Factors associated with confidence in decision making and satisfaction with risk communication among patients with atrial fibrillation.

PubMed

Hedberg, Berith; Malm, Dan; Karlsson, Jan-Erik; Årestedt, Kristofer; Broström, Anders

2018-06-01

Atrial fibrillation is a prevalent cardiac arrhythmia. Effective communication of risks (e.g. stroke risk) and benefits of treatment (e.g. oral anticoagulants) is crucial for the process of shared decision making. The aim of this study was to explore factors associated with confidence in decision making and satisfaction with risk communication after a follow-up visit among patients who three months earlier had visited an emergency room for atrial fibrillation related symptoms. A cross-sectional design was used and 322 patients (34% women), mean age 66.1 years (SD 10.5 years) with atrial fibrillation were included in the south of Sweden. Clinical examinations were done post an atrial fibrillation episode. Self-rating scales for communication (Combined Outcome Measure for Risk Communication and Treatment Decision Making Effectiveness), uncertainty in illness (Mishel Uncertainty in Illness Scale-Community), mastery of daily life (Mastery Scale), depressive symptoms (Hospital Anxiety and Depression Scale) and vitality, physical health and mental health (36-item Short Form Health Survey) were used to collect data. Decreased vitality and mastery of daily life, as well as increased uncertainty in illness, were independently associated with lower confidence in decision making. Absence of hypertension and increased uncertainty in illness were independently associated with lower satisfaction with risk communication. Clinical atrial fibrillation variables or depressive symptoms were not associated with satisfaction with confidence in decision making or satisfaction with risk communication. The final models explained 29.1% and 29.5% of the variance in confidence in decision making and satisfaction with risk communication. Confidence in decision making is associated with decreased vitality and mastery of daily life, as well as increased uncertainty in illness, while absence of hypertension and increased uncertainty in illness are associated with risk communication satisfaction.

The effect of uncertainties in distance-based ranking methods for multi-criteria decision making

NASA Astrophysics Data System (ADS)

Jaini, Nor I.; Utyuzhnikov, Sergei V.

2017-08-01

Data in the multi-criteria decision making are often imprecise and changeable. Therefore, it is important to carry out sensitivity analysis test for the multi-criteria decision making problem. The paper aims to present a sensitivity analysis for some ranking techniques based on the distance measures in multi-criteria decision making. Two types of uncertainties are considered for the sensitivity analysis test. The first uncertainty is related to the input data, while the second uncertainty is towards the Decision Maker preferences (weights). The ranking techniques considered in this study are TOPSIS, the relative distance and trade-off ranking methods. TOPSIS and the relative distance method measure a distance from an alternative to the ideal and antiideal solutions. In turn, the trade-off ranking calculates a distance of an alternative to the extreme solutions and other alternatives. Several test cases are considered to study the performance of each ranking technique in both types of uncertainties.

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

Do (un)certainty appraisal tendencies reverse the influence of emotions on risk taking in sequential tasks?

PubMed

Bagneux, Virginie; Bollon, Thierry; Dantzer, Cécile

2012-01-01

According to the Appraisal-Tendency Framework (Han, Lerner, & Keltner, 2007), certainty-associated emotions increase risk taking compared with uncertainty-associated emotions. To date, this general effect has only been shown in static judgement and decision-making paradigms; therefore, the present study tested the effect of certainty on risk taking in a sequential decision-making task. We hypothesised that the effect would be reversed due to the kind of processing involved, as certainty is considered to encourage heuristic processing that takes into account the emotional cues arising from previous decisions, whereas uncertainty leads to more systematic processing. One hundred and one female participants were induced to feel one of three emotions (film clips) before performing a decision-making task involving risk (Game of Dice Task; Brand et al., 2005). As expected, the angry and happy participants (certainty-associated emotions) were more likely than the fearful participants (uncertainty-associated emotion) to make safe decisions (vs. risky decisions).

Decision-making and evacuation planning for flood risk management in the Netherlands.

PubMed

Kolen, Bas; Helsloot, Ira

2014-07-01

A traditional view of decision-making for evacuation planning is that, given an uncertain threat, there is a deterministic way of defining the best decision. In other words, there is a linear relation between threat, decision, and execution consequences. Alternatives and the impact of uncertainties are not taken into account. This study considers the 'top strategic decision-making' for mass evacuation owing to flooding in the Netherlands. It reveals that the top strategic decision-making process itself is probabilistic because of the decision-makers involved and their crisis managers (as advisers). The paper concludes that deterministic planning is not sufficient, and it recommends probabilistic planning that considers uncertainties in the decision-making process itself as well as other uncertainties, such as forecasts, citizens responses, and the capacity of infrastructure. This results in less optimistic, but more realistic, strategies and a need to pay attention to alternative strategies. © 2014 The Author(s). Disasters © Overseas Development Institute, 2014.

Social, institutional, and psychological factors affecting wildfire incident decision making

Treesearch

Matthew P. Thompson

2014-01-01

Managing wildland fire incidents can be fraught with complexity and uncertainty. Myriad human factors can exert significant influence on incident decision making, and can contribute additional uncertainty regarding programmatic evaluations of wildfire management and attainment of policy goals. This article develops a framework within which human sources of uncertainty...

Risk, rationality, and regret: responding to the uncertainty of childhood food anaphylaxis.

PubMed

Hu, W; Kerridge, I; Kemp, A

2005-06-01

Risk and uncertainty are unavoidable in clinical medicine. In the case of childhood food allergy, the dysphoric experience of uncertainty is heightened by the perception of unpredictable danger to young children. Medicine has tended to respond to uncertainty with forms of rational decision making. Rationality cannot, however, resolve uncertainty and provides an insufficient account of risk. This paper compares the medical and parental accounts of two peanut allergic toddlers to highlight the value of emotions in decision making. One emotion in particular, regret, assists in explaining the actions taken to prevent allergic reactions, given the diffuse nature of responsibility for children. In this light, the assumption that doctors make rational judgments while patients have emotion led preferences is a false dichotomy. Reconciling medical and lay accounts requires acknowledgement of the interrelationship between the rational and the emotional, and may lead to more appropriate clinical decision making under conditions of uncertainty.

Uncertainty Estimation Cheat Sheet for Probabilistic Risk Assessment

NASA Technical Reports Server (NTRS)

Britton, Paul; Al Hassan, Mohammad; Ring, Robert

2017-01-01

Quantitative results for aerospace engineering problems are influenced by many sources of uncertainty. Uncertainty analysis aims to make a technical contribution to decision-making through the quantification of uncertainties in the relevant variables as well as through the propagation of these uncertainties up to the result. Uncertainty can be thought of as a measure of the 'goodness' of a result and is typically represented as statistical dispersion. This paper will explain common measures of centrality and dispersion; and-with examples-will provide guidelines for how they may be estimated to ensure effective technical contributions to decision-making.

Spatial planning using probabilistic flood maps

NASA Astrophysics Data System (ADS)

Alfonso, Leonardo; Mukolwe, Micah; Di Baldassarre, Giuliano

2015-04-01

Probabilistic flood maps account for uncertainty in flood inundation modelling and convey a degree of certainty in the outputs. Major sources of uncertainty include input data, topographic data, model structure, observation data and parametric uncertainty. Decision makers prefer less ambiguous information from modellers; this implies that uncertainty is suppressed to yield binary flood maps. Though, suppressing information may potentially lead to either surprise or misleading decisions. Inclusion of uncertain information in the decision making process is therefore desirable and transparent. To this end, we utilise the Prospect theory and information from a probabilistic flood map to evaluate potential decisions. Consequences related to the decisions were evaluated using flood risk analysis. Prospect theory explains how choices are made given options for which probabilities of occurrence are known and accounts for decision makers' characteristics such as loss aversion and risk seeking. Our results show that decision making is pronounced when there are high gains and loss, implying higher payoffs and penalties, therefore a higher gamble. Thus the methodology may be appropriately considered when making decisions based on uncertain information.

Uncertainty Estimation Cheat Sheet for Probabilistic Risk Assessment

NASA Technical Reports Server (NTRS)

Britton, Paul T.; Al Hassan, Mohammad; Ring, Robert W.

2017-01-01

"Uncertainty analysis itself is uncertain, therefore, you cannot evaluate it exactly," Source Uncertain Quantitative results for aerospace engineering problems are influenced by many sources of uncertainty. Uncertainty analysis aims to make a technical contribution to decision-making through the quantification of uncertainties in the relevant variables as well as through the propagation of these uncertainties up to the result. Uncertainty can be thought of as a measure of the 'goodness' of a result and is typically represented as statistical dispersion. This paper will explain common measures of centrality and dispersion; and-with examples-will provide guidelines for how they may be estimated to ensure effective technical contributions to decision-making.

Lognormal Uncertainty Estimation for Failure Rates

NASA Technical Reports Server (NTRS)

Britton, Paul T.; Al Hassan, Mohammad; Ring, Robert W.

2017-01-01

"Uncertainty analysis itself is uncertain, therefore, you cannot evaluate it exactly," Source Uncertain. Quantitative results for aerospace engineering problems are influenced by many sources of uncertainty. Uncertainty analysis aims to make a technical contribution to decision-making through the quantification of uncertainties in the relevant variables as well as through the propagation of these uncertainties up to the result. Uncertainty can be thought of as a measure of the 'goodness' of a result and is typically represented as statistical dispersion. This presentation will explain common measures of centrality and dispersion; and-with examples-will provide guidelines for how they may be estimated to ensure effective technical contributions to decision-making.

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.

[Decision process in a multidisciplinary cancer team with limited evidence].

PubMed

Lassalle, R; Marold, J; Schöbel, M; Manzey, D; Bohn, S; Dietz, A; Boehm, A

2014-04-01

The Head and Neck Cancer Tumor Board is a multispeciality comprehensive conference that brings together experts with different backgrounds to make group decisions about the appropriate treatment. Due to the complexity of the patient cases and the collaboration of different medical disciplines most of these decisions have to be made under uncertainty, i. e., with-out knowing all relevant factors and without being quite sure about the outcome. To develop effective team decision making under uncertainty, it is necessary to understand how medical experts perceive and handle uncertainties. The aim of this field study was to develop a knowledge base by exploring additionally the factors that influence group decision making processes. A structured nonparticipant observational study was employed to address the research goal. Video data were analyzed by 2 independent observers using an observation checklist. A total of 20 videotaped case discussions were studied. Observations were complemented by a questionnaire gathering subjective evaluations of board members about the process and quality of their decisions (N=15). The results show that uncertainty is recognized by board members. Reasons for uncertainty may stem from the complexity of the cases (e. g. therapy options) or the assessment from different disciplines coming together at the board. With respect to handling uncertainty and guaranteeing an optimal decision making process potential for improvement could be defined. This pertains to the handling of different levels of competence, the promotion of a positive discussion culture as well as structuring of the decision making process. © Georg Thieme Verlag KG Stuttgart · New York.

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.

Uncertainty Categorization, Modeling, and Management for Regional Water Supply Planning

NASA Astrophysics Data System (ADS)

Fletcher, S.; Strzepek, K. M.; AlSaati, A.; Alhassan, A.

2016-12-01

Many water planners face increased pressure on water supply systems from growing demands, variability in supply and a changing climate. Short-term variation in water availability and demand; long-term uncertainty in climate, groundwater storage, and sectoral competition for water; and varying stakeholder perspectives on the impacts of water shortages make it difficult to assess the necessity of expensive infrastructure investments. We categorize these uncertainties on two dimensions: whether they are the result of stochastic variation or epistemic uncertainty, and whether the uncertainties can be described probabilistically or are deep uncertainties whose likelihood is unknown. We develop a decision framework that combines simulation for probabilistic uncertainty, sensitivity analysis for deep uncertainty and Bayesian decision analysis for uncertainties that are reduced over time with additional information. We apply this framework to two contrasting case studies - drought preparedness in Melbourne, Australia and fossil groundwater depletion in Riyadh, Saudi Arabia - to assess the impacts of different types of uncertainty on infrastructure decisions. Melbourne's water supply system relies on surface water, which is impacted by natural variation in rainfall, and a market-based system for managing water rights. Our results show that small, flexible investment increases can mitigate shortage risk considerably at reduced cost. Riyadh, by contrast, relies primarily on desalination for municipal use and fossil groundwater for agriculture, and a centralized planner makes allocation decisions. Poor regional groundwater measurement makes it difficult to know when groundwater pumping will become uneconomical, resulting in epistemic uncertainty. However, collecting more data can reduce the uncertainty, suggesting the need for different uncertainty modeling and management strategies in Riyadh than in Melbourne. We will categorize the two systems and propose appropriate decision making under uncertainty methods from the state of the art. We will compare the efficiency of alternative approaches to the two case studies. Finally, we will present a hybrid decision analytic tool to address the synthesis of uncertainties.

Neural mechanisms of risky decision-making and reward response in adolescent onset cannabis use disorder.

PubMed

De Bellis, Michael D; Wang, Lihong; Bergman, Sara R; Yaxley, Richard H; Hooper, Stephen R; Huettel, Scott A

2013-11-01

Neural mechanisms of decision-making and reward response in adolescent cannabis use disorder (CUD) are underexplored. Three groups of male adolescents were studied: CUD in full remission (n=15); controls with psychopathology without substance use disorder history (n=23); and healthy controls (n=18). We investigated neural processing of decision-making and reward under conditions of varying risk and uncertainty with the Decision-Reward Uncertainty Task while participants were scanned using functional magnetic resonance imaging. Abstinent adolescents with CUD compared to controls with psychopathology showed hyperactivation in one cluster that spanned left superior parietal lobule/left lateral occipital cortex/precuneus while making risky decisions that involved uncertainty, and hypoactivation in left orbitofrontal cortex to rewarded outcomes compared to no-reward after making risky decisions. Post hoc region of interest analyses revealed that both control groups significantly differed from the CUD group (but not from each other) during both the decision-making and reward outcome phase of the Decision-Reward Uncertainty Task. In the CUD group, orbitofrontal activations to reward significantly and negatively correlated with total number of individual drug classes the CUD patients experimented with prior to treatment. CUD duration significantly and negatively correlated with orbitofrontal activations to no-reward. The adolescent CUD group demonstrated distinctly different activation patterns during risky decision-making and reward processing (after risky decision-making) compared to both the controls with psychopathology and healthy control groups. These findings suggest that neural differences in risky decision-making and reward processes are present in adolescent addiction, persist after remission from first CUD treatment, and may contribute to vulnerability for adolescent addiction. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Revisiting the generation and interpretation of climate models experiments for adaptation decision-making (Invited)

NASA Astrophysics Data System (ADS)

Ranger, N.; Millner, A.; Niehoerster, F.

2010-12-01

Traditionally, climate change risk assessments have taken a roughly four-stage linear ‘chain’ of moving from socioeconomic projections, to climate projections, to primary impacts and then finally onto economic and social impact assessment. Adaptation decisions are then made on the basis of these outputs. The escalation of uncertainty through this chain is well known; resulting in an ‘explosion’ of uncertainties in the final risk and adaptation assessment. The space of plausible future risk scenarios is growing ever wider with the application of new techniques which aim to explore uncertainty ever more deeply; such as those used in the recent ‘probabilistic’ UK Climate Projections 2009, and the stochastic integrated assessment models, for example PAGE2002. This explosion of uncertainty can make decision-making problematic, particularly given that the uncertainty information communicated can not be treated as strictly probabilistic and therefore, is not an easy fit with standard decision-making under uncertainty approaches. Additional problems can arise from the fact that the uncertainty estimated for different components of the ‘chain’ is rarely directly comparable or combinable. Here, we explore the challenges and limitations of using current projections for adaptation decision-making. We report the findings of a recent report completed for the UK Adaptation Sub-Committee on approaches to deal with these challenges and make robust adaptation decisions today. To illustrate these approaches, we take a number of illustrative case studies, including a case of adaptation to hurricane risk on the US Gulf Coast. This is a particularly interesting case as it involves urgent adaptation of long-lived infrastructure but requires interpreting highly uncertain climate change science and modelling; i.e. projections of Atlantic basin hurricane activity. An approach we outline is reversing the linear chain of assessments to put the economics and decision-making first. Such an approach forces one to focus on the information of greatest value for the specific decision. We suggest that such an approach will help to accommodate the uncertainties in the chain and facilitate robust decision-making. Initial findings of these case studies will be presented with the aim of raising open questions and promoting discussion of the methodology. Finally, we reflect on the implications for the design of climate model experiments.

Data-driven Modelling for decision making under uncertainty

NASA Astrophysics Data System (ADS)

Angria S, Layla; Dwi Sari, Yunita; Zarlis, Muhammad; Tulus

2018-01-01

The rise of the issues with the uncertainty of decision making has become a very warm conversation in operation research. Many models have been presented, one of which is with data-driven modelling (DDM). The purpose of this paper is to extract and recognize patterns in data, and find the best model in decision-making problem under uncertainty by using data-driven modeling approach with linear programming, linear and nonlinear differential equation, bayesian approach. Model criteria tested to determine the smallest error, and it will be the best model that can be used.

Framing of Uncertainty in Scientific Publications: Towards Recommendations for Decision Support

NASA Astrophysics Data System (ADS)

Guillaume, J. H. A.; Helgeson, C.; Elsawah, S.; Jakeman, A. J.; Kummu, M.

2016-12-01

Uncertainty is recognised as an essential issue in environmental decision making and decision support. As modellers, we notably use a variety of tools and techniques within an analysis, for example related to uncertainty quantification and model validation. We also address uncertainty by how we present results. For example, experienced modellers are careful to distinguish robust conclusions from those that need further work, and the precision of quantitative results is tailored to their accuracy. In doing so, the modeller frames how uncertainty should be interpreted by their audience. This is an area which extends beyond modelling to fields such as philosophy of science, semantics, discourse analysis, intercultural communication and rhetoric. We propose that framing of uncertainty deserves greater attention in the context of decision support, and that there are opportunities in this area for fundamental research, synthesis and knowledge transfer, development of teaching curricula, and significant advances in managing uncertainty in decision making. This presentation reports preliminary results of a study of framing practices. Specifically, we analyse the framing of uncertainty that is visible in the abstracts from a corpus of scientific articles. We do this through textual analysis of the content and structure of those abstracts. Each finding that appears in an abstract is classified according to the uncertainty framing approach used, using a classification scheme that was iteratively revised based on reflection and comparison amongst three coders. This analysis indicates how frequently the different framing approaches are used, and provides initial insights into relationships between frames, how the frames relate to interpretation of uncertainty, and how rhetorical devices are used by modellers to communicate uncertainty in their work. We propose initial hypotheses for how the resulting insights might influence decision support, and help advance decision making to better address uncertainty.

Using structured decision making with landowners to address private forest management and parcelization: balancing multiple objectives and incorporating uncertainty

Treesearch

Paige F. B. Ferguson; Michael J. Conroy; John F. Chamblee; Jeffrey Hepinstall-Cymerman

2015-01-01

Parcelization and forest fragmentation are of concern for ecological, economic, and social reasons. Efforts to keep large, private forests intact may be supported by a decision-making process that incorporates landowners’ objectives and uncertainty. We used structured decision making (SDM) with owners of large, private forests in Macon County, North Carolina....

Affective decision making under uncertainty during a plausible aviation task: an fMRI study.

PubMed

Causse, Mickaël; Péran, Patrice; Dehais, Frédéric; Caravasso, Chiara Falletta; Zeffiro, Thomas; Sabatini, Umberto; Pastor, Josette

2013-05-01

In aeronautics, plan continuation error (PCE) represents failure to revise a flight plan despite emerging evidence suggesting that it is no longer safe. Assuming that PCE may be associated with a shift from cold to hot reasoning, we hypothesized that this transition may result from a large range of strong negative emotional influences linked with the decision to abort a landing and circle for a repeat attempt, referred to as a "go-around". We investigated this hypothesis by combining functional neuroimaging with an ecologically valid aviation task performed under contextual variation in incentive and situational uncertainty. Our goal was to identify regional brain activity related to the sorts of conservative or liberal decision-making strategies engaged when participants were both exposed to a financial payoff matrix constructed to bias responses in favor of landing acceptance, while they were simultaneously experiencing maximum levels of uncertainty related to high levels of stimulus ambiguity. Combined with the observed behavioral outcomes, our neuroimaging results revealed a shift from cold to hot decision making in response to high uncertainty when participants were exposed to the financial incentive. Most notably, while we observed activity increases in response to uncertainty in many frontal regions such as dorsolateral prefrontal cortex (DLPFC) and anterior cingulate cortex (ACC), less overall activity was observed when the reward was combined with uncertainty. Moreover, participants with poor decision making, quantified as a lower discriminability index d', exhibited riskier behavior coupled with lower activity in the right DLPFC. These outcomes suggest a disruptive effect of biased financial incentive and high uncertainty on the rational decision-making neural network, and consequently, on decision relevance. Copyright © 2013 Elsevier Inc. All rights reserved.

An Integrated Understanding of Confidence and User Calibration in Information Systems Use

ERIC Educational Resources Information Center

Tang, Fengchun

2012-01-01

Dealing with uncertainty is a critical part of human decision-making and confidence reflects one's belief about the relative likelihood that various outcomes occur when making decision under uncertainty. Unfortunately, confidence often deviates from the actual quality of the decision, leading to under- or over-confidence. Calibration, the…

[Ethics, empiricism and uncertainty].

PubMed

Porz, R; Zimmermann, H; Exadaktylos, A K

2011-01-01

Accidents can lead to difficult boundary situations. Such situations often take place in the emergency units. The medical team thus often and inevitably faces professional uncertainty in their decision-making. It is essential to communicate these uncertainties within the medical team, instead of downplaying or overriding existential hurdles in decision-making. Acknowledging uncertainties might lead to alert and prudent decisions. Thus uncertainty can have ethical value in treatment or withdrawal of treatment. It does not need to be covered in evidence-based arguments, especially as some singular situations of individual tragedies cannot be grasped in terms of evidence-based medicine. © Georg Thieme Verlag KG Stuttgart · New York.

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.

Eye tracking measures of uncertainty during perceptual decision making.

PubMed

Brunyé, Tad T; Gardony, Aaron L

2017-10-01

Perceptual decision making involves gathering and interpreting sensory information to effectively categorize the world and inform behavior. For instance, a radiologist distinguishing the presence versus absence of a tumor, or a luggage screener categorizing objects as threatening or non-threatening. In many cases, sensory information is not sufficient to reliably disambiguate the nature of a stimulus, and resulting decisions are done under conditions of uncertainty. The present study asked whether several oculomotor metrics might prove sensitive to transient states of uncertainty during perceptual decision making. Participants viewed images with varying visual clarity and were asked to categorize them as faces or houses, and rate the certainty of their decisions, while we used eye tracking to monitor fixations, saccades, blinks, and pupil diameter. Results demonstrated that decision certainty influenced several oculomotor variables, including fixation frequency and duration, the frequency, peak velocity, and amplitude of saccades, and phasic pupil diameter. Whereas most measures tended to change linearly along with decision certainty, pupil diameter revealed more nuanced and dynamic information about the time course of perceptual decision making. Together, results demonstrate robust alterations in eye movement behavior as a function of decision certainty and attention demands, and suggest that monitoring oculomotor variables during applied task performance may prove valuable for identifying and remediating transient states of uncertainty. Published by Elsevier B.V.

Integrating info-gap decision theory with robust population management: a case study using the Mountain Plover.

PubMed

van der Burg, Max Post; Tyre, Andrew J

2011-01-01

Wildlife managers often make decisions under considerable uncertainty. In the most extreme case, a complete lack of data leads to uncertainty that is unquantifiable. Information-gap decision theory deals with assessing management decisions under extreme uncertainty, but it is not widely used in wildlife management. So too, robust population management methods were developed to deal with uncertainties in multiple-model parameters. However, the two methods have not, as yet, been used in tandem to assess population management decisions. We provide a novel combination of the robust population management approach for matrix models with the information-gap decision theory framework for making conservation decisions under extreme uncertainty. We applied our model to the problem of nest survival management in an endangered bird species, the Mountain Plover (Charadrius montanus). Our results showed that matrix sensitivities suggest that nest management is unlikely to have a strong effect on population growth rate, confirming previous analyses. However, given the amount of uncertainty about adult and juvenile survival, our analysis suggested that maximizing nest marking effort was a more robust decision to maintain a stable population. Focusing on the twin concepts of opportunity and robustness in an information-gap model provides a useful method of assessing conservation decisions under extreme uncertainty.

An Intuitionistic Fuzzy Logic Models for Multicriteria Decision Making Under Uncertainty

NASA Astrophysics Data System (ADS)

Jana, Biswajit; Mohanty, Sachi Nandan

2017-04-01

The purpose of this paper is to enhance the applicability of the fuzzy sets for developing mathematical models for decision making under uncertainty, In general a decision making process consist of four stages, namely collection of information from various sources, compile the information, execute the information and finally take the decision/action. Only fuzzy sets theory is capable to quantifying the linguistic expression to mathematical form in complex situation. Intuitionistic fuzzy set (IFSs) which reflects the fact that the degree of non membership is not always equal to one minus degree of membership. There may be some degree of hesitation. Thus, there are some situations where IFS theory provides a more meaningful and applicable to cope with imprecise information present for solving multiple criteria decision making problem. This paper emphasis on IFSs, which is help for solving real world problem in uncertainty situation.

Optimization and resilience in natural resources management

USGS Publications Warehouse

Williams, Byron K.; Johnson, Fred A.

2015-01-01

We consider the putative tradeoff between optimization and resilience in the management of natural resources, using a framework that incorporates different sources of uncertainty that are common in natural resources management. We address one-time decisions, and then expand the decision context to the more complex problem of iterative decision making. For both cases we focus on two key sources of uncertainty: partial observability of system state and uncertainty as to system dynamics. Optimal management strategies will vary considerably depending on the timeframe being considered and the amount and quality of information that is available to characterize system features and project the consequences of potential decisions. But in all cases an optimal decision making framework, if properly identified and focused, can be useful in recognizing sound decisions. We argue that under the conditions of deep uncertainty that characterize many resource systems, an optimal decision process that focuses on robustness does not automatically induce a loss of resilience.

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'.

Confronting dynamics and uncertainty in optimal decision making for conservation

USGS Publications Warehouse

Williams, Byron K.; Johnson, Fred A.

2013-01-01

The effectiveness of conservation efforts ultimately depends on the recognition that decision making, and the systems that it is designed to affect, are inherently dynamic and characterized by multiple sources of uncertainty. To cope with these challenges, conservation planners are increasingly turning to the tools of decision analysis, especially dynamic optimization methods. Here we provide a general framework for optimal, dynamic conservation and then explore its capacity for coping with various sources and degrees of uncertainty. In broadest terms, the dynamic optimization problem in conservation is choosing among a set of decision options at periodic intervals so as to maximize some conservation objective over the planning horizon. Planners must account for immediate objective returns, as well as the effect of current decisions on future resource conditions and, thus, on future decisions. Undermining the effectiveness of such a planning process are uncertainties concerning extant resource conditions (partial observability), the immediate consequences of decision choices (partial controllability), the outcomes of uncontrolled, environmental drivers (environmental variation), and the processes structuring resource dynamics (structural uncertainty). Where outcomes from these sources of uncertainty can be described in terms of probability distributions, a focus on maximizing the expected objective return, while taking state-specific actions, is an effective mechanism for coping with uncertainty. When such probability distributions are unavailable or deemed unreliable, a focus on maximizing robustness is likely to be the preferred approach. Here the idea is to choose an action (or state-dependent policy) that achieves at least some minimum level of performance regardless of the (uncertain) outcomes. We provide some examples of how the dynamic optimization problem can be framed for problems involving management of habitat for an imperiled species, conservation of a critically endangered population through captive breeding, control of invasive species, construction of biodiversity reserves, design of landscapes to increase habitat connectivity, and resource exploitation. Although these decision making problems and their solutions present significant challenges, we suggest that a systematic and effective approach to dynamic decision making in conservation need not be an onerous undertaking. The requirements are shared with any systematic approach to decision making--a careful consideration of values, actions, and outcomes.

Pupil dilation signals uncertainty and surprise in a learning gambling task.

PubMed

Lavín, Claudio; San Martín, René; Rosales Jubal, Eduardo

2013-01-01

Pupil dilation under constant illumination is a physiological marker where modulation is related to several cognitive functions involved in daily decision making. There is evidence for a role of pupil dilation change during decision-making tasks associated with uncertainty, reward-prediction errors and surprise. However, while some work suggests that pupil dilation is mainly modulated by reward predictions, others point out that this marker is related to uncertainty signaling and surprise. Supporting the latter hypothesis, the neural substrate of this marker is related to noradrenaline (NA) activity which has been also related to uncertainty signaling. In this work we aimed to test whether pupil dilation is a marker for uncertainty and surprise in a learning task. We recorded pupil dilation responses in 10 participants performing the Iowa Gambling Task (IGT), a decision-making task that requires learning and constant monitoring of outcomes' feedback, which are important variables within the traditional study of human decision making. Results showed that pupil dilation changes were modulated by learned uncertainty and surprise regardless of feedback magnitudes. Interestingly, greater pupil dilation changes were found during positive feedback (PF) presentation when there was lower uncertainty about a future negative feedback (NF); and by surprise during NF presentation. These results support the hypothesis that pupil dilation is a marker of learned uncertainty, and may be used as a marker of NA activity facing unfamiliar situations in humans.

Pupil dilation signals uncertainty and surprise in a learning gambling task

PubMed Central

Lavín, Claudio; San Martín, René; Rosales Jubal, Eduardo

2014-01-01

Pupil dilation under constant illumination is a physiological marker where modulation is related to several cognitive functions involved in daily decision making. There is evidence for a role of pupil dilation change during decision-making tasks associated with uncertainty, reward-prediction errors and surprise. However, while some work suggests that pupil dilation is mainly modulated by reward predictions, others point out that this marker is related to uncertainty signaling and surprise. Supporting the latter hypothesis, the neural substrate of this marker is related to noradrenaline (NA) activity which has been also related to uncertainty signaling. In this work we aimed to test whether pupil dilation is a marker for uncertainty and surprise in a learning task. We recorded pupil dilation responses in 10 participants performing the Iowa Gambling Task (IGT), a decision-making task that requires learning and constant monitoring of outcomes’ feedback, which are important variables within the traditional study of human decision making. Results showed that pupil dilation changes were modulated by learned uncertainty and surprise regardless of feedback magnitudes. Interestingly, greater pupil dilation changes were found during positive feedback (PF) presentation when there was lower uncertainty about a future negative feedback (NF); and by surprise during NF presentation. These results support the hypothesis that pupil dilation is a marker of learned uncertainty, and may be used as a marker of NA activity facing unfamiliar situations in humans. PMID:24427126

The cerebellum and decision making under uncertainty.

PubMed

Blackwood, Nigel; Ffytche, Dominic; Simmons, Andrew; Bentall, Richard; Murray, Robin; Howard, Robert

2004-06-01

This study aimed to identify the neural basis of probabilistic reasoning, a type of inductive inference that aids decision making under conditions of uncertainty. Eight normal subjects performed two separate two-alternative-choice tasks (the balls in a bottle and personality survey tasks) while undergoing functional magnetic resonance imaging (fMRI). The experimental conditions within each task were chosen so that they differed only in their requirement to make a decision under conditions of uncertainty (probabilistic reasoning and frequency determination required) or under conditions of certainty (frequency determination required). The same visual stimuli and motor responses were used in the experimental conditions. We provide evidence that the neo-cerebellum, in conjunction with the premotor cortex, inferior parietal lobule and medial occipital cortex, mediates the probabilistic inferences that guide decision making under uncertainty. We hypothesise that the neo-cerebellum constructs internal working models of uncertain events in the external world, and that such probabilistic models subserve the predictive capacity central to induction. Copyright 2004 Elsevier B.V.

Models in animal collective decision-making: information uncertainty and conflicting preferences

PubMed Central

Conradt, Larissa

2012-01-01

Collective decision-making plays a central part in the lives of many social animals. Two important factors that influence collective decision-making are information uncertainty and conflicting preferences. Here, I bring together, and briefly review, basic models relating to animal collective decision-making in situations with information uncertainty and in situations with conflicting preferences between group members. The intention is to give an overview about the different types of modelling approaches that have been employed and the questions that they address and raise. Despite the use of a wide range of different modelling techniques, results show a coherent picture, as follows. Relatively simple cognitive mechanisms can lead to effective information pooling. Groups often face a trade-off between decision accuracy and speed, but appropriate fine-tuning of behavioural parameters could achieve high accuracy while maintaining reasonable speed. The right balance of interdependence and independence between animals is crucial for maintaining group cohesion and achieving high decision accuracy. In conflict situations, a high degree of decision-sharing between individuals is predicted, as well as transient leadership and leadership according to needs and physiological status. Animals often face crucial trade-offs between maintaining group cohesion and influencing the decision outcome in their own favour. Despite the great progress that has been made, there remains one big gap in our knowledge: how do animals make collective decisions in situations when information uncertainty and conflict of interest operate simultaneously? PMID:23565335

Staged decision making based on probabilistic forecasting

NASA Astrophysics Data System (ADS)

Booister, Nikéh; Verkade, Jan; Werner, Micha; Cranston, Michael; Cumiskey, Lydia; Zevenbergen, Chris

2016-04-01

Flood forecasting systems reduce, but cannot eliminate uncertainty about the future. Probabilistic forecasts explicitly show that uncertainty remains. However, as - compared to deterministic forecasts - a dimension is added ('probability' or 'likelihood'), with this added dimension decision making is made slightly more complicated. A technique of decision support is the cost-loss approach, which defines whether or not to issue a warning or implement mitigation measures (risk-based method). With the cost-loss method a warning will be issued when the ratio of the response costs to the damage reduction is less than or equal to the probability of the possible flood event. This cost-loss method is not widely used, because it motivates based on only economic values and is a technique that is relatively static (no reasoning, yes/no decision). Nevertheless it has high potential to improve risk-based decision making based on probabilistic flood forecasting because there are no other methods known that deal with probabilities in decision making. The main aim of this research was to explore the ways of making decision making based on probabilities with the cost-loss method better applicable in practice. The exploration began by identifying other situations in which decisions were taken based on uncertain forecasts or predictions. These cases spanned a range of degrees of uncertainty: from known uncertainty to deep uncertainty. Based on the types of uncertainties, concepts of dealing with situations and responses were analysed and possible applicable concepts where chosen. Out of this analysis the concepts of flexibility and robustness appeared to be fitting to the existing method. Instead of taking big decisions with bigger consequences at once, the idea is that actions and decisions are cut-up into smaller pieces and finally the decision to implement is made based on economic costs of decisions and measures and the reduced effect of flooding. The more lead-time there is in flood event management, the more damage can be reduced. And with decisions based on probabilistic forecasts, partial decisions can be made earlier in time (with a lower probability) and can be scaled up or down later in time when there is more certainty; whether the event takes place or not. Partial decisions are often more cheap, or shorten the final mitigation-time at the moment when there is more certainty. The proposed method is tested on Stonehaven, on the Carron River in Scotland. Decisions to implement demountable defences in the town are currently made based on a very short lead-time due to the absence of certainty. Application showed that staged decision making is possible and gives the decision maker more time to respond to a situation. The decision maker is able to take a lower regret decision with higher uncertainty and less related negative consequences. Although it is not possible to quantify intangible effects, it is part of the analysis to reduce these effects. Above all, the proposed approach has shown to be a possible improvement in economic terms and opens up possibilities of more flexible and robust decision making.

Quantum Uncertainty and Decision-Making in Game Theory

NASA Astrophysics Data System (ADS)

Asano, M.; Ohya, M.; Tanaka, Y.; Khrennikov, A.; Basieva, I.

2011-01-01

Recently a few authors pointed to a possibility to apply the mathematical formalism of quantum mechanics to cognitive psychology, in particular, to games of the Prisoners Dilemma (PD) type.6_18 In this paper, we discuss the problem of rationality in game theory and point out that the quantum uncertainty is similar to the uncertainty of knowledge, which a player feels subjectively in his decision-making.

National evidence on the use of shared decision making in prostate-specific antigen screening.

PubMed

Han, Paul K J; Kobrin, Sarah; Breen, Nancy; Joseph, Djenaba A; Li, Jun; Frosch, Dominick L; Klabunde, Carrie N

2013-01-01

Recent clinical practice guidelines on prostate cancer screening using the prostate-specific antigen (PSA) test (PSA screening) have recommended that clinicians practice shared decision making-a process involving clinician-patient discussion of the pros, cons, and uncertainties of screening. We undertook a study to determine the prevalence of shared decision making in both PSA screening and nonscreening, as well as patient characteristics associated with shared decision making. A nationally representative sample of 3,427 men aged 50 to 74 years participating in the 2010 National Health Interview Survey responded to questions on the extent of shared decision making (past physician-patient discussion of advantages, disadvantages, and scientific uncertainty associated with PSA screening), PSA screening intensity (tests in past 5 years), and sociodemographic and health-related characteristics. Nearly two-thirds (64.3%) of men reported no past physician-patient discussion of advantages, disadvantages, or scientific uncertainty (no shared decision making); 27.8% reported discussion of 1 to 2 elements only (partial shared decision making); 8.0% reported discussion of all 3 elements (full shared decision making). Nearly one-half (44.2%) reported no PSA screening, 27.8% reported low-intensity (less-than-annual) screening, and 25.1% reported high-intensity (nearly annual) screening. Absence of shared decision making was more prevalent in men who were not screened; 88% (95% CI, 86.2%-90.1%) of nonscreened men reported no shared decision making compared with 39% (95% CI, 35.0%-43.3%) of men undergoing high-intensity screening. Extent of shared decision making was associated with black race, Hispanic ethnicity, higher education, health insurance, and physician recommendation. Screening intensity was associated with older age, higher education, usual source of medical care, and physician recommendation, as well as with partial vs no or full shared decision making. Most US men report little shared decision making in PSA screening, and the lack of shared decision making is more prevalent in nonscreened than in screened men. Screening intensity is greatest with partial shared decision making, and different elements of shared decision making are associated with distinct patient characteristics. Shared decision making needs to be improved in decisions for and against PSA screening.

Wildfire Decision Making Under Uncertainty

NASA Astrophysics Data System (ADS)

Thompson, M.

2013-12-01

Decisions relating to wildfire management are subject to multiple sources of uncertainty, and are made by a broad range of individuals, across a multitude of environmental and socioeconomic contexts. In this presentation I will review progress towards identification and characterization of uncertainties and how this information can support wildfire decision-making. First, I will review a typology of uncertainties common to wildfire management, highlighting some of the more salient sources of uncertainty and how they present challenges to assessing wildfire risk. This discussion will cover the expanding role of burn probability modeling, approaches for characterizing fire effects, and the role of multi-criteria decision analysis, and will provide illustrative examples of integrated wildfire risk assessment across a variety of planning scales. Second, I will describe a related uncertainty typology that focuses on the human dimensions of wildfire management, specifically addressing how social, psychological, and institutional factors may impair cost-effective risk mitigation. This discussion will encompass decision processes before, during, and after fire events, with a specific focus on active management of complex wildfire incidents. An improved ability to characterize uncertainties faced in wildfire management could lead to improved delivery of decision support, targeted communication strategies, and ultimately to improved wildfire management outcomes.

Making Decisions about an Educational Game, Simulation or Workshop: A 'Game Theory' Perspective.

ERIC Educational Resources Information Center

Cryer, Patricia

1988-01-01

Uses game theory to help practitioners make decisions about educational games, simulations, or workshops whose outcomes depend to some extent on chance. Highlights include principles for making decisions involving risk; elementary laws of probability; utility theory; and principles for making decisions involving uncertainty. (eight references)…

A Decision Support System for effective use of probability forecasts

NASA Astrophysics Data System (ADS)

De Kleermaeker, Simone; Verkade, Jan

2013-04-01

Often, water management decisions are based on hydrological forecasts. These forecasts, however, are affected by inherent uncertainties. It is increasingly common for forecasting agencies to make explicit estimates of these uncertainties and thus produce probabilistic forecasts. Associated benefits include the decision makers' increased awareness of forecasting uncertainties and the potential for risk-based decision-making. Also, a stricter separation of responsibilities between forecasters and decision maker can be made. However, simply having probabilistic forecasts available is not sufficient to realise the associated benefits. Additional effort is required in areas such as forecast visualisation and communication, decision making in uncertainty and forecast verification. Also, revised separation of responsibilities requires a shift in institutional arrangements and responsibilities. A recent study identified a number of additional issues related to the effective use of probability forecasts. When moving from deterministic to probability forecasting, a dimension is added to an already multi-dimensional problem; this makes it increasingly difficult for forecast users to extract relevant information from a forecast. A second issue is that while probability forecasts provide a necessary ingredient for risk-based decision making, other ingredients may not be present. For example, in many cases no estimates of flood damage, of costs of management measures and of damage reduction are available. This paper presents the results of the study, including some suggestions for resolving these issues and the integration of those solutions in a prototype decision support system (DSS). A pathway for further development of the DSS is outlined.

Creating dialogue: a workshop on "Uncertainty in Decision Making in a Changing Climate"

NASA Astrophysics Data System (ADS)

Ewen, Tracy; Addor, Nans; Johnson, Leigh; Coltekin, Arzu; Derungs, Curdin; Muccione, Veruska

2014-05-01

Uncertainty is present in all fields of climate research, spanning from projections of future climate change, to assessing regional impacts and vulnerabilities, to adaptation policy and decision-making. In addition to uncertainties, managers and planners in many sectors are often confronted with large amounts of information from climate change research whose complex and interdisciplinary nature make it challenging to incorporate into the decision-making process. An overarching issue in tackling this problem is the lack of institutionalized dialogue between climate researchers, decision-makers and user groups. Forums that facilitate such dialogue would allow climate researchers to actively engage with end-users and researchers in different disciplines to better characterize uncertainties and ultimately understand which ones are critically considered and incorporated into decisions made. We propose that the introduction of students to these challenges at an early stage of their education and career is a first step towards improving future dialogue between climate researchers, decision-makers and user groups. To this end, we organized a workshop at the University of Zurich, Switzerland, entitled "Uncertainty in Decision Making in a Changing Climate". It brought together 50 participants, including Bachelor, Master and PhD students and academic staff, and nine selected speakers from academia, industry, government, and philanthropy. Speakers introduced participants to topics ranging from uncertainties in climate model scenarios to managing uncertainties in development and aid agencies. The workshop consisted of experts' presentations, a panel discussion and student group work on case studies. Pedagogical goals included i) providing participants with an overview of the current research on uncertainty and on how uncertainty is dealt with by decision-makers, ii) fostering exchange between practitioners, students, and scientists from different backgrounds, iii) exposing students, at an early stage of their professional life, to multidisciplinary collaborations and real-world problems involving decisions under uncertainty. An opinion survey conducted before and after the workshop enabled us to observe changes in participants' perspectives on what information and tools should be exchanged between researchers and decision-makers to better address uncertainty. Responses demonstrated a marked shift from a pre-workshop vertical conceptualizations of researcher—user group interaction to a post-workshop horizontal mode: in the former, researchers were portrayed as bestowing data-based products to decision-makers, while in the latter, both sets of actors engaged in institutionalized dialogues and frequent communication, exchanging their needs, expertise, and personnel. In addition to the survey, we will draw on examples from the course evaluation to illustrate the strengths and weaknesses of our approach. By doing so, we seek to encourage the organization of similar events by other universities, with the mid-term goal to improve future dialogue. From a pedagogical perspective, introducing students to these ideas at a very early stage in their research careers is an ideal opportunity to establish new modes of communication with an interdisciplinary perspective and strengthen dialogue between climate researchers, decision-makers and user groups.

Gendered uncertainty and variation in physicians' decisions for coronary heart disease: the double-edged sword of "atypical symptoms".

PubMed

Welch, Lisa C; Lutfey, Karen E; Gerstenberger, Eric; Grace, Matthew

2012-09-01

Nonmedical factors and diagnostic certainty contribute to variation in clinical decision making, but the process by which this occurs remains unclear. We examine how physicians' interpretations of patient sex-gender affect diagnostic certainty and, in turn, decision making for coronary heart disease. Data are from a factorial experiment of 256 physicians who viewed 1 of 16 video vignettes with different patient-actors presenting the same symptoms of coronary heart disease. Physician participants completed a structured interview and provided a narrative about their decision-making processes. Quantitative analysis showed that diagnostic uncertainty reduces the likelihood that physicians will order tests and medications appropriate for an urgent cardiac condition in particular. Qualitative analysis revealed that a subset of physicians applied knowledge that women have "atypical symptoms" as a generalization, which engendered uncertainty for some. Findings are discussed in relation to social-psychological processes that underlie clinical decision making and the social framing of medical knowledge.

Gendered Uncertainty and Variation in Physicians’ Decisions for Coronary Heart Disease: The Double-Edged Sword of “Atypical Symptoms”*

PubMed Central

Welch, Lisa C.; Lutfey, Karen E.; Gerstenberger, Eric; Grace, Matthew

2013-01-01

Nonmedical factors and diagnostic certainty contribute to variation in clinical decision making, but the process by which this occurs remains unclear. We examine how physicians’ interpretations of patient sex/gender affect diagnostic certainty and, in turn, decision making for coronary heart disease (CHD). Data are from a factorial experiment of 256 physicians who viewed one of 16 video vignettes with different patient-actors presenting the same CHD symptoms. Physician participants completed a structured interview and provided a narrative about their decision-making processes. Quantitative analysis showed that diagnostic uncertainty reduces the likelihood that physicians will order tests and medications appropriate for an urgent cardiac condition in particular. Qualitative analysis revealed that a subset of physicians applied knowledge that women have “atypical symptoms” as a generalization, which engendered uncertainty for some. Findings are discussed in relation to social-psychological processes that underlie clinical decision making and the social framing of medical knowledge. PMID:22933590

Can the uncertainty appraisal associated with emotion cancel the effect of the hunch period in the Iowa Gambling Task?

PubMed

Bollon, Thierry; Bagneux, Virginie

2013-01-01

Research has given little attention to the influence of incidental emotions on the Iowa Gambling Task (IGT), in which processing of the emotional cues associated with each decision is necessary to make advantageous decisions. Drawing on cognitive theories of emotions, we tested whether uncertainty-associated emotion can cancel the positive effect of the hunch period, by preventing participants from developing a tendency towards advantageous decisions. Our explanation is that uncertainty appraisals initiate deliberative processing that is irrelevant to process emotional cues, contrary to intuitive processing (Kahneman, 2003; Tiedens & Linton, 2001). As expected, uncertainty-associated emotion cancelled the positive effect of the hunch period in the IGT compared to certainty-associated emotion: disgusted participants (certainty-associated emotion) and sad participants induced to feel certainty developed a stronger tendency towards advantageous decisions than sad participants induced to feel uncertainty. We discuss the importance of the core components that trigger incidental emotions to predict decision making.

Using measurement uncertainty in decision-making and conformity assessment

NASA Astrophysics Data System (ADS)

Pendrill, L. R.

2014-08-01

Measurements often provide an objective basis for making decisions, perhaps when assessing whether a product conforms to requirements or whether one set of measurements differs significantly from another. There is increasing appreciation of the need to account for the role of measurement uncertainty when making decisions, so that a ‘fit-for-purpose’ level of measurement effort can be set prior to performing a given task. Better mutual understanding between the metrologist and those ordering such tasks about the significance and limitations of the measurements when making decisions of conformance will be especially useful. Decisions of conformity are, however, currently made in many important application areas, such as when addressing the grand challenges (energy, health, etc), without a clear and harmonized basis for sharing the risks that arise from measurement uncertainty between the consumer, supplier and third parties. In reviewing, in this paper, the state of the art of the use of uncertainty evaluation in conformity assessment and decision-making, two aspects in particular—the handling of qualitative observations and of impact—are considered key to bringing more order to the present diverse rules of thumb of more or less arbitrary limits on measurement uncertainty and percentage risk in the field. (i) Decisions of conformity can be made on a more or less quantitative basis—referred in statistical acceptance sampling as by ‘variable’ or by ‘attribute’ (i.e. go/no-go decisions)—depending on the resources available or indeed whether a full quantitative judgment is needed or not. There is, therefore, an intimate relation between decision-making, relating objects to each other in terms of comparative or merely qualitative concepts, and nominal and ordinal properties. (ii) Adding measures of impact, such as the costs of incorrect decisions, can give more objective and more readily appreciated bases for decisions for all parties concerned. Such costs are associated with a variety of consequences, such as unnecessary re-manufacturing by the supplier as well as various consequences for the customer, arising from incorrect measures of quantity, poor product performance and so on.

Confronting dynamics and uncertainty in optimal decision making for conservation

NASA Astrophysics Data System (ADS)

Williams, Byron K.; Johnson, Fred A.

2013-06-01

The effectiveness of conservation efforts ultimately depends on the recognition that decision making, and the systems that it is designed to affect, are inherently dynamic and characterized by multiple sources of uncertainty. To cope with these challenges, conservation planners are increasingly turning to the tools of decision analysis, especially dynamic optimization methods. Here we provide a general framework for optimal, dynamic conservation and then explore its capacity for coping with various sources and degrees of uncertainty. In broadest terms, the dynamic optimization problem in conservation is choosing among a set of decision options at periodic intervals so as to maximize some conservation objective over the planning horizon. Planners must account for immediate objective returns, as well as the effect of current decisions on future resource conditions and, thus, on future decisions. Undermining the effectiveness of such a planning process are uncertainties concerning extant resource conditions (partial observability), the immediate consequences of decision choices (partial controllability), the outcomes of uncontrolled, environmental drivers (environmental variation), and the processes structuring resource dynamics (structural uncertainty). Where outcomes from these sources of uncertainty can be described in terms of probability distributions, a focus on maximizing the expected objective return, while taking state-specific actions, is an effective mechanism for coping with uncertainty. When such probability distributions are unavailable or deemed unreliable, a focus on maximizing robustness is likely to be the preferred approach. Here the idea is to choose an action (or state-dependent policy) that achieves at least some minimum level of performance regardless of the (uncertain) outcomes. We provide some examples of how the dynamic optimization problem can be framed for problems involving management of habitat for an imperiled species, conservation of a critically endangered population through captive breeding, control of invasive species, construction of biodiversity reserves, design of landscapes to increase habitat connectivity, and resource exploitation. Although these decision making problems and their solutions present significant challenges, we suggest that a systematic and effective approach to dynamic decision making in conservation need not be an onerous undertaking. The requirements are shared with any systematic approach to decision making—a careful consideration of values, actions, and outcomes.

A fuzzy stochastic framework for managing hydro-environmental and socio-economic interactions under uncertainty

NASA Astrophysics Data System (ADS)

Subagadis, Yohannes Hagos; Schütze, Niels; Grundmann, Jens

2014-05-01

An amplified interconnectedness between a hydro-environmental and socio-economic system brings about profound challenges of water management decision making. In this contribution, we present a fuzzy stochastic approach to solve a set of decision making problems, which involve hydrologically, environmentally, and socio-economically motivated criteria subjected to uncertainty and ambiguity. The proposed methodological framework combines objective and subjective criteria in a decision making procedure for obtaining an acceptable ranking in water resources management alternatives under different type of uncertainty (subjective/objective) and heterogeneous information (quantitative/qualitative) simultaneously. The first step of the proposed approach involves evaluating the performance of alternatives with respect to different types of criteria. The ratings of alternatives with respect to objective and subjective criteria are evaluated by simulation-based optimization and fuzzy linguistic quantifiers, respectively. Subjective and objective uncertainties related to the input information are handled through linking fuzziness and randomness together. Fuzzy decision making helps entail the linguistic uncertainty and a Monte Carlo simulation process is used to map stochastic uncertainty. With this framework, the overall performance of each alternative is calculated using an Order Weighted Averaging (OWA) aggregation operator accounting for decision makers' experience and opinions. Finally, ranking is achieved by conducting pair-wise comparison of management alternatives. This has been done on the basis of the risk defined by the probability of obtaining an acceptable ranking and mean difference in total performance for the pair of management alternatives. The proposed methodology is tested in a real-world hydrosystem, to find effective and robust intervention strategies for the management of a coastal aquifer system affected by saltwater intrusion due to excessive groundwater extraction for irrigated agriculture and municipal use. The results show that the approach gives useful support for robust decision-making and is sensitive to the decision makers' degree of optimism.

An introduction to behavioural decision-making theories for paediatricians.

PubMed

Haward, Marlyse F; Janvier, Annie

2015-04-01

Behavioural decision-making theories provide insights into how people make choices under conditions of uncertainty. However, few have been studied in paediatrics. This study introduces these theories, reviews current research and makes recommendations for their application within the context of shared decision-making. As parents are expected to share decision-making in paediatrics, it is critical that the fields of behavioural economics, communication and decision sciences merge with paediatric clinical ethics to optimise decision-making. ©2015 Foundation Acta Paediatrica. Published by John Wiley & Sons Ltd.

Decision-making under uncertainty: results from an experiment conducted at EGU 2012

NASA Astrophysics Data System (ADS)

Ramos, Maria-Helena; van Andel, Schalk Jan; Pappenberger, Florian

2013-04-01

Do probabilistic forecasts lead to better decisions? At the EGU General Assembly 2012, we conducted a laboratory-style experiment to address this question. Several cases of flood forecasts and a choice of actions to take were presented as part of a game to participants, who acted as decision makers. Participants were prompted to make decisions when forecasts were provided with and without uncertainty information. They had to decide whether to open or not a gate which was the inlet of a retention basin designed to protect a town. The rules were such that: if they decided to open the gate, the retention basin was flooded and the farmers in this basin demanded a compensation for flooding their land; if they decided not to open the gate and a flood occurred on the river, the town was flooded and they had to pay a fine to the town. Participants were encouraged to keep note of their individual decisions in a worksheet. About 100 worksheets were collected at the end of the game and the results of their evaluation are presented here. In general, they show that decisions are based on a combination of what is displayed by the expected (forecast) value and what is given by the uncertainty information. In the absence of uncertainty information, decision makers are compelled towards a more risk-averse attitude. Besides, more money was lost by a large majority of participants when they had to make decisions without uncertainty information. Limitations of the experiment setting are discussed, as well as the importance of the development of training tools to increase effectiveness in the use of probabilistic predictions to support decisions under uncertainty.

Modeling the value for money of changing clinical practice change: a stochastic application in diabetes care.

PubMed

Hoomans, Ties; Abrams, Keith R; Ament, Andre J H A; Evers, Silvia M A A; Severens, Johan L

2009-10-01

Decision making about resource allocation for guideline implementation to change clinical practice is inevitably undertaken in a context of uncertainty surrounding the cost-effectiveness of both clinical guidelines and implementation strategies. Adopting a total net benefit approach, a model was recently developed to overcome problems with the use of combined ratio statistics when analyzing decision uncertainty. To demonstrate the stochastic application of the model for informing decision making about the adoption of an audit and feedback strategy for implementing a guideline recommending intensive blood glucose control in type 2 diabetes in primary care in the Netherlands. An integrated Bayesian approach to decision modeling and evidence synthesis is adopted, using Markov Chain Monte Carlo simulation in WinBUGs. Data on model parameters is gathered from various sources, with effectiveness of implementation being estimated using pooled, random-effects meta-analysis. Decision uncertainty is illustrated using cost-effectiveness acceptability curves and frontier. Decisions about whether to adopt intensified glycemic control and whether to adopt audit and feedback alter for the maximum values that decision makers are willing to pay for health gain. Through simultaneously incorporating uncertain economic evidence on both guidance and implementation strategy, the cost-effectiveness acceptability curves and cost-effectiveness acceptability frontier show an increase in decision uncertainty concerning guideline implementation. The stochastic application in diabetes care demonstrates that the model provides a simple and useful tool for quantifying and exploring the (combined) uncertainty associated with decision making about adopting guidelines and implementation strategies and, therefore, for informing decisions about efficient resource allocation to change clinical practice.

[Dealing with diagnostic uncertainty in general practice].

PubMed

Wübken, Magdalena; Oswald, Jana; Schneider, Antonius

2013-01-01

In general, the prevalence of diseases is low in primary care. Therefore, the positive predictive value of diagnostic tests is lower than in hospitals where patients are highly selected. In addition, the patients present with milder forms of disease; and many diseases might hide behind the initial symptom(s). These facts lead to diagnostic uncertainty which is somewhat inherent to general practice. This narrative review discusses different sources of and reasons for uncertainty and strategies to deal with it in the context of the current literature. Fear of uncertainty correlates with higher diagnostic activities. The attitude towards uncertainty correlates with the choice of medical speciality by vocational trainees or medical students. An intolerance of uncertainty, which still increases as medicine is making steady progress, might partly explain the growing shortage of general practitioners. The bio-psycho-social context appears to be important to diagnostic decision-making. The effect of intuition and heuristics are investigated by cognitive psychologists. It is still unclear whether these aspects are prone to bias or useful, which might depend on the context of medical decisions. Good communication is of great importance to share uncertainty with the patients in a transparent way and to alleviate shared decision-making. Dealing with uncertainty should be seen as an important core component of general practice and needs to be investigated in more detail to improve the respective medical decisions. Copyright © 2013. Published by Elsevier GmbH.

National Evidence on the Use of Shared Decision Making in Prostate-Specific Antigen Screening

PubMed Central

Han, Paul K. J.; Kobrin, Sarah; Breen, Nancy; Joseph, Djenaba A.; Li, Jun; Frosch, Dominick L.; Klabunde, Carrie N.

2013-01-01

PURPOSE Recent clinical practice guidelines on prostate cancer screening using the prostate-specific antigen (PSA) test (PSA screening) have recommended that clinicians practice shared decision making—a process involving clinician-patient discussion of the pros, cons, and uncertainties of screening. We undertook a study to determine the prevalence of shared decision making in both PSA screening and nonscreening, as well as patient characteristics associated with shared decision making. METHODS A nationally representative sample of 3,427 men aged 50 to 74 years participating in the 2010 National Health Interview Survey responded to questions on the extent of shared decision making (past physician-patient discussion of advantages, disadvantages, and scientific uncertainty associated with PSA screening), PSA screening intensity (tests in past 5 years), and sociodemographic and health-related characteristics. RESULTS Nearly two-thirds (64.3%) of men reported no past physician-patient discussion of advantages, disadvantages, or scientific uncertainty (no shared decision making); 27.8% reported discussion of 1 to 2 elements only (partial shared decision making); 8.0% reported discussion of all 3 elements (full shared decision making). Nearly one-half (44.2%) reported no PSA screening, 27.8% reported low-intensity (less-than-annual) screening, and 25.1% reported high-intensity (nearly annual) screening. Absence of shared decision making was more prevalent in men who were not screened; 88% (95% CI, 86.2%–90.1%) of nonscreened men reported no shared decision making compared with 39% (95% CI, 35.0%–43.3%) of men undergoing high-intensity screening. Extent of shared decision making was associated with black race, Hispanic ethnicity, higher education, health insurance, and physician recommendation. Screening intensity was associated with older age, higher education, usual source of medical care, and physician recommendation, as well as with partial vs no or full shared decision making. CONCLUSIONS Most US men report little shared decision making in PSA screening, and the lack of shared decision making is more prevalent in nonscreened than in screened men. Screening intensity is greatest with partial shared decision making, and different elements of shared decision making are associated with distinct patient characteristics. Shared decision making needs to be improved in decisions for and against PSA screening. PMID:23835816

Emotion and Decision-Making Under Uncertainty: Physiological arousal predicts increased gambling during ambiguity but not risk

PubMed Central

FeldmanHall, Oriel; Glimcher, Paul; Baker, Augustus L; Phelps, Elizabeth A

2016-01-01

Uncertainty, which is ubiquitous in decision-making, can be fractionated into known probabilities (risk) and unknown probabilities (ambiguity). Although research illustrates that individuals more often avoid decisions associated with ambiguity compared to risk, it remains unclear why ambiguity is perceived as more aversive. Here we examine the role of arousal in shaping the representation of value and subsequent choice under risky and ambiguous decisions. To investigate the relationship between arousal and decisions of uncertainty, we measure skin conductance response—a quantifiable measure reflecting sympathetic nervous system arousal—during choices to gamble under risk and ambiguity. To quantify the discrete influences of risk and ambiguity sensitivity and the subjective value of each option under consideration, we model fluctuating uncertainty, as well as the amount of money that can be gained by taking the gamble. Results reveal that while arousal tracks the subjective value of a lottery regardless of uncertainty type, arousal differentially contributes to the computation of value—i.e. choice—depending on whether the uncertainty is risky or ambiguous: enhanced arousal adaptively decreases risk-taking only when the lottery is highly risky but increases risk-taking when the probability of winning is ambiguous (even after controlling for subjective value). Together, this suggests that the role of arousal during decisions of uncertainty is modulatory and highly dependent on the context in which the decision is framed. PMID:27690508

Introducing Decision Making under Uncertainty and Strategic Considerations in Engineering Design

ERIC Educational Resources Information Center

Kosmopoulou, Georgia; Jog, Chintamani; Freeman, Margaret; Papavassiliou, Dimitrios V.

2010-01-01

Chemical Engineering graduates will face challenges at the workplace that even their peers who graduated a few years ago were not expected to face. One such major challenge is the management and operation of companies and plants under conditions of uncertainty and the need to make decisions in competitive situations. Modern developments in…

Opinion: The use of natural hazard modeling for decision making under uncertainty

Treesearch

David E. Calkin; Mike Mentis

2015-01-01

Decision making to mitigate the effects of natural hazards is a complex undertaking fraught with uncertainty. Models to describe risks associated with natural hazards have proliferated in recent years. Concurrently, there is a growing body of work focused on developing best practices for natural hazard modeling and to create structured evaluation criteria for complex...

Uncertainty in Agricultural Impact Assessment

NASA Technical Reports Server (NTRS)

Wallach, Daniel; Mearns, Linda O.; Rivington, Michael; Antle, John M.; Ruane, Alexander C.

2014-01-01

This chapter considers issues concerning uncertainty associated with modeling and its use within agricultural impact assessments. Information about uncertainty is important for those who develop assessment methods, since that information indicates the need for, and the possibility of, improvement of the methods and databases. Such information also allows one to compare alternative methods. Information about the sources of uncertainties is an aid in prioritizing further work on the impact assessment method. Uncertainty information is also necessary for those who apply assessment methods, e.g., for projecting climate change impacts on agricultural production and for stakeholders who want to use the results as part of a decision-making process (e.g., for adaptation planning). For them, uncertainty information indicates the degree of confidence they can place in the simulated results. Quantification of uncertainty also provides stakeholders with an important guideline for making decisions that are robust across the known uncertainties. Thus, uncertainty information is important for any decision based on impact assessment. Ultimately, we are interested in knowledge about uncertainty so that information can be used to achieve positive outcomes from agricultural modeling and impact assessment.

Robust Decision Making to Support Water Quality Climate Adaptation: a Case Study in the Chesapeake Bay Watershed

NASA Astrophysics Data System (ADS)

Fischbach, J. R.; Lempert, R. J.; Molina-Perez, E.

2017-12-01

The U.S. Environmental Protection Agency (USEPA), together with state and local partners, develops watershed implementation plans designed to meet water quality standards. Climate uncertainty, along with uncertainty about future land use changes or the performance of water quality best management practices (BMPs), may make it difficult for these implementation plans to meet water quality goals. In this effort, we explored how decision making under deep uncertainty (DMDU) methods such as Robust Decision Making (RDM) could help USEPA and its partners develop implementation plans that are more robust to future uncertainty. The study focuses on one part of the Chesapeake Bay watershed, the Patuxent River, which is 2,479 sq km in area, highly urbanized, and has a rapidly growing population. We simulated the contribution of stormwater contaminants from the Patuxent to the overall Total Maximum Daily Load (TMDL) for the Chesapeake Bay under multiple scenarios reflecting climate and other uncertainties. Contaminants considered included nitrogen, phosphorus, and sediment loads. The assessment included a large set of scenario simulations using the USEPA Chesapeake Bay Program's Phase V watershed model. Uncertainties represented in the analysis included 18 downscaled climate projections (based on 6 general circulation models and 3 emissions pathways), 12 land use scenarios with different population projections and development patterns, and alternative assumptions about BMP performance standards and efficiencies associated with different suites of stormwater BMPs. Finally, we developed cost estimates for each of the performance standards and compared cost to TMDL performance as a key tradeoff for future water quality management decisions. In this talk, we describe how this research can help inform climate-related decision support at USEPA's Chesapeake Bay Program, and more generally how RDM and other DMDU methods can support improved water quality management under climate uncertainty.

Value-based decision making under uncertainty in hoarding and obsessive-compulsive disorders

PubMed Central

Pushkarskaya, Helen; Tolin, David; Ruderman, Lital; Henick, Daniel; Kelly, J. MacLaren; Pittenger, Christopher; Levy, Ifat

2017-01-01

Difficulties in decision making are a core impairment in a range of disease states. For instance, both obsessive-compulsive disorder (OCD) and hoarding disorder (HD) are associated with indecisiveness, inefficient planning, and enhanced uncertainty intolerance, even in contexts unrelated to their core symptomology. We examined decision-making patterns in 19 individuals with OCD, 19 individuals with HD, 19 individuals with comorbid OCD and HD, and 57 individuals from the general population, using a well-validated choice task grounded in behavioral economic theory. Our results suggest that difficulties in decision making in individuals with OCD (with or without comorbid HD) are linked to reduced fidelity of value-based decision making (i.e. increase in inconsistent choices). In contrast, we find that performance of individuals with HD on our laboratory task is largely intact. Overall, these results support our hypothesis that decision-making impairments in OCD and HD, which can appear quite similar clinically, have importantly different underpinnings. Systematic investigation of different aspects of decision making, under varying conditions, may shed new light on commonalities between and distinctions among clinical syndromes. PMID:28864119

Structured decision making as a framework for large-scale wildlife harvest management decisions

USGS Publications Warehouse

Robinson, Kelly F.; Fuller, Angela K.; Hurst, Jeremy E.; Swift, Bryan L.; Kirsch, Arthur; Farquhar, James F.; Decker, Daniel J.; Siemer, William F.

2016-01-01

Fish and wildlife harvest management at large spatial scales often involves making complex decisions with multiple objectives and difficult tradeoffs, population demographics that vary spatially, competing stakeholder values, and uncertainties that might affect management decisions. Structured decision making (SDM) provides a formal decision analytic framework for evaluating difficult decisions by breaking decisions into component parts and separating the values of stakeholders from the scientific evaluation of management actions and uncertainty. The result is a rigorous, transparent, and values-driven process. This decision-aiding process provides the decision maker with a more complete understanding of the problem and the effects of potential management actions on stakeholder values, as well as how key uncertainties can affect the decision. We use a case study to illustrate how SDM can be used as a decision-aiding tool for management decision making at large scales. We evaluated alternative white-tailed deer (Odocoileus virginianus) buck-harvest regulations in New York designed to reduce harvest of yearling bucks, taking into consideration the values of the state wildlife agency responsible for managing deer, as well as deer hunters. We incorporated tradeoffs about social, ecological, and economic management concerns throughout the state. Based on the outcomes of predictive models, expert elicitation, and hunter surveys, the SDM process identified management alternatives that optimized competing objectives. The SDM process provided biologists and managers insight about aspects of the buck-harvest decision that helped them adopt a management strategy most compatible with diverse hunter values and management concerns.

Geospatial decision support systems for societal decision making

USGS Publications Warehouse

Bernknopf, R.L.

2005-01-01

While science provides reliable information to describe and understand the earth and its natural processes, it can contribute more. There are many important societal issues in which scientific information can play a critical role. Science can add greatly to policy and management decisions to minimize loss of life and property from natural and man-made disasters, to manage water, biological, energy, and mineral resources, and in general, to enhance and protect our quality of life. However, the link between science and decision-making is often complicated and imperfect. Technical language and methods surround scientific research and the dissemination of its results. Scientific investigations often are conducted under different conditions, with different spatial boundaries, and in different timeframes than those needed to support specific policy and societal decisions. Uncertainty is not uniformly reported in scientific investigations. If society does not know that data exist, what the data mean, where to use the data, or how to include uncertainty when a decision has to be made, then science gets left out -or misused- in a decision making process. This paper is about using Geospatial Decision Support Systems (GDSS) for quantitative policy analysis. Integrated natural -social science methods and tools in a Geographic Information System that respond to decision-making needs can be used to close the gap between science and society. The GDSS has been developed so that nonscientists can pose "what if" scenarios to evaluate hypothetical outcomes of policy and management choices. In this approach decision makers can evaluate the financial and geographic distribution of potential policy options and their societal implications. Actions, based on scientific information, can be taken to mitigate hazards, protect our air and water quality, preserve the planet's biodiversity, promote balanced land use planning, and judiciously exploit natural resources. Applications using the GDSS have demonstrated the benefits of utilizing science for policy decisions. Investment in science reduces decision-making uncertainty and reducing that uncertainty has economic value.

Forecasting resource-allocation decisions under climate uncertainty: fire suppression with assessment of net benefits of research

Treesearch

Jeffrey P. Prestemon; Geoffrey H. Donovan

2008-01-01

Making input decisions under climate uncertainty often involves two-stage methods that use expensive and opaque transfer functions. This article describes an alternative, single-stage approach to such decisions using forecasting methods. The example shown is for preseason fire suppression resource contracting decisions faced by the United States Forest Service. Two-...

Deciding to institutionalize: caregiving crisis, intergenerational communication, and uncertainty management for elders and their children in Shanghai.

PubMed

Chen, Lin

2015-01-01

This phenomenological study integrated crisis theory, social identity theory, and uncertainty management theory to conceptualize the decision-making process around institutionalization among nursing home residents and their children in Shanghai. I conducted face-to-face, semistructured interviews with 12 dyads of matched elders and their children (N = 24). The findings suggest that caregiving crises triggered intergenerational communication about caregiving alternatives and new arrangements, although each generation had different stances and motivations. Children finalized the decision by helping their parents to manage the uncertainties pertaining to institutionalization. This study sheds light on caregiving decision-making dynamics for the increasing aging population across cultures.

Uncertainty quantification in downscaling procedures for effective decisions in energy systems

NASA Astrophysics Data System (ADS)

Constantinescu, E. M.

2010-12-01

Weather is a major driver both of energy supply and demand, and with the massive adoption of renewable energy sources and changing economic and producer-consumer paradigms, the management of the next-generation energy systems is becoming ever more challenging. The operational and planning decisions in energy systems are guided by efficiency and reliability, and therefore a central role in these decisions will be played by the ability to obtain weather condition forecasts with accurate uncertainty estimates. The appropriate temporal and spatial resolutions needed for effective decision-making, be it operational or planning, is not clear. It is arguably certain however, that such temporal scales as hourly variations of temperature or wind conditions and ramp events are essential in this process. Planning activities involve decade or decades-long projections of weather. One sensible way to achieve this is to embed regional weather models in a global climate system. This strategy acts as a downscaling procedure. Uncertainty modeling techniques must be developed in order to quantify and minimize forecast errors as well as target variables that impact the decision-making process the most. We discuss the challenges of obtaining a realistic uncertainty quantification estimate using mathematical algorithms based on scalable matrix-free computations and physics-based statistical models. The process of making decisions for energy management systems based on future weather scenarios is a very complex problem. We shall focus on the challenges in generating wind power predictions based on regional weather predictions, and discuss the implications of making the common assumptions about the uncertainty models.

Voices of African American, Caucasian, and Hispanic surrogates on the burdens of end-of-life decision making.

PubMed

Braun, Ursula K; Beyth, Rebecca J; Ford, Marvella E; McCullough, Laurence B

2008-03-01

End-of-life decisions are frequently made by patients' surrogates. Race and ethnicity may affect such decision making. Few studies have described how different racial/ethnic groups experience end-of-life surrogate decision making. To describe the self-reported experience the self-reported experience of African-American, Caucasian, and Hispanic surrogate decision makers of seriously ill patients and to examine the relationship of race, ethnicity, and culture to that experience. Purposive sample to include racial/ethnic minorities in a qualitative study using focus group interviews. The participants of the study were 44 experienced, mostly female, surrogate decision makers for older veterans. Transcripts were qualitatively analyzed to identify major themes, with particular attention to themes that might be unique to each of the three groups. The experience of burden of end-of-life decision making was similar in all three groups. This burden in its medical, personal, and familial dimensions is compounded by uncertainty about prognosis and the patient's preferences. Racial/ethnic variations of responses to this burden concerned the physician-family relationship, religion and faith, and past experiences with race/ethnicity concordant versus non-concordant physicians. Regardless of race/ethnicity, surrogates for seriously ill patients appeared to experience increased significant, multidimensional burdens of decision making under conditions of uncertainty about a patient's preferences. This aspect of the burden of surrogate decision making may not be fully appreciated by physicians. Physicians should identify and be especially attentive to strategies used by surrogates, which may vary by race/ethnicity, to reduce the uncertainty about a patient's preferences and thus the burden of surrogate decision making to assist them in this difficult process.

Fuzzy methods in decision making process - A particular approach in manufacturing systems

NASA Astrophysics Data System (ADS)

Coroiu, A. M.

2015-11-01

We are living in a competitive environment, so we can see and understand that the most of manufacturing firms do the best in order to accomplish meeting demand, increasing quality, decreasing costs, and delivery rate. In present a stake point of interest is represented by the development of fuzzy technology. A particular approach for this is represented through the development of methodologies to enhance the ability to managed complicated optimization and decision making aspects involving non-probabilistic uncertainty with the reason to understand, development, and practice the fuzzy technologies to be used in fields such as economic, engineering, management, and societal problems. Fuzzy analysis represents a method for solving problems which are related to uncertainty and vagueness; it is used in multiple areas, such as engineering and has applications in decision making problems, planning and production. As a definition for decision making process we can use the next one: result of mental processes based upon cognitive process with a main role in the selection of a course of action among several alternatives. Every process of decision making can be represented as a result of a final choice and the output can be represented as an action or as an opinion of choice. Different types of uncertainty can be discovered in a wide variety of optimization and decision making problems related to planning and operation of power systems and subsystems. The mixture of the uncertainty factor in the construction of different models serves for increasing their adequacy and, as a result, the reliability and factual efficiency of decisions based on their analysis. Another definition of decision making process which came to illustrate and sustain the necessity of using fuzzy method: the decision making is an approach of choosing a strategy among many different projects in order to achieve some purposes and is formulated as three different models: high risk decision, usual risk decision and low risk decision - some specific formulas of fuzzy logic. The fuzzy set concepts has some certain parameterization features which are certain extensions of crisp and fuzzy relations respectively and have a rich potential for application to the decision making problems. The proposed approach from this paper presents advantages of fuzzy approach, in comparison with other paradigm and presents a particular way in which fuzzy logic can emerge in decision making process and planning process with implication, as a simulation, in manufacturing - involved in measuring performance of advanced manufacturing systems. Finally, an example is presented to illustrate our simulation.

Robustness for slope stability modelling under deep uncertainty

NASA Astrophysics Data System (ADS)

Almeida, Susana; Holcombe, Liz; Pianosi, Francesca; Wagener, Thorsten

2015-04-01

Landslides can have large negative societal and economic impacts, such as loss of life and damage to infrastructure. However, the ability of slope stability assessment to guide management is limited by high levels of uncertainty in model predictions. Many of these uncertainties cannot be easily quantified, such as those linked to climate change and other future socio-economic conditions, restricting the usefulness of traditional decision analysis tools. Deep uncertainty can be managed more effectively by developing robust, but not necessarily optimal, policies that are expected to perform adequately under a wide range of future conditions. Robust strategies are particularly valuable when the consequences of taking a wrong decision are high as is often the case of when managing natural hazard risks such as landslides. In our work a physically based numerical model of hydrologically induced slope instability (the Combined Hydrology and Stability Model - CHASM) is applied together with robust decision making to evaluate the most important uncertainties (storm events, groundwater conditions, surface cover, slope geometry, material strata and geotechnical properties) affecting slope stability. Specifically, impacts of climate change on long-term slope stability are incorporated, accounting for the deep uncertainty in future climate projections. Our findings highlight the potential of robust decision making to aid decision support for landslide hazard reduction and risk management under conditions of deep uncertainty.

Heuristics in Managing Complex Clinical Decision Tasks in Experts’ Decision Making

PubMed Central

Islam, Roosan; Weir, Charlene; Del Fiol, Guilherme

2016-01-01

Background Clinical decision support is a tool to help experts make optimal and efficient decisions. However, little is known about the high level of abstractions in the thinking process for the experts. Objective The objective of the study is to understand how clinicians manage complexity while dealing with complex clinical decision tasks. Method After approval from the Institutional Review Board (IRB), three clinical experts were interviewed the transcripts from these interviews were analyzed. Results We found five broad categories of strategies by experts for managing complex clinical decision tasks: decision conflict, mental projection, decision trade-offs, managing uncertainty and generating rule of thumb. Conclusion Complexity is created by decision conflicts, mental projection, limited options and treatment uncertainty. Experts cope with complexity in a variety of ways, including using efficient and fast decision strategies to simplify complex decision tasks, mentally simulating outcomes and focusing on only the most relevant information. Application Understanding complex decision making processes can help design allocation based on the complexity of task for clinical decision support design. PMID:27275019

Heuristics in Managing Complex Clinical Decision Tasks in Experts' Decision Making.

PubMed

Islam, Roosan; Weir, Charlene; Del Fiol, Guilherme

2014-09-01

Clinical decision support is a tool to help experts make optimal and efficient decisions. However, little is known about the high level of abstractions in the thinking process for the experts. The objective of the study is to understand how clinicians manage complexity while dealing with complex clinical decision tasks. After approval from the Institutional Review Board (IRB), three clinical experts were interviewed the transcripts from these interviews were analyzed. We found five broad categories of strategies by experts for managing complex clinical decision tasks: decision conflict, mental projection, decision trade-offs, managing uncertainty and generating rule of thumb. Complexity is created by decision conflicts, mental projection, limited options and treatment uncertainty. Experts cope with complexity in a variety of ways, including using efficient and fast decision strategies to simplify complex decision tasks, mentally simulating outcomes and focusing on only the most relevant information. Understanding complex decision making processes can help design allocation based on the complexity of task for clinical decision support design.

Emotion and decision-making under uncertainty: Physiological arousal predicts increased gambling during ambiguity but not risk.

PubMed

FeldmanHall, Oriel; Glimcher, Paul; Baker, Augustus L; Phelps, Elizabeth A

2016-10-01

Uncertainty, which is ubiquitous in decision-making, can be fractionated into known probabilities (risk) and unknown probabilities (ambiguity). Although research has illustrated that individuals more often avoid decisions associated with ambiguity compared to risk, it remains unclear why ambiguity is perceived as more aversive. Here we examine the role of arousal in shaping the representation of value and subsequent choice under risky and ambiguous decisions. To investigate the relationship between arousal and decisions of uncertainty, we measure skin conductance response-a quantifiable measure reflecting sympathetic nervous system arousal-during choices to gamble under risk and ambiguity. To quantify the discrete influences of risk and ambiguity sensitivity and the subjective value of each option under consideration, we model fluctuating uncertainty, as well as the amount of money that can be gained by taking the gamble. Results reveal that although arousal tracks the subjective value of a lottery regardless of uncertainty type, arousal differentially contributes to the computation of value-that is, choice-depending on whether the uncertainty is risky or ambiguous: Enhanced arousal adaptively decreases risk-taking only when the lottery is highly risky but increases risk-taking when the probability of winning is ambiguous (even after controlling for subjective value). Together, this suggests that the role of arousal during decisions of uncertainty is modulatory and highly dependent on the context in which the decision is framed. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Visualising Uncertainty for Decision Support

DTIC Science & Technology

2016-12-01

25 4.2.7 The perceived trust level of information in decision making ......... 26 4.3 User issues...crucial to understanding the “reliability” of information , and consequently affect decision making (Deitrick, 2007). Olston and Mackinlay (2002...have long been regarded as a difficult topic since the commander has to make decisions in a limited time frame with information that comes from

Decision making with epistemic uncertainty under safety constraints: An application to seismic design

USGS Publications Warehouse

Veneziano, D.; Agarwal, A.; Karaca, E.

2009-01-01

The problem of accounting for epistemic uncertainty in risk management decisions is conceptually straightforward, but is riddled with practical difficulties. Simple approximations are often used whereby future variations in epistemic uncertainty are ignored or worst-case scenarios are postulated. These strategies tend to produce sub-optimal decisions. We develop a general framework based on Bayesian decision theory and exemplify it for the case of seismic design of buildings. When temporal fluctuations of the epistemic uncertainties and regulatory safety constraints are included, the optimal level of seismic protection exceeds the normative level at the time of construction. Optimal Bayesian decisions do not depend on the aleatory or epistemic nature of the uncertainties, but only on the total (epistemic plus aleatory) uncertainty and how that total uncertainty varies randomly during the lifetime of the project. ?? 2009 Elsevier Ltd. All rights reserved.

Assessment of Group Preferences and Group Uncertainty for Decision Making

DTIC Science & Technology

1976-06-01

the individ- uals. decision making , group judgments should be preferred to individual judgments if obtaining group judgments costs more. -26- -YI IV... decision making group . IV. A. 3. Aggregation using conjugate distribution. Arvther procedure for combining indivi(jai probability judgments into a group...statisticized group group decision making group judgment subjective probability Delphi method expected utility nominal group 20. ABSTRACT (Continue on

Transformational Leadership & Decision Making in Schools

ERIC Educational Resources Information Center

Brower, Robert E.; Balch, Bradley V.

2005-01-01

It is essential for every school leader to possess the savvy to effect positive change, raise achievement levels, and foster a positive school climate. Now it seems that the struggle for school leaders to make productive decisions has become clouded with ever-growing uncertainty and skepticism. "Transformational Leadership & Decision Making in…

Scrutinizing screening: a critical interpretive review of primary care provider perspectives on mammography decision-making with average-risk women.

PubMed

Siedlikowski, Sophia; Ells, Carolyn; Bartlett, Gillian

2018-01-01

A decision to undertake screening for breast cancer often takes place within the primary care setting, but current controversies such as overdiagnosis and inconsistent screening recommendations based on evolving evidence render this a challenging process, particularly for average-risk women. Given the responsibility of primary care providers in counseling women in this decision-making process, it is important to understand their thoughts on these controversies and how they manage uncertainty in their practice. To review the perspectives and approaches of primary care providers regarding mammography decision-making with average-risk women. This study is a critical interpretive review of peer-review literature that reports primary care provider perspectives on mammography screening decision-making. Ovid MEDLINE®, Ovid PsycInfo, and Scopus databases were searched with dates from 2002 to 2017 using search terms related to mammography screening, uncertainty, counseling, decision-making, and primary health care providers. Nine articles were included following a review process involving the three authors. Using an inductive and iterative approach, data were grouped into four thematic categories: (1) perceptions on the effectiveness of screening, screening initiation age, and screening frequency; (2) factors guiding primary care providers in the screening decision-making process, including both provider and patient-related factors, (3) uncertainty faced by primary care providers regarding guidelines and screening discussions with their patients; and (4) informed decision-making with average-risk women, including factors that facilitate and hinder this process. The discussion of results addresses several factors about the diversity of perspectives and practices of physicians counseling average-risk women regarding breast cancer screening. This has implications for the challenge of understanding and explaining evidence, what should be shared with average-risk women considering screening, the forms of knowledge that physicians value to guide screening decision-making, and the consent process for population-based screening initiatives. Within the data, there was little attention placed on how physicians coped with uncertainty in practice. Given the dual responsibility of physicians in caring for both individuals and the larger population, further research should probe more deeply into how they balance their duties to individual patients with those to the larger population they serve.

The Irrelevance of the Risk-Uncertainty Distinction.

PubMed

Roser, Dominic

2017-10-01

Precautionary Principles are often said to be appropriate for decision-making in contexts of uncertainty such as climate policy. Contexts of uncertainty are contrasted to contexts of risk depending on whether we have probabilities or not. Against this view, I argue that the risk-uncertainty distinction is practically irrelevant. I start by noting that the history of the distinction between risk and uncertainty is more varied than is sometimes assumed. In order to examine the distinction, I unpack the idea of having probabilities, in particular by distinguishing three interpretations of probability: objective, epistemic, and subjective probability. I then claim that if we are concerned with whether we have probabilities at all-regardless of how low their epistemic credentials are-then we almost always have probabilities for policy-making. The reason is that subjective and epistemic probability are the relevant interpretations of probability and we almost always have subjective and epistemic probabilities. In contrast, if we are only concerned with probabilities that have sufficiently high epistemic credentials, then we obviously do not always have probabilities. Climate policy, for example, would then be a case of decision-making under uncertainty. But, so I argue, we should not dismiss probabilities with low epistemic credentials. Rather, when they are the best available probabilities our decision principles should make use of them. And, since they are almost always available, the risk-uncertainty distinction remains irrelevant.

Accepting uncertainty, assessing risk: decision quality in managing wildfire, forest resource values, and new technology

Treesearch

Jeffrey G. Borchers

2005-01-01

The risks, uncertainties, and social conflicts surrounding uncharacteristic wildfire and forest resource values have defied conventional approaches to planning and decision-making. Paradoxically, the adoption of technological innovations such as risk assessment, decision analysis, and landscape simulation models by land management organizations has been limited. The...

Prospect Theory and Interval-Valued Hesitant Set for Safety Evacuation Model

NASA Astrophysics Data System (ADS)

Kou, Meng; Lu, Na

2018-01-01

The study applies the research results of prospect theory and multi attribute decision making theory, combined with the complexity, uncertainty and multifactor influence of the underground mine fire system and takes the decision makers’ psychological behavior of emotion and intuition into full account to establish the intuitionistic fuzzy multiple attribute decision making method that is based on the prospect theory. The model established by this method can explain the decision maker’s safety evacuation decision behavior in the complex system of underground mine fire due to the uncertainty of the environment, imperfection of the information and human psychological behavior and other factors.

Pupil-linked arousal is driven by decision uncertainty and alters serial choice bias

NASA Astrophysics Data System (ADS)

Urai, Anne E.; Braun, Anke; Donner, Tobias H.

2017-03-01

While judging their sensory environments, decision-makers seem to use the uncertainty about their choices to guide adjustments of their subsequent behaviour. One possible source of these behavioural adjustments is arousal: decision uncertainty might drive the brain's arousal systems, which control global brain state and might thereby shape subsequent decision-making. Here, we measure pupil diameter, a proxy for central arousal state, in human observers performing a perceptual choice task of varying difficulty. Pupil dilation, after choice but before external feedback, reflects three hallmark signatures of decision uncertainty derived from a computational model. This increase in pupil-linked arousal boosts observers' tendency to alternate their choice on the subsequent trial. We conclude that decision uncertainty drives rapid changes in pupil-linked arousal state, which shape the serial correlation structure of ongoing choice behaviour.

Decision Making Under Uncertainty and Complexity: A Model-Based Scenario Approach to Supporting Integrated Water Resources Management

NASA Astrophysics Data System (ADS)

Liu, Y.; Gupta, H.; Wagener, T.; Stewart, S.; Mahmoud, M.; Hartmann, H.; Springer, E.

2007-12-01

Some of the most challenging issues facing contemporary water resources management are those typified by complex coupled human-environmental systems with poorly characterized uncertainties. In other words, major decisions regarding water resources have to be made in the face of substantial uncertainty and complexity. It has been suggested that integrated models can be used to coherently assemble information from a broad set of domains, and can therefore serve as an effective means for tackling the complexity of environmental systems. Further, well-conceived scenarios can effectively inform decision making, particularly when high complexity and poorly characterized uncertainties make the problem intractable via traditional uncertainty analysis methods. This presentation discusses the integrated modeling framework adopted by SAHRA, an NSF Science & Technology Center, to investigate stakeholder-driven water sustainability issues within the semi-arid southwestern US. The multi-disciplinary, multi-resolution modeling framework incorporates a formal scenario approach to analyze the impacts of plausible (albeit uncertain) alternative futures to support adaptive management of water resources systems. Some of the major challenges involved in, and lessons learned from, this effort will be discussed.

Constructing (un-)certainty: An exploration of journalistic decision-making in the reporting of neuroscience.

PubMed

Lehmkuhl, Markus; Peters, Hans Peter

2016-11-01

Based on 21 individual case studies, this article inventories the ways journalism deals with scientific uncertainty. The study identifies the decisions that impact a journalist's perception of a truth claim as unambiguous or ambiguous and the strategies to deal with uncertainty that arise from this perception. Key for understanding journalistic action is the outcome of three evaluations: What is the story about? How shall the story be told? What type of story is it? We reconstructed the strategies to overcome journalistic decision-making uncertainty in those cases in which they perceived scientific contingency as a problem. Journalism deals with uncertainty by way of omission, by contrasting the conflicting messages or by acknowledging the problem via the structure or language. One finding deserves particular mention: The lack of focus on scientific uncertainty is not only a problem of how journalists perceive and communicate but also a problem of how science communicates. © The Author(s) 2016.

Towards a more open debate about values in decision-making on agricultural biotechnology.

PubMed

Devos, Yann; Sanvido, Olivier; Tait, Joyce; Raybould, Alan

2014-12-01

Regulatory decision-making over the use of products of new technology aims to be based on science-based risk assessment. In some jurisdictions, decision-making about the cultivation of genetically modified (GM) plants is blocked supposedly because of scientific uncertainty about risks to the environment. However, disagreement about the acceptability of risks is primarily a dispute over normative values, which is not resolvable through natural sciences. Natural sciences may improve the quality and relevance of the scientific information used to support environmental risk assessments and make scientific uncertainties explicit, but offer little to resolve differences about values. Decisions about cultivating GM plants will thus not necessarily be eased by performing more research to reduce scientific uncertainty in environmental risk assessments, but by clarifying the debate over values. We suggest several approaches to reveal values in decision-making: (1) clarifying policy objectives; (2) determining what constitutes environmental harm; (3) making explicit the factual and normative premises on which risk assessments are based; (4) better demarcating environmental risk assessment studies from ecological research; (5) weighing the potential for environmental benefits (i.e., opportunities) as well as the potential for environmental harms (i.e., risks); and (6) expanding participation in the risk governance of GM plants. Recognising and openly debating differences about values will not remove controversy about the cultivation of GM plants. However, by revealing what is truly in dispute, debates about values will clarify decision-making criteria.

Probabilistic Risk Assessment to Inform Decision Making: Frequently Asked Questions

EPA Pesticide Factsheets

General concepts and principles of Probabilistic Risk Assessment (PRA), describe how PRA can improve the bases of Agency decisions, and provide illustrations of how PRA has been used in risk estimation and in describing the uncertainty in decision making.

Minimizing Uncertainties Impact in Decision Making with an Applicability Study for Economic Power Dispatch

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

Wang, Hong; Wang, Shaobu; Fan, Rui

This report summaries the work performed under the LDRD project on the preliminary study on knowledge automation, where specific focus has been made on the investigation of the impact of uncertainties of human decision making onto the optimization of the process operation. At first the statistics on signals from the Brain-Computing Interface (BCI) is analyzed so as to obtain the uncertainties characterization of human operators during the decision making phase using the electroencephalogram (EEG) signals. This is then followed by the discussions of an architecture that reveals the equivalence between optimization and closed loop feedback control design, where it hasmore » been shown that all the optimization problems can be transferred into the control design problem for closed loop systems. This has led to a “closed loop” framework, where the structure of the decision making is shown to be subjected to both process disturbances and controller’s uncertainties. The latter can well represent the uncertainties or randomness occurred during human decision making phase. As a result, a stochastic optimization problem has been formulated and a novel solution has been proposed using probability density function (PDF) shaping for both the cost function and the constraints using stochastic distribution control concept. A sufficient condition has been derived that guarantees the convergence of the optimal solution and discussions have been made for both the total probabilistic solution and chanced constrained optimization which have been well-studied in optimal power flows (OPF) area. A simple case study has been carried out for the economic dispatch of powers for a grid system when there are distributed energy resources (DERs) in the system, and encouraging results have been obtained showing that a significant savings on the generation cost can be expected.« less

Physicians’ Anxiety Due to Uncertainty and Use of Race in Medical Decision-Making

PubMed Central

Cunningham, Brooke A.; Bonham, Vence L.; Sellers, Sherrill L.; Yeh, Hsin-Chieh; Cooper, Lisa A.

2014-01-01

Background The explicit use of race in medical decision-making is contested. Researchers have hypothesized that physicians use race in care when they are uncertain. Objectives To investigate whether physician anxiety due to uncertainty is associated with a higher propensity to use race in medical decision-making. Research Design A national cross-sectional survey of general internists Subjects A national sample of 1738 clinically active general internists drawn from the SK&A physician database Measures Anxiety Due to Uncertainty (ADU) is a 5-item measure of emotional reactions to clinical uncertainty. Bonham and Sellers Racial Attributes in Clinical Evaluation (RACE) scale includes 7 items that measure self-reported use of race in medical decision-making. We used bivariate regression to test for associations between physician characteristics, ADU and RACE. Multivariate linear regression was performed to test for associations between ADU and RACE while adjusting for potential confounders. Results The mean score on ADU was 19.9 (SD=5.6). Mean score on RACE was 13.5 (SD=5.6). After adjusting for physician demographics, physicians with higher levels of ADU scored higher on RACE (+β=0.08 in RACE, p=0.04, for each 1-point increase in ADU), as did physicians who understand “race” to mean biological or genetic ancestral, rather than sociocultural, group. Physicians who graduated from a US medical school, completed fellowship, and had more white patients, scored lower on RACE. Conclusions This study demonstrates positive associations between physicians’ anxiety due to uncertainty, meanings attributed to race, and self-reported use of race in medical decision-making. Future research should examine the potential impact of these associations on patient outcomes and healthcare disparities. PMID:25025871

Risk Communication in Special Education.

ERIC Educational Resources Information Center

Bull, Kay S.; Kimball, Sarah

This paper describes the application of a risk-based decision-making process in education and the use of risk communication with special education students and their parents. Risk-based decision making clarifies uncertainties inherent in a decision by examining the probability of a resulting harmful effect and the consequences of decisions made.…

Strategic control in decision-making under uncertainty.

PubMed

Venkatraman, Vinod; Huettel, Scott A

2012-04-01

Complex economic decisions - whether investing money for retirement or purchasing some new electronic gadget - often involve uncertainty about the likely consequences of our choices. Critical for resolving that uncertainty are strategic meta-decision processes, which allow people to simplify complex decision problems, evaluate outcomes against a variety of contexts, and flexibly match behavior to changes in the environment. In recent years, substantial research has implicated the dorsomedial prefrontal cortex (dmPFC) in the flexible control of behavior. However, nearly all such evidence comes from paradigms involving executive function or response selection, not complex decision-making. Here, we review evidence that demonstrates that the dmPFC contributes to strategic control in complex decision-making. This region contains a functional topography such that the posterior dmPFC supports response-related control, whereas the anterior dmPFC supports strategic control. Activation in the anterior dmPFC signals changes in how a decision problem is represented, which in turn can shape computational processes elsewhere in the brain. Based on these findings, we argue for both generalized contributions of the dmPFC to cognitive control, and specific computational roles for its subregions depending upon the task demands and context. We also contend that these strategic considerations are likely to be critical for decision-making in other domains, including interpersonal interactions in social settings. © 2012 The Authors. European Journal of Neuroscience © 2012 Federation of European Neuroscience Societies and Blackwell Publishing Ltd.

Strategic Control in Decision Making under Uncertainty

PubMed Central

Venkatraman, Vinod; Huettel, Scott

2012-01-01

Complex economic decisions – whether investing money for retirement or purchasing some new electronic gadget – often involve uncertainty about the likely consequences of our choices. Critical for resolving that uncertainty are strategic meta-decision processes, which allow people to simplify complex decision problems, to evaluate outcomes against a variety of contexts, and to flexibly match behavior to changes in the environment. In recent years, substantial research implicates the dorsomedial prefrontal cortex (dmPFC) in the flexible control of behavior. However, nearly all such evidence comes from paradigms involving executive function or response selection, not complex decision making. Here, we review evidence that demonstrates that the dmPFC contributes to strategic control in complex decision making. This region contains a functional topography such that the posterior dmPFC supports response-related control while the anterior dmPFC supports strategic control. Activation in the anterior dmPFC signals changes in how a decision problem is represented, which in turn can shape computational processes elsewhere in the brain. Based on these findings, we argue both for generalized contributions of the dmPFC to cognitive control, and for specific computational roles for its subregions depending upon the task demands and context. We also contend that these strategic considerations are also likely to be critical for decision making in other domains, including interpersonal interactions in social settings. PMID:22487037

How contextual issues can distort shared decision making.

PubMed

Gartlehner, Gerald; Matyas, Nina

2016-12-01

Shared decision making in medicine has become a widely promoted approach. The goal is for patients and physicians to reach a mutual, informed decision by taking into consideration scientific evidence, clinical experience, and the patient's personal values or preferences. Shared decision making, however, is not a straightforward process. In practice, it might fall short of what it promises and might even be misused to whitewash monetary motives. In this article, which summarizes a presentation given at the 17 th Annual Conference of the German Network Evidence-based Medicine on March 4 th , 2016 in Cologne, Germany, we discuss three contextual factors that in our opinion can have a tremendous impact on any informed decision making: 1) opinions and convictions of physicians or other clinicians; 2) uncertainty of the evidence regarding benefits and harms; 3) uncertainty of patients about their own values and preferences. But despite barriers and shortcomings, modern medicine currently does not have an alternative to shared decision making. Shared decision making has become a central theme in good quality health care because it has a strong ethical component. Advocates of shared decision making, however, must realize that not all patients prefer to participate in decision making. For those who do, however, we must ensure that shared decisions can be made in a neutral environment as free of biases and conflicts of interest as possible. Copyright © 2016. Published by Elsevier GmbH.

Differential Effects of Insular and Ventromedial Prefrontal Cortex Lesions on Risky Decision-Making

ERIC Educational Resources Information Center

Clark, L.; Bechara, A.; Damasio, H.; Aitken, M. R. F.; Sahakian, B. J.; Robbins, T. W.

2008-01-01

The ventromedial prefrontal cortex (vmPFC) and insular cortex are implicated in distributed neural circuitry that supports emotional decision-making. Previous studies of patients with vmPFC lesions have focused primarily on decision-making under uncertainty, when outcome probabilities are ambiguous (e.g. the Iowa Gambling Task). It remains unclear…

Uncertainty and Cognitive Control

PubMed Central

Mushtaq, Faisal; Bland, Amy R.; Schaefer, Alexandre

2011-01-01

A growing trend of neuroimaging, behavioral, and computational research has investigated the topic of outcome uncertainty in decision-making. Although evidence to date indicates that humans are very effective in learning to adapt to uncertain situations, the nature of the specific cognitive processes involved in the adaptation to uncertainty are still a matter of debate. In this article, we reviewed evidence suggesting that cognitive control processes are at the heart of uncertainty in decision-making contexts. Available evidence suggests that: (1) There is a strong conceptual overlap between the constructs of uncertainty and cognitive control; (2) There is a remarkable overlap between the neural networks associated with uncertainty and the brain networks subserving cognitive control; (3) The perception and estimation of uncertainty might play a key role in monitoring processes and the evaluation of the “need for control”; (4) Potential interactions between uncertainty and cognitive control might play a significant role in several affective disorders. PMID:22007181

Integrative evaluation for sustainable decisions of urban wastewater system management under uncertainty

NASA Astrophysics Data System (ADS)

Hadjimichael, A.; Corominas, L.; Comas, J.

2017-12-01

With sustainable development as their overarching goal, urban wastewater system (UWS) managers need to take into account multiple social, economic, technical and environmental facets related to their decisions. In this complex decision-making environment, uncertainty can be formidable. It is present both in the ways the system is interpreted stochastically, but also in its natural ever-shifting behavior. This inherent uncertainty suggests that wiser decisions would be made under an adaptive and iterative decision-making regime. No decision-support framework has been presented in the literature to effectively addresses all these needs. The objective of this work is to describe such a conceptual framework to evaluate and compare alternative solutions for various UWS challenges within an adaptive management structure. Socio-economic aspects such as externalities are taken into account, along with other traditional criteria as necessary. Robustness, reliability and resilience analyses test the performance of the system against present and future variability. A valuation uncertainty analysis incorporates uncertain valuation assumptions in the decision-making process. The framework is demonstrated with an application to a case study presenting a typical problem often faced by managers: poor river water quality, increasing population, and more stringent water quality legislation. The application of the framework made use of: i) a cost-benefit analysis including monetized environmental benefits and damages; ii) a robustness analysis of system performance against future conditions; iii) reliability and resilience analyses of the system given contextual variability; and iv) a valuation uncertainty analysis of model parameters. The results suggest that the installation of bigger volumes would give rise to increased benefits despite larger capital costs, as well as increased robustness and resilience. Population numbers appear to affect the estimated benefits most, followed by electricity prices and climate change projections. The presented framework is expected to be a valuable tool for the next generation of UWS decision-making and the application demonstrates a novel and valuable integration of metrics and methods for UWS analysis.

Fostering climate dialogue by introducing students to uncertainty in decision-making

NASA Astrophysics Data System (ADS)

Addor, N.; Ewen, T.; Johnson, L.; Coltekin, A.; Derungs, C.; Muccione, V.

2014-12-01

Uncertainty is present in all fields of climate research, spanning from climate projections, to assessing regional impacts and vulnerabilities to adaptation policy and decision-making. The complex and interdisciplinary nature of climate information, however, makes the decision-making process challenging. This process is further hindered by a lack of institutionalized dialogue between climate researchers, decision-makers and user groups. Forums that facilitate such dialogue would allow these groups to actively engage with each other to improve decisions. In parallel, introducing students to these challenges is one way to foster such climate dialogue. We present the design and outcome of an innovative workshop-seminar series we convened at the University of Zurich to demonstrate the pedagogical importance of such forums. An initial two-day workshop brought together 50 participants, including bachelor, master and PhD students and academic staff, and nine speakers from academia, industry, government, and philanthropy. The main objectives were to provide participants with tools to communicate uncertainty in their current or future research projects, to foster exchange between practitioners, students and scientists from different backgrounds and finally to expose students to multidisciplinary collaborations and real-world problems involving decisions under uncertainty. An opinion survey conducted before and after the workshop enabled us to observe changes in participants' perspectives on what information and tools should be exchanged between researchers and decision-makers to better address uncertainty. Responses demonstrated a marked shift from a pre-workshop vertical conceptualization of researcher-user group interaction to a post-workshop horizontal mode: in the former, researchers were portrayed as bestowing data-based products to decision-makers, while in the latter, both sets of actors engaged in frequent communication, exchanging their needs and expertise. Drawing on examples from the course evaluation, we seek to encourage the organization of similar events, introducing students to these challenges at an early stage of their education and career as a first step towards improving future dialogue.

Evaluating a multispecies adaptive management framework: Must uncertainty impede effective decision-making?

USGS Publications Warehouse

Smith, David R.; McGowan, Conor P.; Daily, Jonathan P.; Nichols, James D.; Sweka, John A.; Lyons, James E.

2013-01-01

Application of adaptive management to complex natural resource systems requires careful evaluation to ensure that the process leads to improved decision-making. As part of that evaluation, adaptive policies can be compared with alternative nonadaptive management scenarios. Also, the value of reducing structural (ecological) uncertainty to achieving management objectives can be quantified.A multispecies adaptive management framework was recently adopted by the Atlantic States Marine Fisheries Commission for sustainable harvest of Delaware Bay horseshoe crabs Limulus polyphemus, while maintaining adequate stopover habitat for migrating red knots Calidris canutus rufa, the focal shorebird species. The predictive model set encompassed the structural uncertainty in the relationships between horseshoe crab spawning, red knot weight gain and red knot vital rates. Stochastic dynamic programming was used to generate a state-dependent strategy for harvest decisions given that uncertainty. In this paper, we employed a management strategy evaluation approach to evaluate the performance of this adaptive management framework. Active adaptive management was used by including model weights as state variables in the optimization and reducing structural uncertainty by model weight updating.We found that the value of information for reducing structural uncertainty is expected to be low, because the uncertainty does not appear to impede effective management. Harvest policy responded to abundance levels of both species regardless of uncertainty in the specific relationship that generated those abundances. Thus, the expected horseshoe crab harvest and red knot abundance were similar when the population generating model was uncertain or known, and harvest policy was robust to structural uncertainty as specified.Synthesis and applications. The combination of management strategy evaluation with state-dependent strategies from stochastic dynamic programming was an informative approach to evaluate adaptive management performance and value of learning. Although natural resource decisions are characterized by uncertainty, not all uncertainty will cause decisions to be altered substantially, as we found in this case. It is important to incorporate uncertainty into the decision framing and evaluate the effect of reducing that uncertainty on achieving the desired outcomes

Attitudes toward risk and ambiguity in patients with autism spectrum disorder.

PubMed

Fujino, Junya; Tei, Shisei; Hashimoto, Ryu-Ichiro; Itahashi, Takashi; Ohta, Haruhisa; Kanai, Chieko; Okada, Rieko; Kubota, Manabu; Nakamura, Motoaki; Kato, Nobumasa; Takahashi, Hidehiko

2017-01-01

Although the ability to make optimal decisions under uncertainty is an integral part of everyday life, individuals with autism spectrum disorder (ASD) frequently report that they experience difficulties with this skill. In behavioral economics, researchers distinguish two types of uncertainty to understand decision-making in this setting: risk (known probabilities) and ambiguity (unknown probabilities). However, it remains unclear how individuals with ASD behave under risk and ambiguity, despite growing evidence of their altered decision-making under uncertainty. We therefore extended previous research by studying the attitudes of those with ASD toward risk and ambiguity in both positive and negative contexts (i.e., gain and loss). In gain contexts, no significant difference was observed between the groups in risk attitudes, but ambiguity aversion was attenuated in ASD. In loss contexts, ambiguity attitudes did not significantly differ between the groups, but the ASD participants were less risk-seeking compared with the controls. In addition, insensitivity to the context change under risk and ambiguity in ASD was both significantly associated with poor social skills. These results improve our understanding of altered decision-making under uncertainty by disentangling the attitudes toward risk and ambiguity in ASD individuals. Applying behavioral economic tools may provide insights into the mechanisms underlying behavioral disturbances in ASD.

Decision making under uncertainty: Recommendations for the Wildland Fire Decision Support System (WFDSS)

Treesearch

Matthew P. Thompson

2015-01-01

The management of wildfire is a dynamic, complex, and fundamentally uncertain enterprise. Fire managers face uncertainties regarding fire weather and subsequent influence on fire behavior, the effects of fire on socioeconomic and ecological resources, and the efficacy of alternative suppression actions on fire outcomes. In these types of difficult decision environments...

Uncertainty analysis for effluent trading planning using a Bayesian estimation-based simulation-optimization modeling approach.

PubMed

Zhang, J L; Li, Y P; Huang, G H; Baetz, B W; Liu, J

2017-06-01

In this study, a Bayesian estimation-based simulation-optimization modeling approach (BESMA) is developed for identifying effluent trading strategies. BESMA incorporates nutrient fate modeling with soil and water assessment tool (SWAT), Bayesian estimation, and probabilistic-possibilistic interval programming with fuzzy random coefficients (PPI-FRC) within a general framework. Based on the water quality protocols provided by SWAT, posterior distributions of parameters can be analyzed through Bayesian estimation; stochastic characteristic of nutrient loading can be investigated which provides the inputs for the decision making. PPI-FRC can address multiple uncertainties in the form of intervals with fuzzy random boundaries and the associated system risk through incorporating the concept of possibility and necessity measures. The possibility and necessity measures are suitable for optimistic and pessimistic decision making, respectively. BESMA is applied to a real case of effluent trading planning in the Xiangxihe watershed, China. A number of decision alternatives can be obtained under different trading ratios and treatment rates. The results can not only facilitate identification of optimal effluent-trading schemes, but also gain insight into the effects of trading ratio and treatment rate on decision making. The results also reveal that decision maker's preference towards risk would affect decision alternatives on trading scheme as well as system benefit. Compared with the conventional optimization methods, it is proved that BESMA is advantageous in (i) dealing with multiple uncertainties associated with randomness and fuzziness in effluent-trading planning within a multi-source, multi-reach and multi-period context; (ii) reflecting uncertainties existing in nutrient transport behaviors to improve the accuracy in water quality prediction; and (iii) supporting pessimistic and optimistic decision making for effluent trading as well as promoting diversity of decision alternatives. Copyright © 2017 Elsevier Ltd. All rights reserved.

Neural Mechanisms of Updating under Reducible and Irreducible Uncertainty.

PubMed

Kobayashi, Kenji; Hsu, Ming

2017-07-19

Adaptive decision making depends on an agent's ability to use environmental signals to reduce uncertainty. However, because of multiple types of uncertainty, agents must take into account not only the extent to which signals violate prior expectations but also whether uncertainty can be reduced in the first place. Here we studied how human brains of both sexes respond to signals under conditions of reducible and irreducible uncertainty. We show behaviorally that subjects' value updating was sensitive to the reducibility of uncertainty, and could be quantitatively characterized by a Bayesian model where agents ignore expectancy violations that do not update beliefs or values. Using fMRI, we found that neural processes underlying belief and value updating were separable from responses to expectancy violation, and that reducibility of uncertainty in value modulated connections from belief-updating regions to value-updating regions. Together, these results provide insights into how agents use knowledge about uncertainty to make better decisions while ignoring mere expectancy violation. SIGNIFICANCE STATEMENT To make good decisions, a person must observe the environment carefully, and use these observations to reduce uncertainty about consequences of actions. Importantly, uncertainty should not be reduced purely based on how surprising the observations are, particularly because in some cases uncertainty is not reducible. Here we show that the human brain indeed reduces uncertainty adaptively by taking into account the nature of uncertainty and ignoring mere surprise. Behaviorally, we show that human subjects reduce uncertainty in a quasioptimal Bayesian manner. Using fMRI, we characterize brain regions that may be involved in uncertainty reduction, as well as the network they constitute, and dissociate them from brain regions that respond to mere surprise. Copyright © 2017 the authors 0270-6474/17/376972-11$15.00/0.

Neural Mechanisms of Updating under Reducible and Irreducible Uncertainty

PubMed Central

2017-01-01

Adaptive decision making depends on an agent's ability to use environmental signals to reduce uncertainty. However, because of multiple types of uncertainty, agents must take into account not only the extent to which signals violate prior expectations but also whether uncertainty can be reduced in the first place. Here we studied how human brains of both sexes respond to signals under conditions of reducible and irreducible uncertainty. We show behaviorally that subjects' value updating was sensitive to the reducibility of uncertainty, and could be quantitatively characterized by a Bayesian model where agents ignore expectancy violations that do not update beliefs or values. Using fMRI, we found that neural processes underlying belief and value updating were separable from responses to expectancy violation, and that reducibility of uncertainty in value modulated connections from belief-updating regions to value-updating regions. Together, these results provide insights into how agents use knowledge about uncertainty to make better decisions while ignoring mere expectancy violation. SIGNIFICANCE STATEMENT To make good decisions, a person must observe the environment carefully, and use these observations to reduce uncertainty about consequences of actions. Importantly, uncertainty should not be reduced purely based on how surprising the observations are, particularly because in some cases uncertainty is not reducible. Here we show that the human brain indeed reduces uncertainty adaptively by taking into account the nature of uncertainty and ignoring mere surprise. Behaviorally, we show that human subjects reduce uncertainty in a quasioptimal Bayesian manner. Using fMRI, we characterize brain regions that may be involved in uncertainty reduction, as well as the network they constitute, and dissociate them from brain regions that respond to mere surprise. PMID:28626019

Research implications of science-informed, value-based decision making.

PubMed

Dowie, Jack

2004-01-01

In 'Hard' science, scientists correctly operate as the 'guardians of certainty', using hypothesis testing formulations and value judgements about error rates and time discounting that make classical inferential methods appropriate. But these methods can neither generate most of the inputs needed by decision makers in their time frame, nor generate them in a form that allows them to be integrated into the decision in an analytically coherent and transparent way. The need for transparent accountability in public decision making under uncertainty and value conflict means the analytical coherence provided by the stochastic Bayesian decision analytic approach, drawing on the outputs of Bayesian science, is needed. If scientific researchers are to play the role they should be playing in informing value-based decision making, they need to see themselves also as 'guardians of uncertainty', ensuring that the best possible current posterior distributions on relevant parameters are made available for decision making, irrespective of the state of the certainty-seeking research. The paper distinguishes the actors employing different technologies in terms of the focus of the technology (knowledge, values, choice); the 'home base' mode of their activity on the cognitive continuum of varying analysis-to-intuition ratios; and the underlying value judgements of the activity (especially error loss functions and time discount rates). Those who propose any principle of decision making other than the banal 'Best Principle', including the 'Precautionary Principle', are properly interpreted as advocates seeking to have their own value judgements and preferences regarding mode location apply. The task for accountable decision makers, and their supporting technologists, is to determine the best course of action under the universal conditions of uncertainty and value difference/conflict.

Decision-Making Amplification under Uncertainty: An Exploratory Study of Behavioral Similarity and Intelligent Decision Support Systems

ERIC Educational Resources Information Center

Campbell, Merle Wayne

2013-01-01

Intelligent decision systems have the potential to support and greatly amplify human decision-making across a number of industries and domains. However, despite the rapid improvement in the underlying capabilities of these "intelligent" systems, increasing their acceptance as decision aids in industry has remained a formidable challenge.…

Essential information: Uncertainty and optimal control of Ebola outbreaks

USGS Publications Warehouse

Li, Shou-Li; Bjornstad, Ottar; Ferrari, Matthew J.; Mummah, Riley; Runge, Michael C.; Fonnesbeck, Christopher J.; Tildesley, Michael J.; Probert, William J. M.; Shea, Katriona

2017-01-01

Early resolution of uncertainty during an epidemic outbreak can lead to rapid and efficient decision making, provided that the uncertainty affects prioritization of actions. The wide range in caseload projections for the 2014 Ebola outbreak caused great concern and debate about the utility of models. By coding and running 37 published Ebola models with five candidate interventions, we found that, despite this large variation in caseload projection, the ranking of management options was relatively consistent. Reducing funeral transmission and reducing community transmission were generally ranked as the two best options. Value of information (VoI) analyses show that caseloads could be reduced by 11% by resolving all model-specific uncertainties, with information about model structure accounting for 82% of this reduction and uncertainty about caseload only accounting for 12%. Our study shows that the uncertainty that is of most interest epidemiologically may not be the same as the uncertainty that is most relevant for management. If the goal is to improve management outcomes, then the focus of study should be to identify and resolve those uncertainties that most hinder the choice of an optimal intervention. Our study further shows that simplifying multiple alternative models into a smaller number of relevant groups (here, with shared structure) could streamline the decision-making process and may allow for a better integration of epidemiological modeling and decision making for policy.

Essential information: Uncertainty and optimal control of Ebola outbreaks.

PubMed

Li, Shou-Li; Bjørnstad, Ottar N; Ferrari, Matthew J; Mummah, Riley; Runge, Michael C; Fonnesbeck, Christopher J; Tildesley, Michael J; Probert, William J M; Shea, Katriona

2017-05-30

Early resolution of uncertainty during an epidemic outbreak can lead to rapid and efficient decision making, provided that the uncertainty affects prioritization of actions. The wide range in caseload projections for the 2014 Ebola outbreak caused great concern and debate about the utility of models. By coding and running 37 published Ebola models with five candidate interventions, we found that, despite this large variation in caseload projection, the ranking of management options was relatively consistent. Reducing funeral transmission and reducing community transmission were generally ranked as the two best options. Value of information (VoI) analyses show that caseloads could be reduced by 11% by resolving all model-specific uncertainties, with information about model structure accounting for 82% of this reduction and uncertainty about caseload only accounting for 12%. Our study shows that the uncertainty that is of most interest epidemiologically may not be the same as the uncertainty that is most relevant for management. If the goal is to improve management outcomes, then the focus of study should be to identify and resolve those uncertainties that most hinder the choice of an optimal intervention. Our study further shows that simplifying multiple alternative models into a smaller number of relevant groups (here, with shared structure) could streamline the decision-making process and may allow for a better integration of epidemiological modeling and decision making for policy.

Multi-criteria group decision making for evaluating the performance of e-waste recycling programs under uncertainty.

PubMed

Wibowo, Santoso; Deng, Hepu

2015-06-01

This paper presents a multi-criteria group decision making approach for effectively evaluating the performance of e-waste recycling programs under uncertainty in an organization. Intuitionistic fuzzy numbers are used for adequately representing the subjective and imprecise assessments of the decision makers in evaluating the relative importance of evaluation criteria and the performance of individual e-waste recycling programs with respect to individual criteria in a given situation. An interactive fuzzy multi-criteria decision making algorithm is developed for facilitating consensus building in a group decision making environment to ensure that all the interest of individual decision makers have been appropriately considered in evaluating alternative e-waste recycling programs with respect to their corporate sustainability performance. The developed algorithm is then incorporated into a multi-criteria decision support system for making the overall performance evaluation process effectively and simple to use. Such a multi-criteria decision making system adequately provides organizations with a proactive mechanism for incorporating the concept of corporate sustainability into their regular planning decisions and business practices. An example is presented for demonstrating the applicability of the proposed approach in evaluating the performance of e-waste recycling programs in organizations. Copyright © 2015 Elsevier Ltd. All rights reserved.

Accounting for methodological, structural, and parameter uncertainty in decision-analytic models: a practical guide.

PubMed

Bilcke, Joke; Beutels, Philippe; Brisson, Marc; Jit, Mark

2011-01-01

Accounting for uncertainty is now a standard part of decision-analytic modeling and is recommended by many health technology agencies and published guidelines. However, the scope of such analyses is often limited, even though techniques have been developed for presenting the effects of methodological, structural, and parameter uncertainty on model results. To help bring these techniques into mainstream use, the authors present a step-by-step guide that offers an integrated approach to account for different kinds of uncertainty in the same model, along with a checklist for assessing the way in which uncertainty has been incorporated. The guide also addresses special situations such as when a source of uncertainty is difficult to parameterize, resources are limited for an ideal exploration of uncertainty, or evidence to inform the model is not available or not reliable. for identifying the sources of uncertainty that influence results most are also described. Besides guiding analysts, the guide and checklist may be useful to decision makers who need to assess how well uncertainty has been accounted for in a decision-analytic model before using the results to make a decision.

Structured decision making for managing pneumonia epizootics in bighorn sheep

USGS Publications Warehouse

Sells, Sarah N.; Mitchell, Michael S.; Edwards, Victoria L.; Gude, Justin A.; Anderson, Neil J.

2016-01-01

Good decision-making is essential to conserving wildlife populations. Although there may be multiple ways to address a problem, perfect solutions rarely exist. Managers are therefore tasked with identifying decisions that will best achieve desired outcomes. Structured decision making (SDM) is a method of decision analysis used to identify the most effective, efficient, and realistic decisions while accounting for values and priorities of the decision maker. The stepwise process includes identifying the management problem, defining objectives for solving the problem, developing alternative approaches to achieve the objectives, and formally evaluating which alternative is most likely to accomplish the objectives. The SDM process can be more effective than informal decision-making because it provides a transparent way to quantitatively evaluate decisions for addressing multiple management objectives while incorporating science, uncertainty, and risk tolerance. To illustrate the application of this process to a management need, we present an SDM-based decision tool developed to identify optimal decisions for proactively managing risk of pneumonia epizootics in bighorn sheep (Ovis canadensis) in Montana. Pneumonia epizootics are a major challenge for managers due to long-term impacts to herds, epistemic uncertainty in timing and location of future epizootics, and consequent difficulty knowing how or when to manage risk. The decision tool facilitates analysis of alternative decisions for how to manage herds based on predictions from a risk model, herd-specific objectives, and predicted costs and benefits of each alternative. Decision analyses for 2 example herds revealed that meeting management objectives necessitates specific approaches unique to each herd. The analyses showed how and under what circumstances the alternatives are optimal compared to other approaches and current management. Managers can be confident that these decisions are effective, efficient, and realistic because they explicitly account for important considerations managers implicitly weigh when making decisions, including competing management objectives, uncertainty in potential outcomes, and risk tolerance.

Uncertainty and equipoise: at interplay between epistemology, decision making and ethics.

PubMed

Djulbegovic, Benjamin

2011-10-01

In recent years, various authors have proposed that the concept of equipoise be abandoned because it conflates the practice of clinical care with clinical research. At the same time, the equipoise opponents acknowledge the necessity of clinical research if there are unresolved uncertainties about the effects of proposed healthcare interventions. As equipoise represents just 1 measure of uncertainty, proposals to abandon equipoise while maintaining a requirement for addressing uncertainties are contradictory and ultimately not valid. As acknowledgment and articulation of uncertainties represent key scientific and moral requirements for human experimentation, the concept of equipoise remains the most useful framework to link the theory of human experimentation with the theory of rational choice. In this article, I show how uncertainty (equipoise) is at the intersection between epistemology, decision making and ethics of clinical research. In particular, I show how our formulation of responses to uncertainties of hoped-for benefits and unknown harms of testing is a function of the way humans cognitively process information. This approach is based on the view that considerations of ethics and rationality cannot be separated. I analyze the response to uncertainties as it relates to the dual-processing theory, which postulates that rational approach to (clinical research) decision making depends both on analytical, deliberative processes embodied in scientific method (system II), and good human intuition (system I). Ultimately, our choices can only become wiser if we understand a close and intertwined relationship between irreducible uncertainty, inevitable errors and unavoidable injustice.

Uncertainty and Equipoise: At Interplay Between Epistemology, Decision-Making and Ethics

PubMed Central

Djulbegovic, Benjamin

2011-01-01

In recent years, various authors have proposed that the concept of equipoise be abandoned since it conflates the practice of clinical care with clinical research. At the same time, the equipoise opponents acknowledge the necessity of clinical research if there are unresolved uncertainties about the effects of proposed healthcare interventions. Since equipoise represents just one measure of uncertainty, proposals to abandon equipoise while maintaining a requirement for addressing uncertainties are contradictory and ultimately not valid. As acknowledgment and articulation of uncertainties represent key scientific and moral requirements for human experimentation, the concept of equipoise remains the most useful framework to link the theory of human experimentation with the theory of rational choice. In this paper, I show how uncertainty (equipoise) is at the intersection between epistemology, decision-making and ethics of clinical research. In particular, I show how our formulation of responses to uncertainties of hoped-for benefits and unknown harms of testing is a function of the way humans cognitively process information. This approach is based on the view that considerations of ethics and rationality cannot be separated. I analyze the response to uncertainties as it relates to the dual-processing theory, which postulates that rational approach to (clinical research) decision-making depends both on analytical, deliberative processes embodied in scientific method (system II) and “good” human intuition (system I). Ultimately, our choices can only become wiser if we understand a close and intertwined relationship between irreducible uncertainty, inevitable errors, and unavoidable injustice. PMID:21817885

Uncertainty Representation and Interpretation in Model-Based Prognostics Algorithms Based on Kalman Filter Estimation

NASA Technical Reports Server (NTRS)

Galvan, Jose Ramon; Saxena, Abhinav; Goebel, Kai Frank

2012-01-01

This article discusses several aspects of uncertainty representation and management for model-based prognostics methodologies based on our experience with Kalman Filters when applied to prognostics for electronics components. In particular, it explores the implications of modeling remaining useful life prediction as a stochastic process, and how it relates to uncertainty representation, management and the role of prognostics in decision-making. A distinction between the interpretations of estimated remaining useful life probability density function is explained and a cautionary argument is provided against mixing interpretations for two while considering prognostics in making critical decisions.

Uncertainty exposure causes behavioural sensitization and increases risky decision-making in male rats: toward modelling gambling disorder.

PubMed

Zeeb, Fiona D; Li, Zhaoxia; Fisher, Daniel C; Zack, Martin H; Fletcher, Paul J

2017-11-01

An animal model of gambling disorder, previously known as pathological gambling, could advance our understanding of the disorder and help with treatment development. We hypothesized that repeated exposure to uncertainty during gambling induces behavioural and dopamine (DA) sensitization - similar to chronic exposure to drugs of abuse. Uncertainty exposure (UE) may also increase risky decision-making in an animal model of gambling disorder. Male Sprague Dawley rats received 56 UE sessions, during which animals responded for saccharin according to an unpredictable, variable ratio schedule of reinforcement (VR group). Control animals responded on a predictable, fixed ratio schedule (FR group). Rats yoked to receive unpredictable reward were also included (Y group). Animals were then tested on the Rat Gambling Task (rGT), an analogue of the Iowa Gambling Task, to measure decision-making. Compared with the FR group, the VR and Y groups experienced a greater locomotor response following administration of amphetamine. On the rGT, the FR and Y groups preferred the advantageous options over the risky, disadvantageous options throughout testing (40 sessions). However, rats in the VR group did not have a significant preference for the advantageous options during sessions 20-40. Amphetamine had a small, but significant, effect on decision-making only in the VR group. After rGT testing, only the VR group showed greater hyperactivity following administration of amphetamine compared with the FR group. Reward uncertainty was the only gambling feature modelled. Actively responding for uncertain reward likely sensitized the DA system and impaired the ability to make optimal decisions, modelling some aspects of gambling disorder.

Managing Uncertainty: Environmental Analysis/Forecasting in Academic Planning.

ERIC Educational Resources Information Center

Morrison, James L.; Mecca, Thomas V.

An approach to environmental analysis and forecasting that educational policymakers can employ in dealing with the level of uncertainty in strategic decision making is presented. Traditional planning models are weak in identifying environmental changes and assessing their organizational impact. The proposed approach does not lead decision makers…

Embracing uncertainty in applied ecology.

PubMed

Milner-Gulland, E J; Shea, K

2017-12-01

Applied ecologists often face uncertainty that hinders effective decision-making.Common traps that may catch the unwary are: ignoring uncertainty, acknowledging uncertainty but ploughing on, focussing on trivial uncertainties, believing your models, and unclear objectives.We integrate research insights and examples from a wide range of applied ecological fields to illustrate advances that are generally underused, but could facilitate ecologists' ability to plan and execute research to support management.Recommended approaches to avoid uncertainty traps are: embracing models, using decision theory, using models more effectively, thinking experimentally, and being realistic about uncertainty. Synthesis and applications . Applied ecologists can become more effective at informing management by using approaches that explicitly take account of uncertainty.

Probabilistic Flood Maps to support decision-making: Mapping the Value of Information

NASA Astrophysics Data System (ADS)

Alfonso, L.; Mukolwe, M. M.; Di Baldassarre, G.

2016-02-01

Floods are one of the most frequent and disruptive natural hazards that affect man. Annually, significant flood damage is documented worldwide. Flood mapping is a common preimpact flood hazard mitigation measure, for which advanced methods and tools (such as flood inundation models) are used to estimate potential flood extent maps that are used in spatial planning. However, these tools are affected, largely to an unknown degree, by both epistemic and aleatory uncertainty. Over the past few years, advances in uncertainty analysis with respect to flood inundation modeling show that it is appropriate to adopt Probabilistic Flood Maps (PFM) to account for uncertainty. However, the following question arises; how can probabilistic flood hazard information be incorporated into spatial planning? Thus, a consistent framework to incorporate PFMs into the decision-making is required. In this paper, a novel methodology based on Decision-Making under Uncertainty theories, in particular Value of Information (VOI) is proposed. Specifically, the methodology entails the use of a PFM to generate a VOI map, which highlights floodplain locations where additional information is valuable with respect to available floodplain management actions and their potential consequences. The methodology is illustrated with a simplified example and also applied to a real case study in the South of France, where a VOI map is analyzed on the basis of historical land use change decisions over a period of 26 years. Results show that uncertain flood hazard information encapsulated in PFMs can aid decision-making in floodplain planning.

The impact of uncertainty on optimal emission policies

NASA Astrophysics Data System (ADS)

Botta, Nicola; Jansson, Patrik; Ionescu, Cezar

2018-05-01

We apply a computational framework for specifying and solving sequential decision problems to study the impact of three kinds of uncertainties on optimal emission policies in a stylized sequential emission problem.We find that uncertainties about the implementability of decisions on emission reductions (or increases) have a greater impact on optimal policies than uncertainties about the availability of effective emission reduction technologies and uncertainties about the implications of trespassing critical cumulated emission thresholds. The results show that uncertainties about the implementability of decisions on emission reductions (or increases) call for more precautionary policies. In other words, delaying emission reductions to the point in time when effective technologies will become available is suboptimal when these uncertainties are accounted for rigorously. By contrast, uncertainties about the implications of exceeding critical cumulated emission thresholds tend to make early emission reductions less rewarding.

Evidence accumulation in obsessive-compulsive disorder: the role of uncertainty and monetary reward on perceptual decision-making thresholds.

PubMed

Banca, Paula; Vestergaard, Martin D; Rankov, Vladan; Baek, Kwangyeol; Mitchell, Simon; Lapa, Tatyana; Castelo-Branco, Miguel; Voon, Valerie

2015-03-13

The compulsive behaviour underlying obsessive-compulsive disorder (OCD) may be related to abnormalities in decision-making. The inability to commit to ultimate decisions, for example, patients unable to decide whether their hands are sufficiently clean, may reflect failures in accumulating sufficient evidence before a decision. Here we investigate the process of evidence accumulation in OCD in perceptual discrimination, hypothesizing enhanced evidence accumulation relative to healthy volunteers. Twenty-eight OCD patients and thirty-five controls were tested with a low-level visual perceptual task (random-dot-motion task, RDMT) and two response conflict control tasks. Regression analysis across different motion coherence levels and Hierarchical Drift Diffusion Modelling (HDDM) were used to characterize response strategies between groups in the RDMT. Patients required more evidence under high uncertainty perceptual contexts, as indexed by longer response time and higher decision boundaries. HDDM, which defines a decision when accumulated noisy evidence reaches a decision boundary, further showed slower drift rate towards the decision boundary reflecting poorer quality of evidence entering the decision process in patients under low uncertainty. With monetary incentives emphasizing speed and penalty for slower responses, patients decreased the decision thresholds relative to controls, accumulating less evidence in low uncertainty. These findings were unrelated to visual perceptual deficits and response conflict. This study provides evidence for impaired decision-formation processes in OCD, with a differential influence of high and low uncertainty contexts on evidence accumulation (decision threshold) and on the quality of evidence gathered (drift rates). It further emphasizes that OCD patients are sensitive to monetary incentives heightening speed in the speed-accuracy tradeoff, improving evidence accumulation.

Satisficing in split-second decision making is characterized by strategic cue discounting.

PubMed

Oh, Hanna; Beck, Jeffrey M; Zhu, Pingping; Sommer, Marc A; Ferrari, Silvia; Egner, Tobias

2016-12-01

Much of our real-life decision making is bounded by uncertain information, limitations in cognitive resources, and a lack of time to allocate to the decision process. It is thought that humans overcome these limitations through satisficing, fast but "good-enough" heuristic decision making that prioritizes some sources of information (cues) while ignoring others. However, the decision-making strategies we adopt under uncertainty and time pressure, for example during emergencies that demand split-second choices, are presently unknown. To characterize these decision strategies quantitatively, the present study examined how people solve a novel multicue probabilistic classification task under varying time pressure, by tracking shifts in decision strategies using variational Bayesian inference. We found that under low time pressure, participants correctly weighted and integrated all available cues to arrive at near-optimal decisions. With increasingly demanding, subsecond time pressures, however, participants systematically discounted a subset of the cue information by dropping the least informative cue(s) from their decision making process. Thus, the human cognitive apparatus copes with uncertainty and severe time pressure by adopting a "drop-the-worst" cue decision making strategy that minimizes cognitive time and effort investment while preserving the consideration of the most diagnostic cue information, thus maintaining "good-enough" accuracy. This advance in our understanding of satisficing strategies could form the basis of predicting human choices in high time pressure scenarios. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Decision analysis of shoreline protection under climate change uncertainty

NASA Astrophysics Data System (ADS)

Chao, Philip T.; Hobbs, Benjamin F.

1997-04-01

If global warming occurs, it could significantly affect water resource distribution and availability. Yet it is unclear whether the prospect of such change is relevant to water resources management decisions being made today. We model a shoreline protection decision problem with a stochastic dynamic program (SDP) to determine whether consideration of the possibility of climate change would alter the decision. Three questions are addressed with the SDP: (l) How important is climate change compared to other uncertainties?, (2) What is the economic loss if climate change uncertainty is ignored?, and (3) How does belief in climate change affect the timing of the decision? In the case study, sensitivity analysis shows that uncertainty in real discount rates has a stronger effect upon the decision than belief in climate change. Nevertheless, a strong belief in climate change makes the shoreline protection project less attractive and often alters the decision to build it.

"Utilizing" signal detection theory.

PubMed

Lynn, Spencer K; Barrett, Lisa Feldman

2014-09-01

What do inferring what a person is thinking or feeling, judging a defendant's guilt, and navigating a dimly lit room have in common? They involve perceptual uncertainty (e.g., a scowling face might indicate anger or concentration, for which different responses are appropriate) and behavioral risk (e.g., a cost to making the wrong response). Signal detection theory describes these types of decisions. In this tutorial, we show how incorporating the economic concept of utility allows signal detection theory to serve as a model of optimal decision making, going beyond its common use as an analytic method. This utility approach to signal detection theory clarifies otherwise enigmatic influences of perceptual uncertainty on measures of decision-making performance (accuracy and optimality) and on behavior (an inverse relationship between bias magnitude and sensitivity optimizes utility). A "utilized" signal detection theory offers the possibility of expanding the phenomena that can be understood within a decision-making framework. © The Author(s) 2014.

“UTILIZING” SIGNAL DETECTION THEORY

PubMed Central

Lynn, Spencer K.; Barrett, Lisa Feldman

2014-01-01

What do inferring what a person is thinking or feeling, deciding to report a symptom to your doctor, judging a defendant’s guilt, and navigating a dimly lit room have in common? They involve perceptual uncertainty (e.g., a scowling face might indicate anger or concentration, which engender different appropriate responses), and behavioral risk (e.g., a cost to making the wrong response). Signal detection theory describes these types of decisions. In this tutorial we show how, by incorporating the economic concept of utility, signal detection theory serves as a model of optimal decision making, beyond its common use as an analytic method. This utility approach to signal detection theory highlights potentially enigmatic influences of perceptual uncertainty on measures of decision-making performance (accuracy and optimality) and on behavior (a functional relationship between bias and sensitivity). A “utilized” signal detection theory offers the possibility of expanding the phenomena that can be understood within a decision-making framework. PMID:25097061

Adapting to Uncertainty: Comparing Methodological Approaches to Climate Adaptation and Mitigation Policy

NASA Astrophysics Data System (ADS)

Huda, J.; Kauneckis, D. L.

2013-12-01

Climate change adaptation represents a number of unique policy-making challenges. Foremost among these is dealing with the range of future climate impacts to a wide scope of inter-related natural systems, their interaction with social and economic systems, and uncertainty resulting from the variety of downscaled climate model scenarios and climate science projections. These cascades of uncertainty have led to a number of new approaches as well as a reexamination of traditional methods for evaluating risk and uncertainty in policy-making. Policy makers are required to make decisions and formulate policy irrespective of the level of uncertainty involved and while a debate continues regarding the level of scientific certainty required in order to make a decision, incremental change in the climate policy continues at multiple governance levels. This project conducts a comparative analysis of the range of methodological approaches that are evolving to address uncertainty in climate change policy. It defines 'methodologies' to include a variety of quantitative and qualitative approaches involving both top-down and bottom-up policy processes that attempt to enable policymakers to synthesize climate information into the policy process. The analysis examines methodological approaches to decision-making in climate policy based on criteria such as sources of policy choice information, sectors to which the methodology has been applied, sources from which climate projections were derived, quantitative and qualitative methods used to deal with uncertainty, and the benefits and limitations of each. A typology is developed to better categorize the variety of approaches and methods, examine the scope of policy activities they are best suited for, and highlight areas for future research and development.

"World of Uncertainty" Game for Decision-Makers

ERIC Educational Resources Information Center

Kyzy, Jyldyz Tabyldy

2011-01-01

Decisions on both personal and public matters benefit significantly if uncertainties and risks are handled with more care and accuracy. It is crucial to refine and express degrees of confidence and subjective probabilities of various outcomes. Experience, intuition, and skills help make the most of uncertain information. This paper proposes a…

Cognitive Processes in Decisions Under Risk are not the Same as in Decisions Under Uncertainty

PubMed Central

Volz, Kirsten G.; Gigerenzer, Gerd

2012-01-01

We deal with risk versus uncertainty, a distinction that is of fundamental importance for cognitive neuroscience yet largely neglected. In a world of risk (“small world”), all alternatives, consequences, and probabilities are known. In uncertain (“large”) worlds, some of this information is unknown or unknowable. Most of cognitive neuroscience studies exclusively study the neural correlates for decisions under risk (e.g., lotteries), with the tacit implication that understanding these would lead to an understanding of decision making in general. First, we show that normative strategies for decisions under risk do not generalize to uncertain worlds, where simple heuristics are often the more accurate strategies. Second, we argue that the cognitive processes for making decisions in a world of risk are not the same as those for dealing with uncertainty. Because situations with known risks are the exception rather than the rule in human evolution, it is unlikely that our brains are adapted to them. We therefore suggest a paradigm shift toward studying decision processes in uncertain worlds and provide first examples. PMID:22807893

Influence of uncertainty on framed decision-making with moral dilemma

PubMed Central

Mermillod, Martial; Le Pennec, Jean-Luc; Dutheil, Frédéric; Mondillon, Laurie

2018-01-01

In cases of impending natural disasters, most events are uncertain and emotionally relevant, both critical factors for decision-making. Moreover, for exposed individuals, the sensitivity to the framing of the consequences (gain or loss) and the moral judgments they have to perform (e.g., evacuate or help an injured person) constitute two central effects that have never been examined in the same context of decision-making. In a framed decision-making task with moral dilemma, we investigated whether uncertainty (i.e., unpredictably of events) and a threatening context would influence the framing effect (actions framed in loss are avoided in comparison to the ones framed in gain) and the personal intention effect (unintentional actions are more morally acceptable in comparison to intentional actions) on the perceived moral acceptability of taking action. Considering the impact of uncertainty and fear on the processes underlying these effects, we assumed that these emotions would lead to the negation of the two effects. Our results indicate that the exposure to uncertain events leads to the negation of the framing effect, but does not influence the moral acceptability and the effect of personal intention. We discuss our results in the light of dual-process models (i.e. systematic vs. heuristic), appraisal theories, and neurocognitive aspects. These elements highlight the importance of providing solutions to cope with uncertainty, both for scientists and local populations exposed to natural hazards. PMID:29847589

Influence of uncertainty on framed decision-making with moral dilemma.

PubMed

Merlhiot, Gaëtan; Mermillod, Martial; Le Pennec, Jean-Luc; Dutheil, Frédéric; Mondillon, Laurie

2018-01-01

In cases of impending natural disasters, most events are uncertain and emotionally relevant, both critical factors for decision-making. Moreover, for exposed individuals, the sensitivity to the framing of the consequences (gain or loss) and the moral judgments they have to perform (e.g., evacuate or help an injured person) constitute two central effects that have never been examined in the same context of decision-making. In a framed decision-making task with moral dilemma, we investigated whether uncertainty (i.e., unpredictably of events) and a threatening context would influence the framing effect (actions framed in loss are avoided in comparison to the ones framed in gain) and the personal intention effect (unintentional actions are more morally acceptable in comparison to intentional actions) on the perceived moral acceptability of taking action. Considering the impact of uncertainty and fear on the processes underlying these effects, we assumed that these emotions would lead to the negation of the two effects. Our results indicate that the exposure to uncertain events leads to the negation of the framing effect, but does not influence the moral acceptability and the effect of personal intention. We discuss our results in the light of dual-process models (i.e. systematic vs. heuristic), appraisal theories, and neurocognitive aspects. These elements highlight the importance of providing solutions to cope with uncertainty, both for scientists and local populations exposed to natural hazards.

A qualitative study of nulliparous women's decision making on mode of delivery under China's two-child policy.

PubMed

Gu, Chunyi; Zhu, Xinli; Ding, Yan; Setterberg Simone; Wang, Xiaojiao; Tao, Hua; Zhang, Yu

2018-07-01

To explore nulliparous women's perceptions of decision making regarding mode of delivery under China's two-child policy. Qualitative descriptive design with in-depth semi-structured interviews. Postnatal wards at a tertiary specialized women's hospital in Shanghai, China. 21 nulliparous women 2-3 days postpartum were purposively sampled until data saturation. In-depth semi-structured interviews were conducted between October 8th, 2015 and January 31st, 2016. Two overarching descriptive categories were identified: (1) women's decision-making process: stability versus variability, and (2) factors affecting decision making: variety versus interactivity. Four key themes emerged from each category: (1) initial decision making with certainty: anticipated trial of labour, failed trial of labour, 'shy away' and compromise, anticipated caesarean delivery; (2) initial decision making with uncertainty: anticipated trial of labour, failed trial of labour, 'shy away' and compromise; (3) internal factors affecting decision making: knowledge and attitude, and childbirth self-efficacy; and (4) external factors affecting decision making: social support, and the situational environment. At the initial period of China's two-child policy, nulliparous women have perceived their decision-making process regarding mode of delivery as one with complexity and uncertainty, influenced by both internal and external factors. This may have implications for the obstetric setting to develop a well-designed decision support system for pregnant women during the entire pregnancy periods. And it is recommended that care providers should assess women's preferences for mode of delivery from early pregnancy and provide adequate perinatal support and continuity of care for them. Copyright © 2018 Elsevier Ltd. All rights reserved.

Health technology assessment and primary data collection for reducing uncertainty in decision making.

PubMed

Goeree, Ron; Levin, Les; Chandra, Kiran; Bowen, James M; Blackhouse, Gord; Tarride, Jean-Eric; Burke, Natasha; Bischof, Matthias; Xie, Feng; O'Reilly, Daria

2009-05-01

Health care expenditures continue to escalate, and pressures for increased spending will continue. Health care decision makers from publicly financed systems, private insurance companies, or even from individual health care institutions, will continue to be faced with making difficult purchasing, access, and reimbursement decisions. As a result, decision makers are increasingly turning to evidence-based platforms to help control costs and make the most efficient use of existing resources. Most tools used to assist with evidence-based decision making focus on clinical outcomes. Health technology assessment (HTA) is increasing in popularity because it also considers other factors important for decision making, such as cost, social and ethical values, legal issues, and factors such as the feasibility of implementation. In some jurisdictions, HTAs have also been supplemented with primary data collection to help address uncertainty that may still exist after conducting a traditional HTA. The HTA process adopted in Ontario, Canada, is unique in that assessments are also made to determine what primary data research should be conducted and what should be collected in these studies. In this article, concerns with the traditional HTA process are discussed, followed by a description of the HTA process that has been established in Ontario, with a particular focus on the data collection program followed by the Programs for Assessment of Technology in Health Research Institute. An illustrative example is used to show how the Ontario HTA process works and the role value of information analyses plays in addressing decision uncertainty, determining research feasibility, and determining study data collection needs.

The application of the heuristic-systematic processing model to treatment decision making about prostate cancer.

PubMed

Steginga, Suzanne K; Occhipinti, Stefano

2004-01-01

The study investigated the utility of the Heuristic-Systematic Processing Model as a framework for the investigation of patient decision making. A total of 111 men recently diagnosed with localized prostate cancer were assessed using Verbal Protocol Analysis and self-report measures. Study variables included men's use of nonsystematic and systematic information processing, desire for involvement in decision making, and the individual differences of health locus of control, tolerance of ambiguity, and decision-related uncertainty. Most men (68%) preferred that decision making be shared equally between them and their doctor. Men's use of the expert opinion heuristic was related to men's verbal reports of decisional uncertainty and having a positive orientation to their doctor and medical care; a desire for greater involvement in decision making was predicted by a high internal locus of health control. Trends were observed for systematic information processing to increase when the heuristic strategy used was negatively affect laden and when men were uncertain about the probabilities for cure and side effects. There was a trend for decreased systematic processing when the expert opinion heuristic was used. Findings were consistent with the Heuristic-Systematic Processing Model and suggest that this model has utility for future research in applied decision making about health.

Using real options analysis to support strategic management decisions

NASA Astrophysics Data System (ADS)

Kabaivanov, Stanimir; Markovska, Veneta; Milev, Mariyan

2013-12-01

Decision making is a complex process that requires taking into consideration multiple heterogeneous sources of uncertainty. Standard valuation and financial analysis techniques often fail to properly account for all these sources of risk as well as for all sources of additional flexibility. In this paper we explore applications of a modified binomial tree method for real options analysis (ROA) in an effort to improve decision making process. Usual cases of use of real options are analyzed with elaborate study on the applications and advantages that company management can derive from their application. A numeric results based on extending simple binomial tree approach for multiple sources of uncertainty are provided to demonstrate the improvement effects on management decisions.

Bayesian-information-gap decision theory with an application to CO 2 sequestration

DOE PAGES

O'Malley, D.; Vesselinov, V. V.

2015-09-04

Decisions related to subsurface engineering problems such as groundwater management, fossil fuel production, and geologic carbon sequestration are frequently challenging because of an overabundance of uncertainties (related to conceptualizations, parameters, observations, etc.). Because of the importance of these problems to agriculture, energy, and the climate (respectively), good decisions that are scientifically defensible must be made despite the uncertainties. We describe a general approach to making decisions for challenging problems such as these in the presence of severe uncertainties that combines probabilistic and non-probabilistic methods. The approach uses Bayesian sampling to assess parametric uncertainty and Information-Gap Decision Theory (IGDT) to addressmore » model inadequacy. The combined approach also resolves an issue that frequently arises when applying Bayesian methods to real-world engineering problems related to the enumeration of possible outcomes. In the case of zero non-probabilistic uncertainty, the method reduces to a Bayesian method. Lastly, to illustrate the approach, we apply it to a site-selection decision for geologic CO 2 sequestration.« less

Parent Preferences for Shared Decision-making in Acute Versus Chronic Illness.

PubMed

Tom, Dina M; Aquino, Christian; Arredondo, Anthony R; Foster, Byron A

2017-10-01

The goal of this study was to examine preferences for shared decision-making (SDM) in parents of acutely ill versus chronically ill children in the inpatient setting. Additionally, we explored the effect of parental perception of illness severity and uncertainty in illness on decision-making preference. In this cross-sectional study, we surveyed parents of children admitted to pediatric inpatient units at an academic, tertiary-care hospital. Surveys were administered in person and used validated tools to assess SDM preferences and uncertainty in illness. Descriptive statistics evaluated associations stratified by acute versus chronic illness, and multivariable analyses were performed. Of the 200 parents who participated, the majority were women (78%), Hispanic (81.5%), English speaking (73%), between 30 and 39 years old (37.5%), and had an education achievement of less than a college degree (77%). The mean age of hospitalized children was 8.1 years, and half reported a chronic illness. Most parents preferred an active (43%) or collaborative (40%) role in SDM. There was no association with SDM preference by demographics, number of previous hospitalizations, perception of illness severity, or uncertainty. However, parents of chronically ill children significantly preferred a passive role in SDM when they perceived a high level of uncertainty in illness. Most parents of hospitalized children prefer to take an active or collaborative role in SDM. However, parents of chronically ill children who perceive high levels of uncertainty surrounding their children's illness prefer a passive role, thus illustrating the complexity in decision-making among this parent population. Copyright © 2017 by the American Academy of Pediatrics.

A strategy for monitoring and managing declines in an amphibian community.

PubMed

Grant, Evan H Campbell; Zipkin, Elise F; Nichols, James D; Campbell, J Patrick

2013-12-01

Although many taxa have declined globally, conservation actions are inherently local. Ecosystems degrade even in protected areas, and maintaining natural systems in a desired condition may require active management. Implementing management decisions under uncertainty requires a logical and transparent process to identify objectives, develop management actions, formulate system models to link actions with objectives, monitor to reduce uncertainty and identify system state (i.e., resource condition), and determine an optimal management strategy. We applied one such structured decision-making approach that incorporates these critical elements to inform management of amphibian populations in a protected area managed by the U.S. National Park Service. Climate change is expected to affect amphibian occupancy of wetlands and to increase uncertainty in management decision making. We used the tools of structured decision making to identify short-term management solutions that incorporate our current understanding of the effect of climate change on amphibians, emphasizing how management can be undertaken even with incomplete information. Estrategia para Monitorear y Manejar Disminuciones en una Comunidad de Anfibios. © 2013 Society for Conservation Biology.

Neural Correlates of Sequence Learning with Stochastic Feedback

ERIC Educational Resources Information Center

Averbeck, Bruno B.; Kilner, James; Frith, Christopher D.

2011-01-01

Although much is known about decision making under uncertainty when only a single step is required in the decision process, less is known about sequential decision making. We carried out a stochastic sequence learning task in which subjects had to use noisy feedback to learn sequences of button presses. We compared flat and hierarchical behavioral…

Assessment of Competence in Clinical Reasoning and Decision-Making under Uncertainty: The Script Concordance Test Method

ERIC Educational Resources Information Center

Ramaekers, Stephan; Kremer, Wim; Pilot, Albert; van Beukelen, Peter; van Keulen, Hanno

2010-01-01

Real-life, complex problems often require that decisions are made despite limited information or insufficient time to explore all relevant aspects. Incorporating authentic uncertainties into an assessment, however, poses problems in establishing results and analysing their methodological qualities. This study aims at developing a test on clinical…

Making framing of uncertainty in water management practice explicit by using a participant-structured approach.

PubMed

Isendahl, Nicola; Dewulf, Art; Pahl-Wostl, Claudia

2010-01-01

By now, the need for addressing uncertainty in the management of water resources is widely recognized, yet there is little expertise and experience how to effectively deal with uncertainty in practice. Uncertainties in water management practice so far are mostly dealt with intuitively or based on experience. That way decisions can be quickly taken but analytic processes of deliberate reasoning are bypassed. To meet the desire of practitioners for better guidance and tools how to deal with uncertainty more practice-oriented systematic approaches are needed. For that purpose we consider it important to understand how practitioners frame uncertainties. In this paper we present an approach where water managers developed criteria of relevance to understand and address uncertainties. The empirical research took place in the Doñana region of the Guadalquivir estuary in southern Spain making use of the method of card sorting. Through the card sorting exercise a broad range of criteria to make sense of and describe uncertainties was produced by different subgroups, which were then merged into a shared list of criteria. That way framing differences were made explicit and communication on uncertainty and on framing differences was enhanced. In that, the present approach constitutes a first step to enabling reframing and overcoming framing differences, which are important features on the way to robust decision-making. Moreover, the elaborated criteria build a basis for the development of more structured approaches to deal with uncertainties in water management practice. Copyright 2009 Elsevier Ltd. All rights reserved.

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.

Achieving Robustness to Uncertainty for Financial Decision-making

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

Barnum, George M.; Van Buren, Kendra L.; Hemez, Francois M.

2014-01-10

This report investigates the concept of robustness analysis to support financial decision-making. Financial models, that forecast future stock returns or market conditions, depend on assumptions that might be unwarranted and variables that might exhibit large fluctuations from their last-known values. The analysis of robustness explores these sources of uncertainty, and recommends model settings such that the forecasts used for decision-making are as insensitive as possible to the uncertainty. A proof-of-concept is presented with the Capital Asset Pricing Model. The robustness of model predictions is assessed using info-gap decision theory. Info-gaps are models of uncertainty that express the “distance,” or gapmore » of information, between what is known and what needs to be known in order to support the decision. The analysis yields a description of worst-case stock returns as a function of increasing gaps in our knowledge. The analyst can then decide on the best course of action by trading-off worst-case performance with “risk”, which is how much uncertainty they think needs to be accommodated in the future. The report also discusses the Graphical User Interface, developed using the MATLAB® programming environment, such that the user can control the analysis through an easy-to-navigate interface. Three directions of future work are identified to enhance the present software. First, the code should be re-written using the Python scientific programming software. This change will achieve greater cross-platform compatibility, better portability, allow for a more professional appearance, and render it independent from a commercial license, which MATLAB® requires. Second, a capability should be developed to allow users to quickly implement and analyze their own models. This will facilitate application of the software to the evaluation of proprietary financial models. The third enhancement proposed is to add the ability to evaluate multiple models simultaneously. When two models reflect past data with similar accuracy, the more robust of the two is preferable for decision-making because its predictions are, by definition, less sensitive to the uncertainty.« less

Categorization = Decision Making + Generalization

PubMed Central

Seger, Carol A; Peterson, Erik J.

2013-01-01

We rarely, if ever, repeatedly encounter exactly the same situation. This makes generalization crucial for real world decision making. We argue that categorization, the study of generalizable representations, is a type of decision making, and that categorization learning research would benefit from approaches developed to study the neuroscience of decision making. Similarly, methods developed to examine generalization and learning within the field of categorization may enhance decision making research. We first discuss perceptual information processing and integration, with an emphasis on accumulator models. We then examine learning the value of different decision making choices via experience, emphasizing reinforcement learning modeling approaches. Next we discuss how value is combined with other factors in decision making, emphasizing the effects of uncertainty. Finally, we describe how a final decision is selected via thresholding processes implemented by the basal ganglia and related regions. We also consider how memory related functions in the hippocampus may be integrated with decision making mechanisms and contribute to categorization. PMID:23548891

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

The neural systems for perceptual updating.

PubMed

Stöttinger, Elisabeth; Aichhorn, Markus; Anderson, Britt; Danckert, James

2018-04-01

In a constantly changing environment we must adapt to both abrupt and gradual changes to incoming information. Previously, we demonstrated that a distributed network (including the anterior insula and anterior cingulate cortex) was active when participants updated their initial representations (e.g., it's a cat) in a gradually morphing picture task (e.g., now it's a rabbit; Stöttinger et al., 2015). To shed light on whether these activations reflect the proactive decisions to update or perceptual uncertainty, we introduced two additional conditions. By presenting picture morphs twice we controlled for uncertainty in perceptual decision making. Inducing an abrupt shift in a third condition allowed us to differentiate between a proactive decision in uncertainty-driven updating and a reactive decision in surprise-based updating. We replicated our earlier result, showing the robustness of the effect. In addition, we found activation in the anterior insula (bilaterally) and the mid frontal area/ACC in all three conditions, indicative of the importance of these areas in updating of all kinds. When participants were naïve as to the identity of the second object, we found higher activations in the mid-cingulate cortex and cuneus - areas typically associated with task difficulty, in addition to higher activations in the right TPJ most likely reflecting the shift to a new perspective. Activations associated with the proactive decision to update to a new interpretation were found in a network including the dorsal ACC known to be involved in exploration and the endogenous decision to switch to a new interpretation. These findings suggest a general network commonly engaged in all types of perceptual decision making supported by additional networks associated with perceptual uncertainty or updating provoked by either proactive or reactive decision making. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

An uncertainty analysis of wildfire modeling [Chapter 13

Treesearch

Karin Riley; Matthew Thompson

2017-01-01

Before fire models can be understood, evaluated, and effectively applied to support decision making, model-based uncertainties must be analyzed. In this chapter, we identify and classify sources of uncertainty using an established analytical framework, and summarize results graphically in an uncertainty matrix. Our analysis facilitates characterization of the...

Cue acquisition: A feature of Malawian midwives decision making process to support normality during the first stage of labour.

PubMed

Chodzaza, Elizabeth; Haycock-Stuart, Elaine; Holloway, Aisha; Mander, Rosemary

2018-03-01

to explore Malawian midwives decision making when caring for women during the first stage of labour in the hospital setting. this focused ethnographic study examined the decision making process of 9 nurse-midwives with varying years of clinical experience in the real world setting of an urban and semi urban hospital from October 2013 to May 2014.This was done using 27 participant observations and 27 post-observation in-depth interviews over a period of six months. Qualitative data analysis software, NVivo 10, was used to assist with data management for the analysis. All data was analysed using the principle of theme and category formation. analysis revealed a six-stage process of decision making that include a baseline for labour, deciding to admit a woman to labour ward, ascertaining the normal physiological progress of labour, supporting the normal physiological progress of labour, embracing uncertainty: the midwives' construction of unusual labour as normal, dealing with uncertainty and deciding to intervene in unusual labour. This six-stage process of decision making is conceptualised as the 'role of cue acquisition', illustrating the ways in which midwives utilise their assessment of labouring women to reason and make decisions on how to care for them in labour. Cue acquisition involved the midwives piecing together segments of information they obtained from the women to formulate an understanding of the woman's birthing progress and inform the midwives decision making process. This understanding of cue acquisition by midwives is significant for supporting safe care in the labour setting. When there was uncertainty in a woman's progress of labour, midwives used deductive reasoning, for example, by cross-checking and analysing the information obtained during the span of labour. Supporting normal labour physiological processes was identified as an underlying principle that shaped the midwives clinical judgement and decision making when they cared for women in labour. the significance of this study is in the new understanding and insight into the process of midwifery decision making. Whilst the approach to decision making by the midwives requires further testing and refinement in order to explore implications for practice, the findings here provide new conceptual and practical clarity of midwifery decision making. The work contributes to the identified lack of knowledge of how midwives working clinically, in the 'real world setting. These findings therefore, contribute to this body of knowledge with regards to our understanding of decision making of midwives. Copyright © 2017 Elsevier Ltd. All rights reserved.

Multi-criteria decision making in flood risk management: research progress and the challenge of handling uncertainty and stakeholder participation

NASA Astrophysics Data System (ADS)

Madruga de Brito, Mariana; Evers, Mariele

2016-04-01

Multi-Criteria Decision Making (MCDM) methods have received much attention from researchers and practitioners for solving flood risk management problems in the last decades due to its capacity to deal with multiple criteria, conflicting objectives as well as the knowledge arising from the participation of several actors. In order to consolidate recent research conducted in this area, this study presents a state-of-the-art literature review of MCDM applications to flood risk management, seeking to provide a better understanding of the current status of how participatory MCDM is being conducted and the way uncertainties are included in the decision-making process. Totally, 128 peer-reviewed papers published from 1995 to June 2015 in 72 different journals were systematically analyzed. Results indicated that the number of flood MCDM publications has exponentially grown during this period, with over 82% of all papers published since 2009. A wide range of application areas was identified, with most papers focusing on ranking alternatives for flood mitigation (22.78% of the total) followed by risk (21.11%) and vulnerability assessment (15%). The Analytical Hierarchy Process (AHP) was the most popular MCDM method (42.72%) followed by Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) (13.33%) and Weighted Sum Method (WSM) (12.73%). Although significant improvements have been made over the last decades, shortcomings remain in handling the uncertainty. Only eight papers (6.25%) have conducted uncertainty analysis, suggesting that a general procedure for performing it in MCDM does not yet exist. Researchers have applied the Monte Carlo simulation, Taylor's series error propagation method or assessed the uncertainty in qualitative ways, by describing its main sources or analyzing the stakeholders' degree of confidence. In addition, 35 articles (27.34%) have performed a sensitivity analysis of the criteria weights. Three distinct approaches were identified: one-way, global, and probabilistic sensitivity analysis. About half of the studies have acknowledged the involvement of multiple stakeholders. However, participation was fragmented and focused on particular stages of the decision-making process such as the elicitation of criteria weights. This segmentation may be related to methodological and time constraints since participatory decision making is time-consuming and costly. Policy makers and experts were the most participated stakeholders, with few papers considering the involvement of local community members. Another issue is that only four studies seek to obtain consensus and that decisions were often made by majority vote or averaging approaches. Therefore, greater rigor in addressing the uncertainties around stakeholders' judgments as well as in endorsing an active participation in all stages of the decision-making process should be undertaken in future applications. This could help to increase the quality of decisions and subsequent implementation of chosen measures.

Sleep deprivation alters choice strategy without altering uncertainty or loss aversion preferences

PubMed Central

Mullette-Gillman, O'Dhaniel A.; Kurnianingsih, Yoanna A.; Liu, Jean C. J.

2015-01-01

Sleep deprivation alters decision making; however, it is unclear what specific cognitive processes are modified to drive altered choices. In this manuscript, we examined how one night of total sleep deprivation (TSD) alters economic decision making. We specifically examined changes in uncertainty preferences dissociably from changes in the strategy with which participants engage with presented choice information. With high test-retest reliability, we show that TSD does not alter uncertainty preferences or loss aversion. Rather, TSD alters the information the participants rely upon to make their choices. Utilizing a choice strategy metric which contrasts the influence of maximizing and satisficing information on choice behavior, we find that TSD alters the relative reliance on maximizing information and satisficing information, in the gains domain. This alteration is the result of participants both decreasing their reliance on cognitively-complex maximizing information and a concomitant increase in the use of readily-available satisficing information. TSD did not result in a decrease in overall information use in either domain. These results show that sleep deprivation alters decision making by altering the informational strategies that participants employ, without altering their preferences. PMID:26500479

Recognizing and responding to uncertainty: a grounded theory of nurses' uncertainty.

PubMed

Cranley, Lisa A; Doran, Diane M; Tourangeau, Ann E; Kushniruk, Andre; Nagle, Lynn

2012-08-01

There has been little research to date exploring nurses' uncertainty in their practice. Understanding nurses' uncertainty is important because it has potential implications for how care is delivered. The purpose of this study is to develop a substantive theory to explain how staff nurses experience and respond to uncertainty in their practice. Between 2006 and 2008, a grounded theory study was conducted that included in-depth semi-structured interviews. Fourteen staff nurses working in adult medical-surgical intensive care units at two teaching hospitals in Ontario, Canada, participated in the study. The theory recognizing and responding to uncertainty characterizes the processes through which nurses' uncertainty manifested and how it was managed. Recognizing uncertainty involved the processes of assessing, reflecting, questioning, and/or being unable to predict aspects of the patient situation. Nurses' responses to uncertainty highlighted the cognitive-affective strategies used to manage uncertainty. Study findings highlight the importance of acknowledging uncertainty and having collegial support to manage uncertainty. The theory adds to our understanding the processes involved in recognizing uncertainty, strategies and outcomes of managing uncertainty, and influencing factors. Tailored nursing education programs should be developed to assist nurses in developing skills in articulating and managing their uncertainty. Further research is needed to extend, test and refine the theory of recognizing and responding to uncertainty to develop strategies for managing uncertainty. This theory advances the nursing perspective of uncertainty in clinical practice. The theory is relevant to nurses who are faced with uncertainty and complex clinical decisions, to managers who support nurses in their clinical decision-making, and to researchers who investigate ways to improve decision-making and care delivery. ©2012 Sigma Theta Tau International.

Incorporating uncertainty of management costs in sensitivity analyses of matrix population models.

PubMed

Salomon, Yacov; McCarthy, Michael A; Taylor, Peter; Wintle, Brendan A

2013-02-01

The importance of accounting for economic costs when making environmental-management decisions subject to resource constraints has been increasingly recognized in recent years. In contrast, uncertainty associated with such costs has often been ignored. We developed a method, on the basis of economic theory, that accounts for the uncertainty in population-management decisions. We considered the case where, rather than taking fixed values, model parameters are random variables that represent the situation when parameters are not precisely known. Hence, the outcome is not precisely known either. Instead of maximizing the expected outcome, we maximized the probability of obtaining an outcome above a threshold of acceptability. We derived explicit analytical expressions for the optimal allocation and its associated probability, as a function of the threshold of acceptability, where the model parameters were distributed according to normal and uniform distributions. To illustrate our approach we revisited a previous study that incorporated cost-efficiency analyses in management decisions that were based on perturbation analyses of matrix population models. Incorporating derivations from this study into our framework, we extended the model to address potential uncertainties. We then applied these results to 2 case studies: management of a Koala (Phascolarctos cinereus) population and conservation of an olive ridley sea turtle (Lepidochelys olivacea) population. For low aspirations, that is, when the threshold of acceptability is relatively low, the optimal strategy was obtained by diversifying the allocation of funds. Conversely, for high aspirations, the budget was directed toward management actions with the highest potential effect on the population. The exact optimal allocation was sensitive to the choice of uncertainty model. Our results highlight the importance of accounting for uncertainty when making decisions and suggest that more effort should be placed on understanding the distributional characteristics of such uncertainty. Our approach provides a tool to improve decision making. © 2013 Society for Conservation Biology.

Role of affect in decision making.

PubMed

Bandyopadhyay, Debarati; Pammi, V S Chandrasekhar; Srinivasan, Narayanan

2013-01-01

Emotion plays a major role in influencing our everyday cognitive and behavioral functions, including decision making. We introduce different ways in which emotions are characterized in terms of the way they influence or elicited by decision making. This chapter discusses different theories that have been proposed to explain the role of emotions in judgment and decision making. We also discuss incidental emotional influences, both long-duration influences like mood and short-duration influences by emotional context present prior to or during decision making. We present and discuss results from a study with emotional pictures presented prior to decision making and how that influences both decision processes and postdecision experience as a function of uncertainty. We conclude with a summary of the work on emotions and decision making in the context of decision-making theories and our work on incidental emotions. Copyright © 2013 Elsevier B.V. All rights reserved.

Surgeons' Silence: A History of Informed Consent in Orthopaedics

PubMed Central

Jones, Kevin B

2007-01-01

The moment of decision to proceed with surgical intervention is charged with some of the deepest uncertainties in medicine, but has long been cloaked under the confidence asserted by the traditionally custodial surgeon. This paper reviews the history and ethical basis for informed surgical consent. Beginning with theoretical foundations and the changing ethics of medical decision making since the ancient Greeks, it then reviews how the stage was set for informed consent by technological breakthroughs that made surgical interventions tolerable and acceptably safe. Finally, the legal generation of the doctrine of informed consent is reviewed and the current state of disclosure, shared decision-making, and uncertainty explored. PMID:17907443

Exploiting risk-reward structures in decision making under uncertainty.

PubMed

Leuker, Christina; Pachur, Thorsten; Hertwig, Ralph; Pleskac, Timothy J

2018-06-01

People often have to make decisions under uncertainty-that is, in situations where the probabilities of obtaining a payoff are unknown or at least difficult to ascertain. One solution to this problem is to infer the probability from the magnitude of the potential payoff and thus exploit the inverse relationship between payoffs and probabilities that occurs in many domains in the environment. Here, we investigated how the mind may implement such a solution: (1) Do people learn about risk-reward relationships from the environment-and if so, how? (2) How do learned risk-reward relationships impact preferences in decision-making under uncertainty? Across three experiments (N = 352), we found that participants can learn risk-reward relationships from being exposed to choice environments with a negative, positive, or uncorrelated risk-reward relationship. They were able to learn the associations both from gambles with explicitly stated payoffs and probabilities (Experiments 1 & 2) and from gambles about epistemic events (Experiment 3). In subsequent decisions under uncertainty, participants often exploited the learned association by inferring probabilities from the magnitudes of the payoffs. This inference systematically influenced their preferences under uncertainty: Participants who had been exposed to a negative risk-reward relationship tended to prefer the uncertain option over a smaller sure option for low payoffs, but not for high payoffs. This pattern reversed in the positive condition and disappeared in the uncorrelated condition. This adaptive change in preferences is consistent with the use of the risk-reward heuristic. Copyright © 2018 Elsevier B.V. All rights reserved.

Believer-Skeptic Meets Actor-Critic: Rethinking the Role of Basal Ganglia Pathways during Decision-Making and Reinforcement Learning

PubMed Central

Dunovan, Kyle; Verstynen, Timothy

2016-01-01

The flexibility of behavioral control is a testament to the brain's capacity for dynamically resolving uncertainty during goal-directed actions. This ability to select actions and learn from immediate feedback is driven by the dynamics of basal ganglia (BG) pathways. A growing body of empirical evidence conflicts with the traditional view that these pathways act as independent levers for facilitating (i.e., direct pathway) or suppressing (i.e., indirect pathway) motor output, suggesting instead that they engage in a dynamic competition during action decisions that computationally captures action uncertainty. Here we discuss the utility of encoding action uncertainty as a dynamic competition between opposing control pathways and provide evidence that this simple mechanism may have powerful implications for bridging neurocomputational theories of decision making and reinforcement learning. PMID:27047328

Believer-Skeptic Meets Actor-Critic: Rethinking the Role of Basal Ganglia Pathways during Decision-Making and Reinforcement Learning.

PubMed

Dunovan, Kyle; Verstynen, Timothy

2016-01-01

The flexibility of behavioral control is a testament to the brain's capacity for dynamically resolving uncertainty during goal-directed actions. This ability to select actions and learn from immediate feedback is driven by the dynamics of basal ganglia (BG) pathways. A growing body of empirical evidence conflicts with the traditional view that these pathways act as independent levers for facilitating (i.e., direct pathway) or suppressing (i.e., indirect pathway) motor output, suggesting instead that they engage in a dynamic competition during action decisions that computationally captures action uncertainty. Here we discuss the utility of encoding action uncertainty as a dynamic competition between opposing control pathways and provide evidence that this simple mechanism may have powerful implications for bridging neurocomputational theories of decision making and reinforcement learning.

Selection of climate policies under the uncertainties in the Fifth Assessment Report of the IPCC

NASA Astrophysics Data System (ADS)

Drouet, L.; Bosetti, V.; Tavoni, M.

2015-10-01

Strategies for dealing with climate change must incorporate and quantify all the relevant uncertainties, and be designed to manage the resulting risks. Here we employ the best available knowledge so far, summarized by the three working groups of the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR5; refs , , ), to quantify the uncertainty of mitigation costs, climate change dynamics, and economic damage for alternative carbon budgets. We rank climate policies according to different decision-making criteria concerning uncertainty, risk aversion and intertemporal preferences. Our findings show that preferences over uncertainties are as important as the choice of the widely discussed time discount factor. Climate policies consistent with limiting warming to 2 °C above preindustrial levels are compatible with a subset of decision-making criteria and some model parametrizations, but not with the commonly adopted expected utility framework.

Predictive Uncertainty And Parameter Sensitivity Of A Sediment-Flux Model: Nitrogen Flux and Sediment Oxygen Demand

EPA Science Inventory

Estimating model predictive uncertainty is imperative to informed environmental decision making and management of water resources. This paper applies the Generalized Sensitivity Analysis (GSA) to examine parameter sensitivity and the Generalized Likelihood Uncertainty Estimation...

An experiment with interactive planning models

NASA Technical Reports Server (NTRS)

Beville, J.; Wagner, J. H.; Zannetos, Z. S.

1970-01-01

Experiments on decision making in planning problems are described. Executives were tested in dealing with capital investments and competitive pricing decisions under conditions of uncertainty. A software package, the interactive risk analysis model system, was developed, and two controlled experiments were conducted. It is concluded that planning models can aid management, and predicted uses of the models are as a central tool, as an educational tool, to improve consistency in decision making, to improve communications, and as a tool for consensus decision making.

Uncertainty assessment of urban pluvial flood risk in a context of climate change adaptation decision making

NASA Astrophysics Data System (ADS)

Arnbjerg-Nielsen, Karsten; Zhou, Qianqian

2014-05-01

There has been a significant increase in climatic extremes in many regions. In Central and Northern Europe, this has led to more frequent and more severe floods. Along with improved flood modelling technologies this has enabled development of economic assessment of climate change adaptation to increasing urban flood risk. Assessment of adaptation strategies often requires a comprehensive risk-based economic analysis of current risk, drivers of change of risk over time, and measures to reduce the risk. However, such studies are often associated with large uncertainties. The uncertainties arise from basic assumptions in the economic analysis and the hydrological model, but also from the projection of future societies to local climate change impacts and suitable adaptation options. This presents a challenge to decision makers when trying to identify robust measures. We present an integrated uncertainty analysis, which can assess and quantify the overall uncertainty in relation to climate change adaptation to urban flash floods. The analysis is based on an uncertainty cascade that by means of Monte Carlo simulations of flood risk assessments incorporates climate change impacts as a key driver of risk changes over time. The overall uncertainty is then attributed to six bulk processes: climate change impact, urban rainfall-runoff processes, stage-depth functions, unit cost of repair, cost of adaptation measures, and discount rate. We apply the approach on an urban hydrological catchment in Odense, Denmark, and find that the uncertainty on the climate change impact appears to have the least influence on the net present value of the studied adaptation measures-. This does not imply that the climate change impact is not important, but that the uncertainties are not dominating when deciding on action or in-action. We then consider the uncertainty related to choosing between adaptation options given that a decision of action has been taken. In this case the major part of the uncertainty on the estimated net present values is identical for all adaptation options and will therefore not affect a comparison between adaptation measures. This makes the chose among the options easier. Furthermore, the explicit attribution of uncertainty also enables a reduction of the overall uncertainty by identifying the processes which contributes the most. This knowledge can then be used to further reduce the uncertainty related to decision making, as a substantial part of the remaining uncertainty is epistemic.

Understanding and applying principles of social cognition and decision making in adaptive environmental governance

EPA Science Inventory

Environmental governance systems are under greater pressure to adapt and to cope with increased social and ecological uncertainty from stressors like climate change. We review principles of social cognition and decision making that shape and constrain how environmental governance...

CEOs, Information, and Decision Making: Scanning the Environment for Strategic Advantage.

ERIC Educational Resources Information Center

Auster, Ethel; Choo, Chun Wei

1994-01-01

Describes a study that investigated how CEOs (Chief Executive Officers) in the Canadian publishing and telecommunications industries acquire and use information about the business environment. Topics discussed include environmental scanning; perceived environmental uncertainty; information sources; information use in decision making; and a…

Bridging groundwater models and decision support with a Bayesian network

USGS Publications Warehouse

Fienen, Michael N.; Masterson, John P.; Plant, Nathaniel G.; Gutierrez, Benjamin T.; Thieler, E. Robert

2013-01-01

Resource managers need to make decisions to plan for future environmental conditions, particularly sea level rise, in the face of substantial uncertainty. Many interacting processes factor in to the decisions they face. Advances in process models and the quantification of uncertainty have made models a valuable tool for this purpose. Long-simulation runtimes and, often, numerical instability make linking process models impractical in many cases. A method for emulating the important connections between model input and forecasts, while propagating uncertainty, has the potential to provide a bridge between complicated numerical process models and the efficiency and stability needed for decision making. We explore this using a Bayesian network (BN) to emulate a groundwater flow model. We expand on previous approaches to validating a BN by calculating forecasting skill using cross validation of a groundwater model of Assateague Island in Virginia and Maryland, USA. This BN emulation was shown to capture the important groundwater-flow characteristics and uncertainty of the groundwater system because of its connection to island morphology and sea level. Forecast power metrics associated with the validation of multiple alternative BN designs guided the selection of an optimal level of BN complexity. Assateague island is an ideal test case for exploring a forecasting tool based on current conditions because the unique hydrogeomorphological variability of the island includes a range of settings indicative of past, current, and future conditions. The resulting BN is a valuable tool for exploring the response of groundwater conditions to sea level rise in decision support.

A Discussion on Uncertainty Representation and Interpretation in Model-Based Prognostics Algorithms based on Kalman Filter Estimation Applied to Prognostics of Electronics Components

NASA Technical Reports Server (NTRS)

Celaya, Jose R.; Saxen, Abhinav; Goebel, Kai

2012-01-01

This article discusses several aspects of uncertainty representation and management for model-based prognostics methodologies based on our experience with Kalman Filters when applied to prognostics for electronics components. In particular, it explores the implications of modeling remaining useful life prediction as a stochastic process and how it relates to uncertainty representation, management, and the role of prognostics in decision-making. A distinction between the interpretations of estimated remaining useful life probability density function and the true remaining useful life probability density function is explained and a cautionary argument is provided against mixing interpretations for the two while considering prognostics in making critical decisions.

Communicating Uncertainty in Volcanic Ash Forecasts: Decision-Making and Information Preferences

NASA Astrophysics Data System (ADS)

Mulder, Kelsey; Black, Alison; Charlton-Perez, Andrew; McCloy, Rachel; Lickiss, Matthew

2016-04-01

The Robust Assessment and Communication of Environmental Risk (RACER) consortium, an interdisciplinary research team focusing on communication of uncertainty with respect to natural hazards, hosted a Volcanic Ash Workshop to discuss issues related to volcanic ash forecasting, especially forecast uncertainty. Part of the workshop was a decision game in which participants including forecasters, academics, and members of the Aviation Industry were given hypothetical volcanic ash concentration forecasts and asked whether they would approve a given flight path. The uncertainty information was presented in different formats including hazard maps, line graphs, and percent probabilities. Results from the decision game will be presented with a focus on information preferences, understanding of the forecasts, and whether different formats of the same volcanic ash forecast resulted in different flight decisions. Implications of this research will help the design and presentation of volcanic ash plume decision tools and can also help advise design of other natural hazard information.

Clarity versus complexity: land-use modeling as a practical tool for decision-makers

USGS Publications Warehouse

Sohl, Terry L.; Claggett, Peter

2013-01-01

The last decade has seen a remarkable increase in the number of modeling tools available to examine future land-use and land-cover (LULC) change. Integrated modeling frameworks, agent-based models, cellular automata approaches, and other modeling techniques have substantially improved the representation of complex LULC systems, with each method using a different strategy to address complexity. However, despite the development of new and better modeling tools, the use of these tools is limited for actual planning, decision-making, or policy-making purposes. LULC modelers have become very adept at creating tools for modeling LULC change, but complicated models and lack of transparency limit their utility for decision-makers. The complicated nature of many LULC models also makes it impractical or even impossible to perform a rigorous analysis of modeling uncertainty. This paper provides a review of land-cover modeling approaches and the issues causes by the complicated nature of models, and provides suggestions to facilitate the increased use of LULC models by decision-makers and other stakeholders. The utility of LULC models themselves can be improved by 1) providing model code and documentation, 2) through the use of scenario frameworks to frame overall uncertainties, 3) improving methods for generalizing key LULC processes most important to stakeholders, and 4) adopting more rigorous standards for validating models and quantifying uncertainty. Communication with decision-makers and other stakeholders can be improved by increasing stakeholder participation in all stages of the modeling process, increasing the transparency of model structure and uncertainties, and developing user-friendly decision-support systems to bridge the link between LULC science and policy. By considering these options, LULC science will be better positioned to support decision-makers and increase real-world application of LULC modeling results.

Do systematic reviews address community healthcare professionals' wound care uncertainties? Results from evidence mapping in wound care.

PubMed

Christie, Janice; Gray, Trish A; Dumville, Jo C; Cullum, Nicky A

2018-01-01

Complex wounds such as leg and foot ulcers are common, resource intensive and have negative impacts on patients' wellbeing. Evidence-based decision-making, substantiated by high quality evidence such as from systematic reviews, is widely advocated for improving patient care and healthcare efficiency. Consequently, we set out to classify and map the extent to which up-to-date systematic reviews containing robust evidence exist for wound care uncertainties prioritised by community-based healthcare professionals. We asked healthcare professionals to prioritise uncertainties based on complex wound care decisions, and then classified 28 uncertainties according to the type and level of decision. For each uncertainty, we searched for relevant systematic reviews. Two independent reviewers screened abstracts and full texts of reviews against the following criteria: meeting an a priori definition of a systematic review, sufficiently addressing the uncertainty, published during or after 2012, and identifying high quality research evidence. The most common uncertainty type was 'interventions' 24/28 (85%); the majority concerned wound level decisions 15/28 (53%) however, service delivery level decisions (10/28) were given highest priority. Overall, we found 162 potentially relevant reviews of which 57 (35%) were not systematic reviews. Of 106 systematic reviews, only 28 were relevant to an uncertainty and 18 of these were published within the preceding five years; none identified high quality research evidence. Despite the growing volume of published primary research, healthcare professionals delivering wound care have important clinical uncertainties which are not addressed by up-to-date systematic reviews containing high certainty evidence. These are high priority topics requiring new research and systematic reviews which are regularly updated. To reduce clinical and research waste, we recommend systematic reviewers and researchers make greater efforts to ensure that research addresses important clinical uncertainties and is of sufficient rigour to inform practice.

Information asymmetry, social networking site word of mouth, and mobility effects on social commerce in Korea.

PubMed

Hwang, In Jeong; Lee, Bong Gyou; Kim, Ki Youn

2014-02-01

The purpose of this research is to examine the issues that affect customers' behavioral character and purchasing behavior. The study proposes a research hypothesis with independent variables that include social presence, trust, and information asymmetry, and the dependent variable purchase decision making, to explain differentiated customer decision making processes in social commerce (S-commerce). To prove the hypothesis, positive verification was performed by focusing on mediating effects through a customer uncertainty variable and moderating effects through mobility and social networking site word of mouth (SNS WOM) variables. The number of studies on customer trends has rapidly increased together with the market size of S-commerce. However, few studies have examined the negative variables that make customers hesitant to make decisions in S-commerce. This study investigates the causes of customer uncertainty and focuses on deducing the control variables that offset this negative relationship. The study finds that in customers' S-commerce purchasing actions, the SNS WOM and mobility variables show control effects between information asymmetry and uncertainty and between trust and uncertainty. Additionally, this research defines the variables related to customer uncertainty that are hidden in S-commerce, and statistically verifies their relationship. The research results can be used in Internet marketing practices to establish marketing mix strategies for customer demand or as research data to predict customer behavior. The results are scientifically meaningful as a precedent for research on customers in S-commerce.

Sustainable energy planning decision using the intuitionistic fuzzy analytic hierarchy process: choosing energy technology in Malaysia

NASA Astrophysics Data System (ADS)

Abdullah, Lazim; Najib, Liana

2016-04-01

Energy consumption for developing countries is sharply increasing due to the higher economic growth due to industrialisation along with population growth and urbanisation. The increasing demand of energy leads to global energy crisis. Selecting the best energy technology and conservation requires both quantitative and qualitative evaluation criteria. The fuzzy set-based approach is one of the well-known theories to handle fuzziness, uncertainty in decision-making and vagueness of information. This paper proposes a new method of intuitionistic fuzzy analytic hierarchy process (IF-AHP) to deal with the uncertainty in decision-making. The new IF-AHP is applied to establish a preference in the sustainable energy planning decision-making problem. Three decision-makers attached with Malaysian government agencies were interviewed to provide linguistic judgement prior to analysing with the new IF-AHP. Nuclear energy has been decided as the best alternative in energy planning which provides the highest weight among all the seven alternatives.

Decision analysis of emergency ventilation and evacuation strategies against suddenly released contaminant indoors by considering the uncertainty of source locations.

PubMed

Cai, Hao; Long, Weiding; Li, Xianting; Kong, Lingjuan; Xiong, Shuang

2010-06-15

In case hazardous contaminants are suddenly released indoors, the prompt and proper emergency responses are critical to protect occupants. This paper aims to provide a framework for determining the optimal combination of ventilation and evacuation strategies by considering the uncertainty of source locations. The certainty of source locations is classified as complete certainty, incomplete certainty, and complete uncertainty to cover all the possible situations. According to this classification, three types of decision analysis models are presented. A new concept, efficiency factor of contaminant source (EFCS), is incorporated in these models to evaluate the payoffs of the ventilation and evacuation strategies. A procedure of decision-making based on these models is proposed and demonstrated by numerical studies of one hundred scenarios with ten ventilation modes, two evacuation modes, and five source locations. The results show that the models can be useful to direct the decision analysis of both the ventilation and evacuation strategies. In addition, the certainty of the source locations has an important effect on the outcomes of the decision-making. Copyright 2010 Elsevier B.V. All rights reserved.

Uncertainty As a Trigger for a Paradigm Change in Science Communication

NASA Astrophysics Data System (ADS)

Schneider, S.

2014-12-01

Over the last decade, the need to communicate uncertainty increased. Climate sciences and environmental sciences have faced massive propaganda campaigns by global industry and astroturf organizations. These organizations use the deep societal mistrust in uncertainty to point out alleged unethical and intentional delusion of decision makers and the public by scientists and their consultatory function. Scientists, who openly communicate uncertainty of climate model calculations, earthquake occurrence frequencies, or possible side effects of genetic manipulated semen have to face massive campaigns against their research, and sometimes against their person and live as well. Hence, new strategies to communicate uncertainty have to face the societal roots of the misunderstanding of the concept of uncertainty itself. Evolutionary biology has shown, that human mind is well suited for practical decision making by its sensory structures. Therefore, many of the irrational concepts about uncertainty are mitigated if data is presented in formats the brain is adapted to understand. At the end, the impact of uncertainty to the decision-making process is finally dominantly driven by preconceptions about terms such as uncertainty, vagueness or probabilities. Parallel to the increasing role of scientific uncertainty in strategic communication, science communicators for example at the Research and Development Program GEOTECHNOLOGIEN developed a number of techniques to master the challenge of putting uncertainty in the focus. By raising the awareness of scientific uncertainty as a driving force for scientific development and evolution, the public perspective on uncertainty is changing. While first steps to implement this process are under way, the value of uncertainty still is underestimated in the public and in politics. Therefore, science communicators are in need for new and innovative ways to talk about scientific uncertainty.

A Panel Study on the Effects of Task Uncertainty, Interdependence , and Size on Unit Decision Making

ERIC Educational Resources Information Center

Van De Ven, Andrew H.

1977-01-01

This panel study examined the determinants of supervisory, employee, and group decision-making in departments or units within a complex organization. Available from: Comparative Administration Research Institute, Kent State University Press, Kent State University, Kent, OH 44242. (Author)

Gendered Uncertainty and Variation in Physicians' Decisions for Coronary Heart Disease: The Double-Edged Sword of "Atypical Symptoms"

ERIC Educational Resources Information Center

Welch, Lisa C.; Lutfey, Karen E.; Gerstenberger, Eric; Grace, Matthew

2012-01-01

Nonmedical factors and diagnostic certainty contribute to variation in clinical decision making, but the process by which this occurs remains unclear. We examine how physicians' interpretations of patient sex-gender affect diagnostic certainty and, in turn, decision making for coronary heart disease. Data are from a factorial experiment of 256…

Markov logic network based complex event detection under uncertainty

NASA Astrophysics Data System (ADS)

Lu, Jingyang; Jia, Bin; Chen, Genshe; Chen, Hua-mei; Sullivan, Nichole; Pham, Khanh; Blasch, Erik

2018-05-01

In a cognitive reasoning system, the four-stage Observe-Orient-Decision-Act (OODA) reasoning loop is of interest. The OODA loop is essential for the situational awareness especially in heterogeneous data fusion. Cognitive reasoning for making decisions can take advantage of different formats of information such as symbolic observations, various real-world sensor readings, or the relationship between intelligent modalities. Markov Logic Network (MLN) provides mathematically sound technique in presenting and fusing data at multiple levels of abstraction, and across multiple intelligent sensors to conduct complex decision-making tasks. In this paper, a scenario about vehicle interaction is investigated, in which uncertainty is taken into consideration as no systematic approaches can perfectly characterize the complex event scenario. MLNs are applied to the terrestrial domain where the dynamic features and relationships among vehicles are captured through multiple sensors and information sources regarding the data uncertainty.

Risk, Uncertainty and Precaution in Science: The Threshold of the Toxicological Concern Approach in Food Toxicology.

PubMed

Bschir, Karim

2017-04-01

Environmental risk assessment is often affected by severe uncertainty. The frequently invoked precautionary principle helps to guide risk assessment and decision-making in the face of scientific uncertainty. In many contexts, however, uncertainties play a role not only in the application of scientific models but also in their development. Building on recent literature in the philosophy of science, this paper argues that precaution should be exercised at the stage when tools for risk assessment are developed as well as when they are used to inform decision-making. The relevance and consequences of this claim are discussed in the context of the threshold of the toxicological concern approach in food toxicology. I conclude that the approach does not meet the standards of an epistemic version of the precautionary principle.

Robustness of risk maps and survey networks to knowledge gaps about a new invasive pest

Treesearch

Denys Yemshanov; Frank H. Koch; Yakov Ben-Haim; William D. Smith

2010-01-01

In pest risk assessment it is frequently necessary to make management decisions regarding emerging threats under severe uncertainty. Although risk maps provide useful decision support for invasive alien species, they rarely address knowledge gaps associated with the underlying risk model or how they may change the risk estimates. Failure to recognize uncertainty leads...

Bayesian Decision Support

NASA Astrophysics Data System (ADS)

Berliner, M.

2017-12-01

Bayesian statistical decision theory offers a natural framework for decision-policy making in the presence of uncertainty. Key advantages of the approach include efficient incorporation of information and observations. However, in complicated settings it is very difficult, perhaps essentially impossible, to formalize the mathematical inputs needed in the approach. Nevertheless, using the approach as a template is useful for decision support; that is, organizing and communicating our analyses. Bayesian hierarchical modeling is valuable in quantifying and managing uncertainty such cases. I review some aspects of the idea emphasizing statistical model development and use in the context of sea-level rise.

Reason, emotion and decision-making: risk and reward computation with feeling.

PubMed

Quartz, Steven R

2009-05-01

Many models of judgment and decision-making posit distinct cognitive and emotional contributions to decision-making under uncertainty. Cognitive processes typically involve exact computations according to a cost-benefit calculus, whereas emotional processes typically involve approximate, heuristic processes that deliver rapid evaluations without mental effort. However, it remains largely unknown what specific parameters of uncertain decision the brain encodes, the extent to which these parameters correspond to various decision-making frameworks, and their correspondence to emotional and rational processes. Here, I review research suggesting that emotional processes encode in a precise quantitative manner the basic parameters of financial decision theory, indicating a reorientation of emotional and cognitive contributions to risky choice.

Aging and loss decision making: increased risk aversion and decreased use of maximizing information, with correlated rationality and value maximization.

PubMed

Kurnianingsih, Yoanna A; Sim, Sam K Y; Chee, Michael W L; Mullette-Gillman, O'Dhaniel A

2015-01-01

We investigated how adult aging specifically alters economic decision-making, focusing on examining alterations in uncertainty preferences (willingness to gamble) and choice strategies (what gamble information influences choices) within both the gains and losses domains. Within each domain, participants chose between certain monetary outcomes and gambles with uncertain outcomes. We examined preferences by quantifying how uncertainty modulates choice behavior as if altering the subjective valuation of gambles. We explored age-related preferences for two types of uncertainty, risk, and ambiguity. Additionally, we explored how aging may alter what information participants utilize to make their choices by comparing the relative utilization of maximizing and satisficing information types through a choice strategy metric. Maximizing information was the ratio of the expected value of the two options, while satisficing information was the probability of winning. We found age-related alterations of economic preferences within the losses domain, but no alterations within the gains domain. Older adults (OA; 61-80 years old) were significantly more uncertainty averse for both risky and ambiguous choices. OA also exhibited choice strategies with decreased use of maximizing information. Within OA, we found a significant correlation between risk preferences and choice strategy. This linkage between preferences and strategy appears to derive from a convergence to risk neutrality driven by greater use of the effortful maximizing strategy. As utility maximization and value maximization intersect at risk neutrality, this result suggests that OA are exhibiting a relationship between enhanced rationality and enhanced value maximization. While there was variability in economic decision-making measures within OA, these individual differences were unrelated to variability within examined measures of cognitive ability. Our results demonstrate that aging alters economic decision-making for losses through changes in both individual preferences and the strategies individuals employ.

Methods for handling uncertainty within pharmaceutical funding decisions

NASA Astrophysics Data System (ADS)

Stevenson, Matt; Tappenden, Paul; Squires, Hazel

2014-01-01

This article provides a position statement regarding decision making under uncertainty within the economic evaluation of pharmaceuticals, with a particular focus upon the National Institute for Health and Clinical Excellence context within England and Wales. This area is of importance as funding agencies have a finite budget from which to purchase a selection of competing health care interventions. The objective function generally used is that of maximising societal health with an explicit acknowledgement that there will be opportunity costs associated with purchasing a particular intervention. Three components of uncertainty are discussed within a pharmaceutical funding perspective: methodological uncertainty, parameter uncertainty and structural uncertainty, alongside a discussion of challenges that are particularly pertinent to health economic evaluation. The discipline has focused primarily on handling methodological and parameter uncertainty and a clear reference case has been developed for consistency across evaluations. However, uncertainties still remain. Less attention has been given to methods for handling structural uncertainty. The lack of adequate methods to explicitly incorporate this aspect of model development may result in the true uncertainty surrounding health care investment decisions being underestimated. Research in this area is ongoing as we review.

Probabilistic Radiological Performance Assessment Modeling and Uncertainty

NASA Astrophysics Data System (ADS)

Tauxe, J.

2004-12-01

A generic probabilistic radiological Performance Assessment (PA) model is presented. The model, built using the GoldSim systems simulation software platform, concerns contaminant transport and dose estimation in support of decision making with uncertainty. Both the U.S. Nuclear Regulatory Commission (NRC) and the U.S. Department of Energy (DOE) require assessments of potential future risk to human receptors of disposal of LLW. Commercially operated LLW disposal facilities are licensed by the NRC (or agreement states), and the DOE operates such facilities for disposal of DOE-generated LLW. The type of PA model presented is probabilistic in nature, and hence reflects the current state of knowledge about the site by using probability distributions to capture what is expected (central tendency or average) and the uncertainty (e.g., standard deviation) associated with input parameters, and propagating through the model to arrive at output distributions that reflect expected performance and the overall uncertainty in the system. Estimates of contaminant release rates, concentrations in environmental media, and resulting doses to human receptors well into the future are made by running the model in Monte Carlo fashion, with each realization representing a possible combination of input parameter values. Statistical summaries of the results can be compared to regulatory performance objectives, and decision makers are better informed of the inherently uncertain aspects of the model which supports their decision-making. While this information may make some regulators uncomfortable, they must realize that uncertainties which were hidden in a deterministic analysis are revealed in a probabilistic analysis, and the chance of making a correct decision is now known rather than hoped for. The model includes many typical features and processes that would be part of a PA, but is entirely fictitious. This does not represent any particular site and is meant to be a generic example. A practitioner could, however, start with this model as a GoldSim template and, by adding site specific features and parameter values (distributions), use this model as a starting point for a real model to be used in real decision making.

When is enough evidence enough? - Using systematic decision analysis and value-of-information analysis to determine the need for further evidence.

PubMed

Siebert, Uwe; Rochau, Ursula; Claxton, Karl

2013-01-01

Decision analysis (DA) and value-of-information (VOI) analysis provide a systematic, quantitative methodological framework that explicitly considers the uncertainty surrounding the currently available evidence to guide healthcare decisions. In medical decision making under uncertainty, there are two fundamental questions: 1) What decision should be made now given the best available evidence (and its uncertainty)?; 2) Subsequent to the current decision and given the magnitude of the remaining uncertainty, should we gather further evidence (i.e., perform additional studies), and if yes, which studies should be undertaken (e.g., efficacy, side effects, quality of life, costs), and what sample sizes are needed? Using the currently best available evidence, VoI analysis focuses on the likelihood of making a wrong decision if the new intervention is adopted. The value of performing further studies and gathering additional evidence is based on the extent to which the additional information will reduce this uncertainty. A quantitative framework allows for the valuation of the additional information that is generated by further research, and considers the decision maker's objectives and resource constraints. Claxton et al. summarise: "Value of information analysis can be used to inform a range of policy questions including whether a new technology should be approved based on existing evidence, whether it should be approved but additional research conducted or whether approval should be withheld until the additional evidence becomes available." [Claxton K. Value of information entry in Encyclopaedia of Health Economics, Elsevier, forthcoming 2014.] The purpose of this tutorial is to introduce the framework of systematic VoI analysis to guide further research. In our tutorial article, we explain the theoretical foundations and practical methods of decision analysis and value-of-information analysis. To illustrate, we use a simple case example of a foot ulcer (e.g., with diabetes) as well as key references from the literature, including examples for the use of the decision-analytic VoI framework by health technology assessment agencies to guide further research. These concepts may guide stakeholders involved or interested in how to determine whether or not and, if so, which additional evidence is needed to make decisions. Copyright © 2013. Published by Elsevier GmbH.

Group decision-making approach for flood vulnerability identification using the fuzzy VIKOR method

NASA Astrophysics Data System (ADS)

Lee, G.; Jun, K. S.; Cung, E. S.

2014-09-01

This study proposes an improved group decision making (GDM) framework that combines VIKOR method with fuzzified data to quantify the spatial flood vulnerability including multi-criteria evaluation indicators. In general, GDM method is an effective tool for formulating a compromise solution that involves various decision makers since various stakeholders may have different perspectives on their flood risk/vulnerability management responses. The GDM approach is designed to achieve consensus building that reflects the viewpoints of each participant. The fuzzy VIKOR method was developed to solve multi-criteria decision making (MCDM) problems with conflicting and noncommensurable criteria. This comprising method can be used to obtain a nearly ideal solution according to all established criteria. Triangular fuzzy numbers are used to consider the uncertainty of weights and the crisp data of proxy variables. This approach can effectively propose some compromising decisions by combining the GDM method and fuzzy VIKOR method. The spatial flood vulnerability of the south Han River using the GDM approach combined with the fuzzy VIKOR method was compared with the results from general MCDM methods, such as the fuzzy TOPSIS and classical GDM methods, such as those developed by Borda, Condorcet, and Copeland. The evaluated priorities were significantly dependent on the employed decision-making method. The proposed fuzzy GDM approach can reduce the uncertainty in the data confidence and weight derivation techniques. Thus, the combination of the GDM approach with the fuzzy VIKOR method can provide robust prioritization because it actively reflects the opinions of various groups and considers uncertainty in the input data.

Relationship of external influence to parental distress in decision making regarding children with a life-threatening illness.

PubMed

Miller, Victoria A; Luce, Mary Frances; Nelson, Robert M

2011-01-01

To examine the relationship of external influence to parental distress when making a decision about research or treatment for a child with a life-threatening illness and to test potential moderators of this relationship. Parents (n = 219) who made a decision about research or treatment for a child completed measures of external influence, distress, decision-making preference, and coping. More external influence was associated with more hostility, uncertainty, and confusion. Decision-making preference and coping style moderated the relationship between external influence and distress: More external influence was associated with more distress when decision-making preference was low and task-focused coping was high. External influence appears to be related to distress in parents making research and treatment decisions for children with life-threatening illnesses. However, it is important to consider parent characteristics, such as decision-making preference and coping style, when examining the effects of contextual factors on distress during decision making.

Transportation planning, climate change, and decision making under uncertainty

DOT National Transportation Integrated Search

2008-01-01

Case studies are presented that illustrate the application of methods which incorporate : decisionmaking under uncertainty. The applications of these methods that are summarized in : this paper deal with cases outside of transportation, including mil...

Research strategies for addressing uncertainties

USGS Publications Warehouse

Busch, David E.; Brekke, Levi D.; Averyt, Kristen; Jardine, Angela; Welling, Leigh; Garfin, Gregg; Jardine, Angela; Merideth, Robert; Black, Mary; LeRoy, Sarah

2013-01-01

Research Strategies for Addressing Uncertainties builds on descriptions of research needs presented elsewhere in the book; describes current research efforts and the challenges and opportunities to reduce the uncertainties of climate change; explores ways to improve the understanding of changes in climate and hydrology; and emphasizes the use of research to inform decision making.

Managing risk and expected financial return from selective expansion of operating room capacity: mean-variance analysis of a hospital's portfolio of surgeons.

PubMed

Dexter, Franklin; Ledolter, Johannes

2003-07-01

Surgeons using the same amount of operating room (OR) time differ in their achieved hospital contribution margins (revenue minus variable costs) by >1000%. Thus, to improve the financial return from perioperative facilities, OR strategic decisions should selectively focus additional OR capacity and capital purchasing on a few surgeons or subspecialties. These decisions use estimates of each surgeon's and/or subspecialty's contribution margin per OR hour. The estimates are subject to uncertainty (e.g., from outliers). We account for the uncertainties by using mean-variance portfolio analysis (i.e., quadratic programming). This method characterizes the problem of selectively expanding OR capacity based on the expected financial return and risk of different portfolios of surgeons. The assessment reveals whether the choices, of which surgeons have their OR capacity expanded, are sensitive to the uncertainties in the surgeons' contribution margins per OR hour. Thus, mean-variance analysis reduces the chance of making strategic decisions based on spurious information. We also assess the financial benefit of using mean-variance portfolio analysis when the planned expansion of OR capacity is well diversified over at least several surgeons or subspecialties. Our results show that, in such circumstances, there may be little benefit from further changing the portfolio to reduce its financial risk. Surgeon and subspecialty specific hospital financial data are uncertain, a fact that should be taken into account when making decisions about expanding operating room capacity. We show that mean-variance portfolio analysis can incorporate this uncertainty, thereby guiding operating room management decision-making and reducing the chance of a strategic decision being made based on spurious information.

Siting and Routing Assessment for Solid Waste Management Under Uncertainty Using the Grey Mini-Max Regret Criterion

NASA Astrophysics Data System (ADS)

Chang, Ni-Bin; Davila, Eric

2006-10-01

Solid waste management (SWM) is at the forefront of environmental concerns in the Lower Rio Grande Valley (LRGV), South Texas. The complexity in SWM drives area decision makers to look for innovative and forward-looking solutions to address various waste management options. In decision analysis, it is not uncommon for decision makers to go by an option that may minimize the maximum regret when some determinant factors are vague, ambiguous, or unclear. This article presents an innovative optimization model using the grey mini-max regret (GMMR) integer programming algorithm to outline an optimal regional coordination of solid waste routing and possible landfill/incinerator construction under an uncertain environment. The LRGV is an ideal location to apply the GMMR model for SWM planning because of its constant urban expansion, dwindling landfill space, and insufficient data availability signifying the planning uncertainty combined with vagueness in decision-making. The results give local decision makers hedged sets of options that consider various forms of systematic and event-based uncertainty. By extending the dimension of decision-making, this may lead to identifying a variety of beneficial solutions with efficient waste routing and facility siting for the time frame of 2005 through 2010 in LRGV. The results show the ability of the GMMR model to open insightful scenario planning that can handle situational and data-driven uncertainty in a way that was previously unavailable. Research findings also indicate that the large capital investment of incineration facilities makes such an option less competitive among municipal options for landfills. It is evident that the investment from a municipal standpoint is out of the question, but possible public-private partnerships may alleviate this obstacle.

Striatal Activity Underlies Novelty-Based Choice in Humans

PubMed Central

Wittmann, Bianca C.; Daw, Nathaniel D.; Seymour, Ben; Dolan, Raymond J.

2008-01-01

Summary The desire to seek new and unfamiliar experiences is a fundamental behavioral tendency in humans and other species. In economic decision making, novelty seeking is often rational, insofar as uncertain options may prove valuable and advantageous in the long run. Here, we show that, even when the degree of perceptual familiarity of an option is unrelated to choice outcome, novelty nevertheless drives choice behavior. Using functional magnetic resonance imaging (fMRI), we show that this behavior is specifically associated with striatal activity, in a manner consistent with computational accounts of decision making under uncertainty. Furthermore, this activity predicts interindividual differences in susceptibility to novelty. These data indicate that the brain uses perceptual novelty to approximate choice uncertainty in decision making, which in certain contexts gives rise to a newly identified and quantifiable source of human irrationality. PMID:18579085

[Diagnostic rationalism. Views of general practitioners on fibromyalgia].

PubMed

Daehli, B

1993-09-20

Clinical practice is characterized by having to make numerous important decisions, including the diagnosis. In this study, general practitioners were asked to agree or to disagree with statements of fibromyalgia. The main purpose was to test the usefulness of two well-known models for decision-making when studying diagnosis in cases of uncertainty and scepticism. The results show that the models are inadequate to explain the decisions.

Altered subjective reward valuation among drug-deprived heavy marijuana users: Aversion to uncertainty

PubMed Central

Hefner, Kathryn R.; Starr, Mark. J.; Curtin, John. J.

2015-01-01

Marijuana is the most commonly used illicit drug in the United States and its use is rising. Nonetheless, scientific efforts to clarify the risk for addiction and other harm associated with marijuana use have been lacking. Maladaptive decision-making is a cardinal feature of addiction that is likely to emerge in heavy users. In particular, distorted subjective reward valuation related to homeostatic or allostatic processes has been implicated for many drugs of abuse. Selective changes in responses to uncertainty have been observed in response to intoxication and deprivation from various drugs of abuse. To assess for these potential neuroadaptive changes in reward valuation associated with marijuana deprivation, we examined the subjective value of uncertain and certain rewards among deprived and non-deprived heavy marijuana users in a behavioral economics decision-making task. Deprived users displayed reduced valuation of uncertain rewards, particularly when these rewards were more objectively valuable. This uncertainty aversion increased with increasing quantity of marijuana use. These results suggest comparable decision-making vulnerability from marijuana use as other drugs of abuse, and highlights targets for intervention. PMID:26595464

Value Focused Thinking in Developing Aerobatic Aircraft Selection Model for Turkish Air Force

DTIC Science & Technology

2012-03-22

many reasons . Most problems in decision- making involve multiple objectives and uncertainties. The number of alternatives can be significant and make ...and Republic of Turkey all around the world”. This is a clear and concise statement of the most basic reason for decision. After making interview...Hwang, C.-L. (1995). Multiple Attribute Decison Making : An Introduction. California: Sage Publications. 90 Vita First Lieutenant

Preferred information sources for clinical decision making: critical care nurses' perceptions of information accessibility and usefulness.

PubMed

Marshall, Andrea P; West, Sandra H; Aitken, Leanne M

2011-12-01

Variability in clinical practice may result from the use of diverse information sources to guide clinical decisions. In routine clinical practice, nurses privilege information from colleagues over more formal information sources. It is not clear whether similar information-seeking behaviour is exhibited when critical care nurses make decisions about a specific clinical practice, where extensive practice variability exists alongside a developing research base. This study explored the preferred sources of information intensive care nurses used and their perceptions of the accessibility and usefulness of this information for making decisions in clinically uncertain situations specific to enteral feeding practice. An instrumental case study design, incorporating concurrent verbal protocols, Q methodology and focus groups, was used to determine intensive care nurses' perspectives of information use in the resolution of clinical uncertainty. A preference for information from colleagues to support clinical decisions was observed. People as information sources were considered most useful and most accessible in the clinical setting. Text and electronic information sources were seen as less accessible, mainly because of the time required to access the information within the documents. When faced with clinical uncertainty, obtaining information from colleagues allows information to be quickly accessed and applied within the context of a specific clinical presentation. Seeking information from others also provides opportunities for shared decision-making and potential validation of clinical judgment, although differing views may exacerbate clinical uncertainty. The social exchange of clinical information may meet the needs of nurses working in a complex, time-pressured environment but the extent of the evidence base for information passed through verbal communication is unclear. The perceived usefulness and accessibility of information is premised on the ease of use and access and thus the variability in information may be contributing to clinical uncertainty. Copyright ©2011 Sigma Theta Tau International.

Speed accuracy trade-off under response deadlines

PubMed Central

Karşılar, Hakan; Simen, Patrick; Papadakis, Samantha; Balcı, Fuat

2014-01-01

Perceptual decision making has been successfully modeled as a process of evidence accumulation up to a threshold. In order to maximize the rewards earned for correct responses in tasks with response deadlines, participants should collapse decision thresholds dynamically during each trial so that a decision is reached before the deadline. This strategy ensures on-time responding, though at the cost of reduced accuracy, since slower decisions are based on lower thresholds and less net evidence later in a trial (compared to a constant threshold). Frazier and Yu (2008) showed that the normative rate of threshold reduction depends on deadline delays and on participants' uncertainty about these delays. Participants should start collapsing decision thresholds earlier when making decisions under shorter deadlines (for a given level of timing uncertainty) or when timing uncertainty is higher (for a given deadline). We tested these predictions using human participants in a random dot motion discrimination task. Each participant was tested in free-response, short deadline (800 ms), and long deadline conditions (1000 ms). Contrary to optimal-performance predictions, the resulting empirical function relating accuracy to response time (RT) in deadline conditions did not decline to chance level near the deadline; nor did the slight decline we typically observed relate to measures of endogenous timing uncertainty. Further, although this function did decline slightly with increasing RT, the decline was explainable by the best-fitting parameterization of Ratcliff's diffusion model (Ratcliff, 1978), whose parameters are constant within trials. Our findings suggest that at the very least, typical decision durations are too short for participants to adapt decision parameters within trials. PMID:25177265

Physicians' reactions to uncertainty in the context of shared decision making.

PubMed

Politi, Mary C; Légaré, France

2010-08-01

Physicians' reactions towards uncertainty may influence their willingness to engage in shared decision making (SDM). This study aimed to identify variables associated with physician's anxiety from uncertainty and reluctance to disclose uncertainty to patients. We conducted a cross-sectional secondary analysis of longitudinal data of an implementation study of SDM among primary care professionals (n=122). Outcomes were anxiety from uncertainty and reluctance to disclose uncertainty to patients. Hypothesized factors that would be associated with outcomes included attitude, social norm, perceived behavioral control, intention to implement SDM in practice, and socio-demographics. Stepwise linear regression was used to identify predictors of anxiety from uncertainty and reluctance to disclose uncertainty to patients. In multivariate analyses, anxiety from uncertainty was influenced by female gender (beta=0.483; p=0.0039), residency status (1st year: beta=0.600; p=0.001; 2nd year: beta=0.972; p<0.001), and number of hours worked per week (beta=-0.012; p=0.048). Reluctance to disclose uncertainty to patients was influenced by having more years in formal education (beta=-1.996; p=0.012). Variables associated with anxiety from uncertainty differ from those associated with reluctance to disclose uncertainty to patients. Given the importance of communicating uncertainty during SDM, measuring physicians' reactions to uncertainty is essential in SDM implementation studies. Copyright 2009 Elsevier Ireland Ltd. All rights reserved.

Assessment of spatial variation of risks in small populations.

PubMed Central

Riggan, W B; Manton, K G; Creason, J P; Woodbury, M A; Stallard, E

1991-01-01

Often environmental hazards are assessed by examining the spatial variation of disease-specific mortality or morbidity rates. These rates, when estimated for small local populations, can have a high degree of random variation or uncertainty associated with them. If those rate estimates are used to prioritize environmental clean-up actions or to allocate resources, then those decisions may be influenced by this high degree of uncertainty. Unfortunately, the effect of this uncertainty is not to add "random noise" into the decision-making process, but to systematically bias action toward the smallest populations where uncertainty is greatest and where extreme high and low rate deviations are most likely to be manifest by chance. We present a statistical procedure for adjusting rate estimates for differences in variability due to differentials in local area population sizes. Such adjustments produce rate estimates for areas that have better properties than the unadjusted rates for use in making statistically based decisions about the entire set of areas. Examples are provided for county variation in bladder, stomach, and lung cancer mortality rates for U.S. white males for the period 1970 to 1979. PMID:1820268

Making sense of genetic uncertainty: the role of religion and spirituality.

PubMed

White, Mary T

2009-02-15

This article argues that to the extent that religious and spiritual beliefs can help people cope with genetic uncertainty, a limited spiritual assessment may be appropriate in genetic counseling. The article opens by establishing why genetic information is inherently uncertain and why this uncertainty can be medically, morally, and spiritually problematic. This is followed by a review of the range of factors that can contribute to risk assessments, including a few heuristics commonly used in responses to uncertainty. The next two sections summarize recent research on the diverse roles of religious and spiritual beliefs in genetic decisions and challenges to conducting spiritual assessments in genetic counseling. Based on these findings, religious and spiritual beliefs are posited as serving essentially as a heuristic that some people will utilize in responding to their genetic risks. In the interests of helping such clients make informed decisions, a limited spiritual assessment is recommended and described. Some of the challenges and risks associated with this limited assessment are discussed. Since some religious and spiritual beliefs can conflict with the values of medicine, some decisions will remain problematic. (c) 2009 Wiley-Liss, Inc.

Has Lean improved organizational decision making?

PubMed

Simons, Pascale; Benders, Jos; Bergs, Jochen; Marneffe, Wim; Vandijck, Dominique

2016-06-13

Purpose - Sustainable improvement is likely to be hampered by ambiguous objectives and uncertain cause-effect relations in care processes (the organization's decision-making context). Lean management can improve implementation results because it decreases ambiguity and uncertainties. But does it succeed? Many quality improvement (QI) initiatives are appropriate improvement strategies in organizational contexts characterized by low ambiguity and uncertainty. However, most care settings do not fit this context. The purpose of this paper is to investigate whether a Lean-inspired change program changed the organization's decision-making context, making it more amenable for QI initiatives. Design/methodology/approach - In 2014, 12 professionals from a Dutch radiotherapy institute were interviewed regarding their perceptions of a Lean program in their organization and the perceived ambiguous objectives and uncertain cause-effect relations in their clinical processes. A survey (25 questions), addressing the same concepts, was conducted among the interviewees in 2011 and 2014. The structured interviews were analyzed using a deductive approach. Quantitative data were analyzed using appropriate statistics. Findings - Interviewees experienced improved shared visions and the number of uncertain cause-effect relations decreased. Overall, more positive (99) than negative Lean effects (18) were expressed. The surveys revealed enhanced process predictability and standardization, and improved shared visions. Practical implications - Lean implementation has shown to lead to greater transparency and increased shared visions. Originality/value - Lean management decreased ambiguous objectives and reduced uncertainties in clinical process cause-effect relations. Therefore, decision making benefitted from Lean increasing QI's sustainability.

Improving Shipboard Decision Making in the CBR-D (Chemical/Biological Radiological Defense) Environment: Concepts of Use for and Functional Description of a Decision Aid/Training System (DECAID)

DTIC Science & Technology

1988-08-19

take place over the period of several days. Decisions regarding MOPP level or resource allocation made on day I may have no immediate impact, but a...present -- conditions, and manage a resource library to assist the DCA in making decisions under conditions of uncertainty. Several areas of utilization are...students work through a scenario, the device couid then display the consequences of those decisions or provide optimal decision recommendations

Success matters: Recasting the relationship among geophysical, biological, and behavioral scientists to support decision making on major environmental challenges

NASA Astrophysics Data System (ADS)

Knopman, Debra S.

2006-03-01

Coping with global change, providing clean water for growing populations, and disposing of nuclear waste are some of the most difficult public policy challenges of our time. Unknowns in the physical sciences are one source of the difficulty. Real difficulties in meeting these challenges also arise in the behavioral sciences. A potentially rich vein of transdisciplinary research is to integrate the psychology of decision making, known as "judgment and decision making," or JDM, with the development of technical information and decision support tools for complex, long-term environmental problems. Practitioners of JDM conduct research on how individuals and groups respond to uncertainty and ambiguity, hedge against risks, anchor decisions to the status quo, compare relative risks and rewards of alternative strategies, and cope with other classes of decisions. Practitioners use a variety of stimuli, chance devices, hypothetical and real choices involving small stakes, scenarios, and questionnaires to measure (directly and indirectly) preferences under varying conditions. These kinds of experiments can help guide choices about the level of complexity required for different types of decision-making processes, the value of new data collection efforts, and the ways in which uncertainty in model outcomes can be cast to minimize decision-making paralysis. They can also provide a scientific basis for interacting with decision makers throughout the model development process, designing better ways of eliciting and combining opinions and of communicating information relevant to public policy issues with the goal of improving the value of the scientific contribution to the social decision.

Anthropology and decision making about chronic technological disasters: Mixed waste remediation on the Oak Ridge Reservation

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

Wolfe, A.K.; Schweitzer, M.

This paper discusses two related case studies of decision making about the remediation of mixed (hazardous and radioactive) wastes on the Oak Ridge Reservation in Tennessee. The three goals of the paper are to (1) place current decision-making efforts in the varied and evolving social, political, regulatory, economic, and technological contexts in which they occur; (2) present definitions and attributes of {open_quotes}successful{close_quotes} environmental decision making from the perspectives of key constituency groups that participate in decision making; and (3) discuss the role of anthropology in addressing environmental decision making. Environmental decision making about remediation is extraordinarily complex, involving human healthmore » and ecological risks; uncertainties about risks, technological ability to clean up, the financial costs of clean up; multiple and sometimes conflicting regulations; social equity and justice considerations; and decreasing budgets. Anthropological theories and methods can contribute to better understanding and, potentially, to better decision making.« less

Language of Uncertainty: the Expression of Decisional Conflict Related to Skin Cancer Prevention Recommendations.

PubMed

Strekalova, Yulia A; James, Vaughan S

2017-09-01

User-generated information on the Internet provides opportunities for the monitoring of health information consumer attitudes. For example, information about cancer prevention may cause decisional conflict. Yet posts and conversations shared by health information consumers online are often not readily actionable for interpretation and decision-making due to their unstandardized format. This study extends prior research on the use of natural language as a predictor of consumer attitudes and provides a link to decision-making by evaluating the predictive role of uncertainty indicators expressed in natural language. Analyzed data included free-text comments and structured scale responses related to information about skin cancer prevention options. The study identified natural language indicators of uncertainty and showed that it can serve as a predictor of decisional conflict. The natural indicators of uncertainty reported here can facilitate the monitoring of health consumer perceptions about cancer prevention recommendations and inform education and communication campaign planning and evaluation.

Decision strategies for handling the uncertainty of future extreme rainfall under the influence of climate change.

PubMed

Gregersen, I B; Arnbjerg-Nielsen, K

2012-01-01

Several extraordinary rainfall events have occurred in Denmark within the last few years. For each event, problems in urban areas occurred as the capacity of the existing drainage systems were exceeded. Adaptation to climate change is necessary but also very challenging as urban drainage systems are characterized by long technical lifetimes and high, unrecoverable construction costs. One of the most important barriers for the initiation and implementation of the adaptation strategies is therefore the uncertainty when predicting the magnitude of the extreme rainfall in the future. This challenge is explored through the application and discussion of three different theoretical decision support strategies: the precautionary principle, the minimax strategy and Bayesian decision support. The reviewed decision support strategies all proved valuable for addressing the identified uncertainties, at best applied together as they all yield information that improved decision making and thus enabled more robust decisions.

Integrating Land Cover Modeling and Adaptive Management to Conserve Endangered Species and Reduce Catastrophic Fire Risk

NASA Technical Reports Server (NTRS)

Breininger, David; Duncan, Brean; Eaton, Mitchell; Johnson, Fred; Nichols, James

2014-01-01

Land cover modeling is used to inform land management, but most often via a two-step process where science informs how management alternatives can influence resources and then decision makers can use this to make decisions. A more efficient process is to directly integrate science and decision making, where science allows us to learn to better accomplish management objectives and is developed to address specific decisions. Co-development of management and science is especially productive when decisions are complicated by multiple objectives and impeded by uncertainty. Multiple objectives can be met by specification of tradeoffs, and relevant uncertainty can be addressed through targeted science (i.e., models and monitoring). We describe how to integrate habitat and fuels monitoring with decision making focused on dual objectives of managing for endangered species and minimizing catastrophic fire risk. Under certain conditions, both objectives might be achieved by a similar management policy, but habitat trajectories suggest tradeoffs. Knowledge about system responses to actions can be informed by applying competing management actions to different land units in the same system state and by ideas about fire behavior. Monitoring and management integration is important to optimize state-specific management decisions and increase knowledge about system responses. We believe this approach has broad utility for and cover modeling programs intended to inform decision making.

Shared decision making in endocrinology: present and future directions.

PubMed

Rodriguez-Gutierrez, Rene; Gionfriddo, Michael R; Ospina, Naykky Singh; Maraka, Spyridoula; Tamhane, Shrikant; Montori, Victor M; Brito, Juan P

2016-08-01

In medicine and endocrinology, there are few clinical circumstances in which clinicians can accurately predict what is best for their patients. As a result, patients and clinicians frequently have to make decisions about which there is uncertainty. Uncertainty results from limitations in the research evidence, unclear patient preferences, or an inability to predict how treatments will fit into patients' daily lives. The work that patients and clinicians do together to address the patient's situation and engage in a deliberative dialogue about reasonable treatment options is often called shared decision making. Decision aids are evidence-based tools that facilitate this process. Shared decision making is a patient-centred approach in which clinicians share information about the benefits, harms, and burden of different reasonable diagnostic and treatment options, and patients explain what matters to them in view of their particular values, preferences, and personal context. Beyond the ethical argument in support of this approach, decision aids have been shown to improve patients' knowledge about the available options, accuracy of risk estimates, and decisional comfort. Decision aids also promote patient participation in the decision-making process. Despite accumulating evidence from clinical trials, policy support, and expert recommendations in endocrinology practice guidelines, shared decision making is still not routinely implemented in endocrine practice. Additional work is needed to enrich the number of available tools and to implement them in practice workflows. Also, although the evidence from randomised controlled trials favours the use of this shared decision making in other settings, populations, and illnesses, the effect of this approach has been studied in a few endocrine disorders. Future pragmatic trials are needed to explore the effect and feasibility of shared decision making implementation into routine endocrinology and primary care practice. With the available evidence, however, endocrinologists can now start to practice shared decision making, partner with their patients, and use their expertise to formulate treatment plans that reflect patient preferences and are more likely to fit into the context of patients' lives. In this Personal View, we describe shared decision making, the evidence behind the approach, and why and how both endocrinologists and their patients could benefit from this approach. Copyright © 2016 Elsevier Ltd. All rights reserved.

How Do Cultural Producers Make Creative Decisions? Lessons from the Catwalk

ERIC Educational Resources Information Center

Godart, Frederic C. Mears, Ashley

2009-01-01

Faced with high uncertainty, how do producers in the cultural economy make creative decisions? We present a case study of the fashion modeling industry. Using participant observation, interviews and network analysis of the Spring/Summer 2007 Fashion Week collections, we explain how producers select models for fashion shows. While fashion producers…

Variability Is Not the Villain: Finding Patterns in Complex Natural Images

ERIC Educational Resources Information Center

Brinton, Brigette Adair; Curran, Mary Carla

2015-01-01

Everyone needs strong observational skills to solve challenging problems and make informed decisions. However, many students expect to find exact answers to their questions by using the internet and do not understand the role of uncertainty, especially in decision making and scientific research. Humans and other animals choose among many options…

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.

Primary care clinicians' experiences with treatment decision making for older persons with multiple conditions.

PubMed

Fried, Terri R; Tinetti, Mary E; Iannone, Lynne

2011-01-10

Clinicians are caring for an increasing number of older patients with multiple diseases in the face of uncertainty concerning the benefits and harms associated with guideline-directed interventions. Understanding how primary care clinicians approach treatment decision making for these patients is critical to the design of interventions to improve the decision-making process. Focus groups were conducted with 40 primary care clinicians (physicians, nurse practitioners, and physician assistants) in academic, community, and Veterans Affairs-affiliated primary care practices. Participants were given open-ended questions about their approach to treatment decision making for older persons with multiple medical conditions. Responses were organized into themes using qualitative content analysis. The participants were concerned about their patients' ability to adhere to complex regimens derived from guideline-directed care. There was variability in beliefs regarding, and approaches to balancing, the benefits and harms of guideline-directed care. There was also variability regarding how the participants involved patients in the process of decision making, with clinicians describing conflicts between their own and their patients' goals. The participants listed a number of barriers to making good treatment decisions, including the lack of outcome data, the role of specialists, patient and family expectations, and insufficient time and reimbursement. The experiences of practicing clinicians suggest that they struggle with the uncertainties of applying disease-specific guidelines to their older patients with multiple conditions. To improve decision making, they need more data, alternative guidelines, approaches to reconciling their own and their patients' priorities, the support of their subspecialist colleagues, and an altered reimbursement system.

Stakeholder views of management and decision support tools to integrate climate change into Great Lakes Lake Whitefish management

USGS Publications Warehouse

Lynch, Abigail J.; Taylor, William W.; McCright, Aaron M.

2016-01-01

Decision support tools can aid decision making by systematically incorporating information, accounting for uncertainties, and facilitating evaluation between alternatives. Without user buy-in, however, decision support tools can fail to influence decision-making processes. We surveyed fishery researchers, managers, and fishers affiliated with the Lake Whitefish Coregonus clupeaformis fishery in the 1836 Treaty Waters of Lakes Huron, Michigan, and Superior to assess opinions of current and future management needs to identify barriers to, and opportunities for, developing a decision support tool based on Lake Whitefish recruitment projections with climate change. Approximately 64% of 39 respondents were satisfied with current management, and nearly 85% agreed that science was well integrated into management programs. Though decision support tools can facilitate science integration into management, respondents suggest that they face significant implementation barriers, including lack of political will to change management and perceived uncertainty in decision support outputs. Recommendations from this survey can inform development of decision support tools for fishery management in the Great Lakes and other regions.

Characterizing uncertain sea-level rise projections to support investment decisions.

PubMed

Sriver, Ryan L; Lempert, Robert J; Wikman-Svahn, Per; Keller, Klaus

2018-01-01

Many institutions worldwide are considering how to include uncertainty about future changes in sea-levels and storm surges into their investment decisions regarding large capital infrastructures. Here we examine how to characterize deeply uncertain climate change projections to support such decisions using Robust Decision Making analysis. We address questions regarding how to confront the potential for future changes in low probability but large impact flooding events due to changes in sea-levels and storm surges. Such extreme events can affect investments in infrastructure but have proved difficult to consider in such decisions because of the deep uncertainty surrounding them. This study utilizes Robust Decision Making methods to address two questions applied to investment decisions at the Port of Los Angeles: (1) Under what future conditions would a Port of Los Angeles decision to harden its facilities against extreme flood scenarios at the next upgrade pass a cost-benefit test, and (2) Do sea-level rise projections and other information suggest such conditions are sufficiently likely to justify such an investment? We also compare and contrast the Robust Decision Making methods with a full probabilistic analysis. These two analysis frameworks result in similar investment recommendations for different idealized future sea-level projections, but provide different information to decision makers and envision different types of engagement with stakeholders. In particular, the full probabilistic analysis begins by aggregating the best scientific information into a single set of joint probability distributions, while the Robust Decision Making analysis identifies scenarios where a decision to invest in near-term response to extreme sea-level rise passes a cost-benefit test, and then assembles scientific information of differing levels of confidence to help decision makers judge whether or not these scenarios are sufficiently likely to justify making such investments. Results highlight the highly-localized and context dependent nature of applying Robust Decision Making methods to inform investment decisions.

Characterizing uncertain sea-level rise projections to support investment decisions

PubMed Central

Lempert, Robert J.; Wikman-Svahn, Per; Keller, Klaus

2018-01-01

Many institutions worldwide are considering how to include uncertainty about future changes in sea-levels and storm surges into their investment decisions regarding large capital infrastructures. Here we examine how to characterize deeply uncertain climate change projections to support such decisions using Robust Decision Making analysis. We address questions regarding how to confront the potential for future changes in low probability but large impact flooding events due to changes in sea-levels and storm surges. Such extreme events can affect investments in infrastructure but have proved difficult to consider in such decisions because of the deep uncertainty surrounding them. This study utilizes Robust Decision Making methods to address two questions applied to investment decisions at the Port of Los Angeles: (1) Under what future conditions would a Port of Los Angeles decision to harden its facilities against extreme flood scenarios at the next upgrade pass a cost-benefit test, and (2) Do sea-level rise projections and other information suggest such conditions are sufficiently likely to justify such an investment? We also compare and contrast the Robust Decision Making methods with a full probabilistic analysis. These two analysis frameworks result in similar investment recommendations for different idealized future sea-level projections, but provide different information to decision makers and envision different types of engagement with stakeholders. In particular, the full probabilistic analysis begins by aggregating the best scientific information into a single set of joint probability distributions, while the Robust Decision Making analysis identifies scenarios where a decision to invest in near-term response to extreme sea-level rise passes a cost-benefit test, and then assembles scientific information of differing levels of confidence to help decision makers judge whether or not these scenarios are sufficiently likely to justify making such investments. Results highlight the highly-localized and context dependent nature of applying Robust Decision Making methods to inform investment decisions. PMID:29414978

From products to processes: Academic events to foster interdisciplinary and iterative dialogue in a changing climate

NASA Astrophysics Data System (ADS)

Addor, Nans; Ewen, Tracy; Johnson, Leigh; Ćöltekin, Arzu; Derungs, Curdin; Muccione, Veruska

2015-08-01

In the context of climate change, both climate researchers and decision makers deal with uncertainties, but these uncertainties differ in fundamental ways. They stem from different sources, cover different temporal and spatial scales, might or might not be reducible or quantifiable, and are generally difficult to characterize and communicate. Hence, a mutual understanding between current and future climate researchers and decision makers must evolve for adaptation strategies and planning to progress. Iterative two-way dialogue can help to improve the decision making process by bridging current top-down and bottom-up approaches. One way to cultivate such interactions is by providing venues for these actors to interact and exchange on the uncertainties they face. We use a workshop-seminar series involving academic researchers, students, and decision makers as an opportunity to put this idea into practice and evaluate it. Seminars, case studies, and a round table allowed participants to reflect upon and experiment with uncertainties. An opinion survey conducted before and after the workshop-seminar series allowed us to qualitatively evaluate its influence on the participants. We find that the event stimulated new perspectives on research products and communication processes, and we suggest that similar events may ultimately contribute to the midterm goal of improving support for decision making in a changing climate. Therefore, we recommend integrating bridging events into university curriculum to foster interdisciplinary and iterative dialogue among researchers, decision makers, and students.

Adaptive resource management and the value of information

USGS Publications Warehouse

Williams, Byron K.; Eaton, Mitchell J.; Breininger, David R.

2011-01-01

The value of information is a general and broadly applicable concept that has been used for several decades to aid in making decisions in the face of uncertainty. Yet there are relatively few examples of its use in ecology and natural resources management, and almost none that are framed in terms of the future impacts of management decisions. In this paper we discuss the value of information in a context of adaptive management, in which actions are taken sequentially over a timeframe and both future resource conditions and residual uncertainties about resource responses are taken into account. Our objective is to derive the value of reducing or eliminating uncertainty in adaptive decision making. We describe several measures of the value of information, with each based on management objectives that are appropriate for adaptive management. We highlight some mathematical properties of these measures, discuss their geometries, and illustrate them with an example in natural resources management. Accounting for the value of information can help to inform decisions about whether and how much to monitor resource conditions through time.

Adaptive resource management and the value of information

USGS Publications Warehouse

Williams, B.K.; Eaton, M.J.; Breininger, D.R.

2011-01-01

The value of information is a general and broadly applicable concept that has been used for several decades to aid in making decisions in the face of uncertainty. Yet there are relatively few examples of its use in ecology and natural resources management, and almost none that are framed in terms of the future impacts of management decisions. In this paper we discuss the value of information in a context of adaptive management, in which actions are taken sequentially over a timeframe and both future resource conditions and residual uncertainties about resource responses are taken into account. Our objective is to derive the value of reducing or eliminating uncertainty in adaptive decision making. We describe several measures of the value of information, with each based on management objectives that are appropriate for adaptive management. We highlight some mathematical properties of these measures, discuss their geometries, and illustrate them with an example in natural resources management. Accounting for the value of information can help to inform decisions about whether and how much to monitor resource conditions through time. ?? 2011.

Bayesian decision analysis as a tool for defining monitoring needs in the field of effects of CSOs on receiving waters.

PubMed

Korving, H; Clemens, F

2002-01-01

In recent years, decision analysis has become an important technique in many disciplines. It provides a methodology for rational decision-making allowing for uncertainties in the outcome of several possible actions to be undertaken. An example in urban drainage is the situation in which an engineer has to decide upon a major reconstruction of a system in order to prevent pollution of receiving waters due to CSOs. This paper describes the possibilities of Bayesian decision-making in urban drainage. In particular, the utility of monitoring prior to deciding on the reconstruction of a sewer system to reduce CSO emissions is studied. Our concern is with deciding whether a price should be paid for new information and which source of information is the best choice given the expected uncertainties in the outcome. The influence of specific uncertainties (sewer system data and model parameters) on the probability of CSO volumes is shown to be significant. Using Bayes' rule, to combine prior impressions with new observations, reduces the risks linked with the planning of sewer system reconstructions.

Enhancing emotion-based learning in decision-making under uncertainty.

PubMed

Alarcón, David; Amián, Josué G; Sánchez-Medina, José A

2015-01-01

The Iowa Gambling Task (IGT) is widely used to study decision-making differences between several clinical and healthy populations. Unlike the healthy participants, clinical participants have difficulty choosing between advantageous options, which yield long-term benefits, and disadvantageous options, which give high immediate rewards but lead to negative profits. However, recent studies have found that healthy participants avoid the options with a higher frequency of losses regardless of whether or not they are profitable in the long run. The aim of this study was to control for the confounding effect of the frequency of losses between options to improve the performance of healthy participants on the IGT. Eighty healthy participants were randomly assigned to the original IGT or a modified version of the IGT that diminished the gap in the frequency of losses between options. The participants who used the modified IGT version learned to make better decisions based on long-term profit, as indicated by an earlier ability to discriminate good from bad options, and took less time to make their choices. This research represents an advance in the study of decision making under uncertainty by showing that emotion-based learning is improved by controlling for the loss-frequency bias effect.

Precipitation Variability and Projection Uncertainties in Climate Change Adaptation: Go Local!

EPA Science Inventory

Presentations agenda includes: Regional and local climate change effects: The relevance; Variability and uncertainty in decision- making and adaptation approaches; Adaptation attributes for the U.S. Southwest: Water availability, storage capacity, and related; EPA research...

Assessing and reducing hydrogeologic model uncertainty

USDA-ARS?s Scientific Manuscript database

NRC is sponsoring research that couples model abstraction techniques with model uncertainty assessment methods. Insights and information from this program will be useful in decision making by NRC staff, licensees and stakeholders in their assessment of subsurface radionuclide transport. All analytic...

Dynamic fluctuations in dopamine efflux in the prefrontal cortex and nucleus accumbens during risk-based decision making.

PubMed

St Onge, Jennifer R; Ahn, Soyon; Phillips, Anthony G; Floresco, Stan B

2012-11-21

Mesocorticolimbic dopamine (DA) has been implicated in cost/benefit decision making about risks and rewards. The prefrontal cortex (PFC) and nucleus accumbens (NAc) are two DA terminal regions that contribute to decision making in distinct manners. However, how fluctuations of tonic DA levels may relate to different aspects of decision making remains to be determined. The present study measured DA efflux in the PFC and NAc with microdialysis in well trained rats performing a probabilistic discounting task. Selection of a small/certain option always delivered one pellet, whereas another, large/risky option yielded four pellets, with probabilities that decreased (100-12.5%) or increased (12.5-100%) across four blocks of trials. Yoked-reward groups were also included to control for reward delivery. PFC DA efflux during decision making decreased or increased over a session, corresponding to changes in large/risky reward probabilities. Similar profiles were observed from yoked-rewarded rats, suggesting that fluctuations in PFC DA reflect changes in the relative rate of reward received. NAc DA efflux also showed decreasing/increasing trends over the session during both tasks. However, DA efflux was higher during decision making on free- versus forced-choice trials and during periods of greater reward uncertainty. Moreover, changes in NAc DA closely tracked shifts in choice biases. These data reveal dynamic and dissociable fluctuations in PFC and NAc DA transmission associated with different aspects of risk-based decision making. PFC DA may signal changes in reward availability that facilitates modification of choice biases, whereas NAc DA encodes integrated signals about reward rates, uncertainty, and choice, reflecting implementation of decision policies.

A Qualitative Exploration of Clinician Views and Experiences of Treatment Decision-Making in Bipolar II Disorder.

PubMed

Fisher, Alana; Manicavasagar, Vijaya; Sharpe, Louise; Laidsaar-Powell, Rebekah; Juraskova, Ilona

2017-11-01

This study qualitatively explored clinicians' views and experiences of treatment decision-making in BPII. Semi-structured interviews were conducted with 20 practising clinicians (n = 10 clinical psychologists, n = 6 GPs, n = 4 psychiatrists) with experience in treating adult outpatients with BPII. Interviews were audiotaped, transcribed verbatim and thematically analysed using framework methods. Professional experience, and preferences for patient involvement in decision-making were also assessed. Qualitative analyses yielded four inter-related themes: (1) (non-)acceptance of diagnosis and treatment; (2) types of decisions; (3) treatment uncertainty and balancing act; and (4) decision-making in consultations. Clinician preferences for treatment, professional experience, and self-reported preferences for patient/family involvement seemed to influence decision-making. This study is the first to explore clinician views and experiences of treatment decision-making in BPII. Findings demonstrate how clinician-related factors may shape treatment decision-making, and suggest potential problems such as patient perceptions of lower-than-preferred involvement.

Robust climate policies under uncertainty: a comparison of robust decision making and info-gap methods.

PubMed

Hall, Jim W; Lempert, Robert J; Keller, Klaus; Hackbarth, Andrew; Mijere, Christophe; McInerney, David J

2012-10-01

This study compares two widely used approaches for robustness analysis of decision problems: the info-gap method originally developed by Ben-Haim and the robust decision making (RDM) approach originally developed by Lempert, Popper, and Bankes. The study uses each approach to evaluate alternative paths for climate-altering greenhouse gas emissions given the potential for nonlinear threshold responses in the climate system, significant uncertainty about such a threshold response and a variety of other key parameters, as well as the ability to learn about any threshold responses over time. Info-gap and RDM share many similarities. Both represent uncertainty as sets of multiple plausible futures, and both seek to identify robust strategies whose performance is insensitive to uncertainties. Yet they also exhibit important differences, as they arrange their analyses in different orders, treat losses and gains in different ways, and take different approaches to imprecise probabilistic information. The study finds that the two approaches reach similar but not identical policy recommendations and that their differing attributes raise important questions about their appropriate roles in decision support applications. The comparison not only improves understanding of these specific methods, it also suggests some broader insights into robustness approaches and a framework for comparing them. © 2012 RAND Corporation.

Development of an integrated model for energy systems planning and carbon dioxide mitigation under uncertainty - Tradeoffs between two-level decision makers.

PubMed

Jin, S W; Li, Y P; Xu, L P

2018-07-01

A bi-level fuzzy programming (BFLP) method was developed for energy systems planning (ESP) and carbon dioxide (CO 2 ) mitigation under uncertainty. BFLP could handle fuzzy information and leader-follower problem in decision-making processes. It could also address the tradeoffs among different decision makers in two decision-making levels through prioritizing the most important goal. Then, a BFLP-ESP model was formulated for planning energy system of Beijing, in which the upper-level objective is to minimize CO 2 emission and the lower-level objective is to minimize the system cost. Results provided a range of decision alternatives that corresponded to a tradeoff between system optimality and reliability under uncertainty. Compared to the single-level model with a target to minimize system cost, the amounts of pollutant/CO 2 emissions from BFLP-ESP were reduced since the study system would prefer more clean energies (i.e. natural gas, LPG and electricity) to replace coal fuel. Decision alternatives from BFLP were more beneficial for supporting Beijing to adjust its energy mix and enact its emission-abatement policy. Results also revealed that the low-carbon policy for power plants (e.g., shutting down all coal-fired power plants) could lead to a potentially increment of imported energy for Beijing, which would increase the risk of energy shortage. The findings could help decision makers analyze the interactions between different stakeholders in ESP and provide useful information for policy design under uncertainty. Copyright © 2018 Elsevier Inc. All rights reserved.

Climate change and European forests: what do we know, what are the uncertainties, and what are the implications for forest management?

PubMed

Lindner, Marcus; Fitzgerald, Joanne B; Zimmermann, Niklaus E; Reyer, Christopher; Delzon, Sylvain; van der Maaten, Ernst; Schelhaas, Mart-Jan; Lasch, Petra; Eggers, Jeannette; van der Maaten-Theunissen, Marieke; Suckow, Felicitas; Psomas, Achilleas; Poulter, Benjamin; Hanewinkel, Marc

2014-12-15

The knowledge about potential climate change impacts on forests is continuously expanding and some changes in growth, drought induced mortality and species distribution have been observed. However despite a significant body of research, a knowledge and communication gap exists between scientists and non-scientists as to how climate change impact scenarios can be interpreted and what they imply for European forests. It is still challenging to advise forest decision makers on how best to plan for climate change as many uncertainties and unknowns remain and it is difficult to communicate these to practitioners and other decision makers while retaining emphasis on the importance of planning for adaptation. In this paper, recent developments in climate change observations and projections, observed and projected impacts on European forests and the associated uncertainties are reviewed and synthesised with a view to understanding the implications for forest management. Current impact assessments with simulation models contain several simplifications, which explain the discrepancy between results of many simulation studies and the rapidly increasing body of evidence about already observed changes in forest productivity and species distribution. In simulation models uncertainties tend to cascade onto one another; from estimating what future societies will be like and general circulation models (GCMs) at the global level, down to forest models and forest management at the local level. Individual climate change impact studies should not be uncritically used for decision-making without reflection on possible shortcomings in system understanding, model accuracy and other assumptions made. It is important for decision makers in forest management to realise that they have to take long-lasting management decisions while uncertainty about climate change impacts are still large. We discuss how to communicate about uncertainty - which is imperative for decision making - without diluting the overall message. Considering the range of possible trends and uncertainties in adaptive forest management requires expert knowledge and enhanced efforts for providing science-based decision support. Copyright © 2014 Elsevier Ltd. All rights reserved.

Physicians' anxiety due to uncertainty and use of race in medical decision making.

PubMed

Cunningham, Brooke A; Bonham, Vence L; Sellers, Sherrill L; Yeh, Hsin-Chieh; Cooper, Lisa A

2014-08-01

The explicit use of race in medical decision making is contested. Researchers have hypothesized that physicians use race in care when they are uncertain. The aim of this study was to investigate whether physician anxiety due to uncertainty (ADU) is associated with a higher propensity to use race in medical decision making. This study included a national cross-sectional survey of general internists. A national sample of 1738 clinically active general internists drawn from the SK&A physician database were included in the study. ADU is a 5-item measure of emotional reactions to clinical uncertainty. Bonham and Sellers Racial Attributes in Clinical Evaluation (RACE) scale includes 7 items that measure self-reported use of race in medical decision making. We used bivariate regression to test for associations between physician characteristics, ADU, and RACE. Multivariate linear regression was performed to test for associations between ADU and RACE while adjusting for potential confounders. The mean score on ADU was 19.9 (SD=5.6). Mean score on RACE was 13.5 (SD=5.6). After adjusting for physician demographics, physicians with higher levels of ADU scored higher on RACE (+β=0.08 in RACE, P=0.04, for each 1-point increase in ADU), as did physicians who understood "race" to mean biological or genetic ancestral, rather than sociocultural, group. Physicians who graduated from a US medical school, completed fellowship, and had more white patients scored lower on RACE. This study demonstrates positive associations between physicians' ADU, meanings attributed to race, and self-reported use of race in medical decision making. Future research should examine the potential impact of these associations on patient outcomes and health care disparities.

Decision Making in Paediatric Cardiology. Are We Prone to Heuristics, Biases and Traps?

PubMed

Ryan, Aedin; Duignan, Sophie; Kenny, Damien; McMahon, Colin J

2018-01-01

Hidden traps in decision making have been long recognised in the behavioural economics community. Yet we spend very limited, if any time, analysing our decision-making processes in medicine and paediatric cardiology. Systems 1 and 2 thought processes differentiate between rapid emotional thoughts and slow deliberate rational thoughts. For fairly clear cut medical decisions, in-depth analysis may not be needed, but in our field of paediatric cardiology it is not uncommon for challenging cases and occasionally 'simple' cases to generate significant debate and uncertainty as to the best decision. Although morbidity and mortality meetings frequently highlight poor outcomes for our patients, they often neglect to analyse the process of thought which underlined those decisions taken. This article attempts to review commonly acknowledged traps in decision making in the behavioural economics world to ascertain whether these heuristics translate to decision making in the paediatric cardiology environment. We also discuss potential individual and collective solutions to pitfalls in decision making.

Effects of risk attitudes on extended attack fire management decisionmaking

Treesearch

Donald G. MacGregor; Armando González-Cabán

2009-01-01

Fire management inherently involves the assessment and management of risk, and decision making under uncertainty. Although organizational standards and guides are an important determinant of how decision problems are structured and framed, decision makers may view risk-based decisions from a perspective that is unique to their background and experience. Previous...

Studying the effect of clinical uncertainty on physicians' decision-making using ILIAD.

PubMed

Anderson, J D; Jay, S J; Weng, H C; Anderson, M M

1995-01-01

The influence of uncertainty on physicians' practice behavior is not well understood. In this research, ILIAD, a diagnostic expert system, has been used to study physicians' responses to uncertainty and how their responses affected clinical performance. The simulation mode of ILIAD was used to standardize the presentation and scoring of two cases to 46 residents in emergency medicine, internal medicine, family practice and transitional medicine at Methodist Hospital of Indiana. A questionnaire was used to collect additional data on how physicians respond to clinical uncertainty. A structural equation model was developed, estimated, and tested. The results indicate that stress that physicians experience in dealing with clinical uncertainty has a negative effect on their clinical performance. Moreover, the way that physicians respond to uncertainty has positive and negative effects on their performance. Open discussions with patients about clinical decisions and the use of practice guidelines improves performance. However, when the physician's clinical decisions are influenced by patient demands or their peers, their performance scores decline.

How to pose the question matters: Behavioural Economics concepts in decision making on the basis of ensemble forecasts

NASA Astrophysics Data System (ADS)

Alfonso, Leonardo; van Andel, Schalk Jan

2014-05-01

Part of recent research in ensemble and probabilistic hydro-meteorological forecasting analyses which probabilistic information is required by decision makers and how it can be most effectively visualised. This work, in addition, analyses if decision making in flood early warning is also influenced by the way the decision question is posed. For this purpose, the decision-making game "Do probabilistic forecasts lead to better decisions?", which Ramos et al (2012) conducted at the EGU General Assembly 2012 in the city of Vienna, has been repeated with a small group and expanded. In that game decision makers had to decide whether or not to open a flood release gate, on the basis of flood forecasts, with and without uncertainty information. A conclusion of that game was that, in the absence of uncertainty information, decision makers are compelled towards a more risk-averse attitude. In order to explore to what extent the answers were driven by the way the questions were framed, in addition to the original experiment, a second variant was introduced where participants were asked to choose between a sure value (for either loosing or winning with a giving probability) and a gamble. This set-up is based on Kahneman and Tversky (1979). Results indicate that the way how the questions are posed may play an important role in decision making and that Prospect Theory provides promising concepts to further understand how this works.

Uncertainties in hydrological extremes projections and its effects on decision-making processes in an Amazonian sub-basin.

NASA Astrophysics Data System (ADS)

Andres Rodriguez, Daniel; Garofolo, Lucas; Lazaro Siqueira Junior, Jose

2013-04-01

Uncertainties in Climate Change projections are affected by irreducible uncertainties due to knowledge's limitations, chaotic nature of climate system and human decision-making process. Such uncertainties affect the impact studies, complicating the decision-making process aimed at mitigation and adaptation. However, these uncertainties allow the possibility to develop exploratory analyses on system's vulnerability to different sceneries. Through these kinds of analyses it is possible to identify critical issues, which must be deeper studied. For this study we used several future's projections from General Circulation Models to feed a Hydrological Model, applied to the Amazonian sub-basin of Ji-Paraná. Hydrological Model integrations are performed for present historical time (1970-1990) and for future period (2010-2100). Extreme values analyses are performed to each simulated time series and results are compared with extremes events in present time. A simple approach to identify potential vulnerabilities consists of evaluating the hydrologic system response to climate variability and extreme events observed in the past, comparing them with the conditions projected for the future. Thus it is possible to identify critical issues that need attention and more detailed studies. For the goal of this work, we used socio-economic data from Brazilian Institute of Geography and Statistics, the Operator of the National Electric System, the Brazilian National Water Agency and scientific and press published information. This information is used to characterize impacts associated to extremes hydrological events in the basin during the present historical time and to evaluate potential impacts in the future face to the different hydrological projections. Results show inter-model variability results in a broad dispersion on projected extreme's values. The impact of such dispersion is differentiated for different aspects of socio-economic and natural systems and must be carefully addressed in order to help in decision-making processes.

Incorporating uncertainty into medical decision making: an approach to unexpected test results.

PubMed

Bianchi, Matt T; Alexander, Brian M; Cash, Sydney S

2009-01-01

The utility of diagnostic tests derives from the ability to translate the population concepts of sensitivity and specificity into information that will be useful for the individual patient: the predictive value of the result. As the array of available diagnostic testing broadens, there is a temptation to de-emphasize history and physical findings and defer to the objective rigor of technology. However, diagnostic test interpretation is not always straightforward. One significant barrier to routine use of probability-based test interpretation is the uncertainty inherent in pretest probability estimation, the critical first step of Bayesian reasoning. The context in which this uncertainty presents the greatest challenge is when test results oppose clinical judgment. It is this situation when decision support would be most helpful. The authors propose a simple graphical approach that incorporates uncertainty in pretest probability and has specific application to the interpretation of unexpected results. This method quantitatively demonstrates how uncertainty in disease probability may be amplified when test results are unexpected (opposing clinical judgment), even for tests with high sensitivity and specificity. The authors provide a simple nomogram for determining whether an unexpected test result suggests that one should "switch diagnostic sides.'' This graphical framework overcomes the limitation of pretest probability uncertainty in Bayesian analysis and guides decision making when it is most challenging: interpretation of unexpected test results.

Outbreak Column 16: Cognitive errors in outbreak decision making.

PubMed

Curran, Evonne T

2015-01-01

During outbreaks, decisions must be made without all the required information. People, including infection prevention and control teams (IPCTs), who have to make decisions during uncertainty use heuristics to fill the missing data gaps. Heuristics are mental model short cuts that by-and-large enable us to make good decisions quickly. However, these heuristics contain biases and effects that at times lead to cognitive (thinking) errors. These cognitive errors are not made to deliberately misrepresent any given situation; we are subject to heuristic biases when we are trying to perform optimally. The science of decision making is large; there are over 100 different biases recognised and described. Outbreak Column 16 discusses and relates these heuristics and biases to decision making during outbreak prevention, preparedness and management. Insights as to how we might recognise and avoid them are offered.

An fMRI Examination of Developmental Differences in the Neural Correlates of Uncertainty and Decision-Making

ERIC Educational Resources Information Center

Krain, Amy L.; Hefton, Sara; Pine, Daniel S.; Ernst, Monique; Castellanos, F. Xavier; Klein, Rachel G.; Milham, Michael P.

2006-01-01

Background: Maturation of prefrontal circuits during adolescence contributes to the development of cognitive processes such as decision-making. Recent theories suggest that these neural changes also play a role in the shift from generalized anxiety disorder (GAD) to depression that often occurs during this developmental period. Cognitive models of…

Decision Making under Uncertainty: The Case of Adoption vs. Foster Care.

ERIC Educational Resources Information Center

Ambrosino, Robert J.

This report provides a detailed description of Decision Analysis, a program designed to help social services administrators make informed judgments about the impact of implementing various program alternatives which compete for funding. A familiar example, whether to place a child in long term foster care or a permanent adoptive home is used to…

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.

Risk-based flood protection planning under climate change and modeling uncertainty: a pre-alpine case study

NASA Astrophysics Data System (ADS)

Dittes, Beatrice; Kaiser, Maria; Špačková, Olga; Rieger, Wolfgang; Disse, Markus; Straub, Daniel

2018-05-01

Planning authorities are faced with a range of questions when planning flood protection measures: is the existing protection adequate for current and future demands or should it be extended? How will flood patterns change in the future? How should the uncertainty pertaining to this influence the planning decision, e.g., for delaying planning or including a safety margin? Is it sufficient to follow a protection criterion (e.g., to protect from the 100-year flood) or should the planning be conducted in a risk-based way? How important is it for flood protection planning to accurately estimate flood frequency (changes), costs and damage? These are questions that we address for a medium-sized pre-alpine catchment in southern Germany, using a sequential Bayesian decision making framework that quantitatively addresses the full spectrum of uncertainty. We evaluate different flood protection systems considered by local agencies in a test study catchment. Despite large uncertainties in damage, cost and climate, the recommendation is robust for the most conservative approach. This demonstrates the feasibility of making robust decisions under large uncertainty. Furthermore, by comparison to a previous study, it highlights the benefits of risk-based planning over the planning of flood protection to a prescribed return period.

Multi-objective decision-making under uncertainty: Fuzzy logic methods

NASA Technical Reports Server (NTRS)

Hardy, Terry L.

1995-01-01

Fuzzy logic allows for quantitative representation of vague or fuzzy objectives, and therefore is well-suited for multi-objective decision-making. This paper presents methods employing fuzzy logic concepts to assist in the decision-making process. In addition, this paper describes software developed at NASA Lewis Research Center for assisting in the decision-making process. Two diverse examples are used to illustrate the use of fuzzy logic in choosing an alternative among many options and objectives. One example is the selection of a lunar lander ascent propulsion system, and the other example is the selection of an aeration system for improving the water quality of the Cuyahoga River in Cleveland, Ohio. The fuzzy logic techniques provided here are powerful tools which complement existing approaches, and therefore should be considered in future decision-making activities.

Constraint reasoning in deep biomedical models.

PubMed

Cruz, Jorge; Barahona, Pedro

2005-05-01

Deep biomedical models are often expressed by means of differential equations. Despite their expressive power, they are difficult to reason about and make decisions, given their non-linearity and the important effects that the uncertainty on data may cause. The objective of this work is to propose a constraint reasoning framework to support safe decisions based on deep biomedical models. The methods used in our approach include the generic constraint propagation techniques for reducing the bounds of uncertainty of the numerical variables complemented with new constraint reasoning techniques that we developed to handle differential equations. The results of our approach are illustrated in biomedical models for the diagnosis of diabetes, tuning of drug design and epidemiology where it was a valuable decision-supporting tool notwithstanding the uncertainty on data. The main conclusion that follows from the results is that, in biomedical decision support, constraint reasoning may be a worthwhile alternative to traditional simulation methods, especially when safe decisions are required.

Incorporating uncertainty in watershed management decision-making: A mercury TMDL case study

USGS Publications Warehouse

Labiosa, W.; Leckie, J.; Shachter, R.; Freyberg, D.; Rytuba, J.; ,

2005-01-01

Water quality impairment due to high mercury fish tissue concentrations and high mercury aqueous concentrations is a widespread problem in several sub-watersheds that are major sources of mercury to the San Francisco Bay. Several mercury Total Maximum Daily Load regulations are currently being developed to address this problem. Decisions about control strategies are being made despite very large uncertainties about current mercury loading behavior, relationships between total mercury loading and methyl mercury formation, and relationships between potential controls and mercury fish tissue levels. To deal with the issues of very large uncertainties, data limitations, knowledge gaps, and very limited State agency resources, this work proposes a decision analytical alternative for mercury TMDL decision support. The proposed probabilistic decision model is Bayesian in nature and is fully compatible with a "learning while doing" adaptive management approach. Strategy evaluation, sensitivity analysis, and information collection prioritization are examples of analyses that can be performed using this approach.

Leadership of risk decision making in a complex, technology organization: The deliberative decision making model

NASA Astrophysics Data System (ADS)

Flaming, Susan C.

2007-12-01

The continuing saga of satellite technology development is as much a story of successful risk management as of innovative engineering. How do program leaders on complex, technology projects manage high stakes risks that threaten business success and satellite performance? This grounded theory study of risk decision making portrays decision leadership practices at one communication satellite company. Integrated product team (IPT) leaders of multi-million dollar programs were interviewed and observed to develop an extensive description of the leadership skills required to navigate organizational influences and drive challenging risk decisions to closure. Based on the study's findings the researcher proposes a new decision making model, Deliberative Decision Making, to describe the program leaders' cognitive and organizational leadership practices. This Deliberative Model extends the insights of prominent decision making models including the rational (or classical) and the naturalistic and qualifies claims made by bounded rationality theory. The Deliberative Model describes how leaders proactively engage resources to play a variety of decision leadership roles. The Model incorporates six distinct types of leadership decision activities, undertaken in varying sequence based on the challenges posed by specific risks. Novel features of the Deliberative Decision Model include: an inventory of leadership methods for managing task challenges, potential stakeholder bias and debates; four types of leadership meta-decisions that guide decision processes, and aligned organizational culture. Both supporting and constraining organizational influences were observed as leaders managed major risks, requiring active leadership on the most difficult decisions. Although the company's engineering culture emphasized the importance of data-based decisions, the uncertainties intrinsic to satellite risks required expert engineering judgment to be exercised throughout. An investigation into the co-variation of decision methods with uncertainty suggests that perceived risk severity may serve as a robust indicator for choices about decision practices. The Deliberative Decision processes incorporate multiple organizational and cultural controls as cross-checks to mitigate potential parochial bias of individuals, stakeholder groups, or leaders. Overall the Deliberative Decision framework describes how expert leadership practices, supportive organizational systems along with aligned cultural values and behavioral norms help leaders drive high stakes risk decisions to closure in this complex, advanced-technology setting.

Collaborative decision-analytic framework to maximize resilience of tidal marshes to climate change

USGS Publications Warehouse

Thorne, Karen M.; Mattsson, Brady J.; Takekawa, John Y.; Cummings, Jonathan; Crouse, Debby; Block, Giselle; Bloom, Valary; Gerhart, Matt; Goldbeck, Steve; Huning, Beth; Sloop, Christina; Stewart, Mendel; Taylor, Karen; Valoppi, Laura

2015-01-01

Decision makers that are responsible for stewardship of natural resources face many challenges, which are complicated by uncertainty about impacts from climate change, expanding human development, and intensifying land uses. A systematic process for evaluating the social and ecological risks, trade-offs, and cobenefits associated with future changes is critical to maximize resilience and conserve ecosystem services. This is particularly true in coastal areas where human populations and landscape conversion are increasing, and where intensifying storms and sea-level rise pose unprecedented threats to coastal ecosystems. We applied collaborative decision analysis with a diverse team of stakeholders who preserve, manage, or restore tidal marshes across the San Francisco Bay estuary, California, USA, as a case study. Specifically, we followed a structured decision-making approach, and we using expert judgment developed alternative management strategies to increase the capacity and adaptability to manage tidal marsh resilience while considering uncertainties through 2050. Because sea-level rise projections are relatively confident to 2050, we focused on uncertainties regarding intensity and frequency of storms and funding. Elicitation methods allowed us to make predictions in the absence of fully compatible models and to assess short- and long-term trade-offs. Specifically we addressed two questions. (1) Can collaborative decision analysis lead to consensus among a diverse set of decision makers responsible for environmental stewardship and faced with uncertainties about climate change, funding, and stakeholder values? (2) What is an optimal strategy for the conservation of tidal marshes, and what strategy is robust to the aforementioned uncertainties? We found that when taking this approach, consensus was reached among the stakeholders about the best management strategies to maintain tidal marsh integrity. A Bayesian decision network revealed that a strategy considering sea-level rise and storms explicitly in wetland restoration planning and designs was optimal, and it was robust to uncertainties about management effectiveness and budgets. We found that strategies that avoided explicitly accounting for future climate change had the lowest expected performance based on input from the team. Our decision-analytic framework is sufficiently general to offer an adaptable template, which can be modified for use in other areas that include a diverse and engaged stakeholder group.

Bridging the gap between science and decision making.

PubMed

von Winterfeldt, Detlof

2013-08-20

All decisions, whether they are personal, public, or business-related, are based on the decision maker's beliefs and values. Science can and should help decision makers by shaping their beliefs. Unfortunately, science is not easily accessible to decision makers, and scientists often do not understand decision makers' information needs. This article presents a framework for bridging the gap between science and decision making and illustrates it with two examples. The first example is a personal health decision. It shows how a formal representation of the beliefs and values can reflect scientific inputs by a physician to combine with the values held by the decision maker to inform a medical choice. The second example is a public policy decision about managing a potential environmental hazard. It illustrates how controversial beliefs can be reflected as uncertainties and informed by science to make better decisions. Both examples use decision analysis to bridge science and decisions. The conclusions suggest that this can be a helpful process that requires skills in both science and decision making.

Bridging the gap between science and decision making

PubMed Central

von Winterfeldt, Detlof

2013-01-01

All decisions, whether they are personal, public, or business-related, are based on the decision maker’s beliefs and values. Science can and should help decision makers by shaping their beliefs. Unfortunately, science is not easily accessible to decision makers, and scientists often do not understand decision makers’ information needs. This article presents a framework for bridging the gap between science and decision making and illustrates it with two examples. The first example is a personal health decision. It shows how a formal representation of the beliefs and values can reflect scientific inputs by a physician to combine with the values held by the decision maker to inform a medical choice. The second example is a public policy decision about managing a potential environmental hazard. It illustrates how controversial beliefs can be reflected as uncertainties and informed by science to make better decisions. Both examples use decision analysis to bridge science and decisions. The conclusions suggest that this can be a helpful process that requires skills in both science and decision making. PMID:23940310

[Treatment Decision-Making Process of Cancer Patients].

PubMed

Lee, Shiu-Yu C Katie

2016-10-01

The decision-making process that is used by cancer patients to determine their treatment has become more multi-foci, difficult and complicated in recent years. This has in part been attributed to the increasing incidence rate of cancer in Taiwan and the rapid development of medical technologies and treatment modalities. Oncology nurses must assist patients and family to make informed and value-based treatment decisions. Decision-making is an information process that involves appraising one's own expectation and values based on his/her knowledge on cancer and treatment options. Because cancer treatment involves risks and uncertainties, and impacts quality of life, the treatment decision-making for cancer is often stressful, or even conflicting. This paper discusses the decision-making behaviors of cancer patients and the decisional conflict, participation, and informational needs that are involved in cancer treatment. The trend toward shared decision-making and decisional support will be also explored in order to facilitate the future development of appropriate clinical interventions and research.

Modeling uncertainty in producing natural gas from tight sands

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

Chermak, J.M.; Dahl, C.A.; Patrick, R.H

1995-12-31

Since accurate geologic, petroleum engineering, and economic information are essential ingredients in making profitable production decisions for natural gas, we combine these ingredients in a dynamic framework to model natural gas reservoir production decisions. We begin with the certainty case before proceeding to consider how uncertainty might be incorporated in the decision process. Our production model uses dynamic optimal control to combine economic information with geological constraints to develop optimal production decisions. To incorporate uncertainty into the model, we develop probability distributions on geologic properties for the population of tight gas sand wells and perform a Monte Carlo study tomore » select a sample of wells. Geological production factors, completion factors, and financial information are combined into the hybrid economic-petroleum reservoir engineering model to determine the optimal production profile, initial gas stock, and net present value (NPV) for an individual well. To model the probability of the production abandonment decision, the NPV data is converted to a binary dependent variable. A logit model is used to model this decision as a function of the above geological and economic data to give probability relationships. Additional ways to incorporate uncertainty into the decision process include confidence intervals and utility theory.« less

The cognitive processes underpinning clinical decision in triage assessment: a theoretical conundrum?

PubMed

Noon, Amy J

2014-01-01

High quality clinical decision-making (CDM) has been highlighted as a priority across the nursing profession. Triage nurses, in the Accident and Emergency (A&E) department, work in considerable levels of uncertainty and require essential skills including: critical thinking, evaluation and decision-making. The content of this paper aims to promote awareness of how triage nurses make judgements and decisions in emergency situations. By exploring relevant literature on clinical judgement and decision-making theory, this paper demonstrates the importance of high quality decision-making skills underpinning the triage nurse's role. Having an awareness of how judgements and decisions are made is argued as essential, in a time where traditional nurse boundaries and responsibilities are never more challenged. It is hoped that the paper not only raises this awareness in general but also, in particular, engages the triage nurse to look more critically at how they make their own decisions in their everyday practice. Copyright © 2013 Elsevier Ltd. All rights reserved.

How to deal with climate change uncertainty in the planning of engineering systems

NASA Astrophysics Data System (ADS)

Spackova, Olga; Dittes, Beatrice; Straub, Daniel

2016-04-01

The effect of extreme events such as floods on the infrastructure and built environment is associated with significant uncertainties: These include the uncertain effect of climate change, uncertainty on extreme event frequency estimation due to limited historic data and imperfect models, and, not least, uncertainty on future socio-economic developments, which determine the damage potential. One option for dealing with these uncertainties is the use of adaptable (flexible) infrastructure that can easily be adjusted in the future without excessive costs. The challenge is in quantifying the value of adaptability and in finding the optimal sequence of decision. Is it worth to build a (potentially more expensive) adaptable system that can be adjusted in the future depending on the future conditions? Or is it more cost-effective to make a conservative design without counting with the possible future changes to the system? What is the optimal timing of the decision to build/adjust the system? We develop a quantitative decision-support framework for evaluation of alternative infrastructure designs under uncertainties, which: • probabilistically models the uncertain future (trough a Bayesian approach) • includes the adaptability of the systems (the costs of future changes) • takes into account the fact that future decisions will be made under uncertainty as well (using pre-posterior decision analysis) • allows to identify the optimal capacity and optimal timing to build/adjust the infrastructure. Application of the decision framework will be demonstrated on an example of flood mitigation planning in Bavaria.

Negotiating end-of-life decision making: a comparison of Japanese and U.S. residents' approaches.

PubMed

Gabbay, Baback B; Matsumura, Shinji; Etzioni, Shiri; Asch, Steven M; Rosenfeld, Kenneth E; Shiojiri, Toshiaki; Balingit, Peter P; Lorenz, Karl A

2005-07-01

To compare Japanese and U.S. resident physicians' attitudes, clinical experiences, and emotional responses regarding making disclosures to patients facing incurable illnesses. From September 2003 to June 2004, the authors used a ten-item self-administered anonymous questionnaire in a cross-sectional survey of 103 internal medicine residents at two U.S. sites in Los Angeles, California, and 244 general medical practice residents at five Japanese sites in Central Honshu, Kyushu, Okinawa, Japan. The Japanese residents were more likely to favor including the family in disclosing diagnosis (95% versus 45%, p<.001) and prognosis (95% versus 51%, p<.001) of metastatic gastric cancer. Of residents who favored diagnostic or prognostic disclosure to both the patient and family, Japanese residents were more likely to prefer discussion with the family first. Trainees in Japan expressed greater uncertainty about ethical practices related to disclosure of diagnosis or prognosis. Many Japanese and U.S. residents indicated that they had deceived a patient at the request of a family (76% versus 18 %, p<.001), or provided nonbeneficial care (56% versus 72%, p<.05), and many expressed guilt about these behaviors. The residents' approaches to end-of-life decision making reflect known cultural preferences related to the role of patients and their families. Although Japanese trainees were more likely to endorse the role of the family, they expressed greater uncertainty about their approach. Difficulty and uncertainty in end-of-life decision making were common among both the Japanese and U.S. residents. Both groups would benefit from ethical training to negotiate diverse, changing norms regarding end-of-life decision making.

A Framework for Modeling Emerging Diseases to Inform Management

PubMed Central

Katz, Rachel A.; Richgels, Katherine L.D.; Walsh, Daniel P.; Grant, Evan H.C.

2017-01-01

The rapid emergence and reemergence of zoonotic diseases requires the ability to rapidly evaluate and implement optimal management decisions. Actions to control or mitigate the effects of emerging pathogens are commonly delayed because of uncertainty in the estimates and the predicted outcomes of the control tactics. The development of models that describe the best-known information regarding the disease system at the early stages of disease emergence is an essential step for optimal decision-making. Models can predict the potential effects of the pathogen, provide guidance for assessing the likelihood of success of different proposed management actions, quantify the uncertainty surrounding the choice of the optimal decision, and highlight critical areas for immediate research. We demonstrate how to develop models that can be used as a part of a decision-making framework to determine the likelihood of success of different management actions given current knowledge. PMID:27983501

A Framework for Modeling Emerging Diseases to Inform Management.

PubMed

Russell, Robin E; Katz, Rachel A; Richgels, Katherine L D; Walsh, Daniel P; Grant, Evan H C

2017-01-01

The rapid emergence and reemergence of zoonotic diseases requires the ability to rapidly evaluate and implement optimal management decisions. Actions to control or mitigate the effects of emerging pathogens are commonly delayed because of uncertainty in the estimates and the predicted outcomes of the control tactics. The development of models that describe the best-known information regarding the disease system at the early stages of disease emergence is an essential step for optimal decision-making. Models can predict the potential effects of the pathogen, provide guidance for assessing the likelihood of success of different proposed management actions, quantify the uncertainty surrounding the choice of the optimal decision, and highlight critical areas for immediate research. We demonstrate how to develop models that can be used as a part of a decision-making framework to determine the likelihood of success of different management actions given current knowledge.

A framework for modeling emerging diseases to inform management

USGS Publications Warehouse

Russell, Robin E.; Katz, Rachel A.; Richgels, Katherine L. D.; Walsh, Daniel P.; Grant, Evan H. Campbell

2017-01-01

The rapid emergence and reemergence of zoonotic diseases requires the ability to rapidly evaluate and implement optimal management decisions. Actions to control or mitigate the effects of emerging pathogens are commonly delayed because of uncertainty in the estimates and the predicted outcomes of the control tactics. The development of models that describe the best-known information regarding the disease system at the early stages of disease emergence is an essential step for optimal decision-making. Models can predict the potential effects of the pathogen, provide guidance for assessing the likelihood of success of different proposed management actions, quantify the uncertainty surrounding the choice of the optimal decision, and highlight critical areas for immediate research. We demonstrate how to develop models that can be used as a part of a decision-making framework to determine the likelihood of success of different management actions given current knowledge.

Valuing flexibilities in the design of urban water management systems.

PubMed

Deng, Yinghan; Cardin, Michel-Alexandre; Babovic, Vladan; Santhanakrishnan, Deepak; Schmitter, Petra; Meshgi, Ali

2013-12-15

Climate change and rapid urbanization requires decision-makers to develop a long-term forward assessment on sustainable urban water management projects. This is further complicated by the difficulties of assessing sustainable designs and various design scenarios from an economic standpoint. A conventional valuation approach for urban water management projects, like Discounted Cash Flow (DCF) analysis, fails to incorporate uncertainties, such as amount of rainfall, unit cost of water, and other uncertainties associated with future changes in technological domains. Such approach also fails to include the value of flexibility, which enables managers to adapt and reconfigure systems over time as uncertainty unfolds. This work describes an integrated framework to value investments in urban water management systems under uncertainty. It also extends the conventional DCF analysis through explicit considerations of flexibility in systems design and management. The approach incorporates flexibility as intelligent decision-making mechanisms that enable systems to avoid future downside risks and increase opportunities for upside gains over a range of possible futures. A water catchment area in Singapore was chosen to assess the value of a flexible extension of standard drainage canals and a flexible deployment of a novel water catchment technology based on green roofs and porous pavements. Results show that integrating uncertainty and flexibility explicitly into the decision-making process can reduce initial capital expenditure, improve value for investment, and enable decision-makers to learn more about system requirements during the lifetime of the project. Copyright © 2013 Elsevier Ltd. All rights reserved.

Patient participation in palliative care decisions: An ethnographic discourse analysis

PubMed Central

Bélanger, Emmanuelle; Rodríguez, Charo; Groleau, Danielle; Légaré, France; MacDonald, Mary Ellen; Marchand, Robert

2016-01-01

The participation of patients in making decisions about their care is especially important towards the end of life because palliative care decisions involve extensive uncertainty and are heavily influenced by personal values. Yet, there is a scarcity of studies directly observing clinical interactions between palliative patients and their health care providers. In this study, we aimed to understand how patient participation in palliative care decisions is constructed through discourse in a community hospital-based palliative care team. This qualitative study combined ethnographic observations of a palliative care team with discourse analysis. Eighteen palliative care patients with cancer diagnoses, six family physicians, and two nurses were involved in the study. Multiple interactions were observed between each patient and health care providers over the course of 1 year, for a total of 101 consultations, 24 of which were audio-recorded. The analysis consisted in looking for the interpretive repertoires (i.e., familiar lines of argument used to justify actions) that were used to justify patient participation in decision-making during clinical interactions, as well as exploring their implications for decision roles and end-of-life care. Patients and their health care providers seldom addressed their decision-making roles explicitly. Rather, they constructed patient participation in palliative care decisions in a covert manner. Four interpretive repertoires were used to justify patient participation: (1) exposing uncertainty, (2) co-constructing patient preferences, (3) affirming patient autonomy, and finally (4) upholding the authority of health care providers. The results demonstrate how patients and health care providers used these arguments to negotiate their respective roles in decision-making. In conclusion, patients and health care providers used a variety of interpretive repertoires to covertly negotiate their roles in decision-making, and to legitimize decisions that shaped patients’ dying trajectories. Discourse analysis encourages awareness of the role of language in either promoting or hindering patient participation in decision-making. PMID:27882864

Patient participation in palliative care decisions: An ethnographic discourse analysis.

PubMed

Bélanger, Emmanuelle; Rodríguez, Charo; Groleau, Danielle; Légaré, France; MacDonald, Mary Ellen; Marchand, Robert

2016-01-01

The participation of patients in making decisions about their care is especially important towards the end of life because palliative care decisions involve extensive uncertainty and are heavily influenced by personal values. Yet, there is a scarcity of studies directly observing clinical interactions between palliative patients and their health care providers. In this study, we aimed to understand how patient participation in palliative care decisions is constructed through discourse in a community hospital-based palliative care team. This qualitative study combined ethnographic observations of a palliative care team with discourse analysis. Eighteen palliative care patients with cancer diagnoses, six family physicians, and two nurses were involved in the study. Multiple interactions were observed between each patient and health care providers over the course of 1 year, for a total of 101 consultations, 24 of which were audio-recorded. The analysis consisted in looking for the interpretive repertoires (i.e., familiar lines of argument used to justify actions) that were used to justify patient participation in decision-making during clinical interactions, as well as exploring their implications for decision roles and end-of-life care. Patients and their health care providers seldom addressed their decision-making roles explicitly. Rather, they constructed patient participation in palliative care decisions in a covert manner. Four interpretive repertoires were used to justify patient participation: (1) exposing uncertainty, (2) co-constructing patient preferences, (3) affirming patient autonomy, and finally (4) upholding the authority of health care providers. The results demonstrate how patients and health care providers used these arguments to negotiate their respective roles in decision-making. In conclusion, patients and health care providers used a variety of interpretive repertoires to covertly negotiate their roles in decision-making, and to legitimize decisions that shaped patients' dying trajectories. Discourse analysis encourages awareness of the role of language in either promoting or hindering patient participation in decision-making.

Psychological defense, ideological hideaway, or rational reckoning? The role of uncertainty in local adaptation to climate change

NASA Astrophysics Data System (ADS)

Moser, S. C.

2011-12-01

As adaptation planning is rising rapidly on the agenda of decision-makers, the need for adequate information to inform those decisions is growing. Locally relevant climate change (as well as related impacts and vulnerability) information, however, is difficult to obtain and that which can be obtained carries the burden of significant scientific uncertainty. This paper aims to assess how important such uncertainty is in adaptation planning, decision-making, and related stakeholder engagement. Does uncertainty actually hinder adaptation planning? Is scientific uncertainty used to postpone decisions reflecting ideologically agendas? Or is it a convenient defense against cognitive and affective engagement with the emerging and projected - and in some cases daunting - climate change risks? To whom does such uncertainty matter and how important is it relative to other challenges decision-makers and stakeholders face? The paper draws on four sources of information to answer these questions: (1) a statewide survey of California coastal managers conducted in summer 2011, (2) years of continual engagement with, and observation of, decision-makers in local adaptation efforts, (3) findings from focus groups with lay individuals in coastal California; and (4) a review of relevant adaptation literature to guide and contextualize the empirical research. The findings entail some "inconvenient truths" for those claiming critical technical or political importance. Rather, the insights suggest that some uncertainties matter more than others; they matter at certain times, but not at others; and they matter to some decision-makers, but not to others. Implications for scientists communicating and engaging with communities are discussed.

RECOVERY ACT - Methods for Decision under Technological Change Uncertainty and Risk Assessment for Integrated Assessment of Climate Change

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

Webster, Mort David

2015-03-10

This report presents the final outcomes and products of the project as performed at the Massachusetts Institute of Technology. The research project consists of three main components: methodology development for decision-making under uncertainty, improving the resolution of the electricity sector to improve integrated assessment, and application of these methods to integrated assessment. Results in each area is described in the report.

A Collaborator's Reputation Can Bias Decisions and Anxiety under Uncertainty.

PubMed

Qi, Song; Footer, Owen; Camerer, Colin F; Mobbs, Dean

2018-02-28

Informational social influence theory posits that under conditions of uncertainty, we are inclined to look to others for advice. This leaves us remarkably vulnerable to being influenced by others' opinions or advice. Rational agents, however, do not blindly seek and act on arbitrary information, but often consider the quality of its source before committing to a course of action. Here, we ask the question of whether a collaborator's reputation can increase their social influence and, in turn, bias perception and anxiety under changing levels of uncertainty. Human male and female participants were asked to provide estimations of dot direction using the random dot motion (RDM) perceptual discrimination task and were paired with transient collaborators of high or low reputation whom provided their own estimations. The RDM varied in degrees of uncertainty and joint performance accuracy was linked to risk of an electric shock. Despite providing identical information, we show that collaborating with a high reputation compared with a low reputation partner, led to significantly more conformity during the RDM task for uncertain perceptual decisions. Consequently, high reputation partners decreased the subjects' anxiety during the anticipatory shock periods. fMRI data showed that parametric changes in conformity resulted in increased activity in the ventromedial PFC, whereas dissent was associated with increased in activity in the dorsal anterior cingulate cortex (dACC). Furthermore, the dACC and insula, regions involved in anticipatory pain, were significantly more active when collaborating with a low reputation partner. These results suggest that information about reputation can influence both cognitive and affective processes and in turn alter the neural circuits that underlie decision-making and emotion. SIGNIFICANCE STATEMENT Humans look to others for advice when making decisions under uncertainty. Rational agents, however, do not blindly seek information, but often consider the quality of its source before committing to a course of action. Here, we ask the question of whether a collaborators' reputation can increase social influence and in turn bias perception and anxiety in the context of perceptual uncertainty. We show that when subjects are partnered with collaborators with a high reputation, this leads to increased conformity during uncertain perceptual decision-making and reduces anxiety when joint performance accuracy leads to an electric shock. Furthermore, our results show that information about reputation alters the neural circuits that underlie decision-making and emotion. Copyright © 2018 the authors 0270-6474/18/382262-08$15.00/0.

Methods for Health Economic Evaluation of Vaccines and Immunization Decision Frameworks: A Consensus Framework from a European Vaccine Economics Community.

PubMed

Ultsch, Bernhard; Damm, Oliver; Beutels, Philippe; Bilcke, Joke; Brüggenjürgen, Bernd; Gerber-Grote, Andreas; Greiner, Wolfgang; Hanquet, Germaine; Hutubessy, Raymond; Jit, Mark; Knol, Mirjam; von Kries, Rüdiger; Kuhlmann, Alexander; Levy-Bruhl, Daniel; Perleth, Matthias; Postma, Maarten; Salo, Heini; Siebert, Uwe; Wasem, Jürgen; Wichmann, Ole

2016-03-01

Incremental cost-effectiveness and cost-utility analyses [health economic evaluations (HEEs)] of vaccines are routinely considered in decision making on immunization in various industrialized countries. While guidelines advocating more standardization of such HEEs (mainly for curative drugs) exist, several immunization-specific aspects (e.g. indirect effects or discounting approach) are still a subject of debate within the scientific community. The objective of this study was to develop a consensus framework for HEEs of vaccines to support the development of national guidelines in Europe. A systematic literature review was conducted to identify prevailing issues related to HEEs of vaccines. Furthermore, European experts in the field of health economics and immunization decision making were nominated and asked to select relevant aspects for discussion. Based on this, a workshop was held with these experts. Aspects on 'mathematical modelling', 'health economics' and 'decision making' were debated in group-work sessions (GWS) to formulate recommendations and/or--if applicable--to state 'pros' and 'contras'. A total of 13 different aspects were identified for modelling and HEE: model selection, time horizon of models, natural disease history, measures of vaccine-induced protection, duration of vaccine-induced protection, indirect effects apart from herd protection, target population, model calibration and validation, handling uncertainty, discounting, health-related quality of life, cost components, and perspectives. For decision making, there were four aspects regarding the purpose and the integration of HEEs of vaccines in decision making as well as the variation of parameters within uncertainty analyses and the reporting of results from HEEs. For each aspect, background information and an expert consensus were formulated. There was consensus that when HEEs are used to prioritize healthcare funding, this should be done in a consistent way across all interventions, including vaccines. However, proper evaluation of vaccines implies using tools that are not commonly used for therapeutic drugs. Due to the complexity of and uncertainties around vaccination, transparency in the documentation of HEEs and during subsequent decision making is essential.

Decision Analysis Techniques for Adult Learners: Application to Leadership

ERIC Educational Resources Information Center

Toosi, Farah

2017-01-01

Most decision analysis techniques are not taught at higher education institutions. Leaders, project managers and procurement agents in industry have strong technical knowledge, and it is crucial for them to apply this knowledge at the right time to make critical decisions. There are uncertainties, problems, and risks involved in business…

Integrating land cover modeling and adaptive management to conserve endangered species and reduce catastrophic fire risk

USGS Publications Warehouse

Breininger, David; Duncan, Brean; Eaton, Mitchell J.; Johnson, Fred; Nichols, James

2014-01-01

Land cover modeling is used to inform land management, but most often via a two-step process, where science informs how management alternatives can influence resources, and then, decision makers can use this information to make decisions. A more efficient process is to directly integrate science and decision-making, where science allows us to learn in order to better accomplish management objectives and is developed to address specific decisions. Co-development of management and science is especially productive when decisions are complicated by multiple objectives and impeded by uncertainty. Multiple objectives can be met by the specification of tradeoffs, and relevant uncertainty can be addressed through targeted science (i.e., models and monitoring). We describe how to integrate habitat and fuel monitoring with decision-making focused on the dual objectives of managing for endangered species and minimizing catastrophic fire risk. Under certain conditions, both objectives might be achieved by a similar management policy; other conditions require tradeoffs between objectives. Knowledge about system responses to actions can be informed by developing hypotheses based on ideas about fire behavior and then applying competing management actions to different land units in the same system state. Monitoring and management integration is important to optimize state-specific management decisions and to increase knowledge about system responses. We believe this approach has broad utility and identifies a clear role for land cover modeling programs intended to inform decision-making.

Making better decisions in uncertain times (Invited)

NASA Astrophysics Data System (ADS)

St John, C.

2013-12-01

Scientific information about climate change and other human impacts on the environment are increasingly available and sought after (often in the form of probabilistic forecasts or technical information related to engineering solutions). However, it is increasingly apparent that there are barriers to the use of this information by decision makers - either from its lack of application altogether, its usability for people without scientific backgrounds, or its ability to inform sound decisions and widespread behavior change. While the argument has been made that an information deficit is to blame, we argue that there is also a motivation deficit contributing to a lack of understanding of information about climate change impacts and solutions. Utilizing insight from over thirty years of research in social and cognitive psychology, in addition to other social sciences, the Center for Research on Environmental Decisions (CRED) seeks to understand how people make environmental decisions under conditions of uncertainty, and how these decisions can be improved. This presentation will focus specifically on recent research that has come forth since the 2009 publication of CRED's popular guide 'The Psychology of Climate Change Communication: A Guide for Scientists, Journalists, Educators, Political Aides, and the Interested Public.' Utilizing case studies from real world examples, this talk will explore how decision making can be improved through a better understanding of how people perceive and process uncertainty and risk. It will explore techniques such as choice architecture and 'nudging' behavior change, how social goals and group participation affect decision making, and how framing of environmental information influences mitigative behavior.

Reducing risk and increasing confidence of decision making at a lower cost: In-situ pXRF assessment of metal-contaminated sites.

PubMed

Rouillon, Marek; Taylor, Mark P; Dong, Chenyin

2017-10-01

This study evaluates the in-situ use of field portable X-ray Fluorescence (pXRF) for metal-contaminated site assessments, and assesses the advantages of increased sampling to reduce risk, and increase confidence of decision making at a lower cost. Five metal-contaminated sites were assessed using both in-situ pXRF and ex-situ inductively coupled plasma mass spectrometry (ICP-MS) analyses at various sampling resolutions. Twenty second in-situ pXRF measurements of Mn, Zn and Pb were corrected using a subset of parallel ICP-MS measurements taken at each site. Field and analytical duplicates revealed sampling as the major contributor (>95% variation) to measurement uncertainties. This study shows that increased sampling led to several benefits including more representative site characterisation, higher soil-metal mapping resolution, reduced uncertainty around the site mean, and reduced sampling uncertainty. Real time pXRF data enabled efficient, on-site decision making for further judgemental sampling, without the need to return to the site. Additionally, in-situ pXRF was more cost effective than the current approach of ex-situ sampling and ICP-MS analysis, even with higher sampling at each site. Lastly, a probabilistic site assessment approach was applied to demonstrate the advantages of integrating estimated measurement uncertainties into site reporting. Copyright © 2017 Elsevier Ltd. All rights reserved.

Climate change adaptation under uncertainty in the developing world: A case study of sea level rise in Kiribati

NASA Astrophysics Data System (ADS)

Donner, S. D.; Webber, S.

2011-12-01

Climate change is expected to have the greatest impact in parts of the developing world. At the 2010 meeting of U.N. Framework Convention on Climate Change in Cancun, industrialized countries agreed in principle to provide US$100 billion per year by 2020 to assist the developing world respond to climate change. This "Green Climate Fund" is a critical step towards addressing the challenge of climate change. However, the policy and discourse on supporting adaptation in the developing world remains highly idealized. For example, the efficacy of "no regrets" adaptation efforts or "mainstreaming" adaptation into decision-making are rarely evaluated in the real world. In this presentation, I will discuss the gap between adaptation theory and practice using a multi-year case study of the cultural, social and scientific obstacles to adapting to sea level rise in the Pacific atoll nation of Kiribati. Our field research reveals how scientific and institutional uncertainty can limit international efforts to fund adaptation and lead to spiraling costs. Scientific uncertainty about hyper-local impacts of sea level rise, though irreducible, can at times limit decision-making about adaptation measures, contrary to the notion that "good" decision-making practices can incorporate scientific uncertainty. Efforts to improve institutional capacity must be done carefully, or they risk inadvertently slowing the implementation of adaptation measures and increasing the likelihood of "mal"-adaptation.

Shared decision-making at the end of life: A focus group study exploring the perceptions and experiences of multi-disciplinary healthcare professionals working in the home setting.

PubMed

Brogan, Paula; Hasson, Felicity; McIlfatrick, Sonja

2018-01-01

Globally recommended in healthcare policy, Shared Decision-Making is also central to international policy promoting community palliative care. Yet realities of implementation by multi-disciplinary healthcare professionals who provide end-of-life care in the home are unclear. To explore multi-disciplinary healthcare professionals' perceptions and experiences of Shared Decision-Making at end of life in the home. Qualitative design using focus groups, transcribed verbatim and analysed thematically. A total of 43 participants, from multi-disciplinary community-based services in one region of the United Kingdom, were recruited. While the rhetoric of Shared Decision-Making was recognised, its implementation was impacted by several interconnecting factors, including (1) conceptual confusion regarding Shared Decision-Making, (2) uncertainty in the process and (3) organisational factors which impeded Shared Decision-Making. Multiple interacting factors influence implementation of Shared Decision-Making by professionals working in complex community settings at the end of life. Moving from rhetoric to reality requires future work exploring the realities of Shared Decision-Making practice at individual, process and systems levels.

Managing wildfire events: risk-based decision making among a group of federal fire managers

Treesearch

Robyn S. Wilson; Patricia L. Winter; Lynn A. Maguire; Timothy Ascher

2011-01-01

Managing wildfire events to achieve multiple management objectives involves a high degree of decision complexity and uncertainty, increasing the likelihood that decisions will be informed by experience-based heuristics triggered by available cues at the time of the decision. The research reported here tests the prevalence of three risk-based biases among 206...

Assessment of adaptation measures to high-mountain risks in Switzerland under climate uncertainties

NASA Astrophysics Data System (ADS)

Muccione, Veruska; Lontzek, Thomas; Huggel, Christian; Ott, Philipp; Salzmann, Nadine

2015-04-01

The economic evaluation of different adaptation options is important to support policy-makers that need to set priorities in the decision-making process. However, the decision-making process faces considerable uncertainties regarding current and projected climate impacts. First, physical climate and related impact systems are highly complex and not fully understood. Second, the further we look into the future, the more important the emission pathways become, with effects on the frequency and severity of climate impacts. Decision on adaptation measures taken today and in the future must be able to adequately consider the uncertainties originating from the different sources. Decisions are not taken in a vacuum but always in the context of specific social, economic, institutional and political conditions. Decision finding processes strongly depend on the socio-political system and usually have evolved over some time. Finding and taking decisions in the respective socio-political and economic context multiplies the uncertainty challenge. Our presumption is that a sound assessment of the different adaptation options in Switzerland under uncertainty necessitates formulating and solving a dynamic, stochastic optimization problem. Economic optimization models in the field of climate change are not new. Typically, such models are applied for global-scale studies but barely for local-scale problems. In this analysis, we considered the case of the Guttannen-Grimsel Valley, situated in the Swiss Bernese Alps. The alpine community has been affected by high-magnitude, high-frequency debris flows that started in 2009 and were historically unprecendented. They were related to thaw of permafrost in the rock slopes of Ritzlihorn and repeated rock fall events that accumulated at the debris fan and formed a sediment source for debris flows and were transported downvalley. An important transit road, a trans-European gas pipeline and settlements were severely affected and partly destroyed. Several adaptation measures were discussed by the responsible authorities but decision making is particularly challenging under multiple uncertainties. For this area, we developed a stochastic optimization model for concrete and real-case adaptation options and measures and use dynamic programming to explore the optimal adaptation decisions under uncertainty in face of uncertain impacts from climate change of debris flows and flooding. Even though simplification needed to be made the results produced were concrete and tangible, indicating that excavation is a preferable adaptation option based on our assumption and modeling in comparison to building a dam or relocation, which is not necessarily intuitive and adds an additional perspective to what has so far been sketched and evaluated by cantonal and communal authorities for Guttannen. Moreover, the building of an alternative cantonal road appears to be more expensive than costs incurring due to road closure.

The potential for meta-analysis to support decision analysis in ecology.

PubMed

Mengersen, Kerrie; MacNeil, M Aaron; Caley, M Julian

2015-06-01

Meta-analysis and decision analysis are underpinned by well-developed methods that are commonly applied to a variety of problems and disciplines. While these two fields have been closely linked in some disciplines such as medicine, comparatively little attention has been paid to the potential benefits of linking them in ecology, despite reasonable expectations that benefits would be derived from doing so. Meta-analysis combines information from multiple studies to provide more accurate parameter estimates and to reduce the uncertainty surrounding them. Decision analysis involves selecting among alternative choices using statistical information that helps to shed light on the uncertainties involved. By linking meta-analysis to decision analysis, improved decisions can be made, with quantification of the costs and benefits of alternate decisions supported by a greater density of information. Here, we briefly review concepts of both meta-analysis and decision analysis, illustrating the natural linkage between them and the benefits from explicitly linking one to the other. We discuss some examples in which this linkage has been exploited in the medical arena and how improvements in precision and reduction of structural uncertainty inherent in a meta-analysis can provide substantive improvements to decision analysis outcomes by reducing uncertainty in expected loss and maximising information from across studies. We then argue that these significant benefits could be translated to ecology, in particular to the problem of making optimal ecological decisions in the face of uncertainty. Copyright © 2013 John Wiley & Sons, Ltd.

Policy decision-making under scientific uncertainty: radiological risk assessment and the role of expert advisory groups.

PubMed

Mossman, Kenneth L

2009-08-01

Standard-setting agencies such as the U.S. Nuclear Regulatory Commission and the U.S. Environmental Protection Agency depend on advice from external expert advisory groups on matters of public policy and standard-setting. Authoritative bodies including the National Research Council and the National Council on Radiation Protection and Measurements provide analyses and recommendations that enable the technical and scientific soundness in decision-making. In radiological protection the nature of the scientific evidence is such that risk assessment at radiation doses typically encountered in environmental and occupational settings is highly uncertain, and several policy alternatives are scientifically defensible. The link between science and policy is problematic. The fundamental issue is the failure to properly consider risk assessment, risk communication, and risk management and then consolidate them in a process that leads to sound policy. Authoritative bodies should serve as unbiased brokers of policy choices by providing balanced and objective scientific analyses. As long as the policy-decision environment is characterized by high scientific uncertainty and a lack of values consensus, advisory groups should present unbiased evaluations of all scientifically plausible alternatives and recommend selection criteria that decision makers can use in the policy-setting process. To do otherwise (e.g., by serving as single position advocates) weakens decision-making by eliminating options and narrowing discussions of scientific perspectives. Understanding uncertainties and the limitations on available scientific information and conveying such information to policy makers remain key challenges for the technical and policy communities.

Aging and loss decision making: increased risk aversion and decreased use of maximizing information, with correlated rationality and value maximization

PubMed Central

Kurnianingsih, Yoanna A.; Sim, Sam K. Y.; Chee, Michael W. L.; Mullette-Gillman, O’Dhaniel A.

2015-01-01

We investigated how adult aging specifically alters economic decision-making, focusing on examining alterations in uncertainty preferences (willingness to gamble) and choice strategies (what gamble information influences choices) within both the gains and losses domains. Within each domain, participants chose between certain monetary outcomes and gambles with uncertain outcomes. We examined preferences by quantifying how uncertainty modulates choice behavior as if altering the subjective valuation of gambles. We explored age-related preferences for two types of uncertainty, risk, and ambiguity. Additionally, we explored how aging may alter what information participants utilize to make their choices by comparing the relative utilization of maximizing and satisficing information types through a choice strategy metric. Maximizing information was the ratio of the expected value of the two options, while satisficing information was the probability of winning. We found age-related alterations of economic preferences within the losses domain, but no alterations within the gains domain. Older adults (OA; 61–80 years old) were significantly more uncertainty averse for both risky and ambiguous choices. OA also exhibited choice strategies with decreased use of maximizing information. Within OA, we found a significant correlation between risk preferences and choice strategy. This linkage between preferences and strategy appears to derive from a convergence to risk neutrality driven by greater use of the effortful maximizing strategy. As utility maximization and value maximization intersect at risk neutrality, this result suggests that OA are exhibiting a relationship between enhanced rationality and enhanced value maximization. While there was variability in economic decision-making measures within OA, these individual differences were unrelated to variability within examined measures of cognitive ability. Our results demonstrate that aging alters economic decision-making for losses through changes in both individual preferences and the strategies individuals employ. PMID:26029092

Multi-criteria decision-making for flood risk management: a survey of the current state of the art

NASA Astrophysics Data System (ADS)

Madruga de Brito, Mariana; Evers, Mariele

2016-04-01

This paper provides a review of multi-criteria decision-making (MCDM) applications to flood risk management, seeking to highlight trends and identify research gaps. A total of 128 peer-reviewed papers published from 1995 to June 2015 were systematically analysed. Results showed that the number of flood MCDM publications has exponentially grown during this period, with over 82 % of all papers published since 2009. A wide range of applications were identified, with most papers focusing on ranking alternatives for flood mitigation, followed by risk, hazard, and vulnerability assessment. The analytical hierarchy process (AHP) was the most popular method, followed by Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS), and Simple Additive Weighting (SAW). Although there is greater interest in MCDM, uncertainty analysis remains an issue and was seldom applied in flood-related studies. In addition, participation of multiple stakeholders has been generally fragmented, focusing on particular stages of the decision-making process, especially on the definition of criteria weights. Therefore, addressing the uncertainties around stakeholders' judgments and endorsing an active participation in all steps of the decision-making process should be explored in future applications. This could help to increase the quality of decisions and the implementation of chosen measures.

Modulating the Activity of the DLPFC and OFC Has Distinct Effects on Risk and Ambiguity Decision-Making: A tDCS Study

PubMed Central

Yang, Xiaolan; Gao, Mei; Shi, Jinchuan; Ye, Hang; Chen, Shu

2017-01-01

Human beings are constantly exposed to two types of uncertainty situations, risk and ambiguity. Neuroscientific studies suggest that the dorsolateral prefrontal cortex (DLPFC) and the orbital frontal cortex (OFC) play significant roles in human decision making under uncertainty. We applied the transcranial direct current stimulation (tDCS) device to modulate the activity of participants’ DLPFC and OFC separately, comparing the causal relationships between people’s behaviors and the activity of the corresponding brain cortex when confronted with situations of risk and ambiguity. Our experiment employed a pre–post design and a risk/ambiguity decision-making task, from which we could calculate the preferences via an estimation model. We found evidences that modulating the activity of the DLPFC using right anodal/left cathodal tDCS significantly enhanced the participants’ preferences for risk, whereas modulating the activity of the OFC with right anodal/left cathodal tDCS significantly decreased the participants’ preferences for ambiguity. The reverse effects were also observed in the reversed tDCS treatments on the two areas. Our results suggest that decision-making processes under risk and ambiguity are complicated and may be encoded in two distinct circuits in our brains as the DLPFC primarily impacts decisions under risk whereas the OFC affects ambiguity. PMID:28878714

Modulating the Activity of the DLPFC and OFC Has Distinct Effects on Risk and Ambiguity Decision-Making: A tDCS Study.

PubMed

Yang, Xiaolan; Gao, Mei; Shi, Jinchuan; Ye, Hang; Chen, Shu

2017-01-01

Human beings are constantly exposed to two types of uncertainty situations, risk and ambiguity. Neuroscientific studies suggest that the dorsolateral prefrontal cortex (DLPFC) and the orbital frontal cortex (OFC) play significant roles in human decision making under uncertainty. We applied the transcranial direct current stimulation (tDCS) device to modulate the activity of participants' DLPFC and OFC separately, comparing the causal relationships between people's behaviors and the activity of the corresponding brain cortex when confronted with situations of risk and ambiguity. Our experiment employed a pre-post design and a risk/ambiguity decision-making task, from which we could calculate the preferences via an estimation model. We found evidences that modulating the activity of the DLPFC using right anodal/left cathodal tDCS significantly enhanced the participants' preferences for risk, whereas modulating the activity of the OFC with right anodal/left cathodal tDCS significantly decreased the participants' preferences for ambiguity. The reverse effects were also observed in the reversed tDCS treatments on the two areas. Our results suggest that decision-making processes under risk and ambiguity are complicated and may be encoded in two distinct circuits in our brains as the DLPFC primarily impacts decisions under risk whereas the OFC affects ambiguity.

A framework for sensitivity analysis of decision trees.

PubMed

Kamiński, Bogumił; Jakubczyk, Michał; Szufel, Przemysław

2018-01-01

In the paper, we consider sequential decision problems with uncertainty, represented as decision trees. Sensitivity analysis is always a crucial element of decision making and in decision trees it often focuses on probabilities. In the stochastic model considered, the user often has only limited information about the true values of probabilities. We develop a framework for performing sensitivity analysis of optimal strategies accounting for this distributional uncertainty. We design this robust optimization approach in an intuitive and not overly technical way, to make it simple to apply in daily managerial practice. The proposed framework allows for (1) analysis of the stability of the expected-value-maximizing strategy and (2) identification of strategies which are robust with respect to pessimistic/optimistic/mode-favoring perturbations of probabilities. We verify the properties of our approach in two cases: (a) probabilities in a tree are the primitives of the model and can be modified independently; (b) probabilities in a tree reflect some underlying, structural probabilities, and are interrelated. We provide a free software tool implementing the methods described.

The role of serotonin in nonnormative risky choice: the effects of tryptophan supplements on the "reflection effect" in healthy adult volunteers.

PubMed

Murphy, Susannah E; Longhitano, Carlo; Ayres, Rachael E; Cowen, Philip J; Harmer, Catherine J; Rogers, Robert D

2009-09-01

Risky decision-making involves weighing good and bad outcomes against their probabilities in order to determine the relative values of candidate actions. Although human decision-making sometimes conforms to rational models of how this weighting is achieved, irrational (or nonnormative) patterns of risky choice, including shifts between risk-averse and risk-seeking choices involving equivalent-value gambles (the "reflection effect"), are frequently observed. In the present experiment, we investigated the role of serotonin in decision-making under conditions of uncertainty. Fifteen healthy adult volunteers received a treatment of 3 g per day of the serotonin precursor, tryptophan, in the form of dietary supplements over a 14-day period, whereas 15 age- and IQ-matched control volunteers received a matched placebo substance. At test, all participants completed a risky decision-making task involving a series of choices between two simultaneously presented gambles, differing in the magnitude of their possible gains, the magnitude of their possible losses, and the probabilities with which these outcomes were delivered. Tryptophan supplements were associated with alterations in the weighting of gains and small losses perhaps reflecting reduced loss-aversion, and a marked and significant diminution of the reflection effect. We conclude that serotonin activity plays a significant role in nonnormative risky decision-making under conditions of uncertainty.

Prospective Architectures for Onboard vs Cloud-Based Decision Making for Unmanned Aerial Systems

NASA Technical Reports Server (NTRS)

Sankararaman, Shankar; Teubert, Christopher

2017-01-01

This paper investigates propsective architectures for decision-making in unmanned aerial systems. When these unmanned vehicles operate in urban environments, there are several sources of uncertainty that affect their behavior, and decision-making algorithms need to be robust to account for these different sources of uncertainty. It is important to account for several risk-factors that affect the flight of these unmanned systems, and facilitate decision-making by taking into consideration these various risk-factors. In addition, there are several technical challenges related to autonomous flight of unmanned aerial systems; these challenges include sensing, obstacle detection, path planning and navigation, trajectory generation and selection, etc. Many of these activities require significant computational power and in many situations, all of these activities need to be performed in real-time. In order to efficiently integrate these activities, it is important to develop a systematic architecture that can facilitate real-time decision-making. Four prospective architectures are discussed in this paper; on one end of the spectrum, the first architecture considers all activities/computations being performed onboard the vehicle whereas on the other end of the spectrum, the fourth and final architecture considers all activities/computations being performed in the cloud, using a new service known as Prognostics as a Service that is being developed at NASA Ames Research Center. The four different architectures are compared, their advantages and disadvantages are explained and conclusions are presented.

Effects of emotion on prospection during decision-making.

PubMed

Worthy, Darrell A; Byrne, Kaileigh A; Fields, Sherecce

2014-01-01

In two experiments we examined the role of emotion, specifically worry, anxiety, and mood, on prospection during decision-making. Worry is a particularly relevant emotion to study in the context of prospection because high levels of worry may make individuals more aversive toward the uncertainty associated with the prospect of obtaining future improvements in rewards or states. Thus, high levels of worry might lead to reduced prospection during decision-making and enhance preference for immediate over delayed rewards. In Experiment 1 participants performed a two-choice dynamic decision-making task where they were required to choose between one option (the decreasing option) which provided larger immediate rewards but declines in future states, and another option (the increasing option) which provided smaller immediate rewards but improvements in future states, making it the optimal choice. High levels of worry were associated with poorer performance in the task. Additionally, fits of a sophisticated reinforcement-learning model that incorporated both reward-based and state-based information suggested that individuals reporting high levels of worry gave greater weight to the immediate rewards they would receive on each trial than to the degree to which each action would lead to improvements in their future state. In Experiment 2 we found that high levels of worry were associated with greater delay discounting using a standard delay discounting task. Combined, the results suggest that high levels of worry are associated with reduced prospection during decision-making. We attribute these results to high worriers' aversion toward the greater uncertainty associated with attempting to improve future rewards than to maximize immediate reward. These results have implications for researchers interested in the effects of emotion on cognition, and suggest that emotion strongly affects the focus on temporal outcomes during decision-making.

Ignoring correlation in uncertainty and sensitivity analysis in life cycle assessment: what is the risk?

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

Groen, E.A., E-mail: Evelyne.Groen@gmail.com; Heijungs, R.; Leiden University, Einsteinweg 2, Leiden 2333 CC

Life cycle assessment (LCA) is an established tool to quantify the environmental impact of a product. A good assessment of uncertainty is important for making well-informed decisions in comparative LCA, as well as for correctly prioritising data collection efforts. Under- or overestimation of output uncertainty (e.g. output variance) will lead to incorrect decisions in such matters. The presence of correlations between input parameters during uncertainty propagation, can increase or decrease the the output variance. However, most LCA studies that include uncertainty analysis, ignore correlations between input parameters during uncertainty propagation, which may lead to incorrect conclusions. Two approaches to include correlationsmore » between input parameters during uncertainty propagation and global sensitivity analysis were studied: an analytical approach and a sampling approach. The use of both approaches is illustrated for an artificial case study of electricity production. Results demonstrate that both approaches yield approximately the same output variance and sensitivity indices for this specific case study. Furthermore, we demonstrate that the analytical approach can be used to quantify the risk of ignoring correlations between input parameters during uncertainty propagation in LCA. We demonstrate that: (1) we can predict if including correlations among input parameters in uncertainty propagation will increase or decrease output variance; (2) we can quantify the risk of ignoring correlations on the output variance and the global sensitivity indices. Moreover, this procedure requires only little data. - Highlights: • Ignoring correlation leads to under- or overestimation of the output variance. • We demonstrated that the risk of ignoring correlation can be quantified. • The procedure proposed is generally applicable in life cycle assessment. • In some cases, ignoring correlation has a minimal effect on decision-making tools.« less

Nordic couples' decision-making processes during assisted reproduction treatments.

PubMed

Sol Olafsdottir, Helga; Wikland, Matts; Möller, Anders

2013-06-01

To study couples' perceptions of their decision-making process during the first three years of infertility treatments. This study is a part of a larger project studying the decision-making processes of 22 infertile heterosexual couples, recruited from fertility clinics in all five Nordic countries, over a three year period. A descriptive qualitative method was used. Process of decision-making during assisted reproduction treatments. Seventeen couples had succeeded in becoming parents after approximately three years. Our study suggests that the decision-making process during fertility treatments has three phases: (i) recognizing the decisions to be made, with subcategories; the driving force, mutual project, (ii) gathering knowledge and experience about the options, with subcategories; trust, patient competence, personalized support, and (iii) adapting decisions to possible options, with subcategories; strategic planning, adaption. The core category was "maintaining control in a situation of uncertainty." Two parallel processes affect couples' decision-making process, one within themselves and their relationship, and the other in their contact with the fertility clinic. Couples struggle to make decisions, trusting clinic personnel for guidance, knowledge, and understanding. Nevertheless, couples expressed disappointment with the clinics' reactions to their requests for shared decision-making. Copyright © 2013 Elsevier B.V. All rights reserved.

Heuristics: foundations for a novel approach to medical decision making.

PubMed

Bodemer, Nicolai; Hanoch, Yaniv; Katsikopoulos, Konstantinos V

2015-03-01

Medical decision-making is a complex process that often takes place during uncertainty, that is, when knowledge, time, and resources are limited. How can we ensure good decisions? We present research on heuristics-simple rules of thumb-and discuss how medical decision-making can benefit from these tools. We challenge the common view that heuristics are only second-best solutions by showing that they can be more accurate, faster, and easier to apply in comparison to more complex strategies. Using the example of fast-and-frugal decision trees, we illustrate how heuristics can be studied and implemented in the medical context. Finally, we suggest how a heuristic-friendly culture supports the study and application of heuristics as complementary strategies to existing decision rules.

Policy, practice and decision making for zoonotic disease management: water and Cryptosporidium.

PubMed

Austin, Zoë; Alcock, Ruth E; Christley, Robert M; Haygarth, Philip M; Heathwaite, A Louise; Latham, Sophia M; Mort, Maggie; Oliver, David M; Pickup, Roger; Wastling, Jonathan M; Wynne, Brian

2012-04-01

Decision making for zoonotic disease management should be based on many forms of appropriate data and sources of evidence. However, the criteria and timing for policy response and the resulting management decisions are often altered when a disease outbreak occurs and captures full media attention. In the case of waterborne disease, such as the robust protozoa, Cryptosporidium spp, exposure can cause significant human health risks and preventing exposure by maintaining high standards of biological and chemical water quality remains a priority for water companies in the UK. Little has been documented on how knowledge and information is translated between the many stakeholders involved in the management of Cryptosporidium, which is surprising given the different drivers that have shaped management decisions. Such information, coupled with the uncertainties that surround these data is essential for improving future management strategies that minimise disease outbreaks. Here, we examine the interplay between scientific information, the media, and emergent government and company policies to examine these issues using qualitative and quantitative data relating to Cryptosporidium management decisions by a water company in the North West of England. Our results show that political and media influences are powerful drivers of management decisions if fuelled by high profile outbreaks. Furthermore, the strength of the scientific evidence is often constrained by uncertainties in the data, and in the way knowledge is translated between policy levels during established risk management procedures. In particular, under or over-estimating risk during risk assessment procedures together with uncertainty regarding risk factors within the wider environment, was found to restrict the knowledge-base for decision-making in Cryptosporidium management. Our findings highlight some key current and future challenges facing the management of such diseases that are widely applicable to other risk management situations. Copyright © 2011 Elsevier Ltd. All rights reserved.

Individual Differences in Information Processing in Networked Decision Making

DTIC Science & Technology

2015-03-31

conclu- sion. On the other hand, need-for-cognitive-closure ( NCC ) [Webster and Kruglanski, 1994] indicates the desire to arrive at a decision quickly to...avoid discomfort caused by ambiguity or uncertainty. It has been shown that the individual differences in NC and NCC play a significant role in...and NCC scales on accuracy and timeliness of decision making has not been studied deeply in the literature. In this paper, we introduce an agent-based

Don't bet on it! Wagering as a measure of awareness in decision making under uncertainty.

PubMed

Konstantinidis, Emmanouil; Shanks, David R

2014-12-01

Can our decisions be guided by unconscious or implicit influences? According to the somatic marker hypothesis, emotion-based signals can guide our decisions in uncertain environments outside awareness. Postdecision wagering, in which participants make wagers on the outcomes of their decisions, has been recently proposed as an objective and sensitive measure of conscious content. In 5 experiments we employed variations of a classic decision-making assessment, the Iowa Gambling Task, in combination with wagering in order to investigate the role played by unconscious influences. We examined the validity of postdecision wagering by comparing it with alternative measures of conscious knowledge, specifically confidence ratings and quantitative questions. Consistent with a putative role for unconscious influences, in Experiments 2 and 3 we observed a lag between choice accuracy and the onset of advantageous wagering. However, the lag was eliminated by a change in the wagering payoff matrix (Experiment 2) and by a switch from a binary wager response to either a binary or a 4-point confidence response (Experiment 3), and wagering underestimated awareness compared to explicit quantitative questions (Experiments 1 and 4). Our results demonstrate the insensitivity of postdecision wagering as a direct measure of conscious knowledge and challenge the claim that implicit processes influence decision making under uncertainty. PsycINFO Database Record (c) 2014 APA, all rights reserved.

Impact of inherent meteorology uncertainty on air quality model predictions

EPA Science Inventory

It is well established that there are a number of different classifications and sources of uncertainties in environmental modeling systems. Air quality models rely on two key inputs, namely, meteorology and emissions. When using air quality models for decision making, it is impor...

Measuring decisional certainty among women seeking abortion.

PubMed

Ralph, Lauren J; Foster, Diana Greene; Kimport, Katrina; Turok, David; Roberts, Sarah C M

2017-03-01

Evaluating decisional certainty is an important component of medical care, including preabortion care. However, minimal research has examined how to measure certainty with reliability and validity among women seeking abortion. We examine whether the Decisional Conflict Scale (DCS), a measure widely used in other health specialties and considered the gold standard for measuring this construct, and the Taft-Baker Scale (TBS), a measure developed by abortion counselors, are valid and reliable for use with women seeking abortion and predict the decision to continue the pregnancy. Eligible women at four family planning facilities in Utah completed baseline demographic surveys and scales before their abortion information visit and follow-up interviews 3 weeks later. For each scale, we calculated mean scores and explored factors associated with high uncertainty. We evaluated internal reliability using Cronbach's alpha and assessed predictive validity by examining whether higher scale scores, indicative of decisional uncertainty or conflict, were associated with still being pregnant at follow-up. Five hundred women completed baseline surveys; two-thirds (63%) completed follow-up, at which time 11% were still pregnant. Mean scores on the DCS (15.5/100) and TBS (12.4/100) indicated low uncertainty, with acceptable reliability (α=.93 and .72, respectively). Higher scores on each scale were significantly and positively associated with still being pregnant at follow-up in both unadjusted and adjusted analyses. The DCS and TBS demonstrate acceptable reliability and validity among women seeking abortion care. Comparing scores on the DCS in this population to other studies of decision making suggests that the level of uncertainty in abortion decision making is comparable to or lower than other health decisions. The high levels of decisional certainty found in this study challenge the narrative that abortion decision making is exceptional compared to other healthcare decisions and requires additional protection such as laws mandating waiting periods, counseling and ultrasound viewing. Copyright © 2016. Published by Elsevier Inc.

Probabilistic sensitivity analysis for NICE technology assessment: not an optional extra.

PubMed

Claxton, Karl; Sculpher, Mark; McCabe, Chris; Briggs, Andrew; Akehurst, Ron; Buxton, Martin; Brazier, John; O'Hagan, Tony

2005-04-01

Recently the National Institute for Clinical Excellence (NICE) updated its methods guidance for technology assessment. One aspect of the new guidance is to require the use of probabilistic sensitivity analysis with all cost-effectiveness models submitted to the Institute. The purpose of this paper is to place the NICE guidance on dealing with uncertainty into a broader context of the requirements for decision making; to explain the general approach that was taken in its development; and to address each of the issues which have been raised in the debate about the role of probabilistic sensitivity analysis in general. The most appropriate starting point for developing guidance is to establish what is required for decision making. On the basis of these requirements, the methods and framework of analysis which can best meet these needs can then be identified. It will be argued that the guidance on dealing with uncertainty and, in particular, the requirement for probabilistic sensitivity analysis, is justified by the requirements of the type of decisions that NICE is asked to make. Given this foundation, the main issues and criticisms raised during and after the consultation process are reviewed. Finally, some of the methodological challenges posed by the need fully to characterise decision uncertainty and to inform the research agenda will be identified and discussed. Copyright (c) 2005 John Wiley & Sons, Ltd.

Value of information analysis for groundwater quality monitoring network design Case study: Eocene Aquifer, Palestine

NASA Astrophysics Data System (ADS)

Khader, A.; McKee, M.

2010-12-01

Value of information (VOI) analysis evaluates the benefit of collecting additional information to reduce or eliminate uncertainty in a specific decision-making context. It makes explicit any expected potential losses from errors in decision making due to uncertainty and identifies the “best” information collection strategy as one that leads to the greatest expected net benefit to the decision-maker. This study investigates the willingness to pay for groundwater quality monitoring in the Eocene Aquifer, Palestine, which is an unconfined aquifer located in the northern part of the West Bank. The aquifer is being used by 128,000 Palestinians to fulfill domestic and agricultural demands. The study takes into account the consequences of pollution and the options the decision maker might face. Since nitrate is the major pollutant in the aquifer, the consequences of nitrate pollution were analyzed, which mainly consists of the possibility of methemoglobinemia (blue baby syndrome). In this case, the value of monitoring was compared to the costs of treating for methemoglobinemia or the costs of other options like water treatment, using bottled water or importing water from outside the aquifer. And finally, an optimal monitoring network that takes into account the uncertainties in recharge (climate), aquifer properties (hydraulic conductivity), pollutant chemical reaction (decay factor), and the value of monitoring is designed by utilizing a sparse Bayesian modeling algorithm called a relevance vector machine.

Uncertainty and Decision Making

DTIC Science & Technology

1979-09-01

higher productivity and satisfaction than a nonsupportive co-worker and enriched tasks affected attitudes but not performance . The greatest uncertainty...leadership V- 4••,,. • , -9- style, goals, and task HLructure) on psychological uncertainty and the resultant effect on performance and satisfaction . People...turn related to satisfaction and performance . In general, a stric- turing leadership style, specific goals and a structured task result in lower unce

Understanding and applying principles of social cognition and decision making in adaptive environmental governance.

PubMed

DeCaro, Daniel A; Arnol, Craig Anthony Tony; Boama, Emmanuel Frimpong; Garmestani, Ahjond S

2017-03-01

Environmental governance systems are under greater pressure to adapt and to cope with increased social and ecological uncertainty from stressors like climate change. We review principles of social cognition and decision making that shape and constrain how environmental governance systems adapt. We focus primarily on the interplay between key decision makers in society and legal systems. We argue that adaptive governance must overcome three cooperative dilemmas to facilitate adaptation: (1) encouraging collaborative problem solving, (2) garnering social acceptance and commitment, and (3) cultivating a culture of trust and tolerance for change and uncertainty. However, to do so governance systems must cope with biases in people's decision making that cloud their judgment and create conflict. These systems must also satisfy people's fundamental needs for self-determination, fairness, and security, ensuring that changes to environmental governance are perceived as legitimate, trustworthy, and acceptable. We discuss the implications of these principles for common governance solutions (e.g., public participation, enforcement) and conclude with methodological recommendations. We outline how scholars can investigate the social cognitive principles involved in cases of adaptive governance.

Understanding and applying principles of social cognition and decision making in adaptive environmental governance

PubMed Central

DeCaro, Daniel A.; Arnol, Craig Anthony (Tony); Boama, Emmanuel Frimpong; Garmestani, Ahjond S.

2018-01-01

Environmental governance systems are under greater pressure to adapt and to cope with increased social and ecological uncertainty from stressors like climate change. We review principles of social cognition and decision making that shape and constrain how environmental governance systems adapt. We focus primarily on the interplay between key decision makers in society and legal systems. We argue that adaptive governance must overcome three cooperative dilemmas to facilitate adaptation: (1) encouraging collaborative problem solving, (2) garnering social acceptance and commitment, and (3) cultivating a culture of trust and tolerance for change and uncertainty. However, to do so governance systems must cope with biases in people’s decision making that cloud their judgment and create conflict. These systems must also satisfy people’s fundamental needs for self-determination, fairness, and security, ensuring that changes to environmental governance are perceived as legitimate, trustworthy, and acceptable. We discuss the implications of these principles for common governance solutions (e.g., public participation, enforcement) and conclude with methodological recommendations. We outline how scholars can investigate the social cognitive principles involved in cases of adaptive governance. PMID:29780425

Uncertainty analysis of a groundwater flow model in east-central Florida

USGS Publications Warehouse

Sepúlveda, Nicasio; Doherty, John E.

2014-01-01

A groundwater flow model for east-central Florida has been developed to help water-resource managers assess the impact of increased groundwater withdrawals from the Floridan aquifer system on heads and spring flows originating from the Upper Floridan aquifer. The model provides a probabilistic description of predictions of interest to water-resource managers, given the uncertainty associated with system heterogeneity, the large number of input parameters, and a nonunique groundwater flow solution. The uncertainty associated with these predictions can then be considered in decisions with which the model has been designed to assist. The “Null Space Monte Carlo” method is a stochastic probabilistic approach used to generate a suite of several hundred parameter field realizations, each maintaining the model in a calibrated state, and each considered to be hydrogeologically plausible. The results presented herein indicate that the model’s capacity to predict changes in heads or spring flows that originate from increased groundwater withdrawals is considerably greater than its capacity to predict the absolute magnitudes of heads or spring flows. Furthermore, the capacity of the model to make predictions that are similar in location and in type to those in the calibration dataset exceeds its capacity to make predictions of different types at different locations. The quantification of these outcomes allows defensible use of the modeling process in support of future water-resources decisions. The model allows the decision-making process to recognize the uncertainties, and the spatial/temporal variability of uncertainties that are associated with predictions of future system behavior in a complex hydrogeological context.

Water Resource Planning Under Future Climate and Socioeconomic Uncertainty in the Cauvery River Basin in Karnataka, India.

PubMed

Bhave, Ajay Gajanan; Conway, Declan; Dessai, Suraje; Stainforth, David A

2018-02-01

Decision-Making Under Uncertainty (DMUU) approaches have been less utilized in developing countries than developed countries for water resources contexts. High climate vulnerability and rapid socioeconomic change often characterize developing country contexts, making DMUU approaches relevant. We develop an iterative multi-method DMUU approach, including scenario generation, coproduction with stakeholders and water resources modeling. We apply this approach to explore the robustness of adaptation options and pathways against future climate and socioeconomic uncertainties in the Cauvery River Basin in Karnataka, India. A water resources model is calibrated and validated satisfactorily using observed streamflow. Plausible future changes in Indian Summer Monsoon (ISM) precipitation and water demand are used to drive simulations of water resources from 2021 to 2055. Two stakeholder-identified decision-critical metrics are examined: a basin-wide metric comprising legal instream flow requirements for the downstream state of Tamil Nadu, and a local metric comprising water supply reliability to Bangalore city. In model simulations, the ability to satisfy these performance metrics without adaptation is reduced under almost all scenarios. Implementing adaptation options can partially offset the negative impacts of change. Sequencing of options according to stakeholder priorities into Adaptation Pathways affects metric satisfaction. Early focus on agricultural demand management improves the robustness of pathways but trade-offs emerge between intrabasin and basin-wide water availability. We demonstrate that the fine balance between water availability and demand is vulnerable to future changes and uncertainty. Despite current and long-term planning challenges, stakeholders in developing countries may engage meaningfully in coproduction approaches for adaptation decision-making under deep uncertainty.

Uncertainty analysis of a groundwater flow model in East-central Florida.

PubMed

Sepúlveda, Nicasio; Doherty, John

2015-01-01

A groundwater flow model for east-central Florida has been developed to help water-resource managers assess the impact of increased groundwater withdrawals from the Floridan aquifer system on heads and spring flows originating from the Upper Floridan Aquifer. The model provides a probabilistic description of predictions of interest to water-resource managers, given the uncertainty associated with system heterogeneity, the large number of input parameters, and a nonunique groundwater flow solution. The uncertainty associated with these predictions can then be considered in decisions with which the model has been designed to assist. The "Null Space Monte Carlo" method is a stochastic probabilistic approach used to generate a suite of several hundred parameter field realizations, each maintaining the model in a calibrated state, and each considered to be hydrogeologically plausible. The results presented herein indicate that the model's capacity to predict changes in heads or spring flows that originate from increased groundwater withdrawals is considerably greater than its capacity to predict the absolute magnitudes of heads or spring flows. Furthermore, the capacity of the model to make predictions that are similar in location and in type to those in the calibration dataset exceeds its capacity to make predictions of different types at different locations. The quantification of these outcomes allows defensible use of the modeling process in support of future water-resources decisions. The model allows the decision-making process to recognize the uncertainties, and the spatial or temporal variability of uncertainties that are associated with predictions of future system behavior in a complex hydrogeological context. © 2014, National Ground Water Association.

Water Resource Planning Under Future Climate and Socioeconomic Uncertainty in the Cauvery River Basin in Karnataka, India

NASA Astrophysics Data System (ADS)

Bhave, Ajay Gajanan; Conway, Declan; Dessai, Suraje; Stainforth, David A.

2018-02-01

Decision-Making Under Uncertainty (DMUU) approaches have been less utilized in developing countries than developed countries for water resources contexts. High climate vulnerability and rapid socioeconomic change often characterize developing country contexts, making DMUU approaches relevant. We develop an iterative multi-method DMUU approach, including scenario generation, coproduction with stakeholders and water resources modeling. We apply this approach to explore the robustness of adaptation options and pathways against future climate and socioeconomic uncertainties in the Cauvery River Basin in Karnataka, India. A water resources model is calibrated and validated satisfactorily using observed streamflow. Plausible future changes in Indian Summer Monsoon (ISM) precipitation and water demand are used to drive simulations of water resources from 2021 to 2055. Two stakeholder-identified decision-critical metrics are examined: a basin-wide metric comprising legal instream flow requirements for the downstream state of Tamil Nadu, and a local metric comprising water supply reliability to Bangalore city. In model simulations, the ability to satisfy these performance metrics without adaptation is reduced under almost all scenarios. Implementing adaptation options can partially offset the negative impacts of change. Sequencing of options according to stakeholder priorities into Adaptation Pathways affects metric satisfaction. Early focus on agricultural demand management improves the robustness of pathways but trade-offs emerge between intrabasin and basin-wide water availability. We demonstrate that the fine balance between water availability and demand is vulnerable to future changes and uncertainty. Despite current and long-term planning challenges, stakeholders in developing countries may engage meaningfully in coproduction approaches for adaptation decision-making under deep uncertainty.

Adaptive decision making in a dynamic environment: a test of a sequential sampling model of relative judgment.

PubMed

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

2013-09-01

Research has identified a wide range of factors that influence performance in relative judgment tasks. However, the findings from this research have been inconsistent. Studies have varied with respect to the identification of causal variables and the perceptual and decision-making mechanisms underlying performance. Drawing on the ecological rationality approach, we present a theory of the judgment and decision-making processes involved in a relative judgment task that explains how people judge a stimulus and adapt their decision process to accommodate their own uncertainty associated with those judgments. Undergraduate participants performed a simulated air traffic control conflict detection task. Across two experiments, we systematically manipulated variables known to affect performance. In the first experiment, we manipulated the relative distances of aircraft to a common destination while holding aircraft speeds constant. In a follow-up experiment, we introduced a direct manipulation of relative speed. We then fit a sequential sampling model to the data, and used the best fitting parameters to infer the decision-making processes responsible for performance. Findings were consistent with the theory that people adapt to their own uncertainty by adjusting their criterion and the amount of time they take to collect evidence in order to make a more accurate decision. From a practical perspective, the paper demonstrates that one can use a sequential sampling model to understand performance in a dynamic environment, allowing one to make sense of and interpret complex patterns of empirical findings that would otherwise be difficult to interpret using standard statistical analyses. PsycINFO Database Record (c) 2013 APA, all rights reserved.

A Structured approach to incidental take decision making

USGS Publications Warehouse

McGowan, Conor P.

2013-01-01

Decision making related to incidental take of endangered species under U.S. law lends itself well to a structured decision making approach. Incidental take is the permitted killing, harming, or harassing of a protected species under the law as long as that harm is incidental to an otherwise lawful activity and does not “reduce appreciably the probability of survival and recovery in the wild.” There has been inconsistency in the process used for determining incidental take allowances across species and across time for the same species, and structured decision making has been proposed to improve decision making. I use an example decision analysis to demonstrate the process and its applicability to incidental take decisions, even under significant demographic uncertainty and multiple, competing objectives. I define the example problem, present an objectives statement and a value function, use a simulation model to assess the consequences of a set of management actions, and evaluate the tradeoffs among the different actions. The approach results in transparent and repeatable decisions.

What does the new breed of decision-making methodologies mean for choices and norms in hydrological science?

NASA Astrophysics Data System (ADS)

Wikman-Svahn, Per

2013-04-01

Hydrological sciences are increasingly utilized in decision-making contexts that need to manage deep uncertainty, changing conditions and very long-lead times and lifetimes. Traditional optimizing approaches become problematic in such situations. For example, optimizing approaches may underestimate the importance of low probability outcomes, or very uncertain outcomes. Alternative decision-making strategies are therefore increasingly used in hydrological applications, including "bottom-up/top-down", "context-first", "decision-scaling", "assess risk of policy", "robust", "resilient" or "flexible" approaches. These kinds of strategies are typically designed to handle very uncertain and diverse outcomes, and often start from the particular decision-making context, in contrast to more traditional "predict-then-act" or "science first" approaches. Contemporary research in philosophy of science stress the influence of value judgments and norms in scientific assessments. In particular, this literature points out that implicit anticipated applications often influence choices made in scientific assessments. Furthermore, this literature also emphasize that choices made at within scientific assessments have consequences for decision-making later on. One reason is that it is often difficult for decision-makers to see what choices are made and the implications of these choices. Another reason is that information that could be of use for decision-makers are lost at an early stage. For example, the choice to focus on central estimates and not providing assessments on more unlikely outcomes is a choice that has consequences for what outcomes are taken into account in the decision-making process. This paper develops this argument and then analyzes the implications of these new developments for hydrological science. One implication of the increasing use of the new breed of planning strategies is that a broader range of uncertainty in scientific assessments becomes desirable in order to fully benefit from the power of the new decision-making strategies. Another implication is that bayesian probability assessments become more important. Finally, advantages and risks involved in changing scientific assessments in order to anticipate the new decision-making strategies are discussed.

Cognitive Fatigue Destabilizes Economic Decision Making Preferences and Strategies.

PubMed

Mullette-Gillman, O'Dhaniel A; Leong, Ruth L F; Kurnianingsih, Yoanna A

2015-01-01

It is common for individuals to engage in taxing cognitive activity for prolonged periods of time, resulting in cognitive fatigue that has the potential to produce significant effects in behaviour and decision making. We sought to examine whether cognitive fatigue modulates economic decision making. We employed a between-subject manipulation design, inducing fatigue through 60 to 90 minutes of taxing cognitive engagement against a control group that watched relaxing videos for a matched period of time. Both before and after the manipulation, participants engaged in two economic decision making tasks (one for gains and one for losses). The analyses focused on two areas of economic decision making--preferences and choice strategies. Uncertainty preferences (risk and ambiguity) were quantified as premium values, defined as the degree and direction in which participants alter the valuation of the gamble in comparison to the certain option. The strategies that each participant engaged in were quantified through a choice strategy metric, which contrasts the degree to which choice behaviour relies upon available satisficing or maximizing information. We separately examined these metrics for alterations within both the gains and losses domains, through the two choice tasks. The fatigue manipulation resulted in significantly greater levels of reported subjective fatigue, with correspondingly higher levels of reported effort during the cognitively taxing activity. Cognitive fatigue did not alter uncertainty preferences (risk or ambiguity) or informational strategies, in either the gains or losses domains. Rather, cognitive fatigue resulted in greater test-retest variability across most of our economic measures. These results indicate that cognitive fatigue destabilizes economic decision making, resulting in inconsistent preferences and informational strategies that may significantly reduce decision quality.

Influence of Uncertainty and Time Stress on Decision Making

DTIC Science & Technology

1993-10-01

a. . . . . . . . . . . . 23 A General Theoretical Framwork .a .........* 24 Concepts for Aiding Decisions Under Conditions of...seemed to be how they were conceptualizing uncer- tainty). A third, somewhat %tinor change would be to present participants with the COA after the

Managing the Risks of Climate Change and Terrorism

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

Rosa, Eugene; Dietz, Tom; Moss, Richard H.

2012-04-07

The article describes challenges to comparative risk assessment, a key approach for managing uncertainty in decision making, across diverse threats such as terrorism and climate change and argues new approaches will be particularly important in addressing decisions related to sustainability.

Characterizing Variability and Uncertainty in Exposure Assessments Improves links to Environmental Decision-Making

EPA Science Inventory

Environmental Decisions often rely upon observational data or model estimates. For instance, the evaluation of human health or ecological risks often includes information on pollutant emission rates, environmental concentrations, exposures, and exposure/dose-response data. Whet...

When ranchers don't know what to do: Care and rangeland management decision-making under uncertainity

USDA-ARS?s Scientific Manuscript database

This presentation asks: how do ranchers know what to do when they are faced with a decision under high levels of complexity and uncertainty? In the semi-arid Western Great Plains of North America, rancher decisions have implications for rangeland ecosystems and for livelihoods. Adaptive management r...

Exploring Best Practice Skills to Predict Uncertainties in Venture Capital Investment Decision-Making

NASA Astrophysics Data System (ADS)

Blum, David Arthur

Algae biodiesel is the sole sustainable and abundant transportation fuel source that can replace petrol diesel use; however, high competition and economic uncertainties exist, influencing independent venture capital decision making. Technology, market, management, and government action uncertainties influence competition and economic uncertainties in the venture capital industry. The purpose of this qualitative case study was to identify the best practice skills at IVC firms to predict uncertainty between early and late funding stages. The basis of the study was real options theory, a framework used to evaluate and understand the economic and competition uncertainties inherent in natural resource investment and energy derived from plant-based oils. Data were collected from interviews of 24 venture capital partners based in the United States who invest in algae and other renewable energy solutions. Data were analyzed by coding and theme development interwoven with the conceptual framework. Eight themes emerged: (a) expected returns model, (b) due diligence, (c) invest in specific sectors, (d) reduced uncertainty-late stage, (e) coopetition, (f) portfolio firm relationships, (g) differentiation strategy, and (h) modeling uncertainty and best practice. The most noteworthy finding was that predicting uncertainty at the early stage was impractical; at the expansion and late funding stages, however, predicting uncertainty was possible. The implications of these findings will affect social change by providing independent venture capitalists with best practice skills to increase successful exits, lessen uncertainty, and encourage increased funding of renewable energy firms, contributing to cleaner and healthier communities throughout the United States..

Aiding alternatives assessment with an uncertainty-tolerant hazard scoring method.

PubMed

Faludi, Jeremy; Hoang, Tina; Gorman, Patrick; Mulvihill, Martin

2016-11-01

This research developed a single-score system to simplify and clarify decision-making in chemical alternatives assessment, accounting for uncertainty. Today, assessing alternatives to hazardous constituent chemicals is a difficult task-rather than comparing alternatives by a single definitive score, many independent toxicological variables must be considered at once, and data gaps are rampant. Thus, most hazard assessments are only comprehensible to toxicologists, but business leaders and politicians need simple scores to make decisions. In addition, they must balance hazard against other considerations, such as product functionality, and they must be aware of the high degrees of uncertainty in chemical hazard data. This research proposes a transparent, reproducible method to translate eighteen hazard endpoints into a simple numeric score with quantified uncertainty, alongside a similar product functionality score, to aid decisions between alternative products. The scoring method uses Clean Production Action's GreenScreen as a guide, but with a different method of score aggregation. It provides finer differentiation between scores than GreenScreen's four-point scale, and it displays uncertainty quantitatively in the final score. Displaying uncertainty also illustrates which alternatives are early in product development versus well-defined commercial products. This paper tested the proposed assessment method through a case study in the building industry, assessing alternatives to spray polyurethane foam insulation containing methylene diphenyl diisocyanate (MDI). The new hazard scoring method successfully identified trade-offs between different alternatives, showing finer resolution than GreenScreen Benchmarking. Sensitivity analysis showed that different weighting schemes in hazard scores had almost no effect on alternatives ranking, compared to uncertainty from data gaps. Copyright © 2016 Elsevier Ltd. All rights reserved.

When Advisors' True Intentions Are in Question. How Do Bank Customers Cope with Uncertainty in Financial Consultancies?

PubMed

Mackinger, Barbara; Jonas, Eva; Mühlberger, Christina

2017-01-01

When making financial decisions bank customers are confronted with two types of uncertainty: first, return on investments is uncertain and there is a risk of losing money. Second, customers cannot be certain about their financial advisor's true intentions. This might decrease customers' willingness to cooperate with advisors. However, the uncertainty management model and fairness heuristic theory predict that in uncertain situations customers are willing to cooperate with financial advisors when they perceive fairness. In the current study, we investigated how perceived fairness in the twofold uncertain situations increased people's intended future cooperation with an advisor. We asked customers of financial consultancies about their experienced uncertainty regarding both the investment decision and the advisor's intentions. Moreover, we asked them about their perceived fairness, as well as their intention to cooperate with the advisor in the future. A three-way moderation analysis showed that customers who faced high uncertainty regarding the investment decision and high uncertainty regarding the advisor's true intentions indicated the lowest intended cooperation with the advisor but high fairness increased their cooperation. Interestingly, when people were only uncertain about the advisor's intentions (but certain about the decision) they indicated less cooperation than when they were only uncertain about the decision (but certain about the advisor's intentions). A mediated moderation analysis revealed that this relationship was explained by customers' lower trust in their advisors.

A formal framework for scenario development in support of environmental decision-making

USGS Publications Warehouse

Mahmoud, M.; Liu, Yajing; Hartmann, H.; Stewart, S.; Wagener, T.; Semmens, D.; Stewart, R.; Gupta, H.; Dominguez, D.; Dominguez, F.; Hulse, D.; Letcher, R.; Rashleigh, Brenda; Smith, C.; Street, R.; Ticehurst, J.; Twery, M.; van, Delden H.; Waldick, R.; White, D.; Winter, L.

2009-01-01

Scenarios are possible future states of the world that represent alternative plausible conditions under different assumptions. Often, scenarios are developed in a context relevant to stakeholders involved in their applications since the evaluation of scenario outcomes and implications can enhance decision-making activities. This paper reviews the state-of-the-art of scenario development and proposes a formal approach to scenario development in environmental decision-making. The discussion of current issues in scenario studies includes advantages and obstacles in utilizing a formal scenario development framework, and the different forms of uncertainty inherent in scenario development, as well as how they should be treated. An appendix for common scenario terminology has been attached for clarity. Major recommendations for future research in this area include proper consideration of uncertainty in scenario studies in particular in relation to stakeholder relevant information, construction of scenarios that are more diverse in nature, and sharing of information and resources among the scenario development research community. ?? 2008 Elsevier Ltd.

Conceptual, Methodological, and Ethical Problems in Communicating Uncertainty in Clinical Evidence

PubMed Central

Han, Paul K. J.

2014-01-01

The communication of uncertainty in clinical evidence is an important endeavor that poses difficult conceptual, methodological, and ethical problems. Conceptual problems include logical paradoxes in the meaning of probability and “ambiguity”— second-order uncertainty arising from the lack of reliability, credibility, or adequacy of probability information. Methodological problems include questions about optimal methods for representing fundamental uncertainties and for communicating these uncertainties in clinical practice. Ethical problems include questions about whether communicating uncertainty enhances or diminishes patient autonomy and produces net benefits or harms. This article reviews the limited but growing literature on these problems and efforts to address them and identifies key areas of focus for future research. It is argued that the critical need moving forward is for greater conceptual clarity and consistent representational methods that make the meaning of various uncertainties understandable, and for clinical interventions to support patients in coping with uncertainty in decision making. PMID:23132891

Catholic School Principals' Decision-Making and Problem-Solving Practices during Times of Change and Uncertainty: A North American Analysis

ERIC Educational Resources Information Center

Polka, Walter; Litchka, Peter; Mete, Rosina; Ayaga, Augustine

2016-01-01

The authors of the article outline a historical review of Catholic education and student enrollment in North America and a recent perspective of Catholic school principals' decision-making and problem-solving preferences. The purpose of this article is to provide the reader with an understanding of events which impacted the evolution of Catholic…

Estimating the Health Effects of Greenhouse Gas Mitigation Strategies: Addressing Parametric, Model, and Valuation Challenges

PubMed Central

Hess, Jeremy J.; Ebi, Kristie L.; Markandya, Anil; Balbus, John M.; Wilkinson, Paul; Haines, Andy; Chalabi, Zaid

2014-01-01

Background: Policy decisions regarding climate change mitigation are increasingly incorporating the beneficial and adverse health impacts of greenhouse gas emission reduction strategies. Studies of such co-benefits and co-harms involve modeling approaches requiring a range of analytic decisions that affect the model output. Objective: Our objective was to assess analytic decisions regarding model framework, structure, choice of parameters, and handling of uncertainty when modeling health co-benefits, and to make recommendations for improvements that could increase policy uptake. Methods: We describe the assumptions and analytic decisions underlying models of mitigation co-benefits, examining their effects on modeling outputs, and consider tools for quantifying uncertainty. Discussion: There is considerable variation in approaches to valuation metrics, discounting methods, uncertainty characterization and propagation, and assessment of low-probability/high-impact events. There is also variable inclusion of adverse impacts of mitigation policies, and limited extension of modeling domains to include implementation considerations. Going forward, co-benefits modeling efforts should be carried out in collaboration with policy makers; these efforts should include the full range of positive and negative impacts and critical uncertainties, as well as a range of discount rates, and should explicitly characterize uncertainty. We make recommendations to improve the rigor and consistency of modeling of health co-benefits. Conclusion: Modeling health co-benefits requires systematic consideration of the suitability of model assumptions, of what should be included and excluded from the model framework, and how uncertainty should be treated. Increased attention to these and other analytic decisions has the potential to increase the policy relevance and application of co-benefits modeling studies, potentially helping policy makers to maximize mitigation potential while simultaneously improving health. Citation: Remais JV, Hess JJ, Ebi KL, Markandya A, Balbus JM, Wilkinson P, Haines A, Chalabi Z. 2014. Estimating the health effects of greenhouse gas mitigation strategies: addressing parametric, model, and valuation challenges. Environ Health Perspect 122:447–455; http://dx.doi.org/10.1289/ehp.1306744 PMID:24583270

Follow the heart or the head? The interactive influence model of emotion and cognition.

PubMed

Luo, Jiayi; Yu, Rongjun

2015-01-01

The experience of emotion has a powerful influence on daily-life decision making. Following Plato's description of emotion and reason as two horses pulling us in opposite directions, modern dual-system models of decision making endorse the antagonism between reason and emotion. Decision making is perceived as the competition between an emotion system that is automatic but prone to error and a reason system that is slow but rational. The reason system (in "the head") reins in our impulses (from "the heart") and overrides our snap judgments. However, from Darwin's evolutionary perspective, emotion is adaptive, guiding us to make sound decisions in uncertainty. Here, drawing findings from behavioral economics and neuroeconomics, we provide a new model, labeled "The interactive influence model of emotion and cognition," to elaborate the relationship of emotion and reason in decision making. Specifically, in our model, we identify factors that determine when emotions override reason and delineate the type of contexts in which emotions help or hurt decision making. We then illustrate how cognition modulates emotion and how they cooperate to affect decision making.

Uncertainty and the difficulty of thinking through disjunctions.

PubMed

Shafir, E

1994-01-01

This paper considers the relationship between decision under uncertainty and thinking through disjunctions. Decision situations that lead to violations of Savage's sure-thing principle are examined, and a variety of simple reasoning problems that often generate confusion and error are reviewed. The common difficulty is attributed to people's reluctance to think through disjunctions. Instead of hypothetically traveling through the branches of a decision tree, it is suggested, people suspend judgement and remain at the node. This interpretation is applied to instances of decision making, information search, deductive and inductive reasoning, probabilistic judgement, games, puzzles and paradoxes. Some implications of the reluctance to think through disjunctions, as well as potential corrective procedures, are discussed.

"Maybe the Algae Was from the Filter": Maybe and Similar Modifiers as Mediational Tools and Indicators of Uncertainty and Possibility in Children's Science Talk

ERIC Educational Resources Information Center

Kirch, Susan A.; Siry, Christina A.

2012-01-01

Uncertainty is an essential component of scientific inquiry and it also permeates our daily lives. Understanding how to identify, evaluate, resolve and live in the presence of uncertainty is important for decision-making strategies and engaging in transformative actions. In contrast, confidence and certainty are prized in elementary school…

Bayesian Monte Carlo and Maximum Likelihood Approach for Uncertainty Estimation and Risk Management: Application to Lake Oxygen Recovery Model

EPA Science Inventory

Model uncertainty estimation and risk assessment is essential to environmental management and informed decision making on pollution mitigation strategies. In this study, we apply a probabilistic methodology, which combines Bayesian Monte Carlo simulation and Maximum Likelihood e...

Decision making under uncertainty in a spiking neural network model of the basal ganglia.

PubMed

Héricé, Charlotte; Khalil, Radwa; Moftah, Marie; Boraud, Thomas; Guthrie, Martin; Garenne, André

2016-12-01

The mechanisms of decision-making and action selection are generally thought to be under the control of parallel cortico-subcortical loops connecting back to distinct areas of cortex through the basal ganglia and processing motor, cognitive and limbic modalities of decision-making. We have used these properties to develop and extend a connectionist model at a spiking neuron level based on a previous rate model approach. This model is demonstrated on decision-making tasks that have been studied in primates and the electrophysiology interpreted to show that the decision is made in two steps. To model this, we have used two parallel loops, each of which performs decision-making based on interactions between positive and negative feedback pathways. This model is able to perform two-level decision-making as in primates. We show here that, before learning, synaptic noise is sufficient to drive the decision-making process and that, after learning, the decision is based on the choice that has proven most likely to be rewarded. The model is then submitted to lesion tests, reversal learning and extinction protocols. We show that, under these conditions, it behaves in a consistent manner and provides predictions in accordance with observed experimental data.

Combination of uncertainty theories and decision-aiding methods for natural risk management in a context of imperfect information

NASA Astrophysics Data System (ADS)

Tacnet, Jean-Marc; Dupouy, Guillaume; Carladous, Simon; Dezert, Jean; Batton-Hubert, Mireille

2017-04-01

In mountain areas, natural phenomena such as snow avalanches, debris-flows and rock-falls, put people and objects at risk with sometimes dramatic consequences. Risk is classically considered as a combination of hazard, the combination of the intensity and frequency of the phenomenon, and vulnerability which corresponds to the consequences of the phenomenon on exposed people and material assets. Risk management consists in identifying the risk level as well as choosing the best strategies for risk prevention, i.e. mitigation. In the context of natural phenomena in mountainous areas, technical and scientific knowledge is often lacking. Risk management decisions are therefore based on imperfect information. This information comes from more or less reliable sources ranging from historical data, expert assessments, numerical simulations etc. Finally, risk management decisions are the result of complex knowledge management and reasoning processes. Tracing the information and propagating information quality from data acquisition to decisions are therefore important steps in the decision-making process. One major goal today is therefore to assist decision-making while considering the availability, quality and reliability of information content and sources. A global integrated framework is proposed to improve the risk management process in a context of information imperfection provided by more or less reliable sources: uncertainty as well as imprecision, inconsistency and incompleteness are considered. Several methods are used and associated in an original way: sequential decision context description, development of specific multi-criteria decision-making methods, imperfection propagation in numerical modeling and information fusion. This framework not only assists in decision-making but also traces the process and evaluates the impact of information quality on decision-making. We focus and present two main developments. The first one relates to uncertainty and imprecision propagation in numerical modeling using both classical Monte-Carlo probabilistic approach and also so-called Hybrid approach using possibility theory. Second approach deals with new multi-criteria decision-making methods which consider information imperfection, source reliability, importance and conflict, using fuzzy sets as well as possibility and belief function theories. Implemented methods consider information imperfection propagation and information fusion in total aggregation methods such as AHP (Saaty, 1980) or partial aggregation methods such as the Electre outranking method (see Soft Electre Tri ) or decisions in certain but also risky or uncertain contexts (see new COWA-ER and FOWA-ER- Cautious and Fuzzy Ordered Weighted Averaging-Evidential Reasoning). For example, the ER-MCDA methodology considers expert assessment as a multi-criteria decision process based on imperfect information provided by more or less heterogeneous, reliable and conflicting sources: it mixes AHP, fuzzy sets theory, possibility theory and belief function theory using DSmT (Dezert-Smarandache Theory) framework which provides powerful fusion rules.

A review of uncertainty research in impact assessment

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

Leung, Wanda, E-mail: wanda.leung@usask.ca; Noble, Bram, E-mail: b.noble@usask.ca; Gunn, Jill, E-mail: jill.gunn@usask.ca

2015-01-15

This paper examines uncertainty research in Impact Assessment (IA) and the focus of attention of the IA scholarly literature. We do so by first exploring ‘outside’ the IA literature, identifying three main themes of uncertainty research, and then apply these themes to examine the focus of scholarly research on uncertainty ‘inside’ IA. Based on a search of the database Scopus, we identified 134 journal papers published between 1970 and 2013 that address uncertainty in IA, 75% of which were published since 2005. We found that 90% of IA research addressing uncertainty focused on uncertainty in the practice of IA, includingmore » uncertainty in impact predictions, models and managing environmental impacts. Notwithstanding early guidance on uncertainty treatment in IA from the 1980s, we found no common, underlying conceptual framework that was guiding research on uncertainty in IA practice. Considerably less attention, only 9% of papers, focused on uncertainty communication, disclosure and decision-making under uncertain conditions, the majority of which focused on the need to disclose uncertainties as opposed to providing guidance on how to do so and effectively use that information to inform decisions. Finally, research focused on theory building for explaining human behavior with respect to uncertainty avoidance constituted only 1% of the IA published literature. We suggest the need for further conceptual framework development for researchers focused on identifying and addressing uncertainty in IA practice; the need for guidance on how best to communicate uncertainties in practice, versus criticizing practitioners for not doing so; research that explores how best to interpret and use disclosures about uncertainty when making decisions about project approvals, and the implications of doing so; and academic theory building and exploring the utility of existing theories to better understand and explain uncertainty avoidance behavior in IA. - Highlights: • We identified three main themes of uncertainty research in 134 papers from the scholarly literature. • The majority of research has focused on better methods for managing uncertainty in predictions. • Uncertainty disclosure is demanded of practitioners, but there is little guidance on how to do so. • There is limited theoretical explanation as to why uncertainty is avoided or not disclosed. • Conceptual, practical and theoretical guidance are required for IA uncertainty consideration.« less

Incorporating population viability models into species status assessment and listing decisions under the U.S. Endangered Species Act

USGS Publications Warehouse

McGowan, Conor P.; Allan, Nathan; Servoss, Jeff; Hedwall, Shaula J.; Wooldridge, Brian

2017-01-01

Assessment of a species' status is a key part of management decision making for endangered and threatened species under the U.S. Endangered Species Act. Predicting the future state of the species is an essential part of species status assessment, and projection models can play an important role in developing predictions. We built a stochastic simulation model that incorporated parametric and environmental uncertainty to predict the probable future status of the Sonoran desert tortoise in the southwestern United States and North Central Mexico. Sonoran desert tortoise was a Candidate species for listing under the Endangered Species Act, and decision makers wanted to use model predictions in their decision making process. The model accounted for future habitat loss and possible effects of climate change induced droughts to predict future population growth rates, abundances, and quasi-extinction probabilities. Our model predicts that the population will likely decline over the next few decades, but there is very low probability of quasi-extinction less than 75 years into the future. Increases in drought frequency and intensity may increase extinction risk for the species. Our model helped decision makers predict and characterize uncertainty about the future status of the species in their listing decision. We incorporated complex ecological processes (e.g., climate change effects on tortoises) in transparent and explicit ways tailored to support decision making processes related to endangered species.

Socio-Hydrology Modelling for an Uncertain Future, with Examples from the USA and Canada (Invited)

NASA Astrophysics Data System (ADS)

White, D. D.; Gober, P.; Sampson, D. A.; Quay, R.; Kirkwood, C.

2013-12-01

Socio-hydrology brings an interest in human values, markets, social organizations and public policy to the traditional emphasis of water science on climate, hydrology, toxicology,and ecology. It also conveys a decision focus in the form of decision support tools, engagement, and new knowledge about the science-policy interface. This paper demonstrates how policy decisions and human behavior can be better integrated into climate and hydrological models to improve their usefulness for support in decision making. Examples from the Southwest USA and Western Canada highlight uncertainties, vulnerabilities, and critical tradeoffs facing water decision makers in the face of rapidly changing environmental and societal conditions. Irreducible uncertainties in downscaled climate and hydrological models limit the usefulness of climate-driven, predict-and-plan methods of water resource planning and management. Thus, it is argued that such methods should be replaced by approaches that use exploratory modelling, scenario planning, and risk assessment in which the emphasis is on managing uncertainty rather than on reducing it.

Implicit knowledge of visual uncertainty guides decisions with asymmetric outcomes.

PubMed

Whiteley, Louise; Sahani, Maneesh

2008-03-06

Perception is an "inverse problem," in which the state of the world must be inferred from the sensory neural activity that results. However, this inference is both ill-posed (Helmholtz, 1856; Marr, 1982) and corrupted by noise (Green & Swets, 1989), requiring the brain to compute perceptual beliefs under conditions of uncertainty. Here we show that human observers performing a simple visual choice task under an externally imposed loss function approach the optimal strategy, as defined by Bayesian probability and decision theory (Berger, 1985; Cox, 1961). In concert with earlier work, this suggests that observers possess a model of their internal uncertainty and can utilize this model in the neural computations that underlie their behavior (Knill & Pouget, 2004). In our experiment, optimal behavior requires that observers integrate the loss function with an estimate of their internal uncertainty rather than simply requiring that they use a modal estimate of the uncertain stimulus. Crucially, they approach optimal behavior even when denied the opportunity to learn adaptive decision strategies based on immediate feedback. Our data thus support the idea that flexible representations of uncertainty are pre-existing, widespread, and can be propagated to decision-making areas of the brain.

Dynamics of Sequential Decision Making

NASA Astrophysics Data System (ADS)

Rabinovich, Mikhail I.; Huerta, Ramón; Afraimovich, Valentin

2006-11-01

We suggest a new paradigm for intelligent decision-making suitable for dynamical sequential activity of animals or artificial autonomous devices that depends on the characteristics of the internal and external world. To do it we introduce a new class of dynamical models that are described by ordinary differential equations with a finite number of possibilities at the decision points, and also include rules solving this uncertainty. Our approach is based on the competition between possible cognitive states using their stable transient dynamics. The model controls the order of choosing successive steps of a sequential activity according to the environment and decision-making criteria. Two strategies (high-risk and risk-aversion conditions) that move the system out of an erratic environment are analyzed.

Fuzzy approaches to supplier selection problem

NASA Astrophysics Data System (ADS)

Ozkok, Beyza Ahlatcioglu; Kocken, Hale Gonce

2013-09-01

Supplier selection problem is a multi-criteria decision making problem which includes both qualitative and quantitative factors. In the selection process many criteria may conflict with each other, therefore decision-making process becomes complicated. In this study, we handled the supplier selection problem under uncertainty. In this context; we used minimum criterion, arithmetic mean criterion, regret criterion, optimistic criterion, geometric mean and harmonic mean. The membership functions created with the help of the characteristics of used criteria, and we tried to provide consistent supplier selection decisions by using these memberships for evaluating alternative suppliers. During the analysis, no need to use expert opinion is a strong aspect of the methodology used in the decision-making.

When irrelevance matters: Stimulus-response binding in decision making under uncertainty.

PubMed

Nett, Nadine; Bröder, Arndt; Frings, Christian

2015-11-01

According to distractor-based response retrieval (Frings, Rothermund, & Wentura, 2007), irrelevant information will be integrated with the response to the relevant stimuli and further, the immediate repetition of irrelevant information can retrieve the previously executed response thereby influencing responding to the current target (leading either to benefits or costs if the retrieved response is compatible or incompatible, respectively, to the currently demanded response). We analyzed whether this effect also holds for decisions rather than simple motoric reactions. The hypothesis was tested in 4 experiments in which participants had to decide as fast as possible which disease an imagined patient suffered from. The decisions were based on 2 cues; 1 did not give any hint for a disease (the irrelevant cue), whereas the other did (the relevant cue). We found a significant influence of repeating the irrelevant cue on decision behavior. That is, participants tended to repeat their decision if the irrelevant cue was repeated in the following decision situation. Thus, stimulus-response binding which typically is discussed in basic processes of perception and action has also implications for arguably more deliberative cognitive processes in decision making under uncertainty. (c) 2015 APA, all rights reserved).

Environmental change challenges decision-making during post-market environmental monitoring of transgenic crops.

PubMed

Sanvido, Olivier; Romeis, Jörg; Bigler, Franz

2011-12-01

The ability to decide what kind of environmental changes observed during post-market environmental monitoring of genetically modified (GM) crops represent environmental harm is an essential part of most legal frameworks regulating the commercial release of GM crops into the environment. Among others, such decisions are necessary to initiate remedial measures or to sustain claims of redress linked to environmental liability. Given that consensus on criteria to evaluate 'environmental harm' has not yet been found, there are a number of challenges for risk managers when interpreting GM crop monitoring data for environmental decision-making. In the present paper, we argue that the challenges in decision-making have four main causes. The first three causes relate to scientific data collection and analysis, which have methodological limits. The forth cause concerns scientific data evaluation, which is controversial among the different stakeholders involved in the debate on potential impacts of GM crops on the environment. This results in controversy how the effects of GM crops should be valued and what constitutes environmental harm. This controversy may influence decision-making about triggering corrective actions by regulators. We analyse all four challenges and propose potential strategies for addressing them. We conclude that environmental monitoring has its limits in reducing uncertainties remaining from the environmental risk assessment prior to market approval. We argue that remaining uncertainties related to adverse environmental effects of GM crops would probably be assessed in a more efficient and rigorous way during pre-market risk assessment. Risk managers should acknowledge the limits of environmental monitoring programmes as a tool for decision-making.

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

Democracy under Uncertainty: The Wisdom of Crowds and the Free-Rider Problem in Group Decision Making

ERIC Educational Resources Information Center

Kameda, Tatsuya; Tsukasaki, Takafumi; Hastie, Reid; Berg, Nathan

2011-01-01

We introduce a game theory model of individual decisions to cooperate by contributing personal resources to group decisions versus by free riding on the contributions of other members. In contrast to most public-goods games that assume group returns are linear in individual contributions, the present model assumes decreasing marginal group…

Monitoring in the context of structured decision-making and adaptive management

USGS Publications Warehouse

Lyons, J.E.; Runge, M.C.; Laskowski, H.P.; Kendall, W.L.

2008-01-01

In a natural resource management setting, monitoring is a crucial component of an informed process for making decisions, and monitoring design should be driven by the decision context and associated uncertainties. Monitoring itself can play >3 roles. First, it is important for state-dependent decision-making, as when managers need to know the system state before deciding on the appropriate course of action during the ensuing management cycle. Second, monitoring is critical for evaluating the effectiveness of management actions relative to objectives. Third, in an adaptive management setting, monitoring provides the feedback loop for learning about the system; learning is sought not for its own sake but primarily to better achieve management objectives. In this case, monitoring should be designed to reduce the critical uncertainties in models of the managed system. The United States Geological Survey and United States Fish and Wildlife Service are conducting a large-scale management experiment on 23 National Wildlife Refuges across the Northeast and Midwest Regions. The primary management objective is to provide habitat for migratory waterbirds, particularly during migration, using water-level manipulations in managed wetlands. Key uncertainties are related to the potential trade-offs created by management for a specific waterbird guild (e.g., migratory shorebirds) and the response of waterbirds, plant communities, and invertebrates to specific experimental hydroperiods. We reviewed the monitoring program associated with this study, and the ways that specific observations fill >1 of the roles identified above. We used observations from our monitoring to improve state-dependent decisions to control undesired plants, to evaluate management performance relative to shallow-water habitat objectives, and to evaluate potential trade-offs between waterfowl and shorebird habitat management. With limited staff and budgets, management agencies need efficient monitoring programs that are used for decision-making, not comprehensive studies that elucidate all manner of ecological relationships.

Evaluation of uncertainty in determination of neutral axis and deformed shape of beam structures : final report.

DOT National Transportation Integrated Search

2016-01-01

With aging infrastructure, it becomes crucial to make informed decisions about maintenance and : preservation actions, as well as renewal of civil structures. Structural Health Monitoring (SHM) can be : an important aid in this decision process, but ...

Affordability and cost-effectiveness: decision-making on the cost-effectiveness plane.

PubMed

Sendi, P P; Briggs, A H

2001-10-01

Much recent research interest has focused on handling uncertainty in cost-effectiveness analysis and in particular the calculation of confidence intervals for incremental cost-effectiveness ratios (ICERs). Problems of interpretation when ICERs are negative have led to two important and related developments: the use of the net-benefit statistic and the presentation of uncertainty in cost-effectiveness analysis using acceptability curves. However, neither of these developments directly addresses the problem that decision-makers are constrained by a fixed-budget and may not be able to fund new, more expensive interventions, even if they have been shown to represent good value for money. In response to this limitation, the authors introduce the 'affordability curve' which reflects the probability that a programme is affordable for a wide range of threshold budgets. The authors argue that the joint probability an intervention is affordable and cost-effective is more useful for decision-making since it captures both dimensions of the decision problem faced by those responsible for health service budgets. Copyright 2001 John Wiley & Sons, Ltd.

Cognitive Fatigue Destabilizes Economic Decision Making Preferences and Strategies

PubMed Central

Mullette-Gillman, O’Dhaniel A.; Leong, Ruth L. F.; Kurnianingsih, Yoanna A.

2015-01-01

Objective It is common for individuals to engage in taxing cognitive activity for prolonged periods of time, resulting in cognitive fatigue that has the potential to produce significant effects in behaviour and decision making. We sought to examine whether cognitive fatigue modulates economic decision making. Methods We employed a between-subject manipulation design, inducing fatigue through 60 to 90 minutes of taxing cognitive engagement against a control group that watched relaxing videos for a matched period of time. Both before and after the manipulation, participants engaged in two economic decision making tasks (one for gains and one for losses). The analyses focused on two areas of economic decision making—preferences and choice strategies. Uncertainty preferences (risk and ambiguity) were quantified as premium values, defined as the degree and direction in which participants alter the valuation of the gamble in comparison to the certain option. The strategies that each participant engaged in were quantified through a choice strategy metric, which contrasts the degree to which choice behaviour relies upon available satisficing or maximizing information. We separately examined these metrics for alterations within both the gains and losses domains, through the two choice tasks. Results The fatigue manipulation resulted in significantly greater levels of reported subjective fatigue, with correspondingly higher levels of reported effort during the cognitively taxing activity. Cognitive fatigue did not alter uncertainty preferences (risk or ambiguity) or informational strategies, in either the gains or losses domains. Rather, cognitive fatigue resulted in greater test-retest variability across most of our economic measures. These results indicate that cognitive fatigue destabilizes economic decision making, resulting in inconsistent preferences and informational strategies that may significantly reduce decision quality. PMID:26230404

Uncertainty indication in soil function maps - transparent and easy-to-use information to support sustainable use of soil resources

NASA Astrophysics Data System (ADS)

Greiner, Lucie; Nussbaum, Madlene; Papritz, Andreas; Zimmermann, Stephan; Gubler, Andreas; Grêt-Regamey, Adrienne; Keller, Armin

2018-05-01

Spatial information on soil function fulfillment (SFF) is increasingly being used to inform decision-making in spatial planning programs to support sustainable use of soil resources. Soil function maps visualize soils abilities to fulfill their functions, e.g., regulating water and nutrient flows, providing habitats, and supporting biomass production based on soil properties. Such information must be reliable for informed and transparent decision-making in spatial planning programs. In this study, we add to the transparency of soil function maps by (1) indicating uncertainties arising from the prediction of soil properties generated by digital soil mapping (DSM) that are used for soil function assessment (SFA) and (2) showing the response of different SFA methods to the propagation of uncertainties through the assessment. For a study area of 170 km2 in the Swiss Plateau, we map 10 static soil sub-functions for agricultural soils for a spatial resolution of 20 × 20 m together with their uncertainties. Mapping the 10 soil sub-functions using simple ordinal assessment scales reveals pronounced spatial patterns with a high variability of SFF scores across the region, linked to the inherent properties of the soils and terrain attributes and climate conditions. Uncertainties in soil properties propagated through SFA methods generally lead to substantial uncertainty in the mapped soil sub-functions. We propose two types of uncertainty maps that can be readily understood by stakeholders. Cumulative distribution functions of SFF scores indicate that SFA methods respond differently to the propagated uncertainty of soil properties. Even where methods are comparable on the level of complexity and assessment scale, their comparability in view of uncertainty propagation might be different. We conclude that comparable uncertainty indications in soil function maps are relevant to enable informed and transparent decisions on the sustainable use of soil resources.

Benefits and limitations of using decision analytic tools to assess uncertainty and prioritize Landscape Conservation Cooperative information needs

USGS Publications Warehouse

Post van der Burg, Max; Cullinane Thomas, Catherine; Holcombe, Tracy R.; Nelson, Richard D.

2016-01-01

The Landscape Conservation Cooperatives (LCCs) are a network of partnerships throughout North America that are tasked with integrating science and management to support more effective delivery of conservation at a landscape scale. In order to achieve this integration, some LCCs have adopted the approach of providing their partners with better scientific information in an effort to facilitate more effective and coordinated conservation decisions. Taking this approach has led many LCCs to begin funding research to provide the information for improved decision making. To ensure that funding goes to research projects with the highest likelihood of leading to more integrated broad scale conservation, some LCCs have also developed approaches for prioritizing which information needs will be of most benefit to their partnerships. We describe two case studies in which decision analytic tools were used to quantitatively assess the relative importance of information for decisions made by partners in the Plains and Prairie Potholes LCC. The results of the case studies point toward a few valuable lessons in terms of using these tools with LCCs. Decision analytic tools tend to help shift focus away from research oriented discussions and toward discussions about how information is used in making better decisions. However, many technical experts do not have enough knowledge about decision making contexts to fully inform the latter type of discussion. When assessed in the right decision context, however, decision analyses can point out where uncertainties actually affect optimal decisions and where they do not. This helps technical experts understand that not all research is valuable in improving decision making. But perhaps most importantly, our results suggest that decision analytic tools may be more useful for LCCs as way of developing integrated objectives for coordinating partner decisions across the landscape, rather than simply ranking research priorities.

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.

Breaking the sound barrier: exploring parents' decision-making process of cochlear implants for their children.

PubMed

Chang, Pamara F

2017-08-01

To understand the dynamic experiences of parents undergoing the decision-making process regarding cochlear implants for their child(ren). Thirty-three parents of d/Deaf children participated in semi-structured interviews. Interviews were digitally recorded, transcribed, and coded using iterative and thematic coding. The results from this study reveal four salient topics related to parents' decision-making process regarding cochlear implantation: 1) factors parents considered when making the decision to get the cochlear implant for their child (e.g., desire to acculturate child into one community), 2) the extent to which parents' communities influence their decision-making (e.g., norms), 3) information sources parents seek and value when decision-making (e.g., parents value other parent's experiences the most compared to medical or online sources), and 4) personal experiences with stigma affecting their decision to not get the cochlear implant for their child. This study provides insights into values and perspectives that can be utilized to improve informed decision-making, when making risky medical decisions with long-term implications. With thorough information provisions, delineation of addressing parents' concerns and encompassing all aspects of the decision (i.e., medical, social and cultural), health professional teams could reduce the uncertainty and anxiety for parents in this decision-making process for cochlear implantation. Copyright © 2017 Elsevier B.V. All rights reserved.

A Framework to Determine New System Requirements Under Design Parameter and Demand Uncertainties

DTIC Science & Technology

2015-04-30

relegates quantitative complexities of decision-making to the method and designates trade-space exploration to the practitioner. We demonstrate the...quantitative complexities of decision-making to the method and designates trade-space exploration to the practitioner. We demonstrate the approach...play a critical role in determining new system requirements. Scope and Method of Approach The early stages of the design process have substantial

A Conceptual Framework for Decision-making Support in Uncertainty- and Risk-based Diagnosis of Rare Clinical Cases by Specialist Physicians.

PubMed

Santos, Adriano A; Moura, J Antão B; de Araújo, Joseana Macêdo Fechine Régis

2015-01-01

Mitigating uncertainty and risks faced by specialist physicians in analysis of rare clinical cases is something desired by anyone who needs health services. The number of clinical cases never seen by these experts, with little documentation, may introduce errors in decision-making. Such errors negatively affect well-being of patients, increase procedure costs, rework, health insurance premiums, and impair the reputation of specialists and medical systems involved. In this context, IT and Clinical Decision Support Systems (CDSS) play a fundamental role, supporting decision-making process, making it more efficient and effective, reducing a number of avoidable medical errors and enhancing quality of treatment given to patients. An investigation has been initiated to look into characteristics and solution requirements of this problem, model it, propose a general solution in terms of a conceptual risk-based, automated framework to support rare-case medical diagnostics and validate it by means of case studies. A preliminary validation study of the proposed framework has been carried out by interviews conducted with experts who are practicing professionals, academics, and researchers in health care. This paper summarizes the investigation and its positive results. These results motivate continuation of research towards development of the conceptual framework and of a software tool that implements the proposed model.

Risk-based decision making to manage water quality failures caused by combined sewer overflows

NASA Astrophysics Data System (ADS)

Sriwastava, A. K.; Torres-Matallana, J. A.; Tait, S.; Schellart, A.

2017-12-01

Regulatory authorities set certain environmental permit for water utilities such that the combined sewer overflows (CSO) managed by these companies conform to the regulations. These utility companies face the risk of paying penalty or negative publicity in case they breach the environmental permit. These risks can be addressed by designing appropriate solutions such as investing in additional infrastructure which improve the system capacity and reduce the impact of CSO spills. The performance of these solutions is often estimated using urban drainage models. Hence, any uncertainty in these models can have a significant effect on the decision making process. This study outlines a risk-based decision making approach to address water quality failure caused by CSO spills. A calibrated lumped urban drainage model is used to simulate CSO spill quality in Haute-Sûre catchment in Luxembourg. Uncertainty in rainfall and model parameters is propagated through Monte Carlo simulations to quantify uncertainty in the concentration of ammonia in the CSO spill. A combination of decision alternatives such as the construction of a storage tank at the CSO and the reduction in the flow contribution of catchment surfaces are selected as planning measures to avoid the water quality failure. Failure is defined as exceedance of a concentration-duration based threshold based on Austrian emission standards for ammonia (De Toffol, 2006) with a certain frequency. For each decision alternative, uncertainty quantification results into a probability distribution of the number of annual CSO spill events which exceed the threshold. For each alternative, a buffered failure probability as defined in Rockafellar & Royset (2010), is estimated. Buffered failure probability (pbf) is a conservative estimate of failure probability (pf), however, unlike failure probability, it includes information about the upper tail of the distribution. A pareto-optimal set of solutions is obtained by performing mean- pbf optimization. The effectiveness of using buffered failure probability compared to the failure probability is tested by comparing the solutions obtained by using mean-pbf and mean-pf optimizations.

Social Expectations Bias Decision-Making in Uncertain Inter-Personal Situations

PubMed Central

Ruz, María; Moser, Anna; Webster, Kristin

2011-01-01

Understanding the role that social cues have on interpersonal choice, and their susceptibility to contextual effects, is of core importance to models of social decision-making. Language, on the other hand, is one of the main means of communication during social interactions in our culture. The present experiments tested whether positive and negative linguistic descriptions of alleged partners in a modified Ultimatum Game biased decisions made to the same set of offers, and whether the contextual uncertainty of the game modulated this biasing effect. The results showed that in an uncertain context, the same offers were accepted with higher probability when they were preceded by positive rather than by negative valenced trait-words. Participants also accepted fair offers with higher probability than unfair offers, but this effect did not interact with the valence of the social descriptive words. In addition, the speed of the decision was affected by valence: acceptance choices were faster when they followed a positive adjective, whereas rejection responses were faster after a negative-valenced word. However, these effects were highly reduced when the uncertainty was eliminated from the game. This suggests that positive and negative relevant social information can bias decisions made to the same pieces of evidence during interpersonal interactions, but that this mainly takes place when the uncertainty associated with the choices is high. PMID:21347404

Development of fuzzy multi-criteria approach to prioritize locations of treated wastewater use considering climate change scenarios.

PubMed

Chung, Eun-Sung; Kim, Yeonjoo

2014-12-15

This study proposed a robust prioritization framework to identify the priorities of treated wastewater (TWW) use locations with consideration of various uncertainties inherent in the climate change scenarios and the decision-making process. First, a fuzzy concept was applied because future forecast precipitation and their hydrological impact analysis results displayed significant variances when considering various climate change scenarios and long periods (e.g., 2010-2099). Second, various multi-criteria decision making (MCDM) techniques including weighted sum method (WSM), Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and fuzzy TOPSIS were introduced to robust prioritization because different MCDM methods use different decision philosophies. Third, decision making method under complete uncertainty (DMCU) including maximin, maximax, minimax regret, Hurwicz, and equal likelihood were used to find robust final rankings. This framework is then applied to a Korean urban watershed. As a result, different rankings were obviously appeared between fuzzy TOPSIS and non-fuzzy MCDMs (e.g., WSM and TOPSIS) because the inter-annual variability in effectiveness was considered only with fuzzy TOPSIS. Then, robust prioritizations were derived based on 18 rankings from nine decadal periods of RCP4.5 and RCP8.5. For more robust rankings, five DMCU approaches using the rankings from fuzzy TOPSIS were derived. This framework combining fuzzy TOPSIS with DMCU approaches can be rendered less controversial among stakeholders under complete uncertainty of changing environments. Copyright © 2014 Elsevier Ltd. All rights reserved.

Parameter Uncertainties for a 10-Meter Ground-Based Optical Reception Station

NASA Technical Reports Server (NTRS)

Shaik, K.

1990-01-01

Performance uncertainties for a 10-m optical reception station may arise from the nature of the communications channel or from a specific technology choice. Both types of uncertainties are described in this article to develop an understanding of the limitations imposed by them and to provide a rational basis for making technical decisions. The performance at night will be considerably higher than for daytime reception.

How can surgeons facilitate resident intraoperative decision-making?

PubMed

Hill, Katherine A; Dasari, Mohini; Littleton, Eliza B; Hamad, Giselle G

2017-10-01

Cognitive skills such as decision-making are critical to developing operative autonomy. We explored resident decision-making using a recollection of specific examples, from the attending surgeon and resident, after laparoscopic cholecystectomy. In a separate semi-structured interview, the attending and resident both answered five questions, regarding the resident's operative roles and decisions, ways the attending helped, times when the attending operated, and the effect of the relationship between attending and resident. Themes were extracted using inductive methods. Thirty interviews were completed after 15 cases. Facilitators of decision-making included dialogue, safe struggle, and appreciation for retraction. Aberrant case characteristics, anatomic uncertainties, and time pressures provided barriers. Attending-resident mismatches included descriptions of transitioning control to the attending. Reciprocal dialogue, including concept-driven feedback, is helpful during intraoperative teaching. Unanticipated findings impede resident decision-making, and we describe differences in understanding transfers of operative control. Given these factors, we suggest that pre-operative discussions may be beneficial. Copyright © 2017 Elsevier Inc. All rights reserved.

The Montreal Protocol treaty and its illuminating history of science-policy decision-making

NASA Astrophysics Data System (ADS)

Grady, C.

2017-12-01

The Montreal Protocol on Substances that Deplete the Ozone Layer, hailed as one of the most effective environmental treaties of all time, has a thirty year history of science-policy decision-making. The partnership between Parties to the Montreal Protocol and its technical assessment panels serve as a basis for understanding successes and evaluating stumbles of global environmental decision-making. Real-world environmental treaty negotiations can be highly time-sensitive, politically motivated, and resource constrained thus scientists and policymakers alike are often unable to confront the uncertainties associated with the multitude of choices. The science-policy relationship built within the framework of the Montreal Protocol has helped constrain uncertainty and inform policy decisions but has also highlighted the limitations of the use of scientific understanding in political decision-making. This talk will describe the evolution of the scientist-policymaker relationship over the history of the Montreal Protocol. Examples will illustrate how the Montreal Protocol's technical panels inform decisions of the country governments and will characterize different approaches pursued by different countries with a particular focus on the recently adopted Kigali Amendment. In addition, this talk will take a deeper dive with an analysis of the historic technical panel assessments on estimating financial resources necessary to enable compliance to the Montreal Protocol compared to the political financial decisions made through the Protocol's Multilateral Fund replenishment negotiation process. Finally, this talk will describe the useful lessons and challenges from these interactions and how they may be applicable in other environmental management frameworks across multiple scales under changing climatic conditions.

Anticipatory stress restores decision-making deficits in heavy drinkers by increasing sensitivity to losses.

PubMed

Gullo, Matthew J; Stieger, Adam A

2011-09-01

Substance abusers are characterized by hypersensitivity to reward. This leads to maladaptive decisions generally, as well as those on laboratory-based decision-making tasks, such as the Iowa Gambling Task (IGT). Negative affect has also been shown to disrupt the decision-making of healthy individuals, particularly decisions made under uncertainty. Neuropsychological theories of learning, including the Somatic Marker Hypothesis (SMH), argue this occurs by amplifying affective responses to punishment. In substance abusers, this might serve to rebalance their sensitivity to reward with punishment, and improve decision-making. Before completing the IGT, 45 heavy and 47 light drinkers were randomly assigned to a control condition, or led to believe they had to give a stressful public speech. IGT performance was analyzed with the Expectancy-Valence (EV) learning model. Working memory and IQ were also assessed. Heavy drinkers made more disadvantageous decisions than light drinkers, due to higher attention to gains (versus losses) on the IGT. Anticipatory stress increased participants' attention to losses, significantly improving heavy drinkers' decision-making. Anticipatory stress increased attention to losses, effectively restoring decision-making deficits in heavy drinkers by rebalancing their reward sensitivity with punishment sensitivity. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Use (and abuse) of expert elicitation in support of decision making for public policy

PubMed Central

Morgan, M. Granger

2014-01-01

The elicitation of scientific and technical judgments from experts, in the form of subjective probability distributions, can be a valuable addition to other forms of evidence in support of public policy decision making. This paper explores when it is sensible to perform such elicitation and how that can best be done. A number of key issues are discussed, including topics on which there are, and are not, experts who have knowledge that provides a basis for making informed predictive judgments; the inadequacy of only using qualitative uncertainty language; the role of cognitive heuristics and of overconfidence; the choice of experts; the development, refinement, and iterative testing of elicitation protocols that are designed to help experts to consider systematically all relevant knowledge when they make their judgments; the treatment of uncertainty about model functional form; diversity of expert opinion; and when it does or does not make sense to combine judgments from different experts. Although it may be tempting to view expert elicitation as a low-cost, low-effort alternative to conducting serious research and analysis, it is neither. Rather, expert elicitation should build on and use the best available research and analysis and be undertaken only when, given those, the state of knowledge will remain insufficient to support timely informed assessment and decision making. PMID:24821779

Type-2 fuzzy set extension of DEMATEL method combined with perceptual computing for decision making

NASA Astrophysics Data System (ADS)

Hosseini, Mitra Bokaei; Tarokh, Mohammad Jafar

2013-05-01

Most decision making methods used to evaluate a system or demonstrate the weak and strength points are based on fuzzy sets and evaluate the criteria with words that are modeled with fuzzy sets. The ambiguity and vagueness of the words and different perceptions of a word are not considered in these methods. For this reason, the decision making methods that consider the perceptions of decision makers are desirable. Perceptual computing is a subjective judgment method that considers that words mean different things to different people. This method models words with interval type-2 fuzzy sets that consider the uncertainty of the words. Also, there are interrelations and dependency between the decision making criteria in the real world; therefore, using decision making methods that cannot consider these relations is not feasible in some situations. The Decision-Making Trail and Evaluation Laboratory (DEMATEL) method considers the interrelations between decision making criteria. The current study used the combination of DEMATEL and perceptual computing in order to improve the decision making methods. For this reason, the fuzzy DEMATEL method was extended into type-2 fuzzy sets in order to obtain the weights of dependent criteria based on the words. The application of the proposed method is presented for knowledge management evaluation criteria.

The game of making decisions under uncertainty: How sure must one be?

NASA Astrophysics Data System (ADS)

Werner, Micha; Verkade, Jan; Wetterhall, Fredrik; van Andel, Schalk-Jan; Ramos, Maria-Helena

2016-04-01

Probabilistic hydrometeorological forecasting is now widely accepted to be more skillful than deterministic forecasts, and is increasingly being integrated into operational practice. Provided they are reliable and unbiased, probabilistic forecasts have the advantage that they give decision maker not only the forecast value, but also the uncertainty associated to that prediction. Though that information provides more insight, it does now leave the forecaster/decision maker with the challenge of deciding at what level of probability of a threshold being exceeded the decision to act should be taken. According to the cost-loss theory, that probability should be related to the impact of the threshold being exceeded. However, it is not entirely clear how easy it is for decision makers to follow that rule, even when the impact of a threshold being exceeded, and the actions to choose from are known. To continue the tradition in the "Ensemble Hydrometeorological Forecast" session, we will address the challenge of making decisions based on probabilistic forecasts through a game to be played with the audience. We will explore how decisions made differ depending on the known impacts of the forecasted events. Participants will be divided into a number of groups with differing levels of impact, and will be faced with a number of forecast situations. They will be asked to make decisions and record the consequence of those decisions. A discussion of the differences in the decisions made will be presented at the end of the game, with a fuller analysis later posted on the HEPEX web site blog (www.hepex.org).

Incorporating climate change into ecosystem service assessments and decisions: a review.

PubMed

Runting, Rebecca K; Bryan, Brett A; Dee, Laura E; Maseyk, Fleur J F; Mandle, Lisa; Hamel, Perrine; Wilson, Kerrie A; Yetka, Kathleen; Possingham, Hugh P; Rhodes, Jonathan R

2017-01-01

Climate change is having a significant impact on ecosystem services and is likely to become increasingly important as this phenomenon intensifies. Future impacts can be difficult to assess as they often involve long timescales, dynamic systems with high uncertainties, and are typically confounded by other drivers of change. Despite a growing literature on climate change impacts on ecosystem services, no quantitative syntheses exist. Hence, we lack an overarching understanding of the impacts of climate change, how they are being assessed, and the extent to which other drivers, uncertainties, and decision making are incorporated. To address this, we systematically reviewed the peer-reviewed literature that assesses climate change impacts on ecosystem services at subglobal scales. We found that the impact of climate change on most types of services was predominantly negative (59% negative, 24% mixed, 4% neutral, 13% positive), but varied across services, drivers, and assessment methods. Although uncertainty was usually incorporated, there were substantial gaps in the sources of uncertainty included, along with the methods used to incorporate them. We found that relatively few studies integrated decision making, and even fewer studies aimed to identify solutions that were robust to uncertainty. For management or policy to ensure the delivery of ecosystem services, integrated approaches that incorporate multiple drivers of change and account for multiple sources of uncertainty are needed. This is undoubtedly a challenging task, but ignoring these complexities can result in misleading assessments of the impacts of climate change, suboptimal management outcomes, and the inefficient allocation of resources for climate adaptation. © 2016 John Wiley & Sons Ltd.

Incorporating uncertainty into mercury-offset decisions with a probabilistic network for National Pollutant Discharge Elimination System permit holders: an interim report

USGS Publications Warehouse

Wood, Alexander

2004-01-01

This interim report describes an alternative approach for evaluating the efficacy of using mercury (Hg) offsets to improve water quality. Hg-offset programs may allow dischargers facing higher-pollution control costs to meet their regulatory obligations by making more cost effective pollutant-reduction decisions. Efficient Hg management requires methods to translate that science and economics into a regulatory decision framework. This report documents the work in progress by the U.S. Geological Surveys Western Geographic Science Center in collaboration with Stanford University toward developing this decision framework to help managers, regulators, and other stakeholders decide whether offsets can cost effectively meet the Hg total maximum daily load (TMDL) requirements in the Sacramento River watershed. Two key approaches being considered are: (1) a probabilistic approach that explicitly incorporates scientific uncertainty, cost information, and value judgments; and (2) a quantitative approach that captures uncertainty in testing the feasibility of Hg offsets. Current fate and transport-process models commonly attempt to predict chemical transformations and transport pathways deterministically. However, the physical, chemical, and biologic processes controlling the fate and transport of Hg in aquatic environments are complex and poorly understood. Deterministic models of Hg environmental behavior contain large uncertainties, reflecting this lack of understanding. The uncertainty in these underlying physical processes may produce similarly large uncertainties in the decisionmaking process. However, decisions about control strategies are still being made despite the large uncertainties in current Hg loadings, the relations between total Hg (HgT) loading and methylmercury (MeHg) formation, and the relations between control efforts and Hg content in fish. The research presented here focuses on an alternative analytical approach to the current use of safety factors and deterministic methods for Hg TMDL decision support, one that is fully compatible with an adaptive management approach. This alternative approach uses empirical data and informed judgment to provide a scientific and technical basis for helping National Pollutant Discharge Elimination System (NPDES) permit holders make management decisions. An Hg-offset system would be an option if a wastewater-treatment plant could not achieve NPDES permit requirements for HgT reduction. We develop a probabilistic decision-analytical model consisting of three submodels for HgT loading, MeHg, and cost mitigation within a Bayesian network that integrates information of varying rigor and detail into a simple model of a complex system. Hg processes are identified and quantified by using a combination of historical data, statistical models, and expert judgment. Such an integrated approach to uncertainty analysis allows easy updating of prediction and inference when observations of model variables are made. We demonstrate our approach with data from the Cache Creek watershed (a subbasin of the Sacramento River watershed). The empirical models used to generate the needed probability distributions are based on the same empirical models currently being used by the Central Valley Regional Water Quality Control Cache Creek Hg TMDL working group. The significant difference is that input uncertainty and error are explicitly included in the model and propagated throughout its algorithms. This work demonstrates how to integrate uncertainty into the complex and highly uncertain Hg TMDL decisionmaking process. The various sources of uncertainty are propagated as decision risk that allows decisionmakers to simultaneously consider uncertainties in remediation/implementation costs while attempting to meet environmental/ecologic targets. We must note that this research is on going. As more data are collected, the HgT and cost-mitigation submodels are updated and the uncer

RESTSIM: A Simulation Model That Highlights Decision Making under Conditions of Uncertainty.

ERIC Educational Resources Information Center

Zinkhan, George M.; Taylor, James R.

1983-01-01

Describes RESTSIM, an interactive computer simulation program for graduate and upper-level undergraduate management, marketing, and retailing courses, which introduces naive users to simulation as a decision support technique, and provides a vehicle for studying various statistical procedures for evaluating simulation output. (MBR)

Assessing climate change and socio-economic uncertainties in long term management of water resources

NASA Astrophysics Data System (ADS)

Jahanshahi, Golnaz; Dawson, Richard; Walsh, Claire; Birkinshaw, Stephen; Glenis, Vassilis

2015-04-01

Long term management of water resources is challenging for decision makers given the range of uncertainties that exist. Such uncertainties are a function of long term drivers of change, such as climate, environmental loadings, demography, land use and other socio economic drivers. Impacts of climate change on frequency of extreme events such as drought make it a serious threat to water resources and water security. The release of probabilistic climate information, such as the UKCP09 scenarios, provides improved understanding of some uncertainties in climate models. This has motivated a more rigorous approach to dealing with other uncertainties in order to understand the sensitivity of investment decisions to future uncertainty and identify adaptation options that are as far as possible robust. We have developed and coupled a system of models that includes a weather generator, simulations of catchment hydrology, demand for water and the water resource system. This integrated model has been applied in the Thames catchment which supplies the city of London, UK. This region is one of the driest in the UK and hence sensitive to water availability. In addition, it is one of the fastest growing parts of the UK and plays an important economic role. Key uncertainties in long term water resources in the Thames catchment, many of which result from earth system processes, are identified and quantified. The implications of these uncertainties are explored using a combination of uncertainty analysis and sensitivity testing. The analysis shows considerable uncertainty in future rainfall, river flow and consequently water resource. For example, results indicate that by the 2050s, low flow (Q95) in the Thames catchment will range from -44 to +9% compared with the control scenario (1970s). Consequently, by the 2050s the average number of drought days are expected to increase 4-6 times relative to the 1970s. Uncertainties associated with urban growth increase these risks further. Adaptation measures, such as new reservoirs can manage these risks to a certain extent, but our sensitivity testing demonstrates that they are less robust to future uncertainties than measures taken to reduce water demand. Keywords: Climate change, Uncertainty, Decision making, Drought, Risk, Water resources management.

Exploring the impact of signal types and adjacent vehicles on drivers' choices after the onset of yellow

NASA Astrophysics Data System (ADS)

Bao, Ji; Chen, Qun; Luo, Dandan; Wu, Yuli; Liang, Zuli

2018-06-01

Drivers' choices at signalized intersections may be made in great uncertainty after the onset of yellow, which creates potential hazards for road safety. These choices are analyzed and modeled based on field observations at three comparable signalized intersections in Changsha, China. The results show that intersections without monitoring devices widen the indecision zone, which can increase the risk of rear-end collisions and the uncertainty of drivers' decision-making. In addition, drivers are more likely to stop during the yellow interval at intersections equipped with a green signal countdown device (GSCD) than at those with a green signal flashing device (GSFD). Subsequently, according to the results of a binary logistic regression model (BLRM), drivers' decision making at the onset of the yellow indication is greatly influenced by the vehicle's spot speed, the distance to the stop line, and signal and monitoring devices. The presence of an adjacent vehicle with a short space headway can particularly motivate the following driver to make a go-decision after the first driver chooses to pass the intersection. However, a stop-decision by a driver in an adjacent lane can also prompt the following driver to stop.

Forest Management Under Uncertainty for Multiple Bird Population Objectives

Treesearch

Clinton T. Moore; W. Todd Plummer; Michael J. Conroy

2005-01-01

We advocate adaptive programs of decision making and monitoring for the management of forest birds when responses by populations to management, and particularly management trade-offs among populations, are uncertain. Models are necessary components of adaptive management. Under this approach, uncertainty about the behavior of a managed system is explicitly captured in...

[Rational choice, prediction, and medical decision. Contribution of severity scores].

PubMed

Bizouarn, P; Fiat, E; Folscheid, D

2001-11-01

The aim of this study was to determine what type of representation the medical doctor adopted concerning the uncertainty about the future in critically ill patients in the context of preoperative evaluation and intensive care medicine and to explore through the representation of the patient health status the different possibilities of choice he was able to make. The role played by the severity classification systems in the process of medical decision-making under probabilistic uncertainty was assessed according to the theories of rational behaviour. In this context, a medical rationality needed to be discovered, going beyond the instrumental status of the objective and/or subjective constructions of rational choice theories and reaching a dimension where means and expected ends could be included.

Multi-disciplinary decision making in general practice.

PubMed

Kirby, Ann; Murphy, Aileen; Bradley, Colin

2018-04-09

Purpose Internationally, healthcare systems are moving towards delivering care in an integrated manner which advocates a multi-disciplinary approach to decision making. Such an approach is formally encouraged in the management of Atrial Fibrillation patients through the European Society of Cardiology guidelines. Since the emergence of new oral anticoagulants switching between oral anticoagulants (OACs) has become prevalent. This case study considers the role of multi-disciplinary decision making, given the complex nature of the agents. The purpose of this paper is to explore Irish General Practitioners' (GPs) experience of switching between all OACs for Arial Fibrillation (AF) patients; prevalence of multi-disciplinary decision making in OAC switching decisions and seeks to determine the GP characteristics that appear to influence the likelihood of multi-disciplinary decision making. Design/methodology/approach A probit model is used to determine the factors influencing multi-disciplinary decision making and a multinomial logit is used to examine the factors influencing who is involved in the multi-disciplinary decisions. Findings Results reveal that while some multi-disciplinary decision-making is occurring (64 per cent), it is not standard practice despite international guidelines on integrated care. Moreover, there is a lack of patient participation in the decision-making process. Female GPs and GPs who have initiated prescriptions for OACs are more likely to engage in multi-disciplinary decision-making surrounding switching OACs amongst AF patients. GPs with training practices were less likely to engage with cardiac consultants and those in urban areas were more likely to engage with other (non-cardiac) consultants. Originality/value For optimal decision making under uncertainty multi-disciplinary decision-making is needed to make a more informed judgement and to improve treatment decisions and reduce the opportunity cost of making the wrong decision.

Sensitivity analysis in economic evaluation: an audit of NICE current practice and a review of its use and value in decision-making.

PubMed

Andronis, L; Barton, P; Bryan, S

2009-06-01

To determine how we define good practice in sensitivity analysis in general and probabilistic sensitivity analysis (PSA) in particular, and to what extent it has been adhered to in the independent economic evaluations undertaken for the National Institute for Health and Clinical Excellence (NICE) over recent years; to establish what policy impact sensitivity analysis has in the context of NICE, and policy-makers' views on sensitivity analysis and uncertainty, and what use is made of sensitivity analysis in policy decision-making. Three major electronic databases, MEDLINE, EMBASE and the NHS Economic Evaluation Database, were searched from inception to February 2008. The meaning of 'good practice' in the broad area of sensitivity analysis was explored through a review of the literature. An audit was undertaken of the 15 most recent NICE multiple technology appraisal judgements and their related reports to assess how sensitivity analysis has been undertaken by independent academic teams for NICE. A review of the policy and guidance documents issued by NICE aimed to assess the policy impact of the sensitivity analysis and the PSA in particular. Qualitative interview data from NICE Technology Appraisal Committee members, collected as part of an earlier study, were also analysed to assess the value attached to the sensitivity analysis components of the economic analyses conducted for NICE. All forms of sensitivity analysis, notably both deterministic and probabilistic approaches, have their supporters and their detractors. Practice in relation to univariate sensitivity analysis is highly variable, with considerable lack of clarity in relation to the methods used and the basis of the ranges employed. In relation to PSA, there is a high level of variability in the form of distribution used for similar parameters, and the justification for such choices is rarely given. Virtually all analyses failed to consider correlations within the PSA, and this is an area of concern. Uncertainty is considered explicitly in the process of arriving at a decision by the NICE Technology Appraisal Committee, and a correlation between high levels of uncertainty and negative decisions was indicated. The findings suggest considerable value in deterministic sensitivity analysis. Such analyses serve to highlight which model parameters are critical to driving a decision. Strong support was expressed for PSA, principally because it provides an indication of the parameter uncertainty around the incremental cost-effectiveness ratio. The review and the policy impact assessment focused exclusively on documentary evidence, excluding other sources that might have revealed further insights on this issue. In seeking to address parameter uncertainty, both deterministic and probabilistic sensitivity analyses should be used. It is evident that some cost-effectiveness work, especially around the sensitivity analysis components, represents a challenge in making it accessible to those making decisions. This speaks to the training agenda for those sitting on such decision-making bodies, and to the importance of clear presentation of analyses by the academic community.

Uncertainty in Driftless Area Cold-Water Fishery Decision Making and a Framework for Stakeholder-Based Science

NASA Astrophysics Data System (ADS)

Schuster, Z.

2015-12-01

The paradigm of stakeholder-based science is becoming more popular as organizations such as the U.S. Department of the Interior Climate Science Centers adopt it as a way of providing practicable climate change information to practitioners. One of the key issues stakeholders face in adopting climate change information into their decision processes is how uncertainty is addressed and communicated. In this study, we conducted a series of semi-structured interviews with managers and scientists working on stream habitat restoration of cold-water fisheries in the Driftless Area of Wisconsin that were focused on how they interpret and manage uncertainty and what types of information they need to make better decisions. One of the important lessons we learned from the interviews is that if researchers are going to provide useful climate change information to stakeholders, they need to understand where and how decisions are made and what adaptation measures are actually available in a given decision arena. This method of incorporating social science methods into climate science production can provide a framework for researchers from the Climate Science Centers and others who are interested in pursuing stakeholder-based science. By indentifying a specific ecological system and conducting interviews with actors who work on that system, researchers will be able to gain a better understanding of how their climate change science can fit into existing or shape new decision processes. We also interpreted lessons learned from our interviews via existing literature in areas such as stakeholder-based modeling and the decision sciences to provide guidance specific to the stakeholder-based science process.

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.

Ecologically rational choice and the structure of the environment.

PubMed

Pleskac, Timothy J; Hertwig, Ralph

2014-10-01

In life, risk is reward and vice versa. Unfortunately, the big rewards people desire are relatively unlikely to occur. This relationship between risk and reward or probabilities and payoffs seems obvious to the financial community and to laypeople alike. Yet theories of decision making have largely ignored it. We conducted an ecological analysis of life's gambles, ranging from the domains of roulette and life insurance to scientific publications and artificial insemination. Across all domains, payoffs and probabilities proved intimately tied, with payoff magnitudes signaling their probabilities. In some cases, the constraints of the market result in these two core elements of choice being related via a power function; in other cases, other factors such as social norms appear to produce the inverse relationship between risks and rewards. We offer evidence that decision makers exploit this relationship in the form of a heuristic--the risk-reward heuristic--to infer the probability of a payoff during decisions under uncertainty. We demonstrate how the heuristic can help explain observed ambiguity aversion. We further show how this ecological relationship can inform other aspects of decision making, particularly the approach of using monetary lotteries to study choice under risk and uncertainty. Taken together, these findings suggest that theories of decision making need to model not only the decision process but also the environment to which the process is adapted.

Willingness-to-pay for a probabilistic flood forecast: a risk-based decision-making game

NASA Astrophysics Data System (ADS)

Arnal, Louise; Ramos, Maria-Helena; Coughlan de Perez, Erin; Cloke, Hannah Louise; Stephens, Elisabeth; Wetterhall, Fredrik; van Andel, Schalk Jan; Pappenberger, Florian

2016-08-01

Probabilistic hydro-meteorological forecasts have over the last decades been used more frequently to communicate forecast uncertainty. This uncertainty is twofold, as it constitutes both an added value and a challenge for the forecaster and the user of the forecasts. Many authors have demonstrated the added (economic) value of probabilistic over deterministic forecasts across the water sector (e.g. flood protection, hydroelectric power management and navigation). However, the richness of the information is also a source of challenges for operational uses, due partially to the difficulty in transforming the probability of occurrence of an event into a binary decision. This paper presents the results of a risk-based decision-making game on the topic of flood protection mitigation, called "How much are you prepared to pay for a forecast?". The game was played at several workshops in 2015, which were attended by operational forecasters and academics working in the field of hydro-meteorology. The aim of this game was to better understand the role of probabilistic forecasts in decision-making processes and their perceived value by decision-makers. Based on the participants' willingness-to-pay for a forecast, the results of the game show that the value (or the usefulness) of a forecast depends on several factors, including the way users perceive the quality of their forecasts and link it to the perception of their own performances as decision-makers.

What parents think and feel about deep brain stimulation in paediatric secondary dystonia including cerebral palsy: A qualitative study of parental decision-making.

PubMed

Austin, Allana; Lin, Jean-Pierre; Selway, Richard; Ashkan, Keyoumars; Owen, Tamsin

2017-01-01

Dystonia is characterised by involuntary movements and postures. Deep Brain Stimulation (DBS) is effective in reducing dystonic symptoms in primary dystonia in childhood and to lesser extent in secondary dystonia. How families and children decide to choose DBS surgery has never been explored. To explore parental decision-making for DBS in paediatric secondary dystonia. Data was gathered using semi-structured interviews with eight parents of children with secondary dystonia who had undergone DBS. Interviews were analysed using Interpretative Phenomenological Analysis. For all parents the decision was viewed as significant, with life altering consequences for the child. These results suggested that parents were motivated by a hope for a better life and parental duty. This was weighed against consideration of risks, what the child had to lose, and uncertainty of DBS outcome. Decisions were also influenced by the perspectives of their child and professionals. The decision to undergo DBS was an ongoing process for parents, who ultimately were struggling in the face of uncertainty whilst trying to do their best as parents for their children. These findings have important clinical implications given the growing referrals for consideration of DBS childhood dystonia, and highlights the importance of further quantitative research to fully establish the efficacy of DBS in secondary dystonia to enhance informed decision-making. Copyright © 2016. Published by Elsevier Ltd.

Fuzzy-based decision strategy in real-time strategic games

NASA Astrophysics Data System (ADS)

Volna, Eva

2017-11-01

The aim of this article is to describe our own gaming artificial intelligence for OpenTTD, which is a real-time building strategy game. A multi-agent system with fuzzy decision-making was used for the proposal itself. The multiagent system was chosen because real-time strategy games achieve great complexity and require decomposition of the problem into individual problems, which are then solved by individual cooperating agents. The system becomes then more stable and easily expandable. The fuzzy approach makes the decision-making process of strategies easier thanks to the use of uncertainty. In the conclusion, own experimental results were compared with other approaches.

Decision Aids for Naval Air ASW

DTIC Science & Technology

1980-03-15

Algorithm for Zone Optimization Investigation) NADC Developing Sonobuoy Pattern for Air ASW Search DAISY (Decision Aiding Information System) Wharton...sion making behavior. 0 Artificial intelligence sequential pattern recognition algorithm for reconstructing the decision maker’s utility functions. 0...display presenting the uncertainty area of the target. 3.1.5 Algorithm for Zone Optimization Investigation (AZOI) -- Naval Air Development Center 0 A

Application of decision science to resilience management in Jamaica Bay

USGS Publications Warehouse

Eaton, Mitchell; Fuller, Angela K.; Johnson, Fred A.; Hare, M. P.; Stedman, Richard C.; Sanderson, E.W.; Solecki, W. D.; Waldman, J.R.; Paris, A. S.

2016-01-01

This book highlights the growing interest in management interventions designed to enhance the resilience of the Jamaica Bay socio-ecological system. Effective management, whether the focus is on managing biological processes or human behavior or (most likely) both, requires decision makers to anticipate how the managed system will respond to interventions (i.e., via predictions or projections). In systems characterized by many interacting components and high uncertainty, making probabilistic predictions is often difficult and requires careful thinking not only about system dynamics, but also about how management objectives are specified and the analytic method used to select the preferred action(s). Developing a clear statement of the problem(s) and articulation of management objectives is often best achieved by including input from managers, scientists and other stakeholders affected by the decision through a process of joint problem framing (Marcot and others 2012; Keeney and others 1990). Using a deliberate, coherent and transparent framework for deciding among management alternatives to best meet these objectives then ensures a greater likelihood for successful intervention. Decision science provides the theoretical and practical basis for developing this framework and applying decision analysis methods for making complex decisions under uncertainty and risk.

Adaptive Management and the Value of Information: Learning Via Intervention in Epidemiology

PubMed Central

Shea, Katriona; Tildesley, Michael J.; Runge, Michael C.; Fonnesbeck, Christopher J.; Ferrari, Matthew J.

2014-01-01

Optimal intervention for disease outbreaks is often impeded by severe scientific uncertainty. Adaptive management (AM), long-used in natural resource management, is a structured decision-making approach to solving dynamic problems that accounts for the value of resolving uncertainty via real-time evaluation of alternative models. We propose an AM approach to design and evaluate intervention strategies in epidemiology, using real-time surveillance to resolve model uncertainty as management proceeds, with foot-and-mouth disease (FMD) culling and measles vaccination as case studies. We use simulations of alternative intervention strategies under competing models to quantify the effect of model uncertainty on decision making, in terms of the value of information, and quantify the benefit of adaptive versus static intervention strategies. Culling decisions during the 2001 UK FMD outbreak were contentious due to uncertainty about the spatial scale of transmission. The expected benefit of resolving this uncertainty prior to a new outbreak on a UK-like landscape would be £45–£60 million relative to the strategy that minimizes livestock losses averaged over alternate transmission models. AM during the outbreak would be expected to recover up to £20.1 million of this expected benefit. AM would also recommend a more conservative initial approach (culling of infected premises and dangerous contact farms) than would a fixed strategy (which would additionally require culling of contiguous premises). For optimal targeting of measles vaccination, based on an outbreak in Malawi in 2010, AM allows better distribution of resources across the affected region; its utility depends on uncertainty about both the at-risk population and logistical capacity. When daily vaccination rates are highly constrained, the optimal initial strategy is to conduct a small, quick campaign; a reduction in expected burden of approximately 10,000 cases could result if campaign targets can be updated on the basis of the true susceptible population. Formal incorporation of a policy to update future management actions in response to information gained in the course of an outbreak can change the optimal initial response and result in significant cost savings. AM provides a framework for using multiple models to facilitate public-health decision making and an objective basis for updating management actions in response to improved scientific understanding. PMID:25333371

Adaptive management and the value of information: learning via intervention in epidemiology

USGS Publications Warehouse

Shea, Katriona; Tildesley, Michael J.; Runge, Michael C.; Fonnesbeck, Christopher J.; Ferrari, Matthew J.

2014-01-01

Optimal intervention for disease outbreaks is often impeded by severe scientific uncertainty. Adaptive management (AM), long-used in natural resource management, is a structured decision-making approach to solving dynamic problems that accounts for the value of resolving uncertainty via real-time evaluation of alternative models. We propose an AM approach to design and evaluate intervention strategies in epidemiology, using real-time surveillance to resolve model uncertainty as management proceeds, with foot-and-mouth disease (FMD) culling and measles vaccination as case studies. We use simulations of alternative intervention strategies under competing models to quantify the effect of model uncertainty on decision making, in terms of the value of information, and quantify the benefit of adaptive versus static intervention strategies. Culling decisions during the 2001 UK FMD outbreak were contentious due to uncertainty about the spatial scale of transmission. The expected benefit of resolving this uncertainty prior to a new outbreak on a UK-like landscape would be £45–£60 million relative to the strategy that minimizes livestock losses averaged over alternate transmission models. AM during the outbreak would be expected to recover up to £20.1 million of this expected benefit. AM would also recommend a more conservative initial approach (culling of infected premises and dangerous contact farms) than would a fixed strategy (which would additionally require culling of contiguous premises). For optimal targeting of measles vaccination, based on an outbreak in Malawi in 2010, AM allows better distribution of resources across the affected region; its utility depends on uncertainty about both the at-risk population and logistical capacity. When daily vaccination rates are highly constrained, the optimal initial strategy is to conduct a small, quick campaign; a reduction in expected burden of approximately 10,000 cases could result if campaign targets can be updated on the basis of the true susceptible population. Formal incorporation of a policy to update future management actions in response to information gained in the course of an outbreak can change the optimal initial response and result in significant cost savings. AM provides a framework for using multiple models to facilitate public-health decision making and an objective basis for updating management actions in response to improved scientific understanding.

Does ambiguity aversion influence the framing effect during decision making?

PubMed

Osmont, Anaïs; Cassotti, Mathieu; Agogué, Marine; Houdé, Olivier; Moutier, Sylvain

2015-04-01

Decision-makers present a systematic tendency to avoid ambiguous options for which the level of risk is unknown. This ambiguity aversion is one of the most striking decision-making biases. Given that human choices strongly depend on the options' presentation, the purpose of the present study was to examine whether ambiguity aversion influences the framing effect during decision making. We designed a new financial decision-making task involving the manipulation of both frame and uncertainty levels. Thirty-seven participants had to choose between a sure option and a gamble depicting either clear or ambiguous probabilities. The results revealed a clear preference for the sure option in the ambiguity condition regardless of frame. However, participants presented a framing effect in both the risk and ambiguity conditions. Indeed, the framing effect was bidirectional in the risk condition and unidirectional in the ambiguity condition given that it did not involve preference reversal but only a more extreme choice tendency.

A Bayesian paradigm for decision-making in proof-of-concept trials.

PubMed

Pulkstenis, Erik; Patra, Kaushik; Zhang, Jianliang

2017-01-01

Decision-making is central to every phase of drug development, and especially at the proof of concept stage where risk and evidence must be weighed carefully, often in the presence of significant uncertainty. The decision to proceed or not to large expensive Phase 3 trials has significant implications to both patients and sponsors alike. Recent experience has shown that Phase 3 failure rates remain high. We present a flexible Bayesian quantitative decision-making paradigm that evaluates evidence relative to achieving a multilevel target product profile. A framework for operating characteristics is provided that allows the drug developer to design a proof-of-concept trial in light of its ability to support decision-making rather than merely achieve statistical significance. Operating characteristics are shown to be superior to traditional p-value-based methods. In addition, discussion related to sample size considerations, application to interim futility analysis and incorporation of prior historical information is evaluated.

The neural basis of belief updating and rational decision making

PubMed Central

Achtziger, Anja; Hügelschäfer, Sabine; Steinhauser, Marco

2014-01-01

Rational decision making under uncertainty requires forming beliefs that integrate prior and new information through Bayes’ rule. Human decision makers typically deviate from Bayesian updating by either overweighting the prior (conservatism) or overweighting new information (e.g. the representativeness heuristic). We investigated these deviations through measurements of electrocortical activity in the human brain during incentivized probability-updating tasks and found evidence of extremely early commitment to boundedly rational heuristics. Participants who overweight new information display a lower sensibility to conflict detection, captured by an event-related potential (the N2) observed around 260 ms after the presentation of new information. Conservative decision makers (who overweight prior probabilities) make up their mind before new information is presented, as indicated by the lateralized readiness potential in the brain. That is, they do not inhibit the processing of new information but rather immediately rely on the prior for making a decision. PMID:22956673

The neural basis of belief updating and rational decision making.

PubMed

Achtziger, Anja; Alós-Ferrer, Carlos; Hügelschäfer, Sabine; Steinhauser, Marco

2014-01-01

Rational decision making under uncertainty requires forming beliefs that integrate prior and new information through Bayes' rule. Human decision makers typically deviate from Bayesian updating by either overweighting the prior (conservatism) or overweighting new information (e.g. the representativeness heuristic). We investigated these deviations through measurements of electrocortical activity in the human brain during incentivized probability-updating tasks and found evidence of extremely early commitment to boundedly rational heuristics. Participants who overweight new information display a lower sensibility to conflict detection, captured by an event-related potential (the N2) observed around 260 ms after the presentation of new information. Conservative decision makers (who overweight prior probabilities) make up their mind before new information is presented, as indicated by the lateralized readiness potential in the brain. That is, they do not inhibit the processing of new information but rather immediately rely on the prior for making a decision.

Follow the heart or the head? The interactive influence model of emotion and cognition

PubMed Central

Luo, Jiayi; Yu, Rongjun

2015-01-01

The experience of emotion has a powerful influence on daily-life decision making. Following Plato’s description of emotion and reason as two horses pulling us in opposite directions, modern dual-system models of decision making endorse the antagonism between reason and emotion. Decision making is perceived as the competition between an emotion system that is automatic but prone to error and a reason system that is slow but rational. The reason system (in “the head”) reins in our impulses (from “the heart”) and overrides our snap judgments. However, from Darwin’s evolutionary perspective, emotion is adaptive, guiding us to make sound decisions in uncertainty. Here, drawing findings from behavioral economics and neuroeconomics, we provide a new model, labeled “The interactive influence model of emotion and cognition,” to elaborate the relationship of emotion and reason in decision making. Specifically, in our model, we identify factors that determine when emotions override reason and delineate the type of contexts in which emotions help or hurt decision making. We then illustrate how cognition modulates emotion and how they cooperate to affect decision making. PMID:25999889

Errors in statistical decision making Chapter 2 in Applied Statistics in Agricultural, Biological, and Environmental Sciences

USDA-ARS?s Scientific Manuscript database

Agronomic and Environmental research experiments result in data that are analyzed using statistical methods. These data are unavoidably accompanied by uncertainty. Decisions about hypotheses, based on statistical analyses of these data are therefore subject to error. This error is of three types,...

Influences on Healthy-Eating Decision Making in Latino Adolescent Children of Migrant and Seasonal Agricultural Workers.

PubMed

Kilanowski, Jill F

2016-01-01

Latino children demonstrate high rates of unhealthy weight, and children of Latino migrant and seasonal agricultural workers are heavier than their Latino peers. This one-group, cross-sectional, mixed-methods pilot study explored healthy-eating decision making with 12- to 14-year-olds recruited from a Midwest summer migrant education program. Demographics, decision-making, self-efficacy, and social support survey instruments were used, along with gender-specific focus groups. In the convenience sample, which included 24 participants, students felt varying degrees of uncertainty when choosing healthy foods in social situations, and 67% made poor-quality decisions. Parents offered greater support for healthy eating compared with friends. Qualitative analyses identified three themes: healthy decision making includes fruits, vegetables, and physical activity; mothers have influence over health and healthy decisions; and friends encourage unhealthy food choices. Influences on healthy-eating decision making in Latino adolescent children of migrant and seasonal agricultural workers, which were previously missing from the literature, were identified. Future research includes development of interventions to assist these adolescents with healthy-eating decision making. Copyright © 2016 National Association of Pediatric Nurse Practitioners. Published by Elsevier Inc. All rights reserved.

"Effects of Stress on Decisions Under Uncertainty: A Meta-Analysis": Correction to Starcke and Brand (2016).

PubMed

2016-09-01

Reports an error in "Effects of Stress on Decisions Under Uncertainty: A Meta-Analysis" by Katrin Starcke and Matthias Brand ( Psychological Bulletin , Advanced Online Publication, May 23, 2016, np). It should have been reported that the inverted u-shaped relationship between cortisol stress responses and decision-making performance was only observed in female, but not in male participants as suggested by the study by van den Bos, Harteveld, and Stoop (2009). Corrected versions of the affected sentences are provided. (The following abstract of the original article appeared in record 2016-25465-001.) The purpose of the present meta-analysis was to quantify the effects that stress has on decisions made under uncertainty. We hypothesized that stress increases reward seeking and risk taking through alterations of dopamine firing rates and reduces executive control by hindering optimal prefrontal cortex functioning. In certain decision situations, increased reward seeking and risk taking is dysfunctional, whereas in others, this is not the case. We also assumed that the type of stressor plays a role. In addition, moderating variables are analyzed, such as the hormonal stress response, the time between stress onset and decisions, and the participants' age and gender. We included studies in the meta-analysis that investigated decision making after a laboratory stress-induction versus a control condition (k = 32 datasets, N = 1829 participants). A random-effects model revealed that overall, stress conditions lead to decisions that can be described as more disadvantageous, more reward seeking, and more risk taking than nonstress conditions (d = .17). In those situations in which increased reward seeking and risk taking is disadvantageous, stress had significant effects (d = .26), whereas in other situations, no effects were observed (d = .01). Effects were observed under processive stressors (d = .19), but not under systemic ones (d = .09). Moderation analyses did not reveal any significant results. We concluded that stress deteriorates overall decision-making performance through the mechanisms proposed. The effects differ, depending on the decision situation and the type of stressor, but not on the characteristics of the individuals. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

A new decision sciences for complex systems.

PubMed

Lempert, Robert J

2002-05-14

Models of complex systems can capture much useful information but can be difficult to apply to real-world decision-making because the type of information they contain is often inconsistent with that required for traditional decision analysis. New approaches, which use inductive reasoning over large ensembles of computational experiments, now make possible systematic comparison of alternative policy options using models of complex systems. This article describes Computer-Assisted Reasoning, an approach to decision-making under conditions of deep uncertainty that is ideally suited to applying complex systems to policy analysis. The article demonstrates the approach on the policy problem of global climate change, with a particular focus on the role of technology policies in a robust, adaptive strategy for greenhouse gas abatement.

Characterising bias in regulatory risk and decision analysis: An analysis of heuristics applied in health technology appraisal, chemicals regulation, and climate change governance.

PubMed

MacGillivray, Brian H

2017-08-01

In many environmental and public health domains, heuristic methods of risk and decision analysis must be relied upon, either because problem structures are ambiguous, reliable data is lacking, or decisions are urgent. This introduces an additional source of uncertainty beyond model and measurement error - uncertainty stemming from relying on inexact inference rules. Here we identify and analyse heuristics used to prioritise risk objects, to discriminate between signal and noise, to weight evidence, to construct models, to extrapolate beyond datasets, and to make policy. Some of these heuristics are based on causal generalisations, yet can misfire when these relationships are presumed rather than tested (e.g. surrogates in clinical trials). Others are conventions designed to confer stability to decision analysis, yet which may introduce serious error when applied ritualistically (e.g. significance testing). Some heuristics can be traced back to formal justifications, but only subject to strong assumptions that are often violated in practical applications. Heuristic decision rules (e.g. feasibility rules) in principle act as surrogates for utility maximisation or distributional concerns, yet in practice may neglect costs and benefits, be based on arbitrary thresholds, and be prone to gaming. We highlight the problem of rule-entrenchment, where analytical choices that are in principle contestable are arbitrarily fixed in practice, masking uncertainty and potentially introducing bias. Strategies for making risk and decision analysis more rigorous include: formalising the assumptions and scope conditions under which heuristics should be applied; testing rather than presuming their underlying empirical or theoretical justifications; using sensitivity analysis, simulations, multiple bias analysis, and deductive systems of inference (e.g. directed acyclic graphs) to characterise rule uncertainty and refine heuristics; adopting "recovery schemes" to correct for known biases; and basing decision rules on clearly articulated values and evidence, rather than convention. Copyright © 2017. Published by Elsevier Ltd.

Contaminated salmon and the public's trust

USGS Publications Warehouse

Luoma, Samuel N.; Löfstedt, Ragnar E.

2007-01-01

Scientific uncertainties often make it difficult for environmental policy makers to determine how to communicate risks to the public. A constructive, holistic, multisectoral dialogue about an issue can improve understanding of uncertainties from different perspectives and clarify options for risk communication. Many environmental issues could benefit from explicit promotion of such a dialogue. When issues are complex, unconstructive advocacy, narrow focus, and exclusion of selected parties from decision making can erode public trust in science and lead to cynicism about the policies of government and the private sector.

Effects of ensemble and summary displays on interpretations of geospatial uncertainty data.

PubMed

Padilla, Lace M; Ruginski, Ian T; Creem-Regehr, Sarah H

2017-01-01

Ensemble and summary displays are two widely used methods to represent visual-spatial uncertainty; however, there is disagreement about which is the most effective technique to communicate uncertainty to the general public. Visualization scientists create ensemble displays by plotting multiple data points on the same Cartesian coordinate plane. Despite their use in scientific practice, it is more common in public presentations to use visualizations of summary displays, which scientists create by plotting statistical parameters of the ensemble members. While prior work has demonstrated that viewers make different decisions when viewing summary and ensemble displays, it is unclear what components of the displays lead to diverging judgments. This study aims to compare the salience of visual features - or visual elements that attract bottom-up attention - as one possible source of diverging judgments made with ensemble and summary displays in the context of hurricane track forecasts. We report that salient visual features of both ensemble and summary displays influence participant judgment. Specifically, we find that salient features of summary displays of geospatial uncertainty can be misunderstood as displaying size information. Further, salient features of ensemble displays evoke judgments that are indicative of accurate interpretations of the underlying probability distribution of the ensemble data. However, when participants use ensemble displays to make point-based judgments, they may overweight individual ensemble members in their decision-making process. We propose that ensemble displays are a promising alternative to summary displays in a geospatial context but that decisions about visualization methods should be informed by the viewer's task.

Supporting Fisheries Management by Means of Complex Models: Can We Point out Isles of Robustness in a Sea of Uncertainty?

PubMed Central

Gasche, Loïc; Mahévas, Stéphanie; Marchal, Paul

2013-01-01

Ecosystems are usually complex, nonlinear and strongly influenced by poorly known environmental variables. Among these systems, marine ecosystems have high uncertainties: marine populations in general are known to exhibit large levels of natural variability and the intensity of fishing efforts can change rapidly. These uncertainties are a source of risks that threaten the sustainability of both fish populations and fishing fleets targeting them. Appropriate management measures have to be found in order to reduce these risks and decrease sensitivity to uncertainties. Methods have been developed within decision theory that aim at allowing decision making under severe uncertainty. One of these methods is the information-gap decision theory. The info-gap method has started to permeate ecological modelling, with recent applications to conservation. However, these practical applications have so far been restricted to simple models with analytical solutions. Here we implement a deterministic approach based on decision theory in a complex model of the Eastern English Channel. Using the ISIS-Fish modelling platform, we model populations of sole and plaice in this area. We test a wide range of values for ecosystem, fleet and management parameters. From these simulations, we identify management rules controlling fish harvesting that allow reaching management goals recommended by ICES (International Council for the Exploration of the Sea) working groups while providing the highest robustness to uncertainties on ecosystem parameters. PMID:24204873

Supporting fisheries management by means of complex models: can we point out isles of robustness in a sea of uncertainty?

PubMed

Gasche, Loïc; Mahévas, Stéphanie; Marchal, Paul

2013-01-01

Ecosystems are usually complex, nonlinear and strongly influenced by poorly known environmental variables. Among these systems, marine ecosystems have high uncertainties: marine populations in general are known to exhibit large levels of natural variability and the intensity of fishing efforts can change rapidly. These uncertainties are a source of risks that threaten the sustainability of both fish populations and fishing fleets targeting them. Appropriate management measures have to be found in order to reduce these risks and decrease sensitivity to uncertainties. Methods have been developed within decision theory that aim at allowing decision making under severe uncertainty. One of these methods is the information-gap decision theory. The info-gap method has started to permeate ecological modelling, with recent applications to conservation. However, these practical applications have so far been restricted to simple models with analytical solutions. Here we implement a deterministic approach based on decision theory in a complex model of the Eastern English Channel. Using the ISIS-Fish modelling platform, we model populations of sole and plaice in this area. We test a wide range of values for ecosystem, fleet and management parameters. From these simulations, we identify management rules controlling fish harvesting that allow reaching management goals recommended by ICES (International Council for the Exploration of the Sea) working groups while providing the highest robustness to uncertainties on ecosystem parameters.

Defense Resource Planning Under Uncertainty: An Application of Robust Decision Making to Munitions Mix Planning

DTIC Science & Technology

2016-02-01

In addition , the parser updates some parameters based on uncertainties. For example, Analytica was very slow to update Pk values based on...moderate range. The additional security environments helped to fill gaps in lower severity. Weapons Effectiveness Pk values were modified to account for two...project is to help improve the value and character of defense resource planning in an era of growing uncertainty and complex strategic challenges

Robust Satisficing Decision Making for Unmanned Aerial Vehicle Complex Missions under Severe Uncertainty

PubMed Central

Ji, Xiaoting; Niu, Yifeng; Shen, Lincheng

2016-01-01

This paper presents a robust satisficing decision-making method for Unmanned Aerial Vehicles (UAVs) executing complex missions in an uncertain environment. Motivated by the info-gap decision theory, we formulate this problem as a novel robust satisficing optimization problem, of which the objective is to maximize the robustness while satisfying some desired mission requirements. Specifically, a new info-gap based Markov Decision Process (IMDP) is constructed to abstract the uncertain UAV system and specify the complex mission requirements with the Linear Temporal Logic (LTL). A robust satisficing policy is obtained to maximize the robustness to the uncertain IMDP while ensuring a desired probability of satisfying the LTL specifications. To this end, we propose a two-stage robust satisficing solution strategy which consists of the construction of a product IMDP and the generation of a robust satisficing policy. In the first stage, a product IMDP is constructed by combining the IMDP with an automaton representing the LTL specifications. In the second, an algorithm based on robust dynamic programming is proposed to generate a robust satisficing policy, while an associated robustness evaluation algorithm is presented to evaluate the robustness. Finally, through Monte Carlo simulation, the effectiveness of our algorithms is demonstrated on an UAV search mission under severe uncertainty so that the resulting policy can maximize the robustness while reaching the desired performance level. Furthermore, by comparing the proposed method with other robust decision-making methods, it can be concluded that our policy can tolerate higher uncertainty so that the desired performance level can be guaranteed, which indicates that the proposed method is much more effective in real applications. PMID:27835670

Robust Satisficing Decision Making for Unmanned Aerial Vehicle Complex Missions under Severe Uncertainty.

PubMed

Ji, Xiaoting; Niu, Yifeng; Shen, Lincheng

2016-01-01

This paper presents a robust satisficing decision-making method for Unmanned Aerial Vehicles (UAVs) executing complex missions in an uncertain environment. Motivated by the info-gap decision theory, we formulate this problem as a novel robust satisficing optimization problem, of which the objective is to maximize the robustness while satisfying some desired mission requirements. Specifically, a new info-gap based Markov Decision Process (IMDP) is constructed to abstract the uncertain UAV system and specify the complex mission requirements with the Linear Temporal Logic (LTL). A robust satisficing policy is obtained to maximize the robustness to the uncertain IMDP while ensuring a desired probability of satisfying the LTL specifications. To this end, we propose a two-stage robust satisficing solution strategy which consists of the construction of a product IMDP and the generation of a robust satisficing policy. In the first stage, a product IMDP is constructed by combining the IMDP with an automaton representing the LTL specifications. In the second, an algorithm based on robust dynamic programming is proposed to generate a robust satisficing policy, while an associated robustness evaluation algorithm is presented to evaluate the robustness. Finally, through Monte Carlo simulation, the effectiveness of our algorithms is demonstrated on an UAV search mission under severe uncertainty so that the resulting policy can maximize the robustness while reaching the desired performance level. Furthermore, by comparing the proposed method with other robust decision-making methods, it can be concluded that our policy can tolerate higher uncertainty so that the desired performance level can be guaranteed, which indicates that the proposed method is much more effective in real applications.

Water supply management using an extended group fuzzy decision-making method: a case study in north-eastern Iran

NASA Astrophysics Data System (ADS)

Minatour, Yasser; Bonakdari, Hossein; Zarghami, Mahdi; Bakhshi, Maryam Ali

2015-09-01

The purpose of this study was to develop a group fuzzy multi-criteria decision-making method to be applied in rating problems associated with water resources management. Thus, here Chen's group fuzzy TOPSIS method extended by a difference technique to handle uncertainties of applying a group decision making. Then, the extended group fuzzy TOPSIS method combined with a consistency check. In the presented method, initially linguistic judgments are being surveyed via a consistency checking process, and afterward these judgments are being used in the extended Chen's fuzzy TOPSIS method. Here, each expert's opinion is turned to accurate mathematical numbers and, then, to apply uncertainties, the opinions of group are turned to fuzzy numbers using three mathematical operators. The proposed method is applied to select the optimal strategy for the rural water supply of Nohoor village in north-eastern Iran, as a case study and illustrated example. Sensitivity analyses test over results and comparing results with project reality showed that proposed method offered good results for water resources projects.

Frontal cortex electrophysiology in reward- and punishment-related feedback processing during advice-guided decision making: An interleaved EEG-DC stimulation study.

PubMed

Wischnewski, Miles; Bekkering, Harold; Schutter, Dennis J L G

2018-04-01

During decision making, individuals are prone to rely on external cues such as expert advice when the outcome is not known. However, the electrophysiological correlates associated with outcome uncertainty and the use of expert advice are not completely understood. The feedback-related negativity (FRN), P3a, and P3b are event-related brain potentials (ERPs) linked to dissociable stages of feedback and attentional processing during decision making. Even though these ERPs are influenced by both reward- and punishment-related feedback, it remains unclear how extrinsic information during uncertainty modulates these brain potentials. In this study, the effects of advice cues on decision making were investigated in two separate experiments. In the first experiment, electroencephalography (EEG) was recorded in healthy volunteers during a decision-making task in which the participants received reward or punishment feedback preceded by novice, amateur, or expert advice. The results showed that the P3a component was significantly influenced by the subjective predictive value of an advice cue, whereas the FRN and P3b were unaffected by the advice cues. In the second, sham-controlled experiment, cathodal transcranial direct current stimulation (ctDCS) was administered in conjunction with EEG in order to explore the direct contributions of the frontal cortex to these brain potentials. Results showed no significant change in either advice-following behavior or decision times. However, ctDCS did decrease FRN amplitudes as compared to sham, with no effect on the P3a or P3b. Together, these findings suggest that advice information may act primarily on attention allocation during feedback processing, whereas the electrophysiological correlates of the detection and updating of internal prediction models are not affected.

Environmental risk assessment of chemicals and nanomaterials--The best foundation for regulatory decision-making?

PubMed

Syberg, Kristian; Hansen, Steffen Foss

2016-01-15

Environmental risk assessment (ERA) is often considered as the most transparent, objective and reliable decision-making tool for informing the risk management of chemicals and nanomaterials. ERAs are based on the assumption that it is possible to provide accurate estimates of hazard and exposure and, subsequently, to quantify risk. In this paper we argue that since the quantification of risk is dominated by uncertainties, ERAs do not provide a transparent or an objective foundation for decision-making and they should therefore not be considered as a "holy grail" for informing risk management. We build this thesis on the analysis of two case studies (of nonylphenol and nanomaterials) as well as a historical analysis in which we address the scientific foundation for ERAs. The analyses show that ERAs do not properly address all aspects of actual risk, such as the mixture effect and the environmentally realistic risk from nanomaterials. Uncertainties have been recognised for decades, and assessment factors are used to compensate for the lack of realism in ERAs. The assessment factors' values were pragmatically determined, thus lowering the scientific accuracy of the ERAs. Furthermore, the default choice of standard assay for assessing a hazard might not always be the most biologically relevant, so we therefore argue that an ERA should be viewed as a pragmatic decision-making tool among several, and it should not have a special status for informing risk management. In relation to other relevant decision-making tools we discuss the use of chemical alternative assessments (CAAs) and the precautionary principle. Copyright © 2015 Elsevier B.V. All rights reserved.

Patient experiences of acute myeloid leukemia: A qualitative study about diagnosis, illness understanding, and treatment decision-making.

PubMed

LeBlanc, Thomas W; Fish, Laura J; Bloom, Catherine T; El-Jawahri, Areej; Davis, Debra M; Locke, Susan C; Steinhauser, Karen E; Pollak, Kathryn I

2017-12-01

Patients with acute myeloid leukemia (AML) face a unique, difficult situation characterized by sudden changes in health, complex information, and pressure to make quick treatment decisions amid sizeable tradeoffs. Yet, little is known about patients' experiences with AML. We used qualitative methods to learn about their experiences with diagnosis and treatment decision-making to identify areas for improvement. We recruited hospitalized patients with AML to participate in semi-structured qualitative interviews about their experiences being diagnosed with AML, receiving information, and making a treatment decision. Interviews were conducted during their hospitalization for induction chemotherapy. We analyzed data by using a constant comparison approach. Thirty-two patients completed an interview. Four main themes emerged: (a) shock and suddenness, (b) difficulty processing information, (c) poor communication, and (d) uncertainty. Patients frequently described their diagnosis as shocking. They also felt that the amount of information was too great and too difficult to process, which negatively impacted their understanding. Patients frequently described a lack of emotional support from clinicians and described uncertainty about their prognosis, the number and nature of available treatments, and what to expect from treatment. Acute myeloid leukemia poses a sudden, emotionally challenging, information-laden situation, where little time is available to make important decisions. This results in difficulty processing information and is sometimes complicated by a lack of emotive communication from clinicians. Results indicate a need for targeted interventions to improve AML patients' understanding of illness and treatment options and to address their traumatic experiences around diagnosis. Copyright © 2016 John Wiley & Sons, Ltd.

Do probabilistic forecasts lead to better decisions?

NASA Astrophysics Data System (ADS)

Ramos, M. H.; van Andel, S. J.; Pappenberger, F.

2012-12-01

The last decade has seen growing research in producing probabilistic hydro-meteorological forecasts and increasing their reliability. This followed the promise that, supplied with information about uncertainty, people would take better risk-based decisions. In recent years, therefore, research and operational developments have also start putting attention to ways of communicating the probabilistic forecasts to decision makers. Communicating probabilistic forecasts includes preparing tools and products for visualization, but also requires understanding how decision makers perceive and use uncertainty information in real-time. At the EGU General Assembly 2012, we conducted a laboratory-style experiment in which several cases of flood forecasts and a choice of actions to take were presented as part of a game to participants, who acted as decision makers. Answers were collected and analyzed. In this paper, we present the results of this exercise and discuss if indeed we make better decisions on the basis of probabilistic forecasts.

Do probabilistic forecasts lead to better decisions?

NASA Astrophysics Data System (ADS)

Ramos, M. H.; van Andel, S. J.; Pappenberger, F.

2013-06-01

The last decade has seen growing research in producing probabilistic hydro-meteorological forecasts and increasing their reliability. This followed the promise that, supplied with information about uncertainty, people would take better risk-based decisions. In recent years, therefore, research and operational developments have also started focusing attention on ways of communicating the probabilistic forecasts to decision-makers. Communicating probabilistic forecasts includes preparing tools and products for visualisation, but also requires understanding how decision-makers perceive and use uncertainty information in real time. At the EGU General Assembly 2012, we conducted a laboratory-style experiment in which several cases of flood forecasts and a choice of actions to take were presented as part of a game to participants, who acted as decision-makers. Answers were collected and analysed. In this paper, we present the results of this exercise and discuss if we indeed make better decisions on the basis of probabilistic forecasts.

Understanding clinical and non-clinical decisions under uncertainty: a scenario-based survey.

PubMed

Simianu, Vlad V; Grounds, Margaret A; Joslyn, Susan L; LeClerc, Jared E; Ehlers, Anne P; Agrawal, Nidhi; Alfonso-Cristancho, Rafael; Flaxman, Abraham D; Flum, David R

2016-12-01

Prospect theory suggests that when faced with an uncertain outcome, people display loss aversion by preferring to risk a greater loss rather than incurring certain, lesser cost. Providing probability information improves decision making towards the economically optimal choice in these situations. Clinicians frequently make decisions when the outcome is uncertain, and loss aversion may influence choices. This study explores the extent to which prospect theory, loss aversion, and probability information in a non-clinical domain explains clinical decision making under uncertainty. Four hundred sixty two participants (n = 117 non-medical undergraduates, n = 113 medical students, n = 117 resident trainees, and n = 115 medical/surgical faculty) completed a three-part online task. First, participants completed an iced-road salting task using temperature forecasts with or without explicit probability information. Second, participants chose between less or more risk-averse ("defensive medicine") decisions in standardized scenarios. Last, participants chose between recommending therapy with certain outcomes or risking additional years gained or lost. In the road salting task, the mean expected value for decisions made by clinicians was better than for non-clinicians(-$1,022 vs -$1,061; <0.001). Probability information improved decision making for all participants, but non-clinicians improved more (mean improvement of $64 versus $33; p = 0.027). Mean defensive decisions decreased across training level (medical students 2.1 ± 0.9, residents 1.6 ± 0.8, faculty1.6 ± 1.1; p-trend < 0.001) and prospect-theory-concordant decisions increased (25.4%, 33.9%, and 40.7%;p-trend = 0.016). There was no relationship identified between road salting choices with defensive medicine and prospect-theory-concordant decisions. All participants made more economically-rational decisions when provided explicit probability information in a non-clinical domain. However, choices in the non-clinical domain were not related to prospect-theory concordant decision making and risk aversion tendencies in the clinical domain. Recognizing this discordance may be important when applying prospect theory to interventions aimed at improving clinical care.

Intrinsic Valuation of Information in Decision Making under Uncertainty

PubMed Central

Bode, Stefan; Brydevall, Maja; Murawski, Carsten

2016-01-01

In a dynamic world, an accurate model of the environment is vital for survival, and agents ought regularly to seek out new information with which to update their world models. This aspect of behaviour is not captured well by classical theories of decision making, and the cognitive mechanisms of information seeking are poorly understood. In particular, it is not known whether information is valued only for its instrumental use, or whether humans also assign it a non-instrumental intrinsic value. To address this question, the present study assessed preference for non-instrumental information among 80 healthy participants in two experiments. Participants performed a novel information preference task in which they could choose to pay a monetary cost to receive advance information about the outcome of a monetary lottery. Importantly, acquiring information did not alter lottery outcome probabilities. We found that participants were willing to incur considerable monetary costs to acquire payoff-irrelevant information about the lottery outcome. This behaviour was well explained by a computational cognitive model in which information preference resulted from aversion to temporally prolonged uncertainty. These results strongly suggest that humans assign an intrinsic value to information in a manner inconsistent with normative accounts of decision making under uncertainty. This intrinsic value may be associated with adaptive behaviour in real-world environments by producing a bias towards exploratory and information-seeking behaviour. PMID:27416034

Assessing patient-centered communication in a family practice setting: how do we measure it, and whose opinion matters?

PubMed

Clayton, Margaret F; Latimer, Seth; Dunn, Todd W; Haas, Leonard

2011-09-01

This study evaluated variables thought to influence patient's perceptions of patient-centeredness. We also compared results from two coding schemes that purport to evaluate patient-centeredness, the Measure of Patient-Centered Communication (MPCC) and the 4 Habits Coding Scheme (4HCS). 174 videotaped family practice office visits, and patient self-report measures were analyzed. Patient factors contributing to positive perceptions of patient-centeredness were successful negotiation of decision-making roles and lower post-visit uncertainty. MPCC coding found visits were on average 59% patient-centered (range 12-85%). 4HCS coding showed an average of 83 points (maximum possible 115). However, patients felt their visits were highly patient-centered (mean 3.7, range 1.9-4; maximum possible 4). There was a weak correlation between coding schemes, but no association between coding results and patient variables (number of pre-visit concerns, attainment of desired decision-making role, post-visit uncertainty, patients' perception of patient-centeredness). Coder inter-rater reliability was lower than expected; convergent and divergent validity were not supported. The 4HCS and MPCC operationalize patient-centeredness differently, illustrating a lack of conceptual clarity. The patient's perspective is important. Family practice providers can facilitate a more positive patient perception of patient-centeredness by addressing patient concerns to help reduce patient uncertainty, and by negotiating decision-making roles. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Heuristic reasoning and cognitive biases: Are they hindrances to judgments and decision making in orthodontics?

PubMed

Hicks, E Preston; Kluemper, G Thomas

2011-03-01

Studies show that our brains use 2 modes of reasoning: heuristic (intuitive, automatic, implicit processing) and analytic (deliberate, rule-based, explicit processing). The use of intuition often dominates problem solving when innovative, creative thinking is required. Under conditions of uncertainty, we default to an even greater reliance on the heuristic processing. In health care settings and other such environments of increased importance, this mode becomes problematic. Since choice heuristics are quickly constructed from fragments of memory, they are often biased by prior evaluations of and preferences for the alternatives being considered. Therefore, a rigorous and systematic decision process notwithstanding, clinical judgments under uncertainty are often flawed by a number of unwitting biases. Clinical orthodontics is as vulnerable to this fundamental failing in the decision-making process as any other health care discipline. Several of the more common cognitive biases relevant to clinical orthodontics are discussed in this article. By raising awareness of these sources of cognitive errors in our clinical decision making, our intent was to equip the clinician to take corrective action to avoid them. Our secondary goal was to expose this important area of empirical research and encourage those with expertise in the cognitive sciences to explore, through further research, the possible relevance and impact of cognitive heuristics and biases on the accuracy of orthodontic judgments and decision making. Copyright © 2011 American Association of Orthodontists. Published by Mosby, Inc. All rights reserved.

TACtic- A Multi Behavioral Agent for Trading Agent Competition

NASA Astrophysics Data System (ADS)

Khosravi, Hassan; Shiri, Mohammad E.; Khosravi, Hamid; Iranmanesh, Ehsan; Davoodi, Alireza

Software agents are increasingly being used to represent humans in online auctions. Such agents have the advantages of being able to systematically monitor a wide variety of auctions and then make rapid decisions about what bids to place in what auctions. They can do this continuously and repetitively without losing concentration. To provide a means of evaluating and comparing (benchmarking) research methods in this area the trading agent competition (TAC) was established. This paper describes the design, of TACtic. Our agent uses multi behavioral techniques at the heart of its decision making to make bidding decisions in the face of uncertainty, to make predictions about the likely outcomes of auctions, and to alter the agent's bidding strategy in response to the prevailing market conditions.

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…

Multi-objective decision-making under uncertainty: Fuzzy logic methods

NASA Technical Reports Server (NTRS)

Hardy, Terry L.

1994-01-01

Selecting the best option among alternatives is often a difficult process. This process becomes even more difficult when the evaluation criteria are vague or qualitative, and when the objectives vary in importance and scope. Fuzzy logic allows for quantitative representation of vague or fuzzy objectives, and therefore is well-suited for multi-objective decision-making. This paper presents methods employing fuzzy logic concepts to assist in the decision-making process. In addition, this paper describes software developed at NASA Lewis Research Center for assisting in the decision-making process. Two diverse examples are used to illustrate the use of fuzzy logic in choosing an alternative among many options and objectives. One example is the selection of a lunar lander ascent propulsion system, and the other example is the selection of an aeration system for improving the water quality of the Cuyahoga River in Cleveland, Ohio. The fuzzy logic techniques provided here are powerful tools which complement existing approaches, and therefore should be considered in future decision-making activities.

The Role of Integrated Modelling and Assessment for Decision-Making: Lessons from Water Allocation Issues in Australia

NASA Astrophysics Data System (ADS)

Jakeman, A. J.; Guillaume, J. H. A.; El Sawah, S.; Hamilton, S.

2014-12-01

Integrated modelling and assessment (IMA) is best regarded as a process that can support environmental decision-making when issues are strongly contested and uncertainties pervasive. To be most useful, the process must be multi-dimensional and phased. Principally, it must be tailored to the problem context to encompass diverse issues of concern, management settings and stakeholders. This in turn requires the integration of multiple processes and components of natural and human systems and their corresponding spatial and temporal scales. Modellers therefore need to be able to integrate multiple disciplines, methods, models, tools and data, and many sources and types of uncertainty. These dimensions are incorporated into iteration between the various phases of the IMA process, including scoping, problem framing and formulation, assessing options and communicating findings. Two case studies in Australia are employed to share the lessons of how integration can be achieved in these IMA phases using a mix of stakeholder participation processes and modelling tools. One case study aims to improve the relevance of modelling by incorporating stakeholder's views of irrigated viticulture and water management decision making. It used a novel methodology with the acronym ICTAM, consisting of Interviews to elicit mental models, Cognitive maps to represent and analyse individual and group mental models, Time-sequence diagrams to chronologically structure the decision making process, an All-encompassing conceptual model, and computational Models of stakeholder decision making. The second case uses a hydro-economic river network model to examine basin-wide impacts of water allocation cuts and adoption of farm innovations. The knowledge exchange approach used in each case was designed to integrate data and knowledge bearing in mind the contextual dimensions of the problem at hand, and the specific contributions that environmental modelling was thought to be able to make.

A model for medical decision making and problem solving.

PubMed

Werner, M

1995-08-01

Clinicians confront the classical problem of decision making under uncertainty, but a universal procedure by which they deal with this situation, both in diagnosis and therapy, can be defined. This consists in the choice of a specific course of action from available alternatives so as to reduce uncertainty. Formal analysis evidences that the expected value of this process depends on the a priori probabilities confronted, the discriminatory power of the action chosen, and the values and costs associated with possible outcomes. Clinical problem-solving represents the construction of a systematic strategy from multiple decisional building blocks. Depending on the level of uncertainty the physicians attach to their working hypothesis, they can choose among at least four prototype strategies: pattern recognition, the hypothetico-deductive process, arborization, and exhaustion. However, the resolution of real-life problems can involve a combination of these game plans. Formal analysis of each strategy permits definition of its appropriate a priori probabilities, action characteristics, and cost implications.

Use of PRA in Shuttle Decision Making Process

NASA Technical Reports Server (NTRS)

Boyer, Roger L.; Hamlin, Teri L.

2010-01-01

How do you use PRA to support an operating program? This presentation will explore how the Shuttle Program Management has used the Shuttle PRA in its decision making process. It will reveal how the PRA has evolved from a tool used to evaluate Shuttle upgrades like Electric Auxiliary Power Unit (EAPU) to a tool that supports Flight Readiness Reviews (FRR) and real-time flight decisions. Specific examples of Shuttle Program decisions that have used the Shuttle PRA as input will be provided including how it was used in the Hubble Space Telescope (HST) manifest decision. It will discuss the importance of providing management with a clear presentation of the analysis, applicable assumptions and limitations, along with estimates of the uncertainty. This presentation will show how the use of PRA by the Shuttle Program has evolved overtime and how it has been used in the decision making process providing specific examples.

A Descriptive Study of Decision-Making Conversations during Pediatric Intensive Care Unit Family Conferences.

PubMed

Smith, Michael A; Clayman, Marla L; Frader, Joel; Arenson, Melanie; Haber-Barker, Natalie; Ryan, Claire; Emanuel, Linda; Michelson, Kelly

2018-06-19

Little is known about how decision-making conversations occur during pediatric intensive care unit (PICU) family conferences (FCs). Describe the decision-making process and implementation of shared decision making (SDM) during PICU FCs. Observational study. University-based tertiary care PICU, including 31 parents and 94 PICU healthcare professionals involved in FCs. We recorded, transcribed, and analyzed 14 PICU FCs involving decision-making discussions. We used a modified grounded theory and content analysis approach to explore the use of traditionally described stages of decision making (DM) (information exchange, deliberation, and determining a plan). We also identified the presence or absence of predefined SDM elements. DM involved the following modified stages: information exchange; information-oriented deliberation; plan-oriented deliberation; and determining a plan. Conversations progressed through stages in a nonlinear manner. For the main decision discussed, all conferences included a presentation of the clinical issues, treatment alternatives, and uncertainty. A minority of FCs included assessing the family's understanding (21%), assessing the family's need for input from others (28%), exploring the family's desired decision-making role (35%), and eliciting the family's opinion (42%). In the FCs studied, we found that DM is a nonlinear process. We also found that several SDM elements that could provide information about parents' perspectives and needs did not always occur, identifying areas for process improvement.

Uncertainty and sensitivity assessment of flood risk assessments

NASA Astrophysics Data System (ADS)

de Moel, H.; Aerts, J. C.

2009-12-01

Floods are one of the most frequent and costly natural disasters. In order to protect human lifes and valuable assets from the effect of floods many defensive structures have been build. Despite these efforts economic losses due to catastrophic flood events have, however, risen substantially during the past couple of decades because of continuing economic developments in flood prone areas. On top of that, climate change is expected to affect the magnitude and frequency of flood events. Because these ongoing trends are expected to continue, a transition can be observed in various countries to move from a protective flood management approach to a more risk based flood management approach. In a risk based approach, flood risk assessments play an important role in supporting decision making. Most flood risk assessments assess flood risks in monetary terms (damage estimated for specific situations or expected annual damage) in order to feed cost-benefit analysis of management measures. Such flood risk assessments contain, however, considerable uncertainties. This is the result from uncertainties in the many different input parameters propagating through the risk assessment and accumulating in the final estimate. Whilst common in some other disciplines, as with integrated assessment models, full uncertainty and sensitivity analyses of flood risk assessments are not so common. Various studies have addressed uncertainties regarding flood risk assessments, but have mainly focussed on the hydrological conditions. However, uncertainties in other components of the risk assessment, like the relation between water depth and monetary damage, can be substantial as well. This research therefore tries to assess the uncertainties of all components of monetary flood risk assessments, using a Monte Carlo based approach. Furthermore, the total uncertainty will also be attributed to the different input parameters using a variance based sensitivity analysis. Assessing and visualizing the uncertainties of the final risk estimate will be helpful to decision makers to make better informed decisions and attributing this uncertainty to the input parameters helps to identify which parameters are most important when it comes to uncertainty in the final estimate and should therefore deserve additional attention in further research.

Forest management under uncertainty for multiple bird population objectives

USGS Publications Warehouse

Moore, C.T.; Plummer, W.T.; Conroy, M.J.; Ralph, C. John; Rich, Terrell D.

2005-01-01

We advocate adaptive programs of decision making and monitoring for the management of forest birds when responses by populations to management, and particularly management trade-offs among populations, are uncertain. Models are necessary components of adaptive management. Under this approach, uncertainty about the behavior of a managed system is explicitly captured in a set of alternative models. The models generate testable predictions about the response of populations to management, and monitoring data provide the basis for assessing these predictions and informing future management decisions. To illustrate these principles, we examine forest management at the Piedmont National Wildlife Refuge, where management attention is focused on the recovery of the Red-cockaded Woodpecker (Picoides borealis) population. However, managers are also sensitive to the habitat needs of many non-target organisms, including Wood Thrushes (Hylocichla mustelina) and other forest interior Neotropical migratory birds. By simulating several management policies on a set of-alternative forest and bird models, we found a decision policy that maximized a composite response by woodpeckers and Wood Thrushes despite our complete uncertainty regarding system behavior. Furthermore, we used monitoring data to update our measure of belief in each alternative model following one cycle of forest management. This reduction of uncertainty translates into a reallocation of model influence on the choice of optimal decision action at the next decision opportunity.

Uncertainty quantification and optimal decisions

PubMed Central

2017-01-01

A mathematical model can be analysed to construct policies for action that are close to optimal for the model. If the model is accurate, such policies will be close to optimal when implemented in the real world. In this paper, the different aspects of an ideal workflow are reviewed: modelling, forecasting, evaluating forecasts, data assimilation and constructing control policies for decision-making. The example of the oil industry is used to motivate the discussion, and other examples, such as weather forecasting and precision agriculture, are used to argue that the same mathematical ideas apply in different contexts. Particular emphasis is placed on (i) uncertainty quantification in forecasting and (ii) how decisions are optimized and made robust to uncertainty in models and judgements. This necessitates full use of the relevant data and by balancing costs and benefits into the long term may suggest policies quite different from those relevant to the short term. PMID:28484343

Nurses' decision-making process in cases of physical restraint in acute elderly care: a qualitative study.

PubMed

Goethals, S; Dierckx de Casterlé, B; Gastmans, C

2013-05-01

The increasing vulnerability of patients in acute elderly care requires constant critical reflection in ethically charged situations such as when employing physical restraint. Qualitative evidence concerning nurses' decision making in cases of physical restraint is limited and fragmented. A thorough understanding of nurses' decision-making process could be useful to understand how nurses reason and make decisions in ethically laden situations. The aims of this study were to explore and describe nurses' decision-making process in cases of physical restraint. We used a qualitative interview design inspired by the Grounded Theory approach. Data analysis was guided by the Qualitative Analysis Guide of Leuven. Twelve hospitals geographically spread throughout the five provinces of Flanders, Belgium. Twenty-one acute geriatric nurses interviewed between October 2009 and April 2011 were purposively and theoretically selected, with the aim of including nurses having a variety of characteristics and experiences concerning decisions on using physical restraint. In cases of physical restraint in acute elderly care, nurses' decision making was never experienced as a fixed decision but rather as a series of decisions. Decision making was mostly reasoned upon and based on rational arguments; however, decisions were also made routinely and intuitively. Some nurses felt very certain about their decisions, while others experienced feelings of uncertainty regarding their decisions. Nurses' decision making is an independent process that requires nurses to obtain a good picture of the patient, to be constantly observant, and to assess and reassess the patient's situation. Coming to thoughtful and individualized decisions requires major commitment and constant critical reflection. Copyright © 2012 Elsevier Ltd. All rights reserved.

NASA Risk-Informed Decision Making Handbook

NASA Technical Reports Server (NTRS)

Dezfuli, Homayoon; Stamatelatos, Michael; Maggio, Gaspare; Everett, Christopher; Youngblood, Robert; Rutledge, Peter; Benjamin, Allan; Williams, Rodney; Smith, Curtis; Guarro, Sergio

2010-01-01

This handbook provides guidance for conducting risk-informed decision making in the context of NASA risk management (RM), with a focus on the types of direction-setting key decisions that are characteristic of the NASA program and project life cycles, and which produce derived requirements in accordance with existing systems engineering practices that flow down through the NASA organizational hierarchy. The guidance in this handbook is not meant to be prescriptive. Instead, it is meant to be general enough, and contain a sufficient diversity of examples, to enable the reader to adapt the methods as needed to the particular decision problems that he or she faces. The handbook highlights major issues to consider when making decisions in the presence of potentially significant uncertainty, so that the user is better able to recognize and avoid pitfalls that might otherwise be experienced.

On formally integrating science and policy: walking the walk

USGS Publications Warehouse

Nichols, James D.; Johnson, Fred A.; Williams, Byron K.; Boomer, G. Scott

2015-01-01

The contribution of science to the development and implementation of policy is typically neither direct nor transparent.  In 1995, the U.S. Fish and Wildlife Service (FWS) made a decision that was unprecedented in natural resource management, turning to an unused and unproven decision process to carry out trust responsibilities mandated by an international treaty.  The decision process was adopted for the establishment of annual sport hunting regulations for the most economically important duck population in North America, the 6 to 11 million mallards Anas platyrhynchos breeding in the mid-continent region of north-central United States and central Canada.  The key idea underlying the adopted decision process was to formally embed within it a scientific process designed to reduce uncertainty (learn) and thus make better decisions in the future.  The scientific process entails use of models to develop predictions of competing hypotheses about system response to the selected action at each decision point.  These prediction not only are used to select the optimal management action, but also are compared with the subsequent estimates of system state variables, providing evidence for modifying degrees of confidence in, and hence relative influence of, these models at the next decision point.  Science and learning in one step are formally and directly incorporated into the next decision, contrasting with the usual ad hoc and indirect use of scientific results in policy development and decision-making.  Application of this approach over the last 20 years has led to a substantial reduction in uncertainty, as well as to an increase in transparency and defensibility of annual decisions and a decrease in the contentiousness of the decision process.  As resource managers are faced with increased uncertainty associated with various components of global change, this approach provides a roadmap for the future scientific management of natural resources.  

Decision Neuroscience: Neuroeconomics

PubMed Central

Smith, David V.; Huettel, Scott A.

2012-01-01

Few aspects of human cognition are more personal than the choices we make. Our decisions – from the mundane to the impossibly complex – continually shape the courses of our lives. In recent years, researchers have applied the tools of neuroscience to understand the mechanisms that underlie decision making, as part of the new discipline of decision neuroscience. A primary goal of this emerging field has been to identify the processes that underlie specific decision variables, including the value of rewards, the uncertainty associated with particular outcomes, and the consequences of social interactions. Recent work suggests potential neural substrates that integrate these variables, potentially reflecting a common neural currency for value, to facilitate value comparisons. Despite the successes of decision neuroscience research for elucidating brain mechanisms, significant challenges remain. These include building new conceptual frameworks for decision making, integrating research findings across disparate techniques and species, and extending results from neuroscience to shape economic theory. To overcome these challenges, future research will likely focus on interpersonal variability in decision making, with the eventual goal of creating biologically plausible models for individual choice. PMID:22754602

Communication of uncertainty in hydrological predictions: a user-driven example web service for Europe

NASA Astrophysics Data System (ADS)

Fry, Matt; Smith, Katie; Sheffield, Justin; Watts, Glenn; Wood, Eric; Cooper, Jon; Prudhomme, Christel; Rees, Gwyn

2017-04-01

Water is fundamental to society as it impacts on all facets of life, the economy and the environment. But whilst it creates opportunities for growth and life, it can also cause serious damages to society and infrastructure through extreme hydro-meteorological events such as floods or droughts. Anticipation of future water availability and extreme event risks would both help optimise growth and limit damage through better preparedness and planning, hence providing huge societal benefits. Recent scientific research advances make it now possible to provide hydrological outlooks at monthly to seasonal lead time, and future projections up to the end of the century accounting for climatic changes. However, high uncertainty remains in the predictions, which varies depending on location, time of the year, prediction range and hydrological variable. It is essential that this uncertainty is fully understood by decision makers so they can account for it in their planning. Hence, the challenge is to finds ways to communicate such uncertainty for a range of stakeholders with different technical background and environmental science knowledge. The project EDgE (End-to end Demonstrator for improved decision making in the water sector for Europe) funded by the Copernicus programme (C3S) is a proof-of-concept project that develops a unique service to support decision making for the water sector at monthly to seasonal and to multi-decadal lead times. It is a mutual effort of co-production between hydrologists and environmental modellers, computer scientists and stakeholders representative of key decision makers in Europe for the water sector. This talk will present the iterative co-production process of a web service that serves the need of the user community. Through a series of Focus Group meetings in Spain, Norway and the UK, options for visualising the hydrological predictions and associated uncertainties are presented and discussed first as mock-up dash boards, off-line tools and pre-operational services. Feedbacks received from the users are listed and prioritised for the next-generation of development to take place. In addition, sprint-review webinars are also organised to insure the developed services address the users' demands correctly. The tools are formally tested through a set of case studies representative of decision making in contrasting water sectors, including hydro-power in snow-dominated regions, public water supply in heavily regulated countries, and river basin management in an arid environments with multiple users. In addition to the visualisation, a key component of the project is the provision of user guidance. This helps the user understand the challenges of dealing with uncertainty and interpretation of the results, provides contextual background information, describes the service's functionality, and showcases examples of good practice.

Ensemble modelling and structured decision-making to support Emergency Disease Management.

PubMed

Webb, Colleen T; Ferrari, Matthew; Lindström, Tom; Carpenter, Tim; Dürr, Salome; Garner, Graeme; Jewell, Chris; Stevenson, Mark; Ward, Michael P; Werkman, Marleen; Backer, Jantien; Tildesley, Michael

2017-03-01

Epidemiological models in animal health are commonly used as decision-support tools to understand the impact of various control actions on infection spread in susceptible populations. Different models contain different assumptions and parameterizations, and policy decisions might be improved by considering outputs from multiple models. However, a transparent decision-support framework to integrate outputs from multiple models is nascent in epidemiology. Ensemble modelling and structured decision-making integrate the outputs of multiple models, compare policy actions and support policy decision-making. We briefly review the epidemiological application of ensemble modelling and structured decision-making and illustrate the potential of these methods using foot and mouth disease (FMD) models. In case study one, we apply structured decision-making to compare five possible control actions across three FMD models and show which control actions and outbreak costs are robustly supported and which are impacted by model uncertainty. In case study two, we develop a methodology for weighting the outputs of different models and show how different weighting schemes may impact the choice of control action. Using these case studies, we broadly illustrate the potential of ensemble modelling and structured decision-making in epidemiology to provide better information for decision-making and outline necessary development of these methods for their further application. Crown Copyright © 2017. Published by Elsevier B.V. All rights reserved.

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

Decision-Making Uncertainty and the Use of Force in Cyberspace: A Phenomenological Study of Military Officers

DTIC Science & Technology

2010-10-01

theory becomes a more comprehensive and persuasive model for describing and predicting behavioral decision-making factors ( Bell , 1982). Böhm and...inductively analyzing the rich data collected in their natural setting ( Bryman , 1984; Leedy & Ormrod, 2010; Neuman, 2005). A phenomenological...qualitative methods, the “sine qua non is a commitment to see the world from the point of view of the actor” ( Bryman , 1984, p. 77). Therefore, the

Impaired decision-making under risk in individuals with alcohol dependence

PubMed Central

Brevers, Damien; Bechara, Antoine; Cleeremans, Axel; Kornreich, Charles; Verbanck, Paul; Noël, Xavier

2014-01-01

Background Alcohol dependence is associated with poor decision-making under ambiguity, that is, when decisions are to be made in the absence of known probabilities of reward and loss. However, little is known regarding decisions made by individuals with alcohol dependence in the context of known probabilities (decision under risk). In this study, we investigated the relative contribution of these distinct aspects of decision making to alcohol dependence. Methods Thirty recently detoxified and sober asymptomatic alcohol-dependent individuals, and thirty healthy control participants were tested for decision-making under ambiguity (using the Iowa Gambling Task), and decision-making under-risk (using the Cups Task and Coin Flipping Task). We also tested their capacities for working memory storage (Digit-span Forward), and dual-tasking (Operation-span Task). Results Compared to healthy control participants, alcohol-dependent individuals made disadvantageous decisions on the Iowa Gambling Task, reflecting poor decisions under ambiguity. They also made more risky choices on the Cups and Coin Flipping Tasks reflecting poor decision-making under risk. In addition, alcohol-dependent participants showed some working memory impairments, as measured by the dual tasking, and the degree of this impairment correlated with high-risk decision-making, thus suggesting a relationship between processes sub-serving working memory and risky decisions. Conclusion These results suggest that alcohol dependent individuals are impaired in their ability to decide optimally in multiple facets of uncertainty (i.e., both risk and ambiguity), and that at least some aspects of these deficits are linked to poor working memory processes. PMID:24948198

Relationship between Physicians' Uncertainty about Clinical Assessments and Patient-Centered Recommendations for Colorectal Cancer Screening in the Elderly.

PubMed

Dalton, Alexandra F; Golin, Carol E; Esserman, Denise; Pignone, Michael P; Pathman, Donald E; Lewis, Carmen L

2015-05-01

The goal of this study was to examine associations between physicians' clinical assessments, their certainty in these assessments, and the likelihood of a patient-centered recommendation about colorectal cancer (CRC) screening in the elderly. Two hundred seventy-six primary care physicians in the United States read 3 vignettes about an 80-year-old female patient and answered questions about her life expectancy, their confidence in their life expectancy estimate, the balance of benefits/downsides of CRC screening, their certainty in their benefit/downside assessment, and the best course of action regarding CRC screening. We used logistic regression to determine the relationship between these variables and patient-centered recommendations about CRC screening. In bivariate analyses, physicians had higher odds of making a patient-centered recommendation about CRC screening when their clinical assessments did not lead to a clear screening recommendation or when they experienced uncertainty in their clinical assessments. However, in a multivariate regression model, only benefit/downside assessment and best course of action remained statistically significant predictors of a patient-centered recommendation. Our findings demonstrate that when the results of clinical assessments do not lead to obvious screening decisions or when physicians feel uncertain about their clinical assessments, they are more likely to make patient-centered recommendations. Existing uncertainty frameworks do not adequately describe the uncertainty associated with patient-centered recommendations found in this study. Adapting or modifying these frameworks to better reflect the constructs associated with uncertainty and the interactions between uncertainty and the complexity inherent in clinical decisions will facilitate a more complete understanding of how and when physicians choose to include patients in clinical decisions. © The Author(s) 2015.

Uncertainty, robustness, and the value of information in managing a population of northern bobwhites

USGS Publications Warehouse

Johnson, Fred A.; Hagan, Greg; Palmer, William E.; Kemmerer, Michael

2014-01-01

The abundance of northern bobwhites (Colinus virginianus) has decreased throughout their range. Managers often respond by considering improvements in harvest and habitat management practices, but this can be challenging if substantial uncertainty exists concerning the cause(s) of the decline. We were interested in how application of decision science could be used to help managers on a large, public management area in southwestern Florida where the bobwhite is a featured species and where abundance has severely declined. We conducted a workshop with managers and scientists to elicit management objectives, alternative hypotheses concerning population limitation in bobwhites, potential management actions, and predicted management outcomes. Using standard and robust approaches to decision making, we determined that improved water management and perhaps some changes in hunting practices would be expected to produce the best management outcomes in the face of uncertainty about what is limiting bobwhite abundance. We used a criterion called the expected value of perfect information to determine that a robust management strategy may perform nearly as well as an optimal management strategy (i.e., a strategy that is expected to perform best, given the relative importance of different management objectives) with all uncertainty resolved. We used the expected value of partial information to determine that management performance could be increased most by eliminating uncertainty over excessive-harvest and human-disturbance hypotheses. Beyond learning about the factors limiting bobwhites, adoption of a dynamic management strategy, which recognizes temporal changes in resource and environmental conditions, might produce the greatest management benefit. Our research demonstrates that robust approaches to decision making, combined with estimates of the value of information, can offer considerable insight into preferred management approaches when great uncertainty exists about system dynamics and the effects of management.

Life support technology investment strategies for flight programs: An application of decision analysis

NASA Technical Reports Server (NTRS)

Schlater, Nelson J.; Simonds, Charles H.; Ballin, Mark G.

1993-01-01

Applied research and technology development (R&TD) is often characterized by uncertainty, risk, and significant delays before tangible returns are obtained. Given the increased awareness of limitations in resources, effective R&TD today needs a method for up-front assessment of competing technologies to help guide technology investment decisions. Such an assessment approach must account for uncertainties in system performance parameters, mission requirements and architectures, and internal and external events influencing a development program. The methodology known as decision analysis has the potential to address these issues. It was evaluated by performing a case study assessment of alternative carbon dioxide removal technologies for NASA"s proposed First Lunar Outpost program. An approach was developed that accounts for the uncertainties in each technology's cost and performance parameters as well as programmatic uncertainties such as mission architecture. Life cycle cost savings relative to a baseline, adjusted for the cost of money, was used as a figure of merit to evaluate each of the alternative carbon dioxide removal technology candidates. The methodology was found to provide a consistent decision-making strategy for the develpoment of new life support technology. The case study results provided insight that was not possible from more traditional analysis approaches.

Life support technology investment strategies for flight programs: An application of decision analysis

NASA Technical Reports Server (NTRS)

Schlater, Nelson J.; Simonds, Charles H.; Ballin, Mark G.

1993-01-01

Applied research and technology development (R&TD) is often characterized by uncertainty, risk, and significant delays before tangible returns are obtained. Given the increased awareness of limitations in resources, effective R&TD today needs a method for up-front assessment of competing technologies to help guide technology investment decisions. Such an assessment approach must account for uncertainties in system performance parameters, mission requirements and architectures, and internal and external events influencing a development program. The methodology known as decision analysis has the potential to address these issues. It was evaluated by performing a case study assessment of alternative carbon dioxide removal technologies for NASA's proposed First Lunar Outpost program. An approach was developed that accounts for the uncertainties in each technology's cost and performance parameters as well as programmatic uncertainties such as mission architecture. Life cycle cost savings relative to a baseline, adjusted for the cost of money, was used as a figure of merit to evaluate each of the alternative carbon dioxide removal technology candidates. The methodology was found to provide a consistent decision-making strategy for development of new life support technology. The case study results provided insight that was not possible from more traditional analysis approaches.

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.

Mainstreaming Climate Change: Recent and Ongoing Efforts to Understand, Improve, and Expand Consideration of Climate Change in Federal Water Resources Planning

NASA Astrophysics Data System (ADS)

Ferguson, I. M.; McGuire, M.; Broman, D.; Gangopadhyay, S.

2017-12-01

The Bureau of Reclamation is a Federal agency tasked with developing and managing water supply and hydropower projects in the Western U.S. Climate and hydrologic variability and change significantly impact management actions and outcomes across Reclamation's programs and initiatives, including water resource planning and operations, infrastructure design and maintenance, hydropower generation, and ecosystem restoration, among others. Planning, design, and implementation of these programs therefore requires consideration of future climate and hydrologic conditions will impact program objectives. Over the past decade, Reclamation and other Federal agencies have adopted new guidelines, directives, and mandates that require consideration of climate change in water resources planning and decision making. Meanwhile, the scientific community has developed a large number of climate projections, along with an array of models, methods, and tools to facilitate consideration of climate projections in planning and decision making. However, water resources engineers, planners, and decision makers continue to face challenges regarding how best to use the available data and tools to support major decisions, including decisions regarding infrastructure investments and long-term operating criteria. This presentation will discuss recent and ongoing research towards understanding, improving, and expanding consideration of climate projections and related uncertainties in Federal water resources planning and decision making. These research efforts address a variety of challenges, including: How to choose between available climate projection datasets and related methods, models, and tools—many of which are considered experimental or research tools? How to select an appropriate decision framework when design or operating alternatives may differ between climate scenarios? How to effectively communicate results of a climate impacts analysis to decision makers? And, how to improve robustness and resilience of water resources systems in the face of significant uncertainty? Discussion will focus on the intersection between technical challenges and decision making paradigms and the need for improved scientist-decision maker engagement through the lens of this Federal water management agency.

Preparing Students for Front-Line Management: Non-Routine Day-to-Day Decisions

ERIC Educational Resources Information Center

Clydesdale, Greg; Tan, John

2009-01-01

Purpose: This paper attempts to reduce the gap between management education and practice. It emphasises day-to-day decisions that middle and lower level managers make. The purpose is to provide an education framework embodying a flexible approach to interpretation and solution creation, suitable for situations of ambiguity and uncertainty.…

Uncertainty Reasoning for Service-Based Situational Awareness Information on the Semantic Web

ERIC Educational Resources Information Center

Dinkel, Stephen C.

2012-01-01

Accurate situational assessment is key to any decision maker and especially crucial in military command and control, air traffic control, and complex system decision making. Endsley described three dependent levels of situational awareness, (1) perception, (2) understanding, and (3) projection. This research was focused on Endsley's…

Applying principles from the game theory to acute stroke care: Learning from the prisoner's dilemma, stag-hunt, and other strategies.

PubMed

Saposnik, Gustavo; Johnston, S Claiborne

2016-04-01

Acute stroke care represents a challenge for decision makers. Decisions based on erroneous assessments may generate false expectations of patients and their family members, and potentially inappropriate medical advice. Game theory is the analysis of interactions between individuals to study how conflict and cooperation affect our decisions. We reviewed principles of game theory that could be applied to medical decisions under uncertainty. Medical decisions in acute stroke care are usually made under constrains: short period of time, with imperfect clinical information, limit understanding about patients and families' values and beliefs. Game theory brings some strategies to help us manage complex medical situations under uncertainty. For example, it offers a different perspective by encouraging the consideration of different alternatives through the understanding of patients' preferences and the careful evaluation of cognitive distortions when applying 'real-world' data. The stag-hunt game teaches us the importance of trust to strength cooperation for a successful patient-physician interaction that is beyond a good or poor clinical outcome. The application of game theory to stroke care may improve our understanding of complex medical situations and help clinicians make practical decisions under uncertainty. © 2016 World Stroke Organization.

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.

Physics of risk and uncertainty in quantum decision making

NASA Astrophysics Data System (ADS)

Yukalov, V. I.; Sornette, D.

2009-10-01

The Quantum Decision Theory, developed recently by the authors, is applied to clarify the role of risk and uncertainty in decision making and in particular in relation to the phenomenon of dynamic inconsistency. By formulating this notion in precise mathematical terms, we distinguish three types of inconsistency: time inconsistency, planning paradox, and inconsistency occurring in some discounting effects. While time inconsistency is well accounted for in classical decision theory, the planning paradox is in contradiction with classical utility theory. It finds a natural explanation in the frame of the Quantum Decision Theory. Different types of discounting effects are analyzed and shown to enjoy a straightforward explanation within the suggested theory. We also introduce a general methodology based on self-similar approximation theory for deriving the evolution equations for the probabilities of future prospects. This provides a novel classification of possible discount factors, which include the previously known cases (exponential or hyperbolic discounting), but also predicts a novel class of discount factors that decay to a strictly positive constant for very large future time horizons. This class may be useful to deal with very long-term discounting situations associated with intergenerational public policy choices, encompassing issues such as global warming and nuclear waste disposal.

Group decision-making approach for flood vulnerability identification using the fuzzy VIKOR method

NASA Astrophysics Data System (ADS)

Lee, G.; Jun, K. S.; Chung, E.-S.

2015-04-01

This study proposes an improved group decision making (GDM) framework that combines the VIKOR method with data fuzzification to quantify the spatial flood vulnerability including multiple criteria. In general, GDM method is an effective tool for formulating a compromise solution that involves various decision makers since various stakeholders may have different perspectives on their flood risk/vulnerability management responses. The GDM approach is designed to achieve consensus building that reflects the viewpoints of each participant. The fuzzy VIKOR method was developed to solve multi-criteria decision making (MCDM) problems with conflicting and noncommensurable criteria. This comprising method can be used to obtain a nearly ideal solution according to all established criteria. This approach effectively can propose some compromising decisions by combining the GDM method and fuzzy VIKOR method. The spatial flood vulnerability of the southern Han River using the GDM approach combined with the fuzzy VIKOR method was compared with the spatial flood vulnerability using general MCDM methods, such as the fuzzy TOPSIS and classical GDM methods (i.e., Borda, Condorcet, and Copeland). As a result, the proposed fuzzy GDM approach can reduce the uncertainty in the data confidence and weight derivation techniques. Thus, the combination of the GDM approach with the fuzzy VIKOR method can provide robust prioritization because it actively reflects the opinions of various groups and considers uncertainty in the input data.

Design of Adaptive Policy Pathways under Deep Uncertainties

NASA Astrophysics Data System (ADS)

Babovic, Vladan

2013-04-01

The design of large-scale engineering and infrastructural systems today is growing in complexity. Designers need to consider sociotechnical uncertainties, intricacies, and processes in the long- term strategic deployment and operations of these systems. In this context, water and spatial management is increasingly challenged not only by climate-associated changes such as sea level rise and increased spatio-temporal variability of precipitation, but also by pressures due to population growth and particularly accelerating rate of urbanisation. Furthermore, high investment costs and long term-nature of water-related infrastructure projects requires long-term planning perspective, sometimes extending over many decades. Adaptation to such changes is not only determined by what is known or anticipated at present, but also by what will be experienced and learned as the future unfolds, as well as by policy responses to social and water events. As a result, a pathway emerges. Instead of responding to 'surprises' and making decisions on ad hoc basis, exploring adaptation pathways into the future provide indispensable support in water management decision-making. In this contribution, a structured approach for designing a dynamic adaptive policy based on the concepts of adaptive policy making and adaptation pathways is introduced. Such an approach provides flexibility which allows change over time in response to how the future unfolds, what is learned about the system, and changes in societal preferences. The introduced flexibility provides means for dealing with complexities of adaptation under deep uncertainties. It enables engineering systems to change in the face of uncertainty to reduce impacts from downside scenarios while capitalizing on upside opportunities. This contribution presents comprehensive framework for development and deployment of adaptive policy pathway framework, and demonstrates its performance under deep uncertainties on a case study related to urban water catchment in Singapore. Ingredients of this approach are: (a) transient scenarios (time series of various uncertain developments such as climate change, economic developments, societal changes), (b) a methodology for exploring many options and sequences of these options across different futures, and (c) a stepwise policy analysis. The strategy is applied on case of flexible deployment of novel, so-called Next Generation Infrastructure, and assessed in context of the proposed. Results of the study show that flexible design alternatives deliver much enhanced performance compared to systems optimized under deterministic forecasts of the future. The work also demonstrates that explicit incorporation of uncertainty and flexibility into decision-making process reduces capital expenditures while allowing decision makers to learn about system evolution throughout the lifetime of the project.

Decision Making in Health and Medicine

NASA Astrophysics Data System (ADS)

Hunink, Myriam; Glasziou, Paul; Siegel, Joanna; Weeks, Jane; Pliskin, Joseph; Elstein, Arthur; Weinstein, Milton C.

2001-11-01

Decision making in health care means navigating through a complex and tangled web of diagnostic and therapeutic uncertainties, patient preferences and values, and costs. In addition, medical therapies may include side effects, surgery may lead to undesirable complications, and diagnostic technologies may produce inconclusive results. In many clinical and health policy decisions it is necessary to counterbalance benefits and risks, and to trade off competing objectives such as maximizing life expectancy vs optimizing quality of life vs minimizing the required resources. This textbook plots a clear course through these complex and conflicting variables. It clearly explains and illustrates tools for integrating quantitative evidence-based data and subjective outcome values in making clinical and health policy decisions. An accompanying CD-ROM features solutions to the exercises, PowerPoint® presentations of the illustrations, and sample models and tables.

The known unknowns: neural representation of second-order uncertainty, and ambiguity

PubMed Central

Bach, Dominik R.; Hulme, Oliver; Penny, William D.; Dolan, Raymond J.

2011-01-01

Predictions provided by action-outcome probabilities entail a degree of (first-order) uncertainty. However, these probabilities themselves can be imprecise and embody second-order uncertainty. Tracking second-order uncertainty is important for optimal decision making and reinforcement learning. Previous functional magnetic resonance imaging investigations of second-order uncertainty in humans have drawn on an economic concept of ambiguity, where action-outcome associations in a gamble are either known (unambiguous) or completely unknown (ambiguous). Here, we relaxed the constraints associated with a purely categorical concept of ambiguity and varied the second-order uncertainty of gambles continuously, quantified as entropy over second-order probabilities. We show that second-order uncertainty influences decisions in a pessimistic way by biasing second-order probabilities, and that second-order uncertainty is negatively correlated with posterior cingulate cortex activity. The category of ambiguous (compared to non-ambiguous) gambles also biased choice in a similar direction, but was associated with distinct activation of a posterior parietal cortical area; an activation that we show reflects a different computational mechanism. Our findings indicate that behavioural and neural responses to second-order uncertainty are distinct from those associated with ambiguity and may call for a reappraisal of previous data. PMID:21451019

Getting Beyond First Base: Science-Society Communication for Climate Adaptation

NASA Astrophysics Data System (ADS)

Garfin, G. M.

2010-12-01

At a 2009 international workshop on transboundary climate and water issues, a former World Bank official and current academic mentioned that “crisis, risk and uncertainty” are the three words that motivate decision-makers to act. However, decade-scale climate variability and trend-driven climate changes are phenomena characterized by creeping onset, diffuse and non-synchronous impacts, and complexity. Thus, there is a balancing act to addressing the complexity of uncertainties, while adequately assessing risk, and keeping the potential for crisis in focus without creating a “Chicken Little” situation. This presentation examines translational science approaches to three stages in the continuum from initial communication to societal action: raising awareness, building capacity, and making progress toward action. We examine the roles of scientists, knowledge brokers, decision makers, and the general public in the context of climate services. Although there is no “one size fits all” science communication method, we argue that best practices require that scientists pay particular attention to cultural and political sensitivities associated with decision contexts. We give examples from seasonal forecast communication, drought planning, climate literacy and education needs assessments, and the nexus of climate adaptation planning and uncertainty. In general, we find that constructive approaches make use of alliances with early adopters and opinion leaders, and make strong links between (a) predictions, impacts and solutions and (b) global to regional to local spatial scales. Often building partnerships for moving science information from observations to knowledge to decisions requires discussion support, a concept borrowed from Australian colleagues, which describes a multi-faceted and undervalued aspect of moving forward in adaptation planning: clarifying plausible cascades of interactions leading to potential impacts. Discussion support also fosters examination of how others confronting similar issues have both adapted well-known management strategies and developed outside-the-box ideas to move beyond “uncertainty paralysis.” Some preliminary conclusions from our work include the following: (a) iterative and ongoing engagements are necessary to build trust and bolster science credibility; (b) uncertainty, formerly a topic to avoided, forms the foundation for constructive progress in adaptation planning and improving forecast use, and (c) candid exploration of the array of uncertainties, which includes those due to modeling, institutional, policy and economic factors - with decision-making peers, science translators, and subject experts, is needed to stimulate constructive thinking on adaptation strategies. For scientists, gaining insight into how decisions are made is the most important part of scientist-stakeholder interactions. For managers, the most important factors are holistic, cross-sectoral, examination of both climate and non-climate factors affecting resources, and the diversity of public values regarding resource management.

Revealing, Reducing, and Representing Uncertainties in New Hydrologic Projections for Climate-changed Futures

NASA Astrophysics Data System (ADS)

Arnold, Jeffrey; Clark, Martyn; Gutmann, Ethan; Wood, Andy; Nijssen, Bart; Rasmussen, Roy

2016-04-01

The United States Army Corps of Engineers (USACE) has had primary responsibility for multi-purpose water resource operations on most of the major river systems in the U.S. for more than 200 years. In that time, the USACE projects and programs making up those operations have proved mostly robust against the range of natural climate variability encountered over their operating life spans. However, in some watersheds and for some variables, climate change now is known to be shifting the hydroclimatic baseline around which that natural variability occurs and changing the range of that variability as well. This makes historical stationarity an inappropriate basis for assessing continued project operations under climate-changed futures. That means new hydroclimatic projections are required at multiple scales to inform decisions about specific threats and impacts, and for possible adaptation responses to limit water-resource vulnerabilities and enhance operational resilience. However, projections of possible future hydroclimatologies have myriad complex uncertainties that require explicit guidance for interpreting and using them to inform those decisions about climate vulnerabilities and resilience. Moreover, many of these uncertainties overlap and interact. Recent work, for example, has shown the importance of assessing the uncertainties from multiple sources including: global model structure [Meehl et al., 2005; Knutti and Sedlacek, 2013]; internal climate variability [Deser et al., 2012; Kay et al., 2014]; climate downscaling methods [Gutmann et al., 2012; Mearns et al., 2013]; and hydrologic models [Addor et al., 2014; Vano et al., 2014; Mendoza et al., 2015]. Revealing, reducing, and representing these uncertainties is essential for defining the plausible quantitative climate change narratives required to inform water-resource decision-making. And to be useful, such quantitative narratives, or storylines, of climate change threats and hydrologic impacts must sample from the full range of uncertainties associated with all parts of the simulation chain, from global climate models with simulations of natural climate variability, through regional climate downscaling, and on to modeling of affected hydrologic processes and downstream water resources impacts. This talk will present part of the work underway now both to reveal and reduce some important uncertainties and to develop explicit guidance for future generation of quantitative hydroclimatic storylines. Topics will include: 1- model structural and parameter-set limitations of some methods widely used to quantify climate impacts to hydrologic processes [Gutmann et al., 2014; Newman et al., 2015]; 2- development and evaluation of new, spatially consistent, U.S. national-scale climate downscaling and hydrologic simulation capabilities directly relevant at the multiple scales of water-resource decision-making [Newman et al., 2015; Mizukami et al., 2015; Gutmann et al., 2016]; and 3- development and evaluation of advanced streamflow forecasting methods to reduce and represent integrated uncertainties in a tractable way [Wood et al., 2014; Wood et al., 2015]. A key focus will be areas where climatologic and hydrologic science is currently under-developed to inform decisions - or is perhaps wrongly scaled or misapplied in practice - indicating the need for additional fundamental science and interpretation.

Differing levels of clinical evidence: exploring communication challenges in shared decision making. Introduction.

PubMed

Smith, Quentin W; Street, Richard L; Volk, Robert J; Fordis, Michael

2013-02-01

The near ubiquitous access to information is transforming the roles and relationships among clinical professionals, patients, and their care givers in nearly all aspects of healthcare. Informed patients engage their physicians in conversations about their conditions, options and the tradeoffs among diagnostic and therapeutic benefits and harms. The processes of care today increasingly and explicitly integrate exploration of patient values and preferences as patients and clinicians jointly engage in reaching decisions about care. The informed patient of today who can understand and use scientific information can participate as an equal partner with her clinician. Others with beliefs or educational, cultural, or literacy backgrounds that pose challenges to comprehending and applying evidence may face disenfranchisement. These barriers are significant enough, even in the face of certainty of evidence, that clinicians and investigators have given much thought to how best to engage all patients in decision making. However, barriers remain, as most decision making must occur in settings where uncertainty, if not considerable uncertainty, accompanies any statement of what we know. In September 2011, health care and health communication experts came together in Rockville, Maryland under the auspices of the Agency for Healthcare Research and Quality (AHRQ) John M. Eisenberg Center for Clinical Decisions and Communications Science Annual Meeting to explore the challenges of differing levels of evidence in promoting shared decisions and to propose strategies for going forward in addressing these challenges. Eight scholarly papers emerged, and with this introductory article, comprise this special issue of Medical Care Research and Review.

Frequencies of decision making and monitoring in adaptive resource management

PubMed Central

Johnson, Fred A.

2017-01-01

Adaptive management involves learning-oriented decision making in the presence of uncertainty about the responses of a resource system to management. It is implemented through an iterative sequence of decision making, monitoring and assessment of system responses, and incorporating what is learned into future decision making. Decision making at each point is informed by a value or objective function, for example total harvest anticipated over some time frame. The value function expresses the value associated with decisions, and it is influenced by system status as updated through monitoring. Often, decision making follows shortly after a monitoring event. However, it is certainly possible for the cadence of decision making to differ from that of monitoring. In this paper we consider different combinations of annual and biennial decision making, along with annual and biennial monitoring. With biennial decision making decisions are changed only every other year; with biennial monitoring field data are collected only every other year. Different cadences of decision making combine with annual and biennial monitoring to define 4 scenarios. Under each scenario we describe optimal valuations for active and passive adaptive decision making. We highlight patterns in valuation among scenarios, depending on the occurrence of monitoring and decision making events. Differences between years are tied to the fact that every other year a new decision can be made no matter what the scenario, and state information is available to inform that decision. In the subsequent year, however, in 3 of the 4 scenarios either a decision is repeated or monitoring does not occur (or both). There are substantive differences in optimal values among the scenarios, as well as the optimal policies producing those values. Especially noteworthy is the influence of monitoring cadence on valuation in some years. We highlight patterns in policy and valuation among the scenarios, and discuss management implications and extensions. PMID:28800591

Frequencies of decision making and monitoring in adaptive resource management

USGS Publications Warehouse

Williams, Byron K.; Johnson, Fred A.

2017-01-01

Adaptive management involves learning-oriented decision making in the presence of uncertainty about the responses of a resource system to management. It is implemented through an iterative sequence of decision making, monitoring and assessment of system responses, and incorporating what is learned into future decision making. Decision making at each point is informed by a value or objective function, for example total harvest anticipated over some time frame. The value function expresses the value associated with decisions, and it is influenced by system status as updated through monitoring. Often, decision making follows shortly after a monitoring event. However, it is certainly possible for the cadence of decision making to differ from that of monitoring. In this paper we consider different combinations of annual and biennial decision making, along with annual and biennial monitoring. With biennial decision making decisions are changed only every other year; with biennial monitoring field data are collected only every other year. Different cadences of decision making combine with annual and biennial monitoring to define 4 scenarios. Under each scenario we describe optimal valuations for active and passive adaptive decision making. We highlight patterns in valuation among scenarios, depending on the occurrence of monitoring and decision making events. Differences between years are tied to the fact that every other year a new decision can be made no matter what the scenario, and state information is available to inform that decision. In the subsequent year, however, in 3 of the 4 scenarios either a decision is repeated or monitoring does not occur (or both). There are substantive differences in optimal values among the scenarios, as well as the optimal policies producing those values. Especially noteworthy is the influence of monitoring cadence on valuation in some years. We highlight patterns in policy and valuation among the scenarios, and discuss management implications and extensions.

Tuning the Brake While Raising the Stake: Network Dynamics during Sequential Decision-Making.

PubMed

Meder, David; Haagensen, Brian Numelin; Hulme, Oliver; Morville, Tobias; Gelskov, Sofie; Herz, Damian Marc; Diomsina, Beata; Christensen, Mark Schram; Madsen, Kristoffer Hougaard; Siebner, Hartwig Roman

2016-05-11

When gathering valued goods, risk and reward are often coupled and escalate over time, for instance, during foraging, trading, or gambling. This escalating frame requires agents to continuously balance expectations of reward against those of risk. To address how the human brain dynamically computes these tradeoffs, we performed whole-brain fMRI while healthy young individuals engaged in a sequential gambling task. Participants were repeatedly confronted with the option to continue with throwing a die to accumulate monetary reward under escalating risk, or the alternative option to stop to bank the current balance. Within each gambling round, the accumulation of gains gradually increased reaction times for "continue" choices, indicating growing uncertainty in the decision to continue. Neural activity evoked by "continue" choices was associated with growing activity and connectivity of a cortico-subcortical "braking" network that positively scaled with the accumulated gains, including pre-supplementary motor area (pre-SMA), inferior frontal gyrus, caudate, and subthalamic nucleus (STN). The influence of the STN on continue-evoked activity in the pre-SMA was predicted by interindividual differences in risk-aversion attitudes expressed during the gambling task. Furthermore, activity in dorsal anterior cingulate cortex (ACC) reflected individual choice tendencies by showing increased activation when subjects made nondefault "continue" choices despite an increasing tendency to stop, but ACC activity did not change in proportion with subjective choice uncertainty. Together, the results implicate a key role of dorsal ACC, pre-SMA, inferior frontal gyrus, and STN in computing the trade-off between escalating reward and risk in sequential decision-making. Using a paradigm where subjects experienced increasing potential rewards coupled with increasing risk, this study addressed two unresolved questions in the field of decision-making: First, we investigated an "inhibitory" network of regions that has so far been investigated with externally cued action inhibition. In this study, we show that the dynamics in this network under increasingly risky decisions are predictive of subjects' risk attitudes. Second, we contribute to a currently ongoing debate about the anterior cingulate cortex's role in sequential foraging decisions by showing that its activity is related to making nondefault choices rather than to choice uncertainty. Copyright © 2016 Meder, Haagensen, et al.

Learning in Noise: Dynamic Decision-Making in a Variable Environment

PubMed Central

Gureckis, Todd M.; Love, Bradley C.

2009-01-01

In engineering systems, noise is a curse, obscuring important signals and increasing the uncertainty associated with measurement. However, the negative effects of noise and uncertainty are not universal. In this paper, we examine how people learn sequential control strategies given different sources and amounts of feedback variability. In particular, we consider people’s behavior in a task where short- and long-term rewards are placed in conflict (i.e., the best option in the short-term is worst in the long-term). Consistent with a model based on reinforcement learning principles (Gureckis & Love, in press), we find that learners differentially weight information predictive of the current task state. In particular, when cues that signal state are noisy and uncertain, we find that participants’ ability to identify an optimal strategy is strongly impaired relative to equivalent amounts of uncertainty that obscure the rewards/valuations of those states. In other situations, we find that noise and uncertainty in reward signals may paradoxically improve performance by encouraging exploration. Our results demonstrate how experimentally-manipulated task variability can be used to test predictions about the mechanisms that learners engage in dynamic decision making tasks. PMID:20161328

Neural mechanisms regulating different forms of risk-related decision-making: Insights from animal models.

PubMed

Orsini, Caitlin A; Moorman, David E; Young, Jared W; Setlow, Barry; Floresco, Stan B

2015-11-01

Over the past 20 years there has been a growing interest in the neural underpinnings of cost/benefit decision-making. Recent studies with animal models have made considerable advances in our understanding of how different prefrontal, striatal, limbic and monoaminergic circuits interact to promote efficient risk/reward decision-making, and how dysfunction in these circuits underlies aberrant decision-making observed in numerous psychiatric disorders. This review will highlight recent findings from studies exploring these questions using a variety of behavioral assays, as well as molecular, pharmacological, neurophysiological, and translational approaches. We begin with a discussion of how neural systems related to decision subcomponents may interact to generate more complex decisions involving risk and uncertainty. This is followed by an overview of interactions between prefrontal-amygdala-dopamine and habenular circuits in regulating choice between certain and uncertain rewards and how different modes of dopamine transmission may contribute to these processes. These data will be compared with results from other studies investigating the contribution of some of these systems to guiding decision-making related to rewards vs. punishment. Lastly, we provide a brief summary of impairments in risk-related decision-making associated with psychiatric disorders, highlighting recent translational studies in laboratory animals. Copyright © 2015 Elsevier Ltd. All rights reserved.

Multi-criteria decision-making on assessment of proposed tidal barrage schemes in terms of environmental impacts.

PubMed

Wu, Yunna; Xu, Chuanbo; Ke, Yiming; Chen, Kaifeng; Xu, Hu

2017-12-15

For tidal range power plants to be sustainable, the environmental impacts caused by the implement of various tidal barrage schemes must be assessed before construction. However, several problems exist in the current researches: firstly, evaluation criteria of the tidal barrage schemes environmental impact assessment (EIA) are not adequate; secondly, uncertainty of criteria information fails to be processed properly; thirdly, correlation among criteria is unreasonably measured. Hence the contributions of this paper are as follows: firstly, an evaluation criteria system is established from three dimensions of hydrodynamic, biological and morphological aspects. Secondly, cloud model is applied to describe the uncertainty of criteria information. Thirdly, Choquet integral with respect to λ-fuzzy measure is introduced to measure the correlation among criteria. On the above bases, a multi-criteria decision-making decision framework for tidal barrage scheme EIA is established to select the optimal scheme. Finally, a case study demonstrates the effectiveness of the proposed framework. Copyright © 2017 Elsevier Ltd. All rights reserved.

Scalable methodology for large scale building energy improvement: Relevance of calibration in model-based retrofit analysis

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

Heo, Yeonsook; Augenbroe, Godfried; Graziano, Diane

2015-05-01

The increasing interest in retrofitting of existing buildings is motivated by the need to make a major contribution to enhancing building energy efficiency and reducing energy consumption and CO2 emission by the built environment. This paper examines the relevance of calibration in model-based analysis to support decision-making for energy and carbon efficiency retrofits of individual buildings and portfolios of buildings. The authors formulate a set of real retrofit decision-making situations and evaluate the role of calibration by using a case study that compares predictions and decisions from an uncalibrated model with those of a calibrated model. The case study illustratesmore » both the mechanics and outcomes of a practical alternative to the expert- and time-intense application of dynamic energy simulation models for large-scale retrofit decision-making under uncertainty.« less

Effects of Gain/Loss Framing in Cyber Defense Decision-Making

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

Bos, Nathan; Paul, Celeste; Gersh, John

Cyber defense requires decision making under uncertainty. Yet this critical area has not been a strong focus of research in judgment and decision-making. Future defense systems, which will rely on software-defined networks and may employ ‘moving target’ defenses, will increasingly automate lower level detection and analysis, but will still require humans in the loop for higher level judgment. We studied the decision making process and outcomes of 17 experienced network defense professionals who worked through a set of realistic network defense scenarios. We manipulated gain versus loss framing in a cyber defense scenario, and found significant effects in one ofmore » two focal problems. Defenders that began with a network already in quarantine (gain framing) used a quarantine system more than those that did not (loss framing). We also found some difference in perceived workload and efficacy. Alternate explanations of these findings and implications for network defense are discussed.« less

Argumentation for Decision Making

NASA Astrophysics Data System (ADS)

Amgoud, Leila

Decision making, often viewed as a form of reasoning toward action, has raised the interest of many scholars including economists, psychologists, and computer scientists for a long time. Any decision problem amounts to selecting the “best” or sufficiently “good” action(s) that are feasible among different alternatives, given some available information about the current state of the world and the consequences of potential actions. Available information may be incomplete or pervaded with uncertainty. Besides, the goodness of an action is judged by estimating how much its possible consequences fit the preferences of the decision maker. This agent is assumed to behave in a rational way [29] amgoud-woold, at least in the sense that his decisions should be as much as possible consistent with his preferences.

Telling the truth in the face of medical uncertainty and disagreement.

PubMed

Forman, E N; Ladd, R E

1989-01-01

The pediatric oncologist often must face medical uncertainty and differing opinions among consultants. This raises a dilemma about telling the truth: Does the ethical requirement for telling the truth include informing parents about uncertainties and disagreements, or does the obligation to protect from emotional burden justify withholding information? Answering this question requires an analysis of the nature of medical disagreements. It is argued that disagreements that arise because of medical uncertainties are not disagreements about facts, but disagreements in attitude, where appeal to expertise is not possible. Thus, treatment recommendations must be offered carefully, in order to avoid imposing values on patients. Physicians should make clear the reasoning behind their recommendations, as well as areas of uncertainty. This approach offers the only possibility for parents to give informed consent and to participate in responsible decision making for their child that is consistent with their own values.

Exploring Scientific Information for Policy Making under Deep Uncertainty

NASA Astrophysics Data System (ADS)

Forni, L.; Galaitsi, S.; Mehta, V. K.; Escobar, M.; Purkey, D. R.; Depsky, N. J.; Lima, N. A.

2016-12-01

Each actor evaluating potential management strategies brings her/his own distinct set of objectives to a complex decision space of system uncertainties. The diversity of these objectives require detailed and rigorous analyses that responds to multifaceted challenges. However, the utility of this information depends on the accessibility of scientific information to decision makers. This paper demonstrates data visualization tools for presenting scientific results to decision makers in two case studies, La Paz/ El Alto, Bolivia, and Yuba County,California. Visualization output from the case studies combines spatiotemporal, multivariate and multirun/multiscenario information to produce information corresponding to the objectives defined by key actors and stakeholders. These tools can manage complex data and distill scientific information into accessible formats. Using the visualizations, scientists and decision makers can navigate the decision space and potential objective trade-offs to facilitate discussion and consensus building. These efforts can support identifying stable negotiatedagreements between different stakeholders.

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

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

Cardenas, Ibsen C., E-mail: c.cardenas@utwente.nl; Halman, Johannes I.M., E-mail: J.I.M.Halman@utwente.nl

Uncertainty is virtually unavoidable in environmental impact assessments (EIAs). From the literature related to treating and managing uncertainty, we have identified specific techniques for coping with uncertainty in EIAs. Here, we have focused on basic steps in the decision-making process that take place within an EIA setting. More specifically, we have identified uncertainties involved in each decision-making step and discussed the extent to which these can be treated and managed in the context of an activity or project that may have environmental impacts. To further demonstrate the relevance of the techniques identified, we have examined the extent to which themore » EIA guidelines currently used in Colombia consider and provide guidance on managing the uncertainty involved in these assessments. Some points that should be considered in order to provide greater robustness in impact assessments in Colombia have been identified. These include the management of stakeholder values, the systematic generation of project options, and their associated impacts as well as the associated management actions, and the evaluation of uncertainties and assumptions. We believe that the relevant and specific techniques reported here can be a reference for future evaluations of other EIA guidelines in different countries. - Highlights: • uncertainty is unavoidable in environmental impact assessments, EIAs; • we have identified some open techniques to EIAs for treating and managing uncertainty in these assessments; • points for improvement that should be considered in order to provide greater robustness in EIAs in Colombia have been identified; • the paper provides substantiated a reference for possible examinations of EIAs guidelines in other countries.« less

Optimization of monitoring networks based on uncertainty quantification of model predictions of contaminant transport

NASA Astrophysics Data System (ADS)

Vesselinov, V. V.; Harp, D.

2010-12-01

The process of decision making to protect groundwater resources requires a detailed estimation of uncertainties in model predictions. Various uncertainties associated with modeling a natural system, such as: (1) measurement and computational errors; (2) uncertainties in the conceptual model and model-parameter estimates; (3) simplifications in model setup and numerical representation of governing processes, contribute to the uncertainties in the model predictions. Due to this combination of factors, the sources of predictive uncertainties are generally difficult to quantify individually. Decision support related to optimal design of monitoring networks requires (1) detailed analyses of existing uncertainties related to model predictions of groundwater flow and contaminant transport, (2) optimization of the proposed monitoring network locations in terms of their efficiency to detect contaminants and provide early warning. We apply existing and newly-proposed methods to quantify predictive uncertainties and to optimize well locations. An important aspect of the analysis is the application of newly-developed optimization technique based on coupling of Particle Swarm and Levenberg-Marquardt optimization methods which proved to be robust and computationally efficient. These techniques and algorithms are bundled in a software package called MADS. MADS (Model Analyses for Decision Support) is an object-oriented code that is capable of performing various types of model analyses and supporting model-based decision making. The code can be executed under different computational modes, which include (1) sensitivity analyses (global and local), (2) Monte Carlo analysis, (3) model calibration, (4) parameter estimation, (5) uncertainty quantification, and (6) model selection. The code can be externally coupled with any existing model simulator through integrated modules that read/write input and output files using a set of template and instruction files (consistent with the PEST I/O protocol). MADS can also be internally coupled with a series of built-in analytical simulators. MADS provides functionality to work directly with existing control files developed for the code PEST (Doherty 2009). To perform the computational modes mentioned above, the code utilizes (1) advanced Latin-Hypercube sampling techniques (including Improved Distributed Sampling), (2) various gradient-based Levenberg-Marquardt optimization methods, (3) advanced global optimization methods (including Particle Swarm Optimization), and (4) a selection of alternative objective functions. The code has been successfully applied to perform various model analyses related to environmental management of real contamination sites. Examples include source identification problems, quantification of uncertainty, model calibration, and optimization of monitoring networks. The methodology and software codes are demonstrated using synthetic and real case studies where monitoring networks are optimized taking into account the uncertainty in model predictions of contaminant transport.

Robustness of risk maps and survey networks to knowledge gaps about a new invasive pest.

PubMed

Yemshanov, Denys; Koch, Frank H; Ben-Haim, Yakov; Smith, William D

2010-02-01

In pest risk assessment it is frequently necessary to make management decisions regarding emerging threats under severe uncertainty. Although risk maps provide useful decision support for invasive alien species, they rarely address knowledge gaps associated with the underlying risk model or how they may change the risk estimates. Failure to recognize uncertainty leads to risk-ignorant decisions and miscalculation of expected impacts as well as the costs required to minimize these impacts. Here we use the information gap concept to evaluate the robustness of risk maps to uncertainties in key assumptions about an invading organism. We generate risk maps with a spatial model of invasion that simulates potential entries of an invasive pest via international marine shipments, their spread through a landscape, and establishment on a susceptible host. In particular, we focus on the question of how much uncertainty in risk model assumptions can be tolerated before the risk map loses its value. We outline this approach with an example of a forest pest recently detected in North America, Sirex noctilio Fabricius. The results provide a spatial representation of the robustness of predictions of S. noctilio invasion risk to uncertainty and show major geographic hotspots where the consideration of uncertainty in model parameters may change management decisions about a new invasive pest. We then illustrate how the dependency between the extent of uncertainties and the degree of robustness of a risk map can be used to select a surveillance network design that is most robust to knowledge gaps about the pest.

The Iowa Gambling Task and the three fallacies of dopamine in gambling disorder

PubMed Central

Linnet, Jakob

2013-01-01

Gambling disorder sufferers prefer immediately larger rewards despite long term losses on the Iowa Gambling Task (IGT), and these impairments are associated with dopamine dysfunctions. Dopamine is a neurotransmitter linked with temporal and structural dysfunctions in substance use disorder, which has supported the idea of impaired decision-making and dopamine dysfunctions in gambling disorder. However, evidence from substance use disorders cannot be directly transferred to gambling disorder. This article focuses on three hypotheses of dopamine dysfunctions in gambling disorder, which appear to be “fallacies,” i.e., have not been supported in a series of positron emission tomography (PET) studies. The first “fallacy” suggests that gambling disorder sufferers have lower dopamine receptor availability, as seen in substance use disorders. However, no evidence supported this hypothesis. The second “fallacy” suggests that maladaptive decision-making in gambling disorder is associated with higher dopamine release during gambling. No evidence supported the hypothesis, and the literature on substance use disorders offers limited support for this hypothesis. The third “fallacy” suggests that maladaptive decision-making in gambling disorder is associated with higher dopamine release during winning. The evidence did not support this hypothesis either. Instead, dopaminergic coding of reward prediction and uncertainty might better account for dopamine dysfunctions in gambling disorder. Studies of reward prediction and reward uncertainty show a sustained dopamine response toward stimuli with maximum uncertainty, which may explain the continued dopamine release and gambling despite losses in gambling disorder. The findings from the studies presented here are consistent with the notion of dopaminergic dysfunctions of reward prediction and reward uncertainty signals in gambling disorder. PMID:24115941

Communication between patients and providers and informed decision making.

PubMed

Elmore, Joann G; Ganschow, Pamela S; Geller, Berta M

2010-01-01

Women with ductal carcinoma in situ (DCIS) need to comprehend the meaning of the diagnosis and the potential benefits and harms of treatment options. Full and understandable information is a requirement, not an option. However, with DCIS, as with many areas of medicine, a high level of uncertainty about the disease remains. In this article, we define informed medical decision making, review challenges to its implementation, and provide suggestions on how to improve communication with women about the diagnosis and treatment of DCIS.

Intelligence Preparation of the Battlefield: Is It Worth the Effort?

DTIC Science & Technology

1990-12-27

Oaetaon and Na~lpOKu. Iji Jelef/qonl 1. AGENCY USE ONLY (Leave blanko) 2. REPORT DATE 3. REPORT TYPE AND DATES COVERED 1 71/0MONOGRAPH_____________ 4...process as a decision making tool. In or der for IPB to be of practical use in decision making it must reduce uncertainty in a timely manner. Today’s...findings of Combat Maneu- ver Training Center and field training exercises regarding recent use of IPB in tactical planning. Section four completes the study

Assessment of Two Desk-Top Computer Simulations Used to Train Tactical Decision Making (TDM) of Small Unit Infantry Leaders

DTIC Science & Technology

2007-04-01

judgmental self-doubt, depression, and causal uncertainty, tend to take fewer risks, and have lower self-esteem. Results from two studies (Nygren, 2000...U.S. Army Research Institute for the Behavioral and Social Sciences Research Report 1869 Assessment of Two Desk-Top Computer Simulations Used to...SUBTITLE 5a. CONTRACT OR GRANT NUMBER Assessment of Two Desk-Top Computer Simulations Used to Train Tactical Decision Making (TDM) of Small Unit

Feedback Blunting: Total Sleep Deprivation Impairs Decision Making that Requires Updating Based on Feedback.

PubMed

Whitney, Paul; Hinson, John M; Jackson, Melinda L; Van Dongen, Hans P A

2015-05-01

To better understand the sometimes catastrophic effects of sleep loss on naturalistic decision making, we investigated effects of sleep deprivation on decision making in a reversal learning paradigm requiring acquisition and updating of information based on outcome feedback. Subjects were randomized to a sleep deprivation or control condition, with performance testing at baseline, after 2 nights of total sleep deprivation (or rested control), and following 2 nights of recovery sleep. Subjects performed a decision task involving initial learning of go and no go response sets followed by unannounced reversal of contingencies, requiring use of outcome feedback for decisions. A working memory scanning task and psychomotor vigilance test were also administered. Six consecutive days and nights in a controlled laboratory environment with continuous behavioral monitoring. Twenty-six subjects (22-40 y of age; 10 women). Thirteen subjects were randomized to a 62-h total sleep deprivation condition; the others were controls. Unlike controls, sleep deprived subjects had difficulty with initial learning of go and no go stimuli sets and had profound impairment adapting to reversal. Skin conductance responses to outcome feedback were diminished, indicating blunted affective reactions to feedback accompanying sleep deprivation. Working memory scanning performance was not significantly affected by sleep deprivation. And although sleep deprived subjects showed expected attentional lapses, these could not account for impairments in reversal learning decision making. Sleep deprivation is particularly problematic for decision making involving uncertainty and unexpected change. Blunted reactions to feedback while sleep deprived underlie failures to adapt to uncertainty and changing contingencies. Thus, an error may register, but with diminished effect because of reduced affective valence of the feedback or because the feedback is not cognitively bound with the choice. This has important implications for understanding and managing sleep loss-induced cognitive impairment in emergency response, disaster management, military operations, and other dynamic real-world settings with uncertain outcomes and imperfect information. © 2015 Associated Professional Sleep Societies, LLC.

Integrating uncertainty into public energy research and development decisions

NASA Astrophysics Data System (ADS)

Anadón, Laura Díaz; Baker, Erin; Bosetti, Valentina

2017-05-01

Public energy research and development (R&D) is recognized as a key policy tool for transforming the world's energy system in a cost-effective way. However, managing the uncertainty surrounding technological change is a critical challenge for designing robust and cost-effective energy policies. The design of such policies is particularly important if countries are going to both meet the ambitious greenhouse-gas emissions reductions goals set by the Paris Agreement and achieve the required harmonization with the broader set of objectives dictated by the Sustainable Development Goals. The complexity of informing energy technology policy requires, and is producing, a growing collaboration between different academic disciplines and practitioners. Three analytical components have emerged to support the integration of technological uncertainty into energy policy: expert elicitations, integrated assessment models, and decision frameworks. Here we review efforts to incorporate all three approaches to facilitate public energy R&D decision-making under uncertainty. We highlight emerging insights that are robust across elicitations, models, and frameworks, relating to the allocation of public R&D investments, and identify gaps and challenges that remain.

Testosterone, Cortisol and Financial Risk-Taking

PubMed Central

Herbert, Joe

2018-01-01

Both testosterone and cortisol have major actions on financial decision-making closely related to their primary biological functions, reproductive success and response to stress, respectively. Financial risk-taking represents a particular example of strategic decisions made in the context of choice under conditions of uncertainty. Such decisions have multiple components, and this article considers how much we know of how either hormone affects risk-appetite, reward value, information processing and estimation of the costs and benefits of potential success or failure, both personal and social. It also considers how far we can map these actions on neural mechanisms underlying risk appetite and decision-making, with particular reference to areas of the brain concerned in either cognitive or emotional functions. PMID:29867399

Feedback Blunting: Total Sleep Deprivation Impairs Decision Making that Requires Updating Based on Feedback

PubMed Central

Whitney, Paul; Hinson, John M.; Jackson, Melinda L.; Van Dongen, Hans P.A.

2015-01-01

Study Objectives: To better understand the sometimes catastrophic effects of sleep loss on naturalistic decision making, we investigated effects of sleep deprivation on decision making in a reversal learning paradigm requiring acquisition and updating of information based on outcome feedback. Design: Subjects were randomized to a sleep deprivation or control condition, with performance testing at baseline, after 2 nights of total sleep deprivation (or rested control), and following 2 nights of recovery sleep. Subjects performed a decision task involving initial learning of go and no go response sets followed by unannounced reversal of contingencies, requiring use of outcome feedback for decisions. A working memory scanning task and psychomotor vigilance test were also administered. Setting: Six consecutive days and nights in a controlled laboratory environment with continuous behavioral monitoring. Subjects: Twenty-six subjects (22–40 y of age; 10 women). Interventions: Thirteen subjects were randomized to a 62-h total sleep deprivation condition; the others were controls. Results: Unlike controls, sleep deprived subjects had difficulty with initial learning of go and no go stimuli sets and had profound impairment adapting to reversal. Skin conductance responses to outcome feedback were diminished, indicating blunted affective reactions to feedback accompanying sleep deprivation. Working memory scanning performance was not significantly affected by sleep deprivation. And although sleep deprived subjects showed expected attentional lapses, these could not account for impairments in reversal learning decision making. Conclusions: Sleep deprivation is particularly problematic for decision making involving uncertainty and unexpected change. Blunted reactions to feedback while sleep deprived underlie failures to adapt to uncertainty and changing contingencies. Thus, an error may register, but with diminished effect because of reduced affective valence of the feedback or because the feedback is not cognitively bound with the choice. This has important implications for understanding and managing sleep loss-induced cognitive impairment in emergency response, disaster management, military operations, and other dynamic real-world settings with uncertain outcomes and imperfect information. Citation: Whitney P, Hinson JM, Jackson ML, Van Dongen HPA. Feedback blunting: total sleep deprivation impairs decision making that requires updating based on feedback. SLEEP 2015;38(5):745–754. PMID:25515105

Statistics, Uncertainty, and Transmitted Variation

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

Wendelberger, Joanne Roth

2014-11-05

The field of Statistics provides methods for modeling and understanding data and making decisions in the presence of uncertainty. When examining response functions, variation present in the input variables will be transmitted via the response function to the output variables. This phenomenon can potentially have significant impacts on the uncertainty associated with results from subsequent analysis. This presentation will examine the concept of transmitted variation, its impact on designed experiments, and a method for identifying and estimating sources of transmitted variation in certain settings.

Influence of COMT Val158Met polymorphism on emotional decision-making: A sex-dependent relationship?

PubMed

Costa, Danielle de Souza; Bechara, Antoine; de Paula, Jonas Jardim; Romano-Silva, Marco Aurélio; Correa, Humberto; Lage, Guilherme Menezes; Miranda, Débora Marques de; Malloy-Diniz, Leandro Fernandes

2016-12-30

The biological underpinnings of sex-related differences in decision-making are still under-explored. The COMT gene is related to sexual dimorphism and with different choices made under uncertainty, albeit no study has specifically investigated a moderation effect of sex on the association between the COMT gene and the performance on decision-making paradigms. In this study, we investigated the influence of the COMT Val 158 Met polymorphism on Iowa Gambling Task (IGT) performance depending on sex in a healthy adult sample. Participants were 192 healthy adults (84 men and 108 women). The first 40 choices in the IGT were considered decisions under ambiguity and the last 60 choices decisions under risk. To test our moderation hypothesis we used a separate regressions approach. The results revealed a sex-dependent effect of COMT Va l 158 Met polymorphism on decision-making as measured by the IGT. Val/Val women showed the best performance in the last trials of the IGT. Therefore, the COMT Val 158 Met polymorphism may be considered a genetic marker underlying sex differences in decision-making. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Heuristic and optimal policy computations in the human brain during sequential decision-making.

PubMed

Korn, Christoph W; Bach, Dominik R

2018-01-23

Optimal decisions across extended time horizons require value calculations over multiple probabilistic future states. Humans may circumvent such complex computations by resorting to easy-to-compute heuristics that approximate optimal solutions. To probe the potential interplay between heuristic and optimal computations, we develop a novel sequential decision-making task, framed as virtual foraging in which participants have to avoid virtual starvation. Rewards depend only on final outcomes over five-trial blocks, necessitating planning over five sequential decisions and probabilistic outcomes. Here, we report model comparisons demonstrating that participants primarily rely on the best available heuristic but also use the normatively optimal policy. FMRI signals in medial prefrontal cortex (MPFC) relate to heuristic and optimal policies and associated choice uncertainties. Crucially, reaction times and dorsal MPFC activity scale with discrepancies between heuristic and optimal policies. Thus, sequential decision-making in humans may emerge from integration between heuristic and optimal policies, implemented by controllers in MPFC.

A Benefit-Risk Analysis Approach to Capture Regulatory Decision-Making: Multiple Myeloma.

PubMed

Raju, G K; Gurumurthi, Karthik; Domike, Reuben; Kazandjian, Dickran; Landgren, Ola; Blumenthal, Gideon M; Farrell, Ann; Pazdur, Richard; Woodcock, Janet

2018-01-01

Drug regulators around the world make decisions about drug approvability based on qualitative benefit-risk analysis. In this work, a quantitative benefit-risk analysis approach captures regulatory decision-making about new drugs to treat multiple myeloma (MM). MM assessments have been based on endpoints such as time to progression (TTP), progression-free survival (PFS), and objective response rate (ORR) which are different than benefit-risk analysis based on overall survival (OS). Twenty-three FDA decisions on MM drugs submitted to FDA between 2003 and 2016 were identified and analyzed. The benefits and risks were quantified relative to comparators (typically the control arm of the clinical trial) to estimate whether the median benefit-risk was positive or negative. A sensitivity analysis was demonstrated using ixazomib to explore the magnitude of uncertainty. FDA approval decision outcomes were consistent and logical using this benefit-risk framework. © 2017 American Society for Clinical Pharmacology and Therapeutics.

Public and stakeholder participation for managing and reducing the risks of shale gas development.

PubMed

North, D Warner; Stern, Paul C; Webler, Thomas; Field, Patrick

2014-01-01

Emerging technologies pose particularly strong challenges for risk governance when they have multidimensional and inequitable impacts, when there is scientific uncertainty about the technology and its risks, when there are strong value conflicts over the perceived benefits and risks, when decisions must be made urgently, and when the decision making environment is rife with mistrust. Shale gas development is one such emerging technology. Drawing on previous U.S. National Research Council committee reports that examined risk decision making for complex issues like these, we point to the benefits and challenges of applying the analytic-deliberative process recommended in those reports for stakeholder and public engagement in risk decision making about shale gas development in the United States. We discuss the different phases of such a process and conclude by noting the dangers of allowing controversy to ossify and the benefits of sound dialogue and learning among publics, stakeholders, industry, and regulatory decision makers.

Putting the value into biosimilar decision making: the judgment value criteria.

PubMed

Mendes de Abreu, Mirhelen; Strand, Vibeke; Levy, Roger Abramino; Araujo, Denizar Vianna

2014-06-01

Uncertainties remain the key issue surrounding biosimilars, although decisions regarding their use must be made. The challenges for policymakers, doctors, patients and others seeking to navigate in the uncharted waters of biosimilars must be clarified. At the most basic level, scientific understanding of the issue remains limited and when making decisions, policymakers must consider all those affected by health policy decisions, particularly the ultimate recipients of these medicines: the patients. The biosimilar-value chain relies on measurement of comparabilities. The goal is to demonstrate how, from a molecular perspective, closely similar they are or are not and how potential small differences may be relevant to clinical outcomes. To critically understand these points, this conceptual paper will present a knowledge-value chain and discuss each dimension assigning value in the decision making process re-utilization of biosimilars. Copyright © 2014 Elsevier B.V. All rights reserved.

Chronic atomoxetine treatment during adolescence does not influence decision-making on a rodent gambling task, but does modulate amphetamine's effect on impulsive action in adulthood.

PubMed

Silveira, Mason M; Murch, W Spencer; Clark, Luke; Winstanley, Catharine A

2016-06-01

In addition to the symptoms of inattention, hyperactivity, and impulsivity, individuals with attention deficit hyperactivity disorder exhibit impaired performance on tests of real-world cost/benefit decision-making. Atomoxetine, a nonstimulant drug approved for the treatment of attention deficit hyperactivity disorder, is a selective norepinephrine reuptake inhibitor administered chronically during adolescence, a time during which the frontal brain regions necessary for executive function undergo extensive maturation. This treatment protocol can affect behavior well into adulthood, but whether it produces long-term changes in complex decision-making has not been investigated. Twenty-four Long-Evans rats were administered saline or 1.0 mg/kg atomoxetine daily from postnatal day 40 to 54. Two weeks after treatment, the adult rats were trained and assessed on the rodent gambling task, in which the animals chose from four options varying in reward, punishment, and uncertainty. Impulsive action was also measured by recording the number of premature responses made. Regardless of the treatment administered during adolescence, rats learned to favor the advantageous options characterized by small, low-penalty rewards in lieu of the larger, higher-penalty reward options. Rodent gambling task performance was then assessed following acute treatment with atomoxetine (0.1-1.0 mg/kg) and amphetamine (0.3-1.5 mg/kg). Across groups, the highest dose of atomoxetine impaired decision-making and decreased premature responding at all doses tested. Amphetamine also impaired choice performance, but selectively increased impulsive action in rats that had previously received atomoxetine treatment during adolescence. These findings contribute to our understanding of the long-term effects associated with chronic adolescent atomoxetine exposure and suggest that this treatment does not alter decision-making under conditions of risk and uncertainty in adulthood.

Neural functional architecture and modulation during decision making under uncertainty in individuals with generalized anxiety disorder.

PubMed

Assaf, Michal; Rabany, Liron; Zertuche, Luis; Bragdon, Laura; Tolin, David; Goethe, John; Diefenbach, Gretchen

2018-06-21

Recent evidence suggests that repetitive transcranial magnetic stimulation (rTMS) might be effective in treating generalized anxiety disorder (GAD). Cognitive models of GAD highlight the role of intolerance of uncertainty (IU) in precipitating and maintaining worry, and it has been hypothesized that patients with GAD exhibit decision-making deficits under uncertain conditions. Improving understanding of the neural mechanisms underlying cognitive deficits associated with IU may lead to the identification of novel rTMS treatment targets and optimization of treatment parameters. The current report describes two interrelated studies designed to identify and verify a potential neural target for rTMS treatment of GAD. Study I explored the integrity of prefrontal cortex (PFC) and amygdala neural networks, which underlie decision making under conditions of uncertainty, in GAD. Individuals diagnosed with GAD (n = 31) and healthy controls (n = 20) completed a functional magnetic resonance imaging (fMRI) gambling task that manipulated uncertainty using high versus low error rates. In a subsequent randomized-controlled trial (Study II), a subset of the GAD sample (n = 16) completed the fMRI gambling task again after 30 sessions of active versus sham rTMS (1 Hz, right dorsolateral prefrontal cortex) to investigate the modulation of functional networks and symptoms. In Study I, participants with GAD demonstrated impairments in PFC-PFC and PFC-amygdala functional connectivity (FC) mostly during the high uncertainty condition. In Study II, one region of interest pair, dorsal anterior cingulate (ACC) - subgenual ACC, showed "normalization" of FC following active, but not sham, rTMS, and neural changes were associated with improvement in worry symptoms. These results outline a possible treatment mechanism of rTMS in GAD, and pave the way for future studies of treatment optimization. © 2018 The Authors. Brain and Behavior published by Wiley Periodicals, Inc.

Incentivizing monitoring and compliance in trophy hunting.

PubMed

Bunnefeld, Nils; Edwards, Charles T T; Atickem, Anagaw; Hailu, Fetene; Milner-Gulland, E J

2013-12-01

Conservation scientists are increasingly focusing on the drivers of human behavior and on the implications of various sources of uncertainty for management decision making. Trophy hunting has been suggested as a conservation tool because it gives economic value to wildlife, but recent examples show that overharvesting is a substantial problem and that data limitations are rife. We use a case study of trophy hunting of an endangered antelope, the mountain nyala (Tragelaphus buxtoni), to explore how uncertainties generated by population monitoring and poaching interact with decision making by 2 key stakeholders: the safari companies and the government. We built a management strategy evaluation model that encompasses the population dynamics of mountain nyala, a monitoring model, and a company decision making model. We investigated scenarios of investment into antipoaching and monitoring by governments and safari companies. Harvest strategy was robust to the uncertainty in the population estimates obtained from monitoring, but poaching had a much stronger effect on quota and sustainability. Hence, reducing poaching is in the interests of companies wishing to increase the profitability of their enterprises, for example by engaging community members as game scouts. There is a threshold level of uncertainty in the population estimates beyond which the year-to-year variation in the trophy quota prevented planning by the safari companies. This suggests a role for government in ensuring that a baseline level of population monitoring is carried out such that this level is not exceeded. Our results illustrate the importance of considering the incentives of multiple stakeholders when designing frameworks for resource use and when designing management frameworks to address the particular sources of uncertainty that affect system sustainability most heavily. Incentivando el Monitoreo y el Cumplimiento en la Caza de Trofeos. © 2013 The Authors. Conservation Biology published by Wiley Periodicals, Inc., on behalf of the Society for Conservation Biology.

Emotion regulation and decision making under risk and uncertainty.

PubMed

Heilman, Renata M; Crişan, Liviu G; Houser, Daniel; Miclea, Mircea; Miu, Andrei C

2010-04-01

It is well established that emotion plays a key role in human social and economic decision making. The recent literature on emotion regulation (ER), however, highlights that humans typically make efforts to control emotion experiences. This leaves open the possibility that decision effects previously attributed to acute emotion may be a consequence of acute ER strategies such as cognitive reappraisal and expressive suppression. In Study 1, we manipulated ER of laboratory-induced fear and disgust, and found that the cognitive reappraisal of these negative emotions promotes risky decisions (reduces risk aversion) in the Balloon Analogue Risk Task and is associated with increased performance in the prehunch/hunch period of the Iowa Gambling Task. In Study 2, we found that naturally occurring negative emotions also increase risk aversion in Balloon Analogue Risk Task, but the incidental use of cognitive reappraisal of emotions impedes this effect. We offer evidence that the increased effectiveness of cognitive reappraisal in reducing the experience of emotions underlies its beneficial effects on decision making. Copyright 2010 APA, all rights reserved.

Adaptive sampling of information in perceptual decision-making.

PubMed

Cassey, Thomas C; Evens, David R; Bogacz, Rafal; Marshall, James A R; Ludwig, Casimir J H

2013-01-01

In many perceptual and cognitive decision-making problems, humans sample multiple noisy information sources serially, and integrate the sampled information to make an overall decision. We derive the optimal decision procedure for two-alternative choice tasks in which the different options are sampled one at a time, sources vary in the quality of the information they provide, and the available time is fixed. To maximize accuracy, the optimal observer allocates time to sampling different information sources in proportion to their noise levels. We tested human observers in a corresponding perceptual decision-making task. Observers compared the direction of two random dot motion patterns that were triggered only when fixated. Observers allocated more time to the noisier pattern, in a manner that correlated with their sensory uncertainty about the direction of the patterns. There were several differences between the optimal observer predictions and human behaviour. These differences point to a number of other factors, beyond the quality of the currently available sources of information, that influences the sampling strategy.

Learning from the Past, Looking to the Future: Modeling Social Unrest in Karachi, Pakistan

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

Olson, Jarrod; Kurzrok, Andrew J.; Hund, Gretchen

Social unrest represents a major challenge for policy makers around the globe, as it can quickly escalate from small scale disturbances to highly public protests, riots and even civil war. This research was motivated by a need to understand social instability and to unpack the comments made during a spring 2013 conference hosted by Pacific Northwest National Laboratory’s Center for Global Security and the U.S. Institute for Peace, where policymakers noted that models considering social instability are often not suitable for decision-making. This analysis shows that existing state level models of instability could be improved in spatial scale to themore » city level, even without significantly improved data access. Better data would make this analysis more complete and likely improve the quality of the model. Another challenge with incorporating modeling into decision-making is the need to understand uncertainty in a model. Policy makers are frequently tasked with making decisions without a clear outcome, so characterization of uncertainty is critical. This report describes the work and findings of the project. It took place in three phases: a literature review of social stability research, a “hindsight scan” that looked at historical data, and a “foresight scan” looking at future scenarios.« less

Scenario Planning: A Phenomenological Examination of Influence on Organizational Learning and Decision-Making in a K-12 Public Education System

ERIC Educational Resources Information Center

Deklotz, Patricia F.

2013-01-01

Organizations commonly engage in long range planning to direct decisions. Scenario planning, one method of private sector planning, is recognized as useful when organizations are facing uncertainty. Scenario planning engages the organization in a process that produces plausible stories, called scenarios, describing the organization in several…

The economic value of drought information: Application to water resources management decisions in Spain

NASA Astrophysics Data System (ADS)

Garrote, Luis; Sordo, Alvaro; Iglesias, Ana

2016-04-01

Information is valuable when it improves decision-making (e.g., actions can be adjusted to better suit the situation at hand) and enables the mitigation of damage. However, quantifying the value of information is often difficult. Here we explore a general approach to understand the economic value of drought information for water managers framing our approach in the precautionary principle that reminds us that uncertainty is not a reason to postpone or avoid action. We explore how decision making can disregard uncertain effects, taking a short-term approach and focusing instead on the certain costs and benefits of taking action. Two main questions arise: How do we know that advanced drought information is actually helping decisions?; and What is the value of information in the decision process? The approach is applied to several regulated water resources systems in Spain. It first views drought information as a factor in the decision process which can be used by water managers to reduce uncertainty. Second, the value of drought information is the expected gain in a decision outcome (utility) from using additional information. Finally, the gains of improved information are compared with the information collection costs. Here we estimate the value by taking into account the accuracy of the drought information, the subjective probabilities about the value, analyzed as Bayesian probabilities, and the ability or skill of the stakeholders to apply the drought information to modify their actions. Since information may be considered a public good (non-rivalry and non-excludability), it may justify public policy in the provision of information, considering social costs and benefits. The application of the framework to the Spanish case studies shows that information benefits exceeds to costs when drought frequency is 20-40% above normal values; below these values uncertainty in the decisions dominate the results; above these values, the management decisions are limited even with perfect information.

The Application of Climate Risk Informed Decision Analysis to the Ioland Water Treatment Plant in Lusaka, Zambia

NASA Astrophysics Data System (ADS)

Kucharski, John; Tkach, Mark; Olszewski, Jennifer; Chaudhry, Rabia; Mendoza, Guillermo

2016-04-01

This presentation demonstrates the application of Climate Risk Informed Decision Analysis (CRIDA) at Zambia's principal water treatment facility, The Iolanda Water Treatment Plant. The water treatment plant is prone to unacceptable failures during periods of low hydropower production at the Kafue Gorge Dam Hydroelectric Power Plant. The case study explores approaches of increasing the water treatment plant's ability to deliver acceptable levels of service under the range of current and potential future climate states. The objective of the study is to investigate alternative investments to build system resilience that might have been informed by the CRIDA process, and to evaluate the extra resource requirements by a bilateral donor agency to implement the CRIDA process. The case study begins with an assessment of the water treatment plant's vulnerability to climate change. It does so by following general principals described in "Confronting Climate Uncertainty in Water Resource Planning and Project Design: the Decision Tree Framework". By utilizing relatively simple bootstrapping methods a range of possible future climate states is generated while avoiding the use of more complex and costly downscaling methodologies; that are beyond the budget and technical capacity of many teams. The resulting climate vulnerabilities and uncertainty in the climate states that produce them are analyzed as part of a "Level of Concern" analysis. CRIDA principals are then applied to this Level of Concern analysis in order to arrive at a set of actionable water management decisions. The principal goals of water resource management is to transform variable, uncertain hydrology into dependable services (e.g. water supply, flood risk reduction, ecosystem benefits, hydropower production, etc…). Traditional approaches to climate adaptation require the generation of predicted future climate states but do little guide decision makers how this information should impact decision making. In this context it is not surprising that the increased hydrologic variability and uncertainty produced by many climate risk analyses bedevil water resource decision making. The Climate Risk Informed Decision Analysis (CRIDA) approach builds on work found in "Confronting Climate Uncertainty in Water Resource Planning and Project Design: the Decision Tree Framework" which provide guidance of vulnerability assessments. It guides practitioners through a "Level of Concern" analysis where climate vulnerabilities are analyzed to produce actionable alternatives and decisions.

Assessing the environmental impacts of aircraft noise and emissions

NASA Astrophysics Data System (ADS)

Mahashabde, Anuja; Wolfe, Philip; Ashok, Akshay; Dorbian, Christopher; He, Qinxian; Fan, Alice; Lukachko, Stephen; Mozdzanowska, Aleksandra; Wollersheim, Christoph; Barrett, Steven R. H.; Locke, Maryalice; Waitz, Ian A.

2011-01-01

With the projected growth in demand for commercial aviation, many anticipate increased environmental impacts associated with noise, air quality, and climate change. Therefore, decision-makers and stakeholders are seeking policies, technologies, and operational procedures that balance environmental and economic interests. The main objective of this paper is to address shortcomings in current decision-making practices for aviation environmental policies. We review knowledge of the noise, air quality, and climate impacts of aviation, and demonstrate how including environmental impact assessment and quantifying uncertainties can enable a more comprehensive evaluation of aviation environmental policies. A comparison is presented between the cost-effectiveness analysis currently used for aviation environmental policy decision-making and an illustrative cost-benefit analysis. We focus on assessing a subset of the engine NO X emissions certification stringency options considered at the eighth meeting of the International Civil Aviation Organization’s Committee on Aviation Environmental Protection. The FAA Aviation environmental Portfolio Management Tool (APMT) is employed to conduct the policy assessments. We show that different conclusions may be drawn about the same policy options depending on whether benefits and interdependencies are estimated in terms of health and welfare impacts versus changes in NO X emissions inventories as is the typical practice. We also show that these conclusions are sensitive to a variety of modeling uncertainties. While our more comprehensive analysis makes the best policy option less clear, it represents a more accurate characterization of the scientific and economic uncertainties underlying impacts and the policy choices.

Emotion, decision-making and the brain.

PubMed

Chang, Luke J; Sanfey, Alan G

2008-01-01

Initial explorations in the burgeoning field of neuroeconomics have highlighted evidence supporting a potential dissociation between a fast automatic system and a slow deliberative controlled system. Growing research in the role of emotion in decision-making has attempted to draw parallels to the automatic system. This chapter will discuss a theoretical framework for understanding the role of emotion in decision-making and evidence supporting the underlying neural substrates. This chapter applies a conceptual framework to understanding the role of emotion in decision-making, and emphasizes a distinction between expected and immediate emotions. Expected emotions refer to anticipated emotional states associated with a given decision that are never actually experienced. Immediate emotions, however, are experienced at the time of decision, and either can occur in response to a particular decision or merely as a result of a transitory fluctuation. This chapter will review research from the neuroeconomics literature that supports a neural dissociation between these two classes of emotion and also discuss a few interpretive caveats. Several lines of research including regret, uncertainty, social decision-making, and moral decision-making have yielded evidence consistent with our formulization--expected and immediate emotions may invoke dissociable neural systems. This chapter provides a more specific conceptualization of the mediating role of emotions in the decision-making process, which has important implications for understanding the interacting neural systems underlying the interface between emotion and cognition--a topic of immediate value to anyone investigating topics within the context of social-cognitive-affective-neuroscience.

Informed decision-making in elective major vascular surgery: analysis of 145 surgeon-patient consultations.

PubMed

Etchells, Edward; Ferrari, Michel; Kiss, Alex; Martyn, Nikki; Zinman, Deborah; Levinson, Wendy

2011-06-01

Prior studies show significant gaps in the informed decision-making process, a central goal of surgical care. These studies have been limited by their focus on low-risk decisions, single visits rather than entire consultations, or both. Our objectives were, first, to rate informed decision-making for major elective vascular surgery based on audiotapes of actual physician-patient conversations and, second, to compare ratings of informed decision-making for first visits to ratings for multiple visits by the same patient over time. We prospectively enrolled patients for whom vascular surgical treatment was a potential option at a tertiary care outpatient vascular surgery clinic. We audio-taped all surgeon-patient conversations, including multiple visits when necessary, until a decision was made. Using an existing method, we evaluated the transcripts for elements of decision-making, including basic elements (e.g., an explanation of the clinical condition), intermediate elements (e.g., risks and benefits) and complex elements (e.g., uncertainty around the decision). We analyzed 145 surgeon-patient consultations. Overall, 45% of consultations contained complex elements, whereas 23% did not contain the basic elements of decision-making. For the 67 consultations that involved multiple visits, ratings were significantly higher when evaluating all visits (50% complex elements) compared with evaluating only the first visit (33% complex elements, p < 0.001.) We found that 45% of consultations contained complex elements, which is higher than prior studies with similar methods. Analyzing decision-making over multiple visits yielded different results than analyzing decision-making for single visits.

Prospect theory on the brain? Toward a cognitive neuroscience of decision under risk.

PubMed

Trepel, Christopher; Fox, Craig R; Poldrack, Russell A

2005-04-01

Most decisions must be made without advance knowledge of their consequences. Economists and psychologists have devoted much attention to modeling decisions made under conditions of risk in which options can be characterized by a known probability distribution over possible outcomes. The descriptive shortcomings of classical economic models motivated the development of prospect theory (D. Kahneman, A. Tversky, Prospect theory: An analysis of decision under risk. Econometrica, 4 (1979) 263-291; A. Tversky, D. Kahneman, Advances in prospect theory: Cumulative representation of uncertainty. Journal of Risk and Uncertainty, 5 (4) (1992) 297-323) the most successful behavioral model of decision under risk. In the prospect theory, subjective value is modeled by a value function that is concave for gains, convex for losses, and steeper for losses than for gains; the impact of probabilities are characterized by a weighting function that overweights low probabilities and underweights moderate to high probabilities. We outline the possible neural bases of the components of prospect theory, surveying evidence from human imaging, lesion, and neuropharmacology studies as well as animal neurophysiology studies. These results provide preliminary suggestions concerning the neural bases of prospect theory that include a broad set of brain regions and neuromodulatory systems. These data suggest that focused studies of decision making in the context of quantitative models may provide substantial leverage towards a fuller understanding of the cognitive neuroscience of decision making.

Many-Objective Robust Decision Making: Managing Water in a Deeply Uncertain World of Change (Invited)

NASA Astrophysics Data System (ADS)

Reed, P. M.

2013-12-01

Water resources planning and management has always required the consideration of uncertainties and the associated system vulnerabilities that they may cause. Despite the long legacy of these issues, our decision support frameworks that have dominated the literature over the past 50 years have struggled with the strongly multiobjective and deeply uncertain nature of water resources systems. The term deep uncertainty (or Knightian uncertainty) refers to factors in planning that strongly shape system risks that maybe unknown and even if known there is a strong lack of consensus on their likelihoods over decadal planning horizons (population growth, financial stability, valuation of resources, ecosystem requirements, evolving water institutions, regulations, etc). In this presentation, I will propose and demonstrate the many-objective robust decision making (MORDM) framework for water resources management under deep uncertainty. The MORDM framework will be demonstrated using an urban water portfolio management test case. In the test case, a city in the Lower Rio Grande Valley managing population and drought pressures must cost effectively maintain the reliability of its water supply by blending permanent rights to reservoir inflows with alternative strategies for purchasing water within the region's water market. The case study illustrates the significant potential pitfalls in the classic Cost-Reliability conception of the problem. Moreover, the proposed MORDM framework exploits recent advances in multiobjective search, visualization, and sensitivity analysis to better expose these pitfalls en route to identifying highly robust water planning alternatives.

The Role of Time-Limited Trials in Dialysis Decision Making in Critically Ill Patients.

PubMed

Scherer, Jennifer S; Holley, Jean L

2016-02-05

Technologic advances, such as continuous RRT, provide lifesaving therapy for many patients. AKI in the critically ill patient, a fatal diagnosis in the past, is now often a survivable condition. Dialysis decision making for the critically ill patient with AKI is complex. What was once a question solely of survival now is nuanced by an individual's definition of quality of life, personal values, and short- and long-term prognoses. Clinical evaluation of AKI in the critically ill is multifaceted. Treatment decision making requires consideration of the natural evolution of the patient's AKI within the context of the global prognosis. Situations are often marked by prognostic uncertainty and clinical unknowns. In the face of these uncertainties, establishment of patient-directed therapies is imperative. A time-limited trial of continuous RRT in this setting is often appropriate but difficult to execute. Using patient preferences as a clinical guide, a proper time-limited trial requires assessment of prognosis, elicitation of patient values, strong communication skills, clear documentation, and often, appropriate integration of palliative care services. A well conducted time-limited trial can avoid interprofessional conflict and provide support for the patient, family, and staff. Copyright © 2016 by the American Society of Nephrology.

From axiomatics of quantum probability to modelling geological uncertainty and management of intelligent hydrocarbon reservoirs with the theory of open quantum systems.

PubMed

Lozada Aguilar, Miguel Ángel; Khrennikov, Andrei; Oleschko, Klaudia

2018-04-28

As was recently shown by the authors, quantum probability theory can be used for the modelling of the process of decision-making (e.g. probabilistic risk analysis) for macroscopic geophysical structures such as hydrocarbon reservoirs. This approach can be considered as a geophysical realization of Hilbert's programme on axiomatization of statistical models in physics (the famous sixth Hilbert problem). In this conceptual paper , we continue development of this approach to decision-making under uncertainty which is generated by complexity, variability, heterogeneity, anisotropy, as well as the restrictions to accessibility of subsurface structures. The belief state of a geological expert about the potential of exploring a hydrocarbon reservoir is continuously updated by outputs of measurements, and selection of mathematical models and scales of numerical simulation. These outputs can be treated as signals from the information environment E The dynamics of the belief state can be modelled with the aid of the theory of open quantum systems: a quantum state (representing uncertainty in beliefs) is dynamically modified through coupling with E ; stabilization to a steady state determines a decision strategy. In this paper, the process of decision-making about hydrocarbon reservoirs (e.g. 'explore or not?'; 'open new well or not?'; 'contaminated by water or not?'; 'double or triple porosity medium?') is modelled by using the Gorini-Kossakowski-Sudarshan-Lindblad equation. In our model, this equation describes the evolution of experts' predictions about a geophysical structure. We proceed with the information approach to quantum theory and the subjective interpretation of quantum probabilities (due to quantum Bayesianism).This article is part of the theme issue 'Hilbert's sixth problem'. © 2018 The Author(s).

From axiomatics of quantum probability to modelling geological uncertainty and management of intelligent hydrocarbon reservoirs with the theory of open quantum systems

NASA Astrophysics Data System (ADS)

Lozada Aguilar, Miguel Ángel; Khrennikov, Andrei; Oleschko, Klaudia

2018-04-01

As was recently shown by the authors, quantum probability theory can be used for the modelling of the process of decision-making (e.g. probabilistic risk analysis) for macroscopic geophysical structures such as hydrocarbon reservoirs. This approach can be considered as a geophysical realization of Hilbert's programme on axiomatization of statistical models in physics (the famous sixth Hilbert problem). In this conceptual paper, we continue development of this approach to decision-making under uncertainty which is generated by complexity, variability, heterogeneity, anisotropy, as well as the restrictions to accessibility of subsurface structures. The belief state of a geological expert about the potential of exploring a hydrocarbon reservoir is continuously updated by outputs of measurements, and selection of mathematical models and scales of numerical simulation. These outputs can be treated as signals from the information environment E. The dynamics of the belief state can be modelled with the aid of the theory of open quantum systems: a quantum state (representing uncertainty in beliefs) is dynamically modified through coupling with E; stabilization to a steady state determines a decision strategy. In this paper, the process of decision-making about hydrocarbon reservoirs (e.g. `explore or not?'; `open new well or not?'; `contaminated by water or not?'; `double or triple porosity medium?') is modelled by using the Gorini-Kossakowski-Sudarshan-Lindblad equation. In our model, this equation describes the evolution of experts' predictions about a geophysical structure. We proceed with the information approach to quantum theory and the subjective interpretation of quantum probabilities (due to quantum Bayesianism). This article is part of the theme issue `Hilbert's sixth problem'.

Determining rules for closing customer service centers: A public utility company's fuzzy decision

NASA Technical Reports Server (NTRS)

Dekorvin, Andre; Shipley, Margaret F.

1992-01-01

In the present work, we consider the general problem of knowledge acquisition under uncertainty. A commonly used method is to learn by examples. We observe how the expert solves specific cases and from this infer some rules by which the decision was made. Unique to this work is the fuzzy set representation of the conditions or attributes upon which the decision make may base his fuzzy set decision. From our examples, we infer certain and possible rules containing fuzzy terms. It should be stressed that the procedure determines how closely the expert follows the conditions under consideration in making his decision. We offer two examples pertaining to the possible decision to close a customer service center of a public utility company. In the first example, the decision maker does not follow too closely the conditions. In the second example, the conditions are much more relevant to the decision of the expert.

Recent Patterns in Shared Decision Making for Prostate-Specific Antigen Testing in the United States.

PubMed

Fedewa, Stacey A; Gansler, Ted; Smith, Robert; Sauer, Ann Goding; Wender, Richard; Brawley, Otis W; Jemal, Ahmedin

2018-03-01

Previous studies report infrequent use of shared decision making for prostate-specific antigen (PSA) testing. It is unknown whether this pattern has changed recently considering increased emphasis on shared decision making in prostate cancer screening recommendations. Thus, the objective of this study is to examine recent changes in shared decision making. We conducted a retrospective cross-sectional study among men aged 50 years and older in the United States using 2010 and 2015 National Health Interview Survey (NHIS) data (n = 9,598). Changes in receipt of shared decision making were expressed as adjusted prevalence ratios (aPR) and 95% confidence intervals (CI). Analyses were stratified on PSA testing (recent [in the past year] or no testing). Elements of shared decision making assessed included the patient being informed about the advantages only, advantages and disadvantages, and full shared decision making (advantages, disadvantages, and uncertainties). Among men with recent PSA testing, 58.5% and 62.6% reported having received ≥1 element of shared decision making in 2010 and 2015, respectively ( P = .054, aPR = 1.04; 95% CI, 0.98-1.11). Between 2010 and 2015, being told only about the advantages of PSA testing significantly declined (aPR = 0.82; 95% CI, 0.71-0.96) and full shared decision making prevalence significantly increased (aPR = 1.51; 95% CI, 1.28-1.79) in recently tested men. Among men without prior PSA testing, 10% reported ≥1 element of shared decision making, which did not change with time. Between 2010 and 2015, there was no increase in shared decision making among men with recent PSA testing though there was a shift away from only being told about the advantages of PSA testing towards full shared decision making. Many men receiving PSA testing did not receive shared decision making. © 2018 Annals of Family Medicine, Inc.

Perceptual uncertainty and line-call challenges in professional tennis

PubMed Central

Mather, George

2008-01-01

Fast-moving sports such as tennis require both players and match officials to make rapid accurate perceptual decisions about dynamic events in the visual world. Disagreements arise regularly, leading to disputes about decisions such as line calls. A number of factors must contribute to these disputes, including lapses in concentration, bias and gamesmanship. Fundamental uncertainty or variability in the sensory information supporting decisions must also play a role. Modern technological innovations now provide detailed and accurate physical information that can be compared against the decisions of players and officials. The present paper uses this psychophysical data to assess the significance of perceptual limitations as a contributor to real-world decisions in professional tennis. A detailed analysis is presented of a large body of data on line-call challenges in professional tennis tournaments over the last 2 years. Results reveal that the vast majority of challenges can be explained in a direct highly predictable manner by a simple model of uncertainty in perceptual information processing. Both players and line judges are remarkably accurate at judging ball bounce position, with a positional uncertainty of less than 40 mm. Line judges are more reliable than players. Judgements are more difficult for balls bouncing near base and service lines than those bouncing near side and centre lines. There is no evidence for significant errors in localization due to image motion. PMID:18426755

Perceptual uncertainty and line-call challenges in professional tennis.

PubMed

Mather, George

2008-07-22

Fast-moving sports such as tennis require both players and match officials to make rapid accurate perceptual decisions about dynamic events in the visual world. Disagreements arise regularly, leading to disputes about decisions such as line calls. A number of factors must contribute to these disputes, including lapses in concentration, bias and gamesmanship. Fundamental uncertainty or variability in the sensory information supporting decisions must also play a role. Modern technological innovations now provide detailed and accurate physical information that can be compared against the decisions of players and officials. The present paper uses this psychophysical data to assess the significance of perceptual limitations as a contributor to real-world decisions in professional tennis. A detailed analysis is presented of a large body of data on line-call challenges in professional tennis tournaments over the last 2 years. Results reveal that the vast majority of challenges can be explained in a direct highly predictable manner by a simple model of uncertainty in perceptual information processing. Both players and line judges are remarkably accurate at judging ball bounce position, with a positional uncertainty of less than 40mm. Line judges are more reliable than players. Judgements are more difficult for balls bouncing near base and service lines than those bouncing near side and centre lines. There is no evidence for significant errors in localization due to image motion.

An Innovative Approach to Effective Climate Science Application through Stakeholder Participation in Great Plains Grasslands

NASA Astrophysics Data System (ADS)

Athearn, N.; Broska, J.

2015-12-01

For natural resource managers and other Great Plains stakeholders, climate uncertainties further confound decision-making on a highly altered landscape. Partner organizations comprising the Great Plains Landscape Conservation Cooperative (GPLCC) acknowledge climate change as a high-priority threat to grasslands and associated habitats, affecting water availability, species composition, and other factors. Despite its importance, incorporation of climate change impacts into planning is hindered by high uncertainty and lack of translation to a tangible outcome: effects on species and their habitats. In 2014, the GPLCC initiated a Landscape Conservation Design (LCD) process to ultimately improve the size and connectivity of grasslands - informing land managers of the landscape-scale impacts of local decisions about where to restore, enhance, protect, and develop lands. Defining this goal helped stakeholders envision a tangible product. High resolution land cover data recently completed for Texas and Oklahoma represent current grassland locations. By focusing climate change models to project changes in these land cover datasets, resulting land cover projections can be directly incorporated into LCD-based models to focus restoration where future climates will support grasslands. Broad organizational cooperation has been critical for this USGS-led project, which uses downscaled climate data and other support from the South Central Climate Science Center Consortium and builds on existing work including LCD efforts of the Playa Lakes Joint Venture and the Bureau of Land Management's Southern Great Plains Rapid Ecological Assessment. Ongoing stakeholder guidance through an advisory team ensures effective application of a product that will be both relevant to and understood by decision makers, for whom the primary role of research is to reduce uncertainties and clear the path for more efficient decision-making in the face of climatic uncertainty.

Uncertainty quantification in flood risk assessment

NASA Astrophysics Data System (ADS)

Blöschl, Günter; Hall, Julia; Kiss, Andrea; Parajka, Juraj; Perdigão, Rui A. P.; Rogger, Magdalena; Salinas, José Luis; Viglione, Alberto

2017-04-01

Uncertainty is inherent to flood risk assessments because of the complexity of the human-water system, which is characterised by nonlinearities and interdependencies, because of limited knowledge about system properties and because of cognitive biases in human perception and decision-making. On top of the uncertainty associated with the assessment of the existing risk to extreme events, additional uncertainty arises because of temporal changes in the system due to climate change, modifications of the environment, population growth and the associated increase in assets. Novel risk assessment concepts are needed that take into account all these sources of uncertainty. They should be based on the understanding of how flood extremes are generated and how they change over time. They should also account for the dynamics of risk perception of decision makers and population in the floodplains. In this talk we discuss these novel risk assessment concepts through examples from Flood Frequency Hydrology, Socio-Hydrology and Predictions Under Change. We believe that uncertainty quantification in flood risk assessment should lead to a robust approach of integrated flood risk management aiming at enhancing resilience rather than searching for optimal defense strategies.

Error Analysis of CM Data Products Sources of Uncertainty

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

Hunt, Brian D.; Eckert-Gallup, Aubrey Celia; Cochran, Lainy Dromgoole

This goal of this project is to address the current inability to assess the overall error and uncertainty of data products developed and distributed by DOE’s Consequence Management (CM) Program. This is a widely recognized shortfall, the resolution of which would provide a great deal of value and defensibility to the analysis results, data products, and the decision making process that follows this work. A global approach to this problem is necessary because multiple sources of error and uncertainty contribute to the ultimate production of CM data products. Therefore, this project will require collaboration with subject matter experts across amore » wide range of FRMAC skill sets in order to quantify the types of uncertainty that each area of the CM process might contain and to understand how variations in these uncertainty sources contribute to the aggregated uncertainty present in CM data products. The ultimate goal of this project is to quantify the confidence level of CM products to ensure that appropriate public and worker protections decisions are supported by defensible analysis.« less

Adaptive harvest management of North American waterfowl populations - recent successes and future prospects

USGS Publications Warehouse

Nichols, J.D.; Runge, M.C.; Johnson, F.A.; Williams, B.K.; Schodde, Richard; Hannon, Susan; Scheiffarth, Gregor; Bairlein, Franz

2006-01-01

The history of North American waterfowl harvest management has been characterized by attempts to use population monitoring data to make informed harvest management decisions. Early attempts can be characterized as intuitive decision processes, and later efforts were guided increasingly by population models and associated predictions. In 1995, a formal adaptive management process was implemented, and annual decisions about duck harvest regulations in the United States are still based on this process. This formal decision process is designed to deal appropriately with the various forms of uncertainty that characterize management decisions, environmental uncertainty, structural uncertainty, partial controllability and partial observability. The key components of the process are (1) objectives, (2) potential management actions, (3) model(s) of population response to management actions, (4) credibility measures for these models, and (5) a monitoring program. The operation of this iterative process is described, and a brief history of a decade of its use is presented. Future challenges range from social and political issues such as appropriate objectives and management actions, to technical issues such as multispecies management, geographic allocation of harvest, and incorporation of actions that include habitat acquisition and management.

Information needs, acceptability of risk, trust, and reliance: the case of national predictive services customers

Treesearch

Patricia L. Winter; Heidi Bigler-Cole

2010-01-01

Making complex risk-related decisions involves a degree of uncertainty. How that uncertainty is addressed or presented in reports or data tables can be tailored to meet information users’ needs and preferences. Involving the recipients of risk-related information in the design of information to be delivered (including the types of information delivered, format, and...

Information needs, acceptability of risk, trust, and reliance: The case of National Predictive Services customers

Treesearch

Patricia L. Winter; Heidi Bigler-Cole

2010-01-01

Making complex risk-related decisions involves a degree of uncertainty. How that uncertainty is addressed or presented in reports or data tables can be tailored to meet information users’ needs and preferences. Involving the recipients of risk-related information in the design of information to be delivered (including the types of information delivered, format, and...

Toward sensor-based context aware systems.

PubMed

Sakurai, Yoshitaka; Takada, Kouhei; Anisetti, Marco; Bellandi, Valerio; Ceravolo, Paolo; Damiani, Ernesto; Tsuruta, Setsuo

2012-01-01

This paper proposes a methodology for sensor data interpretation that can combine sensor outputs with contexts represented as sets of annotated business rules. Sensor readings are interpreted to generate events labeled with the appropriate type and level of uncertainty. Then, the appropriate context is selected. Reconciliation of different uncertainty types is achieved by a simple technique that moves uncertainty from events to business rules by generating combs of standard Boolean predicates. Finally, context rules are evaluated together with the events to take a decision. The feasibility of our idea is demonstrated via a case study where a context-reasoning engine has been connected to simulated heartbeat sensors using prerecorded experimental data. We use sensor outputs to identify the proper context of operation of a system and trigger decision-making based on context information.

Patients' Non-Medical Characteristics Contribute to Collective Medical Decision-Making at Multidisciplinary Oncological Team Meetings.

PubMed

Restivo, Léa; Apostolidis, Thémis; Bouhnik, Anne-Déborah; Garciaz, Sylvain; Aurran, Thérèse; Julian-Reynier, Claire

2016-01-01

The contribution of patients' non-medical characteristics to individual physicians' decision-making has attracted considerable attention, but little information is available on this topic in the context of collective decision-making. Medical decision-making at cancer centres is currently carried out using a collective approach, at MultiDisciplinary Team (MDT) meetings. The aim of this study was to determine how patients' non-medical characteristics are presented at MDT meetings and how this information may affect the team's final medical decisions. Observations were conducted at a French Cancer Centre during MDT meetings at which non-standard cases involving some uncertainty were discussed from March to May 2014. Physicians' verbal statements and predefined contextual parameters were collected with a non-participant observational approach. Non numerical data collected in the form of open notes were then coded for quantitative analysis. Univariate and multivariate statistical analyses were performed. In the final sample of patients' records included and discussed (N = 290), non-medical characteristics were mentioned in 32.8% (n = 95) of the cases. These characteristics corresponded to demographics in 22.8% (n = 66) of the cases, psychological data in 11.7% (n = 34), and relational data in 6.2% (n = 18). The patient's age and his/her "likeability" were the most frequently mentioned characteristics. In 17.9% of the cases discussed, the final decision was deferred: this outcome was positively associated with the patients' non-medical characteristics and with uncertainty about the outcome of the therapeutic options available. The design of the study made it difficult to draw definite cause-and-effect conclusions. The Social Representations approach suggests that patients' non-medical characteristics constitute a kind of tacit professional knowledge that may be frequently mobilised in physicians' everyday professional practice. The links observed between patients' attributes and the medical decisions made at these meetings show that these attributes should be taken into account in order to understand how medical decisions are reached in difficult situations of this kind.