in which nurses had traditionally prioritised their technical skills. This paper examines the characteristics of the nurse's professional role in Spain, where the model of nursing practice has historically placed them in a position akin to that of physician assistants. The study design was qualitative and used the method of analytic induction. Participants were selected by means of theoretical sampling and then underwent in-depth interviews. The resulting material was analysed using an approach based on the principles of grounded theory. Strategies were applied to ensure the credibility, transferability, dependability and confirmability of the findings. The main conclusion is that nurses in Spain continue to work within a disease-focused model of care, making it difficult for them to take responsibility for decision-making. © 2017 John Wiley & Sons Ltd.

Cognitive Control Predicts Use of Model-Based Reinforcement-Learning

PubMed Central

Otto, A. Ross; Skatova, Anya; Madlon-Kay, Seth; Daw, Nathaniel D.

2015-01-01

Accounts of decision-making and its neural substrates have long posited the operation of separate, competing valuation systems in the control of choice behavior. Recent theoretical and experimental work suggest that this classic distinction between behaviorally and neurally dissociable systems for habitual and goal-directed (or more generally, automatic and controlled) choice may arise from two computational strategies for reinforcement learning (RL), called model-free and model-based RL, but the cognitive or computational processes by which one system may dominate over the other in the control of behavior is a matter of ongoing investigation. To elucidate this question, we leverage the theoretical framework of cognitive control, demonstrating that individual differences in utilization of goal-related contextual information—in the service of overcoming habitual, stimulus-driven responses—in established cognitive control paradigms predict model-based behavior in a separate, sequential choice task. The behavioral correspondence between cognitive control and model-based RL compellingly suggests that a common set of processes may underpin the two behaviors. In particular, computational mechanisms originally proposed to underlie controlled behavior may be applicable to understanding the interactions between model-based and model-free choice behavior. PMID:25170791

Effects of a decision support intervention on decisional conflict associated with microsatellite instability testing.

PubMed

Hall, Michael J; Manne, Sharon L; Winkel, Gary; Chung, Daniel S; Weinberg, David S; Meropol, Neal J

2011-02-01

Decision support to facilitate informed consent is increasingly important for complicated medical tests. Here, we test a theoretical model of factors influencing decisional conflict in a study examining the effects of a decision support aid that was designed to assist patients at high risk for hereditary nonpolyposis colorectal cancer (CRC) deciding whether to pursue the microsatellite instability (MSI) test. Participants were 239 CRC patients at high familial risk for a genetic mutation who completed surveys before and after exposure to the intervention. Half of the sample was assigned to the CD-ROM aid and half received a brief description of the test. Structural equation modeling was employed to examine associations among the intervention, knowledge, pros and cons to having MSI testing, self-efficacy, preparedness, and decisional conflict. The goodness of fit for the model was acceptable [FIML, full information maximum likelihood, χ(2) (df = 280) = 392.24; P = 0.00]. As expected, the paths to decisional conflict were significant for postintervention pros of MSI testing (t = -2.43; P < 0.05), cons of MSI testing (t = 2.78; P < 0.05), and preparedness (t = -7.27; P < 0.01). The intervention impacted decisional conflict by increasing knowledge about the MSI test and knowledge exerted its effects on decisional conflict by increasing preparedness to make a decision about the test and by increases in perceived benefits of having the test. Increasing knowledge, preparedness, and perceived benefits of undergoing the MSI test facilitate informed decision making for this test. Understanding mechanisms underlying health decisions is critical for improving decisional support. Individuals with Lynch syndrome have an elevated lifetime risk of CRC. Risk of Lynch syndrome may be assessed with a tumor-based screening test (MSI testing or immunohistochemical tissue staining). ©2011 AACR.

Against all odds -- Probabilistic forecasts and decision making

NASA Astrophysics Data System (ADS)

Liechti, Katharina; Zappa, Massimiliano

2015-04-01

In the city of Zurich (Switzerland) the setting is such that the damage potential due to flooding of the river Sihl is estimated to about 5 billion US dollars. The flood forecasting system that is used by the administration for decision making runs continuously since 2007. It has a time horizon of max. five days and operates at hourly time steps. The flood forecasting system includes three different model chains. Two of those are run by the deterministic NWP models COSMO-2 and COSMO-7 and one is driven by the probabilistic NWP COSMO-Leps. The model chains are consistent since February 2010, so five full years are available for the evaluation for the system. The system was evaluated continuously and is a very nice example to present the added value that lies in probabilistic forecasts. The forecasts are available on an online-platform to the decision makers. Several graphical representations of the forecasts and forecast-history are available to support decision making and to rate the current situation. The communication between forecasters and decision-makers is quite close. To put it short, an ideal situation. However, an event or better put a non-event in summer 2014 showed that the knowledge about the general superiority of probabilistic forecasts doesn't necessarily mean that the decisions taken in a specific situation will be based on that probabilistic forecast. Some years of experience allow gaining confidence in the system, both for the forecasters and for the decision-makers. Even if from the theoretical point of view the handling during crisis situation is well designed, a first event demonstrated that the dialog with the decision-makers still lacks of exercise during such situations. We argue, that a false alarm is a needed experience to consolidate real-time emergency procedures relying on ensemble predictions. A missed event would probably also fit, but, in our case, we are very happy not to report about this option.

Pedagogical Decision Making through the Lens of Teacher Preparation Program

ERIC Educational Resources Information Center

Prachagool, Veena; Nuangchalerm, Prasart; Subramaniam, Ganakumaran; Dostal, Jirí

2016-01-01

Pedagogical decision making is very important for professional teachers, it concerns belief, self-efficacy, and actions that teachers expose to classroom. This paper employed theoretical lens and education policy in Thailand to examine the preservice teachers' views about pedagogical decision making. Discussion helps school mentors understand…

Bayesian Decision Theoretical Framework for Clustering

ERIC Educational Resources Information Center

Chen, Mo

2011-01-01

In this thesis, we establish a novel probabilistic framework for the data clustering problem from the perspective of Bayesian decision theory. The Bayesian decision theory view justifies the important questions: what is a cluster and what a clustering algorithm should optimize. We prove that the spectral clustering (to be specific, the…

An Assessment of Reading Compliance Decisions among Undergraduate Students

ERIC Educational Resources Information Center

Sharma, Amit; Van Hoof, Bert; Pursel, Barton

2013-01-01

Research suggests that reading compliance among undergraduate students is low. This study assesses the factors that influence students' decisions to comply with their assigned course readings using two theoretical underpinnings: students' self-rationing ability of time and construal effects on their decision process. Data collected through focus…

The Measurement and Correlates of Career Decision Making.

ERIC Educational Resources Information Center

Harren, Vincent A.; Kass, Richard A.

This paper presents a theoretical framework for understanding career decision making (CDM); introduces an instrument, Assessment of Career Decision Making (ACDM) to measure CDM with college students; and presents correlational data on sex role and cognitive style factors hypothesized to influence CDM. The ACDM, designed to measure the Tiedeman and…

Mental model mapping as a new tool to analyse the use of information in decision-making in integrated water management

NASA Astrophysics Data System (ADS)

Kolkman, M. J.; Kok, M.; van der Veen, A.

The solution of complex, unstructured problems is faced with policy controversy and dispute, unused and misused knowledge, project delay and failure, and decline of public trust in governmental decisions. Mental model mapping (also called concept mapping) is a technique to analyse these difficulties on a fundamental cognitive level, which can reveal experiences, perceptions, assumptions, knowledge and subjective beliefs of stakeholders, experts and other actors, and can stimulate communication and learning. This article presents the theoretical framework from which the use of mental model mapping techniques to analyse this type of problems emerges as a promising technique. The framework consists of the problem solving or policy design cycle, the knowledge production or modelling cycle, and the (computer) model as interface between the cycles. Literature attributes difficulties in the decision-making process to communication gaps between decision makers, stakeholders and scientists, and to the construction of knowledge within different paradigm groups that leads to different interpretation of the problem situation. Analysis of the decision-making process literature indicates that choices, which are made in all steps of the problem solving cycle, are based on an individual decision maker’s frame of perception. This frame, in turn, depends on the mental model residing in the mind of the individual. Thus we identify three levels of awareness on which the decision process can be analysed. This research focuses on the third level. Mental models can be elicited using mapping techniques. In this way, analysing an individual’s mental model can shed light on decision-making problems. The steps of the knowledge production cycle are, in the same manner, ultimately driven by the mental models of the scientist in a specific discipline. Remnants of this mental model can be found in the resulting computer model. The characteristics of unstructured problems (complexity, uncertainty and disagreement) can be positioned in the framework, as can the communities of knowledge construction and valuation involved in the solution of these problems (core science, applied science, and professional consultancy, and “post-normal” science). Mental model maps, this research hypothesises, are suitable to analyse the above aspects of the problem. This hypothesis is tested for the case of the Zwolle storm surch barrier. Analysis can aid integration between disciplines, participation of public stakeholders, and can stimulate learning processes. Mental model mapping is recommended to visualise the use of knowledge, to analyse difficulties in problem solving process, and to aid information transfer and communication. Mental model mapping help scientists to shape their new, post-normal responsibilities in a manner that complies with integrity when dealing with unstructured problems in complex, multifunctional systems.

The effect of information on household water and energy use

NASA Astrophysics Data System (ADS)

Hans, Liesel

Water and Energy Utilities are faced with growing demand at a time when supply expansion is increasingly costly, inconsistent and taxing on the environment. Given that supply expansion is limited, to meet future needs utilities need demand-side management policies to result in more reliable and consistent consumer responsiveness. Currently, most households do not have access to the level or type of information needed to respond to price signals in a reliable and effective way. Advanced information technology solutions exist and are being increasingly adopted, but we need to know more about how the informational setting affects decision-making, consumption levels and price responsiveness. This research analyzes the effect of information on household water and energy consumption, which is a decision-making environment characterized by uncertainty and imperfect information. This study also analyzes additional complexities stemming from infrequent billing, non-linear pricing structures, and combined utility bills, each of which may dampen price signals. I first develop a theoretical model of decision-making under uncertainty. I use this model to illustrate the effect of more frequent information, which eliminates uncertainty about past decisions, on remaining decisions within the billing period. The model emphasizes the role of risk preferences and the realization of the uncertain quantity. On average, risk averse consumers will increase consumption when uncertainty is reduced; risk seeking consumers will do the opposite. Introduction of a non-linear rate structure induces behavior that makes individuals appear as if they are risk averse or risk seeking, despite their actual risk preferences. This model highlights the importance of modeling multiple decisions within a billing period and accounting for a spectrum of risk preferences. In Chapter 3, I create a computerized laboratory experiment designed to generate data used to test some of the hypotheses formulated in the theoretical model presented in Chapter 2. Results from the experiment show that, on average, individuals consume more when provided with more frequent information that resolves uncertainty about past decisions made within a single billing period. This result is driven by the fact that the majority of participants are risk averse or risk neutral. Risk seeking participants instead reduce use when facing less uncertainty. Also as predicted by the theoretical model in Chapter 2, combining behavior driven by risk preferences with the presence of an increasing block rate structure results in behavior that looks like consumers are targeting the block boundary. This experiment shows that providing more information may not lead to reduced use without other incentives, goal-setting, or mechanisms designed to help individuals process the information. In Chapter 4, I empirically analyze a ten-year household-level panel data set of monthly utility bills. A single utility provides electricity, natural gas and water services to its customers and therefore bills through a single utility bill. I first show that price responsiveness varies by the number and combination of services subscribed to by a given household. Second, through a price salience model I show that households are more responsive to the price of water when the water portion of the total bill is greater. When multiple services are contained on a single bill, the salience of any individual price signal is dampened. This study confirms that households are inelastic though not unresponsive to water prices. In order to make pricing policies more effective, utilities need to acknowledge that households may be responding to total utility costs (i.e., may respond to a high utility bill by reducing electricity use despite the true driver of the high bill) and will need to find ways to make quantity and price information more salient to their customers. Chapter 5 concludes this dissertation by summarizing the contributions of the research and possible extensions for future work. By improving the informational environment surrounding household water and energy use, there will be great capacity for households to use water and energy more efficiently and ultimately make choices that reduce residential water/energy consumption and yield benefits for customers, utilities, and the environment.

Mentor judgements and decision-making in the assessment of student nurse competence in practice: A mixed-methods study.

PubMed

Burden, Sarah; Topping, Anne Elizabeth; O'Halloran, Catherine

2018-05-01

To investigate how mentors form judgements and reach summative assessment decisions regarding student competence in practice. Competence assessment is a significant component of pre-registration nursing programmes in the United Kingdom. Concerns exist that assessments are subjective, lack consistency and that mentors fail to judge student performance as unsatisfactory. A two-stage sequential embedded mixed-methods design. Data collected 2012-2013. This study involved a whole student cohort completing a UK undergraduate adult nursing programme (N = 41). Stage 1: quantitative data on mentor conduct of assessment interviews and the final decision recorded (N = 330 from 270 mentors) were extracted from student Practice Assessment Documents (PADs). Stage 2: mentor feedback in student PADs was used in Stimulated Recall interviews with a purposive sample of final placement mentors (N = 17). These were thematically analysed. Findings were integrated to develop a theoretically driven model of mentor decision-making. Course assessment strategies and documentation had limited effect in framing mentor judgements and decisions. Rather, mentors amassed impressions, moderated by expectations of an "idealized student" by practice area and programme stage that influenced their management and outcome of the assessment process. These impressions were accumulated and combined into judgements that informed the final decision. This process can best be understood and conceptualized through the Brunswik's lens model of social judgement. Mentor decisions were reasoned and there was a shared understanding of judgement criteria and their importance. This impression-based nature of mentor decision-making questions the reliability and validity of competency-based assessments used in nursing pre-registration programmes. © 2017 John Wiley & Sons Ltd.

Physician, Patient and Contextual Factors Affecting Treatment Decisions in Older Adults with Cancer: A Literature Review

PubMed Central

Tariman, J. D.; Berry, D. L.; Cochrane, B.; Doorenbos, A.; Schepp, K.

2010-01-01

Purpose/Objectives To review physician, patient, and contextual factors that affect treatment decision-making in older adults diagnosed with cancer and relate these factors to theoretical models of decision-making. Data Sources PubMed (1966-April 2010), PsycINFO (1967-April 2010) and CINAHL (1982-April 2010) databases were searched to access relevant medical, psychological and nursing literature. Data Synthesis Physician factors in treatment decisions include physician personal beliefs and values, expertise, practice type, perception of lowered life expectancy, medical factors, power, and communication style. Patient factors include personal beliefs and values, ethnicity, decisional control preferences, previous health-related experience, perception of the decision-making process, and personal factors. Contextual factors include availability of caregiver, lack of insurance, poor financial status, and geographical barrier. The interplay of physician, patient, and contextual factors are not well understood. Existing models of decision-making are not sufficient to explicate TDM process in older adults diagnosed with cancer. Conclusions Clinical studies in older adult patient population using a longitudinal and prospective design are needed to examine real-time interplay of patient, physician, and contextual factors and to better understand how these divergent factors influenced actual treatment decisions. Implications for Nursing Oncology nurses can advocate for a patient’s autonomy during TDM by coaching them to seek evidence-based discussion of various treatment options, benefits and risks assessments, and truthful discussion of the probability of success for each treatment option from their physicians. Oncology nurses must promote an informed treatment decisions that are consistent with a patient’s personal preference and values within the limits of the patient’s personal contexts. PMID:22201670

Locating Sensors for Detecting Source-to-Target Patterns of Special Nuclear Material Smuggling: A Spatial Information Theoretic Approach

PubMed Central

Przybyla, Jay; Taylor, Jeffrey; Zhou, Xuesong

2010-01-01

In this paper, a spatial information-theoretic model is proposed to locate sensors for detecting source-to-target patterns of special nuclear material (SNM) smuggling. In order to ship the nuclear materials from a source location with SNM production to a target city, the smugglers must employ global and domestic logistics systems. This paper focuses on locating a limited set of fixed and mobile radiation sensors in a transportation network, with the intent to maximize the expected information gain and minimize the estimation error for the subsequent nuclear material detection stage. A Kalman filtering-based framework is adapted to assist the decision-maker in quantifying the network-wide information gain and SNM flow estimation accuracy. PMID:22163641

Locating sensors for detecting source-to-target patterns of special nuclear material smuggling: a spatial information theoretic approach.

PubMed

Przybyla, Jay; Taylor, Jeffrey; Zhou, Xuesong

2010-01-01

In this paper, a spatial information-theoretic model is proposed to locate sensors for detecting source-to-target patterns of special nuclear material (SNM) smuggling. In order to ship the nuclear materials from a source location with SNM production to a target city, the smugglers must employ global and domestic logistics systems. This paper focuses on locating a limited set of fixed and mobile radiation sensors in a transportation network, with the intent to maximize the expected information gain and minimize the estimation error for the subsequent nuclear material detection stage. A Kalman filtering-based framework is adapted to assist the decision-maker in quantifying the network-wide information gain and SNM flow estimation accuracy.

Information-theoretic approach to interactive learning

NASA Astrophysics Data System (ADS)

Still, S.

2009-01-01

The principles of statistical mechanics and information theory play an important role in learning and have inspired both theory and the design of numerous machine learning algorithms. The new aspect in this paper is a focus on integrating feedback from the learner. A quantitative approach to interactive learning and adaptive behavior is proposed, integrating model- and decision-making into one theoretical framework. This paper follows simple principles by requiring that the observer's world model and action policy should result in maximal predictive power at minimal complexity. Classes of optimal action policies and of optimal models are derived from an objective function that reflects this trade-off between prediction and complexity. The resulting optimal models then summarize, at different levels of abstraction, the process's causal organization in the presence of the learner's actions. A fundamental consequence of the proposed principle is that the learner's optimal action policies balance exploration and control as an emerging property. Interestingly, the explorative component is present in the absence of policy randomness, i.e. in the optimal deterministic behavior. This is a direct result of requiring maximal predictive power in the presence of feedback.

Inside the black box of shared decision making: distinguishing between the process of involvement and who makes the decision

PubMed Central

Edwards, Adrian; Elwyn, Glyn

2006-01-01

Abstract Background  Shared decision making has practical implications for everyday health care. However, it stems from largely theoretical frameworks and is not widely implemented in routine practice. Aims  We undertook an empirical study to inform understanding of shared decision making and how it can be operationalized more widely. Method  The study involved patients visiting UK general practitioners already well experienced in shared decision making. After these consultations, semi‐structured telephone interviews were conducted and analysed using the constant comparative method of content analysis. Results  All patients described at least some components of shared decision making but half appeared to perceive the decision as shared and half as ‘patient‐led’. However, patients exhibited some uncertainty about who had made the decision, reflecting different meanings of decision making from those described in the literature. A distinction is indicated between the process of involvement (option portrayal, exchange of information and exploring preferences for who makes the decision) and the actual decisional responsibility (who makes the decision). The process of involvement appeared to deliver benefits for patients, not the action of making the decision. Preferences for decisional responsibility varied during some consultations, generating unsatisfactory interactions when actual decisional responsibility did not align with patient preferences at that stage of a consultation. However, when conducted well, shared decision making enhanced reported satisfaction, understanding and confidence in the decisions. Conclusions  Practitioners can focus more on the process of involving patients in decision making rather than attaching importance to who actually makes the decision. They also need to be aware of the potential for changing patient preferences for decisional responsibility during a consultation and address non‐alignment of patient preferences with the actual model of decision making if this occurs. PMID:17083558

The Linear Quadratic Gaussian Multistage Game with Nonclassical Information Pattern Using a Direct Solution Method

NASA Astrophysics Data System (ADS)

Clemens, Joshua William

Game theory has application across multiple fields, spanning from economic strategy to optimal control of an aircraft and missile on an intercept trajectory. The idea of game theory is fascinating in that we can actually mathematically model real-world scenarios and determine optimal decision making. It may not always be easy to mathematically model certain real-world scenarios, nonetheless, game theory gives us an appreciation for the complexity involved in decision making. This complexity is especially apparent when the players involved have access to different information upon which to base their decision making (a nonclassical information pattern). Here we will focus on the class of adversarial two-player games (sometimes referred to as pursuit-evasion games) with nonclassical information pattern. We present a two-sided (simultaneous) optimization solution method for the two-player linear quadratic Gaussian (LQG) multistage game. This direct solution method allows for further interpretation of each player's decision making (strategy) as compared to previously used formal solution methods. In addition to the optimal control strategies, we present a saddle point proof and we derive an expression for the optimal performance index value. We provide some numerical results in order to further interpret the optimal control strategies and to highlight real-world application of this game-theoretic optimal solution.

Many faces of rationality: Implications of the great rationality debate for clinical decision‐making

PubMed Central

Elqayam, Shira

2017-01-01

Abstract Given that more than 30% of healthcare costs are wasted on inappropriate care, suboptimal care is increasingly connected to the quality of medical decisions. It has been argued that personal decisions are the leading cause of death, and 80% of healthcare expenditures result from physicians' decisions. Therefore, improving healthcare necessitates improving medical decisions, ie, making decisions (more) rational. Drawing on writings from The Great Rationality Debate from the fields of philosophy, economics, and psychology, we identify core ingredients of rationality commonly encountered across various theoretical models. Rationality is typically classified under umbrella of normative (addressing the question how people “should” or “ought to” make their decisions) and descriptive theories of decision‐making (which portray how people actually make their decisions). Normative theories of rational thought of relevance to medicine include epistemic theories that direct practice of evidence‐based medicine and expected utility theory, which provides the basis for widely used clinical decision analyses. Descriptive theories of rationality of direct relevance to medical decision‐making include bounded rationality, argumentative theory of reasoning, adaptive rationality, dual processing model of rationality, regret‐based rationality, pragmatic/substantive rationality, and meta‐rationality. For the first time, we provide a review of wide range of theories and models of rationality. We showed that what is “rational” behaviour under one rationality theory may be irrational under the other theory. We also showed that context is of paramount importance to rationality and that no one model of rationality can possibly fit all contexts. We suggest that in context‐poor situations, such as policy decision‐making, normative theories based on expected utility informed by best research evidence may provide the optimal approach to medical decision‐making, whereas in the context‐rich circumstances other types of rationality, informed by human cognitive architecture and driven by intuition and emotions such as the aim to minimize regret, may provide better solution to the problem at hand. The choice of theory under which we operate is important as it determines both policy and our individual decision‐making. PMID:28730671

Three essays on multi-level optimization models and applications

NASA Astrophysics Data System (ADS)

Rahdar, Mohammad

The general form of a multi-level mathematical programming problem is a set of nested optimization problems, in which each level controls a series of decision variables independently. However, the value of decision variables may also impact the objective function of other levels. A two-level model is called a bilevel model and can be considered as a Stackelberg game with a leader and a follower. The leader anticipates the response of the follower and optimizes its objective function, and then the follower reacts to the leader's action. The multi-level decision-making model has many real-world applications such as government decisions, energy policies, market economy, network design, etc. However, there is a lack of capable algorithms to solve medium and large scale these types of problems. The dissertation is devoted to both theoretical research and applications of multi-level mathematical programming models, which consists of three parts, each in a paper format. The first part studies the renewable energy portfolio under two major renewable energy policies. The potential competition for biomass for the growth of the renewable energy portfolio in the United States and other interactions between two policies over the next twenty years are investigated. This problem mainly has two levels of decision makers: the government/policy makers and biofuel producers/electricity generators/farmers. We focus on the lower-level problem to predict the amount of capacity expansions, fuel production, and power generation. In the second part, we address uncertainty over demand and lead time in a multi-stage mathematical programming problem. We propose a two-stage tri-level optimization model in the concept of rolling horizon approach to reducing the dimensionality of the multi-stage problem. In the third part of the dissertation, we introduce a new branch and bound algorithm to solve bilevel linear programming problems. The total time is reduced by solving a smaller relaxation problem in each node and decreasing the number of iterations. Computational experiments show that the proposed algorithm is faster than the existing ones.

Some economics on personalized and predictive medicine.

PubMed

Antoñanzas, F; Juárez-Castelló, C A; Rodríguez-Ibeas, R

2015-12-01

To contribute to the theoretical literature on personalized medicine, analyzing and integrating in an economic model, the decision a health authority faces when it must decide on the implementation of personalized medicine in a context of uncertainty. We carry out a stylized model to analyze the decision health authorities face when they do not have perfect information about the best treatment for a population of patients with a given disease. The health authorities decide whether to use a test to match patients with treatments (personalized medicine) to maximize health outcomes. Our model characterizes the situations under which personalized medicine dominates the alternative option of business-as-usual (treatment without previous test). We apply the model to the KRAS test for colorectal cancer, the PCA3 test for prostate cancer and the PCR test for the X-fragile syndrome, to illustrate how the parameters and variables of the model interact. Implementation of personalized medicine requires, as a necessary condition, having some tests with high discriminatory power. This is not a sufficient condition and expected health outcomes must be taken into account to make a decision. When the specificity and the sensitivity of the test are low, the health authority prefers to apply a treatment to all patients without using the test. When both characteristic of the test are high, the health authorities prefer to personalize the treatments when expected health outcomes are better than those under the standard treatment. When we applied the model to the three aforementioned tests, the results illustrate how decisions are adopted in real world. Although promising, the use of personalized medicine is still under scrutiny as there are important issues demanding a response. Personalized medicine may have an impact in the drug development processes, and contribute to the efficiency and effectiveness of health care delivery. Nevertheless, more accurate statistical and economic information related to tests results and treatment costs as well as additional medical information on the efficacy of the treatments are needed to adopt decisions that incorporate economic rationality.

Theoretical basis of the DOE-2 building energy use analysis program

NASA Astrophysics Data System (ADS)

Curtis, R. B.

1981-04-01

A user-oriented, public domain, computer program was developed that will enable architects and engineers to perform design and retrofit studies of the energy-use of buildings under realistic weather conditions. The DOE-2.1A has been named by the US DOE as the standard evaluation technique for the Congressionally mandated building energy performance standards (BEPS). A number of program design decisions were made that determine the breadth of applicability of DOE-2.1. Such design decisions are intrinsic to all building energy use analysis computer programs and determine the types of buildings or the kind of HVAC systems that can be modeled. In particular, the weighting factor method used in DOE-2 has both advantages and disadvantages relative to other computer programs.

Application of household production theory to selected natural-resource problems in less-developed countries

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mercer, D.E.

The objectives are threefold: (1) to perform an analytical survey of household production theory as it relates to natural-resource problems in less-developed countries, (2) to develop a household production model of fuelwood decision making, (3) to derive a theoretical framework for travel-cost demand studies of international nature tourism. The model of household fuelwood decision making provides a rich array of implications and predictions for empirical analysis. For example, it is shown that fuelwood and modern fuels may be either substitutes or complements depending on the interaction of the gross-substitution and income-expansion effects. Therefore, empirical analysis should precede adoption of anymore » inter-fuel substitution policies such as subsidizing kerosene. The fuelwood model also provides a framework for analyzing the conditions and factors determining entry and exit by households into the wood-burning subpopulation, a key for designing optimal household energy policies in the Third World. The international nature tourism travel cost model predicts that the demand for nature tourism is an aggregate of the demand for the individual activities undertaken during the trip.« less

Robust allocation of a defensive budget considering an attacker's private information.

PubMed

Nikoofal, Mohammad E; Zhuang, Jun

2012-05-01

Attackers' private information is one of the main issues in defensive resource allocation games in homeland security. The outcome of a defense resource allocation decision critically depends on the accuracy of estimations about the attacker's attributes. However, terrorists' goals may be unknown to the defender, necessitating robust decisions by the defender. This article develops a robust-optimization game-theoretical model for identifying optimal defense resource allocation strategies for a rational defender facing a strategic attacker while the attacker's valuation of targets, being the most critical attribute of the attacker, is unknown but belongs to bounded distribution-free intervals. To our best knowledge, no previous research has applied robust optimization in homeland security resource allocation when uncertainty is defined in bounded distribution-free intervals. The key features of our model include (1) modeling uncertainty in attackers' attributes, where uncertainty is characterized by bounded intervals; (2) finding the robust-optimization equilibrium for the defender using concepts dealing with budget of uncertainty and price of robustness; and (3) applying the proposed model to real data. © 2011 Society for Risk Analysis.

A stochastic equilibrium model for the North American natural gas market

NASA Astrophysics Data System (ADS)

Zhuang, Jifang

This dissertation is an endeavor in the field of energy modeling for the North American natural gas market using a mixed complementarity formulation combined with the stochastic programming. The genesis of the stochastic equilibrium model presented in this dissertation is the deterministic market equilibrium model developed in [Gabriel, Kiet and Zhuang, 2005]. Based on some improvements that we made to this model, including proving new existence and uniqueness results, we present a multistage stochastic equilibrium model with uncertain demand for the deregulated North American natural gas market using the recourse method of the stochastic programming. The market participants considered by the model are pipeline operators, producers, storage operators, peak gas operators, marketers and consumers. Pipeline operators are described with regulated tariffs but also involve "congestion pricing" as a mechanism to allocate scarce pipeline capacity. Marketers are modeled as Nash-Cournot players in sales to the residential and commercial sectors but price-takers in all other aspects. Consumers are represented by demand functions in the marketers' problem. Producers, storage operators and peak gas operators are price-takers consistent with perfect competition. Also, two types of the natural gas markets are included: the long-term and spot markets. Market participants make both high-level planning decisions (first-stage decisions) in the long-term market and daily operational decisions (recourse decisions) in the spot market subject to their engineering, resource and political constraints, resource constraints as well as market constraints on both the demand and the supply side, so as to simultaneously maximize their expected profits given others' decisions. The model is shown to be an instance of a mixed complementarity problem (MiCP) under minor conditions. The MiCP formulation is derived from applying the Karush-Kuhn-Tucker optimality conditions of the optimization problems faced by the market participants. Some theoretical results regarding the market prices in both markets are shown. We also illustrate the model on a representative, sample network of two production nodes, two consumption nodes with discretely distributed end-user demand and three seasons using four cases.

The Hare and the Tortoise: Emphasizing Speed Can Change the Evidence Used to Make Decisions

ERIC Educational Resources Information Center

Rae, Babette; Heathcote, Andrew; Donkin, Chris; Averell, Lee; Brown, Scott

2014-01-01

Decision-makers effortlessly balance the need for urgency against the need for caution. Theoretical and neurophysiological accounts have explained this tradeoff solely in terms of the "quantity" of evidence required to trigger a decision (the "threshold"). This explanation has also been used as a benchmark test for evaluating…

Teacher Participation in Curriculum and Pedagogical Decisions: Insights into Curriculum Leadership

ERIC Educational Resources Information Center

Ho, Dora Choi Wa

2010-01-01

In recent years, teacher participation in school decision making has become an important topic for discussion in the field of early childhood education in Hong Kong. The purpose of this article is to discuss the theoretical significance, difficulties and issues of greater teacher participation in curriculum and pedagogical decision making in local…

Assessing the Influence of Farm Women's Self-Identity on Task Allocation and Decision Making.

ERIC Educational Resources Information Center

Bokemeier, Janet; Garkovich, Lorraine

1987-01-01

Uses data from survey of 880 Kentucky farm women to present theoretical framework integrating microsocial, household economy, and farm structural perspectives to explain gender allocation of farm-specific tasks and decision making. Finds self-identity validated by participation in farm tasks/decision making, but, overall, women indicate low levels…

Determinants of Thailand household healthcare expenditure: the relevance of permanent resources and other correlates.

PubMed

Okunade, Albert A; Suraratdecha, Chutima; Benson, David A

2010-03-01

Several papers in the leading health economics journals modeled the determinants of healthcare expenditure using household survey or family budgets data of developed countries. Past work largely used self-reported current income as the core determinant, whereas the theoretically correct concept of household resource constraint is permanent or long-run income (á lá Milton Friedman). This paper strives to rectify the theoretical oversight of using current income by augmenting the model with household asset. Using longitudinal data, we constructed 'wealth index' as a distinct covariate to capture the households' tendency to liquidate assets when defraying necessary healthcare liabilities after exhausting cash incomes. (Current income and assets together capture the household expanded resource base). Using 98 632 household observations from Thailand Socio-Economic Surveys (1994-2000 biennial data cycles) we found, using a double-hurdle model with dependent errors, that out-of-pocket healthcare spending behaves as a technical necessity across income quintiles and household sizes. Pre-1997 economic shock income elasticities are smaller than the post-shock estimates across income quintiles for large and small households. Proximity to death, median age, and assets are also among other significant determinants. Our novel findings extend the theoretical consistency of a multi-level decision model in household healthcare expenditure in the developing Asian country context. (c) 2009 John Wiley & Sons, Ltd.

Seeking for the rational basis of the median model: the optimal combination of multi-model ensemble results

NASA Astrophysics Data System (ADS)

Riccio, A.; Giunta, G.; Galmarini, S.

2007-04-01

In this paper we present an approach for the statistical analysis of multi-model ensemble results. The models considered here are operational long-range transport and dispersion models, also used for the real-time simulation of pollutant dispersion or the accidental release of radioactive nuclides. We first introduce the theoretical basis (with its roots sinking into the Bayes theorem) and then apply this approach to the analysis of model results obtained during the ETEX-1 exercise. We recover some interesting results, supporting the heuristic approach called "median model", originally introduced in Galmarini et al. (2004a, b). This approach also provides a way to systematically reduce (and quantify) model uncertainties, thus supporting the decision-making process and/or regulatory-purpose activities in a very effective manner.

Seeking for the rational basis of the Median Model: the optimal combination of multi-model ensemble results

NASA Astrophysics Data System (ADS)

Riccio, A.; Giunta, G.; Galmarini, S.

2007-12-01

In this paper we present an approach for the statistical analysis of multi-model ensemble results. The models considered here are operational long-range transport and dispersion models, also used for the real-time simulation of pollutant dispersion or the accidental release of radioactive nuclides. We first introduce the theoretical basis (with its roots sinking into the Bayes theorem) and then apply this approach to the analysis of model results obtained during the ETEX-1 exercise. We recover some interesting results, supporting the heuristic approach called "median model", originally introduced in Galmarini et al. (2004a, b). This approach also provides a way to systematically reduce (and quantify) model uncertainties, thus supporting the decision-making process and/or regulatory-purpose activities in a very effective manner.

A theoretical framework for measuring knowledge in screening decision aid trials.

PubMed

Smith, Sian K; Barratt, Alexandra; Trevena, Lyndal; Simpson, Judy M; Jansen, Jesse; McCaffery, Kirsten J

2012-11-01

To describe a theoretical framework for assessing knowledge about the possible outcomes of participating in bowel cancer screening for the faecal occult blood test. The content of the knowledge measure was based on the UK General Medical Council's screening guidelines and a theory-based approach to assessing gist knowledge (Fuzzy Trace Theory). It comprised conceptual and numeric questions to assess knowledge of the underlying construct (e.g. false positive concept) and the approximate numbers affected (e.g. likelihood of a false positive). The measure was used in a randomised controlled trial involving 530 adults with low education, to compare the impact of a bowel screening decision aid with a screening information booklet developed for the Australian Government National Bowel Cancer Screening Program. The numeric knowledge scale was particularly responsive to the effects of the decision aid; at follow-up decision aid participants' numeric knowledge was significantly greater than the controls (P<0.001). This contrasts with the conceptual knowledge scale which improved significantly in both groups from baseline to follow-up (P<0.001). Our theory-based knowledge measure was responsive to change in conceptual knowledge and to the effect on numeric knowledge of a decision aid. This theoretical framework has the potential to guide the development of knowledge measures in other screening settings. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Combining statistical inference and decisions in ecology.

PubMed

Williams, Perry J; Hooten, Mevin B

2016-09-01

Statistical decision theory (SDT) is a sub-field of decision theory that formally incorporates statistical investigation into a decision-theoretic framework to account for uncertainties in a decision problem. SDT provides a unifying analysis of three types of information: statistical results from a data set, knowledge of the consequences of potential choices (i.e., loss), and prior beliefs about a system. SDT links the theoretical development of a large body of statistical methods, including point estimation, hypothesis testing, and confidence interval estimation. The theory and application of SDT have mainly been developed and published in the fields of mathematics, statistics, operations research, and other decision sciences, but have had limited exposure in ecology. Thus, we provide an introduction to SDT for ecologists and describe its utility for linking the conventionally separate tasks of statistical investigation and decision making in a single framework. We describe the basic framework of both Bayesian and frequentist SDT, its traditional use in statistics, and discuss its application to decision problems that occur in ecology. We demonstrate SDT with two types of decisions: Bayesian point estimation and an applied management problem of selecting a prescribed fire rotation for managing a grassland bird species. Central to SDT, and decision theory in general, are loss functions. Thus, we also provide basic guidance and references for constructing loss functions for an SDT problem. © 2016 by the Ecological Society of America.

Modeling insurer-homeowner interactions in managing natural disaster risk.

PubMed

Kesete, Yohannes; Peng, Jiazhen; Gao, Yang; Shan, Xiaojun; Davidson, Rachel A; Nozick, Linda K; Kruse, Jamie

2014-06-01

The current system for managing natural disaster risk in the United States is problematic for both homeowners and insurers. Homeowners are often uninsured or underinsured against natural disaster losses, and typically do not invest in retrofits that can reduce losses. Insurers often do not want to insure against these losses, which are some of their biggest exposures and can cause an undesirably high chance of insolvency. There is a need to design an improved system that acknowledges the different perspectives of the stakeholders. In this article, we introduce a new modeling framework to help understand and manage the insurer's role in catastrophe risk management. The framework includes a new game-theoretic optimization model of insurer decisions that interacts with a utility-based homeowner decision model and is integrated with a regional catastrophe loss estimation model. Reinsurer and government roles are represented as bounds on the insurer-insured interactions. We demonstrate the model for a full-scale case study for hurricane risk to residential buildings in eastern North Carolina; present the results from the perspectives of all stakeholders-primary insurers, homeowners (insured and uninsured), and reinsurers; and examine the effect of key parameters on the results. © 2014 Society for Risk Analysis.

Eliciting expert opinion for economic models: an applied example.

PubMed

Leal, José; Wordsworth, Sarah; Legood, Rosa; Blair, Edward

2007-01-01

Expert opinion is considered as a legitimate source of information for decision-analytic modeling where required data are unavailable. Our objective was to develop a practical computer-based tool for eliciting expert opinion about the shape of the uncertainty distribution around individual model parameters. We first developed a prepilot survey with departmental colleagues to test a number of alternative approaches to eliciting opinions on the shape of the uncertainty distribution around individual parameters. This information was used to develop a survey instrument for an applied clinical example. This involved eliciting opinions from experts to inform a number of parameters involving Bernoulli processes in an economic model evaluating DNA testing for families with a genetic disease, hypertrophic cardiomyopathy. The experts were cardiologists, clinical geneticists, and laboratory scientists working with cardiomyopathy patient populations and DNA testing. Our initial prepilot work suggested that the more complex elicitation techniques advocated in the literature were difficult to use in practice. In contrast, our approach achieved a reasonable response rate (50%), provided logical answers, and was generally rated as easy to use by respondents. The computer software user interface permitted graphical feedback throughout the elicitation process. The distributions obtained were incorporated into the model, enabling the use of probabilistic sensitivity analysis. There is clearly a gap in the literature between theoretical elicitation techniques and tools that can be used in applied decision-analytic models. The results of this methodological study are potentially valuable for other decision analysts deriving expert opinion.

Structural Equation Model Trees

PubMed Central

Brandmaier, Andreas M.; von Oertzen, Timo; McArdle, John J.; Lindenberger, Ulman

2015-01-01

In the behavioral and social sciences, structural equation models (SEMs) have become widely accepted as a modeling tool for the relation between latent and observed variables. SEMs can be seen as a unification of several multivariate analysis techniques. SEM Trees combine the strengths of SEMs and the decision tree paradigm by building tree structures that separate a data set recursively into subsets with significantly different parameter estimates in a SEM. SEM Trees provide means for finding covariates and covariate interactions that predict differences in structural parameters in observed as well as in latent space and facilitate theory-guided exploration of empirical data. We describe the methodology, discuss theoretical and practical implications, and demonstrate applications to a factor model and a linear growth curve model. PMID:22984789

Evidence - competence - discourse: the theoretical framework of the multi-centre clinical ethics support project METAP.

PubMed

Reiter-Theil, Stella; Mertz, Marcel; Schürmann, Jan; Stingelin Giles, Nicola; Meyer-Zehnder, Barbara

2011-09-01

In this paper we assume that 'theory' is important for Clinical Ethics Support Services (CESS). We will argue that the underlying implicit theory should be reflected. Moreover, we suggest that the theoretical components on which any clinical ethics support (CES) relies should be explicitly articulated in order to enhance the quality of CES. A theoretical framework appropriate for CES will be necessarily complex and should include ethical (both descriptive and normative), metaethical and organizational components. The various forms of CES that exist in North-America and in Europe show their underlying theory more or less explicitly, with most of them referring to some kind of theoretical components including 'how-to' questions (methodology), organizational issues (implementation), problem analysis (phenomenology or typology of problems), and related ethical issues such as end-of-life decisions (major ethical topics). In order to illustrate and explain the theoretical framework that we are suggesting for our own CES project METAP, we will outline this project which has been established in a multi-centre context in several healthcare institutions. We conceptualize three 'pillars' as the major components of our theoretical framework: (1) evidence, (2) competence, and (3) discourse. As a whole, the framework is aimed at developing a foundation of our CES project METAP. We conclude that this specific integration of theoretical components is a promising model for the fruitful further development of CES. © 2011 Blackwell Publishing Ltd.

Research-based-decision-making in Canadian health organizations: a behavioural approach.

PubMed

Jbilou, Jalila; Amara, Nabil; Landry, Réjean

2007-06-01

Decision making in Health sector is affected by a several elements such as economic constraints, political agendas, epidemiologic events, managers' values and environment... These competing elements create a complex environment for decision making. Research-Based-Decision-Making (RBDM) offers an opportunity to reduce the generated uncertainty and to ensure efficacy and efficiency in health administrations. We assume that RBDM is dependant on decision makers' behaviour and the identification of the determinants of this behaviour can help to enhance research results utilization in health sector decision making. This paper explores the determinants of RBDM as a personal behaviour among managers and professionals in health administrations in Canada. From the behavioural theories and the existing literature, we build a model measuring "RBDM" as an index based on five items. These items refer to the steps accomplished by a decision maker while developing a decision which is based on evidence. The determinants of RBDM behaviour are identified using data collected from 942 health care decision makers in Canadian health organizations. Linear regression is used to model the behaviour RBDM. Determinants of this behaviour are derived from Triandis Theory and Bandura's construct "self-efficacy." The results suggest that to improve research use among managers in Canadian governmental health organizations, strategies should focus on enhancing exposition to evidence through facilitating communication networks, partnerships and links between researchers and decision makers, with the key long-term objective of developing a culture that supports and values the contribution that research can make to decision making in governmental health organizations. Nevertheless, depending on the organizational level, determinants of RBDM are different. This difference has to be taken into account if RBDM adoption is desired. Decision makers in Canadian health organizations (CHO) can help to build networks, develop partnerships between professionals locally, regionally and nationally, and also act as change agents in the dissemination and adoption of knowledge and innovations in health services. However, the research focused on knowledge use as a support to decision-making, further research is needed to identify and evaluate effective incentives and strategies to implement so as to enhance RBDM adoption among health decision makers and more theoretical development are to complete in this perspective.

Model-based decision making in early clinical development: minimizing the impact of a blood pressure adverse event.

PubMed

Stroh, Mark; Addy, Carol; Wu, Yunhui; Stoch, S Aubrey; Pourkavoos, Nazaneen; Groff, Michelle; Xu, Yang; Wagner, John; Gottesdiener, Keith; Shadle, Craig; Wang, Hong; Manser, Kimberly; Winchell, Gregory A; Stone, Julie A

2009-03-01

We describe how modeling and simulation guided program decisions following a randomized placebo-controlled single-rising oral dose first-in-man trial of compound A where an undesired transient blood pressure (BP) elevation occurred in fasted healthy young adult males. We proposed a lumped-parameter pharmacokinetic-pharmacodynamic (PK/PD) model that captured important aspects of the BP homeostasis mechanism. Four conceptual units characterized the feedback PD model: a sinusoidal BP set point, an effect compartment, a linear effect model, and a system response. To explore approaches for minimizing the BP increase, we coupled the PD model to a modified PK model to guide oral controlled-release (CR) development. The proposed PK/PD model captured the central tendency of the observed data. The simulated BP response obtained with theoretical release rate profiles suggested some amelioration of the peak BP response with CR. This triggered subsequent CR formulation development; we used actual dissolution data from these candidate CR formulations in the PK/PD model to confirm a potential benefit in the peak BP response. Though this paradigm has yet to be tested in the clinic, our model-based approach provided a common rational framework to more fully utilize the limited available information for advancing the program.

Trait urgency and gambling problems in young people by age: the mediating role of decision-making processes.

PubMed

Canale, Natale; Vieno, Alessio; Griffiths, Mark D; Rubaltelli, Enrico; Santinello, Massimo

2015-07-01

Although the personality trait of urgency has been linked to problem gambling, less is known about psychological mechanisms that mediate the relationship between urgency and problem gambling. One individual variable of potential relevance to impulsivity and addictive disorders is age. The aims of this study were to examine: (i) a theoretical model associating urgency and gambling problems, (ii) the mediating effects of decision-making processes (operationalized as preference for small/immediate rewards and lower levels of deliberative decision-making); and (iii) age differences in these relationships. Participants comprised 986 students (64% male; mean age=19.51 years; SD=2.30) divided into three groups: 16-17 years, 18-21 years, and 22-25 years. All participants completed measures of urgency, problem gambling, and a delay-discounting questionnaire involving choices between a smaller amount of money received immediately and a larger amount of money received later. Participants were also asked to reflect on their decision-making process. Compared to those aged 16-17 years and 22-25 years, participants aged 18-21 years had a higher level of gambling problems and decreased scores on lower levels of deliberative decision-making. Higher levels of urgency were associated with higher levels of gambling problems. The association was mediated by a lower level of deliberative decision-making and preference for an immediate/small reward. A distinct pathway was observed for lower levels of deliberative decision-making. Young people who tend to act rashly in response to extreme moods, had lower levels of deliberative decision-making, that in turn were positively related to gambling problems. This study highlights unique decision-making pathways through which urgency trait may operate, suggesting that those developing prevention and/or treatment strategies may want to consider the model's variables, including urgency, delay discounting, and deliberative decision-making. Copyright © 2015 Elsevier Ltd. All rights reserved.

Optimizing the response to surveillance alerts in automated surveillance systems.

PubMed

Izadi, Masoumeh; Buckeridge, David L

2011-02-28

Although much research effort has been directed toward refining algorithms for disease outbreak alerting, considerably less attention has been given to the response to alerts generated from statistical detection algorithms. Given the inherent inaccuracy in alerting, it is imperative to develop methods that help public health personnel identify optimal policies in response to alerts. This study evaluates the application of dynamic decision making models to the problem of responding to outbreak detection methods, using anthrax surveillance as an example. Adaptive optimization through approximate dynamic programming is used to generate a policy for decision making following outbreak detection. We investigate the degree to which the model can tolerate noise theoretically, in order to keep near optimal behavior. We also evaluate the policy from our model empirically and compare it with current approaches in routine public health practice for investigating alerts. Timeliness of outbreak confirmation and total costs associated with the decisions made are used as performance measures. Using our approach, on average, 80 per cent of outbreaks were confirmed prior to the fifth day of post-attack with considerably less cost compared to response strategies currently in use. Experimental results are also provided to illustrate the robustness of the adaptive optimization approach and to show the realization of the derived error bounds in practice. Copyright © 2011 John Wiley & Sons, Ltd.

Relationship between impulsivity and decision-making in cocaine dependence

PubMed Central

Kjome, Kimberly L.; Lane, Scott D.; Schmitz, Joy M.; Green, Charles; Ma, Liangsuo; Prasla, Irshad; Swann, Alan C.; Moeller, F. Gerard

2010-01-01

Impulsivity and decision-making are associated on a theoretical level in that impaired planning is a component of both. However, few studies have examined the relationship between measures of decision-making and impulsivity in clinical populations. The purpose of this study was to compare cocaine-dependent subjects to controls on a measure of decision-making (the Iowa Gambling Task or IGT), a questionnaire measure of impulsivity (the Barratt Impulsiveness Scale or BIS-11), and a measure of behavioral inhibition (the immediate memory task or IMT), and to examine the interrelationship among these measures. Results of the study showed that cocaine-dependent subjects made more disadvantageous choices on the IGT, had higher scores on the BIS, and more commission errors on the IMT. Cognitive model analysis showed that choice consistency factors on the IGT differed between cocaine-dependent subjects and controls. However, there was no significant correlation between IGT performance and the BIS total score or subscales or IMT commission errors. These results suggest that in cocaine dependent subjects there is little overlap between decision-making as measured by the IGT and impulsivity/behavioral inhibition as measured by the BIS and IMT. PMID:20478631

To kill a kangaroo: understanding the decision to pursue high-risk/high-gain resources.

PubMed

Jones, James Holland; Bird, Rebecca Bliege; Bird, Douglas W

2013-09-22

In this paper, we attempt to understand hunter-gatherer foraging decisions about prey that vary in both the mean and variance of energy return using an expected utility framework. We show that for skewed distributions of energetic returns, the standard linear variance discounting (LVD) model for risk-sensitive foraging can produce quite misleading results. In addition to creating difficulties for the LVD model, the skewed distributions characteristic of hunting returns create challenges for estimating probability distribution functions required for expected utility. We present a solution using a two-component finite mixture model for foraging returns. We then use detailed foraging returns data based on focal follows of individual hunters in Western Australia hunting for high-risk/high-gain (hill kangaroo) and relatively low-risk/low-gain (sand monitor) prey. Using probability densities for the two resources estimated from the mixture models, combined with theoretically sensible utility curves characterized by diminishing marginal utility for the highest returns, we find that the expected utility of the sand monitors greatly exceeds that of kangaroos despite the fact that the mean energy return for kangaroos is nearly twice as large as that for sand monitors. We conclude that the decision to hunt hill kangaroos does not arise simply as part of an energetic utility-maximization strategy and that additional social, political or symbolic benefits must accrue to hunters of this highly variable prey.

Expected utility violations evolve under status-based selection mechanisms.

PubMed

Dickson, Eric S

2008-10-07

The expected utility theory of decision making under uncertainty, a cornerstone of modern economics, assumes that humans linearly weight "utilities" for different possible outcomes by the probabilities with which these outcomes occur. Despite the theory's intuitive appeal, both from normative and from evolutionary perspectives, many experiments demonstrate systematic, though poorly understood, patterns of deviation from EU predictions. This paper offers a novel theoretical account of such patterns of deviation by demonstrating that EU violations can emerge from evolutionary selection when individual "status" affects inclusive fitness. In humans, battles for resources and social standing involve high-stakes decision making, and assortative mating ensures that status matters for fitness outcomes. The paper therefore proposes grounding the study of decision making under uncertainty in an evolutionary game-theoretic framework.

Decision-Theoretic Control of Planetary Rovers

NASA Technical Reports Server (NTRS)

Zilberstein, Shlomo; Washington, Richard; Bernstein, Daniel S.; Mouaddib, Abdel-Illah; Morris, Robert (Technical Monitor)

2003-01-01

Planetary rovers are small unmanned vehicles equipped with cameras and a variety of sensors used for scientific experiments. They must operate under tight constraints over such resources as operation time, power, storage capacity, and communication bandwidth. Moreover, the limited computational resources of the rover limit the complexity of on-line planning and scheduling. We describe two decision-theoretic approaches to maximize the productivity of planetary rovers: one based on adaptive planning and the other on hierarchical reinforcement learning. Both approaches map the problem into a Markov decision problem and attempt to solve a large part of the problem off-line, exploiting the structure of the plan and independence between plan components. We examine the advantages and limitations of these techniques and their scalability.

Child welfare organizations: Do specialization and service integration impact placement decisions?

PubMed

Smith, Carrie; Fluke, John; Fallon, Barbara; Mishna, Faye; Decker Pierce, Barbara

2018-02-01

The objective of this study was to contribute to the understanding of the child welfare organization by testing the hypothesis that the characteristics of organizations influence decisions made by child protection staff for vulnerable children. The influence of two aspects of organizational structure on the decision to place a child in out-of-home care were examined: service integration and worker specialization. A theoretical framework that integrated the Decision-Making Ecology Framework (Baumann et al., 2011) and Yoo et al. (2007) conceptual framework of organizational constructs as predictors of service effectiveness was tested. Secondary data analysis of the Ontario Incidence Study of Reported Child Abuse and Neglect - 2013 (OIS-2013) was conducted. A subsample of 4949 investigations from 16 agencies was included in this study. Given the nested structure of the data, multi-level modelling was used to test the relative contribution of case and organizational factors to the decision to place. Despite the reported differences among child welfare organizations and research that has demonstrated variance in the placement decision as a result of organizational factors, the structure of the organization (i.e., worker specialization and service integration) showed no predictive power in the final models. The lack of variance may be explained by the relatively low frequency of placements during the investigation phase of service, the hierarchical impact of the factors of the DME and the limited information available regarding the structure of child welfare organizations in Ontario. Suggestions for future research are provided. Copyright © 2017 Elsevier Ltd. All rights reserved.

Employee decision-making about disclosure of a mental disorder at work.

PubMed

Toth, Kate E; Dewa, Carolyn S

2014-12-01

Fear of stigma may lead employees to choose not to disclose a mental disorder in the workplace, thereby limiting help-seeking through workplace accommodation. Research suggests that various factors are considered in making decisions related to disclosure of concealable stigmatizing attributes, yet limited literature explores such decision-making in the context of mental disorder and work. The purpose of this grounded theory study was to develop a model of disclosure specific to mental health issues in a work context. In-depth interviews were conducted with 13 employees of a post-secondary educational institution in Canada. Data were analyzed according to grounded theory methods through processes of open, selective, and theoretical coding. Findings indicated that employees begin from a default position of nondisclosure that is attributable to fear of being stigmatized in the workplace as a result of the mental disorder. In order to move from the default position, employees need a reason to disclose. The decision-making process itself is a risk-benefit analysis, during which employees weigh risks and benefits within the existing context as they assess it. The model identifies that fear of stigmatization is one of the problems with disclosure at work and describes the disclosure decision-making process. Understanding of how employees make decisions about disclosure in the workplace may inform organizational policies, practices, and programs to improve the experiences of individuals diagnosed with a mental disorder at work. The findings suggest possible intervention strategies in education, policy, and culture for reducing stigma of mental disorders in the workplace.

Decision Support from Genetic Algorithms for Ship Collision Avoidance Route Planning and Alerts

NASA Astrophysics Data System (ADS)

Tsou, Ming-Cheng; Kao, Sheng-Long; Su, Chien-Min

When an officer of the watch (OOW) faces complicated marine traffic, a suitable decision support tool could be employed in support of collision avoidance decisions, to reduce the burden and greatly improve the safety of marine traffic. Decisions on routes to avoid collisions could also consider economy as well as safety. Through simulating the biological evolution model, this research adopts the genetic algorithm used in artificial intelligence to find a theoretically safety-critical recommendation for the shortest route of collision avoidance from an economic viewpoint, combining the international regulations for preventing collisions at sea (COLREGS) and the safety domain of a ship. Based on this recommendation, an optimal safe avoidance turning angle, navigation restoration time and navigational restoration angle will also be provided. A Geographic Information System (GIS) will be used as the platform for display and operation. In order to achieve advance notice of alerts and due preparation for collision avoidance, a Vessel Traffic Services (VTS) operator and the OOW can use this system as a reference to assess collision avoidance at present location.

Creating Impact with Operations Research in Health: Making Room for Practice in Academia

PubMed Central

Brandeau, Margaret L.

2015-01-01

Operations research (OR)-based analyses have the potential to improve decision making for many important, real-world health care problems. However, junior scholars often avoid working on practical applications in health because promotion and tenure processes tend to value theoretical studies more highly than applied studies. This paper discusses the author's experiences in using OR to inform and influence decisions in health and provides a blueprint for junior researchers who wish to find success by taking a similar path. This involves selecting good problems to study, forming productive collaborations with domain experts, developing appropriate models, identifying the most salient results from an analysis, and effectively disseminating findings to decision makers. The paper then suggests how journals, funding agencies, and senior academics can encourage such work by taking a broader and more informed view of the potential role and contributions of OR to solving health care problems. Making room in academia for the application of OR in health follows in the tradition begun by the founders of operations research: to work on important real-world problems where operations research can contribute to better decision making. PMID:26003321

Individual versus Household Migration Decision Rules: Gender and Marital Status Differences in Intentions to Migrate in South Africa.

PubMed

Gubhaju, Bina; De Jong, Gordon F

2009-03-01

This research tests the thesis that the neoclassical micro-economic and the new household economic theoretical assumptions on migration decision-making rules are segmented by gender, marital status, and time frame of intention to migrate. Comparative tests of both theories within the same study design are relatively rare. Utilizing data from the Causes of Migration in South Africa national migration survey, we analyze how individually held "own-future" versus alternative "household well-being" migration decision rules effect the intentions to migrate of male and female adults in South Africa. Results from the gender and marital status specific logistic regressions models show consistent support for the different gender-marital status decision rule thesis. Specifically, the "maximizing one's own future" neoclassical microeconomic theory proposition is more applicable for never married men and women, the "maximizing household income" proposition for married men with short-term migration intentions, and the "reduce household risk" proposition for longer time horizon migration intentions of married men and women. Results provide new evidence on the way household strategies and individual goals jointly affect intentions to move or stay.

Testing adaptive toolbox models: a Bayesian hierarchical approach.

PubMed

Scheibehenne, Benjamin; Rieskamp, Jörg; Wagenmakers, Eric-Jan

2013-01-01

Many theories of human cognition postulate that people are equipped with a repertoire of strategies to solve the tasks they face. This theoretical framework of a cognitive toolbox provides a plausible account of intra- and interindividual differences in human behavior. Unfortunately, it is often unclear how to rigorously test the toolbox framework. How can a toolbox model be quantitatively specified? How can the number of toolbox strategies be limited to prevent uncontrolled strategy sprawl? How can a toolbox model be formally tested against alternative theories? The authors show how these challenges can be met by using Bayesian inference techniques. By means of parameter recovery simulations and the analysis of empirical data across a variety of domains (i.e., judgment and decision making, children's cognitive development, function learning, and perceptual categorization), the authors illustrate how Bayesian inference techniques allow toolbox models to be quantitatively specified, strategy sprawl to be contained, and toolbox models to be rigorously tested against competing theories. The authors demonstrate that their approach applies at the individual level but can also be generalized to the group level with hierarchical Bayesian procedures. The suggested Bayesian inference techniques represent a theoretical and methodological advancement for toolbox theories of cognition and behavior.

Patients' perception of their involvement in shared treatment decision making: Key factors in the treatment of inflammatory bowel disease.

PubMed

Veilleux, Sophie; Noiseux, Isabelle; Lachapelle, Nathalie; Kohen, Rita; Vachon, Luc; Guay, Brian White; Bitton, Alain; Rioux, John D

2018-02-01

This study aims to characterize the relationships between the quality of the information given by the physician, the involvement of the patient in shared decision making (SDM), and outcomes in terms of satisfaction and anxiety pertaining to the treatment of inflammatory bowel disease (IBD). A Web survey was conducted among 200 Canadian patients affected with IBD. The theoretical model of SDM was adjusted using path analysis. SAS software was used for all statistical analyses. The quality of the knowledge transfer between the physician and the patient is significantly associated with the components of SDM: information comprehension, patient involvement and decision certainty about the chosen treatment. In return, patient involvement in SDM is significantly associated with higher satisfaction and, as a result, lower anxiety as regards treatment selection. This study demonstrates the importance of involving patients in shared treatment decision making in the context of IBD. Understanding shared decision making may motivate patients to be more active in understanding the relevant information for treatment selection, as it is related to their level of satisfaction, anxiety and adherence to treatment. This relationship should encourage physicians to promote shared decision making. Copyright © 2017 Elsevier B.V. All rights reserved.

A Generalized Decision Framework Using Multi-objective Optimization for Water Resources Planning

NASA Astrophysics Data System (ADS)

Basdekas, L.; Stewart, N.; Triana, E.

2013-12-01

Colorado Springs Utilities (CSU) is currently engaged in an Integrated Water Resource Plan (IWRP) to address the complex planning scenarios, across multiple time scales, currently faced by CSU. The modeling framework developed for the IWRP uses a flexible data-centered Decision Support System (DSS) with a MODSIM-based modeling system to represent the operation of the current CSU raw water system coupled with a state-of-the-art multi-objective optimization algorithm. Three basic components are required for the framework, which can be implemented for planning horizons ranging from seasonal to interdecadal. First, a water resources system model is required that is capable of reasonable system simulation to resolve performance metrics at the appropriate temporal and spatial scales of interest. The system model should be an existing simulation model, or one developed during the planning process with stakeholders, so that 'buy-in' has already been achieved. Second, a hydrologic scenario tool(s) capable of generating a range of plausible inflows for the planning period of interest is required. This may include paleo informed or climate change informed sequences. Third, a multi-objective optimization model that can be wrapped around the system simulation model is required. The new generation of multi-objective optimization models do not require parameterization which greatly reduces problem complexity. Bridging the gap between research and practice will be evident as we use a case study from CSU's planning process to demonstrate this framework with specific competing water management objectives. Careful formulation of objective functions, choice of decision variables, and system constraints will be discussed. Rather than treating results as theoretically Pareto optimal in a planning process, we use the powerful multi-objective optimization models as tools to more efficiently and effectively move out of the inferior decision space. The use of this framework will help CSU evaluate tradeoffs in a continually changing world.

Conducting field studies for testing pesticide leaching models

USGS Publications Warehouse

Smith, Charles N.; Parrish, Rudolph S.; Brown, David S.

1990-01-01

A variety of predictive models are being applied to evaluate the transport and transformation of pesticides in the environment. These include well known models such as the Pesticide Root Zone Model (PRZM), the Risk of Unsaturated-Saturated Transport and Transformation Interactions for Chemical Concentrations Model (RUSTIC) and the Groundwater Loading Effects of Agricultural Management Systems Model (GLEAMS). The potentially large impacts of using these models as tools for developing pesticide management strategies and regulatory decisions necessitates development of sound model validation protocols. This paper offers guidance on many of the theoretical and practical problems encountered in the design and implementation of field-scale model validation studies. Recommendations are provided for site selection and characterization, test compound selection, data needs, measurement techniques, statistical design considerations and sampling techniques. A strategy is provided for quantitatively testing models using field measurements.

onlineDeCISion.org: a web-based decision aid for DCIS treatment.

PubMed

Ozanne, Elissa M; Schneider, Katharine H; Soeteman, Djøra; Stout, Natasha; Schrag, Deborah; Fordis, Michael; Punglia, Rinaa S

2015-11-01

Women diagnosed with DCIS face complex treatment decisions and often do so with inaccurate and incomplete understanding of the risks and benefits involved. Our objective was to create a tool to guide these decisions for both providers and patients. We developed a web-based decision aid designed to provide clinicians with tailored information about a patient’s recurrence risks and survival outcomes following different treatment strategies for DCIS. A theoretical framework, microsimulation model (Soeteman et al., J Natl Cancer 105:774–781, 2013) and best practices for web-based decision tools guided the development of the decision aid. The development process used semi-structured interviews and usability testing with key stakeholders, including a diverse group of multidisciplinary clinicians and a patient advocate. We developed onlineDeCISion.​org to include the following features that were rated as important by the stakeholders: (1) descriptions of each of the standard treatment options available; (2) visual projections of the likelihood of time-specific (10-year and lifetime) breast-preservation, recurrence, and survival outcomes; and (3) side-by-side comparisons of down-stream effects of each treatment choice. All clinicians reviewing the decision aid in usability testing were interested in using it in their clinical practice. The decision aid is available in a web-based format and is planned to be publicly available. To improve treatment decision making in patients with DCIS, we have developed a web-based decision aid onlineDeCISion.​org that conforms to best practices and that clinicians are interested in using in their clinics with patients to better inform treatment decisions.

On the suitability of fast and frugal heuristics for designing values clarification methods in patient decision aids: a critical analysis.

PubMed

Pieterse, Arwen H; de Vries, Marieke

2013-09-01

Increasingly, patient decision aids and values clarification methods (VCMs) are being developed to support patients in making preference-sensitive health-care decisions. Many VCMs encourage extensive deliberation about options, without solid theoretical or empirical evidence showing that deliberation is advantageous. Research suggests that simple, fast and frugal heuristic decision strategies sometimes result in better judgments and decisions. Durand et al. have developed two fast and frugal heuristic-based VCMs. To critically analyse the suitability of the 'take the best' (TTB) and 'tallying' fast and frugal heuristics in the context of patient decision making. Analysis of the structural similarities between the environments in which the TTB and tallying heuristics have been proven successful and the context of patient decision making and of the potential of these heuristic decision processes to support patient decision making. The specific nature of patient preference-sensitive decision making does not seem to resemble environments in which the TTB and tallying heuristics have proven successful. Encouraging patients to consider less rather than more relevant information potentially even deteriorates their values clarification process. Values clarification methods promoting the use of more intuitive decision strategies may sometimes be more effective. Nevertheless, we strongly recommend further theoretical thinking about the expected value of such heuristics and of other more intuitive decision strategies in this context, as well as empirical assessments of the mechanisms by which inducing such decision strategies may impact the quality and outcome of values clarification. © 2011 John Wiley & Sons Ltd.

On the suitability of fast and frugal heuristics for designing values clarification methods in patient decision aids: a critical analysis

PubMed Central

Pieterse, Arwen H.; de Vries, Marieke

2011-01-01

Abstract Background  Increasingly, patient decision aids and values clarification methods (VCMs) are being developed to support patients in making preference‐sensitive health‐care decisions. Many VCMs encourage extensive deliberation about options, without solid theoretical or empirical evidence showing that deliberation is advantageous. Research suggests that simple, fast and frugal heuristic decision strategies sometimes result in better judgments and decisions. Durand et al. have developed two fast and frugal heuristic‐based VCMs. Objective  To critically analyse the suitability of the ‘take the best’ (TTB) and ‘tallying’ fast and frugal heuristics in the context of patient decision making. Strategy  Analysis of the structural similarities between the environments in which the TTB and tallying heuristics have been proven successful and the context of patient decision making and of the potential of these heuristic decision processes to support patient decision making. Conclusion  The specific nature of patient preference‐sensitive decision making does not seem to resemble environments in which the TTB and tallying heuristics have proven successful. Encouraging patients to consider less rather than more relevant information potentially even deteriorates their values clarification process. Values clarification methods promoting the use of more intuitive decision strategies may sometimes be more effective. Nevertheless, we strongly recommend further theoretical thinking about the expected value of such heuristics and of other more intuitive decision strategies in this context, as well as empirical assessments of the mechanisms by which inducing such decision strategies may impact the quality and outcome of values clarification. PMID:21902770

Cognitive Systems Modeling and Analysis of Command and Control Systems

NASA Technical Reports Server (NTRS)

Norlander, Arne

2012-01-01

Military operations, counter-terrorism operations and emergency response often oblige operators and commanders to operate within distributed organizations and systems for safe and effective mission accomplishment. Tactical commanders and operators frequently encounter violent threats and critical demands on cognitive capacity and reaction time. In the future they will make decisions in situations where operational and system characteristics are highly dynamic and non-linear, i.e. minor events, decisions or actions may have serious and irreversible consequences for the entire mission. Commanders and other decision makers must manage true real time properties at all levels; individual operators, stand-alone technical systems, higher-order integrated human-machine systems and joint operations forces alike. Coping with these conditions in performance assessment, system development and operational testing is a challenge for both practitioners and researchers. This paper reports on research from which the results led to a breakthrough: An integrated approach to information-centered systems analysis to support future command and control systems research development. This approach integrates several areas of research into a coherent framework, Action Control Theory (ACT). It comprises measurement techniques and methodological advances that facilitate a more accurate and deeper understanding of the operational environment, its agents, actors and effectors, generating new and updated models. This in turn generates theoretical advances. Some good examples of successful approaches are found in the research areas of cognitive systems engineering, systems theory, and psychophysiology, and in the fields of dynamic, distributed decision making and naturalistic decision making.

Differential associations of job control components with both waist circumference and body mass index.

PubMed

Bean, Christopher G; Winefield, Helen R; Sargent, Charli; Hutchinson, Amanda D

2015-10-01

The Job Demand-Control-Support (JDCS) model is commonly used to investigate associations between psychosocial work factors and employee health, yet research considering obesity using the JDCS model remains inconclusive. This study investigates which parts of the JDCS model are associated with measures of obesity and provides a comparison between waist circumference (higher values imply central obesity) and body mass index (BMI, higher values imply overall obesity). Contrary to common practice, in this study the JDCS components are not reduced into composite or global scores. In light of emerging evidence that the two components of job control (skill discretion and decision authority) could have differential associations with related health outcomes, components of the JDCS model were analysed at the subscale level. A cross-sectional design with a South Australian cohort (N = 450) combined computer-assisted telephone interview data and clinic-measured height, weight and waist circumference. After controlling for sex, age, household income, work hours and job nature (blue vs. white-collar), the two components of job control were the only parts of the JDCS model to hold significant associations with measures of obesity. Notably, the associations between skill discretion and waist circumference (b = -.502, p = .001), and skill discretion and BMI (b = -.163, p = .005) were negative. Conversely, the association between decision authority and waist circumference (b = .282, p = .022) was positive. These findings are significant since skill discretion and decision authority are typically combined into a composite measure of job control or decision latitude. Our findings suggest skill discretion and decision authority should be treated separately since combining these theoretically distinct components may conceal their differential associations with measures of obesity, masking their individual importance. Psychosocial work factors displayed stronger associations and explained greater variance in waist circumference compared with BMI, and possible reasons for this are discussed. Copyright © 2015 Elsevier Ltd. All rights reserved.

Evaluation of probabilistic forecasts with the scoringRules package

NASA Astrophysics Data System (ADS)

Jordan, Alexander; Krüger, Fabian; Lerch, Sebastian

2017-04-01

Over the last decades probabilistic forecasts in the form of predictive distributions have become popular in many scientific disciplines. With the proliferation of probabilistic models arises the need for decision-theoretically principled tools to evaluate the appropriateness of models and forecasts in a generalized way in order to better understand sources of prediction errors and to improve the models. Proper scoring rules are functions S(F,y) which evaluate the accuracy of a forecast distribution F , given that an outcome y was observed. In coherence with decision-theoretical principles they allow to compare alternative models, a crucial ability given the variety of theories, data sources and statistical specifications that is available in many situations. This contribution presents the software package scoringRules for the statistical programming language R, which provides functions to compute popular scoring rules such as the continuous ranked probability score for a variety of distributions F that come up in applied work. For univariate variables, two main classes are parametric distributions like normal, t, or gamma distributions, and distributions that are not known analytically, but are indirectly described through a sample of simulation draws. For example, ensemble weather forecasts take this form. The scoringRules package aims to be a convenient dictionary-like reference for computing scoring rules. We offer state of the art implementations of several known (but not routinely applied) formulas, and implement closed-form expressions that were previously unavailable. Whenever more than one implementation variant exists, we offer statistically principled default choices. Recent developments include the addition of scoring rules to evaluate multivariate forecast distributions. The use of the scoringRules package is illustrated in an example on post-processing ensemble forecasts of temperature.

Representing and querying now-relative relational medical data.

PubMed

Anselma, Luca; Piovesan, Luca; Stantic, Bela; Terenziani, Paolo

2018-03-01

Temporal information plays a crucial role in medicine. Patients' clinical records are intrinsically temporal. Thus, in Medical Informatics there is an increasing need to store, support and query temporal data (particularly in relational databases), in order, for instance, to supplement decision-support systems. In this paper, we show that current approaches to relational data have remarkable limitations in the treatment of "now-relative" data (i.e., data holding true at the current time). This can severely compromise their applicability in general, and specifically in the medical context, where "now-relative" data are essential to assess the current status of the patients. We propose a theoretically grounded and application-independent relational approach to cope with now-relative data (which can be paired, e.g., with different decision support systems) overcoming such limitations. We propose a new temporal relational representation, which is the first relational model coping with the temporal indeterminacy intrinsic in now-relative data. We also propose new temporal algebraic operators to query them, supporting the distinction between possible and necessary time, and Allen's temporal relations between data. We exemplify the impact of our approach, and study the theoretical and computational properties of the new representation and algebra. Copyright © 2018 Elsevier B.V. All rights reserved.

School transitions, peer influence, and educational expectation formation: Girls and boys.

PubMed

Andrew, Megan; Flashman, Jennifer

2017-01-01

School transitions are a regular feature of the educational career. While they are of general interest as instances of academic change, they also represent instances of peer environment and influence change. Previous theoretical and empirical work suggests peer influence is important for students' academic and educational outcomes, especially for the complex decision-making processes leading up to those outcomes. In this manuscript, we study the impact of peers on educational expectation formation at the 8th-to-9th-grade school transition. In doing so, we test a theoretical model that links institutional settings, social influence, and individual decision-making. We find the 9th grade transition likely represents a negative shock for students' college attendance expectations. Independent of this transition, however, stable peer environments further depress expectations. A more equal mixture of new and old peers in the 9th grade likely increases students' educational expectations in contrast. These effects of peer perturbations and the re-organization of social ties they imply mainly apply to female students. But, both male and female students revise their educational expectations in light of changing peer intelligence comparisons, albeit in countervailing ways. Copyright © 2016. Published by Elsevier Inc.

Theoretical underpinnings of state institutionalisation of inclusion and struggles in collective health in Latin America.

PubMed

Mahmood, Qamar; Muntaner, Carles

2018-03-28

Community participation as a strategy in health aims to increase the role of citizens in health decision-making which are contextualised within the institutions of democracy. Electoral representation as the dominant model of democracy globally is based on the elite theory of democracy that sees political decision-making a prerogative of political elites. Such political elitism is counter to the idea of democratic participation. Neoliberalism together with elitism in political sphere have worsened social inequities by undermining working class interests. Latin America has seen adverse consequences of these social inequities. In response, social movements representing collective struggles of organised citizens arose in the region. This paper explores the theoretical underpinnings of democratic participation in contemporary Latin American context at the nexus of emerging social movement activism and policy responses. The paper will use empirical examples to highlight how such democratic practices at the societal level evolved while demanding political inclusion. These societal democratic practices in Latin America are redefining democracy, which continues to be seen in the political sphere only. Health reforms promoting participatory democracy in several Latin American countries have demonstrated that establishing institutions and mechanisms of democratic participation facilitate collective participation by the organised citizenry in state affairs.

[L.A. Blumenfeld and study of photosynthesis by spectroscopy methods at Chair of Biophysics, Faculty of Physics, Moscow State University].

PubMed

Kukushkin, A K

2013-01-01

Nowadays spectroscopy methods are widely employed to study photosynthesis. For instance, fluorescence methods are often in use to study virtually all steps of photosynthesis process. Theoretical models of phenomena under study are of importance for interpretation of experimental data. A decisive role of L.A. Blumenfeld, the former head of the Chair of Biophysics, Faculty of Physics, Moscow State University, in the study of photosynthesis process is shown in this work.

Tactical Decision Making: A Proposed Evaluation Criteria Model for the Infantry Battalion’s Tactical Estimate during Offensive Operations

DTIC Science & Technology

1993-06-04

34 J In a paper entitled "Understanding and Developing Combat Power," by Colonel Huba Vass de Czege, a method identifying analytical techniques for...reiterates several important doctrinal and theoretical requirements for the de ’elopment of 9« an optimal «valuation criteria nodal. Although...Methode de Ralsonnenent Tactlque" (The Tactical Reasoning Method)’". Is a version of concurrent COA analysis under conditions at uncertainty. Figure

Using light gradients to investigate symmetry breaking in fish schools

NASA Astrophysics Data System (ADS)

Puckett, James; Giannini, Julia

Theoretical models of social animals successfully reproduce many structures found in nature (e.g. swarms, flocks, mills) using simple interaction rules. However, the interactions between individuals is complex and undoubtedly depends on the environment. Using schools of fish, we use visual perturbations to investigate how individuals negotiate both social and environmental information to reach a consensus. Starting with an unpolarized school of fish, we examine how the symmetry is broken and find that not all fish contribute equally to this decision.