Examining Data-Driven Decision Making in Private/Religious Schools

ERIC Educational Resources Information Center

Hanks, Jason Edward

2011-01-01

The purpose of this study was to investigate non-mandated data-driven decision making in private/religious schools. The school culture support of data use, teacher use of data, leader facilitation of using data, and the availability of data were investigated in three schools. A quantitative survey research design was used to explore the research…

Decision Making Under Objective Risk Conditions-a Review of Cognitive and Emotional Correlates, Strategies, Feedback Processing, and External Influences.

PubMed

Schiebener, Johannes; Brand, Matthias

2015-06-01

While making decisions under objective risk conditions, the probabilities of the consequences of the available options are either provided or calculable. Brand et al. (Neural Networks 19:1266-1276, 2006) introduced a model describing the neuro-cognitive processes involved in such decisions. In this model, executive functions associated with activity in the fronto-striatal loop are important for developing and applying decision-making strategies, and for verifying, adapting, or revising strategies according to feedback. Emotional rewards and punishments learned from such feedback accompany these processes. In this literature review, we found support for the role of executive functions, but also found evidence for the importance of further cognitive abilities in decision making. Moreover, in addition to reflective processing (driven by cognition), decisions can be guided by impulsive processing (driven by anticipation of emotional reward and punishment). Reflective and impulsive processing may interact during decision making, affecting the evaluation of available options, as both processes are affected by feedback. Decision-making processes are furthermore modulated by individual attributes (e.g., age), and external influences (e.g., stressors). Accordingly, we suggest a revised model of decision making under objective risk conditions.

The Myth of the Rational Decision Maker: A Framework for Applying and Enhancing Heuristic and Intuitive Decision Making by School Leaders

ERIC Educational Resources Information Center

Davis, Stephen H.

2004-01-01

This article takes a critical look at administrative decision making in schools and the extent to which complex decisions conform to normative models and common expectations of rationality. An alternative framework for administrative decision making is presented that is informed, but not driven, by theories of rationality. The framework assumes…

ENABLING SMART MANUFACTURING TECHNOLOGIES FOR DECISION-MAKING SUPPORT

PubMed Central

Helu, Moneer; Libes, Don; Lubell, Joshua; Lyons, Kevin; Morris, KC

2017-01-01

Smart manufacturing combines advanced manufacturing capabilities and digital technologies throughout the product lifecycle. These technologies can provide decision-making support to manufacturers through improved monitoring, analysis, modeling, and simulation that generate more and better intelligence about manufacturing systems. However, challenges and barriers have impeded the adoption of smart manufacturing technologies. To begin to address this need, this paper defines requirements for data-driven decision making in manufacturing based on a generalized description of decision making. Using these requirements, we then focus on identifying key barriers that prevent the development and use of data-driven decision making in industry as well as examples of technologies and standards that have the potential to overcome these barriers. The goal of this research is to promote a common understanding among the manufacturing community that can enable standardization efforts and innovation needed to continue adoption and use of smart manufacturing technologies. PMID:28649678

Examining Data Driven Decision Making via Formative Assessment: A Confluence of Technology, Data Interpretation Heuristics and Curricular Policy

ERIC Educational Resources Information Center

Swan, Gerry; Mazur, Joan

2011-01-01

Although the term data-driven decision making (DDDM) is relatively new (Moss, 2007), the underlying concept of DDDM is not. For example, the practices of formative assessment and computer-managed instruction have historically involved the use of student performance data to guide what happens next in the instructional sequence (Morrison, Kemp, &…

How Instructional Coaches Support Data-Driven Decision Making: Policy Implementation and Effects in Florida Middle Schools

ERIC Educational Resources Information Center

Marsh, Julie A.; McCombs, Jennifer Sloan; Martorell, Francisco

2010-01-01

This article examines the convergence of two popular school improvement policies: instructional coaching and data-driven decision making (DDDM). Drawing on a mixed methods study of a statewide reading coach program in Florida middle schools, the article examines how coaches support DDDM and how this support relates to student and teacher outcomes.…

Notification Event Architecture for Traveler Screening: Predictive Traveler Screening Using Event Driven Business Process Management

ERIC Educational Resources Information Center

Lynch, John Kenneth

2013-01-01

Using an exploratory model of the 9/11 terrorists, this research investigates the linkages between Event Driven Business Process Management (edBPM) and decision making. Although the literature on the role of technology in efficient and effective decision making is extensive, research has yet to quantify the benefit of using edBPM to aid the…

Creating a System for Data-Driven Decision-Making: Applying the Principal-Agent Framework

ERIC Educational Resources Information Center

Wohlstetter, Priscilla; Datnow, Amanda; Park, Vicki

2008-01-01

The purpose of this article is to improve our understanding of data-driven decision-making strategies that are initiated at the district or system level. We apply principal-agent theory to the analysis of qualitative data gathered in a case study of 4 urban school systems. Our findings suggest educators at the school level need not only systemic…

Supporting Informed Decision Making - Center for Research Strategy

Cancer.gov

CRS conducts portfolio analyses and collects data on scientific topics, funding mechanisms, and investigator characteristics to help NCI leadership make data-driven decisions about the scientific research enterprise.

Incorporating Science into Decision-Making

USGS Publications Warehouse

Karl, Herman A.; Turner, Christine E.

2003-01-01

Alan Leshner's Editorial “Public engagement with science” (14 Feb., p. 977) highlights a conundrum: Why is science often ignored in important societal decisions, even as the call for decisions based on sound science escalates? One reason is that decision-making is often driven by a variety of nonscientific, adversarial, and stakeholder dynamics

Teacher Talk about Student Ability and Achievement in the Era of Data-Driven Decision Making

ERIC Educational Resources Information Center

Datnow, Amanda; Choi, Bailey; Park, Vicki; St. John, Elise

2018-01-01

Background: Data-driven decision making continues to be a common feature of educational reform agendas across the globe. In many U.S. schools, the teacher team meeting is a key setting in which data use is intended to take place, with the aim of planning instruction to address students' needs. However, most prior research has not examined how the…

Student decision making in large group discussion

NASA Astrophysics Data System (ADS)

Kustusch, Mary Bridget; Ptak, Corey; Sayre, Eleanor C.; Franklin, Scott V.

2015-04-01

It is increasingly common in physics classes for students to work together to solve problems and perform laboratory experiments. When students work together, they need to negotiate the roles and decision making within the group. We examine how a large group of students negotiates authority as part of their two week summer College Readiness Program at Rochester Institute of Technology. The program is designed to develop metacognitive skills in first generation and Deaf and hard-of-hearing (DHH) STEM undergraduates through cooperative group work, laboratory experimentation, and explicit reflection exercises. On the first full day of the program, the students collaboratively developed a sign for the word ``metacognition'' for which there is not a sign in American Sign Language. This presentation will focus on three aspects of the ensuing discussion: (1) how the instructor communicated expectations about decision making; (2) how the instructor promoted student-driven decision making rather than instructor-driven policy; and (3) one student's shifts in decision making behavior. We conclude by discussing implications of this research for activity-based physics instruction.

Data-Driven Decision Making and Its Effects on Leadership Practices and Student Achievement in K-5 Public Elementary Schools in California

ERIC Educational Resources Information Center

Ceja, Rafael, Jr.

2012-01-01

The enactment of the NCLB Act of 2001 and its legislative mandates for accountability testing throughout the nation brought to the forefront the issue of data-driven decision making. This emphasis on improving education has been spurred due to the alleged failure of the public school system. As a result, the role of administrators has evolved to…

Teachers' Experiences with the Data-Driven Decision Making Process in Increasing Students' Reading Achievement in a Title I Elementary Public School

ERIC Educational Resources Information Center

Atkinson, Linton

2015-01-01

This paper is a research dissertation based on a qualitative case study conducted on Teachers' Experiences within a Data-Driven Decision Making (DDDM) process. The study site was a Title I elementary school in a large school district in Central Florida. Background information is given in relation to the need for research that was conducted on the…

Deciding for Future Selves Reduces Loss Aversion

PubMed Central

Cheng, Qiqi; He, Guibing

2017-01-01

In this paper, we present an incentivized experiment to investigate the degree of loss aversion when people make decisions for their current selves and future selves under risk. We find that when participants make decisions for their future selves, they are less loss averse compared to when they make decisions for their current selves. This finding is consistent with the interpretation of loss aversion as a bias in decision-making driven by emotions, which are reduced when making decisions for future selves. Our findings endorsed the external validity of previous studies on the impact of emotion on loss aversion in a real world decision-making environment. PMID:28979234

Deciding for Future Selves Reduces Loss Aversion.

PubMed

Cheng, Qiqi; He, Guibing

2017-01-01

In this paper, we present an incentivized experiment to investigate the degree of loss aversion when people make decisions for their current selves and future selves under risk. We find that when participants make decisions for their future selves, they are less loss averse compared to when they make decisions for their current selves. This finding is consistent with the interpretation of loss aversion as a bias in decision-making driven by emotions, which are reduced when making decisions for future selves. Our findings endorsed the external validity of previous studies on the impact of emotion on loss aversion in a real world decision-making environment.

Dysfunctional decision-making in pathological gambling: pattern specificity and the role of impulsivity.

PubMed

Kräplin, Anja; Dshemuchadse, Maja; Behrendt, Silke; Scherbaum, Stefan; Goschke, Thomas; Bühringer, Gerhard

2014-03-30

Dysfunctional decision-making in individuals with pathological gambling (PGs) may result from dominating reward-driven processes, indicated by higher impulsivity. In the current study we examined (1) if PGs show specific decision-making impairments related to dominating reward-driven processes rather than to strategic planning deficits and (2) whether these impairments are related to impulsivity. Nineteen PGs according to DSM-IV and 19 matched control subjects undertook the Cambridge Gambling Task (CGT) to assess decision-making. The delay discounting paradigm (DDP) as well as the UPPS Impulsive Behavior Scale (measuring urgency, premeditation, perseverance and sensation seeking) were administered as multidimensional measures of impulsivity. Results revealed that (1) PGs exhibited higher risk seeking and an immediate reward focus in the CGT and, in contrast, comparable strategic planning to the control group. (2) Decision-making impairments were related to more severe delay discounting and, specifically, to increased urgency and less premeditation. Our findings suggest (1) the necessity to disentangle decision-making components in order to improve etiological models of PGs, and (2) that urgency and premeditation are specifically related to disadvantageous decision-making and should be tackled in intervention strategies focusing on emotion tolerance and control strategies. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Systemic Data-Based Decision Making: A Systems Approach for Using Data in Schools

ERIC Educational Resources Information Center

Walser, Tamara M.

2009-01-01

No Child Left Behind has increased data collection and reporting, the development of data systems, and interest in using data for decision-making in schools and classrooms. Ends-driven decision making has become common educational practice, where the ends justify the means at all costs, and short-term results trump longer-term outcomes and the…

Social Capital in Data-Driven Community College Reform

ERIC Educational Resources Information Center

Kerrigan, Monica Reid

2015-01-01

The current rhetoric around using data to improve community college student outcomes with only limited research on data-driven decision-making (DDDM) within postsecondary education compels a more comprehensive understanding of colleges' capacity for using data to inform decisions. Based on an analysis of faculty and administrators' perceptions and…

Data-driven freeway performance evaluation framework for project prioritization and decision making.

DOT National Transportation Integrated Search

2017-01-01

This report describes methods that potentially can be incorporated into the performance monitoring and planning processes for freeway performance evaluation and decision making. Reliability analysis was conducted on the selected I-15 corridor by empl...

Data-driven freeway performance evaluation framework for project prioritization and decision making.

DOT National Transportation Integrated Search

2015-03-01

This report describes methods that potentially can be incorporated into the performance monitoring and planning : processes for freeway performance evaluation and decision making. Reliability analysis is conducted on the selected : I-15 corridor by e...

A Neural Signature Encoding Decisions under Perceptual Ambiguity

PubMed Central

Sun, Sai; Yu, Rongjun

2017-01-01

Abstract People often make perceptual decisions with ambiguous information, but it remains unclear whether the brain has a common neural substrate that encodes various forms of perceptual ambiguity. Here, we used three types of perceptually ambiguous stimuli as well as task instructions to examine the neural basis for both stimulus-driven and task-driven perceptual ambiguity. We identified a neural signature, the late positive potential (LPP), that encoded a general form of stimulus-driven perceptual ambiguity. In addition to stimulus-driven ambiguity, the LPP was also modulated by ambiguity in task instructions. To further specify the functional role of the LPP and elucidate the relationship between stimulus ambiguity, behavioral response, and the LPP, we employed regression models and found that the LPP was specifically associated with response latency and confidence rating, suggesting that the LPP encoded decisions under perceptual ambiguity. Finally, direct behavioral ratings of stimulus and task ambiguity confirmed our neurophysiological findings, which could not be attributed to differences in eye movements either. Together, our findings argue for a common neural signature that encodes decisions under perceptual ambiguity but is subject to the modulation of task ambiguity. Our results represent an essential first step toward a complete neural understanding of human perceptual decision making. PMID:29177189

A Neural Signature Encoding Decisions under Perceptual Ambiguity.

PubMed

Sun, Sai; Yu, Rongjun; Wang, Shuo

2017-01-01

People often make perceptual decisions with ambiguous information, but it remains unclear whether the brain has a common neural substrate that encodes various forms of perceptual ambiguity. Here, we used three types of perceptually ambiguous stimuli as well as task instructions to examine the neural basis for both stimulus-driven and task-driven perceptual ambiguity. We identified a neural signature, the late positive potential (LPP), that encoded a general form of stimulus-driven perceptual ambiguity. In addition to stimulus-driven ambiguity, the LPP was also modulated by ambiguity in task instructions. To further specify the functional role of the LPP and elucidate the relationship between stimulus ambiguity, behavioral response, and the LPP, we employed regression models and found that the LPP was specifically associated with response latency and confidence rating, suggesting that the LPP encoded decisions under perceptual ambiguity. Finally, direct behavioral ratings of stimulus and task ambiguity confirmed our neurophysiological findings, which could not be attributed to differences in eye movements either. Together, our findings argue for a common neural signature that encodes decisions under perceptual ambiguity but is subject to the modulation of task ambiguity. Our results represent an essential first step toward a complete neural understanding of human perceptual decision making.

Data: Mining with a Mission- Data-Driven Decision Making Is the Buzz Phrase of Choice for the New Decade. but Once We've Got the Information, How Do We Use It to Yield Results?

ERIC Educational Resources Information Center

Salpeter, Judy

2004-01-01

For some districts, the current obsession with data grows out of the need to comply with No Child Left Behind and additional accountability-related mandates. For others, it dates way back before the phrase "data-driven decision making" rolled so frequently off the tongues of educators. In either case, there is no denying that an integral…

Data key to quest for quality.

PubMed

Chang, Florence S; Nielsen, Jon; Macias, Charles

2013-11-01

Late-binding data warehousing reduces the time it takes to obtain data needed to make crucial decisions. Late binding refers to when and how tightly data from the source applications are bound to the rules and vocabularies that make it useful. In some cases, data can be seen in real time. In historically paper-driven environments where data-driven decisions may be a new concept, buy-in from clinicians, physicians, and hospital leaders is key to success in using data to improve outcomes.

Data to Decisions: Creating a Culture of Model-Driven Drug Discovery.

PubMed

Brown, Frank K; Kopti, Farida; Chang, Charlie Zhenyu; Johnson, Scott A; Glick, Meir; Waller, Chris L

2017-09-01

Merck & Co., Inc., Kenilworth, NJ, USA, is undergoing a transformation in the way that it prosecutes R&D programs. Through the adoption of a "model-driven" culture, enhanced R&D productivity is anticipated, both in the form of decreased attrition at each stage of the process and by providing a rational framework for understanding and learning from the data generated along the way. This new approach focuses on the concept of a "Design Cycle" that makes use of all the data possible, internally and externally, to drive decision-making. These data can take the form of bioactivity, 3D structures, genomics, pathway, PK/PD, safety data, etc. Synthesis of high-quality data into models utilizing both well-established and cutting-edge methods has been shown to yield high confidence predictions to prioritize decision-making and efficiently reposition resources within R&D. The goal is to design an adaptive research operating plan that uses both modeled data and experiments, rather than just testing, to drive project decision-making. To support this emerging culture, an ambitious information management (IT) program has been initiated to implement a harmonized platform to facilitate the construction of cross-domain workflows to enable data-driven decision-making and the construction and validation of predictive models. These goals are achieved through depositing model-ready data, agile persona-driven access to data, a unified cross-domain predictive model lifecycle management platform, and support for flexible scientist-developed workflows that simplify data manipulation and consume model services. The end-to-end nature of the platform, in turn, not only supports but also drives the culture change by enabling scientists to apply predictive sciences throughout their work and over the lifetime of a project. This shift in mindset for both scientists and IT was driven by an early impactful demonstration of the potential benefits of the platform, in which expert-level early discovery predictive models were made available from familiar desktop tools, such as ChemDraw. This was built using a workflow-driven service-oriented architecture (SOA) on top of the rigorous registration of all underlying model entities.

Evidence-informed decision making for nutrition: African experiences and way forward.

PubMed

Aryeetey, Richmond; Holdsworth, Michelle; Taljaard, Christine; Hounkpatin, Waliou Amoussa; Colecraft, Esi; Lachat, Carl; Nago, Eunice; Hailu, Tesfaye; Kolsteren, Patrick; Verstraeten, Roos

2017-11-01

Although substantial amount of nutrition research is conducted in Africa, the research agenda is mainly donor-driven. There is a clear need for a revised research agenda in Africa which is both driven by and responding to local priorities. The present paper summarises proceedings of a symposium on how evidence can guide decision makers towards context-appropriate priorities and decisions in nutrition. The paper focuses on lessons learnt from case studies by the Evidence Informed Decision Making in Nutrition and Health Network implemented between 2015 and 2016 in Benin, Ghana and South Africa. Activities within these countries were organised around problem-oriented evidence-informed decision-making (EIDM), capacity strengthening and leadership and horizontal collaboration. Using a combination of desk-reviews, stakeholder influence-mapping, semi-structured interviews and convening platforms, these country-level studies demonstrated strong interest for partnership between researchers and decision makers, and use of research evidence for prioritisation and decision making in nutrition. Identified capacity gaps were addressed through training workshops on EIDM, systematic reviews, cost-benefit evaluations and evidence contextualisation. Investing in knowledge partnerships and development of capacity and leadership are key to drive appropriate use of evidence in nutrition policy and programming in Africa.

A geospatial framework for dynamic route planning using congestion prediction in transportation systems.

DOT National Transportation Integrated Search

2011-01-01

The goal this research is to develop an end-to-end data-driven system, dubbed TransDec : (short for Transportation Decision-Making), to enable decision-making queries in : transportation systems with dynamic, real-time and historical data. With Trans...

A Framework for Facilitating Ecosystem Services-based Decision-making and the Development of Decision-making Tools

EPA Science Inventory

There is an increasing understanding that top-down regulatory and technology driven responses are not sufficient to address current and emerging environmental challenges such as climate change, sustainable communities, and environmental justice. The vast majority of environmenta...

Enhanced Risk Aversion, But Not Loss Aversion, in Unmedicated Pathological Anxiety.

PubMed

Charpentier, Caroline J; Aylward, Jessica; Roiser, Jonathan P; Robinson, Oliver J

2017-06-15

Anxiety disorders are associated with disruptions in both emotional processing and decision making. As a result, anxious individuals often make decisions that favor harm avoidance. However, this bias could be driven by enhanced aversion to uncertainty about the decision outcome (e.g., risk) or aversion to negative outcomes (e.g., loss). Distinguishing between these possibilities may provide a better cognitive understanding of anxiety disorders and hence inform treatment strategies. To address this question, unmedicated individuals with pathological anxiety (n = 25) and matched healthy control subjects (n = 23) completed a gambling task featuring a decision between a gamble and a safe (certain) option on every trial. Choices on one type of gamble-involving weighing a potential win against a potential loss (mixed)-could be driven by both loss and risk aversion, whereas choices on the other type-featuring only wins (gain only)-were exclusively driven by risk aversion. By fitting a computational prospect theory model to participants' choices, we were able to reliably estimate risk and loss aversion and their respective contribution to gambling decisions. Relative to healthy control subjects, pathologically anxious participants exhibited enhanced risk aversion but equivalent levels of loss aversion. Individuals with pathological anxiety demonstrate clear avoidance biases in their decision making. These findings suggest that this may be driven by a reduced propensity to take risks rather than a stronger aversion to losses. This important clarification suggests that psychological interventions for anxiety should focus on reducing risk sensitivity rather than reducing sensitivity to negative outcomes per se. Copyright © 2017 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

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

PubMed

Hoggart, Lesley

2018-05-21

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

How Business Intelligence and Social Interaction Amplify Organizational Cognition

ERIC Educational Resources Information Center

Penn, Stephen Paul

2012-01-01

This systematic literature review of current scholarship on business intelligence, individual decision-making behavior, strategy as practice, and strategic planning offers a roadmap for firms seeking to increase their competitive advantage through data driven decision-making. Planning, deciding, and using information is a single phenomenon where…

Neural basis of quasi-rational decision making.

PubMed

Lee, Daeyeol

2006-04-01

Standard economic theories conceive homo economicus as a rational decision maker capable of maximizing utility. In reality, however, people tend to approximate optimal decision-making strategies through a collection of heuristic routines. Some of these routines are driven by emotional processes, and others are adjusted iteratively through experience. In addition, routines specialized for social decision making, such as inference about the mental states of other decision makers, might share their origins and neural mechanisms with the ability to simulate or imagine outcomes expected from alternative actions that an individual can take. A recent surge of collaborations across economics, psychology and neuroscience has provided new insights into how such multiple elements of decision making interact in the brain.

Hypothesis-Driven Story Building: Counteracting Human Cognitive Biases to Improve Medical Diagnosis Support

ERIC Educational Resources Information Center

Zhu, Shizhuo

2010-01-01

Clinical decision-making is challenging mainly because of two factors: (1) patient conditions are often complicated with partial and changing information; (2) people have cognitive biases in their decision-making and information-seeking. Consequentially, misdiagnoses and ineffective use of resources may happen. To better support clinical…

Entrepreneurial Decision Making and Institutional Governance within the Academy: A Case Study

ERIC Educational Resources Information Center

French, Edward F.

2011-01-01

This case study explored the relationship between entrepreneurial decision making and optimal institutional governance. The study focused on a single institution, characterized as a small, tuition-driven, private institution. Twelve participants were interviewed in the study, equally divided between members of the faculty and of the…

Data-Driven Decision Making in Community Colleges: An Integrative Model for Institutional Effectiveness

ERIC Educational Resources Information Center

Callery, Claude Adam

2012-01-01

This qualitative study identified the best practices utilized by community colleges to achieve systemic and cultural agreement in support of the integration of institutional effectiveness measures (key performance indicators) to inform decision making. In addition, the study identifies the relevant motives, organizational structure, and processes…

Investigating the Decision-Making of Response to Intervention (RtI) Teams within the School Setting

ERIC Educational Resources Information Center

Thur, Scott M.

2015-01-01

The purpose of this study was to measure decision-making influences within RtI teams. The study examined the factors that influence school personnel involved in three areas of RtI: determining which RtI measures and tools teams select and implement (i.e. Measures and Tools), evaluating the data-driven decisions that are made based on the…

Emotion and decision-making: affect-driven belief systems in anxiety and depression.

PubMed

Paulus, Martin P; Yu, Angela J

2012-09-01

Emotion processing and decision-making are integral aspects of daily life. However, our understanding of the interaction between these constructs is limited. In this review, we summarize theoretical approaches that link emotion and decision-making, and focus on research with anxious or depressed individuals to show how emotions can interfere with decision-making. We integrate the emotional framework based on valence and arousal with a Bayesian approach to decision-making in terms of probability and value processing. We discuss how studies of individuals with emotional dysfunctions provide evidence that alterations of decision-making can be viewed in terms of altered probability and value computation. We argue that the probabilistic representation of belief states in the context of partially observable Markov decision processes provides a useful approach to examine alterations in probability and value representation in individuals with anxiety and depression, and outline the broader implications of this approach. Copyright © 2012. Published by Elsevier Ltd.

Emotion and decision-making: affect-driven belief systems in anxiety and depression

PubMed Central

Paulus, Martin P.; Yu, Angela J.

2012-01-01

Emotion processing and decision-making are integral aspects of daily life. However, our understanding of the interaction between these constructs is limited. In this review, we summarize theoretical approaches to the link between emotion and decision-making, and focus on research with anxious or depressed individuals that reveals how emotions can interfere with decision-making. We integrate the emotional framework based on valence and arousal with a Bayesian approach to decision-making in terms of probability and value processing. We then discuss how studies of individuals with emotional dysfunctions provide evidence that alterations of decision-making can be viewed in terms of altered probability and value computation. We argue that the probabilistic representation of belief states in the context of partially observable Markov decision processes provides a useful approach to examine alterations in probability and value representation in individuals with anxiety and depression and outline the broader implications of this approach. PMID:22898207

THE BESIEGED FORTRESS: MAKING SENSE OF RUSSIA’S ANNEXATION OF CRIMEA AND WHAT IT MEANS TO U.S. POLICY MAKERS

DTIC Science & Technology

2017-02-13

those from whom he derives his true power--the Russian people. Driven to make Russia a great power again, I argue that Putin’s decision to invade...strategically valuable piece of terrain. While undoubtedly seeking to influence Kiev’s strategic decision - making , prior to the 2014 annexation, Putin...inhabited by ethnic kin with its motherland. Putin’s decision to annex Crimea in 2014 was in part motivated by, and rationalized through

Shared decision-making and patient autonomy.

PubMed

Sandman, Lars; Munthe, Christian

2009-01-01

In patient-centred care, shared decision-making is advocated as the preferred form of medical decision-making. Shared decision-making is supported with reference to patient autonomy without abandoning the patient or giving up the possibility of influencing how the patient is benefited. It is, however, not transparent how shared decision-making is related to autonomy and, in effect, what support autonomy can give shared decision-making. In the article, different forms of shared decision-making are analysed in relation to five different aspects of autonomy: (1) self-realisation; (2) preference satisfaction; (3) self-direction; (4) binary autonomy of the person; (5) gradual autonomy of the person. It is argued that both individually and jointly these aspects will support the models called shared rational deliberative patient choice and joint decision as the preferred versions from an autonomy perspective. Acknowledging that both of these models may fail, the professionally driven best interest compromise model is held out as a satisfactory second-best choice.

The Call for Data-Driven Decision Making in the Midwest's Schools: NCREL's Response.

ERIC Educational Resources Information Center

Cromey, Allison; van der Ploeg, Arie; Masini, Blase

This report describes the efforts of the North Central Regional Educational Laboratory (NCREL) during the last several years to respond to direct requests from educational stakeholders to help integrate data into their decision-making processes related to school improvement. In some cases, NCREL cooperated in the development of educational…

Balancing Data, Time, and Expectations: The Complex Decision-­Making Environment of Enrollment Management

ERIC Educational Resources Information Center

Johnson, Adam W.

2016-01-01

As a growing entity within higher education organizational structures, enrollment managers (EMs) are primarily tasked with projecting, recruiting, and retaining the student population of their campuses. Enrollment managers are expected by institutional presidents as well as through industry standards to make data-driven planning decisions to reach…

Balancing Data, Time, and Expectations: The Complex Decision-Making Environment of Enrollment Management

ERIC Educational Resources Information Center

Johnson, Adam W.

2013-01-01

As a growing entity within higher education organizational structures, enrollment managers (EMs) are primarily tasked with projecting, recruiting, and retaining the student population of their campuses. Enrollment managers are expected by institutional presidents as well as through industry standards to make data-driven planning decisions to reach…

Attitudes towards poverty, organizations, ethics and morals: Israeli social workers' shared decision making.

PubMed

Levin, Lia; Schwartz-Tayri, Talia

2017-06-01

Partnerships between service users and social workers are complex in nature and can be driven by both personal and contextual circumstances. This study sought to explore the relationship between social workers' involvement in shared decision making with service users, their attitudes towards service users in poverty, moral standards and health and social care organizations' policies towards shared decision making. Based on the responses of 225 licensed social workers from health and social care agencies in the public, private and third sectors in Israel, path analysis was used to test a hypothesized model. Structural attributions for poverty contributed to attitudes towards people who live in poverty, which led to shared decision making. Also, organizational support in shared decision making, and professional moral identity, contributed to ethical behaviour which led to shared decision making. The results of this analysis revealed that shared decision making may be a scion of branched roots planted in the relationship between ethics, organizations and Stigma. © 2016 The Authors. Health Expectations Published by John Wiley & Sons Ltd.

The Correlation of Data-Driven Instruction to Teacher-Effectiveness, Teacher-Collaboration, and Teacher-Satisfaction

ERIC Educational Resources Information Center

Shaw, Rhonda R.

2017-01-01

Education reform is inevitable; however, the journey of reform must ensure that educators are equipped to meet the diverse needs of all children within the classrooms throughout. Data-driven decision making is going to be the driving force for making that happen. This mixed model research was designed to show how implementing data-driven…

Visualization-based decision support for value-driven system design

NASA Astrophysics Data System (ADS)

Tibor, Elliott

In the past 50 years, the military, communication, and transportation systems that permeate our world, have grown exponentially in size and complexity. The development and production of these systems has seen ballooning costs and increased risk. This is particularly critical for the aerospace industry. The inability to deal with growing system complexity is a crippling force in the advancement of engineered systems. Value-Driven Design represents a paradigm shift in the field of design engineering that has potential to help counteract this trend. The philosophy of Value-Driven Design places the desires of the stakeholder at the forefront of the design process to capture true preferences and reveal system alternatives that were never previously thought possible. Modern aerospace engineering design problems are large, complex, and involve multiple levels of decision-making. To find the best design, the decision-maker is often required to analyze hundreds or thousands of combinations of design variables and attributes. Visualization can be used to support these decisions, by communicating large amounts of data in a meaningful way. Understanding the design space, the subsystem relationships, and the design uncertainties is vital to the advancement of Value-Driven Design as an accepted process for the development of more effective, efficient, robust, and elegant aerospace systems. This research investigates the use of multi-dimensional data visualization tools to support decision-making under uncertainty during the Value-Driven Design process. A satellite design system comprising a satellite, ground station, and launch vehicle is used to demonstrate effectiveness of new visualization methods to aid in decision support during complex aerospace system design. These methods are used to facilitate the exploration of the feasible design space by representing the value impact of system attribute changes and comparing the results of multi-objective optimization formulations with a Value-Driven Design formulation. The visualization methods are also used to assist in the decomposition of a value function, by representing attribute sensitivities to aid with trade-off studies. Lastly, visualization is used to enable greater understanding of the subsystem relationships, by displaying derivative-based couplings, and the design uncertainties, through implementation of utility theory. The use of these visualization methods is shown to enhance the decision-making capabilities of the designer by granting them a more holistic view of the complex design space.

Demystifying Data: Designing and Implementing Data-Driven Systems and Practices for Continuous Quality Improvement

ERIC Educational Resources Information Center

Krugly, Andrew; Stein, Amanda; Centeno, Maribel G.

2014-01-01

Data-based decision making should be the driving force in any early care and education setting. Data usage compels early childhood practitioners and leaders to make decisions on the basis of more than just professional instinct. This article explores why early childhood schools should be using data for continuous quality improvement at various…

An intelligent value-driven scheduling system for Space Station Freedom with special emphasis on the electric power system

NASA Technical Reports Server (NTRS)

Krupp, Joseph C.

1991-01-01

The Electric Power Control System (EPCS) created by Decision-Science Applications, Inc. (DSA) for the Lewis Research Center is discussed. This system makes decisions on what to schedule and when to schedule it, including making choices among various options or ways of performing a task. The system is goal-directed and seeks to shape resource usage in an optimal manner using a value-driven approach. Discussed here are considerations governing what makes a good schedule, how to design a value function to find the best schedule, and how to design the algorithm that finds the schedule that maximizes this value function. Results are shown which demonstrate the usefulness of the techniques employed.

Shared Decision Making: The Need For Patient-Clinician Conversation, Not Just Information.

PubMed

Hargraves, Ian; LeBlanc, Annie; Shah, Nilay D; Montori, Victor M

2016-04-01

The growth of shared decision making has been driven largely by the understanding that patients need information and choices regarding their health care. But while these are important elements for patients who make decisions in partnership with their clinicians, our experience suggests that they are not enough to address the larger issue: the need for the patient and clinician to jointly create a course of action that is best for the individual patient and his or her family. The larger need in evidence-informed shared decision making is for a patient-clinician interaction that offers conversation, not just information, and care, not just choice. Project HOPE—The People-to-People Health Foundation, Inc.

Data for Renewable Energy Planning, Policy, and Investment

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

Cox, Sarah L

Reliable, robust, and validated data are critical for informed planning, policy development, and investment in the clean energy sector. The Renewable Energy (RE) Explorer was developed to support data-driven renewable energy analysis that can inform key renewable energy decisions globally. This document presents the types of geospatial and other data at the core of renewable energy analysis and decision making. Individual data sets used to inform decisions vary in relation to spatial and temporal resolution, quality, and overall usefulness. From Data to Decisions, a complementary geospatial data and analysis decision guide, provides an in-depth view of these and other considerationsmore » to enable data-driven planning, policymaking, and investment. Data support a wide variety of renewable energy analyses and decisions, including technical and economic potential assessment, renewable energy zone analysis, grid integration, risk and resiliency identification, electrification, and distributed solar photovoltaic potential. This fact sheet provides information on the types of data that are important for renewable energy decision making using the RE Data Explorer or similar types of geospatial analysis tools.« less

Decision-making in Swiss home-like childbirth: A grounded theory study.

PubMed

Meyer, Yvonne; Frank, Franziska; Schläppy Muntwyler, Franziska; Fleming, Valerie; Pehlke-Milde, Jessica

2017-12-01

Decision-making in midwifery, including a claim for shared decision-making between midwives and women, is of major significance for the health of mother and child. Midwives have little information about how to share decision-making responsibilities with women, especially when complications arise during birth. To increase understanding of decision-making in complex home-like birth settings by exploring midwives' and women's perspectives and to develop a dynamic model integrating participatory processes for making shared decisions. The study, based on grounded theory methodology, analysed 20 interviews of midwives and 20 women who had experienced complications in home-like births. The central phenomenon that arose from the data was "defining/redefining decision as a joint commitment to healthy childbirth". The sub-indicators that make up this phenomenon were safety, responsibility, mutual and personal commitments. These sub-indicators were also identified to influence temporal conditions of decision-making and to apply different strategies for shared decision-making. Women adopted strategies such as delegating a decision, making the midwife's decision her own, challenging a decision or taking a decision driven by the dynamics of childbirth. Midwives employed strategies such as remaining indecisive, approving a woman's decision, making an informed decision or taking the necessary decision. To respond to recommendations for shared responsibility for care, midwives need to strengthen their shared decision-making skills. The visual model of decision-making in childbirth derived from the data provides a framework for transferring clinical reasoning into practice. Copyright © 2017 Australian College of Midwives. Published by Elsevier Ltd. All rights reserved.

A genetically mediated bias in decision making driven by failure of amygdala control.

PubMed

Roiser, Jonathan P; de Martino, Benedetto; Tan, Geoffrey C Y; Kumaran, Dharshan; Seymour, Ben; Wood, Nicholas W; Dolan, Raymond J

2009-05-06

Genetic variation at the serotonin transporter-linked polymorphic region (5-HTTLPR) is associated with altered amygdala reactivity and lack of prefrontal regulatory control. Similar regions mediate decision-making biases driven by contextual cues and ambiguity, for example the "framing effect." We hypothesized that individuals hemozygous for the short (s) allele at the 5-HTTLPR would be more susceptible to framing. Participants, selected as homozygous for either the long (la) or s allele, performed a decision-making task where they made choices between receiving an amount of money for certain and taking a gamble. A strong bias was evident toward choosing the certain option when the option was phrased in terms of gains and toward gambling when the decision was phrased in terms of losses (the frame effect). Critically, this bias was significantly greater in the ss group compared with the lala group. In simultaneously acquired functional magnetic resonance imaging data, the ss group showed greater amygdala during choices made in accord, compared with those made counter to the frame, an effect not seen in the lala group. These differences were also mirrored by differences in anterior cingulate-amygdala coupling between the genotype groups during decision making. Specifically, lala participants showed increased coupling during choices made counter to, relative to those made in accord with, the frame, with no such effect evident in ss participants. These data suggest that genetically mediated differences in prefrontal-amygdala interactions underpin interindividual differences in economic decision making.

Self-Efficacy as a Predictor of Career Decision Making among Secondary School Students in Busia County, Kenya

ERIC Educational Resources Information Center

Ogutu, Joel Peter; Odera, Peter; Maragia, Samuel N.

2017-01-01

The most common constrain to career progression among youth in Kenya is the inability to make informed career decisions. Majority of high school students suffer from excitement for attaining university degree self-actualization rather than taking up career that enhances development of talents and skills that are job market driven. This study aimed…

Proof in the Pattern: Librarians Follow the Corporate Sector toward More Data-Driven Management

ERIC Educational Resources Information Center

Nicholson, Scott

2006-01-01

As demands on libraries continue to grow, outpacing budget increases, more librarians are forced to make difficult decisions about what materials and services stay and go. Charles R. McClure has written that many librarians use an "adhocracy" method to make these decisions, relying on no data or simple aggregates in determining a course of action.…

Replicating the Relationship between Teachers' Data Use and Student Achievement: The Urban Data Study and the Data Dashboard Usage Study

ERIC Educational Resources Information Center

Faria, Ann-Marie; Greenberg, Ariela; Meakin, John; Bichay, Krystal; Heppen, Jessica

2014-01-01

Educators have long used test scores to make educational decisions, but only within the last decade has the availability of data been systematic (Abelman, Elmore, Even, Kenyon, & Marshall, 1999). In recent years, interest has spiked in data-driven decision making in education (Marsh, Pane, & Hamilton, 2006). With technological advances and…

The impact of data integrity on decision making in early lead discovery

NASA Astrophysics Data System (ADS)

Beck, Bernd; Seeliger, Daniel; Kriegl, Jan M.

2015-09-01

Data driven decision making is a key element of today's pharmaceutical research, including early drug discovery. It comprises questions like which target to pursue, which chemical series to pursue, which compound to make next, or which compound to select for advanced profiling and promotion to pre-clinical development. In the following paper we will exemplify how data integrity, i.e. the context data is generated in and auxiliary information that is provided for individual result records, can influence decision making in early lead discovery programs. In addition we will describe some approaches which we pursue at Boehringer Ingelheim to reduce the risk for getting misguided.

Patterns of reasoning and decision making about condom use by urban college students.

PubMed

Patel, V L; Gutnik, L A; Yoskowitz, N A; O'sullivan, L F; Kaufman, D R

2006-11-01

HIV infection rates are rapidly increasing among young heterosexuals, making it increasingly important to understand how these individuals make decisions regarding risk in sexual encounters. Our objective in this study was to characterize young adults' safer sex behaviour and associate this behaviour with patterns of reasoning, using cognitive, information processing methods to understand the process of sexual risk taking. Sixty urban college students from NYC maintained diaries for two weeks and then were interviewed regarding lifetime condom use and sexual history. Using cognitive analysis, we characterized four patterns of condom use behaviour: consistent condom use (35.0%), inconsistent condom use (16.7%), shifting from consistent to inconsistent condom use (35.0%), and shifting from inconsistent to consistent condom use (13.3%). Directionality of reasoning (i.e. data-driven and hypothesis-driven reasoning) was analysed in the explanations provided for condom use decisions. The consistent and inconsistent patterns of condom use were associated with data-driven heuristic reasoning, where behaviour becomes automated and is associated with a high level of confidence in one's judgment. In the other two patterns, the shift in behaviour was due to a significant event that caused a change in type of reasoning to explanation-based reasoning, reflecting feelings of uncertainty and willingness to evaluate their decisions. We discuss these results within the framework of identifying potentially high-risk groups (e.g. heterosexual young adults) as well as intervention strategies for risk reduction. Further, our findings not only identify different patterns of condom use behaviour, but our investigation of the cognitive process of decision-making characterizes the conditions under which such behaviour and reasoning change.

Shared decision making, paternalism and patient choice.

PubMed

Sandman, Lars; Munthe, Christian

2010-03-01

In patient centred care, shared decision making is a central feature and widely referred to as a norm for patient centred medical consultation. However, it is far from clear how to distinguish SDM from standard models and ideals for medical decision making, such as paternalism and patient choice, and e.g., whether paternalism and patient choice can involve a greater degree of the sort of sharing involved in SDM and still retain their essential features. In the article, different versions of SDM are explored, versions compatible with paternalism and patient choice as well as versions that go beyond these traditional decision making models. Whenever SDM is discussed or introduced it is of importance to be clear over which of these different versions are being pursued, since they connect to basic values and ideals of health care in different ways. It is further argued that we have reason to pursue versions of SDM involving, what is called, a high level dynamics in medical decision-making. This leaves four alternative models to choose between depending on how we balance between the values of patient best interest, patient autonomy, and an effective decision in terms of patient compliance or adherence: Shared Rational Deliberative Patient Choice, Shared Rational Deliberative Paternalism, Shared Rational Deliberative Joint Decision, and Professionally Driven Best Interest Compromise. In relation to these models it is argued that we ideally should use the Shared Rational Deliberative Joint Decision model. However, when the patient and professional fail to reach consensus we will have reason to pursue the Professionally Driven Best Interest Compromise model since this will best harmonise between the different values at stake: patient best interest, patient autonomy, patient adherence and a continued care relationship.

Data-Driven Districts.

ERIC Educational Resources Information Center

LaFee, Scott

2002-01-01

Describes the use of data-driven decision-making in four school districts: Plainfield Public Schools, Plainfield, New Jersey; Palo Alto Unified School District, Palo Alto, California; Francis Howell School District in eastern Missouri, northwest of St. Louis; and Rio Rancho Public Schools, near Albuquerque, New Mexico. Includes interviews with the…

Toward a more data-driven supervision of collegiate counseling centers.

PubMed

Varlotta, Lori E

2012-01-01

Hearing the national call for higher education accountability, the author of this tripartite article urges university administrators to move towards a more data-driven approach to counseling center supervision. Toward that end, the author first examines a key factor--perceived increase in student pathology--that appears to shape budget and staffing decisions in many university centers. Second, she reviews the emerging but conflicting research of clinician-scholars who are trying to empirically verify or refute that perception; their conflicting results suggest that no study alone should be used as the "final word" in evidence-based decision-making. Third, the author delineates the campus-specific data that should be gathered to guide staffing and budgeting decisions on each campus. She concludes by reminding readers that data-driven decisions can and should foster high-quality care that is concurrently efficient, effective, and in sync with the needs of a particular university and student body.

Out-of-Hospital Decision-Making and Factors Influencing the Regional Distribution of Injured Patients in a Trauma System

PubMed Central

Newgard, Craig D.; Nelson, Maria J.; Kampp, Michael; Saha, Somnath; Zive, Dana; Schmidt, Terri; Daya, Mohamud; Jui, Jonathan; Wittwer, Lynn; Warden, Craig; Sahni, Ritu; Stevens, Mark; Gorman, Kyle; Koenig, Karl; Gubler, Dean; Rosteck, Pontine; Lee, Jan; Hedges, Jerris R.

2011-01-01

Background The decision-making processes used for out-of-hospital trauma triage and hospital selection in regionalized trauma systems remain poorly understood. The objective of this study was to understand the process of field triage decision-making in an established trauma system. Methods We used a mixed methods approach, including EMS records to quantify triage decisions and reasons for hospital selection in a population-based, injury cohort (2006 - 2008), plus a focused ethnography to understand EMS cognitive reasoning in making triage decisions. The study included 10 EMS agencies providing service to a 4-county regional trauma system with 3 trauma centers and 13 non-trauma hospitals. For qualitative analyses, we conducted field observation and interviews with 35 EMS field providers and a round-table discussion with 40 EMS management personnel to generate an empirical model of out-of-hospital decision making in trauma triage. Results 64,190 injured patients were evaluated by EMS, of whom 56,444 (88.0%) were transported to acute care hospitals and 9,637 (17.1% of transports) were field trauma activations. For non-trauma activations, patient/family preference and proximity accounted for 78% of destination decisions. EMS provider judgment was cited in 36% of field trauma activations and was the sole criterion in 23% of trauma patients. The empirical model demonstrated that trauma triage is driven primarily by EMS provider “gut feeling” (judgment) and relies heavily on provider experience, mechanism of injury, and early visual cues at the scene. Conclusions Provider cognitive reasoning for field trauma triage is more heuristic than algorithmic and driven primarily by provider judgment, rather than specific triage criteria. PMID:21817971

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.

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

PubMed

Evans, Nathan J; Brown, Scott D

2017-04-01

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

Intelligent Model Management in a Forest Ecosystem Management Decision Support System

Treesearch

Donald Nute; Walter D. Potter; Frederick Maier; Jin Wang; Mark Twery; H. Michael Rauscher; Peter Knopp; Scott Thomasma; Mayukh Dass; Hajime Uchiyama

2002-01-01

Decision making for forest ecosystem management can include the use of a wide variety of modeling tools. These tools include vegetation growth models, wildlife models, silvicultural models, GIS, and visualization tools. NED-2 is a robust, intelligent, goal-driven decision support system that integrates tools in each of these categories. NED-2 uses a blackboard...

In Light of the Limitations of Data-Driven Decision Making

ERIC Educational Resources Information Center

Loeb, Susanna

2012-01-01

Students' experiences and the opportunities they have to learn rest on the quality of education decisions made in each classroom, in each school, in each district, and in each state, federal legislature, and department of education. The role of research and scholarship more broadly in education finance and policy is to inform these decisions for…

Examining Candidate Information Search Processes: The Impact of Processing Goals and Sophistication.

ERIC Educational Resources Information Center

Huang, Li-Ning

2000-01-01

Investigates how 4 different information-processing goals, varying on the dimensions of effortful versus effortless and impression-driven versus non-impression-driven processing, and individual difference in political sophistication affect the depth at which undergraduate students process candidate information and their decision-making strategies.…

Data-Driven Planning: Using Assessment in Strategic Planning

ERIC Educational Resources Information Center

Bresciani, Marilee J.

2010-01-01

Data-driven planning or evidence-based decision making represents nothing new in its concept. For years, business leaders have claimed they have implemented planning informed by data that have been strategically and systematically gathered. Within higher education and student affairs, there may be less evidence of the actual practice of…

Caring Cooperators and Powerful Punishers: Differential Effects of Induced Care and Power Motivation on Different Types of Economic Decision Making.

PubMed

Chierchia, G; Lesemann, F H Parianen; Snower, D; Vogel, M; Singer, T

2017-09-11

Standard economic theory postulates that decisions are driven by stable context-insensitive preferences, while motivation psychology suggests they are driven by distinct context-sensitive motives with distinct evolutionary goals and characteristic psycho-physiological and behavioral patterns. To link these fields and test how distinct motives could differentially predict different types of economic decisions, we experimentally induced participants with either a Care or a Power motive, before having them take part in a suite of classic game theoretical paradigms involving monetary exchange. We show that the Care induction alone raised scores on a latent factor of cooperation-related behaviors, relative to a control condition, while, relative to Care, Power raised scores on a punishment-related factor. These findings argue against context-insensitive stable preferences and theories of strong reciprocity and in favor of a motive-based approach to economic decision making: Care and Power motivation have a dissociable fingerprint in shaping either cooperative or punishment behaviors.

Decision Analysis for a Sustainable Environment, Economy, and Society: A Participatory Framework for Ecosystem Services-Based Decision-Making

EPA Science Inventory

There is an increasing understanding that top-down regulatory and technology driven responses are not sufficient to address current and emerging environmental challenges such as climate change, sustainable communities, and environmental justice. The vast majority of environmenta...

Court-Driven Reform and Equal Educational Opportunity: Centralization, Decentralization, and the Shifting Judicial Role

ERIC Educational Resources Information Center

Superfine, Benjamin Michael

2010-01-01

Judicial decisions focusing on equal educational opportunity involve significant issues of educational governance and often involve explicit questions about the extent to which authority to make educational decisions should be centralized or decentralized across various institutions and entities. This review aims at clarifying scholars'…

Data-Driven Decision-Making: It's a Catch-Up Game

ERIC Educational Resources Information Center

Briggs, Linda L.

2006-01-01

Having an abundance of data residing in individual silos across campus, but little decision-ready information, is a typical scenario at many institutions. One problem is that the terms "data warehousing" and "business intelligence" refer to very different things, although the two often go hand-in-hand. "Data…

Wisdom within: unlocking the potential of big data for nursing regulators.

PubMed

Blumer, L; Giblin, C; Lemermeyer, G; Kwan, J A

2017-03-01

This paper explores the potential for incorporating big data in nursing regulators' decision-making and policy development. Big data, commonly described as the extensive volume of information that individuals and agencies generate daily, is a concept familiar to the business community but is only beginning to be explored by the public sector. Using insights gained from a recent research project, the College and Association of Registered Nurses of Alberta, in Canada is creating an organizational culture of data-driven decision-making throughout its regulatory and professional functions. The goal is to enable the organization to respond quickly and profoundly to nursing issues in a rapidly changing healthcare environment. The evidence includes a review of the Learning from Experience: Improving the Process of Internationally Educated Nurses' Applications for Registration (LFE) research project (2011-2016), combined with a literature review on data-driven decision-making within nursing and healthcare settings, and the incorporation of big data in the private and public sectors, primarily in North America. This paper discusses experience and, more broadly, how data can enhance the rigour and integrity of nursing and health policy. Nursing regulatory bodies have access to extensive data, and the opportunity to use these data to inform decision-making and policy development by investing in how it is captured, analysed and incorporated into decision-making processes. Understanding and using big data is a critical part of developing relevant, sound and credible policy. Rigorous collection and analysis of big data supports the integrity of the evidence used by nurse regulators in developing nursing and health policy. © 2016 International Council of Nurses.

Led into temptation? Rewarding brand logos bias the neural encoding of incidental economic decisions.

PubMed

Murawski, Carsten; Harris, Philip G; Bode, Stefan; Domínguez D, Juan F; Egan, Gary F

2012-01-01

Human decision-making is driven by subjective values assigned to alternative choice options. These valuations are based on reward cues. It is unknown, however, whether complex reward cues, such as brand logos, may bias the neural encoding of subjective value in unrelated decisions. In this functional magnetic resonance imaging (fMRI) study, we subliminally presented brand logos preceding intertemporal choices. We demonstrated that priming biased participants' preferences towards more immediate rewards in the subsequent temporal discounting task. This was associated with modulations of the neural encoding of subjective values of choice options in a network of brain regions, including but not restricted to medial prefrontal cortex. Our findings demonstrate the general susceptibility of the human decision making system to apparently incidental contextual information. We conclude that the brain incorporates seemingly unrelated value information that modifies decision making outside the decision-maker's awareness.

Led into Temptation? Rewarding Brand Logos Bias the Neural Encoding of Incidental Economic Decisions

PubMed Central

Murawski, Carsten; Harris, Philip G.; Bode, Stefan; Domínguez D., Juan F.; Egan, Gary F.

2012-01-01

Human decision-making is driven by subjective values assigned to alternative choice options. These valuations are based on reward cues. It is unknown, however, whether complex reward cues, such as brand logos, may bias the neural encoding of subjective value in unrelated decisions. In this functional magnetic resonance imaging (fMRI) study, we subliminally presented brand logos preceding intertemporal choices. We demonstrated that priming biased participants' preferences towards more immediate rewards in the subsequent temporal discounting task. This was associated with modulations of the neural encoding of subjective values of choice options in a network of brain regions, including but not restricted to medial prefrontal cortex. Our findings demonstrate the general susceptibility of the human decision making system to apparently incidental contextual information. We conclude that the brain incorporates seemingly unrelated value information that modifies decision making outside the decision-maker's awareness. PMID:22479547

Developing a video intervention to model effective patient-physician communication and health-related decision-making skills for a multiethnic audience.

PubMed

Richter, D L; Greaney, M L; McKeown, R E; Cornell, C E; Littleton, M A; Pulley, L; Groff, J Y; Byrd, T L; Herman, C J

2001-01-01

The ENDOW study is a multisite, community-based project designed to improve decision-making and patient-physician communication skills for midlife African-American, white, and Hispanic women facing decisions about hysterectomy. Based on results of initial focus groups, a patient education video was developed in English and Spanish to serve as the centerpiece of various interventions. The video uses community women to model appropriate decision-making and patient-physician communication skills. Women in the target populations rated the video as useful to very useful and would recommend it to others. The use of theory-driven approaches and pilot testing of draft products resulted in the production of a well-accepted, useful video suitable for diverse populations in intervention sites in several states.

Federal Policy to Local Level Decision-Making: Data Driven Education Planning in Nigeria

ERIC Educational Resources Information Center

Iyengar, Radhika; Mahal, Angelique R.; Felicia, Ukaegbu-Nnamchi Ifeyinwa; Aliyu, Balaraba; Karim, Alia

2015-01-01

This article discusses the implementation of local level education data-driven planning as implemented by the Office of the Senior Special Assistant to the President of Nigeria on the Millennium Development Goals (OSSAP-MDGs) in partnership with The Earth Institute, Columbia University. It focuses on the design and implementation of the…

A Collaborative Data Chat: Teaching Summative Assessment Data Use in Pre-Service Teacher Education

ERIC Educational Resources Information Center

Piro, Jody S.; Dunlap, Karen; Shutt, Tammy

2014-01-01

As the quality of educational outputs has been problematized, accountability systems have driven reform based upon summative assessment data. These policies impact the ways that educators use data within schools and subsequently, how teacher education programs may adjust their curricula to teach data-driven decision-making to inform instruction.…

Hands-On Learning: A Problem-Based Approach to Teaching Microsoft Excel

ERIC Educational Resources Information Center

Slayter, Erik; Higgins, Lindsey M.

2018-01-01

The development of a student's ability to make data-driven decisions has become a focus in higher education (Schield 1999; Stephenson and Caravello 2007). Data literacy, the ability to understand and use data to effectively inform decisions, is a fundamental component of information competence (Mandinach and Gummer 2013; Stephenson and Caravello,…

Data-Driven Decision Making: The "Other" Data

ERIC Educational Resources Information Center

Villano, Matt

2007-01-01

Data is a daily reality for school systems. Between standardized tests and tools from companies that offer data warehousing services, educators and district superintendents alike are up to their eyeballs in facts and figures about student performance that they can use as the basis for curricular decisions. Still, there is more to assessment than…

The Role of the Lateral Intraparietal Area in (the Study of) Decision Making.

PubMed

Huk, Alexander C; Katz, Leor N; Yates, Jacob L

2017-07-25

Over the past two decades, neurophysiological responses in the lateral intraparietal area (LIP) have received extensive study for insight into decision making. In a parallel manner, inferred cognitive processes have enriched interpretations of LIP activity. Because of this bidirectional interplay between physiology and cognition, LIP has served as fertile ground for developing quantitative models that link neural activity with decision making. These models stand as some of the most important frameworks for linking brain and mind, and they are now mature enough to be evaluated in finer detail and integrated with other lines of investigation of LIP function. Here, we focus on the relationship between LIP responses and known sensory and motor events in perceptual decision-making tasks, as assessed by correlative and causal methods. The resulting sensorimotor-focused approach offers an account of LIP activity as a multiplexed amalgam of sensory, cognitive, and motor-related activity, with a complex and often indirect relationship to decision processes. Our data-driven focus on multiplexing (and de-multiplexing) of various response components can complement decision-focused models and provides more detailed insight into how neural signals might relate to cognitive processes such as decision making.

Georgia concrete pavement performance and longevity.

DOT National Transportation Integrated Search

2012-02-01

The Georgia Department of Transportation (GDOT) has effectively utilized its pavement management system (PMS) to make informed, data-driven pavement maintenance decisions, including project selection, project prioritization, and funding allocation. C...

Automated control of hierarchical systems using value-driven methods

NASA Technical Reports Server (NTRS)

Pugh, George E.; Burke, Thomas E.

1990-01-01

An introduction is given to the Value-driven methodology, which has been successfully applied to solve a variety of difficult decision, control, and optimization problems. Many real-world decision processes (e.g., those encountered in scheduling, allocation, and command and control) involve a hierarchy of complex planning considerations. For such problems it is virtually impossible to define a fixed set of rules that will operate satisfactorily over the full range of probable contingencies. Decision Science Applications' value-driven methodology offers a systematic way of automating the intuitive, common-sense approach used by human planners. The inherent responsiveness of value-driven systems to user-controlled priorities makes them particularly suitable for semi-automated applications in which the user must remain in command of the systems operation. Three examples of the practical application of the approach in the automation of hierarchical decision processes are discussed: the TAC Brawler air-to-air combat simulation is a four-level computerized hierarchy; the autonomous underwater vehicle mission planning system is a three-level control system; and the Space Station Freedom electrical power control and scheduling system is designed as a two-level hierarchy. The methodology is compared with rule-based systems and with other more widely-known optimization techniques.

Making Instructional Decisions Based on Data: What, How, and Why

ERIC Educational Resources Information Center

Mokhtari, Kouider; Rosemary, Catherine A.; Edwards, Patricia A.

2007-01-01

A carefully coordinated literacy assessment and instruction framework implemented school-wide can support school teams in making sense of various types of data for instructional planning. Instruction that is data based and goal driven sets the stage for continuous reading and writing improvement. (Contains 2 figures.)

Community College Alchemists: Turning Data into Information.

ERIC Educational Resources Information Center

Johnston, George H.; Kristovich, Sharon A. R.

2000-01-01

Examines how one community college has developed a national Bellwether Award-winning data-driven decision-making process that uses its institutional research staff to make the transition from data to information. Characterizes some of the data and resulting information that might be useful to department chairs. Identifies issues and concerns that…

Data-Driven Decision Making in Out-of-School Time Programs. Part 6 in a Series on Implementing Evidence-Based Practices in Out-of-School Time Programs: The Role of Organization-Level Activities. Research-to-Results Brief. Publication #2009-34

ERIC Educational Resources Information Center

Bandy, Tawana; Burkhauser, Mary; Metz, Allison J. R.

2009-01-01

Although many program managers look to data to inform decision-making and manage their programs, high-quality program data may not always be available. Yet such data are necessary for effective program implementation. The use of high-quality data facilitates program management, reduces reliance on anecdotal information, and ensures that data are…

Role of Science at EPA

EPA Pesticide Factsheets

Decision-making is driven by research with the highest standards for integrity, peer review, transparency, and ethics. Ongoing positive impacts include reducing pollution, improving air quality, defining exposure pathways, and protecting water sources.

Sensorimotor Learning Biases Choice Behavior: A Learning Neural Field Model for Decision Making

PubMed Central

Schöner, Gregor; Gail, Alexander

2012-01-01

According to a prominent view of sensorimotor processing in primates, selection and specification of possible actions are not sequential operations. Rather, a decision for an action emerges from competition between different movement plans, which are specified and selected in parallel. For action choices which are based on ambiguous sensory input, the frontoparietal sensorimotor areas are considered part of the common underlying neural substrate for selection and specification of action. These areas have been shown capable of encoding alternative spatial motor goals in parallel during movement planning, and show signatures of competitive value-based selection among these goals. Since the same network is also involved in learning sensorimotor associations, competitive action selection (decision making) should not only be driven by the sensory evidence and expected reward in favor of either action, but also by the subject's learning history of different sensorimotor associations. Previous computational models of competitive neural decision making used predefined associations between sensory input and corresponding motor output. Such hard-wiring does not allow modeling of how decisions are influenced by sensorimotor learning or by changing reward contingencies. We present a dynamic neural field model which learns arbitrary sensorimotor associations with a reward-driven Hebbian learning algorithm. We show that the model accurately simulates the dynamics of action selection with different reward contingencies, as observed in monkey cortical recordings, and that it correctly predicted the pattern of choice errors in a control experiment. With our adaptive model we demonstrate how network plasticity, which is required for association learning and adaptation to new reward contingencies, can influence choice behavior. The field model provides an integrated and dynamic account for the operations of sensorimotor integration, working memory and action selection required for decision making in ambiguous choice situations. PMID:23166483

City Connects Prompts Data-Driven Action in Community Schools in the Bronx

ERIC Educational Resources Information Center

Haywoode, Alyssa

2018-01-01

Community schools have a long history of helping students succeed in school by addressing the problems they face outside of school. But without specific data on students and the full range of their needs, community schools cannot be as effective as they would like to be. Driven by the desire to make more data-informed decisions, the Children's Aid…

Evaluation of the Performance Driven Budget Initiative of the New York City Board of Education. First Annual Report.

ERIC Educational Resources Information Center

Siegel, Dorothy; Naphtali, Zvia Segal; Fruchter, Norm; Berne, Robert

In 1996 the Chancellor introduced Performance Driven Budgeting (PDB) to the New York City schools. PDB is a form of decentralized budgetary decision making intended to provide local educators with increased control and flexibility over the use of resources. The plan established a framework of goals and principles, outlined a phased-in…

Stop making plans; start making decisions.

PubMed

Mankins, Michael C; Steele, Richard

2006-01-01

Many executives have grown skeptical of strategic planning. Is it any wonder? Despite all the time and energy that go into it, strategic planning most often acts as a barrier to good decision making and does little to influence strategy. Strategic planning fails because of two factors: It typically occurs annually, and it focuses on individual business units. As such, the process is completely at odds with the way executives actually make important strategy decisions, which are neither constrained by the calendar nor defined by unit boundaries. Thus, according to a survey of 156 large companies, senior executives often make strategic decisions outside the planning process, in an ad hoc fashion and without rigorous analysis or productive debate. But companies can fix the process if they attack its root problems. A few forward-looking firms have thrown out their calendar-driven, business-unit-focused planning procedures and replaced them with continuous, issues-focused decision making. In doing so, they rely on several basic principles: They separate, but integrate, decision making and plan making. They focus on a few key themes. And they structure strategy reviews to produce real decisions. When companies change the timing and focus of strategic planning, they also change the nature of senior management's discussions about strategy--from "review and approve" to "debate and decide," in which top executives actively think through every major decision and its implications for the company's performance and value. The authors have found that these companies make more than twice as many important strategic decisions per year as companies that follow the traditional planning model.

Big Data & Learning Analytics: A Potential Way to Optimize eLearning Technological Tools

ERIC Educational Resources Information Center

García, Olga Arranz; Secades, Vidal Alonso

2013-01-01

In the information age, one of the most influential institutions is education. The recent emergence of MOOCS [Massively Open Online Courses] is a sample of the new expectations that are offered to university students. Basing decisions on data and evidence seems obvious, and indeed, research indicates that data-driven decision-making improves…

Charting Success: Data Use and Student Achievement in Urban Schools

ERIC Educational Resources Information Center

Faria, Ann-Marie; Heppen, Jessica; Li, Yibing; Stachel, Suzanne; Jones, Wehmah; Sawyer, Katherine; Thomsen, Kerri; Kutner, Melissa; Miser, David; Lewis, Sharon; Casserly, Michael; Simon, Candace; Uzzell, Renata; Corcoran, Amanda; Palacios, Moses

2012-01-01

In recent years, interest has spiked in data-driven decision making in education--that is, using various types of student data to inform decisions in schools and classrooms. In October 2008, the Council of the Great City Schools and American Institutes for Research (AIR) launched a project funded by The Bill & Melinda Gates Foundation that focused…

The Effect of Career Decisions on Entrepreneurial Intention Levels of University Students Studying Sport Sciences

ERIC Educational Resources Information Center

Yildiz, Kadir

2018-01-01

This study investigates the entrepreneurial intention levels and career decisions of a sample of 340 university students studying sport sciences. Entrepreneurship refers to a career-related choice that is driven by a risk-taking and innovation imperative. Entrepreneurs of the future are expected to make their career related choices well before…

Keeping Teachers in the Center: A Framework of Data-Driven Decision-Making

ERIC Educational Resources Information Center

Light, Daniel; Wexler, Dara H.; Heinze, Juliette

2004-01-01

The Education Development Center's Center for Children and Technology (CCT) conducted a three year study of a large-scale data reporting system, developed by the Grow Network for New York City's Department of Education. This paper presents a framework based on two years of research exploring the intersection of decision-support technologies,…

Clinical and regulatory considerations in pharmacogenetic testing.

PubMed

Schuck, Robert N; Marek, Elizabeth; Rogers, Hobart; Pacanowski, Michael

2016-12-01

Both regulatory science and clinical practice rely on best available scientific data to guide decision-making. However, changes in clinical practice may be driven by numerous other factors such as cost. In this review, we reexamine noteworthy examples where pharmacogenetic testing information was added to drug labeling to explore how the available evidence, potential public health impact, and predictive utility of each pharmacogenetic biomarker impacts clinical uptake. Advances in the field of pharmacogenetics have led to new discoveries about the genetic basis for variability in drug response. The Food and Drug Administration recognizes the value of pharmacogenetic testing strategies and has been proactive about incorporating pharmacogenetic information into the labeling of both new drugs and drugs already on the market. Although some examples have readily translated to routine clinical practice, clinical uptake of genetic testing for many drugs has been limited. Both regulatory science and clinical practice rely on data-driven approaches to guide decision making; however, additional factors are also important in clinical practice that do not impact regulatory decision making, and these considerations may result in heterogeneity in clinical uptake of pharmacogenetic testing. Copyright © 2016 by the American Society of Health-System Pharmacists, Inc. All rights reserved.

HPV vaccine introduction at the local level in a developing country: attitudes and criteria among key actors.

PubMed

Piñeros, Marion; Wiesner, Carolina; Cortés, Claudia; Trujillo, Lina María

2010-05-01

In most developing countries, HPV vaccines have been licensed but there are no national policy recommendations, nor is it clear how decisions on the introduction of this new vaccine are made. Decentralization processes in many Latin American countries favor decision-making at the local level. Through a qualitative study we explored knowledge regarding the HPV vaccine and the criteria that influence decision-making among local health actors in four regions of Colombia. We conducted a total of 14 in-depths interviews with different actors; for the analysis we performed content analysis. Results indicate that decision-making on the HPV vaccine at the local level has mainly been driven by pressure from local political actors, in a setting where there is low technical knowledge of the vaccine. This increases the risk of initiatives that may foster inequity. Local decisions and initiatives need to be strengthened technically and supported by national-level decisions, guidelines and follow-up.

Telehealth: When Technology Meets Health Care

MedlinePlus

... of digital information and communication technologies, such as computers and mobile devices, to access health care services ... your medical history may not be considered. The computer-driven decision-making model may not be optimal ...

The use of control charts by laypeople and hospital decision-makers for guiding decision making.

PubMed

Schmidtke, K A; Watson, D G; Vlaev, I

2017-07-01

Graphs presenting healthcare data are increasingly available to support laypeople and hospital staff's decision making. When making these decisions, hospital staff should consider the role of chance-that is, random variation. Given random variation, decision-makers must distinguish signals (sometimes called special-cause data) from noise (common-cause data). Unfortunately, many graphs do not facilitate the statistical reasoning necessary to make such distinctions. Control charts are a less commonly used type of graph that support statistical thinking by including reference lines that separate data more likely to be signals from those more likely to be noise. The current work demonstrates for whom (laypeople and hospital staff) and when (treatment and investigative decisions) control charts strengthen data-driven decision making. We present two experiments that compare people's use of control and non-control charts to make decisions between hospitals (funnel charts vs. league tables) and to monitor changes across time (run charts with control lines vs. run charts without control lines). As expected, participants more accurately identified the outlying data using a control chart than using a non-control chart, but their ability to then apply that information to more complicated questions (e.g., where should I go for treatment?, and should I investigate?) was limited. The discussion highlights some common concerns about using control charts in hospital settings.

Age-related differences in advantageous decision making are associated with distinct differences in functional community structure.

PubMed

Moussa, Malaak Nasser; Wesley, Michael J; Porrino, Linda J; Hayasaka, Satoru; Bechara, Antoine; Burdette, Jonathan H; Laurienti, Paul J

2014-04-01

Human decision making is dependent on not only the function of several brain regions but also their synergistic interaction. The specific function of brain areas within the ventromedial prefrontal cortex has long been studied in an effort to understand choice evaluation and decision making. These data specifically focus on whole-brain functional interconnectivity using the principles of network science. The Iowa Gambling Task (IGT) was the first neuropsychological task used to model real-life decisions in a way that factors reward, punishment, and uncertainty. Clinically, it has been used to detect decision-making impairments characteristic of patients with prefrontal cortex lesions. Here, we used performance on repeated blocks of the IGT as a behavioral measure of advantageous and disadvantageous decision making in young and mature adults. Both adult groups performed poorly by predominately making disadvantageous selections in the beginning stages of the task. In later phases of the task, young adults shifted to more advantageous selections and outperformed mature adults. Modularity analysis revealed stark underlying differences in visual, sensorimotor and medial prefrontal cortex community structure. In addition, changes in orbitofrontal cortex connectivity predicted behavioral deficits in IGT performance. Contrasts were driven by a difference in age but may also prove relevant to neuropsychiatric disorders associated with poor decision making, including the vulnerability to alcohol and/or drug addiction.

Data-Driven Decision-Making: Data Pioneers

ERIC Educational Resources Information Center

Briggs, Linda L.

2006-01-01

Everyone on your campus needs information, and if your institution is like most schools, you have plenty of it to share. But which types of data warehousing and business intelligence systems you choose, and how accessible, usable, and meaningful those tools make all of that information, remain the big questions for many technologists and…

Social-economical decision making in current and remitted major depression.

PubMed

Pulcu, E; Thomas, E J; Trotter, P D; McFarquhar, M; Juhasz, G; Sahakian, B J; Deakin, J F W; Anderson, I M; Zahn, R; Elliott, R

2015-04-01

Prosocial emotions related to self-blame are important in guiding human altruistic decisions. These emotions are elevated in major depressive disorder (MDD), such that MDD has been associated with guilt-driven pathological hyper-altruism. However, the impact of such emotional impairments in MDD on different types of social decision-making is unknown. In order to address this issue, we investigated different kinds of altruistic behaviour (interpersonal cooperation and fund allocation, altruistic punishment and charitable donation) in 33 healthy subjects, 35 patients in full remission (unmedicated) and 24 currently depressed patients (11 on medication) using behavioural-economical paradigms. We show a significant main effect of clinical status on altruistic decisions (p = 0.04) and a significant interaction between clinical status and type of altruistic decisions (p = 0.03). More specifically, symptomatic patients defected significantly more in the Prisoner's Dilemma game (p < 0.05) and made significantly lower charitable donations, whether or not these incurred a personal cost (p < 0.05 and p < 0.01, respectively). Currently depressed patients also reported significantly higher guilt elicited by receiving unfair financial offers in the Ultimatum Game (p < 0.05). Currently depressed individuals were less altruistic in both a charitable donation and an interpersonal cooperation task. Taken together, our results challenge the guilt-driven pathological hyper-altruism hypothesis in depression. There were also differences in both current and remitted patients in the relationship between altruistic behaviour and pathological self-blaming, suggesting an important role for these emotions in moral and social decision-making abnormalities in depression.

How do we trust strangers? The neural correlates of decision making and outcome evaluation of generalized trust

PubMed Central

Wang, Yiwen; Zhang, Zhen; Jing, Yiming; Valadez, Emilio A.

2016-01-01

This study investigates the brain correlates of decision making and outcome evaluation of generalized trust (i.e. trust in unfamiliar social agents)—a core component of social capital which facilitates civic cooperation and economic exchange. We measured 18 (9 male) Chinese participants’ event-related potentials while they played the role of the trustor in a one-shot trust game with unspecified social agents (trustees) allegedly selected from a large representative sample. At the decision-making phase, greater N2 amplitudes were found for trustors’ distrusting decisions compared to trusting decisions, which may reflect greater cognitive control exerted to distrust. Source localization identified the precentral gyrus as one possible neuronal generator of this N2 component. At the outcome evaluation phase, principal components analysis revealed that the so called feedback-related negativity was in fact driven by a reward positivity, which was greater in response to gain feedback compared to loss feedback. This reduced reward positivity following loss feedback may indicate that the absence of reward for trusting decisions was unexpected by the trustor. In addition, we found preliminary evidence suggesting that the decision-making processes may differ between high trustors and low trustors. PMID:27317927

Comparative analysis of nursing and midwifery regulatory and professional bodies' scope of practice and associated decision-making frameworks: a discussion paper.

PubMed

Kennedy, Catriona; O'Reilly, Pauline; Fealy, Gerard; Casey, Mary; Brady, Anne-Marie; McNamara, Martin; Prizeman, Geraldine; Rohde, Daniela; Hegarty, Josephine

2015-08-01

To review, discuss and compare nursing and midwifery regulatory and professional bodies' scope of practice and associated decision-making frameworks. Scope of practice in professional nursing and midwifery is an evolving process which needs to be responsive to clinical, service, societal, demographic and fiscal changes. Codes and frameworks offer a system of rules and principles by which the nursing and midwifery professions are expected to regulate members and demonstrate responsibility to society. Discussion paper. Twelve scope of practice and associated decision-making frameworks (January 2000-March 2014). Two main approaches to the regulation of the scope of practice and associated decision-making frameworks exist internationally. The first approach is policy and regulation driven and behaviour oriented. The second approach is based on notions of autonomous decision-making, professionalism and accountability. The two approaches are not mutually exclusive, but have similar elements with a different emphasis. Both approaches lack explicit recognition of the aesthetic aspects of care and patient choice, which is a fundamental principle of evidence-based practice. Nursing organizations, regulatory authorities and nurses should recognize that scope of practice and the associated responsibility for decision-making provides a very public statement about the status of nursing in a given jurisdiction. © 2015 John Wiley & Sons Ltd.

The Will and the Way of Data Use.

ERIC Educational Resources Information Center

Alwin, Lance

2002-01-01

Superintendent of Antigo Unified School District, Antigo, Wisconsin, explains the use of school-level and community-level data to build support for bond and budget referenda. Describes the benefits of data-driven decision-making. (PKP)

Central Office Supports for Data-Driven Talent Management Decisions: Evidence from the Implementation of New Systems for Measuring Teacher Effectiveness

ERIC Educational Resources Information Center

Grissom, Jason A.; Rubin, Mollie; Neumerski, Christine M.; Cannata, Marisa; Drake, Timothy A.; Goldring, Ellen; Schuermann, Patrick

2017-01-01

School districts increasingly push school leaders to utilize multiple measures of teacher effectiveness, such as observation ratings or value-added scores, in making talent management decisions, including teacher hiring, assignment, support, and retention, but we know little about the local conditions that promote or impede these processes. We…

Prevention of and Early Intervention for Students with Emotional and Behavioral Disorders: Systems to Support Data-Based Decision Making

ERIC Educational Resources Information Center

Lewis, Timothy J.; Mitchell, Barbara S.

2012-01-01

Students with emotional and behavioral disorders are at great risk for long-term negative outcomes. Researchers and practitioners alike acknowledge the need for evidence-based, preventive, and early intervention strategies. Accordingly, in this chapter an expanded view of prevention is presented as a series of data driven decisions to guide…

Charting Success: Data Use and Student Achievement in Urban Schools. Executive Summary

ERIC Educational Resources Information Center

Faria, Ann-Marie; Heppen, Jessica; Li, Yibing; Stachel, Suzanne; Jones, Wehmah; Sawyer, Katherine; Thomsen, Kerri; Kutner, Melissa; Miser, David; Lewis, Sharon; Casserly, Michael; Simon, Candace; Uzzell, Renata; Corcoran, Amanda; Palacios, Moses

2012-01-01

In recent years, interest has spiked in data-driven decision making in education--that is, using various types of student data to inform decisions in schools and classrooms. In October 2008, the Council of the Great City Schools and American Institutes for Research (AIR) launched a project funded by The Bill & Melinda Gates Foundation that focused…

Making things difficult in lexical decision: the impact of pseudohomophones and transposed-letter nonwords on frequency and semantic priming effects.

PubMed

Lupker, Stephen J; Pexman, Penny M

2010-09-01

Performance in a lexical decision task is crucially dependent on the difficulty of the word-nonword discrimination. More wordlike nonwords cause not only a latency increase for words but also, as reported by Stone and Van Orden (1993), larger word frequency effects. Several current models of lexical decision making can explain these types of results in terms of a single mechanism, a mechanism driven by the nature of the interactions within the lexicon. In 2 experiments, we replicated Stone and Van Orden's increased frequency effect using both pseudohomophones (e.g., BEEST) and transposed-letter nonwords (e.g., JUGDE) as the more wordlike nonwords. In a 3rd experiment, we demonstrated that simply increasing word latencies without changing the difficulty of the word-nonword discrimination does not produce larger frequency effects. These results are reasonably consistent with many current models. In contrast, neither pseudohomophones nor transposed-letter nonwords altered the size of semantic priming effects across 4 additional experiments, posing a challenge to models that would attempt to explain both nonword difficulty effects and semantic priming effects in lexical decision tasks in terms of a single, lexically driven mechanism. (c) 2010 APA, all rights reserved).

Concept of operations for knowledge discovery from Big Data across enterprise data warehouses

NASA Astrophysics Data System (ADS)

Sukumar, Sreenivas R.; Olama, Mohammed M.; McNair, Allen W.; Nutaro, James J.

2013-05-01

The success of data-driven business in government, science, and private industry is driving the need for seamless integration of intra and inter-enterprise data sources to extract knowledge nuggets in the form of correlations, trends, patterns and behaviors previously not discovered due to physical and logical separation of datasets. Today, as volume, velocity, variety and complexity of enterprise data keeps increasing, the next generation analysts are facing several challenges in the knowledge extraction process. Towards addressing these challenges, data-driven organizations that rely on the success of their analysts have to make investment decisions for sustainable data/information systems and knowledge discovery. Options that organizations are considering are newer storage/analysis architectures, better analysis machines, redesigned analysis algorithms, collaborative knowledge management tools, and query builders amongst many others. In this paper, we present a concept of operations for enabling knowledge discovery that data-driven organizations can leverage towards making their investment decisions. We base our recommendations on the experience gained from integrating multi-agency enterprise data warehouses at the Oak Ridge National Laboratory to design the foundation of future knowledge nurturing data-system architectures.

Purchase decision-making is modulated by vestibular stimulation.

PubMed

Preuss, Nora; Mast, Fred W; Hasler, Gregor

2014-01-01

Purchases are driven by consumers' product preferences and price considerations. Using caloric vestibular stimulation (CVS), we investigated the role of vestibular-affective circuits in purchase decision-making. CVS is an effective noninvasive brain stimulation method, which activates vestibular and overlapping emotional circuits (e.g., the insular cortex and the anterior cingulate cortex (ACC)). Subjects were exposed to CVS and sham stimulation while they performed two purchase decision-making tasks. In Experiment 1 subjects had to decide whether to purchase or not. CVS significantly reduced probability of buying a product. In Experiment 2 subjects had to rate desirability of the products and willingness to pay (WTP) while they were exposed to CVS and sham stimulation. CVS modulated desirability of the products but not WTP. The results suggest that CVS interfered with emotional circuits and thus attenuated the pleasant and rewarding effect of acquisition, which in turn reduced purchase probability. The present findings contribute to the rapidly growing literature on the neural basis of purchase decision-making.

Purchase decision-making is modulated by vestibular stimulation

PubMed Central

Preuss, Nora; Mast, Fred W.; Hasler, Gregor

2014-01-01

Purchases are driven by consumers’ product preferences and price considerations. Using caloric vestibular stimulation (CVS), we investigated the role of vestibular-affective circuits in purchase decision-making. CVS is an effective noninvasive brain stimulation method, which activates vestibular and overlapping emotional circuits (e.g., the insular cortex and the anterior cingulate cortex (ACC)). Subjects were exposed to CVS and sham stimulation while they performed two purchase decision-making tasks. In Experiment 1 subjects had to decide whether to purchase or not. CVS significantly reduced probability of buying a product. In Experiment 2 subjects had to rate desirability of the products and willingness to pay (WTP) while they were exposed to CVS and sham stimulation. CVS modulated desirability of the products but not WTP. The results suggest that CVS interfered with emotional circuits and thus attenuated the pleasant and rewarding effect of acquisition, which in turn reduced purchase probability. The present findings contribute to the rapidly growing literature on the neural basis of purchase decision-making. PMID:24600365

Simulation of California's Major Reservoirs Outflow Using Data Mining Technique

NASA Astrophysics Data System (ADS)

Yang, T.; Gao, X.; Sorooshian, S.

2014-12-01

The reservoir's outflow is controlled by reservoir operators, which is different from the upstream inflow. The outflow is more important than the reservoir's inflow for the downstream water users. In order to simulate the complicated reservoir operation and extract the outflow decision making patterns for California's 12 major reservoirs, we build a data-driven, computer-based ("artificial intelligent") reservoir decision making tool, using decision regression and classification tree approach. This is a well-developed statistical and graphical modeling methodology in the field of data mining. A shuffled cross validation approach is also employed to extract the outflow decision making patterns and rules based on the selected decision variables (inflow amount, precipitation, timing, water type year etc.). To show the accuracy of the model, a verification study is carried out comparing the model-generated outflow decisions ("artificial intelligent" decisions) with that made by reservoir operators (human decisions). The simulation results show that the machine-generated outflow decisions are very similar to the real reservoir operators' decisions. This conclusion is based on statistical evaluations using the Nash-Sutcliffe test. The proposed model is able to detect the most influential variables and their weights when the reservoir operators make an outflow decision. While the proposed approach was firstly applied and tested on California's 12 major reservoirs, the method is universally adaptable to other reservoir systems.

Empirically derived guidance for social scientists to influence environmental policy

PubMed Central

Brown, Katrina; Crissman, Charles; De Young, Cassandra; Gooch, Margaret; James, Craig; Jessen, Sabine; Johnson, Dave; Marshall, Paul; Wachenfeld, Dave; Wrigley, Damian

2017-01-01

Failure to stem trends of ecological disruption and associated loss of ecosystem services worldwide is partly due to the inadequate integration of the human dimension into environmental decision-making. Decision-makers need knowledge of the human dimension of resource systems and of the social consequences of decision-making if environmental management is to be effective and adaptive. Social scientists have a central role to play, but little guidance exists to help them influence decision-making processes. We distil 348 years of cumulative experience shared by 31 environmental experts across three continents into advice for social scientists seeking to increase their influence in the environmental policy arena. Results focus on the importance of process, engagement, empathy and acumen and reveal the importance of understanding and actively participating in policy processes through co-producing knowledge and building trust. The insights gained during this research might empower a science-driven cultural change in science-policy relations for the routine integration of the human dimension in environmental decision making; ultimately for an improved outlook for earth’s ecosystems and the billions of people that depend on them. PMID:28278238

Information, Please.

ERIC Educational Resources Information Center

Hardy, Lawrence

2003-01-01

Requirements of the No Child Left Behind Act present school districts with a massive lesson in data-driven decision-making. Technology companies offer data-management tools that organize student information from state tests. Offers districts advice in choosing a technology provider. (MLF)

Building a Data Warehouse.

ERIC Educational Resources Information Center

Levine, Elliott

2002-01-01

Describes how to build a data warehouse, using the Schools Interoperability Framework (www.sifinfo.org), that supports data-driven decision making and complies with the Freedom of Information Act. Provides several suggestions for building and maintaining a data warehouse. (PKP)

Evidence of strategic periodicities in collective conflict dynamics.

PubMed

Dedeo, Simon; Krakauer, David; Flack, Jessica

2011-09-07

We analyse the timescales of conflict decision-making in a primate society. We present evidence for multiple, periodic timescales associated with social decision-making and behavioural patterns. We demonstrate the existence of periodicities that are not directly coupled to environmental cycles or known ultraridian mechanisms. Among specific biological and socially defined demographic classes, periodicities span timescales between hours and days. Our results indicate that these periodicities are not driven by exogenous or internal regularities but are instead driven by strategic responses to social interaction patterns. Analyses also reveal that a class of individuals, playing a critical functional role, policing, have a signature timescale of the order of 1 h. We propose a classification of behavioural timescales analogous to those of the nervous system, with high frequency, or α-scale, behaviour occurring on hour-long scales, through to multi-hour, or β-scale, behaviour, and, finally γ periodicities observed on a timescale of days.

Using Data Mining to Identify Actionable Information: Breaking New Ground in Data-Driven Decision Making

ERIC Educational Resources Information Center

Streifer, Philip A.; Schumann, Jeffrey A.

2005-01-01

The implementation of No Child Left Behind (NCLB) presents important challenges for schools across the nation to identify problems that lead to poor performance. Yet schools must intervene with instructional programs that can make a difference and evaluate the effectiveness of such programs. New advances in artificial intelligence (AI) data-mining…

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.

Decision-making in social contexts in youth with ADHD.

PubMed

Ma, Ili; Lambregts-Rommelse, Nanda N J; Buitelaar, Jan K; Cillessen, Antonius H N; Scheres, Anouk P J

2017-03-01

This study examined reward-related decision-making in children and adolescents with ADHD in a social context, using economic games. We furthermore examined the role of individual differences in reward-related decision-making, specifically, the roles of reward sensitivity and prosocial skills. Children and adolescents (9-17 years) with ADHD-combined subtype (n = 29; 20 boys) and healthy controls (n = 38; 20 boys) completed the ultimatum game and dictator game as measures of reward-related decision-making in social contexts. Prosocial skills were measured with the Interpersonal Reactivity Index. The ADHD group had a larger discrepancy between ultimatum game and dictator game offers than controls, indicating strategic rather than fairness driven decisions. This finding was supported by self-reports showing fewer individuals with ADHD than controls who considered fairness as motive for the decisions. Perspective taking or empathic concern did not differ between groups and was not significantly associated with offers. In conclusion, the results suggest that rather than a failure to understand the perspective of others, children and adolescents with ADHD were less motivated by fairness than controls in simple social situations. Results encourage the use of economic games in ADHD research.

Current understanding of decision-making in adolescents with cancer: A narrative systematic review

PubMed Central

Day, Emma; Jones, Louise; Langner, Richard; Bluebond-Langner, Myra

2016-01-01

Background: Policy guidance and bioethical literature urge the involvement of adolescents in decisions about their healthcare. It is uncertain how roles and expectations of adolescents, parents and healthcare professionals influence decision-making and to what extent this is considered in guidance. Aims: To identify recent empirical research on decision-making regarding care and treatment in adolescent cancer: (1) to synthesise evidence to define the role of adolescents, parents and healthcare professionals in the decision-making process and (2) to identify gaps in research. Design: A narrative systematic review of qualitative, quantitative and mixed-methods research. We adopted a textual approach to synthesis, using a theoretical framework of interactionism to interpret findings. Data Sources: The databases MEDLINE, PsycINFO, SCOPUS, EMBASE and CINHAL were searched from 2001 through May 2015 for publications on decision-making for adolescents (13–19 years) with cancer. Results: Twenty-eight articles were identified. Adolescents and parents initially find it difficult to participate in decision-making due to a lack of options in the face of protocol-driven care. Parent and adolescent preferences for information and response to loss of control vary between individuals and over time. No studies indicate parental or adolescent preference for a high degree of independence in decision-making. Conclusion: Striving to make parents and adolescents fully informed or urge them towards more independence than they prefer may add to distress and confusion. This may interfere with their ability to participate in their preferred way in decisions about care and treatment. Future research should include analysis of on-ground interactions among parents, adolescents and clinicians across the trajectory. PMID:27160700

Attention as foraging for information and value

PubMed Central

Manohar, Sanjay G.; Husain, Masud

2013-01-01

What is the purpose of attention? One avenue of research has led to the proposal that attention might be crucial for gathering information about the environment, while other lines of study have demonstrated how attention may play a role in guiding behavior to rewarded options. Many experiments that study attention require participants to make a decision based on information acquired discretely at one point in time. In real-world situations, however, we are usually not presented with information about which option to select in such a manner. Rather we must initially search for information, weighing up reward values of options before we commit to a decision. Here, we propose that attention plays a role in both foraging for information and foraging for value. When foraging for information, attention is guided toward the unknown. When foraging for reward, attention is guided toward high reward values, allowing decision-making to proceed by accept-or-reject decisions on the currently attended option. According to this account, attention can be regarded as a low-cost alternative to moving around and physically interacting with the environment—“teleforaging”—before a decision is made to interact physically with the world. To track the timecourse of attention, we asked participants to seek out and acquire information about two gambles by directing their gaze, before choosing one of them. Participants often made multiple refixations on items before making a decision. Their eye movements revealed that early in the trial, attention was guided toward information, i.e., toward locations that reduced uncertainty about value. In contrast, late in the trial, attention was guided by expected value of the options. At the end of the decision period, participants were generally attending to the item they eventually chose. We suggest that attentional foraging shifts from an uncertainty-driven to a reward-driven mode during the evolution of a decision, permitting decisions to be made by an engage-or-search strategy. PMID:24204335

A unified framework for addiction: Vulnerabilities in the decision process

PubMed Central

Redish, A. David; Jensen, Steve; Johnson, Adam

2013-01-01

The understanding of decision-making systems has come together in recent years to form a unified theory of decision-making in the mammalian brain as arising from multiple, interacting systems (a planning system, a habit system, and a situation-recognition system). This unified decision-making system has multiple potential access points through which it can be driven to make maladaptive choices, particularly choices that entail seeking of certain drugs or behaviors. We identify 10 key vulnerabilities in the system: (1) moving away from homeostasis, (2) changing allostatic set points, (3) euphorigenic “reward-like” signals, (4) overvaluation in the planning system, (5) incorrect search of situation-action-outcome relationships, (6) misclassification of situations, (7) overvaluation in the habit system, (8) a mismatch in the balance of the two decision systems, (9) over-fast discounting processes, and (10) changed learning rates. These vulnerabilities provide a taxonomy of potential problems with decision-making systems. Although each vulnerability can drive an agent to return to the addictive choice, each vulnerability also implies a characteristic symptomology. Different drugs, different behaviors, and different individuals are likely to access different vulnerabilities. This has implications for an individual’s susceptibility to addiction and the transition to addiction, for the potential for relapse, and for the potential for treatment. PMID:18662461

Fronting Integrated Scientific Web Applications: Design Features and Benefits for Regulatory Environments

EPA Science Inventory

Integrated decision support systems for regulatory applications benefit from standardindustry practices such as code reuse, test-driven development, and modularization. Theseapproaches make meeting the federal government’s goals of transparency, efficiency, and quality assurance ...

The value of artefacts in stimulated-recall interviews.

PubMed

Burden, Sarah; Topping, Annie; O'Halloran, Catherine

2015-09-01

To assess the use of artefacts in semi-structured, stimulated-recall interviews in a study exploring mentors' decisions regarding students' competence in practice. Few empirical studies have examined how mentors reach a decision when assessing students' performance in practice. Concerns have repeatedly been voiced that students may lack essential skills at the point of registration or that mentors may have failed or been reticent to judge students' performance as unsatisfactory. Student practice assessment documents (PADs) were used in stimulated-recall (SR) interviews with mentors to explore decision making. A review of the literature identified that artefacts can play a role in triggering a more comprehensive retrospective examination of decision making, thus helping to capture the essence of a mentor's decision over time and in context. Use of an artefact to stimulate recall can elicit evidence of thought processes, which may be difficult to obtain in a normal, semi-structured interview. PADs proved to be a valuable way to generate naturalistic decision making. In addition, discussion of artefacts created by participants can promote participant-driven enquiry, thereby reducing researcher bias. Identifying an approach that captures post hoc decision making based on sustained engagement and interaction between students and their mentors was a challenge. Artefacts can be used to address the difficulties associated with retrospective introspection about a unique decision. There is the potential to increase the use of artefacts in healthcare research. SR can also help novice mentors develop their skills in making decisions regarding assessments of students.

Psychopathic individuals exhibit but do not avoid regret during counterfactual decision making.

PubMed

Baskin-Sommers, Arielle; Stuppy-Sullivan, Allison M; Buckholtz, Joshua W

2016-12-13

Psychopathy is associated with persistent antisocial behavior and a striking lack of regret for the consequences of that behavior. Although explanatory models for psychopathy have largely focused on deficits in affective responsiveness, recent work indicates that aberrant value-based decision making may also play a role. On that basis, some have suggested that psychopathic individuals may be unable to effectively use prospective simulations to update action value estimates during cost-benefit decision making. However, the specific mechanisms linking valuation, affective deficits, and maladaptive decision making in psychopathy remain unclear. Using a counterfactual decision-making paradigm, we found that individuals who scored high on a measure of psychopathy were as or more likely than individuals low on psychopathy to report negative affect in response to regret-inducing counterfactual outcomes. However, despite exhibiting intact affective regret sensitivity, they did not use prospective regret signals to guide choice behavior. In turn, diminished behavioral regret sensitivity predicted a higher number of prior incarcerations, and moderated the relationship between psychopathy and incarceration history. These findings raise the possibility that maladaptive decision making in psychopathic individuals is not a consequence of their inability to generate or experience negative emotions. Rather, antisocial behavior in psychopathy may be driven by a deficit in the generation of forward models that integrate information about rules, costs, and goals with stimulus value representations to promote adaptive behavior.

Psychopathic individuals exhibit but do not avoid regret during counterfactual decision making

PubMed Central

Baskin-Sommers, Arielle; Stuppy-Sullivan, Allison M.; Buckholtz, Joshua W.

2016-01-01

Psychopathy is associated with persistent antisocial behavior and a striking lack of regret for the consequences of that behavior. Although explanatory models for psychopathy have largely focused on deficits in affective responsiveness, recent work indicates that aberrant value-based decision making may also play a role. On that basis, some have suggested that psychopathic individuals may be unable to effectively use prospective simulations to update action value estimates during cost–benefit decision making. However, the specific mechanisms linking valuation, affective deficits, and maladaptive decision making in psychopathy remain unclear. Using a counterfactual decision-making paradigm, we found that individuals who scored high on a measure of psychopathy were as or more likely than individuals low on psychopathy to report negative affect in response to regret-inducing counterfactual outcomes. However, despite exhibiting intact affective regret sensitivity, they did not use prospective regret signals to guide choice behavior. In turn, diminished behavioral regret sensitivity predicted a higher number of prior incarcerations, and moderated the relationship between psychopathy and incarceration history. These findings raise the possibility that maladaptive decision making in psychopathic individuals is not a consequence of their inability to generate or experience negative emotions. Rather, antisocial behavior in psychopathy may be driven by a deficit in the generation of forward models that integrate information about rules, costs, and goals with stimulus value representations to promote adaptive behavior. PMID:27911790

Getting Started with Data Warehousing: The First in a Series on How to Manage Data Efficiently

ERIC Educational Resources Information Center

Mills, Lane B.

2008-01-01

These days, "data-driven decision making" is on every school district's buzzword bingo game board. Accountability pressures and lean budgets make translating data into information a major focus of school systems that are trying to improve district outcomes in all areas. As such, data warehousing has become an essential district tool. Historically…

A Conceptual Analytics Model for an Outcome-Driven Quality Management Framework as Part of Professional Healthcare Education.

PubMed

Hervatis, Vasilis; Loe, Alan; Barman, Linda; O'Donoghue, John; Zary, Nabil

2015-10-06

Preparing the future health care professional workforce in a changing world is a significant undertaking. Educators and other decision makers look to evidence-based knowledge to improve quality of education. Analytics, the use of data to generate insights and support decisions, have been applied successfully across numerous application domains. Health care professional education is one area where great potential is yet to be realized. Previous research of Academic and Learning analytics has mainly focused on technical issues. The focus of this study relates to its practical implementation in the setting of health care education. The aim of this study is to create a conceptual model for a deeper understanding of the synthesizing process, and transforming data into information to support educators' decision making. A deductive case study approach was applied to develop the conceptual model. The analytics loop works both in theory and in practice. The conceptual model encompasses the underlying data, the quality indicators, and decision support for educators. The model illustrates how a theory can be applied to a traditional data-driven analytics approach, and alongside the context- or need-driven analytics approach.

A Conceptual Analytics Model for an Outcome-Driven Quality Management Framework as Part of Professional Healthcare Education

PubMed Central

Loe, Alan; Barman, Linda; O'Donoghue, John; Zary, Nabil

2015-01-01

Background Preparing the future health care professional workforce in a changing world is a significant undertaking. Educators and other decision makers look to evidence-based knowledge to improve quality of education. Analytics, the use of data to generate insights and support decisions, have been applied successfully across numerous application domains. Health care professional education is one area where great potential is yet to be realized. Previous research of Academic and Learning analytics has mainly focused on technical issues. The focus of this study relates to its practical implementation in the setting of health care education. Objective The aim of this study is to create a conceptual model for a deeper understanding of the synthesizing process, and transforming data into information to support educators’ decision making. Methods A deductive case study approach was applied to develop the conceptual model. Results The analytics loop works both in theory and in practice. The conceptual model encompasses the underlying data, the quality indicators, and decision support for educators. Conclusions The model illustrates how a theory can be applied to a traditional data-driven analytics approach, and alongside the context- or need-driven analytics approach. PMID:27731840

Value-driven ERM: making ERM an engine for simultaneous value creation and value protection.

PubMed

Celona, John; Driver, Jeffrey; Hall, Edward

2011-01-01

Enterprise risk management (ERM) began as an effort to integrate the historically disparate silos of risk management in organizations. More recently, as recognition has grown of the need to cover the upside risks in value creation (financial and otherwise), organizations and practitioners have been searching for the means to do this. Existing tools such as heat maps and risk registers are not adequate for this task. Instead, a conceptually new value-driven framework is needed to realize the promise of enterprise-wide coverage of all risks, for both value protection and value creation. The methodology of decision analysis provides the means of capturing systemic, correlated, and value-creation risks on the same basis as value protection risks and has been integrated into the value-driven approach to ERM described in this article. Stanford Hospital and Clinics Risk Consulting and Strategic Decisions Group have been working to apply this value-driven ERM at Stanford University Medical Center. © 2011 American Society for Healthcare Risk Management of the American Hospital Association.

Informed Decision Making: Assessment of the Quality of Physician Communication about Prostate Cancer Diagnosis and Treatment.

PubMed

Holmes-Rovner, Margaret; Montgomery, Jeffrey S; Rovner, David R; Scherer, Laura D; Whitfield, Jesse; Kahn, Valerie C; Merkle, Edgar C; Ubel, Peter A; Fagerlin, Angela

2015-11-01

Little is known about how physicians present diagnosis and treatment planning in routine practice in preference-sensitive treatment decisions. We evaluated completeness and quality of informed decision making in localized prostate cancer post biopsy encounters. We analyzed audio-recorded office visits of 252 men with presumed localized prostate cancer (Gleason 6 and Gleason 7 scores) who were seeing 45 physicians at 4 Veterans Affairs Medical Centers. Data were collected between September 2008 and May 2012 in a trial of 2 decision aids (DAs). Braddock's previously validated Informed Decision Making (IDM) system was used to measure quality. Latent variable models for ordinal data examined the relationship of IDM score to treatment received. Mean IDM score showed modest quality (7.61±2.45 out of 18) and high variability. Treatment choice and risks and benefits were discussed in approximately 95% of encounters. However, in more than one-third of encounters, physicians provided a partial set of treatment options and omitted surveillance as a choice. Informing quality was greater in patients treated with surveillance (β = 1.1, p = .04). Gleason score (7 vs 6) and lower age were often cited as reasons to exclude surveillance. Patient preferences were elicited in the majority of cases, but not used to guide treatment planning. Encounter time was modestly correlated with IDM score (r = 0.237, p = .01). DA type was not associated with IDM score. Physicians informed patients of options and risks and benefits, but infrequently engaged patients in core shared decision-making processes. Despite patients having received DAs, physicians rarely provided an opportunity for preference-driven decision making. More attention to the underused patient decision-making and engagement elements could result in improved shared decision making. © The Author(s) 2015.

Evolution of Patient Decision-Making Regarding Medical Treatment of Rheumatoid Arthritis.

PubMed

Mathews, Alexandra L; Coleska, Adriana; Burns, Patricia B; Chung, Kevin C

2016-03-01

The migration of health care toward a consumer-driven system favors increased patient participation during the treatment decision-making process. Patient involvement in treatment decision discussions has been linked to increased treatment adherence and patient satisfaction. Previous studies have quantified decision-making styles of patients with rheumatoid arthritis (RA); however, none of them have considered the evolution of patient involvement after living with RA for many years. We conducted a qualitative study to determine the decision-making model used by long-term RA patients, and to describe the changes in their involvement over time. Twenty participants were recruited from the ongoing Silicone Arthroplasty in Rheumatoid Arthritis study. Semistructured interviews were conducted and data were analyzed using grounded theory methodology. Nineteen out of 20 participants recalled using the paternalistic decision-making (PDM) model immediately following their diagnosis. Fourteen of the 19 participants who initially used PDM evolved to shared decision-making (SDM). Participants attributed the change in involvement to the development of a trusting relationship with their physician, as well as to becoming educated about the disease. When initially diagnosed with RA, patients may let their physician decide on the best treatment course. However, over time patients may evolve to exercise a more collaborative role. Physicians should understand that even within SDM, each patient can demonstrate a varied amount of autonomy. It is up to the physician to have a discussion with each patient to determine his or her desired level of involvement. © 2016, American College of Rheumatology.

Goal driven kinematic simulation of flexible arm robot for space station missions

NASA Technical Reports Server (NTRS)

Janssen, P.; Choudry, A.

1987-01-01

Flexible arms offer a great degree of flexibility in maneuvering in the space environment. The problem of transporting an astronaut for extra-vehicular activity using a space station based flexible arm robot was studied. Inverse kinematic solutions of the multilink structure were developed. The technique is goal driven and can support decision making for configuration selection as required for stability and obstacle avoidance. Details of this technique and results are given.

Health and Retirement: Do Changes in Health Affect Retirement Expectations?

ERIC Educational Resources Information Center

McGarry, Kathleen

2004-01-01

Health plays a vital role in the decision making process of retirement for an employee. The changes in retirement expectations are driven to a much greater degree by change in health rather than change in income or wealth.

Integrating Information & Communications Technologies into the Classroom

ERIC Educational Resources Information Center

Tomei, Lawrence, Ed.

2007-01-01

"Integrating Information & Communications Technologies Into the Classroom" examines topics critical to business, computer science, and information technology education, such as: school improvement and reform, standards-based technology education programs, data-driven decision making, and strategic technology education planning. This book also…

Troubleshooting Portfolios

ERIC Educational Resources Information Center

Crismond, David; Peterie, Matthew

2017-01-01

The Troubleshooting Portfolios approach was developed at the Olathe Northwest High School in Olathe, Kansas. This approach supports integrated STEM and "informed design" thinking and learning, in which students: (1) use design strategies effectively; (2) work creatively and collaboratively in teams; (3) make knowledge-driven decisions;…

Building an Evidence-Driven Child Welfare Workforce: A University–Agency Partnership

PubMed Central

Lery, Bridgette; Wiegmann, Wendy; Berrick, Jill Duerr

2016-01-01

The federal government increasingly expects child welfare systems to be more responsive to the needs of their local populations, connect strategies to results, and use continuous quality improvement (CQI) to accomplish these goals. A method for improving decision making, CQI relies on an inflow of high-quality data, up-to-date research evidence, and a robust organizational structure and climate that supports the deliberate use of evidence for decision making. This article describes an effort to build and support these essential system components through one public-private child welfare agency–university partnership. PMID:27429534

From Population Databases to Research and Informed Health Decisions and Policy.

PubMed

Machluf, Yossy; Tal, Orna; Navon, Amir; Chaiter, Yoram

2017-01-01

In the era of big data, the medical community is inspired to maximize the utilization and processing of the rapidly expanding medical datasets for clinical-related and policy-driven research. This requires a medical database that can be aggregated, interpreted, and integrated at both the individual and population levels. Policymakers seek data as a lever for wise, evidence-based decision-making and information-driven policy. Yet, bridging the gap between data collection, research, and policymaking, is a major challenge. To bridge this gap, we propose a four-step model: (A) creating a conjoined task force of all relevant parties to declare a national program to promote collaborations; (B) promoting a national digital records project, or at least a network of synchronized and integrated databases, in an accessible transparent manner; (C) creating an interoperative national research environment to enable the analysis of the organized and integrated data and to generate evidence; and (D) utilizing the evidence to improve decision-making, to support a wisely chosen national policy. For the latter purpose, we also developed a novel multidimensional set of criteria to illuminate insights and estimate the risk for future morbidity based on current medical conditions. Used by policymakers, providers of health plans, caregivers, and health organizations, we presume this model will assist transforming evidence generation to support the design of health policy and programs, as well as improved decision-making about health and health care, at all levels: individual, communal, organizational, and national.

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

PubMed

Djulbegovic, Benjamin; Elqayam, Shira

2017-10-01

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

Neural signatures of experience-based improvements in deterministic decision-making.

PubMed

Tremel, Joshua J; Laurent, Patryk A; Wolk, David A; Wheeler, Mark E; Fiez, Julie A

2016-12-15

Feedback about our choices is a crucial part of how we gather information and learn from our environment. It provides key information about decision experiences that can be used to optimize future choices. However, our understanding of the processes through which feedback translates into improved decision-making is lacking. Using neuroimaging (fMRI) and cognitive models of decision-making and learning, we examined the influence of feedback on multiple aspects of decision processes across learning. Subjects learned correct choices to a set of 50 word pairs across eight repetitions of a concurrent discrimination task. Behavioral measures were then analyzed with both a drift-diffusion model and a reinforcement learning model. Parameter values from each were then used as fMRI regressors to identify regions whose activity fluctuates with specific cognitive processes described by the models. The patterns of intersecting neural effects across models support two main inferences about the influence of feedback on decision-making. First, frontal, anterior insular, fusiform, and caudate nucleus regions behave like performance monitors, reflecting errors in performance predictions that signal the need for changes in control over decision-making. Second, temporoparietal, supplementary motor, and putamen regions behave like mnemonic storage sites, reflecting differences in learned item values that inform optimal decision choices. As information about optimal choices is accrued, these neural systems dynamically adjust, likely shifting the burden of decision processing from controlled performance monitoring to bottom-up, stimulus-driven choice selection. Collectively, the results provide a detailed perspective on the fundamental ability to use past experiences to improve future decisions. Copyright © 2016 Elsevier B.V. All rights reserved.

Neural signatures of experience-based improvements in deterministic decision-making

PubMed Central

Tremel, Joshua J.; Laurent, Patryk A.; Wolk, David A.; Wheeler, Mark E.; Fiez, Julie A.

2016-01-01

Feedback about our choices is a crucial part of how we gather information and learn from our environment. It provides key information about decision experiences that can be used to optimize future choices. However, our understanding of the processes through which feedback translates into improved decision-making is lacking. Using neuroimaging (fMRI) and cognitive models of decision-making and learning, we examined the influence of feedback on multiple aspects of decision processes across learning. Subjects learned correct choices to a set of 50 word pairs across eight repetitions of a concurrent discrimination task. Behavioral measures were then analyzed with both a drift-diffusion model and a reinforcement learning model. Parameter values from each were then used as fMRI regressors to identify regions whose activity fluctuates with specific cognitive processes described by the models. The patterns of intersecting neural effects across models support two main inferences about the influence of feedback on decision-making. First, frontal, anterior insular, fusiform, and caudate nucleus regions behave like performance monitors, reflecting errors in performance predictions that signal the need for changes in control over decision-making. Second, temporoparietal, supplementary motor, and putamen regions behave like mnemonic storage sites, reflecting differences in learned item values that inform optimal decision choices. As information about optimal choices is accrued, these neural systems dynamically adjust, likely shifting the burden of decision processing from controlled performance monitoring to bottom-up, stimulus-driven choice selection. Collectively, the results provide a detailed perspective on the fundamental ability to use past experiences to improve future decisions. PMID:27523644

Decisions and desire.

PubMed

Morse, Gardiner

2006-01-01

When we make decisions, we're not always in charge. One moment we hotheadedly let our emotions get the better of us; the next, we're paralyzed by uncertainty. Then we'll pull a brilliant decision out of thin air--and wonder how we did it. Though we may have no idea how decision making happens, neuroscientists peering deep into our brains are beginning to get the picture. What they're finding may not be what you want to hear, but it's worth listening. We have dog brains, basically, with human cortexes stuck on top. By watching the brain in action as it deliberates and decides, neuroscientists are finding that not a second goes by that our animal brains aren't conferring with our modern cortexes to influence their choices. Scientists have discovered, for example, that the "reward" circuits in the brain that activate in response to cocaine, chocolate, sex, and music also find pleasure in the mere anticipation of making money--or getting revenge. And the "aversion" circuits that react to the threat of physical pain also respond with disgust when we feel cheated by a partner. In this article, HBR senior editor Gardiner Morse describes the experiments that illuminate the aggressive participation of our emotion-driven animal brains in decision making. This research also shows that our emotional brains needn't always operate beneath our radar. While our dog brains sometimes hijack our higher cognitive functions to drive bad, or at least illogical, decisions, they play an important part in rational decision making as well. The more we understand about how we make decisions, the better we can manage them.

Concept of Operations for Collaboration and Discovery from Big Data Across Enterprise Data Warehouses

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

Olama, Mohammed M; Nutaro, James J; Sukumar, Sreenivas R

2013-01-01

The success of data-driven business in government, science, and private industry is driving the need for seamless integration of intra and inter-enterprise data sources to extract knowledge nuggets in the form of correlations, trends, patterns and behaviors previously not discovered due to physical and logical separation of datasets. Today, as volume, velocity, variety and complexity of enterprise data keeps increasing, the next generation analysts are facing several challenges in the knowledge extraction process. Towards addressing these challenges, data-driven organizations that rely on the success of their analysts have to make investment decisions for sustainable data/information systems and knowledge discovery. Optionsmore » that organizations are considering are newer storage/analysis architectures, better analysis machines, redesigned analysis algorithms, collaborative knowledge management tools, and query builders amongst many others. In this paper, we present a concept of operations for enabling knowledge discovery that data-driven organizations can leverage towards making their investment decisions. We base our recommendations on the experience gained from integrating multi-agency enterprise data warehouses at the Oak Ridge National Laboratory to design the foundation of future knowledge nurturing data-system architectures.« less

A cross-cultural study of noblesse oblige in economic decision-making.

PubMed

Fiddick, Laurence; Cummins, Denise Dellarosa; Janicki, Maria; Lee, Sean; Erlich, Nicole

2013-09-01

A cornerstone of economic theory is that rational agents are self-interested, yet a decade of research in experimental economics has shown that economic decisions are frequently driven by concerns for fairness, equity, and reciprocity. One aspect of other-regarding behavior that has garnered attention is noblesse oblige, a social norm that obligates those of higher status to be generous in their dealings with those of lower status. The results of a cross-cultural study are reported in which marked noblesse oblige was observed on a reciprocal-contract decision-making task. Participants from seven countries that vary along hierarchical and individualist/collectivist social dimensions were more tolerant of non-reciprocation when they adopted a high-ranking perspective compared with a low-ranking perspective.

Graphics to facilitate informative discussion and team decision making

DOE PAGES

Anderson-Cook, Christine M.; Lu, Lu

2018-03-25

Everyone knows the expression “A picture is worth a thousand words,” and this effectively summarizes the ability of graphical summaries to convey information and persuade. However, in many cases, the goal for the right visualization is to encourage and guide discussion while helping focus a team to make carefully considered, defensible, and data-driven decisions. The aims of graphics differ if we are trying to communicate the merits of a single choice versus outlining several contending alternatives for further comparison and discussion. These choices each have their own strengths and weaknesses depending on how we value different criteria. They also servemore » different purposes at various stages of decision making. Often the role of statisticians is not to provide a single answer but to provide rich information and summaries in a manageable and compact form to enable productive discussion among team members. Through a series of diverse examples, this work present principles and strategies for encouraging discussion and informed decision making and discuss how they can be integrated with versatile use of graphical tools for examining multiple objectives, framing trade-offs between alternatives, and examining the impact of subjective priorities and uncertainty on the final decision.« less

Graphics to facilitate informative discussion and team decision making

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

Anderson-Cook, Christine M.; Lu, Lu

Everyone knows the expression “A picture is worth a thousand words,” and this effectively summarizes the ability of graphical summaries to convey information and persuade. However, in many cases, the goal for the right visualization is to encourage and guide discussion while helping focus a team to make carefully considered, defensible, and data-driven decisions. The aims of graphics differ if we are trying to communicate the merits of a single choice versus outlining several contending alternatives for further comparison and discussion. These choices each have their own strengths and weaknesses depending on how we value different criteria. They also servemore » different purposes at various stages of decision making. Often the role of statisticians is not to provide a single answer but to provide rich information and summaries in a manageable and compact form to enable productive discussion among team members. Through a series of diverse examples, this work present principles and strategies for encouraging discussion and informed decision making and discuss how they can be integrated with versatile use of graphical tools for examining multiple objectives, framing trade-offs between alternatives, and examining the impact of subjective priorities and uncertainty on the final decision.« less

Data Analysis and Data-Driven Decision-Making Strategies Implemented by Elementary Teachers in Selected Exited Program Improvement Safe Harbor Schools in Southern California

ERIC Educational Resources Information Center

Senger, Karen

2012-01-01

Purpose: The purposes of this study were to investigate and describe how elementary teachers in exited Program Improvement-Safe Harbor schools acquire student achievement data through assessments, the strategies and reflections utilized to make sense of the data to improve student achievement, ensure curriculum and instructional goals are aligned,…

Dynamics of Entropy in Quantum-like Model of Decision Making

NASA Astrophysics Data System (ADS)

Basieva, Irina; Khrennikov, Andrei; Asano, Masanari; Ohya, Masanori; Tanaka, Yoshiharu

2011-03-01

We present a quantum-like model of decision making in games of the Prisoner's Dilemma type. By this model the brain processes information by using representation of mental states in complex Hilbert space. Driven by the master equation the mental state of a player, say Alice, approaches an equilibrium point in the space of density matrices. By using this equilibrium point Alice determines her mixed (i.e., probabilistic) strategy with respect to Bob. Thus our model is a model of thinking through decoherence of initially pure mental state. Decoherence is induced by interaction with memory and external environment. In this paper we study (numerically) dynamics of quantum entropy of Alice's state in the process of decision making. Our analysis demonstrates that this dynamics depends nontrivially on the initial state of Alice's mind on her own actions and her prediction state (for possible actions of Bob.)

Effective crisis decision-making.

PubMed

Kaschner, Holger

2017-01-01

When an organisation's reputation is at stake, crisis decision-making (CDM) is challenging and prone to failure. Most CDM schemes are strong at certain aspects of the overall CDM process, but almost none are strong at all of them. This paper defines criteria for good CDM schemes, analyses common approaches and introduces an alternative, stakeholder-driven scheme. Focusing on the most important stakeholders and directing any actions to preserve the relationships with them is crucial. When doing so, the interdependencies between the stakeholders must be identified and considered. Without knowledge of the sometimes less than obvious links, wellmeaning actions can cause adverse effects, so a cross-check for the impacts of potential options is recommended before making the final decision. The paper also gives recommendations on how to implement these steps at any organisation in order to enhance the quality of CDM and thus protect the organisation's reputation.

Normalization is a general neural mechanism for context-dependent decision making

PubMed Central

Louie, Kenway; Khaw, Mel W.; Glimcher, Paul W.

2013-01-01

Understanding the neural code is critical to linking brain and behavior. In sensory systems, divisive normalization seems to be a canonical neural computation, observed in areas ranging from retina to cortex and mediating processes including contrast adaptation, surround suppression, visual attention, and multisensory integration. Recent electrophysiological studies have extended these insights beyond the sensory domain, demonstrating an analogous algorithm for the value signals that guide decision making, but the effects of normalization on choice behavior are unknown. Here, we show that choice models using normalization generate significant (and classically irrational) choice phenomena driven by either the value or number of alternative options. In value-guided choice experiments, both monkey and human choosers show novel context-dependent behavior consistent with normalization. These findings suggest that the neural mechanism of value coding critically influences stochastic choice behavior and provide a generalizable quantitative framework for examining context effects in decision making. PMID:23530203

Distinct effects of prefrontal and parietal cortex inactivations on an accumulation of evidence task in the rat

PubMed Central

Erlich, Jeffrey C; Brunton, Bingni W; Duan, Chunyu A; Hanks, Timothy D; Brody, Carlos D

2015-01-01

Numerous brain regions have been shown to have neural correlates of gradually accumulating evidence for decision-making, but the causal roles of these regions in decisions driven by accumulation of evidence have yet to be determined. Here, in rats performing an auditory evidence accumulation task, we inactivated the frontal orienting fields (FOF) and posterior parietal cortex (PPC), two rat cortical regions that have neural correlates of accumulating evidence and that have been proposed as central to decision-making. We used a detailed model of the decision process to analyze the effect of inactivations. Inactivation of the FOF induced substantial performance impairments that were quantitatively best described as an impairment in the output pathway of an evidence accumulator with a long integration time constant (>240 ms). In contrast, we found a minimal role for PPC in decisions guided by accumulating auditory evidence, even while finding a strong role for PPC in internally-guided decisions. DOI: http://dx.doi.org/10.7554/eLife.05457.001 PMID:25869470

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.

ARL and Association 3.0: Ten Management Challenges

ERIC Educational Resources Information Center

Funk, Carla J.

2009-01-01

Association management in today's "association 3.0" environment presents some new challenges and new perspectives on old ones. This paper summarizes 10 such challenges including collaboration, diversity, innovation, transparency, financial stability, member benefits, knowledge-based decision-making, a demand-driven association model, pro-activity…

Stream traffic data archival, querying, and analysis with TransDec.

DOT National Transportation Integrated Search

2011-01-01

The goal of research was to extend the traffic data analysis of the TransDec (short for : Transportation Decision-Making) system, which was developed under METRANS 09-26 : research grant. The TransDec system is a real-data driven system to support de...

Local data will help Michigan make better safety investment decisions : research spotlight.

DOT National Transportation Integrated Search

2016-07-01

MDOT staff are aiming to use data-driven processes and practices from the AASHTO Highway Safety Manual (HSM) to estimate the safety impacts of various crash reduction strategies and highway design alternatives, such as adding a median or varying the ...

Knowledge Management and the Academy

ERIC Educational Resources Information Center

Cain, Timothy J.; Branin, Joseph J.; Sherman, W. Michael

2008-01-01

Universities and colleges generate extraordinary quantities of knowledge and innovation, but in many ways the academy struggles to keep pace with the digital revolution. Growing pressures are reshaping how universities must do business--students expecting enhanced access and support, administrators eager to make data-driven strategic decisions,…

Knowledge management in healthcare: towards 'knowledge-driven' decision-support services.

PubMed

Abidi, S S

2001-09-01

In this paper, we highlight the involvement of Knowledge Management in a healthcare enterprise. We argue that the 'knowledge quotient' of a healthcare enterprise can be enhanced by procuring diverse facets of knowledge from the seemingly placid healthcare data repositories, and subsequently operationalising the procured knowledge to derive a suite of Strategic Healthcare Decision-Support Services that can impact strategic decision-making, planning and management of the healthcare enterprise. In this paper, we firstly present a reference Knowledge Management environment-a Healthcare Enterprise Memory-with the functionality to acquire, share and operationalise the various modalities of healthcare knowledge. Next, we present the functional and architectural specification of a Strategic Healthcare Decision-Support Services Info-structure, which effectuates a synergy between knowledge procurement (vis-à-vis Data Mining) and knowledge operationalisation (vis-à-vis Knowledge Management) techniques to generate a suite of strategic knowledge-driven decision-support services. In conclusion, we argue that the proposed Healthcare Enterprise Memory is an attempt to rethink the possible sources of leverage to improve healthcare delivery, hereby providing a valuable strategic planning and management resource to healthcare policy makers.

Using Data to Promote Equity

ERIC Educational Resources Information Center

Shum, Brenda

2016-01-01

Data plays a starring role in promoting educational equity, and data-driven decision making begins with good state policies. With the recent passage of the Every Student Succeeds Act (ESSA) and a proposed federal rule to address racial disproportionality in special education, states will shoulder increased responsibility for eliminating…

Role of ideas and ideologies in evidence-based health policy.

PubMed

Prinja, S

2010-01-01

Policy making in health is largely thought to be driven by three 'I's namely ideas, interests and institutions. Recent years have seen a shift in approach with increasing reliance being placed on role of evidence for policy making. The present article ascertains the role of ideas and ideologies in shaping evidence which is used to aid in policy decisions. The article discusses different theories of research-policy interface and the relative freedom of research-based evidence from the influence of ideas. Examples from developed and developed countries are cited to illustrate the contentions made. The article highlights the complexity of the process of evidence-based policy making, in a world driven by existing political, social and cultural ideologies. Consideration of this knowledge is paramount where more efforts are being made to bridge the gap between the 'two worlds' of researchers and policy makers to make evidence-based policy as also for policy analysts.

Technology Infusion Challenges from a Decision Support Perspective

NASA Technical Reports Server (NTRS)

Adumitroaie, V.; Weisbin, C. R.

2009-01-01

In a restricted science budget environment and increasingly numerous required technology developments, the technology investment decisions within NASA are objectively more and more difficult to make such that the end results are satisfying the technical objectives and all the organizational constraints. Under these conditions it is rationally desirable to build an investment portfolio, which has the highest possible technology infusion rate. Arguably the path to infusion is subject to many influencing factors, but here only the challenges associated with the very initial stages are addressed: defining the needs and the subsequent investment decision-support process. It is conceivable that decision consistency and possibly its quality suffer when the decision-making process has limited or no traceability. This paper presents a structured decision-support framework aiming to provide traceable, auditable, infusion- driven recommendations towards a selection process in which these recommendations are used as reference points in further discussions among stakeholders. In this framework addressing well-defined requirements, different measures of success can be defined based on traceability to specific selection criteria. As a direct result, even by using simplified decision models the likelihood of infusion can be probed and consequently improved.

Normative evidence accumulation in unpredictable environments

PubMed Central

Glaze, Christopher M; Kable, Joseph W; Gold, Joshua I

2015-01-01

In our dynamic world, decisions about noisy stimuli can require temporal accumulation of evidence to identify steady signals, differentiation to detect unpredictable changes in those signals, or both. Normative models can account for learning in these environments but have not yet been applied to faster decision processes. We present a novel, normative formulation of adaptive learning models that forms decisions by acting as a leaky accumulator with non-absorbing bounds. These dynamics, derived for both discrete and continuous cases, depend on the expected rate of change of the statistics of the evidence and balance signal identification and change detection. We found that, for two different tasks, human subjects learned these expectations, albeit imperfectly, then used them to make decisions in accordance with the normative model. The results represent a unified, empirically supported account of decision-making in unpredictable environments that provides new insights into the expectation-driven dynamics of the underlying neural signals. DOI: http://dx.doi.org/10.7554/eLife.08825.001 PMID:26322383

Data-driven medicinal chemistry in the era of big data.

PubMed

Lusher, Scott J; McGuire, Ross; van Schaik, René C; Nicholson, C David; de Vlieg, Jacob

2014-07-01

Science, and the way we undertake research, is changing. The increasing rate of data generation across all scientific disciplines is providing incredible opportunities for data-driven research, with the potential to transform our current practices. The exploitation of so-called 'big data' will enable us to undertake research projects never previously possible but should also stimulate a re-evaluation of all our data practices. Data-driven medicinal chemistry approaches have the potential to improve decision making in drug discovery projects, providing that all researchers embrace the role of 'data scientist' and uncover the meaningful relationships and patterns in available data. Copyright © 2013 Elsevier Ltd. All rights reserved.

Advancing research collaborations among agencies through the Interagency Arctic Research Policy Committee: A necessary step for linking science to policy.

NASA Astrophysics Data System (ADS)

LaValley, M.; Starkweather, S.; Bowden, S.

2017-12-01

The Arctic is changing rapidly as average temperatures rise. As an Arctic nation, the United States is directly affected by these changes. It is imperative that these changes be understood to make effective policy decisions. Since the research needs of the Arctic are large and wide-ranging, most Federal agencies fund some aspect of Arctic research. As a result, the U.S. government regularly works to coordinate Federal Arctic research in order to reduce duplication of effort and costs, and to enhance the research's system perspective. The government's Interagency Arctic Research Policy Committee (IARPC) accomplishes this coordination through its policy-driven five-year Arctic Research Plans and collaboration teams (CTs), which are research topic-oriented teams tasked with implementing the plans. The policies put forth by IARPC thus inform science, however IARPC has been less successful of making these science outcomes part of an iterative decision making process. IARPC's mandate to facilitate coordinated research through information sharing communities can be viewed a prerequisite step in the science-to- decision making process. Research collaborations and the communities of practice facilitated by IARPC allow scientists to connect with a wider community of scientists and stakeholders and, in turn, the larger issues in need of policy solutions. These connections help to create a pathway through which research may increasingly reflect policy goals and inform decisions. IARPC has been growing into a more useful model for the science-to-decision making interface since the publication of its Arctic Research Plan FY2017-2021, and it is useful to evaluate how and why IARPC is progressing in this realm. To understand the challenges facing interagency research collaboration and the progress IARPC has made, the Chukchi Beaufort and Communities CTs, were evaluated as case studies. From the case studies, several recommendations for enhancing collaborations across Federal agencies emerge, including establishing appropriate agency leadership; determining focused and achievable scope of team goals; providing room for bottom-up, community-driven determination of goals; and finally, building relationships and creating an inclusive team environment.

Action Research and Differentiating Reading Instruction in Mississippi: Fourth-Grade Students' Reading Success

ERIC Educational Resources Information Center

Mims, Wyn, M.; Lockley, Jeannie

2017-01-01

A fourth-grade teacher utilized action research in order to make data-driven decisions about reading interventions with her students. The teacher decided on a broad intervention, which was differentiating reading instruction, implemented differentiated instruction, collected data and continuously adjusted interventions based on monitoring data.…

Odyssey Reading. What Works Clearinghouse Intervention Report

ERIC Educational Resources Information Center

What Works Clearinghouse, 2012

2012-01-01

"Odyssey Reading," published by CompassLearning[R], is a web-based K-12 reading/language arts program designed to allow for instructional differentiation and data-driven decision making. The online program includes electronic curricula and materials for individual or small-group work, assessments aligned with state curriculum standards,…

Assess. Instruct. Repeat.

ERIC Educational Resources Information Center

Demski, Jennifer

2009-01-01

Response to Intervention, or RTI, is a framework for using data to establish the nature and degree of the help a student needs, and then applying strategies targeting those areas. It is a carefully drawn, systematic form of data-driven decision-making that establishes multiple stages of interventions for varying degrees of problems. Though some…

Data Systems and Reports as Active Participants in Data Interpretation

ERIC Educational Resources Information Center

Rankin, Jenny Grant

2016-01-01

Most data-informed decision-making in education is undermined by flawed interpretations. Educator-driven interventions to improve data use are beneficial but not omnipotent, as data misunderstandings persist at schools and school districts commended for ideal data use support. Meanwhile, most data systems and reports display figures without…

Examining Construct Validity of the Quantitative Literacy VALUE Rubric in College-Level STEM Assignments

ERIC Educational Resources Information Center

Gray, Julie S.; Brown, Melissa A.; Connolly, John P.

2017-01-01

Data-driven decision making is increasingly viewed as essential in a globally competitive society. Initiatives to augment standardized testing with performance-based assessment have increased as educators progressively respond to mandates for authentic measurement of student attainment. To meet this challenge, multidisciplinary rubrics were…

Chinese International Students' Decision-Making Perspectives: A Case Study

ERIC Educational Resources Information Center

Stewart, David

2017-01-01

Unprecedented rapidity of change occurring throughout the higher education sector linked to student mobility driven globalization momentum reinforces the benefits of attracting and cultivating the strongest students to contribute diversity of thought to learning environments. The purpose of this case study was to explore multiple perspectives of…

Health assessment and risk mitigation of railroad networks exposed to natural hazards using commercial remote sensing and spatial information technologies.

DOT National Transportation Integrated Search

2017-05-31

The overarching goal of this project was to integrate data from commercial remote sensing and spatial information (CRS&SI) technologies to create a novel data-driven decision making framework that empowers the railroad industry to monitor, assess, an...

How Data Use for Accountability Undermines Equitable Science Education

ERIC Educational Resources Information Center

Braaten, Melissa; Bradford, Chris; Kirchgasler, Kathryn L.; Barocas, Sadie Fox

2017-01-01

Purpose: When school leaders advance strategic plans focused on improving educational equity through data-driven decision making, how do policies-as-practiced unfold in the daily work of science teachers? The paper aims to discuss this issue. Design/methodology/approach: This ethnographic study examines how data-centric accountability and…

Accountability for Results: The Realities of Data-Driven Decision Making

ERIC Educational Resources Information Center

McCaw, Donna; Watkins, Sandra

2007-01-01

The format of this book addresses the most salient questions administrators, school board members, and community stakeholders need to ask to ensure academic and fiscal accountability, providing definitions, background information and the current research. Readers will be provided with sufficient knowledge to effectively question the financial…

Using GIS Tools and Environmental Scanning to Forecast Industry Workforce Needs

ERIC Educational Resources Information Center

Gaertner, Elaine; Fleming, Kevin; Marquez, Michelle

2009-01-01

The Centers of Excellence (COE) provide regional workforce data on high growth, high demand industries and occupations for use by community colleges in program planning and resource enhancement. This article discusses the environmental scanning research methodology and its application to data-driven decision making in community college program…

My Mentored Relationship with Harold Guetzkow

ERIC Educational Resources Information Center

Chadwick, Richard W.

2011-01-01

Harold Guetzkow's guidance of research on foreign policy decision making was driven by a core concern: the avoidance of nuclear war and preservation of peace. He aimed to do this by supporting the creation and distribution of new knowledge through experiments aimed at simulating the processes and conditions hypothesized to influence such…

Attention and Motivated Response to Simulated Male Advertisement Call Activates Forebrain Dopaminergic and Social Decision-Making Network Nuclei in Female Midshipman Fish.

PubMed

Forlano, Paul M; Licorish, Roshney R; Ghahramani, Zachary N; Timothy, Miky; Ferrari, Melissa; Palmer, William C; Sisneros, Joseph A

2017-10-01

Little is known regarding the coordination of audition with decision-making and subsequent motor responses that initiate social behavior including mate localization during courtship. Using the midshipman fish model, we tested the hypothesis that the time spent by females attending and responding to the advertisement call is correlated with the activation of a specific subset of catecholaminergic (CA) and social decision-making network (SDM) nuclei underlying auditory- driven sexual motivation. In addition, we quantified the relationship of neural activation between CA and SDM nuclei in all responders with the goal of providing a map of functional connectivity of the circuitry underlying a motivated state responsive to acoustic cues during mate localization. In order to make a baseline qualitative comparison of this functional brain map to unmotivated females, we made a similar correlative comparison of brain activation in females who were unresponsive to the advertisement call playback. Our results support an important role for dopaminergic neurons in the periventricular posterior tuberculum and ventral thalamus, putative A11 and A13 tetrapod homologues, respectively, as well as the posterior parvocellular preoptic area and dorsomedial telencephalon, (laterobasal amygdala homologue) in auditory attention and appetitive sexual behavior in fishes. These findings may also offer insights into the function of these highly conserved nuclei in the context of auditory-driven reproductive social behavior across vertebrates. © The Author 2017. Published by Oxford University Press on behalf of the Society for Integrative and Comparative Biology. All rights reserved. For permissions please email: journals.permissions@oup.com.

Cognitive balanced model: a conceptual scheme of diagnostic decision making.

PubMed

Lucchiari, Claudio; Pravettoni, Gabriella

2012-02-01

Diagnostic reasoning is a critical aspect of clinical performance, having a high impact on quality and safety of care. Although diagnosis is fundamental in medicine, we still have a poor understanding of the factors that determine its course. According to traditional understanding, all information used in diagnostic reasoning is objective and logically driven. However, these conditions are not always met. Although we would be less likely to make an inaccurate diagnosis when following rational decision making, as described by normative models, the real diagnostic process works in a different way. Recent work has described the major cognitive biases in medicine as well as a number of strategies for reducing them, collectively called debiasing techniques. However, advances have encountered obstacles in achieving implementation into clinical practice. While traditional understanding of clinical reasoning has failed to consider contextual factors, most debiasing techniques seem to fail in raising sound and safer medical praxis. Technological solutions, being data driven, are fundamental in increasing care safety, but they need to consider human factors. Thus, balanced models, cognitive driven and technology based, are needed in day-to-day applications to actually improve the diagnostic process. The purpose of this article, then, is to provide insight into cognitive influences that have resulted in wrong, delayed or missed diagnosis. Using a cognitive approach, we describe the basis of medical error, with particular emphasis on diagnostic error. We then propose a conceptual scheme of the diagnostic process by the use of fuzzy cognitive maps. © 2011 Blackwell Publishing Ltd.

Visual Analytics Tools for Sustainable Lifecycle Design: Current Status, Challenges, and Future Opportunities.

PubMed

Ramanujan, Devarajan; Bernstein, William Z; Chandrasegaran, Senthil K; Ramani, Karthik

2017-01-01

The rapid rise in technologies for data collection has created an unmatched opportunity to advance the use of data-rich tools for lifecycle decision-making. However, the usefulness of these technologies is limited by the ability to translate lifecycle data into actionable insights for human decision-makers. This is especially true in the case of sustainable lifecycle design (SLD), as the assessment of environmental impacts, and the feasibility of making corresponding design changes, often relies on human expertise and intuition. Supporting human sense-making in SLD requires the use of both data-driven and user-driven methods while exploring lifecycle data. A promising approach for combining the two is through the use of visual analytics (VA) tools. Such tools can leverage the ability of computer-based tools to gather, process, and summarize data along with the ability of human-experts to guide analyses through domain knowledge or data-driven insight. In this paper, we review previous research that has created VA tools in SLD. We also highlight existing challenges and future opportunities for such tools in different lifecycle stages-design, manufacturing, distribution & supply chain, use-phase, end-of-life, as well as life cycle assessment. Our review shows that while the number of VA tools in SLD is relatively small, researchers are increasingly focusing on the subject matter. Our review also suggests that VA tools can address existing challenges in SLD and that significant future opportunities exist.

Logics of pre-merger decision-making processes: the case of Karolinska University Hospital.

PubMed

Choi, Soki; Brommels, Mats

2009-01-01

The purpose of this paper is to examine how and why a decision to merge two university hospitals in a public context might occur by using an in-depth case study of the pre-merger process of Karolinska University Hospital. Based on extensive document analysis and 35 key informant interviews the paper reconstructed the pre-merger process, searched for empirical patterns, and interpreted those by applying neo-institutional theory. Spanning nearly a decade, the pre-merger process goes from idea generation through transition to decision, and took place on two arenas, political, and scientific. Both research excellence and economic efficiency are stated merger motives. By applying a neo-institutional perspective, the paper finds that the two initial phases are driven by decision rationality, which is typical for political organizations and that the final phase demonstrated action rationality, which is typical for private firms. Critical factors behind this radical change of decision logic are means convergence, uniting key stakeholder groups, and an economic and political crisis, triggering critical incidents, which ultimately legitimized the formal decision. It is evident from the paper that merger decisions in the public sector might not necessarily result from stated and/or economic drivers only. This paper suggests that a change of decision logic from decision to action rationality might promote effective decision making on large and complex issues in a public context. This is the first systematic in-depth study of a university hospital merger employing a decision-making perspective.

Neuroeconomic measures of social decision-making across the lifespan.

PubMed

Zhu, Lusha; Walsh, Daniel; Hsu, Ming

2012-01-01

Social and decision-making deficits are often the first symptoms of a striking number of neurodegenerative disorders associated with aging. These includes not only disorders that directly impact dopamine and basal ganglia, such as Parkinson's disorder, but also degeneration in which multiple neural pathways are affected over the course of normal aging. The impact of such deficits can be dramatic, as in cases of financial fraud, which disproportionately affect the elderly. Unlike memory and motor impairments, however, which are readily recognized as symptoms of more serious underlying neurological conditions, social and decision-making deficits often do not elicit comparable concern in the elderly. Furthermore, few behavioral measures exist to quantify these deficits, due in part to our limited knowledge of the core cognitive components or their neurobiological substrates. Here we probe age-related differences in decision-making using a game theory paradigm previously shown to dissociate contributions of basal ganglia and prefrontal regions to behavior. Combined with computational modeling, we provide evidence that age-related changes in elderly participants are driven primarily by an over-reliance in trial-and-error reinforcement learning that does not take into account the strategic context, which may underlie cognitive deficits that contribute to social vulnerability in elderly individuals.

Application of process monitoring to anomaly detection in nuclear material processing systems via system-centric event interpretation of data from multiple sensors of varying reliability

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

Garcia, Humberto E.; Simpson, Michael F.; Lin, Wen-Chiao

In this paper, we apply an advanced safeguards approach and associated methods for process monitoring to a hypothetical nuclear material processing system. The assessment regarding the state of the processing facility is conducted at a systemcentric level formulated in a hybrid framework. This utilizes architecture for integrating both time- and event-driven data and analysis for decision making. While the time-driven layers of the proposed architecture encompass more traditional process monitoring methods based on time series data and analysis, the event-driven layers encompass operation monitoring methods based on discrete event data and analysis. By integrating process- and operation-related information and methodologiesmore » within a unified framework, the task of anomaly detection is greatly improved. This is because decision-making can benefit from not only known time-series relationships among measured signals but also from known event sequence relationships among generated events. This available knowledge at both time series and discrete event layers can then be effectively used to synthesize observation solutions that optimally balance sensor and data processing requirements. The application of the proposed approach is then implemented on an illustrative monitored system based on pyroprocessing and results are discussed.« less

Neural predictors of purchases

PubMed Central

Knutson, Brian; Rick, Scott; Wimmer, G. Elliott; Prelec, Drazen; Loewenstein, George

2007-01-01

Microeconomic theory maintains that purchases are driven by a combination of consumer preference and price. Using event-related FMRI, we investigated how people weigh these factors to make purchasing decisions. Consistent with neuroimaging evidence suggesting that distinct circuits anticipate gain and loss, product preference activated the nucleus accumbens (NAcc), while excessive prices activated the insula and deactivated the mesial prefrontal cortex (MPFC) prior to the purchase decision. Activity from each of these regions independently predicted immediately subsequent purchases above and beyond self-report variables. These findings suggest that activation of distinct neural circuits related to anticipatory affect precedes and supports consumers’ purchasing decisions. PMID:17196537

NASA Wrangler: Automated Cloud-Based Data Assembly in the RECOVER Wildfire Decision Support System

NASA Technical Reports Server (NTRS)

Schnase, John; Carroll, Mark; Gill, Roger; Wooten, Margaret; Weber, Keith; Blair, Kindra; May, Jeffrey; Toombs, William

2017-01-01

NASA Wrangler is a loosely-coupled, event driven, highly parallel data aggregation service designed to take advantageof the elastic resource capabilities of cloud computing. Wrangler automatically collects Earth observational data, climate model outputs, derived remote sensing data products, and historic biophysical data for pre-, active-, and post-wildfire decision making. It is a core service of the RECOVER decision support system, which is providing rapid-response GIS analytic capabilities to state and local government agencies. Wrangler reduces to minutes the time needed to assemble and deliver crucial wildfire-related data.

Perturbations in Effort-Related Decision-Making Driven by Acute Stress and Corticotropin-Releasing Factor.

PubMed

Bryce, Courtney A; Floresco, Stan B

2016-07-01

Acute stress activates numerous systems in a coordinated effort to promote homeostasis, and can exert differential effects on mnemonic and cognitive functions depending on a myriad of factors. Stress can alter different forms of cost/benefit decision-making, yet the mechanisms that drive these effects, remain unclear. In the present study, we probed how corticotropin-releasing factor (CRF) may contribute to stress-induced alterations in cost/benefit decision-making, using an task where well-trained rats chose between a low effort/low reward lever (LR; two pellets) and a high effort/high reward lever (HR; four pellets), with the effort requirement increasing over a session (2, 5, 10, and 20 presses). One-hour restraint stress markedly reduced preference for the HR option, but this effect was attenuated by infusions of the CRF antagonist, alpha-helical CRF. Conversely, central CRF infusion mimicked the effect of stress on decision-making, as well as increased decision latencies and reduced response vigor. CRF infusions did not alter preference for larger vs smaller rewards, but did reduce responding for food delivered on a progressive ratio, suggesting that these treatments may amplify perceived effort costs that may be required to obtain rewards. CRF infusions into the ventral tegmental area recapitulated the effect of central CRF treatment and restraint on choice behavior, suggesting that these effects may be mediated by perturbations in dopamine transmission. These findings highlight the involvement of CRF in regulating effort-related decisions and suggest that increased CRF activity may contribute to motivational impairments and abnormal decision-making associated with stress-related psychiatric disorders such as depression.

Perturbations in Effort-Related Decision-Making Driven by Acute Stress and Corticotropin-Releasing Factor

PubMed Central

Bryce, Courtney A; Floresco, Stan B

2016-01-01

Acute stress activates numerous systems in a coordinated effort to promote homeostasis, and can exert differential effects on mnemonic and cognitive functions depending on a myriad of factors. Stress can alter different forms of cost/benefit decision-making, yet the mechanisms that drive these effects, remain unclear. In the present study, we probed how corticotropin-releasing factor (CRF) may contribute to stress-induced alterations in cost/benefit decision-making, using an task where well-trained rats chose between a low effort/low reward lever (LR; two pellets) and a high effort/high reward lever (HR; four pellets), with the effort requirement increasing over a session (2, 5, 10, and 20 presses). One-hour restraint stress markedly reduced preference for the HR option, but this effect was attenuated by infusions of the CRF antagonist, alpha-helical CRF. Conversely, central CRF infusion mimicked the effect of stress on decision-making, as well as increased decision latencies and reduced response vigor. CRF infusions did not alter preference for larger vs smaller rewards, but did reduce responding for food delivered on a progressive ratio, suggesting that these treatments may amplify perceived effort costs that may be required to obtain rewards. CRF infusions into the ventral tegmental area recapitulated the effect of central CRF treatment and restraint on choice behavior, suggesting that these effects may be mediated by perturbations in dopamine transmission. These findings highlight the involvement of CRF in regulating effort-related decisions and suggest that increased CRF activity may contribute to motivational impairments and abnormal decision-making associated with stress-related psychiatric disorders such as depression. PMID:26830960

An integrated theory of attention and decision making in visual signal detection.

PubMed

Smith, Philip L; Ratcliff, Roger

2009-04-01

The simplest attentional task, detecting a cued stimulus in an otherwise empty visual field, produces complex patterns of performance. Attentional cues interact with backward masks and with spatial uncertainty, and there is a dissociation in the effects of these variables on accuracy and on response time. A computational theory of performance in this task is described. The theory links visual encoding, masking, spatial attention, visual short-term memory (VSTM), and perceptual decision making in an integrated dynamic framework. The theory assumes that decisions are made by a diffusion process driven by a neurally plausible, shunting VSTM. The VSTM trace encodes the transient outputs of early visual filters in a durable form that is preserved for the time needed to make a decision. Attention increases the efficiency of VSTM encoding, either by increasing the rate of trace formation or by reducing the delay before trace formation begins. The theory provides a detailed, quantitative account of attentional effects in spatial cuing tasks at the level of response accuracy and the response time distributions. (c) 2009 APA, all rights reserved

Effects of emotional preferences on value-based decision making are mediated by mentalizing not reward networks

PubMed Central

Evans, Simon; Fleming, Stephen M.; Dolan, Raymond J.; Averbeck, Bruno B.

2012-01-01

Real-world decision-making often involves social considerations. Consequently, the social value of stimuli can induce preferences in choice behavior. However, it is unknown how financial and social values are integrated in the brain. Here, we investigated how smiling and angry face stimuli interacted with financial reward feedback in a stochastically-rewarded decision-making task. Subjects reliably preferred the smiling faces despite equivalent reward feedback, demonstrating a socially driven bias. We fit a Bayesian reinforcement learning model to factor the effects of financial rewards and emotion preferences in individual subjects, and regressed model predictions on the trial-by-trial fMRI signal. Activity in the sub-callosal cingulate and the ventral striatum, both involved in reward learning, correlated with financial reward feedback, whereas the differential contribution of social value activated dorsal temporo-parietal junction and dorsal anterior cingulate cortex, previously proposed as components of a mentalizing network. We conclude that the impact of social stimuli on value-based decision processes is mediated by effects in brain regions partially separable from classical reward circuitry. PMID:20946058

Fathers and Daughters: Using a Multivariate Analysis through Multiple Regression to Help Predict a Daughter's Self-Esteem as Experienced by College-Age Women in Rural Nebraska

ERIC Educational Resources Information Center

Beshaler, Mary E.

2010-01-01

Throughout her life, a woman makes decisions about behaviors, relationships, academic accomplishments, and achievements. What propels women to make these choices may be driven by an image of self. This feeling of self-worth or self-esteem is developed early in life with the help of her primary caregivers as found in her biological mother and…

Intuition: A Needed Component of Leadership for Decision-making in Today’s Technology Driven Air Force

DTIC Science & Technology

2009-12-15

technology‘s influence. She states, ―We treat technology as a family member…‖. Email replaced the Post Office with instant communication worldwide. We can...how or why the conclusion was reached in a rational sense. As Rowan states, ―Not being able to articulate a hazy, indistinct, subliminal impression...decisions and act independently, Kennan was not able to communicate his message and idea to senior leadership for years after his intuition led him

From Data to Improved Decisions: Operations Research in Healthcare Delivery.

PubMed

Capan, Muge; Khojandi, Anahita; Denton, Brian T; Williams, Kimberly D; Ayer, Turgay; Chhatwal, Jagpreet; Kurt, Murat; Lobo, Jennifer Mason; Roberts, Mark S; Zaric, Greg; Zhang, Shengfan; Schwartz, J Sanford

2017-11-01

The Operations Research Interest Group (ORIG) within the Society of Medical Decision Making (SMDM) is a multidisciplinary interest group of professionals that specializes in taking an analytical approach to medical decision making and healthcare delivery. ORIG is interested in leveraging mathematical methods associated with the field of Operations Research (OR) to obtain data-driven solutions to complex healthcare problems and encourage collaborations across disciplines. This paper introduces OR for the non-expert and draws attention to opportunities where OR can be utilized to facilitate solutions to healthcare problems. Decision making is the process of choosing between possible solutions to a problem with respect to certain metrics. OR concepts can help systematically improve decision making through efficient modeling techniques while accounting for relevant constraints. Depending on the problem, methods that are part of OR (e.g., linear programming, Markov Decision Processes) or methods that are derived from related fields (e.g., regression from statistics) can be incorporated into the solution approach. This paper highlights the characteristics of different OR methods that have been applied to healthcare decision making and provides examples of emerging research opportunities. We illustrate OR applications in healthcare using previous studies, including diagnosis and treatment of diseases, organ transplants, and patient flow decisions. Further, we provide a selection of emerging areas for utilizing OR. There is a timely need to inform practitioners and policy makers of the benefits of using OR techniques in solving healthcare problems. OR methods can support the development of sustainable long-term solutions across disease management, service delivery, and health policies by optimizing the performance of system elements and analyzing their interaction while considering relevant constraints.

The Mother's Autonomy in Decision Making (MADM) scale: Patient-led development and psychometric testing of a new instrument to evaluate experience of maternity care.

PubMed

Vedam, Saraswathi; Stoll, Kathrin; Martin, Kelsey; Rubashkin, Nicholas; Partridge, Sarah; Thordarson, Dana; Jolicoeur, Ganga

2017-01-01

To develop and validate a new instrument that assesses women's autonomy and role in decision making during maternity care. Through a community-based participatory research process, service users designed, content validated, and administered a cross-sectional quantitative survey, including 31 items on the experience of decision-making. Pregnancy experiences (n = 2514) were reported by 1672 women who saw a single type of primary maternity care provider in British Columbia. They described care by a midwife, family physician or obstetrician during 1, 2 or 3 maternity care cycles. We conducted psychometric testing in three separate samples. We assessed reliability, item-to-total correlations, and the factor structure of the The Mothers' Autonomy in Decision Making (MADM) scale. We report MADM scores by care provider type, length of prenatal appointments, preferences for role in decision-making, and satisfaction with experience of decision-making. The MADM scale measures a single construct: autonomy in decision-making during maternity care. Cronbach alphas for the scale exceeded 0.90 for all samples and all provider groups. All item-to-total correlations were replicable across three samples and exceeded 0.7. Eigenvalue and scree plots exhibited a clear 90-degree angle, and factor analysis generated a one factor scale. MADM median scores were highest among women who were cared for by midwives, and 10 or more points lower for those who saw physicians. Increased time for prenatal appointments was associated with higher scale scores, and there were significant differences between providers with respect to average time spent in prenatal appointments. Midwifery care was associated with higher MADM scores, even during short prenatal appointments (<15 minutes). Among women who preferred to lead decisions around their care (90.8%), and who were dissatisfied with their experience of decision making, MADM scores were very low (median 14). Women with physician carers were consistently more likely to report dissatisfaction with their involvement in decision making. The Mothers Autonomy in Decision Making (MADM) scale is a reliable instrument for assessment of the experience of decision making during maternity care. This new scale was developed and content validated by community members representing various populations of childbearing women in BC including women from vulnerable populations. MADM measures women's ability to lead decision making, whether they are given enough time to consider their options, and whether their choices are respected. Women who experienced midwifery care reported greater autonomy than women under physician care, when engaging in decision-making around maternity care options. Differences in models of care, professional education, regulatory standards, and compensation for prenatal visits between midwives and physicians likely affect the time available for these discussions and prioritization of a shared decision making process. The MADM scale reflects person-driven priorities, and reliably assesses interactions with maternity providers related to a person's ability to lead decision-making over the course of maternity care.

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.

Value-Based Reimbursement: Impact of Curtailing Physician Autonomy in Medical Decision Making.

PubMed

Gupta, Dipti; Karst, Ingolf; Mendelson, Ellen B

2016-02-01

In this article, we define value in the context of reimbursement and explore the effect of shifting reimbursement paradigms on the decision-making autonomy of a women's imaging radiologist. The current metrics used for value-based reimbursement such as report turnaround time are surrogate measures that do not measure value directly. The true measure of a physician's value in medicine is accomplishment of better health outcomes, which, in breast imaging, are best achieved with a physician-patient relationship. Complying with evidence-based medicine, which includes data-driven best clinical practices, a physician's clinical expertise, and the patient's values, will improve our science and preserve the art of medicine.

Impact of nutrition on social decision making.

PubMed

Strang, Sabrina; Hoeber, Christina; Uhl, Olaf; Koletzko, Berthold; Münte, Thomas F; Lehnert, Hendrik; Dolan, Raymond J; Schmid, Sebastian M; Park, Soyoung Q

2017-06-20

Food intake is essential for maintaining homeostasis, which is necessary for survival in all species. However, food intake also impacts multiple biochemical processes that influence our behavior. Here, we investigate the causal relationship between macronutrient composition, its bodily biochemical impact, and a modulation of human social decision making. Across two studies, we show that breakfasts with different macronutrient compositions modulated human social behavior. Breakfasts with a high-carbohydrate/protein ratio increased social punishment behavior in response to norm violations compared with that in response to a low carbohydrate/protein meal. We show that these macronutrient-induced behavioral changes in social decision making are causally related to a lowering of plasma tyrosine levels. The findings indicate that, in a limited sense, "we are what we eat" and provide a perspective on a nutrition-driven modulation of cognition. The findings have implications for education, economics, and public policy, and emphasize that the importance of a balanced diet may extend beyond the mere physical benefits of adequate nutrition.

Impact of nutrition on social decision making

PubMed Central

Strang, Sabrina; Hoeber, Christina; Uhl, Olaf; Koletzko, Berthold; Münte, Thomas F.; Lehnert, Hendrik; Dolan, Raymond J.; Schmid, Sebastian M.; Park, Soyoung Q.

2017-01-01

Food intake is essential for maintaining homeostasis, which is necessary for survival in all species. However, food intake also impacts multiple biochemical processes that influence our behavior. Here, we investigate the causal relationship between macronutrient composition, its bodily biochemical impact, and a modulation of human social decision making. Across two studies, we show that breakfasts with different macronutrient compositions modulated human social behavior. Breakfasts with a high-carbohydrate/protein ratio increased social punishment behavior in response to norm violations compared with that in response to a low carbohydrate/protein meal. We show that these macronutrient-induced behavioral changes in social decision making are causally related to a lowering of plasma tyrosine levels. The findings indicate that, in a limited sense, “we are what we eat” and provide a perspective on a nutrition-driven modulation of cognition. The findings have implications for education, economics, and public policy, and emphasize that the importance of a balanced diet may extend beyond the mere physical benefits of adequate nutrition. PMID:28607064

Optimal policy for value-based decision-making.

PubMed

Tajima, Satohiro; Drugowitsch, Jan; Pouget, Alexandre

2016-08-18

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

Optimal policy for value-based decision-making

PubMed Central

Tajima, Satohiro; Drugowitsch, Jan; Pouget, Alexandre

2016-01-01

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

Value(s)-Driven Decision-Making: The Ethics Work of English Headteachers within Discourses of Constraint

ERIC Educational Resources Information Center

Hammersley-Fletcher, Linda

2015-01-01

This article considers the experiences and perceptions of practising English headteachers and the tensions that they face when juggling government prescription and government initiatives, which may be antagonistic to their educational values and beliefs. Managerial control over teachers work has been particularly acute and destructive to…

The Role of Human Expertise in Enhancing Data Mining

ERIC Educational Resources Information Center

Kaddouri, Abdelaaziz

2011-01-01

Current data mining (DM) technology is not domain-specific and therefore rarely generates reliable, business actionable knowledge that can be used to improve the effectiveness of the decision-making process in the banking industry. DM is mainly an autonomous, data-driven process with little focus on domain expertise, constraints, or requirements…

Exploring Cloud Computing Tools to Enhance Team-Based Problem Solving for Challenging Behavior

ERIC Educational Resources Information Center

Johnson, LeAnne D.

2017-01-01

Data-driven decision making is central to improving success of children. Actualizing the use of data is challenging when addressing the social, emotional, and behavioral needs of children across different types of early childhood programs (i.e., early childhood special education, early childhood family education, Head Start, and childcare).…

"Scrubbing" Data for D3M

ERIC Educational Resources Information Center

Mercurius, Neil

2005-01-01

Data-driven decision-making (D3M) appears to be the new buzz phrase for this century, the information age. On the education front, teachers and administrators are engaging in data-centered dialog in grade-level meetings, lounges, hallways, and classrooms as they brainstorm toward closing the gap in student achievement. Clearly, such discussion…

Toward Data-Driven Education Systems: Insights into Using Information to Measure Results and Manage Change

ERIC Educational Resources Information Center

Custer, Samantha; King, Elizabeth M.; Atinc, Tamar Manuelyan; Read, Lindsay; Sethi, Tanya

2018-01-01

Governments, organizations, and companies are generating copious amounts of data and analysis to support education decision-making around the world. While continued investments in data creation and management are necessary, the ultimate value of information is not in its "production," but its "use." Herein lies one of the…

Coherent District Reform: A Case Study of Two California School Districts

ERIC Educational Resources Information Center

Ezzani, Miriam

2015-01-01

The purpose of this paper is to enhance our understanding of districts that are implementing sustainable professional learning in data-driven decision-making (DDDM) to improve student achievement. The data-informed leadership framework, comprised of leadership practices that acknowledge the complexities that play into data use, guided the inquiry.…

Seriously Data-Driven Decision Making

ERIC Educational Resources Information Center

Casserly, Michael D.

2011-01-01

As states approach the funding cliff marking the end of federal stimulus help for education, school districts will be feeling more financial pain than they're experiencing now. But there's good news amid the bad: Big city districts are showing schools nationwide a way to save money and improve efficiency by working together. They've created the…

A Crystal Ball for Student Achievement

ERIC Educational Resources Information Center

Pascopella, Angela

2012-01-01

Predicting the future is now in the hands of K12 administrators. While for years districts have collected thousands of pieces of student data, educators have been using them only for data-driven decision-making or formative assessments, which give a "rear-view" perspective only. Now, using predictive analysis--the pulling together of data over…

Statistical Literacy: Data Tell a Story

ERIC Educational Resources Information Center

Sole, Marla A.

2016-01-01

Every day, students collect, organize, and analyze data to make decisions. In this data-driven world, people need to assess how much trust they can place in summary statistics. The results of every survey and the safety of every drug that undergoes a clinical trial depend on the correct application of appropriate statistics. Recognizing the…

Clinical Reasoning in the Assessment and Intervention Planning for Writing Disorder

ERIC Educational Resources Information Center

Harrison, Gina L.; McManus, Kelly L.

2017-01-01

The incidence of writing disorder is as common as reading disorder, but it is frequently under-identified and rarely targeted for intervention. Increasing clinical understanding on various subtypes of writing disorder through assessment guided by data-driven decision making may alleviate this disparity for students with writing disorders. The…

Internal Consistency and Cross-Informant Agreement of the Lithuanian-Translated Behavioral and Emotional Rating Scale

ERIC Educational Resources Information Center

Sointu, Erkko T.; Geležiniene, Renata; Lambert, Matthew C.; Nordness, Philip D.

2015-01-01

Educational professionals need assessments that yield psychometrically sound scores to assess students' behavioral and emotional functioning in order to guide data-driven decision-making processes. Rating scales have been found to be effective and economical, and often multiple informant perspectives can be obtained. The agreement between multiple…

The Principal's Mind-Set for Data

ERIC Educational Resources Information Center

Fox, Dennis

2013-01-01

Is there a school leader anywhere who hasn't been directed, or at least encouraged, to "analyze the data" and practice what has been termed "data-driven decision-making"? Today's principal is expected to be able to skillfully collect, organize, analyze, interpret and use a variety of data in order to improve instruction, services and programs for…

Completing the Link between Exposure Science and Toxicology for Improved Environmental Health Decision Making: The Aggregate Exposure Pathway Framework

EPA Science Inventory

Driven by major scientific advances in analytical methods, biomonitoring, computation, and a newly articulated vision for a greater impact in public health, the field of exposure science is undergoing a rapid transition from a field of observation to a field of prediction. Deploy...

Dare to Share

ERIC Educational Resources Information Center

Briggs, Linda L.

2007-01-01

Today, as difficult as it is for large institutions to keep software and hardware up-to-date, the challenge and expense of keeping up is only amplified for smaller colleges and universities. In the area of data-driven decision-making (DDD), the challenge can be even greater. Because smaller schools are pressed for time and resources on nearly all…

Breaking the Habit of Low Performance: Successful School Restructuring Stories

ERIC Educational Resources Information Center

Brinson, Dana; Rhim, Lauren Morando

2009-01-01

The components of a successful school are clear. Many educators can easily list them: high expectations for all students, a safe and orderly learning environment, strong instructional leadership, highly qualified teachers, data-driven decision making, etc. Then why don't more schools change the what they are doing to mirror them? Knowing the…

A Systemic View of Implementing Data Literacy in Educator Preparation

ERIC Educational Resources Information Center

Mandinach, Ellen B.; Gummer, Edith S.

2013-01-01

Data-driven decision making has become increasingly important in education. Policymakers require educators to use data to inform practice. Although the policy emphasis is growing, what has not increased is attention to building human capacity around data use. Educators need to gain data literacy skills to inform practice. Although some…

A Predictive Model of Inquiry to Enrollment

ERIC Educational Resources Information Center

Goenner, Cullen F.; Pauls, Kenton

2006-01-01

The purpose of this paper is to build a predictive model of enrollment that provides data driven analysis to improve undergraduate recruitment efforts. We utilize an inquiry model, which examines the enrollment decisions of students that have made contact with our institution, a medium sized, public, Doctoral I university. A student, who makes an…

Speed in Information Processing with a Computer Driven Visual Display in a Real-time Digital Simulation. M.S. Thesis - Virginia Polytechnic Inst.

NASA Technical Reports Server (NTRS)

Kyle, R. G.

1972-01-01

Information transfer between the operator and computer-generated display systems is an area where the human factors engineer discovers little useful design data relating human performance to system effectiveness. This study utilized a computer-driven, cathode-ray-tube graphic display to quantify human response speed in a sequential information processing task. The performance criteria was response time to sixteen cell elements of a square matrix display. A stimulus signal instruction specified selected cell locations by both row and column identification. An equal probable number code, from one to four, was assigned at random to the sixteen cells of the matrix and correspondingly required one of four, matched keyed-response alternatives. The display format corresponded to a sequence of diagnostic system maintenance events, that enable the operator to verify prime system status, engage backup redundancy for failed subsystem components, and exercise alternate decision-making judgements. The experimental task bypassed the skilled decision-making element and computer processing time, in order to determine a lower bound on the basic response speed for given stimulus/response hardware arrangement.

Consideration of Insulin Pumps or Continuous Glucose Monitors by Adolescents With Type 1 Diabetes and Their Parents: Stakeholder Engagement in the Design of Web-Based Decision Aids.

PubMed

Wysocki, Tim; Hirschfeld, Fiona; Miller, Louis; Izenberg, Neil; Dowshen, Steven A; Taylor, Alex; Milkes, Amy; Shinseki, Michelle T; Bejarano, Carolina; Kozikowski, Chelsea; Kowal, Karen; Starr-Ashton, Penny; Ross, Judith L; Kummer, Mark; Carakushansky, Mauri; Lyness, D'Arcy; Brinkman, William; Pierce, Jessica; Fiks, Alexander; Christofferson, Jennifer; Rafalko, Jessica; Lawson, Margaret L

2016-08-01

This article describes the stakeholder-driven design, development, and testing of web-based, multimedia decision aids for youth with type 1 diabetes who are considering the insulin pump or continuous glucose monitoring and their parents. This is the initial phase of work designed to develop and evaluate the efficacy of these decision aids in promoting improved decision-making engagement with use of a selected device. Qualitative interviews of 36 parents and adolescents who had previously faced these decisions and 12 health care providers defined the content, format and structure of the decision aids. Experts in children's health media helped the research team to plan, create, and refine multimedia content and its presentation. A web development firm helped organize the content into a user-friendly interface and enabled tracking of decision aid utilization. Throughout, members of the research team, adolescents, parents, and 3 expert consultants offered perspectives about the website content, structure, and function until the design was complete. With the decision aid websites completed, the next phase of the project is a randomized controlled trial of usual clinical practice alone or augmented by use of the decision aid websites. Stakeholder-driven development of multimedia, web-based decision aids requires meticulous attention to detail but can yield exceptional resources for adolescents and parents contemplating major changes to their diabetes regimens. © 2016 The Author(s).

Improving Breast Cancer Surgical Treatment Decision Making: The iCanDecide Randomized Clinical Trial.

PubMed

Hawley, Sarah T; Li, Yun; An, Lawrence C; Resnicow, Kenneth; Janz, Nancy K; Sabel, Michael S; Ward, Kevin C; Fagerlin, Angela; Morrow, Monica; Jagsi, Reshma; Hofer, Timothy P; Katz, Steven J

2018-03-01

Purpose This study was conducted to determine the effect of iCanDecide, an interactive and tailored breast cancer treatment decision tool, on the rate of high-quality patient decisions-both informed and values concordant-regarding locoregional breast cancer treatment and on patient appraisal of decision making. Methods We conducted a randomized clinical trial of newly diagnosed patients with early-stage breast cancer making locoregional treatment decisions. From 22 surgical practices, 537 patients were recruited and randomly assigned online to the iCanDecide interactive and tailored Web site (intervention) or the iCanDecide static Web site (control). Participants completed a baseline survey and were mailed a follow-up survey 4 to 5 weeks after enrollment to assess the primary outcome of a high-quality decision, which consisted of two components, high knowledge and values-concordant treatment, and secondary outcomes (decision preparation, deliberation, and subjective decision quality). Results Patients in the intervention arm had higher odds of making a high-quality decision than did those in the control arm (odds ratio, 2.00; 95% CI, 1.37 to 2.92; P = .0004), which was driven primarily by differences in the rates of high knowledge between groups. The majority of patients in both arms made values-concordant treatment decisions (78.6% in the intervention arm and 81.4% in the control arm). More patients in the intervention arm had high decision preparation (estimate, 0.18; 95% CI, 0.02 to 0.34; P = .027), but there were no significant differences in the other decision appraisal outcomes. The effect of the intervention was similar for women who were leaning strongly toward a treatment option at enrollment compared with those who were not. Conclusion The tailored and interactive iCanDecide Web site, which focused on knowledge building and values clarification, positively affected high-quality decisions largely by improving knowledge compared with static online information. To be effective, future patient-facing decision tools should be integrated into the clinical workflow to improve decision making.

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

PubMed Central

Elqayam, Shira

2017-01-01

Abstract Given that more than 30% of healthcare costs are wasted on inappropriate care, suboptimal care is increasingly connected to the quality of medical decisions. It has been argued that personal decisions are the leading cause of death, and 80% of healthcare expenditures result from physicians' decisions. Therefore, improving healthcare necessitates improving medical decisions, ie, making decisions (more) rational. Drawing on writings from The Great Rationality Debate from the fields of philosophy, economics, and psychology, we identify core ingredients of rationality commonly encountered across various theoretical models. Rationality is typically classified under umbrella of normative (addressing the question how people “should” or “ought to” make their decisions) and descriptive theories of decision‐making (which portray how people actually make their decisions). Normative theories of rational thought of relevance to medicine include epistemic theories that direct practice of evidence‐based medicine and expected utility theory, which provides the basis for widely used clinical decision analyses. Descriptive theories of rationality of direct relevance to medical decision‐making include bounded rationality, argumentative theory of reasoning, adaptive rationality, dual processing model of rationality, regret‐based rationality, pragmatic/substantive rationality, and meta‐rationality. For the first time, we provide a review of wide range of theories and models of rationality. We showed that what is “rational” behaviour under one rationality theory may be irrational under the other theory. We also showed that context is of paramount importance to rationality and that no one model of rationality can possibly fit all contexts. We suggest that in context‐poor situations, such as policy decision‐making, normative theories based on expected utility informed by best research evidence may provide the optimal approach to medical decision‐making, whereas in the context‐rich circumstances other types of rationality, informed by human cognitive architecture and driven by intuition and emotions such as the aim to minimize regret, may provide better solution to the problem at hand. The choice of theory under which we operate is important as it determines both policy and our individual decision‐making. PMID:28730671

Contextual influences on animal decision-making: Significance for behavior-based wildlife conservation and management.

PubMed

Owen, Megan A; Swaisgood, Ronald R; Blumstein, Daniel T

2017-01-01

Survival and successful reproduction require animals to make critical decisions amidst a naturally dynamic environmental and social background (i.e. "context"). However, human activities have pervasively, and rapidly, extended contextual variation into evolutionarily novel territory, potentially rendering evolved animal decision-making mechanisms and strategies maladaptive. We suggest that explicitly focusing on animal decision-making (ADM), by integrating and applying findings from studies of sensory ecology, cognitive psychology, behavioral economics and eco-evolutionary strategies, may enhance our understanding of, and our ability to predict how, human-driven changes in the environment and population demography will influence animal populations. Fundamentally, the decisions animals make involve evolved mechanisms, and behaviors emerge from the combined action of sensory integration, cognitive mechanisms and strategic rules of thumb, and any of these processes may have a disproportionate influence on behavior. Although there is extensive literature exploring ADM, it generally reflects a canalized, discipline-specific approach that lacks a unified conceptual framework. As a result, there has been limited application of ADM theory and research findings into predictive models that can enhance management outcomes, even though it is likely that the relative resilience of species to rapid environmental change is fundamentally a result of how ADM is linked to contextual variation. Here, we focus on how context influences ADM, and highlight ideas and results that may be most applicable to conservation biology. © 2016 International Society of Zoological Sciences, Institute of Zoology/Chinese Academy of Sciences and John Wiley & Sons Australia, Ltd.

Impaired decision-making and selective cortical frontal thinning in Cushing's syndrome.

PubMed

Crespo, Iris; Esther, Granell-Moreno; Santos, Alicia; Valassi, Elena; Yolanda, Vives-Gilabert; De Juan-Delago, Manel; Webb, Susan M; Gómez-Ansón, Beatriz; Resmini, Eugenia

2014-12-01

Cushing's syndrome (CS) is caused by a glucocorticoid excess. This hypercortisolism can damage the prefrontal cortex, known to be important in decision-making. Our aim was to evaluate decision-making in CS and to explore cortical thickness. Thirty-five patients with CS (27 cured, eight medically treated) and thirty-five matched controls were evaluated using Iowa gambling task (IGT) and 3 Tesla magnetic resonance imaging (MRI) to assess cortical thickness. The IGT evaluates decision-making, including strategy and learning during the test. Cortical thickness was determined on MRI using freesurfer software tools, including a whole-brain analysis. There were no differences between medically treated and cured CS patients. They presented an altered decision-making strategy compared to controls, choosing a lower number of the safer cards (P < 0·05). They showed more difficulties than controls to learn the correct profiles of wins and losses for each card group (P < 0·05). In whole-brain analysis, patients with CS showed decreased cortical thickness in the left superior frontal cortex, left precentral cortex, left insular cortex, left and right rostral anterior cingulate cortex, and right caudal middle frontal cortex compared to controls (P < 0·001). Patients with CS failed to learn advantageous strategies and their behaviour was driven by short-term reward and long-term punishment, indicating learning problems because they did not use previous experience as a feedback factor to regulate their choices. These alterations in decision-making and the decreased cortical thickness in frontal areas suggest that chronic hypercortisolism promotes brain changes which are not completely reversible after endocrine remission. © 2014 John Wiley & Sons Ltd.

Resurfacing the care in nursing by telephone: lessons from ambulatory oncology.

PubMed

Wilson, Rosemary; Hubert, John

2002-01-01

The practice of providing telephone mediated advice and assistance is often described as "telephone triage" in relevant literature. The decision-making processes required for priority-setting and the provision of advice have been found to be complex and multifaceted. Conceptualization of this valuable patient care activity as a linear "triage" function serves to make invisible the nursing care provided. This article explores the current practice of providing telephone mediated advice and assistance in the following 2 distinct nursing care settings: emergency departments and ambulatory oncology centers. Examination of this activity in these 2 settings provides a forum to discuss and critique legally and fiscally driven prescriptive protocol use to inform decision-making. The effectiveness of experiential knowledge coupled with the strengths of nurse-patient relationships suggests that a need exists to highlight the caring aspects of telephone mediated assistance.

A visualization tool to support decision making in environmental and biological planning

USGS Publications Warehouse

Romañach, Stephanie S.; McKelvy, James M.; Conzelmann, Craig; Suir, Kevin J.

2014-01-01

Large-scale ecosystem management involves consideration of many factors for informed decision making. The EverVIEW Data Viewer is a cross-platform desktop decision support tool to help decision makers compare simulation model outputs from competing plans for restoring Florida's Greater Everglades. The integration of NetCDF metadata conventions into EverVIEW allows end-users from multiple institutions within and beyond the Everglades restoration community to share information and tools. Our development process incorporates continuous interaction with targeted end-users for increased likelihood of adoption. One of EverVIEW's signature features is side-by-side map panels, which can be used to simultaneously compare species or habitat impacts from alternative restoration plans. Other features include examination of potential restoration plan impacts across multiple geographic or tabular displays, and animation through time. As a result of an iterative, standards-driven approach, EverVIEW is relevant to large-scale planning beyond Florida, and is used in multiple biological planning efforts in the United States.

Why do patients engage in medical tourism?

PubMed

Runnels, Vivien; Carrera, P M

2012-12-01

Medical tourism is commonly perceived and popularly depicted as an economic issue, both at the system and individual levels. The decision to engage in medical tourism, however, is more complex, driven by patients' unmet need, the nature of services sought and the manner by which treatment is accessed. In order to beneficially employ the opportunities medical tourism offers, and address and contain possible threats and harms, an informed decision is crucial. This paper aims to enhance the current knowledge on medical tourism by isolating the focal content of the decisions that patients make. Based on the existing literature, it proposes a sequential decision-making process in opting for or against medical care abroad, and engaging in medical tourism, including considerations of the required treatments, location of treatment, and quality and safety issues attendant to seeking care. Accordingly, it comments on the imperative of access to health information and the current regulatory environment which impact on this increasingly popular and complex form of accessing and providing medical care. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Balance Sheets Versus Decision Dashboards to Support Patient Treatment Choices: A Comparative Analysis.

PubMed

Dolan, James G; Veazie, Peter J

2015-12-01

Growing recognition of the importance of involving patients in preference-driven healthcare decisions has highlighted the need to develop practical strategies to implement patient-centered shared decision-making. The use of tabular balance sheets to support clinical decision-making is well established. More recent evidence suggests that graphic, interactive decision dashboards can help people derive deeper a understanding of information within a specific decision context. We therefore conducted a non-randomized trial comparing the effects of adding an interactive dashboard to a static tabular balance sheet on patient decision-making. The study population consisted of members of the ResearchMatch registry who volunteered to participate in a study of medical decision-making. Two separate surveys were conducted: one in the control group and one in the intervention group. All participants were instructed to imagine they were newly diagnosed with a chronic illness and were asked to choose between three hypothetical drug treatments, which varied with regard to effectiveness, side effects, and out-of-pocket cost. Both groups made an initial treatment choice after reviewing a balance sheet. After a brief "washout" period, members of the control group made a second treatment choice after reviewing the balance sheet again, while intervention group members made a second treatment choice after reviewing an interactive decision dashboard containing the same information. After both choices, participants rated their degree of confidence in their choice on a 1 to 10 scale. Members of the dashboard intervention group were more likely to change their choice of preferred drug (10.2 versus 7.5%; p = 0.054) and had a larger increase in decision confidence than the control group (0.67 versus 0.075; p < 0.03). There were no statistically significant between-group differences in decisional conflict or decision aid acceptability. These findings suggest that clinical decision dashboards may be an effective point-of-care decision-support tool. Further research to explore this possibility is warranted.

Quantum-like model of brain's functioning: decision making from decoherence.

PubMed

Asano, Masanari; Ohya, Masanori; Tanaka, Yoshiharu; Basieva, Irina; Khrennikov, Andrei

2011-07-21

We present a quantum-like model of decision making in games of the Prisoner's Dilemma type. By this model the brain processes information by using representation of mental states in a complex Hilbert space. Driven by the master equation the mental state of a player, say Alice, approaches an equilibrium point in the space of density matrices (representing mental states). This equilibrium state determines Alice's mixed (i.e., probabilistic) strategy. We use a master equation in which quantum physics describes the process of decoherence as the result of interaction with environment. Thus our model is a model of thinking through decoherence of the initially pure mental state. Decoherence is induced by the interaction with memory and the external mental environment. We study (numerically) the dynamics of quantum entropy of Alice's mental state in the process of decision making. We also consider classical entropy corresponding to Alice's choices. We introduce a measure of Alice's diffidence as the difference between classical and quantum entropies of Alice's mental state. We see that (at least in our model example) diffidence decreases (approaching zero) in the process of decision making. Finally, we discuss the problem of neuronal realization of quantum-like dynamics in the brain; especially roles played by lateral prefrontal cortex or/and orbitofrontal cortex. Copyright © 2011 Elsevier Ltd. All rights reserved.

The Mother’s Autonomy in Decision Making (MADM) scale: Patient-led development and psychometric testing of a new instrument to evaluate experience of maternity care

PubMed Central

Vedam, Saraswathi; Stoll, Kathrin; Martin, Kelsey; Rubashkin, Nicholas; Partridge, Sarah; Thordarson, Dana; Jolicoeur, Ganga

2017-01-01

Shared decision making (SDM) is core to person-centered care and is associated with improved health outcomes. Despite this, there are no validated scales measuring women’s agency and ability to lead decision making during maternity care. Objective To develop and validate a new instrument that assesses women’s autonomy and role in decision making during maternity care. Design Through a community-based participatory research process, service users designed, content validated, and administered a cross-sectional quantitative survey, including 31 items on the experience of decision-making. Setting and participants Pregnancy experiences (n = 2514) were reported by 1672 women who saw a single type of primary maternity care provider in British Columbia. They described care by a midwife, family physician or obstetrician during 1, 2 or 3 maternity care cycles. We conducted psychometric testing in three separate samples. Main outcome measures We assessed reliability, item-to-total correlations, and the factor structure of the The Mothers’ Autonomy in Decision Making (MADM) scale. We report MADM scores by care provider type, length of prenatal appointments, preferences for role in decision-making, and satisfaction with experience of decision-making. Results The MADM scale measures a single construct: autonomy in decision-making during maternity care. Cronbach alphas for the scale exceeded 0.90 for all samples and all provider groups. All item-to-total correlations were replicable across three samples and exceeded 0.7. Eigenvalue and scree plots exhibited a clear 90-degree angle, and factor analysis generated a one factor scale. MADM median scores were highest among women who were cared for by midwives, and 10 or more points lower for those who saw physicians. Increased time for prenatal appointments was associated with higher scale scores, and there were significant differences between providers with respect to average time spent in prenatal appointments. Midwifery care was associated with higher MADM scores, even during short prenatal appointments (<15 minutes). Among women who preferred to lead decisions around their care (90.8%), and who were dissatisfied with their experience of decision making, MADM scores were very low (median 14). Women with physician carers were consistently more likely to report dissatisfaction with their involvement in decision making. Discussion The Mothers Autonomy in Decision Making (MADM) scale is a reliable instrument for assessment of the experience of decision making during maternity care. This new scale was developed and content validated by community members representing various populations of childbearing women in BC including women from vulnerable populations. MADM measures women’s ability to lead decision making, whether they are given enough time to consider their options, and whether their choices are respected. Women who experienced midwifery care reported greater autonomy than women under physician care, when engaging in decision-making around maternity care options. Differences in models of care, professional education, regulatory standards, and compensation for prenatal visits between midwives and physicians likely affect the time available for these discussions and prioritization of a shared decision making process. Conclusion The MADM scale reflects person-driven priorities, and reliably assesses interactions with maternity providers related to a person’s ability to lead decision-making over the course of maternity care. PMID:28231285

Role of Ideas and Ideologies in Evidence-Based Health Policy

PubMed Central

Prinja, S

2010-01-01

Policy making in health is largely thought to be driven by three ‘I’s namely ideas, interests and institutions. Recent years have seen a shift in approach with increasing reliance being placed on role of evidence for policy making. The present article ascertains the role of ideas and ideologies in shaping evidence which is used to aid in policy decisions. The article discusses different theories of research-policy interface and the relative freedom of research-based evidence from the influence of ideas. Examples from developed and developed countries are cited to illustrate the contentions made. The article highlights the complexity of the process of evidence-based policy making, in a world driven by existing political, social and cultural ideologies. Consideration of this knowledge is paramount where more efforts are being made to bridge the gap between the ‘two worlds’ of researchers and policy makers to make evidence-based policy as also for policy analysts. PMID:23112991

Quantum ensembles of quantum classifiers.

PubMed

Schuld, Maria; Petruccione, Francesco

2018-02-09

Quantum machine learning witnesses an increasing amount of quantum algorithms for data-driven decision making, a problem with potential applications ranging from automated image recognition to medical diagnosis. Many of those algorithms are implementations of quantum classifiers, or models for the classification of data inputs with a quantum computer. Following the success of collective decision making with ensembles in classical machine learning, this paper introduces the concept of quantum ensembles of quantum classifiers. Creating the ensemble corresponds to a state preparation routine, after which the quantum classifiers are evaluated in parallel and their combined decision is accessed by a single-qubit measurement. This framework naturally allows for exponentially large ensembles in which - similar to Bayesian learning - the individual classifiers do not have to be trained. As an example, we analyse an exponentially large quantum ensemble in which each classifier is weighed according to its performance in classifying the training data, leading to new results for quantum as well as classical machine learning.

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.

Measuring Conditions and Consequences of Tracking in the High School Curriculum

ERIC Educational Resources Information Center

Archbald, Doug; Keleher, Julia

2008-01-01

Despite a decade of advocacy and advances in technology, data driven decision making remains an elusive vision for most high schools. This article identifies key data systems design needs and presents methods for monitoring, managing, and improving programs. Because of its continuing salience, we focus on the issue of tracking (ability grouping).…

Understanding the Voice of the Customer: Practical, Data-Driven Planning and Decision Making for Access Services

ERIC Educational Resources Information Center

Huff-Eibl, Robyn; Miller-Wells, John; Begay, Wendy

2014-01-01

This article describes the process and role frontline access and public service staff play in needs assessment and evaluation of user services, specifically in understanding the voice of the customer. Information includes how the University of Arizona Libraries have incorporated daily data collection into the strategic planning process, resources…

A Framework for Understanding Community Colleges' Organizational Capacity for Data Use: A Convergent Parallel Mixed Methods Study

ERIC Educational Resources Information Center

Kerrigan, Monica Reid

2014-01-01

This convergent parallel design mixed methods case study of four community colleges explores the relationship between organizational capacity and implementation of data-driven decision making (DDDM). The article also illustrates purposive sampling using replication logic for cross-case analysis and the strengths and weaknesses of quantitizing…

Innovation in Data-Driven Decision Making within SWPBIS Systems: Welcome to the Gallery Walk

ERIC Educational Resources Information Center

Kennedy, Michael J.; Mimmack, Jody; Flannery, K. Brigid

2012-01-01

Schools implementing school-wide positive behavioral interventions and supports (SWPBIS) at the high school level face the same challenges as elementary and middle schools, but also encounter an additional set of barriers all their own. To name but a few, these barriers include the need to focus on dropout prevention, postsecondary outcomes,…

The Role of Storytelling in Understanding Children's Moral/Ethic Decision-Making

ERIC Educational Resources Information Center

Hunter, Cheryl; Eder, Donna

2010-01-01

As students advance in their education, the use of stories and specifically the process of storytelling often wane from the central mode of learning to be replaced with more didactic methods and content-driven applications. However, the use of stories has remained a central component of moral/ethics education and continues to be used as a…

Multi-Dimensional Education: A Common Sense Approach to Data-Driven Thinking

ERIC Educational Resources Information Center

Corrigan, Michael W.; Grove, Doug; Vincent, Philip F.

2011-01-01

Schools aren't one dimensional. Your decision making shouldn't be either. If you want to look beyond student test scores to identify the specific areas that need improvement in your school, you will find practical tools for assessing multiple areas with confidence here. The authors detail a step-by-step framework for identifying, collecting,…

Building an Evidence-Driven Child Welfare Workforce: A University-Agency Partnership

ERIC Educational Resources Information Center

Lery, Bridgette; Wiegmann, Wendy; Berrick, Jill Duerr

2015-01-01

The federal government increasingly expects child welfare systems to be more responsive to the needs of their local populations, connect strategies to results, and use continuous quality improvement (CQI) to accomplish these goals. A method for improving decision making, CQI relies on an inflow of high-quality data, up-to-date research evidence,…

Racism? Administrative and Community Perspectives in Data-Driven Decision Making: Systemic Perspectives versus Technical-Rational Perspectives

ERIC Educational Resources Information Center

Khalifa, Muhammad A.; Jennings, Michael E.; Briscoe, Felecia; Oleszweski, Ashley M.; Abdi, Nimo

2014-01-01

This case study describes tensions that became apparent between community members and school administrators after a proposal to close a historically African American public high school in a large urban Southwestern city. When members of the city's longstanding African American community responded with outrage, the school district's senior…

Strategic Framing: How Leaders Craft the Meaning of Data Use for Equity and Learning

ERIC Educational Resources Information Center

Park, Vicki; Daly, Alan J.; Guerra, Alison Wishard

2013-01-01

Although there is an emerging body of research that examines data-driven decision making (DDDM) in schools, little attention has been paid to how local leaders strategically frame sensemaking around data use. This exploratory case examines how district and school leaders consciously framed the implementation of DDDM in one urban high school.…

Data Driven Decision-Making in the Era of Accountability: Fostering Faculty Data Cultures for Learning

ERIC Educational Resources Information Center

Hora, Matthew T.; Bouwma-Gearhart, Jana; Park, Hyoung Joon

2017-01-01

In this article the authors report findings from a practice-based study that examines the cultural practices of data use among 59 science and engineering faculty from three large, public research universities. In this exploratory study they documented how faculty use teaching-related data "in the wild" using interviews and classroom…

Data-Driven Decision Making as a Tool to Improve Software Development Productivity

ERIC Educational Resources Information Center

Brown, Mary Erin

2013-01-01

The worldwide software project failure rate, based on a survey of information technology software manager's view of user satisfaction, product quality, and staff productivity, is estimated to be between 24% and 36% and software project success has not kept pace with the advances in hardware. The problem addressed by this study was the limited…

Teacher Use of Data to Guide Instructional Practice in Elementary Schools

ERIC Educational Resources Information Center

Burrows, Debra C.

2011-01-01

This descriptive study focused on the degree to which data-driven decision making as envisioned by the NCLB legislation was actually occurring in the elementary schools studied. A multi-stage random sample of six Pennsylvania school districts out of 19 located within the service area of Pennsylvania Intermediate Unit #17, one of 29 regional…

Affordances and Constraints in the Context of Teacher Collaboration for the Purpose of Data Use

ERIC Educational Resources Information Center

Datnow, Amanda; Park, Vicki; Kennedy-Lewis, Brianna

2013-01-01

Purpose: An increasing number of schools and districts across the US are requiring teachers to collaborate for the purpose of data-driven decision making. Research suggests that both data use and teacher collaboration are important ingredients in the school improvement process. Existing studies also reveal the complexities of teacher collaboration…

University Governance, Leadership and Management in a Decade of Diversification and Uncertainty

ERIC Educational Resources Information Center

Shattock, Michael

2013-01-01

The last decade has seen an acceleration of change in the way British universities have been governed, led and managed. This has substantially been driven by the instability of the external environment, which has encouraged a greater centralisation of decision-making leading to less governance and more management, but it is also a consequence of…

Investigating the Preservice Primary School, Mathematics and Science Teachers' STEM Awareness

ERIC Educational Resources Information Center

Bakirci, Hasan; Karisan, Dilek

2018-01-01

Today's life requires individuals to be prepared for complex world environment, to make complex decisions, and to have critical thinking skills related to everyday life issues at hand. STEM education is thought to be the glorious solution to thrive in a global knowledge driven world. Teachers are key elements for successful STEM education. Present…

An Investigation of Charter Schools' School Leader and Teacher Level of Assessment Literacy

ERIC Educational Resources Information Center

Pfeiffer-Hoens, Mareen

2017-01-01

Assessment of student performance is one of the most critical responsibilities of school leaders and teachers. Teachers and school leaders must acquire an understanding of assessment literacy for utilizing data to make sound data-driven decisions. The purpose of this descriptive study was to investigate the levels of assessment literacy among…

Junior Faculty of Color in the Corporate University: Implications of Neoliberalism and Neoconservatism on Research, Teaching and Service

ERIC Educational Resources Information Center

Osei-Kofi, Nana

2012-01-01

In higher education today, an overwhelming acceptance of neoliberal and neoconservative ideologies that advance corporate logics of efficiency, competition and profit maximization is commonplace. Market-driven logics and neoconservative ideals shape decision-making about what is taught, how material is taught, who teaches, who does research, who…

The Department of Homeland Security’s Pursuit of Data-Driven Decision Making

DTIC Science & Technology

2015-12-01

agencies’ information management systems pertaining to mission support and business operations 1 KT...Directorate’s operating environment. xviii managed . Meanwhile, adding to the intrinsic organizational change management challenges is the idea that...a timely manner. The lack of a single, enterprise-wide information management system has resulted in numerous, disparate systems operating within

First, Get Their Attention: Getting Your Results Used. Professional File. Number 122, Fall 2011

ERIC Educational Resources Information Center

Leimer, Christina

2011-01-01

Fostering data-driven decision-making is not an easy task, nor is getting busy people's attention in this age of information overload. How we write about and disseminate our findings can help. Writing to the audience, timing, formatting, choice of medium, and connecting results to institutional goals and current, even controversial, issues are…

Charting the expansion of strategic exploratory behavior during adolescence.

PubMed

Somerville, Leah H; Sasse, Stephanie F; Garrad, Megan C; Drysdale, Andrew T; Abi Akar, Nadine; Insel, Catherine; Wilson, Robert C

2017-02-01

Although models of exploratory decision making implicate a suite of strategies that guide the pursuit of information, the developmental emergence of these strategies remains poorly understood. This study takes an interdisciplinary perspective, merging computational decision making and developmental approaches to characterize age-related shifts in exploratory strategy from adolescence to young adulthood. Participants were 149 12-28-year-olds who completed a computational explore-exploit paradigm that manipulated reward value, information value, and decision horizon (i.e., the utility that information holds for future choices). Strategic directed exploration, defined as information seeking selective for long time horizons, emerged during adolescence and maintained its level through early adulthood. This age difference was partially driven by adolescents valuing immediate reward over new information. Strategic random exploration, defined as stochastic choice behavior selective for long time horizons, was invoked at comparable levels over the age range, and predicted individual differences in attitudes toward risk taking in daily life within the adolescent portion of the sample. Collectively, these findings reveal an expansion of the diversity of strategic exploration over development, implicate distinct mechanisms for directed and random exploratory strategies, and suggest novel mechanisms for adolescent-typical shifts in decision making. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

The Influence of Televised Food Commercials on Children's Food Choices: Evidence from Ventromedial Prefrontal Cortex Activations.

PubMed

Bruce, Amanda S; Pruitt, Stephen W; Ha, Oh-Ryeong; Cherry, J Bradley C; Smith, Timothy R; Bruce, Jared M; Lim, Seung-Lark

2016-10-01

To investigate how food commercials influence children's food choices. Twenty-three children ages 8-14 years provided taste and health ratings for 60 food items. Subsequently, these children were scanned with the use of functional magnetic resonance imaging while making food choices (ie, "eat" or "not eat") after watching food and nonfood television commercials. Our results show that watching food commercials changes the way children consider the importance of taste when making food choices. Children did not use health values for their food choices, indicating children's decisions were largely driven by hedonic, immediate rewards (ie, "tastiness"); however, children placed significantly more importance on taste after watching food commercials compared with nonfood commercials. This change was accompanied by faster decision times during food commercial trials. The ventromedial prefrontal cortex, a reward valuation brain region, showed increased activity during food choices after watching food commercials compared with after watching nonfood commercials. Overall, our results suggest watching food commercials before making food choices may bias children's decisions based solely on taste, and that food marketing may systematically alter the psychological and neurobiologic mechanisms of children's food decisions. Copyright © 2016 Elsevier Inc. All rights reserved.

The Influence of Televised Food Commercials on Children's Food Choices: Evidence from Ventromedial Prefrontal Cortex Activations

PubMed Central

Bruce, Amanda S.; Pruitt, Stephen W.; Ha, Oh-Ryeong; Cherry, J. Bradley C.; Smith, Timothy R.; Bruce, Jared M.; Lim, Seung-Lark

2016-01-01

Objective To investigate how food commercials influence children's food choices. Study design Twenty-three children ages 8-14 years provided taste and health ratings for 60 food items. Subsequently, these children were scanned with the use of functional magnetic resonance imaging while making food choices (ie, “eat” or “not eat”) after watching food and nonfood television commercials. Results Our results show that watching food commercials changes the way children consider the importance of taste when making food choices. Children did not use health values for their food choices, indicating children's decisions were largely driven by hedonic, immediate rewards (ie, “tastiness”); however, children placed significantly more importance on taste after watching food commercials compared with nonfood commercials. This change was accompanied by faster decision times during food commercial trials. The ventromedial prefrontal cortex, a reward valuation brain region, showed increased activity during food choices after watching food commercials compared with after watching nonfood commercials. Conclusion Overall, our results suggest watching food commercials before making food choices may bias children's decisions based solely on taste, and that food marketing may systematically alter the psychological and neurobiologic mechanisms of children's food decisions. PMID:27526621

Decisional strategy determines whether frame influences treatment preferences for medical decisions.

PubMed

Woodhead, Erin L; Lynch, Elizabeth B; Edelstein, Barry A

2011-06-01

Decision makers are influenced by the frame of information such that preferences vary depending on whether survival or mortality data are presented. Research is inconsistent as to whether and how age impacts framing effects. This paper presents two studies that used qualitative analyses of think-aloud protocols to understand how the type of information used in the decision making process varies by frame and age. In Study 1, 40 older adults, age 65 to 89, and 40 younger adults, age 18 to 24, responded to a hypothetical lung cancer scenario in a within-subject design. Participants received both a survival and mortality frame. Qualitative analyses revealed that two main decisional strategies were used by all participants: one strategy reflected a data-driven decisional process, whereas the other reflected an experience-driven process. Age predicted decisional strategy, with older adults less likely to use a data-driven strategy. Frame interacted with strategy to predict treatment choice; only those using a data-driven strategy demonstrated framing effects. In Study 2, 61 older adults, age 65 to 98, and 63 younger adults, age 18 to 30, responded to the same scenarios as in Study 1 in a between-subject design. The results of Study 1 were replicated, with age significantly predicting decisional strategy and frame interacting with strategy to predict treatment choice. Findings suggest that framing effects may be more related to decisional strategy than to age. (c) 2011 APA, all rights reserved.

Clinician and cancer patient views on patient participation in treatment decision-making: a quantitative and qualitative exploration

PubMed Central

Pieterse, A H; Baas-Thijssen, M C M; Marijnen, C A M; Stiggelbout, A M

2008-01-01

Patient participation in treatment decision-making is being increasingly advocated, although cancer treatments are often guideline-driven. Trade-offs between benefits and side effects underlying guidelines are made by clinicians. Evidence suggests that clinicians are inaccurate at predicting patient values. The aim was to assess what role oncologists and cancer patients prefer in deciding about treatment, and how they view patient participation in treatment decision-making. Seventy disease-free cancer patients and 60 oncologists (surgical, radiation, and medical) were interviewed about their role preferences using the Control Preferences Scale (CPS) and about their views on patient participation using closed- and open-ended questions. Almost all participants preferred treatment decisions to be the outcome of a shared process. Clinicians viewed participation more often as reaching an agreement, whereas 23% of patients defined participation exclusively as being informed. Of the participants, ⩾81% thought not all patients are able to participate and ⩾74% thought clinicians are not always able to weigh the pros and cons of treatment for patients, especially not quality as compared with length of life. Clinicians seemed reluctant to share probability information on the likely impact of adjuvant treatment. Clinicians should acknowledge the legitimacy of patients' values in treatment decisions. Guidelines should recommend elicitation of patient values at specific decision points. PMID:18781148

Bridging the gap between evidence and policy for infectious diseases: How models can aid public health decision-making.

PubMed

Knight, Gwenan M; Dharan, Nila J; Fox, Gregory J; Stennis, Natalie; Zwerling, Alice; Khurana, Renuka; Dowdy, David W

2016-01-01

The dominant approach to decision-making in public health policy for infectious diseases relies heavily on expert opinion, which often applies empirical evidence to policy questions in a manner that is neither systematic nor transparent. Although systematic reviews are frequently commissioned to inform specific components of policy (such as efficacy), the same process is rarely applied to the full decision-making process. Mathematical models provide a mechanism through which empirical evidence can be methodically and transparently integrated to address such questions. However, such models are often considered difficult to interpret. In addition, models provide estimates that need to be iteratively re-evaluated as new data or considerations arise. Using the case study of a novel diagnostic for tuberculosis, a framework for improved collaboration between public health decision-makers and mathematical modellers that could lead to more transparent and evidence-driven policy decisions for infectious diseases in the future is proposed. The framework proposes that policymakers should establish long-term collaborations with modellers to address key questions, and that modellers should strive to provide clear explanations of the uncertainty of model structure and outputs. Doing so will improve the applicability of models and clarify their limitations when used to inform real-world public health policy decisions. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Neuroscientific Model of Motivational Process

PubMed Central

Kim, Sung-il

2013-01-01

Considering the neuroscientific findings on reward, learning, value, decision-making, and cognitive control, motivation can be parsed into three sub processes, a process of generating motivation, a process of maintaining motivation, and a process of regulating motivation. I propose a tentative neuroscientific model of motivational processes which consists of three distinct but continuous sub processes, namely reward-driven approach, value-based decision-making, and goal-directed control. Reward-driven approach is the process in which motivation is generated by reward anticipation and selective approach behaviors toward reward. This process recruits the ventral striatum (reward area) in which basic stimulus-action association is formed, and is classified as an automatic motivation to which relatively less attention is assigned. By contrast, value-based decision-making is the process of evaluating various outcomes of actions, learning through positive prediction error, and calculating the value continuously. The striatum and the orbitofrontal cortex (valuation area) play crucial roles in sustaining motivation. Lastly, the goal-directed control is the process of regulating motivation through cognitive control to achieve goals. This consciously controlled motivation is associated with higher-level cognitive functions such as planning, retaining the goal, monitoring the performance, and regulating action. The anterior cingulate cortex (attention area) and the dorsolateral prefrontal cortex (cognitive control area) are the main neural circuits related to regulation of motivation. These three sub processes interact with each other by sending reward prediction error signals through dopaminergic pathway from the striatum and to the prefrontal cortex. The neuroscientific model of motivational process suggests several educational implications with regard to the generation, maintenance, and regulation of motivation to learn in the learning environment. PMID:23459598

Neuroscientific model of motivational process.

PubMed

Kim, Sung-Il

2013-01-01

Considering the neuroscientific findings on reward, learning, value, decision-making, and cognitive control, motivation can be parsed into three sub processes, a process of generating motivation, a process of maintaining motivation, and a process of regulating motivation. I propose a tentative neuroscientific model of motivational processes which consists of three distinct but continuous sub processes, namely reward-driven approach, value-based decision-making, and goal-directed control. Reward-driven approach is the process in which motivation is generated by reward anticipation and selective approach behaviors toward reward. This process recruits the ventral striatum (reward area) in which basic stimulus-action association is formed, and is classified as an automatic motivation to which relatively less attention is assigned. By contrast, value-based decision-making is the process of evaluating various outcomes of actions, learning through positive prediction error, and calculating the value continuously. The striatum and the orbitofrontal cortex (valuation area) play crucial roles in sustaining motivation. Lastly, the goal-directed control is the process of regulating motivation through cognitive control to achieve goals. This consciously controlled motivation is associated with higher-level cognitive functions such as planning, retaining the goal, monitoring the performance, and regulating action. The anterior cingulate cortex (attention area) and the dorsolateral prefrontal cortex (cognitive control area) are the main neural circuits related to regulation of motivation. These three sub processes interact with each other by sending reward prediction error signals through dopaminergic pathway from the striatum and to the prefrontal cortex. The neuroscientific model of motivational process suggests several educational implications with regard to the generation, maintenance, and regulation of motivation to learn in the learning environment.

Individual differences in voluntary alcohol intake in rats: relationship with impulsivity, decision making and Pavlovian conditioned approach.

PubMed

Spoelder, Marcia; Flores Dourojeanni, Jacques P; de Git, Kathy C G; Baars, Annemarie M; Lesscher, Heidi M B; Vanderschuren, Louk J M J

2017-07-01

Alcohol use disorder (AUD) has been associated with suboptimal decision making, exaggerated impulsivity, and aberrant responses to reward-paired cues, but the relationship between AUD and these behaviors is incompletely understood. This study aims to assess decision making, impulsivity, and Pavlovian-conditioned approach in rats that voluntarily consume low (LD) or high (HD) amounts of alcohol. LD and HD were tested in the rat gambling task (rGT) or the delayed reward task (DRT). Next, the effect of alcohol (0-1.0 g/kg) was tested in these tasks. Pavlovian-conditioned approach (PCA) was assessed both prior to and after intermittent alcohol access (IAA). Principal component analyses were performed to identify relationships between the most important behavioral parameters. HD showed more optimal decision making in the rGT. In the DRT, HD transiently showed reduced impulsive choice. In both LD and HD, alcohol treatment increased optimal decision making in the rGT and increased impulsive choice in the DRT. PCA prior to and after IAA was comparable for LD and HD. When PCA was tested after IAA only, HD showed a more sign-tracking behavior. The principal component analyses indicated dimensional relationships between alcohol intake, impulsivity, and sign-tracking behavior in the PCA task after IAA. HD showed a more efficient performance in the rGT and DRT. Moreover, alcohol consumption enhanced approach behavior to reward-predictive cues, but sign-tracking did not predict the level of alcohol consumption. Taken together, these findings suggest that high levels of voluntary alcohol intake are associated with enhanced cue- and reward-driven behavior.

Managing risk during care transitions when approaching end of life: A qualitative study of patients' and health care professionals' decision making.

PubMed

Coombs, Maureen A; Parker, Roses; de Vries, Kay

2017-07-01

Increasing importance is being placed on the coordination of services at the end of life. To describe decision-making processes that influence transitions in care when approaching the end of life. Qualitative study using field observations and longitudinal semi-structured interviews. Field observations were undertaken in three sites: a residential care home, a medical assessment unit and a general medical unit in New Zealand. The Supportive and Palliative Care Indicators Tool was used to identify participants with advanced and progressive illness. Patients and family members were interviewed on recruitment and 3-4 months later. Four weeks of fieldwork were conducted in each site. A total of 40 interviews were conducted: 29 initial interviews and 11 follow-up interviews. Thematic analysis was undertaken. Managing risk was an important factor that influenced transitions in care. Patients and health care staff held different perspectives on how such risks were managed. At home, patients tolerated increasing risk and used specific support measures to manage often escalating health and social problems. In contrast, decisions about discharge in hospital were driven by hospital staff who were risk-adverse. Availability of community and carer services supported risk management while a perceived need for early discharge decision making in hospital and making 'safe' discharge options informed hospital discharge decisions. While managing risk is an important factor during care transitions, patients should be able to make choices on how to live with risk at the end of life. This requires reconsideration of transitional care and current discharge planning processes at the end of life.

Dopamine Receptor-Specific Contributions to the Computation of Value.

PubMed

Burke, Christopher J; Soutschek, Alexander; Weber, Susanna; Raja Beharelle, Anjali; Fehr, Ernst; Haker, Helene; Tobler, Philippe N

2018-05-01

Dopamine is thought to play a crucial role in value-based decision making. However, the specific contributions of different dopamine receptor subtypes to the computation of subjective value remain unknown. Here we demonstrate how the balance between D1 and D2 dopamine receptor subtypes shapes subjective value computation during risky decision making. We administered the D2 receptor antagonist amisulpride or placebo before participants made choices between risky options. Compared with placebo, D2 receptor blockade resulted in more frequent choice of higher risk and higher expected value options. Using a novel model fitting procedure, we concurrently estimated the three parameters that define individual risk attitude according to an influential theoretical account of risky decision making (prospect theory). This analysis revealed that the observed reduction in risk aversion under amisulpride was driven by increased sensitivity to reward magnitude and decreased distortion of outcome probability, resulting in more linear value coding. Our data suggest that different components that govern individual risk attitude are under dopaminergic control, such that D2 receptor blockade facilitates risk taking and expected value processing.

Completing the Link between Exposure Science and Toxicology for Improved Environmental Health Decision Making: The Aggregate Exposure Pathway Framework.

PubMed

Teeguarden, Justin G; Tan, Yu-Mei; Edwards, Stephen W; Leonard, Jeremy A; Anderson, Kim A; Corley, Richard A; Kile, Molly L; Simonich, Staci M; Stone, David; Tanguay, Robert L; Waters, Katrina M; Harper, Stacey L; Williams, David E

2016-05-03

Driven by major scientific advances in analytical methods, biomonitoring, computation, and a newly articulated vision for a greater impact in public health, the field of exposure science is undergoing a rapid transition from a field of observation to a field of prediction. Deployment of an organizational and predictive framework for exposure science analogous to the "systems approaches" used in the biological sciences is a necessary step in this evolution. Here we propose the aggregate exposure pathway (AEP) concept as the natural and complementary companion in the exposure sciences to the adverse outcome pathway (AOP) concept in the toxicological sciences. Aggregate exposure pathways offer an intuitive framework to organize exposure data within individual units of prediction common to the field, setting the stage for exposure forecasting. Looking farther ahead, we envision direct linkages between aggregate exposure pathways and adverse outcome pathways, completing the source to outcome continuum for more meaningful integration of exposure assessment and hazard identification. Together, the two frameworks form and inform a decision-making framework with the flexibility for risk-based, hazard-based, or exposure-based decision making.

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.

Symmetry in cold-to-hot and hot-to-cold valuation gaps.

PubMed

Fisher, Geoffrey; Rangel, Antonio

2014-01-01

Individuals commonly mispredict their future preferences when they make decisions in a visceral state different from their anticipated state at consumption. In the research reported here, we asked subjects to bid on different foods while exogenously varying their hunger levels at the time of decision and at the time of consumption. This procedure allowed us to test whether cold-to-hot and hot-to-cold gaps are symmetric in size and driven by similar mechanisms. We found that the effect size was symmetric: Hungry subjects overbid 20¢ for a snack they would eat later when they were satiated, and satiated subjects underbid 19¢ for a snack they would eat later when they were hungry. Furthermore, we found evidence that these gaps were driven by symmetric mechanisms that operate on the evaluation of visceral features of food, such as taste, as opposed to more cognitive features, such as healthiness.

The anatomy of clinical decision-making in multidisciplinary cancer meetings

PubMed Central

Soukup, Tayana; Petrides, Konstantinos V.; Lamb, Benjamin W.; Sarkar, Somita; Arora, Sonal; Shah, Sujay; Darzi, Ara; Green, James S. A.; Sevdalis, Nick

2016-01-01

Abstract In the UK, treatment recommendations for patients with cancer are routinely made by multidisciplinary teams in weekly meetings. However, their performance is variable. The aim of this study was to explore the underlying structure of multidisciplinary decision-making process, and examine how it relates to team ability to reach a decision. This is a cross-sectional observational study consisting of 1045 patient reviews across 4 multidisciplinary cancer teams from teaching and community hospitals in London, UK, from 2010 to 2014. Meetings were chaired by surgeons. We used a validated observational instrument (Metric for the Observation of Decision-making in Cancer Multidisciplinary Meetings) consisting of 13 items to assess the decision-making process of each patient discussion. Rated on a 5-point scale, the items measured quality of presented patient information, and contributions to review by individual disciplines. A dichotomous outcome (yes/no) measured team ability to reach a decision. Ratings were submitted to Exploratory Factor Analysis and regression analysis. The exploratory factor analysis produced 4 factors, labeled “Holistic and Clinical inputs” (patient views, psychosocial aspects, patient history, comorbidities, oncologists’, nurses’, and surgeons’ inputs), “Radiology” (radiology results, radiologists’ inputs), “Pathology” (pathology results, pathologists’ inputs), and “Meeting Management” (meeting chairs’ and coordinators’ inputs). A negative cross-loading was observed from surgeons’ input on the fourth factor with a follow-up analysis showing negative correlation (r = −0.19, P < 0.001). In logistic regression, all 4 factors predicted team ability to reach a decision (P < 0.001). Hawthorne effect is the main limitation of the study. The decision-making process in cancer meetings is driven by 4 underlying factors representing the complete patient profile and contributions to case review by all core disciplines. Evidence of dual-task interference was observed in relation to the meeting chairs’ input and their corresponding surgical input into case reviews. PMID:27310981

Comparative approaches to studying strategy: towards an evolutionary account of primate decision making.

PubMed

Brosnan, Sarah F; Beran, Michael J; Parrish, Audrey E; Price, Sara A; Wilson, Bart J

2013-07-18

How do primates, humans included, deal with novel problems that arise in interactions with other group members? Despite much research regarding how animals and humans solve social problems, few studies have utilized comparable procedures, outcomes, or measures across different species. Thus, it is difficult to piece together the evolution of decision making, including the roots from which human economic decision making emerged. Recently, a comparative body of decision making research has emerged, relying largely on the methodology of experimental economics in order to address these questions in a cross-species fashion. Experimental economics is an ideal method of inquiry for this approach. It is a well-developed method for distilling complex decision making involving multiple conspecifics whose decisions are contingent upon one another into a series of simple decision choices. This allows these decisions to be compared across species and contexts. In particular, our group has used this approach to investigate coordination in New World monkeys, Old World monkeys, and great apes (including humans), using identical methods. We find that in some cases there are remarkable continuities of outcome, as when some pairs in all species solved a coordination game, the Assurance game. On the other hand, we also find that these similarities in outcomes are likely driven by differences in underlying cognitive mechanisms. New World monkeys required exogenous information about their partners' choices in order to solve the task, indicating that they were using a matching strategy. Old World monkeys, on the other hand, solved the task without exogenous cues, leading to investigations into what mechanisms may be underpinning their responses (e.g., reward maximization, strategy formation, etc.). Great apes showed a strong experience effect, with cognitively enriched apes following what appears to be a strategy. Finally, humans were able to solve the task with or without exogenous cues. However, when given the chance to do so, they incorporated an additional mechanism unavailable to the other primates - language - to coordinate outcomes with their partner. We discuss how these results inform not only comparative psychology, but also evolutionary psychology, as they provide an understanding of the evolution of human economic behavior, and the evolution of decision making more broadly.

Supply chain optimization for pediatric perioperative departments.

PubMed

Davis, Janice L; Doyle, Robert

2011-09-01

Economic challenges compel pediatric perioperative departments to reduce nonlabor supply costs while maintaining the quality of patient care. Optimization of the supply chain introduces a framework for decision making that drives fiscally responsible decisions. The cost-effective supply chain is driven by implementing a value analysis process for product selection, being mindful of product sourcing decisions to reduce supply expense, creating logistical efficiency that will eliminate redundant processes, and managing inventory to ensure product availability. The value analysis approach is an analytical methodology for product selection that involves product evaluation and recommendation based on consideration of clinical benefit, overall financial impact, and revenue implications. Copyright © 2011 AORN, Inc. Published by Elsevier Inc. All rights reserved.

Sustainability in health care by allocating resources effectively (SHARE) 3: examining how resource allocation decisions are made, implemented and evaluated in a local healthcare setting.

PubMed

Harris, Claire; Allen, Kelly; Waller, Cara; Brooke, Vanessa

2017-05-09

This is the third in a series of papers reporting a program of Sustainability in Health care by Allocating Resources Effectively (SHARE) in a local healthcare setting. Leaders in a large Australian health service planned to establish an organisation-wide, systematic, integrated, evidence-based approach to disinvestment. In order to introduce new systems and processes for disinvestment into existing decision-making infrastructure, we aimed to understand where, how and by whom resource allocation decisions were made, implemented and evaluated. We also sought the knowledge and experience of staff regarding previous disinvestment activities. Structured interviews, workshops and document analysis were used to collect information from multiple sources in an environmental scan of decision-making systems and processes. Findings were synthesised using a theoretical framework. Sixty-eight respondents participated in interviews and workshops. Eight components in the process of resource allocation were identified: Governance, Administration, Stakeholder engagement, Resources, Decision-making, Implementation, Evaluation and, where appropriate, Reinvestment of savings. Elements of structure and practice for each component are described and a new framework was developed to capture the relationships between them. A range of decision-makers, decision-making settings, type and scope of decisions, criteria used, and strengths, weaknesses, barriers and enablers are outlined. The term 'disinvestment' was not used in health service decision-making. Previous projects that involved removal, reduction or restriction of current practices were driven by quality and safety issues, evidence-based practice or a need to find resource savings and not by initiatives where the primary aim was to disinvest. Measuring resource savings is difficult, in some situations impossible. Savings are often only theoretical as resources released may be utilised immediately by patients waiting for beds, clinic appointments or surgery. Decision-making systems and processes for resource allocation are more complex than assumed in previous studies. There is a wide range of decision-makers, settings, scope and type of decisions, and criteria used for allocating resources within a single institution. To our knowledge, this is the first paper to report this level of detail and to introduce eight components of the resource allocation process identified within a local health service.

A Mixed Methods Bounded Case Study: Data-Driven Decision Making within Professional Learning Communities for Response to Intervention

ERIC Educational Resources Information Center

Rodriguez, Gabriel R.

2017-01-01

A growing number of schools are implementing PLCs to address school improvement, staff engage with data to identify student needs and determine instructional interventions. This is a starting point for engaging in the iterative process of learning for the teach in order to increase student learning (Hord & Sommers, 2008). The iterative process…

An Academic Innovation: The Executive Ph.D. in Urban Higher Education at a Historically Black University

ERIC Educational Resources Information Center

Stevenson, Joseph Martin; Payne, Alfredda Hunt

2016-01-01

This chapter describes how data analysis and data-driven decision making were critical for designing, developing, and assessing a new academic program. The authors--one, the program's founder; the other, an alumna--begin by highlighting some of the elements in the program's incubation and, subsequently, describe some of the components for data…

Conditions for Effective Data Use to Improve Schools: Recommendations for School Leaders

ERIC Educational Resources Information Center

Lange, Christine; Range, Bret; Welsh, Kate

2012-01-01

Although data driven-decision making has been the mantra of school reform for the last 10 years, school leaders benefit from frequent discussions in how to engage teachers in the process. As a result, the purpose of this paper is to apply Reeves' (2004) framework concerning Antecedents of Excellence in creating a school culture that routinely uses…

The Evolution of Big Data and Learning Analytics in American Higher Education

ERIC Educational Resources Information Center

Picciano, Anthony G.

2012-01-01

Data-driven decision making, popularized in the 1980s and 1990s, is evolving into a vastly more sophisticated concept known as big data that relies on software approaches generally referred to as analytics. Big data and analytics for instructional applications are in their infancy and will take a few years to mature, although their presence is…

Are Irrational Reactions to Unfairness Truly Emotionally-Driven? Dissociated Behavioural and Emotional Responses in the Ultimatum Game Task

ERIC Educational Resources Information Center

Civai, Claudia; Corradi-Dell'Acqua, Corrado; Gamer, Matthias; Rumiati, Raffaella I.

2010-01-01

The "irrational" rejections of unfair offers by people playing the Ultimatum Game (UG), a widely used laboratory model of economical decision-making, have traditionally been associated with negative emotions, such as frustration, elicited by unfairness ([Sanfey et al., 2003] and [van't Wout et al., 2006]). We recorded skin conductance responses as…

Comparative Research: An Approach to Teaching Research Methods in Political Science and Public Administration

ERIC Educational Resources Information Center

Engbers, Trent A

2016-01-01

The teaching of research methods has been at the core of public administration education for almost 30 years. But since 1990, this journal has published only two articles on the teaching of research methods. Given the increasing emphasis on data driven decision-making, greater insight is needed into the best practices for teaching public…

Ethical and Appropriate Data Use Requires Data Literacy

ERIC Educational Resources Information Center

Mandinach, Ellen B.; Parton, Brennan M.; Gummer, Edith S.; Anderson, Rachel

2015-01-01

Data use should be a continuous, integrated part of practice, a tool that is used all the time. Good teachers have been doing data-driven decision making all along, it just has not been recognized by that term. But there is more work to be done to ensure that educators know how to continuously, effectively, and ethically use data; that is, to help…

The Elementary School Success Profile Model of Assessment and Prevention: Balancing Effective Practice Standards and Feasibility

ERIC Educational Resources Information Center

Bowen, Natasha K.; Powers, Joelle D.

2011-01-01

Evidence-based practice and data-driven decision making (DDDM) are two approaches to accountability that have been promoted in the school literature. In spite of the push to promote these approaches in schools, barriers to their widespread, appropriate, and effective use have limited their impact on practice and student outcomes. This article…

Involving Teachers in Data-Driven Decision Making: Using Computer Data Systems to Support Teacher Inquiry and Reflection

ERIC Educational Resources Information Center

Wayman, Jeffrey C.

2005-01-01

Accountability mandates such as No Child Left Behind (NCLB) have drawn attention to the practical use of student data for school improvement. Nevertheless, schools may struggle with these mandates because student data are often stored in forms that are difficult to access, manipulate, and interpret. Such access barriers additionally preclude the…

How Leaders Can Support Teachers with Data-Driven Decision Making: A Framework for Understanding Capacity Building

ERIC Educational Resources Information Center

Marsh, Julie A.; Farrell, Caitlin C.

2015-01-01

As accountability systems have increased demands for evidence of student learning, the use of data in education has become more prevalent in many countries. Although school and administrative leaders are recognizing the need to provide support to teachers on how to interpret and respond to data, there is little theoretically sound research on…

Capacity Enablers and Barriers for Learning Analytics: Implications for Policy and Practice

ERIC Educational Resources Information Center

Wolf, Mary Ann; Jones, Rachel; Hall, Sara; Wise, Bob

2014-01-01

The field of learning analytics is being discussed in many circles as an emerging concept in education. In many districts and states, the core philosophy behind learning analytics is not entirely new; for more than a decade, discussions of data-driven decision making and the use of data to drive instruction have been common. Still, the U.S.…

Simultaneous modeling of visual saliency and value computation improves predictions of economic choice.

PubMed

Towal, R Blythe; Mormann, Milica; Koch, Christof

2013-10-01

Many decisions we make require visually identifying and evaluating numerous alternatives quickly. These usually vary in reward, or value, and in low-level visual properties, such as saliency. Both saliency and value influence the final decision. In particular, saliency affects fixation locations and durations, which are predictive of choices. However, it is unknown how saliency propagates to the final decision. Moreover, the relative influence of saliency and value is unclear. Here we address these questions with an integrated model that combines a perceptual decision process about where and when to look with an economic decision process about what to choose. The perceptual decision process is modeled as a drift-diffusion model (DDM) process for each alternative. Using psychophysical data from a multiple-alternative, forced-choice task, in which subjects have to pick one food item from a crowded display via eye movements, we test four models where each DDM process is driven by (i) saliency or (ii) value alone or (iii) an additive or (iv) a multiplicative combination of both. We find that models including both saliency and value weighted in a one-third to two-thirds ratio (saliency-to-value) significantly outperform models based on either quantity alone. These eye fixation patterns modulate an economic decision process, also described as a DDM process driven by value. Our combined model quantitatively explains fixation patterns and choices with similar or better accuracy than previous models, suggesting that visual saliency has a smaller, but significant, influence than value and that saliency affects choices indirectly through perceptual decisions that modulate economic decisions.

Simultaneous modeling of visual saliency and value computation improves predictions of economic choice

PubMed Central

Towal, R. Blythe; Mormann, Milica; Koch, Christof

2013-01-01

Many decisions we make require visually identifying and evaluating numerous alternatives quickly. These usually vary in reward, or value, and in low-level visual properties, such as saliency. Both saliency and value influence the final decision. In particular, saliency affects fixation locations and durations, which are predictive of choices. However, it is unknown how saliency propagates to the final decision. Moreover, the relative influence of saliency and value is unclear. Here we address these questions with an integrated model that combines a perceptual decision process about where and when to look with an economic decision process about what to choose. The perceptual decision process is modeled as a drift–diffusion model (DDM) process for each alternative. Using psychophysical data from a multiple-alternative, forced-choice task, in which subjects have to pick one food item from a crowded display via eye movements, we test four models where each DDM process is driven by (i) saliency or (ii) value alone or (iii) an additive or (iv) a multiplicative combination of both. We find that models including both saliency and value weighted in a one-third to two-thirds ratio (saliency-to-value) significantly outperform models based on either quantity alone. These eye fixation patterns modulate an economic decision process, also described as a DDM process driven by value. Our combined model quantitatively explains fixation patterns and choices with similar or better accuracy than previous models, suggesting that visual saliency has a smaller, but significant, influence than value and that saliency affects choices indirectly through perceptual decisions that modulate economic decisions. PMID:24019496

Visualization and Analysis for Near-Real-Time Decision Making in Distributed Workflows

DOE PAGES

Pugmire, David; Kress, James; Choi, Jong; ...

2016-08-04

Data driven science is becoming increasingly more common, complex, and is placing tremendous stresses on visualization and analysis frameworks. Data sources producing 10GB per second (and more) are becoming increasingly commonplace in both simulation, sensor and experimental sciences. These data sources, which are often distributed around the world, must be analyzed by teams of scientists that are also distributed. Enabling scientists to view, query and interact with such large volumes of data in near-real-time requires a rich fusion of visualization and analysis techniques, middleware and workflow systems. Here, this paper discusses initial research into visualization and analysis of distributed datamore » workflows that enables scientists to make near-real-time decisions of large volumes of time varying data.« less

An early warning and control system for urban, drinking water quality protection: China's experience.

PubMed

Hou, Dibo; Song, Xiaoxuan; Zhang, Guangxin; Zhang, Hongjian; Loaiciga, Hugo

2013-07-01

An event-driven, urban, drinking water quality early warning and control system (DEWS) is proposed to cope with China's urgent need for protecting its urban drinking water. The DEWS has a web service structure and provides users with water quality monitoring functions, water quality early warning functions, and water quality accident decision-making functions. The DEWS functionality is guided by the principles of control theory and risk assessment as applied to the feedback control of urban water supply systems. The DEWS has been deployed in several large Chinese cities and found to perform well insofar as water quality early warning and emergency decision-making is concerned. This paper describes a DEWS for urban water quality protection that has been developed in China.

A rational framework for production decision making in blood establishments.

PubMed

Ramoa, Augusto; Maia, Salomé; Lourenço, Anália

2012-07-24

SAD_BaSe is a blood bank data analysis software, created to assist in the management of blood donations and the blood production chain in blood establishments. In particular, the system keeps track of several collection and production indicators, enables the definition of collection and production strategies, and the measurement of quality indicators required by the Quality Management System regulating the general operation of blood establishments. This paper describes the general scenario of blood establishments and its main requirements in terms of data management and analysis. It presents the architecture of SAD_BaSe and identifies its main contributions. Specifically, it brings forward the generation of customized reports driven by decision making needs and the use of data mining techniques in the analysis of donor suspensions and donation discards.

A Rational Framework for Production Decision Making in Blood Establishments.

PubMed

Ramoa, Augusto; Maia, Salomé; Lourenço, Anália

2012-12-01

SAD_BaSe is a blood bank data analysis software, created to assist in the management of blood donations and the blood production chain in blood establishments. In particular, the system keeps track of several collection and production indicators, enables the definition of collection and production strategies, and the measurement of quality indicators required by the Quality Management System regulating the general operation of blood establishments. This paper describes the general scenario of blood establishments and its main requirements in terms of data management and analysis. It presents the architecture of SAD_BaSe and identifies its main contributions. Specifically, it brings forward the generation of customized reports driven by decision making needs and the use of data mining techniques in the analysis of donor suspensions and donation discards.

Avoiding boredom: Caudate and insula activity reflects boredom-elicited purchase bias.

PubMed

Dal Mas, Dennis E; Wittmann, Bianca C

2017-07-01

People show a strong tendency to avoid boring situations, but the neural systems mediating this behavioural bias are yet unknown. We used functional magnetic resonance imaging (fMRI) to investigate how the anticipation of a boring task influences decisions to purchase entertainment. Participants accepted higher prices to avoid boredom compared to control tasks, and individual differences in boredom experience predicted the increase in price. This behavioural bias was associated with higher activity in the caudate nucleus during music purchases driven by boredom avoidance. Insula activation was increased during performance of the boring task and subsequently associated with individual differences in boredom-related decision making. These results identify a mechanism that drives decisions to avoid boring situations and potentially underlies consumer decisions. Copyright © 2017 Elsevier Ltd. All rights reserved.

How much are you prepared to PAY for a forecast?

NASA Astrophysics Data System (ADS)

Arnal, Louise; Coughlan, Erin; Ramos, Maria-Helena; Pappenberger, Florian; Wetterhall, Fredrik; Bachofen, Carina; van Andel, Schalk Jan

2015-04-01

Probabilistic hydro-meteorological forecasts are a crucial element of the decision-making chain in the field of flood prevention. The operational use of probabilistic forecasts is increasingly promoted through the development of new novel state-of-the-art forecast methods and numerical skill is continuously increasing. However, the value of such forecasts for flood early-warning systems is a topic of diverging opinions. Indeed, the word value, when applied to flood forecasting, is multifaceted. It refers, not only to the raw cost of acquiring and maintaining a probabilistic forecasting system (in terms of human and financial resources, data volume and computational time), but also and most importantly perhaps, to the use of such products. This game aims at investigating this point. It is a willingness to pay game, embedded in a risk-based decision-making experiment. Based on a ``Red Cross/Red Crescent, Climate Centre'' game, it is a contribution to the international Hydrologic Ensemble Prediction Experiment (HEPEX). A limited number of probabilistic forecasts will be auctioned to the participants; the price of these forecasts being market driven. All participants (irrespective of having bought or not a forecast set) will then be taken through a decision-making process to issue warnings for extreme rainfall. This game will promote discussions around the topic of the value of forecasts for decision-making in the field of flood prevention.

Intuitionistic fuzzy evidential power aggregation operator and its application in multiple criteria decision-making

NASA Astrophysics Data System (ADS)

Jiang, Wen; Wei, Boya

2018-02-01

The theory of intuitionistic fuzzy sets (IFS) is widely used for dealing with vagueness and the Dempster-Shafer (D-S) evidence theory has a widespread use in multiple criteria decision-making problems under uncertain situation. However, there are many methods to aggregate intuitionistic fuzzy numbers (IFNs), but the aggregation operator to fuse basic probability assignment (BPA) is rare. Power average (P-A) operator, as a powerful operator, is useful and important in information fusion. Motivated by the idea of P-A power, in this paper, a new operator based on the IFS and D-S evidence theory is proposed, which is named as intuitionistic fuzzy evidential power average (IFEPA) aggregation operator. First, an IFN is converted into a BPA, and the uncertainty is measured in D-S evidence theory. Second, the difference between BPAs is measured by Jousselme distance and a satisfying support function is proposed to get the support degree between each other effectively. Then the IFEPA operator is used for aggregating the original IFN and make a more reasonable decision. The proposed method is objective and reasonable because it is completely driven by data once some parameters are required. At the same time, it is novel and interesting. Finally, an application of developed models to the 'One Belt, One road' investment decision-making problems is presented to illustrate the effectiveness and feasibility of the proposed operator.

Brain responses to social norms: Meta-analyses of fMRI studies.

PubMed

Zinchenko, Oksana; Arsalidou, Marie

2018-02-01

Social norms have a critical role in everyday decision-making, as frequent interaction with others regulates our behavior. Neuroimaging studies show that social-based and fairness-related decision-making activates an inconsistent set of areas, which sometimes includes the anterior insula, anterior cingulate cortex, and others lateral prefrontal cortices. Social-based decision-making is complex and variability in findings may be driven by socio-cognitive activities related to social norms. To distinguish among social-cognitive activities related to social norms, we identified 36 eligible articles in the functional magnetic resonance imaging (fMRI) literature, which we separate into two categories (a) social norm representation and (b) norm violations. The majority of original articles (>60%) used tasks associated with fairness norms and decision-making, such as ultimatum game, dictator game, or prisoner's dilemma; the rest used tasks associated to violation of moral norms, such as scenarios and sentences of moral depravity ratings. Using quantitative meta-analyses, we report common and distinct brain areas that show concordance as a function of category. Specifically, concordance in ventromedial prefrontal regions is distinct to social norm representation processing, whereas concordance in right insula, dorsolateral prefrontal, and dorsal cingulate cortices is distinct to norm violation processing. We propose a neurocognitive model of social norms for healthy adults, which could help guide future research in social norm compliance and mechanisms of its enforcement. © 2017 Wiley Periodicals, Inc.

Optimal information networks: Application for data-driven integrated health in populations

PubMed Central

Servadio, Joseph L.; Convertino, Matteo

2018-01-01

Development of composite indicators for integrated health in populations typically relies on a priori assumptions rather than model-free, data-driven evidence. Traditional variable selection processes tend not to consider relatedness and redundancy among variables, instead considering only individual correlations. In addition, a unified method for assessing integrated health statuses of populations is lacking, making systematic comparison among populations impossible. We propose the use of maximum entropy networks (MENets) that use transfer entropy to assess interrelatedness among selected variables considered for inclusion in a composite indicator. We also define optimal information networks (OINs) that are scale-invariant MENets, which use the information in constructed networks for optimal decision-making. Health outcome data from multiple cities in the United States are applied to this method to create a systemic health indicator, representing integrated health in a city. PMID:29423440

Hypothesis-driven physical examination curriculum.

PubMed

Allen, Sharon; Olson, Andrew; Menk, Jeremiah; Nixon, James

2017-12-01

Medical students traditionally learn physical examination skills as a rote list of manoeuvres. Alternatives like hypothesis-driven physical examination (HDPE) may promote students' understanding of the contribution of physical examination to diagnostic reasoning. We sought to determine whether first-year medical students can effectively learn to perform a physical examination using an HDPE approach, and then tailor the examination to specific clinical scenarios. Medical students traditionally learn physical examination skills as a rote list of manoeuvres CONTEXT: First-year medical students at the University of Minnesota were taught both traditional and HDPE approaches during a required 17-week clinical skills course in their first semester. The end-of-course evaluation assessed HDPE skills: students were assigned one of two cardiopulmonary cases. Each case included two diagnostic hypotheses. During an interaction with a standardised patient, students were asked to select physical examination manoeuvres in order to make a final diagnosis. Items were weighted and selection order was recorded. First-year students with minimal pathophysiology performed well. All students selected the correct diagnosis. Importantly, students varied the order when selecting examination manoeuvres depending on the diagnoses under consideration, demonstrating early clinical decision-making skills. An early introduction to HDPE may reinforce physical examination skills for hypothesis generation and testing, and can foster early clinical decision-making skills. This has important implications for further research in physical examination instruction. © 2016 John Wiley & Sons Ltd and The Association for the Study of Medical Education.

Consideration of reference points for the management of renewable resources under an adaptive management paradigm

USGS Publications Warehouse

Irwin, Brian J.; Conroy, Michael J.

2013-01-01

The success of natural resource management depends on monitoring, assessment and enforcement. In support of these efforts, reference points (RPs) are often viewed as critical values of management-relevant indicators. This paper considers RPs from the standpoint of objective-driven decision making in dynamic resource systems, guided by principles of structured decision making (SDM) and adaptive resource management (AM). During the development of natural resource policy, RPs have been variously treated as either ‘targets’ or ‘triggers’. Under a SDM/AM paradigm, target RPs correspond approximately to value-based objectives, which may in turn be either of fundamental interest to stakeholders or intermediaries to other central objectives. By contrast, trigger RPs correspond to decision rules that are presumed to lead to desirable outcomes (such as the programme targets). Casting RPs as triggers or targets within a SDM framework is helpful towards clarifying why (or whether) a particular metric is appropriate. Further, the benefits of a SDM/AM process include elucidation of underlying untested assumptions that may reveal alternative metrics for use as RPs. Likewise, a structured decision-analytic framework may also reveal that failure to achieve management goals is not because the metrics are wrong, but because the decision-making process in which they are embedded is insufficiently robust to uncertainty, is not efficiently directed at producing a resource objective, or is incapable of adaptation to new knowledge.

CHAMPION: Intelligent Hierarchical Reasoning Agents for Enhanced Decision Support

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

Hohimer, Ryan E.; Greitzer, Frank L.; Noonan, Christine F.

2011-11-15

We describe the design and development of an advanced reasoning framework employing semantic technologies, organized within a hierarchy of computational reasoning agents that interpret domain specific information. Designed based on an inspirational metaphor of the pattern recognition functions performed by the human neocortex, the CHAMPION reasoning framework represents a new computational modeling approach that derives invariant knowledge representations through memory-prediction belief propagation processes that are driven by formal ontological language specification and semantic technologies. The CHAMPION framework shows promise for enhancing complex decision making in diverse problem domains including cyber security, nonproliferation and energy consumption analysis.

A Quantum-Like View to a Generalized Two Players Game

NASA Astrophysics Data System (ADS)

Bagarello, F.

2015-10-01

This paper consider the possibility of using some quantum tools in decision making strategies. In particular, we consider here a dynamical open quantum system helping two players, and , to take their decisions in a specific context. We see that, within our approach, the final choices of the players do not depend in general on their initial mental states, but they are driven essentially by the environment which interacts with them. The model proposed here also considers interactions of different nature between the two players, and it is simple enough to allow for an analytical solution of the equations of motion.

The data life cycle applied to our own data.

PubMed

Goben, Abigail; Raszewski, Rebecca

2015-01-01

Increased demand for data-driven decision making is driving the need for librarians to be facile with the data life cycle. This case study follows the migration of reference desk statistics from handwritten to digital format. This shift presented two opportunities: first, the availability of a nonsensitive data set to improve the librarians' understanding of data-management and statistical analysis skills, and second, the use of analytics to directly inform staffing decisions and departmental strategic goals. By working through each step of the data life cycle, library faculty explored data gathering, storage, sharing, and analysis questions.

Specific Barriers and Drivers in Different Stages of Decision-Making about Energy Efficiency Upgrades in Private Homes

PubMed Central

Klöckner, Christian A.; Nayum, Alim

2016-01-01

Energy efficiency upgrades of privately owned homes like adding to the insulation layers in the walls, roof or floor, or replacing windows with more efficiently insulated versions can contribute significantly to reducing the energy impact of the building sector and thus also the CO2 footprint of a household. However, even in countries like Norway that have a rather high rate of renovation, energy upgrades are not always integrated into such a refurbishment project. This study tests which structural and internal psychological barriers hinder and which drivers foster decision-making to implement such measures, once a renovation project is planned. With a theoretical background in stage-based models of decision-making 24 barriers and drivers were tested for their specific effect in the stages of decision-making. The four stages of decision-making assumed in this study were (1) “not being in a decision mode,” (2) “deciding what to do,” (3) “deciding how to do it,” and (4) “planning implementation.” Based on an online survey of 3787 Norwegian households, it was found that the most important barriers toward deciding to implement energy efficiency upgrades were not owning the dwelling and feeling the right time had not come yet. The most important drivers of starting to decide were higher expected comfort levels, better expected living conditions, and an expected reduction of energy costs. For the transition from deciding what to do to how to do it, not managing to make a decision and feeling the right point in time has not come yet were the strongest barriers, easily accessible information and an expected reduction of energy costs were the most important drivers. The final transition from deciding how to do the upgrades to planning implementation was driven by expecting a payoff within a reasonable time frame and higher expected comfort levels; the most important barriers were time demands for supervising contractors and—again—a feeling that the right point in time has not come yet. Implications for policy-making and marketing are discussed. PMID:27660618

Specific Barriers and Drivers in Different Stages of Decision-Making about Energy Efficiency Upgrades in Private Homes.

PubMed

Klöckner, Christian A; Nayum, Alim

2016-01-01

Energy efficiency upgrades of privately owned homes like adding to the insulation layers in the walls, roof or floor, or replacing windows with more efficiently insulated versions can contribute significantly to reducing the energy impact of the building sector and thus also the CO2 footprint of a household. However, even in countries like Norway that have a rather high rate of renovation, energy upgrades are not always integrated into such a refurbishment project. This study tests which structural and internal psychological barriers hinder and which drivers foster decision-making to implement such measures, once a renovation project is planned. With a theoretical background in stage-based models of decision-making 24 barriers and drivers were tested for their specific effect in the stages of decision-making. The four stages of decision-making assumed in this study were (1) "not being in a decision mode," (2) "deciding what to do," (3) "deciding how to do it," and (4) "planning implementation." Based on an online survey of 3787 Norwegian households, it was found that the most important barriers toward deciding to implement energy efficiency upgrades were not owning the dwelling and feeling the right time had not come yet. The most important drivers of starting to decide were higher expected comfort levels, better expected living conditions, and an expected reduction of energy costs. For the transition from deciding what to do to how to do it, not managing to make a decision and feeling the right point in time has not come yet were the strongest barriers, easily accessible information and an expected reduction of energy costs were the most important drivers. The final transition from deciding how to do the upgrades to planning implementation was driven by expecting a payoff within a reasonable time frame and higher expected comfort levels; the most important barriers were time demands for supervising contractors and-again-a feeling that the right point in time has not come yet. Implications for policy-making and marketing are discussed.

Projecting Future Land Use Changes in West Africa Driven by Climate and Socioeconomic Factors: Uncertainties and Implications for Adaptation

NASA Astrophysics Data System (ADS)

Wang, G.; Ahmed, K. F.; You, L.

2015-12-01

Land use changes constitute an important regional climate change forcing in West Africa, a region of strong land-atmosphere coupling. At the same time, climate change can be an important driver for land use, although its importance relative to the impact of socio-economic factors may vary significant from region to region. This study compares the contributions of climate change and socioeconomic development to potential future changes of agricultural land use in West Africa and examines various sources of uncertainty using a land use projection model (LandPro) that accounts for the impact of socioeconomic drivers on the demand side and the impact of climate-induced crop yield changes on the supply side. Future crop yield changes were simulated by a process-based crop model driven with future climate projections from a regional climate model, and future changes of food demand is projected using a model for policy analysis of agricultural commodities and trade. The impact of human decision-making on land use was explicitly considered through multiple "what-if" scenarios to examine the range of uncertainties in projecting future land use. Without agricultural intensification, the climate-induced decrease of crop yield together with increase of food demand are found to cause a significant increase in agricultural land use at the expense of forest and grassland by the mid-century, and the resulting land use land cover changes are found to feed back to the regional climate in a way that exacerbates the negative impact of climate on crop yield. Analysis of results from multiple decision-making scenarios suggests that human adaptation characterized by science-informed decision making to minimize land use could be very effective in many parts of the region.

Shared decision making in the recovery of people with schizophrenia: the role of metacognitive capacities in insight and pragmatic language use.

PubMed

Chan, Kevin K S; Mak, Winnie W S

2012-08-01

In the development of consumer-centered care for mental health consumers with schizophrenia, one key ingredient is consumer participation in health care decisions together with their healthcare providers, termed "shared decision making" (SDM). SDM requires consumers to form a number of complex ideas about themselves and their providers then use that knowledge to make sense of the illness and reach medical and psychosocial decisions. However, metacognitive deficits widely observed in schizophrenia might lead to poor insight and pragmatic language deficits in some consumers, disrupting the whole process by which a personal and consensually valid narrative account of psychiatric challenges is synthesized and flexibly evolved. Given the current understanding that it is possible to improve metacognition, in this article we summarize how Metacognitive Training (MCT) and individual psychotherapy could potentially be tailored, or modified, to help consumers to develop metacognitive capacities with an end goal of facilitating the SDM process. Consistent with the principles of consumer-defined recovery, we also suggest a strategy for engaging consumers in SDM dialogue based on "where the consumers are at". Providers are advised to be cognizant of their medically driven perspective and attempt to work with the consumers in the perspective of the consumers' own recovery goals. Copyright © 2012 Elsevier Ltd. All rights reserved.

Knowledge Management Implementation and the Tools Utilized in Healthcare for Evidence-Based Decision Making: A Systematic Review.

PubMed

Shahmoradi, Leila; Safadari, Reza; Jimma, Worku

2017-09-01

Healthcare is a knowledge driven process and thus knowledge management and the tools to manage knowledge in healthcare sector are gaining attention. The aim of this systematic review is to investigate knowledge management implementation and knowledge management tools used in healthcare for informed decision making. Three databases, two journals websites and Google Scholar were used as sources for the review. The key terms used to search relevant articles include: "Healthcare and Knowledge Management"; "Knowledge Management Tools in Healthcare" and "Community of Practices in healthcare". It was found that utilization of knowledge management in healthcare is encouraging. There exist numbers of opportunities for knowledge management implementation, though there are some barriers as well. Some of the opportunities that can transform healthcare are advances in health information and communication technology, clinical decision support systems, electronic health record systems, communities of practice and advanced care planning. Providing the right knowledge at the right time, i.e., at the point of decision making by implementing knowledge management in healthcare is paramount. To do so, it is very important to use appropriate tools for knowledge management and user-friendly system because it can significantly improve the quality and safety of care provided for patients both at hospital and home settings.

Building Capacity for Data-Driven Decision Making in African HIV Testing Programs: Field Perspectives on Data Use Workshops.

PubMed

Courtenay-Quirk, Cari; Spindler, Hilary; Leidich, Aimee; Bachanas, Pam

2016-12-01

Strategic, high quality HIV testing services (HTS) delivery is an essential step towards reaching the end of AIDS by 2030. We conducted HTS Data Use workshops in five African countries to increase data use for strategic program decision-making. Feedback was collected on the extent to which workshop skills and tools were applied in practice and to identify future capacity-building needs. We later conducted six semistructured phone interviews with workshop planning teams and sent a web-based survey to 92 past participants. The HTS Data Use workshops provided accessible tools that were readily learned by most respondents. While most respondents reported increased confidence in interpreting data and frequency of using such tools over time, planning team representatives indicated ongoing needs for more automated tools that can function across data systems. To achieve ambitious global HIV/AIDS targets, national decision makers may continue to seek tools and skill-building opportunities to monitor programs and identify opportunities to refine strategies.

IDEA at Age Forty: Weathering Common Core Standards and Data Driven Decision Making

ERIC Educational Resources Information Center

Bicehouse, Vaughn; Faieta, Jean

2017-01-01

Special education, a discipline that aims to provide specialized instruction to meet the unique needs of each child with a disability, has turned 40 years old in the United States. Ever since the passage of the Education for All Handicapped Children Act (P.L. 94-142) in 1975, every state has been directed to provide a free and appropriate…

A Team Approach to Data-Driven Decision-Making Literacy Instruction in Preschool Classrooms: Child Assessment and Intervention through Classroom Team Self-Reflection

ERIC Educational Resources Information Center

Abbott, Mary; Beecher, Constance; Petersen, Sarah; Greenwood, Charles R.; Atwater, Jane

2017-01-01

Many schools around the country are getting positive responses implementing Response to Intervention (RTI) within a Multi-Tiered System of Support (MTSS) framework (e.g., Abbott, 2011; Ball & Trammell, 2011; Buysee & Peisner-Feinberg, 2009). RTI refers to an instructional model that is based on a student's response to instruction. RTI…

Big(ger) Data as Better Data in Open Distance Learning

ERIC Educational Resources Information Center

Prinsloo, Paul; Archer, Elizabeth; Barnes, Glen; Chetty, Yuraisha; van Zyl, Dion

2015-01-01

In the context of the hype, promise and perils of Big Data and the currently dominant paradigm of data-driven decision-making, it is important to critically engage with the potential of Big Data for higher education. We do not question the potential of Big Data, but we do raise a number of issues, and present a number of theses to be seriously…

Child-Bearing Decision Making Among Women Previously Treated for Breast Cancer

DTIC Science & Technology

1997-04-01

this kind of study is an essential preliminary step to developing meaningful theory-driven psychosocial research on the issues of childbearing among...than older women with the disease and may experience unique vulnerability factors. Adult developmental theory ( Erikson , 1963; Levinson, Darrow, Klein...variety of developmental tasks characterize different stages of the adult life cycle. Several significant tasks for younger women are likely to be

Preparing for Decision-Making: Training for Effective School-Based Budgeting in Los Angeles, Chicago, and Denver.

ERIC Educational Resources Information Center

Lauber, Diana; Warden, Christine

So that New York City could build on the experiences of other large cities as it implemented Performance Driven Budgeting (PDB) in the schools, a study was conducted of the school based budgeting training in Los Angeles, Chicago, and Denver. These districts have from 6 to 10 years experience in site-based budgeting. The study is based on…

From Vision to Action: How School Districts Use Data to Improve Performance. 3D: Data-Driven Decision Making

ERIC Educational Resources Information Center

Henke, Karen Greenwood

2005-01-01

With the passage of "No Child Left Behind" in 2001, schools are expected to provide a standards-based curriculum for students to attain math and reading proficiency and demonstrate progress each year. "NCLB" requires more frequent student testing with publicly reported results in an effort to close the achievement gap and to inform parents,…

The Impact of Data-Driven Decision Making on Educational Practice in Louisiana Schools

ERIC Educational Resources Information Center

James-Maxie, Dana

2012-01-01

Using data to improve educational practice in schools has become a popular reform strategy that has grown as a result of the No Child Left Behind Act of 2001. Districts and schools across the United States are under a great deal of pressure to collect and analyze data in hopes of identifying student weaknesses to implement corrective action plans…

Clinical Note Creation, Binning, and Artificial Intelligence

PubMed Central

Deliberato, Rodrigo Octávio; Stone, David J

2017-01-01

The creation of medical notes in software applications poses an intrinsic problem in workflow as the technology inherently intervenes in the processes of collecting and assembling information, as well as the production of a data-driven note that meets both individual and healthcare system requirements. In addition, the note writing applications in currently available electronic health records (EHRs) do not function to support decision making to any substantial degree. We suggest that artificial intelligence (AI) could be utilized to facilitate the workflows of the data collection and assembly processes, as well as to support the development of personalized, yet data-driven assessments and plans. PMID:28778845

Differences in neural activation as a function of risk-taking task parameters.

PubMed

Congdon, Eliza; Bato, Angelica A; Schonberg, Tom; Mumford, Jeanette A; Karlsgodt, Katherine H; Sabb, Fred W; London, Edythe D; Cannon, Tyrone D; Bilder, Robert M; Poldrack, Russell A

2013-01-01

Despite evidence supporting a relationship between impulsivity and naturalistic risk-taking, the relationship of impulsivity with laboratory-based measures of risky decision-making remains unclear. One factor contributing to this gap in our understanding is the degree to which different risky decision-making tasks vary in their details. We conducted an fMRI investigation of the Angling Risk Task (ART), which is an improved behavioral measure of risky decision-making. In order to examine whether the observed pattern of neural activation was specific to the ART or generalizable, we also examined correlates of the Balloon Analog Risk Taking (BART) task in the same sample of 23 healthy adults. Exploratory analyses were conducted to examine the relationship between neural activation, performance, impulsivity and self-reported risk-taking. While activation in a valuation network was associated with reward tracking during the ART but not the BART, increased fronto-cingulate activation was seen during risky choice trials in the BART as compared to the ART. Thus, neural activation during risky decision-making trials differed between the two tasks, and this observation was likely driven by differences in task parameters, namely the absence vs. presence of ambiguity and/or stationary vs. increasing probability of loss on the ART and BART, respectively. Exploratory association analyses suggest that sensitivity of neural response to the magnitude of potential reward during the ART was associated with a suboptimal performance strategy, higher scores on a scale of dysfunctional impulsivity (DI) and a greater likelihood of engaging in risky behaviors, while this pattern was not seen for the BART. Our results suggest that the ART is decomposable and associated with distinct patterns of neural activation; this represents a preliminary step toward characterizing a behavioral measure of risky decision-making that may support a better understanding of naturalistic risk-taking.

Limbic Justice—Amygdala Involvement in Immediate Rejection in the Ultimatum Game

PubMed Central

Fransson, Peter; Petrovic, Predrag; Johannesson, Magnus; Ingvar, Martin

2011-01-01

Imaging studies have revealed a putative neural account of emotional bias in decision making. However, it has been difficult in previous studies to identify the causal role of the different sub-regions involved in decision making. The Ultimatum Game (UG) is a game to study the punishment of norm-violating behavior. In a previous influential paper on UG it was suggested that frontal insular cortex has a pivotal role in the rejection response. This view has not been reconciled with a vast literature that attributes a crucial role in emotional decision making to a subcortical structure (i.e., amygdala). In this study we propose an anatomy-informed model that may join these views. We also present a design that detects the functional anatomical response to unfair proposals in a subcortical network that mediates rapid reactive responses. We used a functional MRI paradigm to study the early components of decision making and challenged our paradigm with the introduction of a pharmacological intervention to perturb the elicited behavioral and neural response. Benzodiazepine treatment decreased the rejection rate (from 37.6% to 19.0%) concomitantly with a diminished amygdala response to unfair proposals, and this in spite of an unchanged feeling of unfairness and unchanged insular response. In the control group, rejection was directly linked to an increase in amygdala activity. These results allow a functional anatomical detection of the early neural components of rejection associated with the initial reactive emotional response. Thus, the act of immediate rejection seems to be mediated by the limbic system and is not solely driven by cortical processes, as previously suggested. Our results also prompt an ethical discussion as we demonstrated that a commonly used drug influences core functions in the human brain that underlie individual autonomy and economic decision making. PMID:21559322

Optimal data systems: the future of clinical predictions and decision support.

PubMed

Celi, Leo A; Csete, Marie; Stone, David

2014-10-01

The purpose of the review is to describe the evolving concept and role of data as it relates to clinical predictions and decision-making. Critical care medicine is, as an especially data-rich specialty, becoming acutely cognizant not only of its historic deficits in data utilization but also of its enormous potential for capturing, mining, and leveraging such data into well-designed decision support modalities as well as the formulation of robust best practices. Modern electronic medical records create an opportunity to design complete and functional data systems that can support clinical care to a degree never seen before. Such systems are often referred to as 'data-driven,' but a better term is 'optimal data systems' (ODS). Here we discuss basic features of an ODS and its benefits, including the potential to transform clinical prediction and decision support.

Mentor judgements and decision-making in the assessment of student nurse competence in practice: A mixed-methods study.

PubMed

Burden, Sarah; Topping, Anne Elizabeth; O'Halloran, Catherine

2018-05-01

To investigate how mentors form judgements and reach summative assessment decisions regarding student competence in practice. Competence assessment is a significant component of pre-registration nursing programmes in the United Kingdom. Concerns exist that assessments are subjective, lack consistency and that mentors fail to judge student performance as unsatisfactory. A two-stage sequential embedded mixed-methods design. Data collected 2012-2013. This study involved a whole student cohort completing a UK undergraduate adult nursing programme (N = 41). Stage 1: quantitative data on mentor conduct of assessment interviews and the final decision recorded (N = 330 from 270 mentors) were extracted from student Practice Assessment Documents (PADs). Stage 2: mentor feedback in student PADs was used in Stimulated Recall interviews with a purposive sample of final placement mentors (N = 17). These were thematically analysed. Findings were integrated to develop a theoretically driven model of mentor decision-making. Course assessment strategies and documentation had limited effect in framing mentor judgements and decisions. Rather, mentors amassed impressions, moderated by expectations of an "idealized student" by practice area and programme stage that influenced their management and outcome of the assessment process. These impressions were accumulated and combined into judgements that informed the final decision. This process can best be understood and conceptualized through the Brunswik's lens model of social judgement. Mentor decisions were reasoned and there was a shared understanding of judgement criteria and their importance. This impression-based nature of mentor decision-making questions the reliability and validity of competency-based assessments used in nursing pre-registration programmes. © 2017 John Wiley & Sons Ltd.

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.

A framework to investigate drivers of adaptation decisions in marine fishing: Evidence from urban, semi-urban and rural communities.

PubMed

Malakar, Krishna; Mishra, Trupti; Patwardhan, Anand

2018-05-11

Traditional fishing livelihoods need to adapt to changing fish catch/populations, led by numerous anthropogenic, environmental and climatic stressors. The decision to adapt can be influenced by a variety of socio-economic and perceptual factors. However, adaptation decision-making in fishing communities has rarely been studied. Based on previous literature and focus group discussions with community, this study identifies few prominent adaptation responses in marine fishing and proposes credible factors driving decisions to adopt them. Further, a household survey is conducted, and the association of these drivers with various adaptation strategies is examined among fisherfolk of Maharashtra (India). This statistical analysis is based on 601 responses collected across three regional fishing groups: urban, semi-urban and rural. Regional segregation is done to understand variability in decision-making among groups which might be having different socio-economic and perceptual attributes. The survey reveals that only few urban fishing households have been able to diversify into other livelihoods. While having economic capital increases the likelihood of adaptation among urban and semi-urban communities, rural fishermen are significantly driven by social capital. Perception of climate change affecting fish catch drives adoption of mechanized boats solely in urban region. But increasing number of extreme events affects decisions of semi-urban and rural fishermen. Further, rising pollution and trade competition is associated with adaptation responses in the urban and semi-urban community. Higher education might help fishermen choose convenient forms of adaptation. Also, cooperative membership and subsidies are critical in adaptation decisions. The framework and insights of the study suggest the importance of acknowledging differential decision-making of individuals and communities, for designing effective adaptation and capacity-building policies. Copyright © 2018 Elsevier B.V. All rights reserved.

Spatially explicit multi-criteria decision analysis for managing vector-borne diseases

PubMed Central

2011-01-01

The complex epidemiology of vector-borne diseases creates significant challenges in the design and delivery of prevention and control strategies, especially in light of rapid social and environmental changes. Spatial models for predicting disease risk based on environmental factors such as climate and landscape have been developed for a number of important vector-borne diseases. The resulting risk maps have proven value for highlighting areas for targeting public health programs. However, these methods generally only offer technical information on the spatial distribution of disease risk itself, which may be incomplete for making decisions in a complex situation. In prioritizing surveillance and intervention strategies, decision-makers often also need to consider spatially explicit information on other important dimensions, such as the regional specificity of public acceptance, population vulnerability, resource availability, intervention effectiveness, and land use. There is a need for a unified strategy for supporting public health decision making that integrates available data for assessing spatially explicit disease risk, with other criteria, to implement effective prevention and control strategies. Multi-criteria decision analysis (MCDA) is a decision support tool that allows for the consideration of diverse quantitative and qualitative criteria using both data-driven and qualitative indicators for evaluating alternative strategies with transparency and stakeholder participation. Here we propose a MCDA-based approach to the development of geospatial models and spatially explicit decision support tools for the management of vector-borne diseases. We describe the conceptual framework that MCDA offers as well as technical considerations, approaches to implementation and expected outcomes. We conclude that MCDA is a powerful tool that offers tremendous potential for use in public health decision-making in general and vector-borne disease management in particular. PMID:22206355

The Evolution of System Safety at NASA

NASA Technical Reports Server (NTRS)

Dezfuli, Homayoon; Everett, Chris; Groen, Frank

2014-01-01

The NASA system safety framework is in the process of change, motivated by the desire to promote an objectives-driven approach to system safety that explicitly focuses system safety efforts on system-level safety performance, and serves to unify, in a purposeful manner, safety-related activities that otherwise might be done in a way that results in gaps, redundancies, or unnecessary work. An objectives-driven approach to system safety affords more flexibility to determine, on a system-specific basis, the means by which adequate safety is achieved and verified. Such flexibility and efficiency is becoming increasingly important in the face of evolving engineering modalities and acquisition models, where, for example, NASA will increasingly rely on commercial providers for transportation services to low-earth orbit. A key element of this objectives-driven approach is the use of the risk-informed safety case (RISC): a structured argument, supported by a body of evidence, that provides a compelling, comprehensible and valid case that a system is or will be adequately safe for a given application in a given environment. The RISC addresses each of the objectives defined for the system, providing a rational basis for making informed risk acceptance decisions at relevant decision points in the system life cycle.

Climate Risk Informed Decision Analysis: A Hypothetical Application to the Waas Region

NASA Astrophysics Data System (ADS)

Gilroy, Kristin; Mens, Marjolein; Haasnoot, Marjolijn; Jeuken, Ad

2016-04-01

More frequent and intense hydrologic events under climate change are expected to enhance water security and flood risk management challenges worldwide. Traditional planning approaches must be adapted to address climate change and develop solutions with an appropriate level of robustness and flexibility. The Climate Risk Informed Decision Analysis (CRIDA) method is a novel planning approach embodying a suite of complementary methods, including decision scaling and adaptation pathways. Decision scaling offers a bottom-up approach to assess risk and tailors the complexity of the analysis to the problem at hand and the available capacity. Through adaptation pathway,s an array of future strategies towards climate robustness are developed, ranging in flexibility and immediacy of investments. Flexible pathways include transfer points to other strategies to ensure that the system can be adapted if future conditions vary from those expected. CRIDA combines these two approaches in a stakeholder driven process which guides decision makers through the planning and decision process, taking into account how the confidence in the available science, the consequences in the system, and the capacity of institutions should influence strategy selection. In this presentation, we will explain the CRIDA method and compare it to existing planning processes, such as the US Army Corps of Engineers Principles and Guidelines as well as Integrated Water Resources Management Planning. Then, we will apply the approach to a hypothetical case study for the Waas Region, a large downstream river basin facing rapid development threatened by increased flood risks. Through the case study, we will demonstrate how a stakeholder driven process can be used to evaluate system robustness to climate change; develop adaptation pathways for multiple objectives and criteria; and illustrate how varying levels of confidence, consequences, and capacity would play a role in the decision making process, specifically in regards to the level of robustness and flexibility in the selected strategy. This work will equip practitioners and decision makers with an example of a structured process for decision making under climate uncertainty that can be scaled as needed to the problem at hand. This presentation builds further on another submitted abstract "Climate Risk Informed Decision Analysis (CRIDA): A novel practical guidance for Climate Resilient Investments and Planning" by Jeuken et al.

Mental models: an alternative evaluation of a sensemaking approach to ethics instruction.

PubMed

Brock, Meagan E; Vert, Andrew; Kligyte, Vykinta; Waples, Ethan P; Sevier, Sydney T; Mumford, Michael D

2008-09-01

In spite of the wide variety of approaches to ethics training it is still debatable which approach has the highest potential to enhance professionals' integrity. The current effort assesses a novel curriculum that focuses on metacognitive reasoning strategies researchers use when making sense of day-to-day professional practices that have ethical implications. The evaluated trainings effectiveness was assessed by examining five key sensemaking processes, such as framing, emotion regulation, forecasting, self-reflection, and information integration that experts and novices apply in ethical decision-making. Mental models of trained and untrained graduate students, as well as faculty, working in the field of physical sciences were compared using a think-aloud protocol 6 months following the ethics training. Evaluation and comparison of the mental models of participants provided further validation evidence for sensemaking training. Specifically, it was found that trained students applied metacognitive reasoning strategies learned during training in their ethical decision-making that resulted in complex mental models focused on the objective assessment of the situation. Mental models of faculty and untrained students were externally-driven with a heavy focus on autobiographical processes. The study shows that sensemaking training has a potential to induce shifts in researchers' mental models by making them more cognitively complex via the use of metacognitive reasoning strategies. Furthermore, field experts may benefit from sensemaking training to improve their ethical decision-making framework in highly complex, novel, and ambiguous situations.

Completing the Link between Exposure Science and Toxicology for Improved Environmental Health Decision Making: The Aggregate Exposure Pathway Framework

PubMed Central

Teeguarden, Justin. G.; Tan, Yu-Mei; Edwards, Stephen W.; Leonard, Jeremy A.; Anderson, Kim A.; Corley, Richard A.; Harding, Anna K; Kile, Molly L.; Simonich, Staci M; Stone, David; Tanguay, Robert L.; Waters, Katrina M.; Harper, Stacey L.; Williams, David E.

2016-01-01

Synopsis Driven by major scientific advances in analytical methods, biomonitoring, computational tools, and a newly articulated vision for a greater impact in public health, the field of exposure science is undergoing a rapid transition from a field of observation to a field of prediction. Deployment of an organizational and predictive framework for exposure science analogous to the “systems approaches” used in the biological sciences is a necessary step in this evolution. Here we propose the Aggregate Exposure Pathway (AEP) concept as the natural and complementary companion in the exposure sciences to the Adverse Outcome Pathway (AOP) concept in the toxicological sciences. Aggregate exposure pathways offer an intuitive framework to organize exposure data within individual units of prediction common to the field, setting the stage for exposure forecasting. Looking farther ahead, we envision direct linkages between aggregate exposure pathways and adverse outcome pathways, completing the source to outcome continuum for more efficient integration of exposure assessment and hazard identification. Together, the two pathways form and inform a decision-making framework with the flexibility for risk-based, hazard-based, or exposure-based decision making. PMID:26759916

Psychopathological and personality traits underlie decision making in recent onset medication naïve anorexia nervosa: a pilot study.

PubMed

Fornasari, Livia; Gregoraci, Giorgia; Isola, Miriam; Laura Negri, Gioia Anna; Rambaldelli, Gianluca; Cremaschi, Silvana; Faleschini, Laura; Canalaz, Francesca; Perini, Laura; Balestrieri, Matteo; Fabbro, Franco; Brambilla, Paolo

2014-04-30

The Iowa Gambling Task (IGT) analyzes the ability of participants to sacrifice immediate rewards in view of a long term gain. Anorexia Nervosa (AN) in addition to weight loss and body image disturbances is also characterized by the tendency to make decisions that may result in long-term negative outcomes. Studies that analyzed IGT performance in patients with AN were not consistent with each other. Fifteen adolescents with AN and 15 matched controls carried out IGT after being clinically and neuropsychologically evaluated. An interesting generalized estimating equation approach showed that four independent clinical variables, and not the group, explained IGT performances, such as blocks repetition, anxiety, psychogenic eating disorders and self transcendence. The impairment of decision making is not related to the diagnosis of AN, but it is driven by high levels of anxiety and self transcendence. Instead, some psychogenic eating disorders traits, related to illness severity, positively affected IGT performance in the whole sample. IGT impairment in AN found by prior studies could be related to these clinical features which are not always taken into account. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Completing the link between exposure science and toxicology for improved environmental health decision making: The aggregate exposure pathway framework

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

Teeguarden, Justin G.; Tan, Yu -Mei; Edwards, Stephen W.

Here, driven by major scientific advances in analytical methods, biomonitoring, computation, and a newly articulated vision for a greater impact in public health, the field of exposure science is undergoing a rapid transition from a field of observation to a field of prediction. Deployment of an organizational and predictive framework for exposure science analogous to the “systems approaches” used in the biological sciences is a necessary step in this evolution. Here we propose the aggregate exposure pathway (AEP) concept as the natural and complementary companion in the exposure sciences to the adverse outcome pathway (AOP) concept in the toxicological sciences.more » Aggregate exposure pathways offer an intuitive framework to organize exposure data within individual units of prediction common to the field, setting the stage for exposure forecasting. Looking farther ahead, we envision direct linkages between aggregate exposure pathways and adverse outcome pathways, completing the source to outcome continuum for more meaningful integration of exposure assessment and hazard identification. Together, the two frameworks form and inform a decision-making framework with the flexibility for risk-based, hazard-based, or exposure-based decision making.« less

Completing the link between exposure science and toxicology for improved environmental health decision making: The aggregate exposure pathway framework

DOE PAGES

Teeguarden, Justin G.; Tan, Yu -Mei; Edwards, Stephen W.; ...

2016-01-13

Here, driven by major scientific advances in analytical methods, biomonitoring, computation, and a newly articulated vision for a greater impact in public health, the field of exposure science is undergoing a rapid transition from a field of observation to a field of prediction. Deployment of an organizational and predictive framework for exposure science analogous to the “systems approaches” used in the biological sciences is a necessary step in this evolution. Here we propose the aggregate exposure pathway (AEP) concept as the natural and complementary companion in the exposure sciences to the adverse outcome pathway (AOP) concept in the toxicological sciences.more » Aggregate exposure pathways offer an intuitive framework to organize exposure data within individual units of prediction common to the field, setting the stage for exposure forecasting. Looking farther ahead, we envision direct linkages between aggregate exposure pathways and adverse outcome pathways, completing the source to outcome continuum for more meaningful integration of exposure assessment and hazard identification. Together, the two frameworks form and inform a decision-making framework with the flexibility for risk-based, hazard-based, or exposure-based decision making.« less

Perceptual-cognitive skill and the in situ performance of soccer players.

PubMed

van Maarseveen, Mariëtte J J; Oudejans, Raôul R D; Mann, David L; Savelsbergh, Geert J P

2018-02-01

Many studies have shown that experts possess better perceptual-cognitive skills than novices (e.g., in anticipation, decision making, pattern recall), but it remains unclear whether a relationship exists between performance on those tests of perceptual-cognitive skill and actual on-field performance. In this study, we assessed the in situ performance of skilled soccer players and related the outcomes to measures of anticipation, decision making, and pattern recall. In addition, we examined gaze behaviour when performing the perceptual-cognitive tests to better understand whether the underlying processes were related when those perceptual-cognitive tasks were performed. The results revealed that on-field performance could not be predicted on the basis of performance on the perceptual-cognitive tests. Moreover, there were no strong correlations between the level of performance on the different tests. The analysis of gaze behaviour revealed differences in search rate, fixation duration, fixation order, gaze entropy, and percentage viewing time when performing the test of pattern recall, suggesting that it is driven by different processes to those used for anticipation and decision making. Altogether, the results suggest that the perceptual-cognitive tests may not be as strong determinants of actual performance as may have previously been assumed.

Women's preferences for contralateral prophylactic mastectomy: An investigation using protection motivation theory.

PubMed

Tesson, Stephanie; Richards, Imogen; Porter, David; Phillips, Kelly-Anne; Rankin, Nicole; Musiello, Toni; Marven, Michelle; Butow, Phyllis

2016-05-01

Most women diagnosed with unilateral breast cancer without BRCA1 or BRCA2 mutations are at low risk of contralateral breast cancer. Contralateral Prophylactic Mastectomy (CPM) decreases the relative risk of contralateral breast cancer, but may not increase life expectancy; yet international uptake is increasing. This study applied protection motivation theory (PMT) to determine factors associated with women's intentions to undergo CPM. Three hundred eighty-eight women previously diagnosed with unilateral breast cancer and of negative or unknown BRCA1 or BRCA2 status were recruited from an advocacy group's research database. Participants completed measures of PMT constructs based on a common hypothetical CPM decision-making scenario. PMT constructs explained 16% of variance in intentions to undergo CPM. Response efficacy (CPM's advantages) and response costs (CPM's disadvantages) were unique individual predictors of intentions. Decision-making appears driven by considerations of the psychological, cosmetic and emotional advantages and disadvantages of CPM. Overestimations of threat to life from contralateral breast cancer and survival benefit from CPM also appear influential factors. Patients require balanced and medically accurate information regarding the pros and cons of CPM, survival rates, and recurrence risks to ensure realistic and informed decision-making.

Factors influencing access to education, decision making, and receipt of preferred dialysis modality in unplanned dialysis start patients.

PubMed

Machowska, Anna; Alscher, Mark Dominik; Reddy Vanga, Satyanarayana; Koch, Michael; Aarup, Michael; Qureshi, Abdul Rashid; Lindholm, Bengt; Rutherford, Peter A

2016-01-01

Unplanned dialysis start (UPS) leads to worse clinical outcomes than planned start, and only a minority of patients ever receive education on this topic and are able to make a modality choice, particularly for home dialysis. This study aimed to determine the predictive factors for patients receiving education, making a decision, and receiving their preferred modality choice in UPS patients following a UPS educational program (UPS-EP). The Offering Patients Therapy Options in Unplanned Start (OPTiONS) study examined the impact of the implementation of a specific UPS-EP, including decision support tools and pathway improvement on dialysis modality choice. Linear regression models were used to examine the factors predicting three key steps: referral and receipt of UPS-EP, modality decision making, and actual delivery of preferred modality choice. A simple economic assessment was performed to examine the potential benefit of implementing UPS-EP in terms of dialysis costs. The majority of UPS patients could receive UPS-EP (214/270 patients) and were able to make a decision (177/214), although not all patients received their preferred choice (159/177). Regression analysis demonstrated that the initial dialysis modality was a predictive factor for referral and receipt of UPS-EP and modality decision making. In contrast, age was a predictor for referral and receipt of UPS-EP only, and comorbidity was not a predictor for any step, except for myocardial infarction, which was a weak predictor for lower likelihood of receiving preferred modality. Country practices predicted UPS-EP receipt and decision making. Economic analysis demonstrated the potential benefit of UPS-EP implementation because dialysis modality costs were associated with modality distribution driven by patient preference. Education and decision support can allow UPS patients to understand their options and choose dialysis modality, and attention needs to be focused on ensuring equity of access to educational programs, especially for the elderly. Physician practice and culture across units/countries is an important predictor of UPS patient management and modality choice independent of patient-related factors. Additional work is required to understand and improve patient pathways to ensure that modality preference is enacted. There appears to be a cost benefit of delivering education, supporting choice, and ensuring that the choice is enacted in UPS patients.

Role of the medial prefrontal cortex in impaired decision making in juvenile attention-deficit/hyperactivity disorder.

PubMed

Hauser, Tobias U; Iannaccone, Reto; Ball, Juliane; Mathys, Christoph; Brandeis, Daniel; Walitza, Susanne; Brem, Silvia

2014-10-01

Attention-deficit/hyperactivity disorder (ADHD) has been associated with deficient decision making and learning. Models of ADHD have suggested that these deficits could be caused by impaired reward prediction errors (RPEs). Reward prediction errors are signals that indicate violations of expectations and are known to be encoded by the dopaminergic system. However, the precise learning and decision-making deficits and their neurobiological correlates in ADHD are not well known. To determine the impaired decision-making and learning mechanisms in juvenile ADHD using advanced computational models, as well as the related neural RPE processes using multimodal neuroimaging. Twenty adolescents with ADHD and 20 healthy adolescents serving as controls (aged 12-16 years) were examined using a probabilistic reversal learning task while simultaneous functional magnetic resonance imaging and electroencephalogram were recorded. Learning and decision making were investigated by contrasting a hierarchical Bayesian model with an advanced reinforcement learning model and by comparing the model parameters. The neural correlates of RPEs were studied in functional magnetic resonance imaging and electroencephalogram. Adolescents with ADHD showed more simplistic learning as reflected by the reinforcement learning model (exceedance probability, Px = .92) and had increased exploratory behavior compared with healthy controls (mean [SD] decision steepness parameter β: ADHD, 4.83 [2.97]; controls, 6.04 [2.53]; P = .02). The functional magnetic resonance imaging analysis revealed impaired RPE processing in the medial prefrontal cortex during cue as well as during outcome presentation (P < .05, family-wise error correction). The outcome-related impairment in the medial prefrontal cortex could be attributed to deficient processing at 200 to 400 milliseconds after feedback presentation as reflected by reduced feedback-related negativity (ADHD, 0.61 [3.90] μV; controls, -1.68 [2.52] μV; P = .04). The combination of computational modeling of behavior and multimodal neuroimaging revealed that impaired decision making and learning mechanisms in adolescents with ADHD are driven by impaired RPE processing in the medial prefrontal cortex. This novel, combined approach furthers the understanding of the pathomechanisms in ADHD and may advance treatment strategies.

Decision making, impulse control and loss of willpower to resist drugs: a neurocognitive perspective.

PubMed

Bechara, Antoine

2005-11-01

Here I argue that addicted people become unable to make drug-use choices on the basis of long-term outcome, and I propose a neural framework that explains this myopia for future consequences. I suggest that addiction is the product of an imbalance between two separate, but interacting, neural systems that control decision making: an impulsive, amygdala system for signaling pain or pleasure of immediate prospects, and a reflective, prefrontal cortex system for signaling pain or pleasure of future prospects. After an individual learns social rules, the reflective system controls the impulsive system via several mechanisms. However, this control is not absolute; hyperactivity within the impulsive system can override the reflective system. I propose that drugs can trigger bottom-up, involuntary signals originating from the amygdala that modulate, bias or even hijack the goal-driven cognitive resources that are needed for the normal operation of the reflective system and for exercising the willpower to resist drugs.

Revisiting Statistical Aspects of Nuclear Material Accounting

DOE PAGES

Burr, T.; Hamada, M. S.

2013-01-01

Nuclear material accounting (NMA) is the only safeguards system whose benefits are routinely quantified. Process monitoring (PM) is another safeguards system that is increasingly used, and one challenge is how to quantify its benefit. This paper considers PM in the role of enabling frequent NMA, which is referred to as near-real-time accounting (NRTA). We quantify NRTA benefits using period-driven and data-driven testing. Period-driven testing makes a decision to alarm or not at fixed periods. Data-driven testing decides as the data arrives whether to alarm or continue testing. The difference between period-driven and datad-riven viewpoints is illustrated by using one-year andmore » two-year periods. For both one-year and two-year periods, period-driven NMA using once-per-year cumulative material unaccounted for (CUMUF) testing is compared to more frequent Shewhart and joint sequential cusum testing using either MUF or standardized, independently transformed MUF (SITMUF) data. We show that the data-driven viewpoint is appropriate for NRTA and that it can be used to compare safeguards effectiveness. In addition to providing period-driven and data-driven viewpoints, new features include assessing the impact of uncertainty in the estimated covariance matrix of the MUF sequence and the impact of both random and systematic measurement errors.« less

Automation for deep space vehicle monitoring

NASA Technical Reports Server (NTRS)

Schwuttke, Ursula M.

1991-01-01

Information on automation for deep space vehicle monitoring is given in viewgraph form. Information is given on automation goals and strategy; the Monitor Analyzer of Real-time Voyager Engineering Link (MARVEL); intelligent input data management; decision theory for making tradeoffs; dynamic tradeoff evaluation; evaluation of anomaly detection results; evaluation of data management methods; system level analysis with cooperating expert systems; the distributed architecture of multiple expert systems; and event driven response.

Use of a Tier 3 Evidence-Based Intervention with Progress Monitoring, Formative Assessment, and Student Goal-Setting: An Evaluation of the Immediate and Long-Term Effects on Student Reading Achievement

ERIC Educational Resources Information Center

McMasters, Angela B.

2011-01-01

Early identification and intervention for students at risk for reading failure is essential to establish the foundational skills necessary for students to become skilled readers. The focus on evidence-based practices and data-driven decision making leads educators to consider additional instructional approaches, such as formative assessment (FA)…

Induction of appropriate Th-cell phenotypes: cellular decision-making in heterogeneous environments.

PubMed

van den Ham, H-J; Andeweg, A C; de Boer, R J

2013-11-01

Helper T (Th)-cell differentiation is a key event in the development of the adaptive immune response. By the production of a range of cytokines, Th cells determine the type of immune response that is raised against an invading pathogen. Th cells can adopt many different phenotypes, and Th-cell phenotype decision-making is crucial in mounting effective host responses. This review discusses the different Th-cell phenotypes that have been identified and how Th cells adopt a particular phenotype. The regulation of Th-cell phenotypes has been studied extensively using mathematical models, which have explored the role of regulatory mechanisms such as autocrine cytokine signalling and cross-inhibition between self-activating transcription factors. At the single cell level, Th responses tend to be heterogeneous, but corrections can be made soon after T-cell activation. Although pathogens and the innate immune system provide signals that direct the induction of Th-cell phenotypes, these instructive mechanisms could be easily subverted by pathogens. We discuss that a model of success-driven feedback would select the most appropriate phenotype for clearing a pathogen. Given the heterogeneity in the induction phase of the Th response, such a success-driven feedback loop would allow the selection of effective Th-cell phenotypes while terminating incorrect responses. © 2013 John Wiley & Sons Ltd.

Viewpoint: Availability of oestrogen receptor and HER2 status for the breast multidisciplinary meeting discussion; time to get it right.

PubMed

Francis, A; Bartlett, J; Rea, D; Pinder, S E; Stein, R C; Stobart, H; Purdie, C A; Rakha, E; Thompson, A; Shaaban, A M

2016-07-01

The efficacy and pivotal role of the multidisciplinary meeting (MDM) in informed decision making is well established. It aims to provide a forum in which clinical evidence combines with individual patient data to create a personalized treatment plan. It does not fulfil this role adequately when undertaken without the full results of the patient's investigations being available. Neither doctor nor patient can make an informed decision about treatment options without knowledge of the tumour receptor status. Both targeted therapies and the aim to treat a majority of patients within clinical trials must now drive MDM decision making to be based on accuracy and best available treatment choices. A fully informed decision on treatment delayed by 1-2 weeks is clearly preferable to rushed time target-driven decisions made without the patient being offered a fully informed choice as ratified by a multidisciplinary team. Whilst the early anxiety of waiting for all relevant information to be available may be stressful for patients, not being sure that they have been offered fully informed treatment choices is also stressful and could cause longer lasting anxiety both during and after treatment. MDMs need to develop (along with targeted therapies) to retain their role as a forum whereby patients receive a correct, but specifically a full diagnosis and allow a fully informed discussion of all treatment options, including pre-operative clinical trials. Copyright © 2016 Elsevier Ltd. All rights reserved.

Modern data-driven decision support systems: the role of computing with words and computational linguistics

NASA Astrophysics Data System (ADS)

Kacprzyk, Janusz; Zadrożny, Sławomir

2010-05-01

We present how the conceptually and numerically simple concept of a fuzzy linguistic database summary can be a very powerful tool for gaining much insight into the very essence of data. The use of linguistic summaries provides tools for the verbalisation of data analysis (mining) results which, in addition to the more commonly used visualisation, e.g. via a graphical user interface, can contribute to an increased human consistency and ease of use, notably for supporting decision makers via the data-driven decision support system paradigm. Two new relevant aspects of the analysis are also outlined which were first initiated by the authors. First, following Kacprzyk and Zadrożny, it is further considered how linguistic data summarisation is closely related to some types of solutions used in natural language generation (NLG). This can make it possible to use more and more effective and efficient tools and techniques developed in NLG. Second, similar remarks are given on relations to systemic functional linguistics. Moreover, following Kacprzyk and Zadrożny, comments are given on an extremely relevant aspect of scalability of linguistic summarisation of data, using a new concept of a conceptual scalability.

Planning for successful outcomes in the new millennium.

PubMed

Matthews, P

2000-02-01

The complexity of the health care environment will increase in the next millennium. Organizations must adopt an approach of selecting outcomes management solutions that are focused on data capture, analysis, and comparative reviews and reporting. They must decisively and creatively implement, in a phased approach, integrated solutions from existing robust systems, while considering future systems targeted for implementation. Outcomes management solutions must be integrated with the organization's information systems strategic plan. The successful organization must be able to turn business-critical data into information that supports both business and clinical decision-making activities. In short, health care organizations will have to become information-driven.

Democracy versus dictatorship in self-organized models of financial markets

NASA Astrophysics Data System (ADS)

D'Hulst, R.; Rodgers, G. J.

2000-06-01

Models to mimic the transmission of information in financial markets are introduced. As an attempt to generate the demand process, we distinguish between dictatorship associations, where groups of agents rely on one of them to make decision, and democratic associations, where each agent takes part in the group decision. In the dictatorship model, agents segregate into two distinct populations, while the democratic model is driven towards a critical state where groups of agents of all sizes exist. Hence, both models display a level of organization, but only the democratic model is self-organized. We show that the dictatorship model generates less-volatile markets than the democratic model.

Risky Decisions Despite Counter Evidence: Modeling a Culture of Safer Sexual Practices

PubMed Central

Patel, Vimla L.; Yoskowitz, Nicole A.; Kaufman, David R.; Gutnik, Lily A.; Shortliffe, Edward H.

2005-01-01

To create a culture of safe practices, we need to understand how and under what conditions the public makes risky decisions about their health. Because risky sexual behaviors are known to be common in young adults, we investigated their decision making regarding sexual activities that could incur a high risk of HIV infection. Sixty young urban adults maintained journals for two weeks and were interviewed regarding condom use and sexual history. We characterized four patterns of condom use behavior: consistent (35.0%), inconsistent (16.7%), consistent to inconsistent (35.0%), and inconsistent to consistent (13.3%). Directionality of reasoning was analyzed in the explanations provided for condom use decisions. The consistent and inconsistent patterns were associated with data-driven heuristic reasoning, where behavior becomes automated and is associated with a high level of confidence in one’s judgment. In the other two patterns, the shift in behavior was due to a significant event that influenced a change in directionality to explanation-based reasoning. We discuss these results within the framework of identifying potentially high-risk groups for whom customized intervention strategies (such as computer-based educational programs) can be used to reduce risk, thereby creating a culture of safer sexual practices. PMID:16779109

Risky decisions despite counter evidence: modeling a culture of safer sexual practices.

PubMed

Patel, Vimla L; Yoskowitz, Nicole A; Kaufman, David R; Gutnik, Lily A; Shortliffe, Edward H

2005-01-01

To create a culture of safe practices, we need to understand how and under what conditions the public makes risky decisions about their health. Because risky sexual behaviors are known to be common in young adults, we investigated their decision making regarding sexual activities that could incur a high risk of HIV infection. Sixty young urban adults maintained journals for two weeks and were interviewed regarding condom use and sexual history. We characterized four patterns of condom use behavior: consistent (35.0%), inconsistent (16.7%), consistent to inconsistent (35.0%), and inconsistent to consistent (13.3%). Directionality of reasoning was analyzed in the explanations provided for condom use decisions. The consistent and inconsistent patterns were associated with data-driven heuristic reasoning, where behavior becomes automated and is associated with a high level of confidence in one's judgment. In the other two patterns, the shift in behavior was due to a significant event that influenced a change in directionality to explanation-based reasoning. We discuss these results within the framework of identifying potentially high-risk groups for whom customized intervention strategies (such as computer-based educational programs) can be used to reduce risk, thereby creating a culture of safer sexual practices.

Integrating environmental monitoring with cumulative effects management and decision making.

PubMed

Cronmiller, Joshua G; Noble, Bram F

2018-05-01

Cumulative effects (CE) monitoring is foundational to emerging regional and watershed CE management frameworks, yet monitoring is often poorly integrated with CE management and decision-making processes. The challenges are largely institutional and organizational, more so than scientific or technical. Calls for improved integration of monitoring with CE management and decision making are not new, but there has been limited research on how best to integrate environmental monitoring programs to ensure credible CE science and to deliver results that respond to the more immediate questions and needs of regulatory decision makers. This paper examines options for the integration of environmental monitoring with CE frameworks. Based on semistructured interviews with practitioners, regulators, and other experts in the Lower Athabasca, Alberta, Canada, 3 approaches to monitoring system design are presented. First, a distributed monitoring system, reflecting the current approach in the Lower Athabasca, where monitoring is delegated to different external programs and organizations; second, a 1-window system in which monitoring is undertaken by a single, in-house agency for the purpose of informing management and regulatory decision making; third, an independent system driven primarily by CE science and understanding causal relationships, with knowledge adopted for decision support where relevant to specific management questions. The strengths and limitations of each approach are presented. A hybrid approach may be optimal-an independent, nongovernment, 1-window model for CE science, monitoring, and information delivery-capitalizing on the strengths of distributed, 1-window, and independent monitoring systems while mitigating their weaknesses. If governments are committed to solving CE problems, they must invest in the long-term science needed to do so; at the same time, if science-based monitoring programs are to be sustainable over the long term, they must be responsive to the more immediate, often shorter term needs and CE information requirements of decision makers. Integr Environ Assess Manag 2018;14:407-417. © 2018 SETAC. © 2018 SETAC.

Risk Tradeoffs in Adaptive Ecosystem Management: The Case of the U.S. Forest Service

NASA Astrophysics Data System (ADS)

Stern, Marc J.; Martin, Caysie A.; Predmore, S. Andrew; Morse, Wayde C.

2014-06-01

Natural resource planning processes on public lands in the United States are driven in large part by the requirements of the National Environmental Policy Act (NEPA), which dictates general processes for analyzing and disclosing the likely impacts of proposed actions. The outcomes of these processes are the result of multiple factors, many related to the manifold smaller incremental decisions made by agency personnel directing the processes. Through interviews with decision makers, team leaders, and team members on five NEPA processes within the U.S. Forest Service, this study examines those incremental decisions. Risk, in particular external relationship risk, emerged as a dominant lens through which agency personnel weigh and make process-related decisions. We discuss the tradeoffs associated with agency actors' emphasis on this form of risk and their potential implications for adaptive ecosystem management and organizational performance.

A strategic decision-making model considering the social costs of carbon dioxide emissions for sustainable supply chain management.

PubMed

Tseng, Shih-Chang; Hung, Shiu-Wan

2014-01-15

Incorporating sustainability into supply chain management has become a critical issue driven by pressures from governments, customers, and various stakeholder groups over the past decade. This study proposes a strategic decision-making model considering both the operational costs and social costs caused by the carbon dioxide emissions from operating such a supply chain network for sustainable supply chain management. This model was used to evaluate carbon dioxide emissions and operational costs under different scenarios in an apparel manufacturing supply chain network. The results showed that the higher the social cost rate of carbon dioxide emissions, the lower the amount of the emission of carbon dioxide. The results also suggested that a legislation that forces the enterprises to bear the social costs of carbon dioxide emissions resulting from their economic activities is an effective approach to reducing carbon dioxide emissions. Copyright © 2013 Elsevier Ltd. All rights reserved.

[Shared decision-making and individualized goal setting - a pilot trial using PRISM (Pictorial Representation of Illness and Self Measure) in psychiatric inpatients].

PubMed

Büchi, S; Straub, S; Schwager, U

2010-12-01

Although there is much talk about shared decision making and individualized goal setting, there is a lack of knowledge and knowhow in their realization in daily clinical practice. There is a lack in tools for easy applicable tools to ameliorate person-centred individualized goal setting processes. In three selected psychiatric inpatients the semistructured, theory driven use of PRISM (Pictorial Representation of Illness and Self Measure) in patients with complex psychiatric problems is presented and discussed. PRISM sustains a person-centred individualized process of goal setting and treatment and reinforces the active participation of patients. The process of visualisation and synchronous documentation is validated positively by patients and clinicians. The visual goal setting requires 30 to 45 minutes. In patients with complex psychiatric illness PRISM was used successfully to ameliorate individual goal setting. Specific effects of PRISM-visualisation are actually evaluated in a randomized controlled trial.

Dysfunctions of decision-making and cognitive control as transdiagnostic mechanisms of mental disorders: advances, gaps, and needs in current research.

PubMed

Goschke, Thomas

2014-01-01

Disadvantageous decision-making and impaired volitional control over actions, thoughts, and emotions are characteristics of a wide range of mental disorders such as addiction, eating disorders, depression, and anxiety disorders and may reflect transdiagnostic core mechanisms and possibly vulnerability factors. Elucidating the underlying neurocognitive mechanisms is a precondition for moving from symptom-based to mechanism-based disorder classifications and ultimately mechanism-targeted interventions. However, despite substantial advances in basic research on decision-making and cognitive control, there are still profound gaps in our current understanding of dysfunctions of these processes in mental disorders. Central unresolved questions are: (i) to which degree such dysfunctions reflect transdiagnostic mechanisms or disorder-specific patterns of impairment; (ii) how phenotypical features of mental disorders relate to dysfunctional control parameter settings and aberrant interactions between large-scale brain systems involved in habit and reward-based learning, performance monitoring, emotion regulation, and cognitive control; (iii) whether cognitive control impairments are consequences or antecedent vulnerability factors of mental disorders; (iv) whether they reflect generalized competence impairments or context-specific performance failures; (v) whether not only impaired but also chronic over-control contributes to mental disorders. In the light of these gaps, needs for future research are: (i) an increased focus on basic cognitive-affective mechanisms underlying decision and control dysfunctions across disorders; (ii) longitudinal-prospective studies systematically incorporating theory-driven behavioural tasks and neuroimaging protocols to assess decision-making and control dysfunctions and aberrant interactions between underlying large-scale brain systems; (iii) use of latent-variable models of cognitive control rather than single tasks; (iv) increased focus on the interplay of implicit and explicit cognitive-affective processes; (v) stronger focus on computational models specifying neurocognitive mechanisms underlying phenotypical expressions of mental disorders. Copyright © 2013 John Wiley & Sons, Ltd.

Improving Federal Cybersecurity Governance Through Data-Driven Decision Making and Execution

DTIC Science & Technology

2015-09-01

responsibility to set the environment 2 Federal IT Dashboard (https://www.itdashboard.gov/sites/default/files/exhibit53report/4), World Bank GDP (http...ance managers  members of the private sector supporting the audience members listed above Figure 1 below graphically depicts the audience for...for root-cause analysis. Common examples of indicators include the Bureau of Labor Statis- tics’ Unemployment Rate and Consumer Price Index. Indices can

Making the Case for the Outlier: Researcher Reflections of an African-American Female Deputy Superintendent Who Decided to Close the Achievement Gap

ERIC Educational Resources Information Center

Beard, Karen Stansberry

2012-01-01

This article presents researcher reflections of a case study of a Black female deputy superintendent who made the value-driven decision to close the achievement gap in her district. I posit that she is an outlier because she is Black and female in a predominantly white male field of practice, she effectively closed the achievement gap through her…

Factors That Affect a School District's Ability to Successfully Implement the Use of Data Warehouse Applications in the Data Driven Decision Making Process

ERIC Educational Resources Information Center

DeLoach, Robin

2012-01-01

The purpose of this study was to explore the factors that influence the ability of teachers and administrators to use data obtained from a data warehouse to inform instruction. The mixed methods study was guided by the following questions: 1) What data warehouse application features affect the ability of an educator to effectively use the…

Neural dynamics of social tie formation in economic decision-making.

PubMed

Bault, Nadège; Pelloux, Benjamin; Fahrenfort, Johannes J; Ridderinkhof, K Richard; van Winden, Frans

2015-06-01

The disposition for prosocial conduct, which contributes to cooperation as arising during social interaction, requires cortical network dynamics responsive to the development of social ties, or care about the interests of specific interaction partners. Here, we formulate a dynamic computational model that accurately predicted how tie formation, driven by the interaction history, influences decisions to contribute in a public good game. We used model-driven functional MRI to test the hypothesis that brain regions key to social interactions keep track of dynamics in tie strength. Activation in the medial prefrontal cortex (mPFC) and posterior cingulate cortex tracked the individual's public good contributions. Activation in the bilateral posterior superior temporal sulcus (pSTS), and temporo-parietal junction was modulated parametrically by the dynamically developing social tie-as estimated by our model-supporting a role of these regions in social tie formation. Activity in these two regions further reflected inter-individual differences in tie persistence and sensitivity to behavior of the interaction partner. Functional connectivity between pSTS and mPFC activations indicated that the representation of social ties is integrated in the decision process. These data reveal the brain mechanisms underlying the integration of interaction dynamics into a social tie representation which in turn influenced the individual's prosocial decisions. © The Author (2014). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Impact of personal economic environment and personality factors on individual financial decision making.

PubMed

Prinz, Susanne; Gründer, Gerhard; Hilgers, Ralf D; Holtemöller, Oliver; Vernaleken, Ingo

2014-01-01

This study on healthy young male students aimed to enlighten the associations between an individual's financial decision making and surrogate makers for environmental factors covering long-term financial socialization, the current financial security/responsibility, and the personal affinity to financial affairs as represented by parental income, funding situation, and field of study. A group of 150 male young healthy students underwent two versions of the Holt and Laury (2002) lottery paradigm (matrix and random sequential version). Their financial decision was mainly driven by the factor "source of funding": students with strict performance control (grants, scholarships) had much higher rates of relative risk aversion (RRA) than subjects with support from family (ΔRRA = 0.22; p = 0.018). Personality scores only modestly affected the outcome. In an ANOVA, however, also the intelligence quotient significantly and relevantly contributed to the explanation of variance; the effects of parental income and the personality factors "agreeableness" and "openness" showed moderate to modest - but significant - effects. These findings suggest that environmental factors more than personality factors affect risk aversion.

Impact of personal economic environment and personality factors on individual financial decision making

PubMed Central

Prinz, Susanne; Gründer, Gerhard; Hilgers, Ralf D.; Holtemöller, Oliver; Vernaleken, Ingo

2014-01-01

This study on healthy young male students aimed to enlighten the associations between an individual’s financial decision making and surrogate makers for environmental factors covering long-term financial socialization, the current financial security/responsibility, and the personal affinity to financial affairs as represented by parental income, funding situation, and field of study. A group of 150 male young healthy students underwent two versions of the Holt and Laury (2002) lottery paradigm (matrix and random sequential version). Their financial decision was mainly driven by the factor “source of funding”: students with strict performance control (grants, scholarships) had much higher rates of relative risk aversion (RRA) than subjects with support from family (ΔRRA = 0.22; p = 0.018). Personality scores only modestly affected the outcome. In an ANOVA, however, also the intelligence quotient significantly and relevantly contributed to the explanation of variance; the effects of parental income and the personality factors “agreeableness” and “openness” showed moderate to modest – but significant – effects. These findings suggest that environmental factors more than personality factors affect risk aversion. PMID:24624100

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.

Releases of whooping cranes to the Florida nonmigratory flock: a structured decision-making approach: report to the International Whooping Crane Recovery Team, September 22, 2008

USGS Publications Warehouse

Moore, Clinton T.; Converse, Sarah J.; Folk, Martin J.; Boughton, Robin; Brooks, Bill; French, John B.; O'Meara, Timothy; Putnam, Michael; Rodgers, James; Spalding, Marilyn

2008-01-01

We used a structured decision-making approach to inform the decision of whether the Florida Fish and Wildlife Conservation Commission should request of the International Whooping Crane Recovery Team that additional whooping crane chicks be released into the Florida Non-Migratory Population (FNMP). Structured decision-making is an application of decision science that strives to produce transparent, replicable, and defensible decisions that recognize the appropriate roles of management policy and science in decision-making. We present a multi-objective decision framework, where management objectives include successful establishment of a whooping crane population in Florida, minimization of costs, positive public relations, information gain, and providing a supply of captive-reared birds to alternative crane release projects, such as the Eastern Migratory Population. We developed models to predict the outcome relative to each of these objectives under 29 different scenarios of the release methodology used from 1993 to 2004, including options of no further releases and variable numbers of releases per year over the next 5-30 years. In particular, we developed a detailed set of population projection models, which make substantially different predictions about the probability of successful establishment of the FNMP. We used expert elicitation to develop prior model weights (measures of confidence in population model predictions); the results of the population model weighting and modelaveraging exercise indicated that the probability of successful establishment of the FNMP ranged from 9% if no additional releases are made, to as high as 41% with additional releases. We also used expert elicitation to develop weights (relative values) on the set of identified objectives, and we then used a formal optimization technique for identifying the optimal decision, which considers the tradeoffs between objectives. The optimal decision was identified as release of 3 cohorts (24 birds) per year over the next 10 years. However, any decision that involved release of 1-3 cohorts (8-24 birds) per year over the next 5 to 20 years, as well as decisions that involve skipping releases in every other year, performed better in our analysis than the alternative of no further releases. These results were driven by the relatively high objective weights that experts placed on the population objective (i.e., successful establishment of the FNMP) and the information gain objective (where releases are expected to accelerate learning on what was identified as a primary uncertainty: the demographic performance of wild-hatched birds). Additional considerations that were not formally integrated into the analysis are also discussed.

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.

Perceptual and categorical decision making: goal-relevant representation of two domains at different levels of abstraction.

PubMed

Shankar, Swetha; Kayser, Andrew S

2017-06-01

To date it has been unclear whether perceptual decision making and rule-based categorization reflect activation of similar cognitive processes and brain regions. On one hand, both map potentially ambiguous stimuli to a smaller set of motor responses. On the other hand, decisions about perceptual salience typically concern concrete sensory representations derived from a noisy stimulus, while categorization is typically conceptualized as an abstract decision about membership in a potentially arbitrary set. Previous work has primarily examined these types of decisions in isolation. Here we independently varied salience in both the perceptual and categorical domains in a random dot-motion framework by manipulating dot-motion coherence and motion direction relative to a category boundary, respectively. Behavioral and modeling results suggest that categorical (more abstract) information, which is more relevant to subjects' decisions, is weighted more strongly than perceptual (more concrete) information, although they also have significant interactive effects on choice. Within the brain, BOLD activity within frontal regions strongly differentiated categorical salience and weakly differentiated perceptual salience; however, the interaction between these two factors activated similar frontoparietal brain networks. Notably, explicitly evaluating feature interactions revealed a frontal-parietal dissociation: parietal activity varied strongly with both features, but frontal activity varied with the combined strength of the information that defined the motor response. Together, these data demonstrate that frontal regions are driven by decision-relevant features and argue that perceptual decisions and rule-based categorization reflect similar cognitive processes and activate similar brain networks to the extent that they define decision-relevant stimulus-response mappings. NEW & NOTEWORTHY Here we study the behavioral and neural dynamics of perceptual categorization when decision information varies in multiple domains at different levels of abstraction. Behavioral and modeling results suggest that categorical (more abstract) information is weighted more strongly than perceptual (more concrete) information but that perceptual and categorical domains interact to influence decisions. Frontoparietal brain activity during categorization flexibly represents decision-relevant features and highlights significant dissociations in frontal and parietal activity during decision making. Copyright © 2017 the American Physiological Society.

Perceptual and categorical decision making: goal-relevant representation of two domains at different levels of abstraction

PubMed Central

Kayser, Andrew S.

2017-01-01

To date it has been unclear whether perceptual decision making and rule-based categorization reflect activation of similar cognitive processes and brain regions. On one hand, both map potentially ambiguous stimuli to a smaller set of motor responses. On the other hand, decisions about perceptual salience typically concern concrete sensory representations derived from a noisy stimulus, while categorization is typically conceptualized as an abstract decision about membership in a potentially arbitrary set. Previous work has primarily examined these types of decisions in isolation. Here we independently varied salience in both the perceptual and categorical domains in a random dot-motion framework by manipulating dot-motion coherence and motion direction relative to a category boundary, respectively. Behavioral and modeling results suggest that categorical (more abstract) information, which is more relevant to subjects’ decisions, is weighted more strongly than perceptual (more concrete) information, although they also have significant interactive effects on choice. Within the brain, BOLD activity within frontal regions strongly differentiated categorical salience and weakly differentiated perceptual salience; however, the interaction between these two factors activated similar frontoparietal brain networks. Notably, explicitly evaluating feature interactions revealed a frontal-parietal dissociation: parietal activity varied strongly with both features, but frontal activity varied with the combined strength of the information that defined the motor response. Together, these data demonstrate that frontal regions are driven by decision-relevant features and argue that perceptual decisions and rule-based categorization reflect similar cognitive processes and activate similar brain networks to the extent that they define decision-relevant stimulus-response mappings. NEW & NOTEWORTHY Here we study the behavioral and neural dynamics of perceptual categorization when decision information varies in multiple domains at different levels of abstraction. Behavioral and modeling results suggest that categorical (more abstract) information is weighted more strongly than perceptual (more concrete) information but that perceptual and categorical domains interact to influence decisions. Frontoparietal brain activity during categorization flexibly represents decision-relevant features and highlights significant dissociations in frontal and parietal activity during decision making. PMID:28250149

Using Decision Trees to Detect and Isolate Simulated Leaks in the J-2X Rocket Engine

NASA Technical Reports Server (NTRS)

Schwabacher, Mark A.; Aguilar, Robert; Figueroa, Fernando F.

2009-01-01

The goal of this work was to use data-driven methods to automatically detect and isolate faults in the J-2X rocket engine. It was decided to use decision trees, since they tend to be easier to interpret than other data-driven methods. The decision tree algorithm automatically "learns" a decision tree by performing a search through the space of possible decision trees to find one that fits the training data. The particular decision tree algorithm used is known as C4.5. Simulated J-2X data from a high-fidelity simulator developed at Pratt & Whitney Rocketdyne and known as the Detailed Real-Time Model (DRTM) was used to "train" and test the decision tree. Fifty-six DRTM simulations were performed for this purpose, with different leak sizes, different leak locations, and different times of leak onset. To make the simulations as realistic as possible, they included simulated sensor noise, and included a gradual degradation in both fuel and oxidizer turbine efficiency. A decision tree was trained using 11 of these simulations, and tested using the remaining 45 simulations. In the training phase, the C4.5 algorithm was provided with labeled examples of data from nominal operation and data including leaks in each leak location. From the data, it "learned" a decision tree that can classify unseen data as having no leak or having a leak in one of the five leak locations. In the test phase, the decision tree produced very low false alarm rates and low missed detection rates on the unseen data. It had very good fault isolation rates for three of the five simulated leak locations, but it tended to confuse the remaining two locations, perhaps because a large leak at one of these two locations can look very similar to a small leak at the other location.

Indicators of ecosystem function identify alternate states in the sagebrush steppe.

PubMed

Kachergis, Emily; Rocca, Monique E; Fernandez-Gimenez, Maria E

2011-10-01

Models of ecosystem change that incorporate nonlinear dynamics and thresholds, such as state-and-transition models (STMs), are increasingly popular tools for land management decision-making. However, few models are based on systematic collection and documentation of ecological data, and of these, most rely solely on structural indicators (species composition) to identify states and transitions. As STMs are adopted as an assessment framework throughout the United States, finding effective and efficient ways to create data-driven models that integrate ecosystem function and structure is vital. This study aims to (1) evaluate the utility of functional indicators (indicators of rangeland health, IRH) as proxies for more difficult ecosystem function measurements and (2) create a data-driven STM for the sagebrush steppe of Colorado, USA, that incorporates both ecosystem structure and function. We sampled soils, plant communities, and IRH at 41 plots with similar clayey soils but different site histories to identify potential states and infer the effects of management practices and disturbances on transitions. We found that many IRH were correlated with quantitative measures of functional indicators, suggesting that the IRH can be used to approximate ecosystem function. In addition to a reference state that functions as expected for this soil type, we identified four biotically and functionally distinct potential states, consistent with the theoretical concept of alternate states. Three potential states were related to management practices (chemical and mechanical shrub treatments and seeding history) while one was related only to ecosystem processes (erosion). IRH and potential states were also related to environmental variation (slope, soil texture), suggesting that there are environmental factors within areas with similar soils that affect ecosystem dynamics and should be noted within STMs. Our approach generated an objective, data-driven model of ecosystem dynamics for rangeland management. Our findings suggest that the IRH approximate ecosystem processes and can distinguish between alternate states and communities and identify transitions when building data-driven STMs. Functional indicators are a simple, efficient way to create data-driven models that are consistent with alternate state theory. Managers can use them to improve current model-building methods and thus apply state-and-transition models more broadly for land management decision-making.

Evidence-Based and Value-Based Decision Making About Healthcare Design: An Economic Evaluation of the Safety and Quality Outcomes.

PubMed

Zadeh, Rana; Sadatsafavi, Hessam; Xue, Ryan

2015-01-01

This study describes a vision and framework that can facilitate the implementation of evidence-based design (EBD), scientific knowledge base into the process of the design, construction, and operation of healthcare facilities and clarify the related safety and quality outcomes for the stakeholders. The proposed framework pairs EBD with value-driven decision making and aims to improve communication among stakeholders by providing a common analytical language. Recent EBD research indicates that the design and operation of healthcare facilities contribute to an organization's operational success by improving safety, quality, and efficiency. However, because little information is available about the financial returns of evidence-based investments, such investments are readily eliminated during the capital-investment decision-making process. To model the proposed framework, we used engineering economy tools to evaluate the return on investments in six successful cases, identified by a literature review, in which facility design and operation interventions resulted in reductions in hospital-acquired infections, patient falls, staff injuries, and patient anxiety. In the evidence-based cases, calculated net present values, internal rates of return, and payback periods indicated that the long-term benefits of interventions substantially outweighed the intervention costs. This article explained a framework to develop a research-based and value-based communication language on specific interventions along the planning, design and construction, operation, and evaluation stages. Evidence-based and value-based design frameworks can be applied to communicate the life-cycle costs and savings of EBD interventions to stakeholders, thereby contributing to more informed decision makings and the optimization of healthcare infrastructures. © The Author(s) 2015.

Big data and high-performance analytics in structural health monitoring for bridge management

NASA Astrophysics Data System (ADS)

Alampalli, Sharada; Alampalli, Sandeep; Ettouney, Mohammed

2016-04-01

Structural Health Monitoring (SHM) can be a vital tool for effective bridge management. Combining large data sets from multiple sources to create a data-driven decision-making framework is crucial for the success of SHM. This paper presents a big data analytics framework that combines multiple data sets correlated with functional relatedness to convert data into actionable information that empowers risk-based decision-making. The integrated data environment incorporates near real-time streams of semi-structured data from remote sensors, historical visual inspection data, and observations from structural analysis models to monitor, assess, and manage risks associated with the aging bridge inventories. Accelerated processing of dataset is made possible by four technologies: cloud computing, relational database processing, support from NOSQL database, and in-memory analytics. The framework is being validated on a railroad corridor that can be subjected to multiple hazards. The framework enables to compute reliability indices for critical bridge components and individual bridge spans. In addition, framework includes a risk-based decision-making process that enumerate costs and consequences of poor bridge performance at span- and network-levels when rail networks are exposed to natural hazard events such as floods and earthquakes. Big data and high-performance analytics enable insights to assist bridge owners to address problems faster.

Suboptimal choice in rats: incentive salience attribution promotes maladaptive decision-making

PubMed Central

Chow, Jonathan J; Smith, Aaron P; Wilson, A George; Zentall, Thomas R; Beckmann, Joshua S

2016-01-01

Stimuli that are more predictive of subsequent reward also function as better conditioned reinforcers. Moreover, stimuli attributed with incentive salience function as more robust conditioned reinforcers. Some theories have suggested that conditioned reinforcement plays an important role in promoting suboptimal choice behavior, like gambling. The present experiments examined how different stimuli, those attributed with incentive salience versus those without, can function in tandem with stimulus-reward predictive utility to promote maladaptive decision-making in rats. One group of rats had lights associated with goal-tracking as the reward-predictive stimuli and another had levers associated with sign-tracking as the reward-predictive stimuli. All rats were first trained on a choice procedure in which the expected value across both alternatives was equivalent but differed in their stimulus-reward predictive utility. Next, the expected value across both alternatives was systematically changed so that the alternative with greater stimulus-reward predictive utility was suboptimal in regard to primary reinforcement. The results demonstrate that in order to obtain suboptimal choice behavior, incentive salience alongside strong stimulus-reward predictive utility may be necessary; thus, maladaptive decision-making can be driven more by the value attributed to stimuli imbued with incentive salience that reliably predict a reward rather than the reward itself. PMID:27993692

Suboptimal choice in rats: Incentive salience attribution promotes maladaptive decision-making.

PubMed

Chow, Jonathan J; Smith, Aaron P; Wilson, A George; Zentall, Thomas R; Beckmann, Joshua S

2017-03-01

Stimuli that are more predictive of subsequent reward also function as better conditioned reinforcers. Moreover, stimuli attributed with incentive salience function as more robust conditioned reinforcers. Some theories have suggested that conditioned reinforcement plays an important role in promoting suboptimal choice behavior, like gambling. The present experiments examined how different stimuli, those attributed with incentive salience versus those without, can function in tandem with stimulus-reward predictive utility to promote maladaptive decision-making in rats. One group of rats had lights associated with goal-tracking as the reward-predictive stimuli and another had levers associated with sign-tracking as the reward-predictive stimuli. All rats were first trained on a choice procedure in which the expected value across both alternatives was equivalent but differed in their stimulus-reward predictive utility. Next, the expected value across both alternatives was systematically changed so that the alternative with greater stimulus-reward predictive utility was suboptimal in regard to primary reinforcement. The results demonstrate that in order to obtain suboptimal choice behavior, incentive salience alongside strong stimulus-reward predictive utility may be necessary; thus, maladaptive decision-making can be driven more by the value attributed to stimuli imbued with incentive salience that reliably predict a reward rather than the reward itself. Copyright © 2016 Elsevier B.V. All rights reserved.

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.

An ontology-driven clinical decision support system (IDDAP) for infectious disease diagnosis and antibiotic prescription.

PubMed

Shen, Ying; Yuan, Kaiqi; Chen, Daoyuan; Colloc, Joël; Yang, Min; Li, Yaliang; Lei, Kai

2018-03-01

The available antibiotic decision-making systems were developed from a physician's perspective. However, because infectious diseases are common, many patients desire access to knowledge via a search engine. Although the use of antibiotics should, in principle, be subject to a doctor's advice, many patients take them without authorization, and some people cannot easily or rapidly consult a doctor. In such cases, a reliable antibiotic prescription support system is needed. This study describes the construction and optimization of the sensitivity and specificity of a decision support system named IDDAP, which is based on ontologies for infectious disease diagnosis and antibiotic therapy. The ontology for this system was constructed by collecting existing ontologies associated with infectious diseases, syndromes, bacteria and drugs into the ontology's hierarchical conceptual schema. First, IDDAP identifies a potential infectious disease based on a patient's self-described disease state. Then, the system searches for and proposes an appropriate antibiotic therapy specifically adapted to the patient based on factors such as the patient's body temperature, infection sites, symptoms/signs, complications, antibacterial spectrum, contraindications, drug-drug interactions between the proposed therapy and previously prescribed medication, and the route of therapy administration. The constructed domain ontology contains 1,267,004 classes, 7,608,725 axioms, and 1,266,993 members of "SubClassOf" that pertain to infectious diseases, bacteria, syndromes, anti-bacterial drugs and other relevant components. The system includes 507 infectious diseases and their therapy methods in combination with 332 different infection sites, 936 relevant symptoms of the digestive, reproductive, neurological and other systems, 371 types of complications, 838,407 types of bacteria, 341 types of antibiotics, 1504 pairs of reaction rates (antibacterial spectrum) between antibiotics and bacteria, 431 pairs of drug interaction relationships and 86 pairs of antibiotic-specific population contraindicated relationships. Compared with the existing infectious disease-relevant ontologies in the field of knowledge comprehension, this ontology is more complete. Analysis of IDDAP's performance in terms of classifiers based on receiver operating characteristic (ROC) curve results (89.91%) revealed IDDAP's advantages when combined with our ontology. This study attempted to bridge the patient/caregiver gap by building a sophisticated application that uses artificial intelligence and machine learning computational techniques to perform data-driven decision-making at the point of primary care. The first level of decision-making is conducted by the IDDAP and provides the patient with a first-line therapy. Patients can then make a subjective judgment, and if any questions arise, should consult a physician for subsequent decisions, particularly in complicated cases or in cases in which the necessary information is not yet available in the knowledge base. Copyright © 2018 Elsevier B.V. All rights reserved.

Differences in neural activation as a function of risk-taking task parameters

PubMed Central

Congdon, Eliza; Bato, Angelica A.; Schonberg, Tom; Mumford, Jeanette A.; Karlsgodt, Katherine H.; Sabb, Fred W.; London, Edythe D.; Cannon, Tyrone D.; Bilder, Robert M.; Poldrack, Russell A.

2013-01-01

Despite evidence supporting a relationship between impulsivity and naturalistic risk-taking, the relationship of impulsivity with laboratory-based measures of risky decision-making remains unclear. One factor contributing to this gap in our understanding is the degree to which different risky decision-making tasks vary in their details. We conducted an fMRI investigation of the Angling Risk Task (ART), which is an improved behavioral measure of risky decision-making. In order to examine whether the observed pattern of neural activation was specific to the ART or generalizable, we also examined correlates of the Balloon Analog Risk Taking (BART) task in the same sample of 23 healthy adults. Exploratory analyses were conducted to examine the relationship between neural activation, performance, impulsivity and self-reported risk-taking. While activation in a valuation network was associated with reward tracking during the ART but not the BART, increased fronto-cingulate activation was seen during risky choice trials in the BART as compared to the ART. Thus, neural activation during risky decision-making trials differed between the two tasks, and this observation was likely driven by differences in task parameters, namely the absence vs. presence of ambiguity and/or stationary vs. increasing probability of loss on the ART and BART, respectively. Exploratory association analyses suggest that sensitivity of neural response to the magnitude of potential reward during the ART was associated with a suboptimal performance strategy, higher scores on a scale of dysfunctional impulsivity (DI) and a greater likelihood of engaging in risky behaviors, while this pattern was not seen for the BART. Our results suggest that the ART is decomposable and associated with distinct patterns of neural activation; this represents a preliminary step toward characterizing a behavioral measure of risky decision-making that may support a better understanding of naturalistic risk-taking. PMID:24137106

Sex-specific enhancement of palatability-driven feeding in adolescent rats

PubMed Central

Liu, Angela T.; Murphy, Niall P.; Maidment, Nigel T.; Ostlund, Sean B.

2017-01-01

It has been hypothesized that brain development during adolescence perturbs reward processing in a way that may ultimately contribute to the risky decision making associated with this stage of life, particularly in young males. To investigate potential reward dysfunction during adolescence, Experiment 1 examined palatable fluid intake in rats as a function of age and sex. During a series of twice-weekly test sessions, non-food-deprived rats were given the opportunity to voluntarily consume a highly palatable sweetened condensed milk (SCM) solution. We found that adolescent male, but not female, rats exhibited a pronounced, transient increase in SCM intake (normalized by body weight) that was centered around puberty. Additionally, adult females consumed more SCM than adult males and adolescent females. Using a well-established analytical framework to parse the influences of reward palatability and satiety on the temporal structure of feeding behavior, we found that palatability-driven intake at the outset of the meal was significantly elevated in adolescent males, relative to the other groups. Furthermore, although we found that there were some group differences in the onset of satiety, they were unlikely to contribute to differences in intake. Experiment 2 confirmed that adolescent male rats exhibit elevated palatable fluid consumption, relative to adult males, even when a non-caloric saccharin solution was used as the taste stimulus, demonstrating that these results were unlikely to be related to age-related differences in metabolic need. These findings suggest that elevated palatable food intake during adolescence is sex specific and driven by a fundamental change in reward processing. As adolescent risk taking has been hypothesized as a potential result of hypersensitivity to and overvaluation of appetitive stimuli, individual differences in reward palatability may factor into individual differences in adolescent risky decision making. PMID:28708901

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.

Personalized health care and health information technology policy: an exploratory analysis.

PubMed

Wald, Jonathan S; Shapiro, Michael

2013-01-01

Personalized healthcare (PHC) is envisioned to enhance clinical practice decision-making using new genome-driven knowledge that tailors diagnosis, treatment, and prevention to the individual patient. In 2012, we conducted a focused environmental scan and informal interviews with fifteen experts to anticipate how PHC might impact health Information Technology (IT) policy in the United States. Findings indicatedthat PHC has a variable impact on current clinical practice, creates complex questions for providers, patients, and policy-makers, and will require a robust health IT infrastructure with advanced data architecture, clinical decision support, provider workflow tools, and re-use of clinical data for research. A number of health IT challenge areas were identified, along with five policy areas including: interoperable clinical decision support, standards for patient values and preferences, patient engagement, data transparency, and robust privacy and security.

E-HOSPITAL - A Digital Workbench for Hospital Operations and Services Planning Using Information Technology and Algebraic Languages.

PubMed

Gartner, Daniel; Padman, Rema

2017-01-01

In this paper, we describe the development of a unified framework and a digital workbench for the strategic, tactical and operational hospital management plan driven by information technology and analytics. The workbench can be used not only by multiple stakeholders in the healthcare delivery setting, but also for pedagogical purposes on topics such as healthcare analytics, services management, and information systems. This tool combines the three classical hierarchical decision-making levels in one integrated environment. At each level, several decision problems can be chosen. Extensions of mathematical models from the literature are presented and incorporated into the digital platform. In a case study using real-world data, we demonstrate how we used the workbench to inform strategic capacity planning decisions in a multi-hospital, multi-stakeholder setting in the United Kingdom.

Integrating Strategic and Operational Decision Making Using Data-Driven Dashboards: The Case of St. Joseph Mercy Oakland Hospital.

PubMed

Jack Weiner; Balijepally, Venugopal; Tanniru, Mohan

2015-01-01

Hospitals have invested and continue to invest heavily in building information systems to support operations at various levels of administration. These systems generate a lot of data but fail to effectively convert these data into actionable information for decision makers. Such ineffectiveness often is attributed to a lack of alignment between strategic planning and information technology (IT) initiatives supporting operational goals. We present a case study that illustrates how the use of digital dashboards at St. Joseph Mercy Oakland (SJMO) Hospital in Pontiac, Michigan, was instrumental in supporting such an alignment. Driven by a focus on key performance indicators (KPIs), dashboard applications also led to other tangible and intangible benefits. An ability to track KPIs over time and against established targets, with drill-down capabilities, allowed leadership to hold staff members accountable for achieving their performance targets. By displaying the dashboards in prominent locations (such as operational unit floors, the physicians' cafeteria, and nursing stations), SJMO ushered in transparency in the planning and monitoring processes. The need to develop KPI metrics and drive data collection efforts became ingrained in the work ethos of people at every level of the organization. Although IT-enabled dashboards have been instrumental in supporting this cultural transformation, the focus of investment was the ability of technology to make collective vision and action the responsibility of all stakeholders.

Augmented Personalized Health: How Smart Data with IoTs and AI is about to Change Healthcare

PubMed Central

Sheth, Amit; Jaimini, Utkarshani; Thirunarayan, Krishnaprasad; Banerjee, Tanvi

2017-01-01

Healthcare as we know it is in the process of going through a massive change - from episodic to continuous, from disease focused to wellness and quality of life focused, from clinic centric to anywhere a patient is, from clinician controlled to patient empowered, and from being driven by limited data to 360-degree, multimodal personal-public-population physical-cyber-social big data driven. While ability to create and capture data is already here, the upcoming innovations will be in converting this big data into smart data through contextual and personalized processing such that patients and clinicians can make better decisions and take timely actions for augmented personalized health. This paper outlines current opportunities and challenges, with a focus on key AI approaches to make this a reality. The broader vision is exemplified using three ongoing applications (asthma in children, bariatric surgery, and pain management) as part of the Kno.e.sis kHealth personalized digital health initiative. PMID:29399675

Augmented Personalized Health: How Smart Data with IoTs and AI is about to Change Healthcare.

PubMed

Sheth, Amit; Jaimini, Utkarshani; Thirunarayan, Krishnaprasad; Banerjee, Tanvi

2017-09-01

Healthcare as we know it is in the process of going through a massive change - from episodic to continuous, from disease focused to wellness and quality of life focused, from clinic centric to anywhere a patient is, from clinician controlled to patient empowered, and from being driven by limited data to 360-degree, multimodal personal-public-population physical-cyber-social big data driven. While ability to create and capture data is already here, the upcoming innovations will be in converting this big data into smart data through contextual and personalized processing such that patients and clinicians can make better decisions and take timely actions for augmented personalized health. This paper outlines current opportunities and challenges, with a focus on key AI approaches to make this a reality. The broader vision is exemplified using three ongoing applications (asthma in children, bariatric surgery, and pain management) as part of the Kno.e.sis kHealth personalized digital health initiative.

How to save distressed IDS-physician marriages: a case study.

PubMed

Collins, H; Johnson, B A

1998-04-01

A hospital-driven IDS that encounters serious problems resulting from ownership of a physician practice should address those problems by focusing on three core areas: vision and leadership, effectiveness of operations, and physician compensation arrangements. If changes in these areas do not lead to improvements, the IDS may need to consider organizational restructuring. In one case study, a hospital-driven IDS faced the problem of owning a poorly performing MSO with a captive physician group. The IDS's governing board determined that the organization lacked effective communication with the physicians and that realization of the organization's vision would require greater physician involvement in organizational decision making. The organization is expected to undergo some corporate reorganization in which physicians will acquire an equity interest in the enterprise.

Against all odds -- Probabilistic forecasts and decision making

NASA Astrophysics Data System (ADS)

Liechti, Katharina; Zappa, Massimiliano

2015-04-01

In the city of Zurich (Switzerland) the setting is such that the damage potential due to flooding of the river Sihl is estimated to about 5 billion US dollars. The flood forecasting system that is used by the administration for decision making runs continuously since 2007. It has a time horizon of max. five days and operates at hourly time steps. The flood forecasting system includes three different model chains. Two of those are run by the deterministic NWP models COSMO-2 and COSMO-7 and one is driven by the probabilistic NWP COSMO-Leps. The model chains are consistent since February 2010, so five full years are available for the evaluation for the system. The system was evaluated continuously and is a very nice example to present the added value that lies in probabilistic forecasts. The forecasts are available on an online-platform to the decision makers. Several graphical representations of the forecasts and forecast-history are available to support decision making and to rate the current situation. The communication between forecasters and decision-makers is quite close. To put it short, an ideal situation. However, an event or better put a non-event in summer 2014 showed that the knowledge about the general superiority of probabilistic forecasts doesn't necessarily mean that the decisions taken in a specific situation will be based on that probabilistic forecast. Some years of experience allow gaining confidence in the system, both for the forecasters and for the decision-makers. Even if from the theoretical point of view the handling during crisis situation is well designed, a first event demonstrated that the dialog with the decision-makers still lacks of exercise during such situations. We argue, that a false alarm is a needed experience to consolidate real-time emergency procedures relying on ensemble predictions. A missed event would probably also fit, but, in our case, we are very happy not to report about this option.

The Development of a Strategic Prioritisation Method for Green Supply Chain Initiatives.

PubMed

Masoumik, S Maryam; Abdul-Rashid, Salwa Hanim; Olugu, Ezutah Udoncy

2015-01-01

To maintain a competitive position, companies are increasingly required to integrate their proactive environmental strategies into their business strategies. The shift from reactive and compliance-based to proactive and strategic environmental management has driven companies to consider the strategic factors while identifying the areas in which they should focus their green initiatives. In previous studies little attention was given to providing the managers with a basis from which they could strategically prioritise these green initiatives across their companies' supply chains. Considering this lacuna in the literature, we present a decision-making method for prioritising green supply chain initiatives aligned with the preferred green strategies alternatives for the manufacturing companies. To develop this method, the study considered a position between determinism and the voluntarism orientation of environmental management involving both external pressures and internal competitive drivers and key resources as decision factors. This decision-making method was developed using the analytic network process (ANP) technique. The elements of the decision model were derived from the literature. The causal relationships among the multiple decision variables were validated based on the results of structural equation modelling (SEM) using a dataset collected from a survey of the ISO 14001-certified manufacturers in Malaysia. A portion of the relative weights required for computation in ANP was also calculated using the SEM results. A case study is presented to demonstrate the applicability of the method.

The Development of a Strategic Prioritisation Method for Green Supply Chain Initiatives

PubMed Central

Masoumik, S. Maryam; Abdul-Rashid, Salwa Hanim; Olugu, Ezutah Udoncy

2015-01-01

To maintain a competitive position, companies are increasingly required to integrate their proactive environmental strategies into their business strategies. The shift from reactive and compliance-based to proactive and strategic environmental management has driven companies to consider the strategic factors while identifying the areas in which they should focus their green initiatives. In previous studies little attention was given to providing the managers with a basis from which they could strategically prioritise these green initiatives across their companies’ supply chains. Considering this lacuna in the literature, we present a decision-making method for prioritising green supply chain initiatives aligned with the preferred green strategies alternatives for the manufacturing companies. To develop this method, the study considered a position between determinism and the voluntarism orientation of environmental management involving both external pressures and internal competitive drivers and key resources as decision factors. This decision-making method was developed using the analytic network process (ANP) technique. The elements of the decision model were derived from the literature. The causal relationships among the multiple decision variables were validated based on the results of structural equation modelling (SEM) using a dataset collected from a survey of the ISO 14001-certified manufacturers in Malaysia. A portion of the relative weights required for computation in ANP was also calculated using the SEM results. A case study is presented to demonstrate the applicability of the method. PMID:26618353

A Decision Fusion Framework for Treatment Recommendation Systems.

PubMed

Mei, Jing; Liu, Haifeng; Li, Xiang; Xie, Guotong; Yu, Yiqin

2015-01-01

Treatment recommendation is a nontrivial task--it requires not only domain knowledge from evidence-based medicine, but also data insights from descriptive, predictive and prescriptive analysis. A single treatment recommendation system is usually trained or modeled with a limited (size or quality) source. This paper proposes a decision fusion framework, combining both knowledge-driven and data-driven decision engines for treatment recommendation. End users (e.g. using the clinician workstation or mobile apps) could have a comprehensive view of various engines' opinions, as well as the final decision after fusion. For implementation, we leverage several well-known fusion algorithms, such as decision templates and meta classifiers (of logistic and SVM, etc.). Using an outcome-driven evaluation metric, we compare the fusion engine with base engines, and our experimental results show that decision fusion is a promising way towards a more valuable treatment recommendation.

Sneeze to leave: African wild dogs (Lycaon pictus) use variable quorum thresholds facilitated by sneezes in collective decisions.

PubMed

Walker, Reena H; King, Andrew J; McNutt, J Weldon; Jordan, Neil R

2017-09-13

In despotically driven animal societies, one or a few individuals tend to have a disproportionate influence on group decision-making and actions. However, global communication allows each group member to assess the relative strength of preferences for different options among their group-mates. Here, we investigate collective decisions by free-ranging African wild dog packs in Botswana. African wild dogs exhibit dominant-directed group living and take part in stereotyped social rallies: high energy greeting ceremonies that occur before collective movements. Not all rallies result in collective movements, for reasons that are not well understood. We show that the probability of rally success (i.e. group departure) is predicted by a minimum number of audible rapid nasal exhalations (sneezes), within the rally. Moreover, the number of sneezes needed for the group to depart (i.e. the quorum) was reduced whenever dominant individuals initiated rallies, suggesting that dominant participation increases the likelihood of a rally's success, but is not a prerequisite. As such, the 'will of the group' may override dominant preferences when the consensus of subordinates is sufficiently great. Our findings illustrate how specific behavioural mechanisms (here, sneezing) allow for negotiation (in effect, voting) that shapes decision-making in a wild, socially complex animal society. © 2017 The Author(s).

Gambling with your life: the process of breast cancer treatment decision making in Chinese women.

PubMed

Lam, Wendy Wt; Fielding, Richard; Chan, Miranda; Chow, Louis; Or, Amy

2005-01-01

Treatment decision making (TDM) studies have primarily focused on assessing TDM quality and predominantly presume rational analytic processes as the gold standard. In a grounded theory study of 22 Hong Kong Chinese women following breast surgery who completed an in-depth interview exploring the process of TDM in breast cancer (BC), narrative data showed that discovery of a breast abnormality and emotional responses to BC diagnosis influence the TDM process. Lack of guidance from surgeons impaired TDM. Decisions were, for the most part, made using intuitive, pragmatic and emotionally driven criteria in the absence of complete information. The experience of TDM, which was likened to gambling, did not end once the decision was made but unfolded while waiting for surgery and the post-operative report. In this waiting period, women were emotionally overwhelmed by fear of death and the uncertainty of the surgical outcome, and equivocated over whether they had made the 'right' choice. This suggests that Chinese women feel they are gambling with their lives during TDM. These women are particularly emotionally vulnerable whilst waiting for their surgery and the post-surgical clinical pathology results. Providing emotional support is particularly important at this time when these women are overwhelmed by uncertainty. 2004 John Wiley & Sons, Ltd.

A framework for a process-driven common foundation programme for graduates.

PubMed

Jasper, M; Rolfe, G

1993-10-01

This paper discusses some of the problems encountered in writing a shortened Common Foundation Programme in nursing for graduates, and outlines a course which takes as its starting point the particular educational needs and requirements of the student group. Thus, the first question to be addressed by the curriculum writers when designing the course was "How can we teach these students?", rather than "What can we teach them?". The resulting process-driven course is heavily influenced by the student-centred philosophy of Carl Rogers, and utilizes a variety of large- and small-group methods to facilitate the students in gradually taking responsibility for, and making decisions about, their learning needs. The paper continues with some strategies for ensuring a smooth transition from a tutor-led, syllabus-driven start to the course, to a student-led, process-driven finish for both the theoretical and clinical components, and for the assessment schedule. Finally, a student-centred approach to evaluation is briefly outlined, and the paper concludes by suggesting that the principles employed in designing and implementing this course could be successfully transferred to a wide variety of other educational settings.

Using the Alaska Ocean Observing System to Inform Decision Making for Coastal Resiliency Relating to Inundation, Ocean Acidification, Harmful Algal Blooms, Navigation Safety and Impacts of Vessel Traffic

NASA Astrophysics Data System (ADS)

McCammon, M.

2017-12-01

State and federal agencies, coastal communities and Alaska Native residents, and non-governmental organizations are increasingly turning to the Alaska Ocean Observing System (AOOS) as a major source of ocean and coastal data and information products to inform decision making relating to a changing Arctic. AOOS implements its mission to provide ocean observing data and information to meet stakeholder needs by ensuring that all programs are "science based, stakeholder driven and policy neutral." Priority goals are to increase access to existing coastal and ocean data; package information and data in useful ways to meet stakeholder needs; and increase observing and forecasting capacity in all regions of the state. Recently certified by NOAA, the AOOS Data Assembly Center houses the largest collection of real-time ocean and coastal data, environmental models, and biological data in Alaska, and develops tools and applications to make it more publicly accessible and useful. Given the paucity of observations in the Alaska Arctic, the challenge is how to make decisions with little data compared to other areas of the U.S. coastline. AOOS addresses this issue by: integrating and visualizing existing data; developing data and information products and tools to make data more useful; serving as a convener role in areas such as coastal inundation and flooding, impacts of warming temperatures on food security, ocean acidification, observing technologies and capacity; and facilitating planning efforts to increase observations. In this presentation, I will give examples of each of these efforts, lessons learned, and suggestions for future actions.

Nonurgent use of a pediatric emergency department: a preliminary qualitative study.

PubMed

Chin, Nancy P; Goepp, Julius G; Malia, Timothy; Harris, LeWanza; Poordabbagh, Armin

2006-01-01

To understand patterns of decision making among families presenting to a pediatric emergency department (ED) for nonacute care and to understand pediatric ED staff responses. Cross-sectional qualitative study using in-depth interviews, direct observations, and nonidentifying demographic data. Eleven percent of visits made during the study period were identified as nonacute. All were made by families from low-income areas. Three main themes emerged: (1) most families had been referred by their primary care providers; (2) the complexity of living in low-income areas makes the ED a choice of convenience for these stressed families; and (3) mistrust of primary health services was not identified by our respondents as a motivator for ED utilization, in contrast with other published data. Two themes emerged from ED staff: (1) actual nonurgent visit rates were lower than staff estimates; and (2) these visits produced frustration among staff members, although their degrees of insight and understanding of factors motivating these visits were variable. In this setting, nonacute visits occurred with lower than perceived frequency and caused disproportionate frustration among staff and families. These visits appear to be driven more by consequences of system design and structure than by family members' decision making. Mistrust of primary care services was not a strong family decision-making factor; the study's setting may have limited its ability to capture such data. Recommended system changes to lower barriers to primary care include expanded office hours, subsidized staffing for offices in medically underserved areas, and lowering barriers to sick care.

Combining Hydrological Modeling and Remote Sensing Observations to Enable Data-Driven Decision Making for Devils Lake Flood Mitigation in a Changing Climate

NASA Technical Reports Server (NTRS)

Zhang, Xiaodong; Kirilenko, Andrei; Lim, Howe; Teng, Williams

2010-01-01

This slide presentation reviews work to combine the hydrological models and remote sensing observations to monitor Devils Lake in North Dakota, to assist in flood damage mitigation. This reports on the use of a distributed rainfall-runoff model, HEC-HMS, to simulate the hydro-dynamics of the lake watershed, and used NASA's remote sensing data, including the TRMM Multi-Satellite Precipitation Analysis (TMPA) and AIRS surface air temperature, to drive the model.

NASA's Agricultural Program: A USDA/Grower Partnership

NASA Technical Reports Server (NTRS)

McKellip, Rodney; Thomas, Michael

2002-01-01

Ag20/20 is a partnership between USDA, NASA, and four national commodity associations. It is driven by the information needs of U.S. farmers. Ag20/20 is focused on utilization of earth science and remote sensing for decision-making and oriented toward economically viable operational solutions. Its purpose is to accelerate the use of remote sensing and other geospatial technologies on the farm to: 1) Increase the production efficiency of the American farmer; 2) Reduce crop production risks; 3) Improve environmental stewardship tools for agricultural production.

Some sequential, distribution-free pattern classification procedures with applications

NASA Technical Reports Server (NTRS)

Poage, J. L.

1971-01-01

Some sequential, distribution-free pattern classification techniques are presented. The decision problem to which the proposed classification methods are applied is that of discriminating between two kinds of electroencephalogram responses recorded from a human subject: spontaneous EEG and EEG driven by a stroboscopic light stimulus at the alpha frequency. The classification procedures proposed make use of the theory of order statistics. Estimates of the probabilities of misclassification are given. The procedures were tested on Gaussian samples and the EEG responses.

Optimal strategies for electric energy contract decision making

NASA Astrophysics Data System (ADS)

Song, Haili

2000-10-01

The power industry restructuring in various countries in recent years has created an environment where trading of electric energy is conducted in a market environment. In such an environment, electric power companies compete for the market share through spot and bilateral markets. Being profit driven, electric power companies need to make decisions on spot market bidding, contract evaluation, and risk management. New methods and software tools are required to meet these upcoming needs. In this research, bidding strategy and contract pricing are studied from a market participant's viewpoint; new methods are developed to guide a market participant in spot and bilateral market operation. A supplier's spot market bidding decision is studied. Stochastic optimization is formulated to calculate a supplier's optimal bids in a single time period. This decision making problem is also formulated as a Markov Decision Process. All the competitors are represented by their bidding parameters with corresponding probabilities. A systematic method is developed to calculate transition probabilities and rewards. The optimal strategy is calculated to maximize the expected reward over a planning horizon. Besides the spot market, a power producer can also trade in the bilateral markets. Bidding strategies in a bilateral market are studied with game theory techniques. Necessary and sufficient conditions of Nash Equilibrium (NE) bidding strategy are derived based on the generators' cost and the loads' willingness to pay. The study shows that in any NE, market efficiency is achieved. Furthermore, all Nash equilibria are revenue equivalent for the generators. The pricing of "Flexible" contracts, which allow delivery flexibility over a period of time with a fixed total amount of electricity to be delivered, is analyzed based on the no-arbitrage pricing principle. The proposed algorithm calculates the price based on the optimality condition of the stochastic optimization formulation. Simulation examples illustrate the tradeoffs between prices and scheduling flexibility. Spot bidding and contract pricing are not independent decision processes. The interaction between spot bidding and contract evaluation is demonstrated with game theory equilibrium model and market simulation results. It leads to the conclusion that a market participant's contract decision making needs to be further investigated as an integrated optimization formulation.

Building an understanding of water use innovation adoption processes through farmer-driven experimentation

NASA Astrophysics Data System (ADS)

Sturdy, Jody D.; Jewitt, Graham P. W.; Lorentz, Simon A.

Smallholder farmers in Southern Africa are faced with the challenge of securing their livelihoods within the context of a wide variety of biophysical and socio-economic constraints. Agriculture is inherently risky, particularly in regions prone to drought or dry spells, and risk-averse farmers may be viewed by researchers or extension agents as reluctant to invest in agricultural innovations that have potential to improve their livelihoods. However, farmers themselves are more interested in personal livelihood security than any other stakeholder and it is the farmers’ perceptions of needs, investment options and risks that drive their decision-making process. A holistic approach to agricultural innovation development and extension is needed to address both socio-economic and biophysical dynamics that influence adoption and dissemination of innovations. This paper, presents a methodology for involving farmers from the Bergville district of South Africa in the process of innovation development through facilitation of farmer-driven gardening experiments. Facilitating farmer-driven experimentation allows farmers to methodically assess the value of innovations they choose to study while providing researchers with a venue for learning about socio-economic as well as biophysical influences on farmers’ decisions. With this knowledge, researchers can focus on developing innovations that are socially and economically appropriate and therefore, more readily adoptable. The participatory process gave farmers the tools they needed to make informed decisions through critical thinking and analysis and improved their confidence in explaining the function of innovations to others. Researchers were able to use farmers’ manually collected data and observations to supplement laboratory generated and electronically recorded information about soil water dynamics to understand water balances associated with different garden bed designs, and to investigate whether trench beds, drip irrigation and water harvesting with run-on ditches tended to improve water use efficiency. Wetting front detectors (WFD) were shown to have some potential as management tools for farmers, provided certain limitations are addressed, while drip irrigation was found to be impractical because the available drip kits were prone to malfunction and farmers believed they did not provide enough water to the plants. Farmers participating in a series of monthly, hands-on workshops that encouraged individual experimentation tended to adopt and sustain use of many introduced garden innovations. Farmers who were also seriously involved in a formalized research and experimentation process at their own homesteads became more proficient with gardening systems in general, through continual trial-and-error comparisons and making decisions based on observations, than those who were not involved. This suggests that the practice of on-going experimentation, once established, reaches beyond the limits of facilitation by researchers or extension agents, into the realm of sustainable change and livelihood improvement through adoption, adaptation and dissemination of agricultural innovations.

Fast but not intuitive, slow but not reflective: Decision conflict drives reaction times in social dilemmas.

PubMed

Evans, Anthony M; Dillon, Kyle D; Rand, David G

2015-10-01

When people have the chance to help others at a cost to themselves, are cooperative decisions driven by intuition or reflection? To answer this question, recent studies have tested the relationship between reaction times (RTs) and cooperation, reporting both positive and negative correlations. To reconcile this apparent contradiction, we argue that decision conflict (rather than the use of intuition vs. reflection) drives response times, leading to an inverted-U shaped relationship between RT and cooperation. Studies 1 through 3 show that intermediate decisions take longer than both extremely selfish and extremely cooperative decisions. Studies 4 and 5 find that the conflict between self-interested and cooperative motives explains individual differences in RTs. Manipulating conflictedness causes longer RTs and more intermediate decisions, and RTs mediate the relationship between conflict and intermediate decisions. Finally, Studies 6 and 7 demonstrate that conflict is distinct from reflection by manipulating the use of intuition (vs. reflection). Experimentally promoting reliance on intuition increases cooperation, but has no effects on decision extremity or feelings of conflictedness. In sum, we provide evidence that RTs should not be interpreted as a direct proxy for the use of intuitive or reflective processes, and dissociate the effects of conflict and reflection in social decision making. (c) 2015 APA, all rights reserved).

Lakeside: Merging Urban Design with Scientific Analysis

ScienceCinema

Guzowski, Leah; Catlett, Charlie; Woodbury, Ed

2018-01-16

Researchers at the U.S. Department of Energy's Argonne National Laboratory and the University of Chicago are developing tools that merge urban design with scientific analysis to improve the decision-making process associated with large-scale urban developments. One such tool, called LakeSim, has been prototyped with an initial focus on consumer-driven energy and transportation demand, through a partnership with the Chicago-based architectural and engineering design firm Skidmore, Owings & Merrill, Clean Energy Trust and developer McCaffery Interests. LakeSim began with the need to answer practical questions about urban design and planning, requiring a better understanding about the long-term impact of design decisions on energy and transportation demand for a 600-acre development project on Chicago's South Side - the Chicago Lakeside Development project.

Data Mining for Understanding and Improving Decision-making Affecting Ground Delay Programs

NASA Technical Reports Server (NTRS)

Kulkarni, Deepak; Wang, Yao; Sridhar, Banavar

2013-01-01

The continuous growth in the demand for air transportation results in an imbalance between airspace capacity and traffic demand. The airspace capacity of a region depends on the ability of the system to maintain safe separation between aircraft in the region. In addition to growing demand, the airspace capacity is severely limited by convective weather. During such conditions, traffic managers at the FAA's Air Traffic Control System Command Center (ATCSCC) and dispatchers at various Airlines' Operations Center (AOC) collaborate to mitigate the demand-capacity imbalance caused by weather. The end result is the implementation of a set of Traffic Flow Management (TFM) initiatives such as ground delay programs, reroute advisories, flow metering, and ground stops. Data Mining is the automated process of analyzing large sets of data and then extracting patterns in the data. Data mining tools are capable of predicting behaviors and future trends, allowing an organization to benefit from past experience in making knowledge-driven decisions.

Does a brief state mindfulness induction moderate disgust-driven social avoidance and decision-making? An experimental investigation.

PubMed

Reynolds, Lisa M; Lin, Yee Sing; Zhou, Eric; Consedine, Nathan S

2015-02-01

In this experimental study, we evaluated whether manipulated disgust and mindfulness predicted social avoidance in bowel health contexts. Community participants (n = 101) were randomised to conditions in which disgust and/or state mindfulness were experimentally induced. Tasks assessing social avoidance and perceptions of available social networks in the context of bowel/health problems were conducted. Manipulation checks confirmed the elicitation of disgust and state mindfulness in the applicable conditions. As expected, persons in the disgust condition were more likely to exhibit immediate social avoidance (rejecting a glass of water). State disgust predicted greater socially avoidant decision-making, less decisional conflict, and smaller social network maps. State mindfulness predicted fewer names on inner network circles and amplified the effect of disgust on creating smaller social network maps. This report furthers understanding of disgust and avoidance in bowel health contexts, and suggests the need for caution in mindfulness interventions that raise awareness of emotion without also providing skills in emotional regulation.

Invited review: Helping dairy farmers to improve economic performance utilizing data-driving decision support tools.

PubMed

Cabrera, V E

2018-01-01

The objective of this review paper is to describe the development and application of a suite of more than 40 computerized dairy farm decision support tools contained at the University of Wisconsin-Madison (UW) Dairy Management website http://DairyMGT.info. These data-driven decision support tools are aimed to help dairy farmers improve their decision-making, environmental stewardship and economic performance. Dairy farm systems are highly dynamic in which changing market conditions and prices, evolving policies and environmental restrictions together with every time more variable climate conditions determine performance. Dairy farm systems are also highly integrated with heavily interrelated components such as the dairy herd, soils, crops, weather and management. Under these premises, it is critical to evaluate a dairy farm following a dynamic integrated system approach. For this approach, it is crucial to use meaningful data records, which are every time more available. These data records should be used within decision support tools for optimal decision-making and economic performance. Decision support tools in the UW-Dairy Management website (http://DairyMGT.info) had been developed using combination and adaptation of multiple methods together with empirical techniques always with the primary goal for these tools to be: (1) highly user-friendly, (2) using the latest software and computer technologies, (3) farm and user specific, (4) grounded on the best scientific information available, (5) remaining relevant throughout time and (6) providing fast, concrete and simple answers to complex farmers' questions. DairyMGT.info is a translational innovative research website in various areas of dairy farm management that include nutrition, reproduction, calf and heifer management, replacement, price risk and environment. This paper discusses the development and application of 20 selected (http://DairyMGT.info) decision support tools.

Medical sieve: a cognitive assistant for radiologists and cardiologists

NASA Astrophysics Data System (ADS)

Syeda-Mahmood, T.; Walach, E.; Beymer, D.; Gilboa-Solomon, F.; Moradi, M.; Kisilev, P.; Kakrania, D.; Compas, C.; Wang, H.; Negahdar, R.; Cao, Y.; Baldwin, T.; Guo, Y.; Gur, Y.; Rajan, D.; Zlotnick, A.; Rabinovici-Cohen, S.; Ben-Ari, R.; Guy, Amit; Prasanna, P.; Morey, J.; Boyko, O.; Hashoul, S.

2016-03-01

Radiologists and cardiologists today have to view large amounts of imaging data relatively quickly leading to eye fatigue. Further, they have only limited access to clinical information relying mostly on their visual interpretation of imaging studies for their diagnostic decisions. In this paper, we present Medical Sieve, an automated cognitive assistant for radiologists and cardiologists designed to help in their clinical decision-making. The sieve is a clinical informatics system that collects clinical, textual and imaging data of patients from electronic health records systems. It then analyzes multimodal content to detect anomalies if any, and summarizes the patient record collecting all relevant information pertinent to a chief complaint. The results of anomaly detection are then fed into a reasoning engine which uses evidence from both patient-independent clinical knowledge and large-scale patient-driven similar patient statistics to arrive at potential differential diagnosis to help in clinical decision making. In compactly summarizing all relevant information to the clinician per chief complaint, the system still retains links to the raw data for detailed review providing holistic summaries of patient conditions. Results of clinical studies in the domains of cardiology and breast radiology have already shown the promise of the system in differential diagnosis and imaging studies summarization.

Sustainability is possible despite greed - Exploring the nexus between profitability and sustainability in common pool resource systems.

PubMed

Osten, Friedrich Burkhard von der; Kirley, Michael; Miller, Tim

2017-05-23

The sustainable use of common pool resources has become a significant global challenge. It is now widely accepted that specific mechanisms such as community-based management strategies, institutional responses such as resource privatization, information availability and emergent social norms can be used to constrain individual 'harvesting' to socially optimal levels. However, there is a paucity of research focused specifically on aligning profitability and sustainability goals. In this paper, an integrated mathematical model of a common pool resource game is developed to explore the nexus between the underlying costs and benefits of harvesting decisions and the sustainable level of a shared, dynamic resource. We derive optimal harvesting efforts analytically and then use numerical simulations to show that individuals in a group can learn to make harvesting decisions that lead to the globally optimal levels. Individual agents make their decision based on signals received and a trade-off between economic and ecological sustainability. When the balance is weighted towards profitability, acceptable economic and social outcomes emerge. However, if individual agents are solely driven by profit, the shared resource is depleted in the long run - sustainability is possible despite some greed, but too much will lead to over-exploitation.

Managing psychosocial issues faced by young women with breast cancer at the time of diagnosis and during active treatment.

PubMed

Fernandes-Taylor, Sara; Adesoye, Taiwo; Bloom, Joan R

2015-09-01

This review examines recent literature on the psychosocial needs of and interventions for young women. We focus on the active treatment period given the toxicity of treatment, the incidence of anxiety, and depressive symptoms in these women during treatment. This review summarizes research relevant to addressing their social and emotional concerns. Young women undergoing treatment for breast cancer remain understudied despite unique needs. Psychoeducational interventions help to relieve symptoms and emotional distress during treatment, but effects do not appear to persist over the longer term. In the clinical context, the performance of prognostic-risk prediction models in this population is poor. Surgical decision-making is often driven by fear of recurrence and body image rather than prognosis, and decision aids may help young women to synthesize information to preserve their role in the treatment process. First, shared decision-making, second, balancing body image, fear of recurrence, and recommended treatment, and third, palliative care for metastasis are essential research priorities for the clinical setting. In the larger social context, unique family/partner dynamics as well as financial and insurance concerns warrant particular attention in this population.

Data quality and processing for decision making: divergence between corporate strategy and manufacturing processes

NASA Astrophysics Data System (ADS)

McNeil, Ronald D.; Miele, Renato; Shaul, Dennis

2000-10-01

Information technology is driving improvements in manufacturing systems. Results are higher productivity and quality. However, corporate strategy is driven by a number of factors and includes data and pressure from multiple stakeholders, which includes employees, managers, executives, stockholders, boards, suppliers and customers. It is also driven by information about competitors and emerging technology. Much information is based on processing of data and the resulting biases of the processors. Thus, stakeholders can base inputs on faulty perceptions, which are not reality based. Prior to processing, data used may be inaccurate. Sources of data and information may include demographic reports, statistical analyses, intelligence reports (e.g., marketing data), technology and primary data collection. The reliability and validity of data as well as the management of sources and information is critical element to strategy formulation. The paper explores data collection, processing and analyses from secondary and primary sources, information generation and report presentation for strategy formulation and contrast this with data and information utilized to drive internal process such as manufacturing. The hypothesis is that internal process, such as manufacturing, are subordinate to corporate strategies. The impact of possible divergence in quality of decisions at the corporate level on IT driven, quality-manufacturing processes based on measurable outcomes is significant. Recommendations for IT improvements at the corporate strategy level are given.

Science Teacher Decision-Making in a Climate of Heightened Accountability: A Rhizomatic Case Study Analysis of Two Science Departments in New York City

NASA Astrophysics Data System (ADS)

Purohit, Kiran Dilip

Secondary science teachers make many daily decisions in the enactment of curriculum. Although curriculum materials are widely available to address science content, practices, and skills, the consideration that goes into deciding how and whether to use such materials is complicated by teachers' beliefs about science, their understandings of school-level accountability and testing measures, and their perspectives on the adolescent students they teach. This study addresses the need to understand how teachers consider multiple forces in their enactment of science curriculum. The purpose of this study was to explore the ways that discourses around accountability, science, and science education emerge in the narratives around teachers' decision-making in secondary science classrooms. Using a case study approach, I worked at two school sites with two pairs of science teachers. We established criteria for critical incidents together, then teachers identified critical decision-making moments in their classrooms. We analyzed those incidents together using a consultancy protocol, allowing teachers to focus their thinking on reframing the incidents and imagining other possible outcomes. Using post-structuralist rhizomatics, I assembled analyses of teachers' discussions of the critical incidents in the form of dramatization--scenes and monologues. I then developed two major interpretive strands. First, I connected teachers' sense of having "no time" to blocs of affect tied to larger discourses of national security, teacher accountability, and the joy of scientific discovery. Second, I demonstrated how teachers' concern in following logical pathways and sequences in science relates to the imposition of accountability measures that echo the outcomes-driven logic of the learning sciences. Across both interpretations, I found accountability to be complex, multidirectional, and unpredictable in how it works on and through teachers as they make decisions. Research in this area has important practical implications in the fields of professional development, curriculum development, and school change. As more states (including New York) adopt standards derived from the Next Generation Science Standards (NGSS), the importance of privileging teachers' investment and critical decision-making in the process of new curriculum development is vital. I suggest that tools like video-based coaching and consultancy protocol discussions support this kind of thoughtful curricular change.

Clinical Note Creation, Binning, and Artificial Intelligence.

PubMed

Deliberato, Rodrigo Octávio; Celi, Leo Anthony; Stone, David J

2017-08-03

The creation of medical notes in software applications poses an intrinsic problem in workflow as the technology inherently intervenes in the processes of collecting and assembling information, as well as the production of a data-driven note that meets both individual and healthcare system requirements. In addition, the note writing applications in currently available electronic health records (EHRs) do not function to support decision making to any substantial degree. We suggest that artificial intelligence (AI) could be utilized to facilitate the workflows of the data collection and assembly processes, as well as to support the development of personalized, yet data-driven assessments and plans. ©Rodrigo Octávio Deliberato, Leo Anthony Celi, David J Stone. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 03.08.2017.

Approaches and incentives to implement integrated pest management that addresses regional and environmental issues.

PubMed

Brewer, Michael J; Goodell, Peter B

2012-01-01

Agricultural, environmental, and social and policy interests have influenced integrated pest management (IPM) from its inception. The first 50 years of IPM paid special attention to field-based management and market-driven decision making. Concurrently, IPM strategies became available that were best applied both within and beyond the bounds of individual fields and that also provided environmental benefits. This generated an incentives dilemma for farmers: selecting IPM activities for individual fields on the basis of market-based economics versus selecting IPM activities best applied regionally that have longer-term benefits, including environmental benefits, that accrue to the broader community as well as the farmer. Over the past several decades, public-supported incentives, such as financial incentives available to farmers from conservation programs for farms, have begun to be employed to encourage use of conservation techniques, including strategies with IPM relevance. Combining private investments with public support may effectively address the incentives dilemma when advanced IPM strategies are used regionally and provide public goods such as those benefiting resource conservation. This review focuses on adaptation of IPM to these broader issues, on transitions of IPM from primarily individual field-based decision making to coordinated community decision making, and on the form of partnerships needed to gain long-lasting regional and environmental benefits. Copyright © 2012 by Annual Reviews. All rights reserved.

Optimizing Clinical Drug Product Performance: Applying Biopharmaceutics Risk Assessment Roadmap (BioRAM) and the BioRAM Scoring Grid.

PubMed

Dickinson, Paul A; Kesisoglou, Filippos; Flanagan, Talia; Martinez, Marilyn N; Mistry, Hitesh B; Crison, John R; Polli, James E; Cruañes, Maria T; Serajuddin, Abu T M; Müllertz, Anette; Cook, Jack A; Selen, Arzu

2016-11-01

The aim of Biopharmaceutics Risk Assessment Roadmap (BioRAM) and the BioRAM Scoring Grid is to facilitate optimization of clinical performance of drug products. BioRAM strategy relies on therapy-driven drug delivery and follows an integrated systems approach for formulating and addressing critical questions and decision-making (J Pharm Sci. 2014,103(11): 3777-97). In BioRAM, risk is defined as not achieving the intended in vivo drug product performance, and success is assessed by time to decision-making and action. Emphasis on time to decision-making and time to action highlights the value of well-formulated critical questions and well-designed and conducted integrated studies. This commentary describes and illustrates application of the BioRAM Scoring Grid, a companion to the BioRAM strategy, which guides implementation of such an integrated strategy encompassing 12 critical areas and 6 assessment stages. Application of the BioRAM Scoring Grid is illustrated using published literature. Organizational considerations for implementing BioRAM strategy, including the interactions, function, and skillsets of the BioRAM group members, are also reviewed. As a creative and innovative systems approach, we believe that BioRAM is going to have a broad-reaching impact, influencing drug development and leading to unique collaborations influencing how we learn, and leverage and share knowledge. Published by Elsevier Inc.

Enabling Data-Driven Methodologies Across the Data Lifecycle and Ecosystem

NASA Astrophysics Data System (ADS)

Doyle, R. J.; Crichton, D.

2017-12-01

NASA has unlocked unprecedented scientific knowledge through exploration of the Earth, our solar system, and the larger universe. NASA is generating enormous amounts of data that are challenging traditional approaches to capturing, managing, analyzing and ultimately gaining scientific understanding from science data. New architectures, capabilities and methodologies are needed to span the entire observing system, from spacecraft to archive, while integrating data-driven discovery and analytic capabilities. NASA data have a definable lifecycle, from remote collection point to validated accessibility in multiple archives. Data challenges must be addressed across this lifecycle, to capture opportunities and avoid decisions that may limit or compromise what is achievable once data arrives at the archive. Data triage may be necessary when the collection capacity of the sensor or instrument overwhelms data transport or storage capacity. By migrating computational and analytic capability to the point of data collection, informed decisions can be made about which data to keep; in some cases, to close observational decision loops onboard, to enable attending to unexpected or transient phenomena. Along a different dimension than the data lifecycle, scientists and other end-users must work across an increasingly complex data ecosystem, where the range of relevant data is rarely owned by a single institution. To operate effectively, scalable data architectures and community-owned information models become essential. NASA's Planetary Data System is having success with this approach. Finally, there is the difficult challenge of reproducibility and trust. While data provenance techniques will be part of the solution, future interactive analytics environments must support an ability to provide a basis for a result: relevant data source and algorithms, uncertainty tracking, etc., to assure scientific integrity and to enable confident decision making. Advances in data science offer opportunities to gain new insights from space missions and their vast data collections. We are working to innovate new architectures, exploit emerging technologies, develop new data-driven methodologies, and transfer them across disciplines, while working across the dual dimensions of the data lifecycle and the data ecosystem.

No Evidence That Gratitude Enhances Neural Performance Monitoring or Conflict-Driven Control

PubMed Central

Saunders, Blair; He, Frank F. H.; Inzlicht, Michael

2015-01-01

It has recently been suggested that gratitude can benefit self-regulation by reducing impulsivity during economic decision making. We tested if comparable benefits of gratitude are observed for neural performance monitoring and conflict-driven self-control. In a pre-post design, 61 participants were randomly assigned to either a gratitude or happiness condition, and then performed a pre-induction flanker task. Subsequently, participants recalled an autobiographical event where they had felt grateful or happy, followed by a post-induction flanker task. Despite closely following existing protocols, participants in the gratitude condition did not report elevated gratefulness compared to the happy group. In regard to self-control, we found no association between gratitude—operationalized by experimental condition or as a continuous predictor—and any control metric, including flanker interference, post-error adjustments, or neural monitoring (the error-related negativity, ERN). Thus, while gratitude might increase economic patience, such benefits may not generalize to conflict-driven control processes. PMID:26633830

No Evidence That Gratitude Enhances Neural Performance Monitoring or Conflict-Driven Control.

PubMed

Saunders, Blair; He, Frank F H; Inzlicht, Michael

2015-01-01

It has recently been suggested that gratitude can benefit self-regulation by reducing impulsivity during economic decision making. We tested if comparable benefits of gratitude are observed for neural performance monitoring and conflict-driven self-control. In a pre-post design, 61 participants were randomly assigned to either a gratitude or happiness condition, and then performed a pre-induction flanker task. Subsequently, participants recalled an autobiographical event where they had felt grateful or happy, followed by a post-induction flanker task. Despite closely following existing protocols, participants in the gratitude condition did not report elevated gratefulness compared to the happy group. In regard to self-control, we found no association between gratitude--operationalized by experimental condition or as a continuous predictor--and any control metric, including flanker interference, post-error adjustments, or neural monitoring (the error-related negativity, ERN). Thus, while gratitude might increase economic patience, such benefits may not generalize to conflict-driven control processes.

Application of stakeholder-based and modelling approaches for supporting robust adaptation decision making under future climatic uncertainty and changing urban-agricultural water demand

NASA Astrophysics Data System (ADS)

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

2016-04-01

Deep uncertainty in future climate change and socio-economic conditions necessitates the use of assess-risk-of-policy approaches over predict-then-act approaches for adaptation decision making. Robust Decision Making (RDM) approaches embody this principle and help evaluate the ability of adaptation options to satisfy stakeholder preferences under wide-ranging future conditions. This study involves the simultaneous application of two RDM approaches; qualitative and quantitative, in the Cauvery River Basin in Karnataka (population ~23 million), India. The study aims to (a) determine robust water resources adaptation options for the 2030s and 2050s and (b) compare the usefulness of a qualitative stakeholder-driven approach with a quantitative modelling approach. For developing a large set of future scenarios a combination of climate narratives and socio-economic narratives was used. Using structured expert elicitation with a group of climate experts in the Indian Summer Monsoon, climatic narratives were developed. Socio-economic narratives were developed to reflect potential future urban and agricultural water demand. In the qualitative RDM approach, a stakeholder workshop helped elicit key vulnerabilities, water resources adaptation options and performance criteria for evaluating options. During a second workshop, stakeholders discussed and evaluated adaptation options against the performance criteria for a large number of scenarios of climatic and socio-economic change in the basin. In the quantitative RDM approach, a Water Evaluation And Planning (WEAP) model was forced by precipitation and evapotranspiration data, coherent with the climatic narratives, together with water demand data based on socio-economic narratives. We find that compared to business-as-usual conditions options addressing urban water demand satisfy performance criteria across scenarios and provide co-benefits like energy savings and reduction in groundwater depletion, while options reducing agricultural water demand significantly affect downstream water availability. Water demand options demonstrate potential to improve environmental flow conditions and satisfy legal water supply requirements for downstream riparian states. On the other hand, currently planned large scale infrastructural projects demonstrate reduced value in certain scenarios, illustrating the impacts of lock-in effects of large scale infrastructure. From a methodological perspective, we find that while the stakeholder-driven approach revealed robust options in a resource-light manner and helped initiate much needed interaction amongst stakeholders, the modelling approach provides complementary quantitative information. The study reveals robust adaptation options for this important basin and provides a strong methodological basis for carrying out future studies that support adaptation decision making.

Ketamine use among regular tobacco and alcohol users as revealed by respondent driven sampling in Taipei: prevalence, expectancy, and users’ risky decision making

PubMed Central

Chen, Wei J.; Ting, Te-Tien; Chang, Chao-Ming; Liu, Ying-Chun; Chen, Chuan-Yu

2014-01-01

The popularity of ketamine for recreational use among young people began to increase, particularly in Asia, in 2000. To gain more knowledge about the use of ketamine among high risk individuals, a respondent-driven sampling (RDS) was implemented among regular alcohol and tobacco users in the Taipei metropolitan area from 2007 to 2010. The sampling was initiated in three different settings (i.e., two in the community and one in a clinic) to recruit seed individuals. Each participant was asked to refer one to five friends known to be regular tobacco smokers and alcohol drinkers to participate in the present study. Incentives were offered differentially upon the completion of an interview and successful referral. Information pertaining to drug use experience was collected by an audio computer-assisted self-interview instrument. Software built for RDS analyses was used for data analyses. Of the 1,115 subjects recruited, about 11.7% of the RDS respondents reported ever having used ketamine. Positive expectancy of ketamine use was positively associated with ketamine use; in contrast, negative expectancy inversely associated with ketamine use. Decision-making characteristics as measured on the Iowa Gambling Task using reinforcement learning models revealed that ketamine users learned less from the most recent event than both tobacco- and drug-naïve controls and regular tobacco and alcohol users. These findings about ketamine use among young people have implications for its prevention and intervention. PMID:25264412

Ontology-Driven Knowledge-Based Health-Care System, An Emerging Area - Challenges And Opportunities - Indian Scenario

NASA Astrophysics Data System (ADS)

Sunitha, A.; Babu, G. Suresh

2014-11-01

Recent studies in the decision making efforts in the area of public healthcare systems have been tremendously inspired and influenced by the entry of ontology. Ontology driven systems results in the effective implementation of healthcare strategies for the policy makers. The central source of knowledge is the ontology containing all the relevant domain concepts such as locations, diseases, environments and their domain sensitive inter-relationships which is the prime objective, concern and the motivation behind this paper. The paper further focuses on the development of a semantic knowledge-base for public healthcare system. This paper describes the approach and methodologies in bringing out a novel conceptual theme in establishing a firm linkage between three different ontologies related to diseases, places and environments in one integrated platform. This platform correlates the real-time mechanisms prevailing within the semantic knowledgebase and establishing their inter-relationships for the first time in India. This is hoped to formulate a strong foundation for establishing a much awaited basic need for a meaningful healthcare decision making system in the country. Introduction through a wide range of best practices facilitate the adoption of this approach for better appreciation, understanding and long term outcomes in the area. The methods and approach illustrated in the paper relate to health mapping methods, reusability of health applications, and interoperability issues based on mapping of the data attributes with ontology concepts in generating semantic integrated data driving an inference engine for user-interfaced semantic queries.

Data Analysis and Data Mining: Current Issues in Biomedical Informatics

PubMed Central

Bellazzi, Riccardo; Diomidous, Marianna; Sarkar, Indra Neil; Takabayashi, Katsuhiko; Ziegler, Andreas; McCray, Alexa T.

2011-01-01

Summary Background Medicine and biomedical sciences have become data-intensive fields, which, at the same time, enable the application of data-driven approaches and require sophisticated data analysis and data mining methods. Biomedical informatics provides a proper interdisciplinary context to integrate data and knowledge when processing available information, with the aim of giving effective decision-making support in clinics and translational research. Objectives To reflect on different perspectives related to the role of data analysis and data mining in biomedical informatics. Methods On the occasion of the 50th year of Methods of Information in Medicine a symposium was organized, that reflected on opportunities, challenges and priorities of organizing, representing and analysing data, information and knowledge in biomedicine and health care. The contributions of experts with a variety of backgrounds in the area of biomedical data analysis have been collected as one outcome of this symposium, in order to provide a broad, though coherent, overview of some of the most interesting aspects of the field. Results The paper presents sections on data accumulation and data-driven approaches in medical informatics, data and knowledge integration, statistical issues for the evaluation of data mining models, translational bioinformatics and bioinformatics aspects of genetic epidemiology. Conclusions Biomedical informatics represents a natural framework to properly and effectively apply data analysis and data mining methods in a decision-making context. In the future, it will be necessary to preserve the inclusive nature of the field and to foster an increasing sharing of data and methods between researchers. PMID:22146916

Conserving analyst attention units: use of multi-agent software and CEP methods to assist information analysis

NASA Astrophysics Data System (ADS)

Rimland, Jeffrey; McNeese, Michael; Hall, David

2013-05-01

Although the capability of computer-based artificial intelligence techniques for decision-making and situational awareness has seen notable improvement over the last several decades, the current state-of-the-art still falls short of creating computer systems capable of autonomously making complex decisions and judgments in many domains where data is nuanced and accountability is high. However, there is a great deal of potential for hybrid systems in which software applications augment human capabilities by focusing the analyst's attention to relevant information elements based on both a priori knowledge of the analyst's goals and the processing/correlation of a series of data streams too numerous and heterogeneous for the analyst to digest without assistance. Researchers at Penn State University are exploring ways in which an information framework influenced by Klein's (Recognition Primed Decision) RPD model, Endsley's model of situational awareness, and the Joint Directors of Laboratories (JDL) data fusion process model can be implemented through a novel combination of Complex Event Processing (CEP) and Multi-Agent Software (MAS). Though originally designed for stock market and financial applications, the high performance data-driven nature of CEP techniques provide a natural compliment to the proven capabilities of MAS systems for modeling naturalistic decision-making, performing process adjudication, and optimizing networked processing and cognition via the use of "mobile agents." This paper addresses the challenges and opportunities of such a framework for augmenting human observational capability as well as enabling the ability to perform collaborative context-aware reasoning in both human teams and hybrid human / software agent teams.

Factors influencing antibiotic-prescribing decisions among inpatient physicians: a qualitative investigation

PubMed Central

Livorsi, D; Comer, AR; Matthias, MS; Perencevich, EN; Bair, MJ

2016-01-01

Objective To understand the professional and psychosocial factors that influence physicians' antibiotic-prescribing habits in the inpatient setting. Design We conducted semi-structured interviews with 30 inpatient physicians. Interviews consisted of open-ended questions and flexible probes based on participants' responses. Interviews were audio recorded, transcribed, de-identified, and reviewed for accuracy and completeness. Data were analyzed using emergent thematic analysis. Setting Two teaching hospitals in Indianapolis, IN Participants Thirty inpatient physicians (10 physicians-in-training, 20 supervising staff) Results Participants recognized that antibiotics are over-used, and many admitted to prescribing antibiotics even when the clinical evidence of infection was uncertain. Over-prescription was largely driven by anxiety about missing an infection while potential adverse effects of antibiotics did not strongly influence decision-making. Participants did not routinely disclose potential adverse effects of antibiotics to inpatients. Physicians-in-training were strongly influenced by the antibiotic prescribing behavior of their supervising staff physicians. Participants sometimes questioned their colleagues' antibiotic-prescribing decisions but frequently avoided providing direct feedback or critique, citing obstacles of hierarchy, infrequent face-to-face encounters, and the awkwardness of these conversations. Conclusion There is a physician-based culture of prescribing antibiotics, which involves over-using antibiotics and not challenging colleagues' decisions. The potential adverse effects of antibiotics do not strongly influence decision-making in this sample. A better understanding of these factors could be leveraged in future efforts to improve antibiotic-prescribing in the inpatient setting. PMID:26078017

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

Family planning decisions, perceptions and gender dynamics among couples in Mwanza, Tanzania: a qualitative study

PubMed Central

2013-01-01

Background Contraceptive use is low in developing countries which are still largely driven by male dominated culture and patriarchal values. This study explored family planning (FP) decisions, perceptions and gender dynamics among couples in Mwanza region of Tanzania. Methods Twelve focus group discussions and six in-depth interviews were used to collect information from married or cohabiting males and females aged 18–49. The participants were purposively selected. Qualitative methods were used to explore family planning decisions, perceptions and gender dynamics among couples. A guide with questions related to family planning perceptions, decisions and gender dynamics was used. The discussions and interviews were tape-recorded, transcribed verbatim and analyzed manually and subjected to content analysis. Results Four themes emerged during the study. First, “risks and costs” which refer to the side effects of FP methods and the treatment of side -effects as well as the costs inherit in being labeled as an unfaithful spouse. Second, “male involvement” as men showed little interest in participating in family planning issues. However, the same men were mentioned as key decision-makers even on the number of children a couple should have and the child spacing of these children. Third, “gender relations and communication” as participants indicated that few women participated in decision-making on family planning and the number of children to have. Fourth, “urban–rural differences”, life in rural favoring having more children than urban areas therefore, the value of children depended on the place of residence. Conclusion Family Planning programs should adapt the promotion of communication as well as joint decision-making on FP among couples as a strategy aimed at enhancing FP use. PMID:23721196

Experiences in Engaging the Public on Biotechnology Advances and Regulation

PubMed Central

Quinlan, M. Megan; Smith, Joe; Layton, Raymond; Keese, Paul; Agbagala, Ma. Lorelie U.; Palacpac, Merle B.; Ball, Louise

2016-01-01

Public input is often sought as part of the biosafety decision-making process. Information and communication about the advances in biotechnology are part of the first step to engagement. This step often relies on the developers and introducers of the particular innovation, for example, an industry-funded website has hosted various authorities to respond to questions from the public. Alternative approaches to providing information have evolved, as demonstrated in sub-Saharan Africa where non-governmental organizations and associations play this role in some countries and subregions. Often times, those in the public who choose to participate in engagement opportunities have opinions about the overall biosafety decision process. Case-by-case decisions are made within defined regulatory frameworks, however, and in general, regulatory consultation does not provide the opportunity for input to the overall decision-making process. The various objectives on both sides of engagement can make the experience challenging; there are no clear metrics for success. The situation is challenging because public input occurs within the context of the local legislative framework, regulatory requirements, and the peculiarities of the fairly recent biosafety frameworks, as well as of public opinion and individual values. Public engagement may be conducted voluntarily, or may be driven by legislation. What can be taken into account by the decision makers, and therefore what will be gathered and the timing of consultation, also may be legally defined. Several practical experiences suggest practices for effective engagement within the confines of regulatory mandates: (1) utilizing a range of resources to facilitate public education and opportunities for understanding complex technologies; (2) defining in advance the goal of seeking input; (3) identifying and communicating with the critical public groups from which input is needed; (4) using a clearly defined approach to gathering and assessing what will be used in making the biosafety decision; and (5) communicating using clear and simple language. These practices create a foundation for systematic methods to gather, acknowledge, respond to, and even incorporate public input. Applying such best practices will increase transparency and optimize the value of input from the public. PMID:26870726

Experiences in Engaging the Public on Biotechnology Advances and Regulation.

PubMed

Quinlan, M Megan; Smith, Joe; Layton, Raymond; Keese, Paul; Agbagala, Ma Lorelie U; Palacpac, Merle B; Ball, Louise

2016-01-01

Public input is often sought as part of the biosafety decision-making process. Information and communication about the advances in biotechnology are part of the first step to engagement. This step often relies on the developers and introducers of the particular innovation, for example, an industry-funded website has hosted various authorities to respond to questions from the public. Alternative approaches to providing information have evolved, as demonstrated in sub-Saharan Africa where non-governmental organizations and associations play this role in some countries and subregions. Often times, those in the public who choose to participate in engagement opportunities have opinions about the overall biosafety decision process. Case-by-case decisions are made within defined regulatory frameworks, however, and in general, regulatory consultation does not provide the opportunity for input to the overall decision-making process. The various objectives on both sides of engagement can make the experience challenging; there are no clear metrics for success. The situation is challenging because public input occurs within the context of the local legislative framework, regulatory requirements, and the peculiarities of the fairly recent biosafety frameworks, as well as of public opinion and individual values. Public engagement may be conducted voluntarily, or may be driven by legislation. What can be taken into account by the decision makers, and therefore what will be gathered and the timing of consultation, also may be legally defined. Several practical experiences suggest practices for effective engagement within the confines of regulatory mandates: (1) utilizing a range of resources to facilitate public education and opportunities for understanding complex technologies; (2) defining in advance the goal of seeking input; (3) identifying and communicating with the critical public groups from which input is needed; (4) using a clearly defined approach to gathering and assessing what will be used in making the biosafety decision; and (5) communicating using clear and simple language. These practices create a foundation for systematic methods to gather, acknowledge, respond to, and even incorporate public input. Applying such best practices will increase transparency and optimize the value of input from the public.

Evolution of Public Participation in the Assessment and Management of Environmental Health Risks: A Brief History of Developments in the United States

PubMed Central

Sexton, Ken

2013-01-01

Significance for public health Risk-based decision making is a core feature of government actions aimed at protecting public health from the adverse effects of environmental hazards. In the past, it has often been an expert-driven, mostly obscure process used by federal agencies to justify and defend regulatory decisions made outside the public arena. But the nature of decision making has changed as it has become apparent that environmental health problems are more complicated, controversial, and costly to solve than originally thought. Meaningful public engagement is now an inherent component of all phases of the risk assessment – risk management paradigm because it promotes stakeholder buy in, taps into unique stakeholder knowledge, and promotes the concept of environmental democracy. In the United States, the risk assessment – risk management paradigm that underpins federal decisions about environmental health risks was first established in 1983. In the beginning, the importance of public participation was not explicitly recognized within the paradigm. Over time, however, it has become evident that not only must risk-based decisions be founded on the best available scientific knowledge and understanding, but also that they must take account of the knowledge, values, and preferences of interested and affected parties, including community members, business people, and environmental advocates. This article examines the gradually expanding role of public participation in risk-based decision making in the United States, and traces its evolution from a peripheral issue labeled as an external pressure to an integral element of the 21st century risk assessment – risk management paradigm. Today, and into the foreseeable future, public participation and stakeholder involvement are intrinsic features of the emerging American regulatory landscape, which emphasizes collaborative approaches for achieving cooperative and cost-effective solutions to complicated and often controversial environmental health problems. PMID:25170489

Evolution of public participation in the assessment and management of environmental health risks: a brief history of developments in the United States.

PubMed

Sexton, Ken

2013-09-02

Significance for public healthRisk-based decision making is a core feature of government actions aimed at protecting public health from the adverse effects of environmental hazards. In the past, it has often been an expert-driven, mostly obscure process used by federal agencies to justify and defend regulatory decisions made outside the public arena. But the nature of decision making has changed as it has become apparent that environmental health problems are more complicated, controversial, and costly to solve than originally thought. Meaningful public engagement is now an inherent component of all phases of the risk assessment - risk management paradigm because it promotes stakeholder buy in, taps into unique stakeholder knowledge, and promotes the concept of environmental democracy.In the United States, the risk assessment - risk management paradigm that underpins federal decisions about environmental health risks was first established in 1983. In the beginning, the importance of public participation was not explicitly recognized within the paradigm. Over time, however, it has become evident that not only must risk-based decisions be founded on the best available scientific knowledge and understanding, but also that they must take account of the knowledge, values, and preferences of interested and affected parties, including community members, business people, and environmental advocates. This article examines the gradually expanding role of public participation in risk-based decision making in the United States, and traces its evolution from a peripheral issue labeled as an external pressure to an integral element of the 21st century risk assessment - risk management paradigm. Today, and into the foreseeable future, public participation and stakeholder involvement are intrinsic features of the emerging American regulatory landscape, which emphasizes collaborative approaches for achieving cooperative and cost-effective solutions to complicated and often controversial environmental health problems.

A vulnerability driven approach to identify adverse climate and land use change combinations for critical hydrologic indicator thresholds: Application to a watershed in Pennsylvania, USA

NASA Astrophysics Data System (ADS)

Singh, R.; Wagener, T.; Crane, R.; Mann, M. E.; Ning, L.

2014-04-01

Large uncertainties in streamflow projections derived from downscaled climate projections of precipitation and temperature can render such simulations of limited value for decision making in the context of water resources management. New approaches are being sought to provide decision makers with robust information in the face of such large uncertainties. We present an alternative approach that starts with the stakeholder's definition of vulnerable ranges for relevant hydrologic indicators. Then the modeled system is analyzed to assess under what conditions these thresholds are exceeded. The space of possible climates and land use combinations for a watershed is explored to isolate subspaces that lead to vulnerability, while considering model parameter uncertainty in the analysis. We implement this concept using classification and regression trees (CART) that separate the input space of climate and land use change into those combinations that lead to vulnerability and those that do not. We test our method in a Pennsylvania watershed for nine ecological and water resources related streamflow indicators for which an increase in temperature between 3°C and 6°C and change in precipitation between -17% and 19% is projected. Our approach provides several new insights, for example, we show that even small decreases in precipitation (˜5%) combined with temperature increases greater than 2.5°C can push the mean annual runoff into a slightly vulnerable regime. Using this impact and stakeholder driven strategy, we explore the decision-relevant space more fully and provide information to the decision maker even if climate change projections are ambiguous.

Development of a personalized decision aid for breast cancer risk reduction and management.

PubMed

Ozanne, Elissa M; Howe, Rebecca; Omer, Zehra; Esserman, Laura J

2014-01-14

Breast cancer risk reduction has the potential to decrease the incidence of the disease, yet remains underused. We report on the development a web-based tool that provides automated risk assessment and personalized decision support designed for collaborative use between patients and clinicians. Under Institutional Review Board approval, we evaluated the decision tool through a patient focus group, usability testing, and provider interviews (including breast specialists, primary care physicians, genetic counselors). This included demonstrations and data collection at two scientific conferences (2009 International Shared Decision Making Conference, 2009 San Antonio Breast Cancer Symposium). Overall, the evaluations were favorable. The patient focus group evaluations and usability testing (N = 34) provided qualitative feedback about format and design; 88% of these participants found the tool useful and 94% found it easy to use. 91% of the providers (N = 23) indicated that they would use the tool in their clinical setting. BreastHealthDecisions.org represents a new approach to breast cancer prevention care and a framework for high quality preventive healthcare. The ability to integrate risk assessment and decision support in real time will allow for informed, value-driven, and patient-centered breast cancer prevention decisions. The tool is being further evaluated in the clinical setting.

Rethinking medical humanities.

PubMed

Chiapperino, Luca; Boniolo, Giovanni

2014-12-01

This paper questions different conceptions of Medical Humanities in order to provide a clearer understanding of what they are and why they matter. Building upon former attempts, we defend a conception of Medical Humanities as a humanistic problem-based approach to medicine aiming at influencing its nature and practice. In particular, we discuss three main conceptual issues regarding the overall nature of this discipline: (i) a problem-driven approach to Medical Humanities; (ii) the need for an integration of Medical Humanities into medicine; (iii) the methodological requirements that could render Medical Humanities an effective framework for medical decision-making.

Consumer-driven health plans: latest challenge to practices' cash flow.

PubMed

Hajny, Tom

2007-01-01

CDHPs are here to stay. Employers welcome CDHPs because they drive costs away from themselves and into the hands of both consumers and provides. The consumer will make medical purchase decisions tempered by personal economic considerations. The providers are left to figure it all out with the hope their cash flow, cost budgets, and customer service will not be negatively impacted. It will not be easy. Practices must become educated on how CDHPs work, become knowledgeable about specific HSA scenarios in their market, develop optimum processes and procedures, and train staff.

Information infrastructure for emergency medical services.

PubMed

Orthner, Helmuth; Mishra, Ninad; Terndrup, Thomas; Acker, Joseph; Grimes, Gary; Gemmill, Jill; Battles, Marcie

2005-01-01

The pre-hospital emergency medical and public safety information environment is nearing a threshold of significant change. The change is driven in part by several emerging technologies such as secure, high-speed wireless communication in the local and wide area networks (wLAN, 3G), Geographic Information Systems (GIS), Global Positioning Systems (GPS), and powerful handheld computing and communication services, that are of sufficient utility to be more widely adopted. We propose a conceptual model to enable improved clinical decision making in the pre-hospital environment using these change agents.

Genetically-Driven Enhancement of Dopaminergic Transmission Affects Moral Acceptability in Females but Not in Males: A Pilot Study

PubMed Central

Pellegrini, Silvia; Palumbo, Sara; Iofrida, Caterina; Melissari, Erika; Rota, Giuseppina; Mariotti, Veronica; Anastasio, Teresa; Manfrinati, Andrea; Rumiati, Rino; Lotto, Lorella; Sarlo, Michela; Pietrini, Pietro

2017-01-01

Moral behavior has been a key topic of debate for philosophy and psychology for a long time. In recent years, thanks to the development of novel methodologies in cognitive sciences, the question of how we make moral choices has expanded to the study of neurobiological correlates that subtend the mental processes involved in moral behavior. For instance, in vivo brain imaging studies have shown that distinct patterns of brain neural activity, associated with emotional response and cognitive processes, are involved in moral judgment. Moreover, while it is well-known that responses to the same moral dilemmas differ across individuals, to what extent this variability may be rooted in genetics still remains to be understood. As dopamine is a key modulator of neural processes underlying executive functions, we questioned whether genetic polymorphisms associated with decision-making and dopaminergic neurotransmission modulation would contribute to the observed variability in moral judgment. To this aim, we genotyped five genetic variants of the dopaminergic pathway [rs1800955 in the dopamine receptor D4 (DRD4) gene, DRD4 48 bp variable number of tandem repeat (VNTR), solute carrier family 6 member 3 (SLC6A3) 40 bp VNTR, rs4680 in the catechol-O-methyl transferase (COMT) gene, and rs1800497 in the ankyrin repeat and kinase domain containing 1 (ANKK1) gene] in 200 subjects, who were requested to answer 56 moral dilemmas. As these variants are all located in genes belonging to the dopaminergic pathway, they were combined in multilocus genetic profiles for the association analysis. While no individual variant showed any significant effects on moral dilemma responses, the multilocus genetic profile analysis revealed a significant gender-specific influence on human moral acceptability. Specifically, those genotype combinations that improve dopaminergic signaling selectively increased moral acceptability in females, by making their responses to moral dilemmas more similar to those provided by males. As females usually give more emotionally-based answers and engage the “emotional brain” more than males, our results, though preliminary and therefore in need of replication in independent samples, suggest that this increase in dopamine availability enhances the cognitive and reduces the emotional components of moral decision-making in females, thus favoring a more rationally-driven decision process. PMID:28900390

Economic inequality increases risk taking.

PubMed

Payne, B Keith; Brown-Iannuzzi, Jazmin L; Hannay, Jason W

2017-05-02

Rising income inequality is a global trend. Increased income inequality has been associated with higher rates of crime, greater consumer debt, and poorer health outcomes. The mechanisms linking inequality to poor outcomes among individuals are poorly understood. This research tested a behavioral account linking inequality to individual decision making. In three experiments ( n = 811), we found that higher inequality in the outcomes of an economic game led participants to take greater risks to try to achieve higher outcomes. This effect of unequal distributions on risk taking was driven by upward social comparisons. Next, we estimated economic risk taking in daily life using large-scale data from internet searches. Risk taking was higher in states with greater income inequality, an effect driven by inequality at the upper end of the income distribution. Results suggest that inequality may promote poor outcomes, in part, by increasing risky behavior.

Sizing Power Components of an Electrically Driven Tail Cone Thruster and a Range Extender

NASA Technical Reports Server (NTRS)

Jansen, Ralph H.; Bowman, Cheryl; Jankovsky, Amy

2016-01-01

The aeronautics industry has been challenged on many fronts to increase efficiency, reduce emissions, and decrease dependency on carbon-based fuels. This paper provides an overview of the turboelectric and hybrid electric technologies being developed under NASA's Advanced Air Transportation Technology (AATT) Project and discusses how these technologies can impact vehicle design. The discussion includes an overview of key hybrid electric studies and technology investments, the approach to making informed investment decisions based on key performance parameters and mission studies, and the power system architectures for two candidate aircraft. Finally, the power components for a single-aisle turboelectric aircraft with an electrically driven tail cone thruster and for a hybrid-electric nine-passenger aircraft with a range extender are parametrically sized, and the sensitivity of these components to key parameters is presented.

Reinforcement Learning Multi-Agent Modeling of Decision-Making Agents for the Study of Transboundary Surface Water Conflicts with Application to the Syr Darya River Basin

NASA Astrophysics Data System (ADS)

Riegels, N.; Siegfried, T.; Pereira Cardenal, S. J.; Jensen, R. A.; Bauer-Gottwein, P.

2008-12-01

In most economics--driven approaches to optimizing water use at the river basin scale, the system is modelled deterministically with the goal of maximizing overall benefits. However, actual operation and allocation decisions must be made under hydrologic and economic uncertainty. In addition, river basins often cross political boundaries, and different states may not be motivated to cooperate so as to maximize basin- scale benefits. Even within states, competing agents such as irrigation districts, municipal water agencies, and large industrial users may not have incentives to cooperate to realize efficiency gains identified in basin- level studies. More traditional simulation--optimization approaches assume pre-commitment by individual agents and stakeholders and unconditional compliance on each side. While this can help determine attainable gains and tradeoffs from efficient management, such hardwired policies do not account for dynamic feedback between agents themselves or between agents and their environments (e.g. due to climate change etc.). In reality however, we are dealing with an out-of-equilibrium multi-agent system, where there is neither global knowledge nor global control, but rather continuous strategic interaction between decision making agents. Based on the theory of stochastic games, we present a computational framework that allows for studying the dynamic feedback between decision--making agents themselves and an inherently uncertain environment in a spatially and temporally distributed manner. Agents with decision-making control over water allocation such as countries, irrigation districts, and municipalities are represented by reinforcement learning agents and coupled to a detailed hydrologic--economic model. This approach emphasizes learning by agents from their continuous interaction with other agents and the environment. It provides a convenient framework for the solution of the problem of dynamic decision-making in a mixed cooperative / non-cooperative environment with which different institutional setups and incentive systems can be studied so to identify reasonable ways to reach desirable, Pareto--optimal allocation outcomes. Preliminary results from an application to the Syr Darya river basin in Central Asia will be presented and discussed. The Syr Darya River is a classic example of a transboundary river basin in which basin-wide efficiency gains identified in optimization studies have not been sufficient to induce cooperative management of the river by the riparian states.

How mechanisms of perceptual decision-making affect the psychometric function

PubMed Central

Gold, Joshua I.; Ding, Long

2012-01-01

Psychometric functions are often interpreted in the context of Signal Detection Theory, which emphasizes a distinction between sensory processing and non-sensory decision rules in the brain. This framework has helped to relate perceptual sensitivity to the “neurometric” sensitivity of sensory-driven neural activity. However, perceptual sensitivity, as interpreted via Signal Detection Theory, is based on not just how the brain represents relevant sensory information, but also how that information is read out to form the decision variable to which the decision rule is applied. Here we discuss recent advances in our understanding of this readout process and describe its effects on the psychometric function. In particular, we show that particular aspects of the readout process can have specific, identifiable effects on the threshold, slope, upper asymptote, time dependence, and choice dependence of psychometric functions. To illustrate these points, we emphasize studies of perceptual learning that have identified changes in the readout process that can lead to changes in these aspects of the psychometric function. We also discuss methods that have been used to distinguish contributions of the sensory representation versus its readout to psychophysical performance. PMID:22609483

Data-driven decision support for radiologists: re-using the National Lung Screening Trial dataset for pulmonary nodule management.

PubMed

Morrison, James J; Hostetter, Jason; Wang, Kenneth; Siegel, Eliot L

2015-02-01

Real-time mining of large research trial datasets enables development of case-based clinical decision support tools. Several applicable research datasets exist including the National Lung Screening Trial (NLST), a dataset unparalleled in size and scope for studying population-based lung cancer screening. Using these data, a clinical decision support tool was developed which matches patient demographics and lung nodule characteristics to a cohort of similar patients. The NLST dataset was converted into Structured Query Language (SQL) tables hosted on a web server, and a web-based JavaScript application was developed which performs real-time queries. JavaScript is used for both the server-side and client-side language, allowing for rapid development of a robust client interface and server-side data layer. Real-time data mining of user-specified patient cohorts achieved a rapid return of cohort cancer statistics and lung nodule distribution information. This system demonstrates the potential of individualized real-time data mining using large high-quality clinical trial datasets to drive evidence-based clinical decision-making.

Proving Value in Radiology: Experience Developing and Implementing a Shareable Open Source Registry Platform Driven by Radiology Workflow.

PubMed

Gichoya, Judy Wawira; Kohli, Marc D; Haste, Paul; Abigail, Elizabeth Mills; Johnson, Matthew S

2017-10-01

Numerous initiatives are in place to support value based care in radiology including decision support using appropriateness criteria, quality metrics like radiation dose monitoring, and efforts to improve the quality of the radiology report for consumption by referring providers. These initiatives are largely data driven. Organizations can choose to purchase proprietary registry systems, pay for software as a service solution, or deploy/build their own registry systems. Traditionally, registries are created for a single purpose like radiation dosage or specific disease tracking like diabetes registry. This results in a fragmented view of the patient, and increases overhead to maintain such single purpose registry system by requiring an alternative data entry workflow and additional infrastructure to host and maintain multiple registries for different clinical needs. This complexity is magnified in the health care enterprise whereby radiology systems usually are run parallel to other clinical systems due to the different clinical workflow for radiologists. In the new era of value based care where data needs are increasing with demand for a shorter turnaround time to provide data that can be used for information and decision making, there is a critical gap to develop registries that are more adapt to the radiology workflow with minimal overhead on resources for maintenance and setup. We share our experience of developing and implementing an open source registry system for quality improvement and research in our academic institution that is driven by our radiology workflow.

Managing industrial risk--having a tested and proven system to prevent and assess risk.

PubMed

Heller, Stephen

2006-03-17

Some relatively easy techniques exist to improve the risk picture/profile to aid in preventing losses. Today with the advent of computer system resources, focusing on specific aspects of risk through systematic scoring and comparison, the risk analysis can be relatively easy to achieve. Techniques like these demonstrate how working experience and common sense can be combined mathematically into a flexible risk management tool or risk model for analyzing risk. The risk assessment methodology provided by companies today is no longer the ideas and practices of one group or even one company. It is reflective of the practice of many companies, as well as the ideas and expertise of academia and government regulators. The use of multi-criteria decision making (MCDM) techniques for making critical decisions has been recognized for many years for a variety of purposes. In today's computer age, the easy accessing and user-friendly nature for using these techniques, makes them a favorable choice for use in the risk assessment environment. The new user of these methodologies should find many ideas directly applicable to his or her needs when approaching risk decision making. The user should find their ideas readily adapted, with slight modification, to accurately reflect a specific situation using MCDM techniques. This makes them an attractive feature for use in assessment and risk modeling. The main advantage of decision making techniques, such as MCDM, is that in the early stages of a risk assessment, accurate data on industrial risk, and failures are lacking. In most cases, it is still insufficient to perform a thorough risk assessment using purely statistical concepts. The practical advantages towards deviating from strict data-driven protocol seem to outweigh the drawbacks. Industry failure data often comes at a high cost when a loss occurs. We can benefit from this unfortunate acquisition of data through the continuous refining of our decisions by incorporating this new information into our assessments. MCDM techniques offer flexibility in accessing comparison within broad data sets to reflect our best estimation of their importance towards contribution to the risk picture. This allows for the accurate determination of the more probable and more consequential issues. This can later be refined using more intensive risk techniques and the avoidance of less critical issues.

Impact of Health Information Exchange on Emergency Medicine Clinical Decision Making.

PubMed

Gordon, Bradley D; Bernard, Kyle; Salzman, Josh; Whitebird, Robin R

2015-12-01

The objective of the study was to understand the immediate utility of health information exchange (HIE) on emergency department (ED) providers by interviewing them shortly after the information was retrieved. Prior studies of physician perceptions regarding HIE have only been performed outside of the care environment. Trained research assistants interviewed resident physicians, physician assistants and attending physicians using a semi-structured questionnaire within two hours of making a HIE request. The responses were recorded, then transcribed for qualitative analysis. The transcribed interviews were analyzed for emerging qualitative themes. We analyzed 40 interviews obtained from 29 providers. Primary qualitative themes discovered included the following: drivers for requests for outside information; the importance of unexpected information; historical lab values as reference points; providing context when determining whether to admit or discharge a patient; the importance of information in refining disposition; improved confidence of provider; and changes in decisions for diagnostic imaging. ED providers are driven to use HIE when they're missing a known piece of information. This study finds two additional impacts not previously reported. First, providers sometimes find additional unanticipated useful information, supporting a workflow that lowers the threshold to request external information. Second, providers sometimes report utility when no changes to their existing plan are made as their confidence is increased based on external records. Our findings are concordant with previous studies in finding exchanged information is useful to provide context for interpreting lab results, making admission decisions, and prevents repeat diagnostic imaging.

Ten Principles to Guide Health Reform.

PubMed

Gerald, Joe K

2017-03-01

Americans face inevitable trade-offs between health care affordability, accessibility, and innovation. Although numerous reforms have been proposed, universal principles to guide decision-making are lacking. Solving the challenges that confront us will be difficult, owing to intense partisan divisions and a dysfunctional political process. Nevertheless, we must engage in reasoned debate that respects deeply held differences of opinion regarding our individual and collective obligations to promote healthy living and ensure affordable access to health care. Otherwise, our decisions will be expressed through political processes that reflect the preferences of narrow interests rather than the general public. Our health care system can be made more efficient and equitable by incentivizing consumers and providers to utilize high-value care and avoid low-value care. To accomplish this, we must understand the determinants of consumer and provider behavior and implement policies that encourage, but do not force, optimal decision-making. Although distinguishing between low- and high-value treatments will invariably threaten established interests, we must expand our capacity to make such judgements. Throughout this process, consumers, taxpayers, and policy makers must maintain realistic expectations. Although realigning incentives to promote high-value care will improve efficiency, it is unlikely to control increasing medical expenditures because they are not primarily caused by inefficiency. Rather, rising medical expenditures are driven by medical innovation made possible by increasing incomes and expanding health insurance coverage. Failure to recognize these linkages risks adopting indiscriminate policies that will reduce spending but slow innovation and impair access to needed care.

Risk seeking for losses modulates the functional connectivity of the default mode and left frontoparietal networks in young males.

PubMed

Deza Araujo, Yacila I; Nebe, Stephan; Neukam, Philipp T; Pooseh, Shakoor; Sebold, Miriam; Garbusow, Maria; Heinz, Andreas; Smolka, Michael N

2018-06-01

Value-based decision making (VBDM) is a principle that states that humans and other species adapt their behavior according to the dynamic subjective values of the chosen or unchosen options. The neural bases of this process have been extensively investigated using task-based fMRI and lesion studies. However, the growing field of resting-state functional connectivity (RSFC) may shed light on the organization and function of brain connections across different decision-making domains. With this aim, we used independent component analysis to study the brain network dynamics in a large cohort of young males (N = 145) and the relationship of these dynamics with VBDM. Participants completed a battery of behavioral tests that evaluated delay aversion, risk seeking for losses, risk aversion for gains, and loss aversion, followed by an RSFC scan session. We identified a set of large-scale brain networks and conducted our analysis only on the default mode network (DMN) and networks comprising cognitive control, appetitive-driven, and reward-processing regions. Higher risk seeking for losses was associated with increased connectivity between medial temporal regions, frontal regions, and the DMN. Higher risk seeking for losses was also associated with increased coupling between the left frontoparietal network and occipital cortices. These associations illustrate the participation of brain regions involved in prospective thinking, affective decision making, and visual processing in participants who are greater risk-seekers, and they demonstrate the sensitivity of RSFC to detect brain connectivity differences associated with distinct VBDM parameters.

Completing the Link between Exposure Science and Toxicology for Improved Environmental Health Decision Making: The Aggregate Exposure Pathway Framework

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

Teeguarden, Justin G.; Tan, Yu-Mei; Edwards, Stephen W.

Driven by major scientific advances in analytical methods, biomonitoring, and computational exposure assessment, and a newly articulated vision for a greater impact in public health, the field of exposure science is undergoing a rapid transition from a field of observation to a field of prediction. Deployment of an organizational and predictive framework for exposure science analogous to the computationally enabled “systems approaches” used in the biological sciences is a necessary step in this evolution. Here we propose the aggregate exposure pathway (AEP) concept as the natural and complementary companion in the exposure sciences to the adverse outcome pathway (AOP) conceptmore » in the toxicological sciences. The AEP framework offers an intuitive approach to successful organization of exposure science data within individual units of prediction common to the field, setting the stage for exposure forecasting. Looking farther ahead, we envision direct linkages between aggregate exposure pathway and adverse outcome pathways, completing the source to outcome continuum and setting the stage for more efficient integration of exposure science and toxicity testing information. Together these frameworks form and inform a decision making framework with the flexibility for risk-based, hazard-based or exposure-based decisions.« less

Improving the cost-effectiveness of IRS with climate informed health surveillance systems

PubMed Central

Worrall, Eve; Connor, Stephen J; Thomson, Madeleine C

2008-01-01

Background This paper examines how the cost-effectiveness of IRS varies depending on the severity of transmission and level of programme coverage and how efficiency could be improved by incorporating climate information into decision making for malaria control programmes as part of an integrated Malaria Early Warning and Response System (MEWS). Methods A climate driven model of malaria transmission was used to simulate cost-effectiveness of alternative IRS coverage levels over six epidemic and non-epidemic years. Decision rules for a potential MEWS system that triggers different IRS coverage are described. The average and marginal cost per case averted with baseline IRS coverage (24%) and under varying IRS coverage levels (50%, 75% and 100%) were calculated. Results Average cost-effectiveness of 24% coverage varies dramatically between years, from US$108 per case prevented in low transmission to US$0.42 in epidemic years. Similarly for higher coverage (24–100%) cost per case prevented is far higher in low than high transmission years ($108–$267 to $0.88–$2.26). Discussion Efficiency and health benefit gains could be achieved by implementing MEWS that provides timely, accurate information. Evidence from southern Africa, (especially Botswana) supports this. Conclusion Advance knowledge of transmission severity can help managers make coverage decisions which optimise resource use and exploit efficiency gains if a fully integrated MEWS is in place alongside a health system with sufficient flexibility to modify control plans in response to information. More countries and programmes should be supported to use the best available evidence and science to integrate climate informed MEWS into decision making within malaria control programmes. PMID:19108723

Visual anticipation biases conscious decision making but not bottom-up visual processing.

PubMed

Mathews, Zenon; Cetnarski, Ryszard; Verschure, Paul F M J

2014-01-01

Prediction plays a key role in control of attention but it is not clear which aspects of prediction are most prominent in conscious experience. An evolving view on the brain is that it can be seen as a prediction machine that optimizes its ability to predict states of the world and the self through the top-down propagation of predictions and the bottom-up presentation of prediction errors. There are competing views though on whether prediction or prediction errors dominate the formation of conscious experience. Yet, the dynamic effects of prediction on perception, decision making and consciousness have been difficult to assess and to model. We propose a novel mathematical framework and a psychophysical paradigm that allows us to assess both the hierarchical structuring of perceptual consciousness, its content and the impact of predictions and/or errors on conscious experience, attention and decision-making. Using a displacement detection task combined with reverse correlation, we reveal signatures of the usage of prediction at three different levels of perceptual processing: bottom-up fast saccades, top-down driven slow saccades and consciousnes decisions. Our results suggest that the brain employs multiple parallel mechanism at different levels of perceptual processing in order to shape effective sensory consciousness within a predicted perceptual scene. We further observe that bottom-up sensory and top-down predictive processes can be dissociated through cognitive load. We propose a probabilistic data association model from dynamical systems theory to model the predictive multi-scale bias in perceptual processing that we observe and its role in the formation of conscious experience. We propose that these results support the hypothesis that consciousness provides a time-delayed description of a task that is used to prospectively optimize real time control structures, rather than being engaged in the real-time control of behavior itself.

Identifying the mechanisms through which behavioral weight-loss treatment improves food decision-making in obesity.

PubMed

Demos, Kathryn E; McCaffery, Jeanne M; Thomas, J Graham; Mailloux, Kimberly A; Hare, Todd A; Wing, Rena R

2017-07-01

Behavioral weight loss (BWL) programs are the recommended treatment for obesity, yet it is unknown whether these programs change one's ability to use self-control in food choices and what specific mechanisms support such change. Using experimental economics methods, we investigated whether changes in dietary behavior in individuals with obesity following BWL are driven by one or more of the following potential mechanisms: changes in the perception of the 1) health or 2) taste of food items, and/or 3) shifting decision weights for health versus taste attributes. Therefore, we compared these mechanisms between obese participants and lifetime normal weight controls (NW) both before and after BWL. Females with obesity (N = 37, mean BMI = 33.2) completed a food choice task involving health ratings, taste ratings, and decision-making pre- and post-standard BWL intervention. NW controls (N = 30, BMI = 22.4) completed the same task. Individuals with obesity exhibited increased self-control (selecting healthier, less tasty food choices) post-treatment. However, their rates of self-control remained significantly lower than NW. We found no differences in initial health perceptions across groups, and no changes with treatment. In contrast, taste ratings and the relative value of taste versus health decreased following treatment. Although, post-treatment participants continued to perceive unhealthy foods as tastier and used less self-control than NW controls, they showed significant improvements in these domains following a BWL intervention. To help individuals improve dietary decisions, additional research is needed to determine how to make greater changes in taste preferences and/or the assignment of value to taste versus health attributes in food choices. Copyright © 2017 Elsevier Ltd. All rights reserved.

Qualitative Interviews Exploring Palliative Care Perspectives of Latinos on Dialysis.

PubMed

Cervantes, Lilia; Jones, Jacqueline; Linas, Stuart; Fischer, Stacy

2017-05-08

Compared with non-Latino whites with advanced illness, Latinos are less likely to have an advance directive or to die with hospice services. To improve palliative care disparities, international ESRD guidelines call for increased research on culturally responsive communication of advance care planning (ACP). The objective of our study was to explore the preferences of Latino patients receiving dialysis regarding symptom management and ACP. Qualitative study design using semistructured face-to-face interviews of 20 Latinos on hemodialysis between February and July of 2015. Data were analyzed using thematic analysis. Four themes were identified: Avoiding harms of medication (fear of addiction and damage to bodies, effective distractions, reliance on traditional remedies, fatalism: the sense that one's illness is deserved punishment); barriers and facilitators to ACP: faith, family, and home (family group decision-making, family reluctance to have ACP conversations, flexible decision-making conversations at home with family, ACP conversations incorporating trust and linguistic congruency, family-first and faith-driven decisions); enhancing wellbeing day-to-day (supportive relationships, improved understanding of illness leads to adherence, recognizing new self-value, maintaining a positive outlook); and distressing aspects of living with their illness (dietary restriction is culturally isolating and challenging for families, logistic challenges and socioeconomic disadvantage compounded by health literacy and language barriers, required rapid adjustments to chronic illness, demanding dialysis schedule). Latinos described unique cultural preferences such as avoidance of medications for symptom alleviation and a preference to have family group decision-making and ACP conversations at home. Understanding and integrating cultural values and preferences into palliative care offers the potential to improve disparities and achieve quality patient-centered care for Latinos with advanced illness. Copyright © 2017 by the American Society of Nephrology.

Qualitative Interviews Exploring Palliative Care Perspectives of Latinos on Dialysis

PubMed Central

Jones, Jacqueline; Linas, Stuart; Fischer, Stacy

2017-01-01

Background and objectives Compared with non-Latino whites with advanced illness, Latinos are less likely to have an advance directive or to die with hospice services. To improve palliative care disparities, international ESRD guidelines call for increased research on culturally responsive communication of advance care planning (ACP). The objective of our study was to explore the preferences of Latino patients receiving dialysis regarding symptom management and ACP. Design, setting, participants, & measurements Qualitative study design using semistructured face-to-face interviews of 20 Latinos on hemodialysis between February and July of 2015. Data were analyzed using thematic analysis. Results Four themes were identified: Avoiding harms of medication (fear of addiction and damage to bodies, effective distractions, reliance on traditional remedies, fatalism: the sense that one’s illness is deserved punishment); barriers and facilitators to ACP: faith, family, and home (family group decision-making, family reluctance to have ACP conversations, flexible decision-making conversations at home with family, ACP conversations incorporating trust and linguistic congruency, family-first and faith-driven decisions); enhancing wellbeing day-to-day (supportive relationships, improved understanding of illness leads to adherence, recognizing new self-value, maintaining a positive outlook); and distressing aspects of living with their illness (dietary restriction is culturally isolating and challenging for families, logistic challenges and socioeconomic disadvantage compounded by health literacy and language barriers, required rapid adjustments to chronic illness, demanding dialysis schedule). Conclusions Latinos described unique cultural preferences such as avoidance of medications for symptom alleviation and a preference to have family group decision-making and ACP conversations at home. Understanding and integrating cultural values and preferences into palliative care offers the potential to improve disparities and achieve quality patient-centered care for Latinos with advanced illness. PMID:28404600

Podium: Ranking Data Using Mixed-Initiative Visual Analytics.

PubMed

Wall, Emily; Das, Subhajit; Chawla, Ravish; Kalidindi, Bharath; Brown, Eli T; Endert, Alex

2018-01-01

People often rank and order data points as a vital part of making decisions. Multi-attribute ranking systems are a common tool used to make these data-driven decisions. Such systems often take the form of a table-based visualization in which users assign weights to the attributes representing the quantifiable importance of each attribute to a decision, which the system then uses to compute a ranking of the data. However, these systems assume that users are able to quantify their conceptual understanding of how important particular attributes are to a decision. This is not always easy or even possible for users to do. Rather, people often have a more holistic understanding of the data. They form opinions that data point A is better than data point B but do not necessarily know which attributes are important. To address these challenges, we present a visual analytic application to help people rank multi-variate data points. We developed a prototype system, Podium, that allows users to drag rows in the table to rank order data points based on their perception of the relative value of the data. Podium then infers a weighting model using Ranking SVM that satisfies the user's data preferences as closely as possible. Whereas past systems help users understand the relationships between data points based on changes to attribute weights, our approach helps users to understand the attributes that might inform their understanding of the data. We present two usage scenarios to describe some of the potential uses of our proposed technique: (1) understanding which attributes contribute to a user's subjective preferences for data, and (2) deconstructing attributes of importance for existing rankings. Our proposed approach makes powerful machine learning techniques more usable to those who may not have expertise in these areas.

The Neural Basis of Risky Choice with Affective Outcomes

PubMed Central

Suter, Renata S.; Pachur, Thorsten; Hertwig, Ralph; Endestad, Tor; Biele, Guido

2015-01-01

Both normative and many descriptive theories of decision making under risk are based on the notion that outcomes are weighted by their probability, with subsequent maximization of the (subjective) expected outcome. Numerous investigations from psychology, economics, and neuroscience have produced evidence consistent with this notion. However, this research has typically investigated choices involving relatively affect-poor, monetary outcomes. We compared choice in relatively affect-poor, monetary lottery problems with choice in relatively affect-rich medical decision problems. Computational modeling of behavioral data and model-based neuroimaging analyses provide converging evidence for substantial differences in the respective decision mechanisms. Relative to affect-poor choices, affect-rich choices yielded a more strongly curved probability weighting function of cumulative prospect theory, thus signaling that the psychological impact of probabilities is strongly diminished for affect-rich outcomes. Examining task-dependent brain activation, we identified a region-by-condition interaction indicating qualitative differences of activation between affect-rich and affect-poor choices. Moreover, brain activation in regions that were more active during affect-poor choices (e.g., the supramarginal gyrus) correlated with individual trial-by-trial decision weights, indicating that these regions reflect processing of probabilities. Formal reverse inference Neurosynth meta-analyses suggested that whereas affect-poor choices seem to be based on brain mechanisms for calculative processes, affect-rich choices are driven by the representation of outcomes’ emotional value and autobiographical memories associated with them. These results provide evidence that the traditional notion of expectation maximization may not apply in the context of outcomes laden with affective responses, and that understanding the brain mechanisms of decision making requires the domain of the decision to be taken into account. PMID:25830918

Building University Capacity to Visualize Solutions to Complex Problems in the Arctic

NASA Astrophysics Data System (ADS)

Broderson, D.; Veazey, P.; Raymond, V. L.; Kowalski, K.; Prakash, A.; Signor, B.

2016-12-01

Rapidly changing environments are creating complex problems across the globe, which are particular magnified in the Arctic. These worldwide challenges can best be addressed through diverse and interdisciplinary research teams. It is incumbent on such teams to promote co-production of knowledge and data-driven decision-making by identifying effective methods to communicate their findings and to engage with the public. Decision Theater North (DTN) is a new semi-immersive visualization system that provides a space for teams to collaborate and develop solutions to complex problems, relying on diverse sets of skills and knowledge. It provides a venue to synthesize the talents of scientists, who gather information (data); modelers, who create models of complex systems; artists, who develop visualizations; communicators, who connect and bridge populations; and policymakers, who can use the visualizations to develop sustainable solutions to pressing problems. The mission of Decision Theater North is to provide a cutting-edge visual environment to facilitate dialogue and decision-making by stakeholders including government, industry, communities and academia. We achieve this mission by adopting a multi-faceted approach reflected in the theater's design, technology, networking capabilities, user support, community relationship building, and strategic partnerships. DTN is a joint project of Alaska's National Science Foundation Experimental Program to Stimulate Competitive Research (NSF EPSCoR) and the University of Alaska Fairbanks (UAF), who have brought the facility up to full operational status and are now expanding its development space to support larger team science efforts. Based in Fairbanks, Alaska, DTN is uniquely poised to address changes taking place in the Arctic and subarctic, and is connected with a larger network of decision theaters that include the Arizona State University Decision Theater Network and the McCain Institute in Washington, DC.

The neural basis of risky choice with affective outcomes.

PubMed

Suter, Renata S; Pachur, Thorsten; Hertwig, Ralph; Endestad, Tor; Biele, Guido

2015-01-01

Both normative and many descriptive theories of decision making under risk are based on the notion that outcomes are weighted by their probability, with subsequent maximization of the (subjective) expected outcome. Numerous investigations from psychology, economics, and neuroscience have produced evidence consistent with this notion. However, this research has typically investigated choices involving relatively affect-poor, monetary outcomes. We compared choice in relatively affect-poor, monetary lottery problems with choice in relatively affect-rich medical decision problems. Computational modeling of behavioral data and model-based neuroimaging analyses provide converging evidence for substantial differences in the respective decision mechanisms. Relative to affect-poor choices, affect-rich choices yielded a more strongly curved probability weighting function of cumulative prospect theory, thus signaling that the psychological impact of probabilities is strongly diminished for affect-rich outcomes. Examining task-dependent brain activation, we identified a region-by-condition interaction indicating qualitative differences of activation between affect-rich and affect-poor choices. Moreover, brain activation in regions that were more active during affect-poor choices (e.g., the supramarginal gyrus) correlated with individual trial-by-trial decision weights, indicating that these regions reflect processing of probabilities. Formal reverse inference Neurosynth meta-analyses suggested that whereas affect-poor choices seem to be based on brain mechanisms for calculative processes, affect-rich choices are driven by the representation of outcomes' emotional value and autobiographical memories associated with them. These results provide evidence that the traditional notion of expectation maximization may not apply in the context of outcomes laden with affective responses, and that understanding the brain mechanisms of decision making requires the domain of the decision to be taken into account.

Distinct effects of apathy and dopamine on effort-based decision-making in Parkinson's disease.

PubMed

Le Heron, Campbell; Plant, Olivia; Manohar, Sanjay; Ang, Yuen-Siang; Jackson, Matthew; Lennox, Graham; Hu, Michele T; Husain, Masud

2018-05-01

Effort-based decision-making is a cognitive process crucial to normal motivated behaviour. Apathy is a common and disabling complication of Parkinson's disease, but its aetiology remains unclear. Intriguingly, the neural substrates associated with apathy also subserve effort-based decision-making in animal models and humans. Furthermore, the dopaminergic system plays a core role in motivating effortful behaviour for reward, and its dysfunction has been proposed to play a crucial role in the aetiology of apathy in Parkinson's disease. We hypothesized that disrupted effort-based decision-making underlies the syndrome of apathy in Parkinson's disease, and that this disruption may be modulated by the dopaminergic system. An effort-based decision-making task was administered to 39 patients with Parkinson's disease, with and without clinical apathy, ON and OFF their normal dopaminergic medications across two separate sessions, as well as 32 healthy age- and gender-matched controls. On a trial-by-trial basis, participants decided whether to accept or reject offers of monetary reward in return for exerting different levels of physical effort via handheld, individually calibrated dynamometers. Effort and reward were manipulated independently, such that offers spanned the full range of effort/reward combinations. Apathy was assessed using the Lille apathy rating scale. Motor effects of the dopamine manipulation were assessed using the Unified Parkinson's Disease Rating Scale part three motor score. The primary outcome variable was choice (accept/decline offer) analysed using a hierarchical generalized linear mixed effects model, and the vigour of squeeze (Newtons exerted above required force). Both apathy and dopamine depletion were associated with reduced acceptance of offers. However, these effects were driven by dissociable patterns of responding. While apathy was characterized by increased rejection of predominantly low reward offers, dopamine increased responding to high effort, high reward offers, irrespective of underlying motivational state. Dopamine also exerted a main effect on motor vigour, increasing force production independently of reward offered, while apathy did not affect this measure. The findings demonstrate that disrupted effort-based decision-making underlies Parkinson's disease apathy, but in a manner distinct to that caused by dopamine depletion. Apathy is associated with reduced incentivization by the rewarding outcomes of actions. In contrast, dopamine has a general effect in motivating behaviour for high effort, high reward options without altering the response pattern that characterizes the apathetic state. Thus, the motivational deficit observed in Parkinson's disease appears not to be simply secondary to dopaminergic depletion of mesocorticolimbic pathways, suggesting non-dopaminergic therapeutic strategies for apathy may be important future targets.

Age differences in the effect of framing on risky choice: A meta-analysis

PubMed Central

Best, Ryan; Charness, Neil

2015-01-01

The framing of decision scenarios in terms of potential gains versus losses has been shown to influence choice preferences between sure and risky options. Normative cognitive changes associated with aging have been known to affect decision-making, which has led to a number of studies investigating the influence of aging on the effect of framing. Mata, Josef, Samanez-Larkin, and Hertwig (2011) systematically reviewed the available literature using a meta-analytic approach, but did not include tests of homogeneity nor subsequent moderator variable analyses. The current review serves to extend the previous analysis to include such tests as well as update the pool of studies available for analysis. Results for both positively and negatively framed conditions were reviewed using two meta-analyses encompassing data collected from 3,232 subjects across 18 studies. Deviating from the previous results, the current analysis finds a tendency for younger adults to choose the risky option more often than older adults for positively framed items. Moderator variable analyses find this effect to likely be driven by the specific decision scenario, showing a significant effect with younger adults choosing the risky option more often in small-amount financial and large-amount mortality-based scenarios. For negatively framed items, the current review found no overall age difference in risky decision making, confirming the results from the prior meta-analysis. Moderator variable analyses conducted to address heterogeneity found younger adults to be more likely than older adults to choose the risky option for negatively framed high-amount mortality-based decision scenarios. Practical implications for older adults are discussed. PMID:26098168

Age differences in the effect of framing on risky choice: A meta-analysis.

PubMed

Best, Ryan; Charness, Neil

2015-09-01

The framing of decision scenarios in terms of potential gains versus losses has been shown to influence choice preferences between sure and risky options. Normative cognitive changes associated with aging have been known to affect decision making, which has led to a number of studies investigating the influence of aging on the effect of framing. Mata, Josef, Samanez-Larkin, and Hertwig (2011) systematically reviewed the available literature using a meta-analytic approach, but did not include tests of homogeneity or subsequent moderator variable analyses. The current review serves to extend the previous analysis to include such tests as well as update the pool of studies available for analysis. Results for both positively and negatively framed conditions were reviewed using 2 meta-analyses encompassing data collected from 3,232 subjects across 18 studies. Deviating from the previous results, the current analysis found a tendency for younger adults to choose the risky option more often than older adults for positively framed items. Moderator variable analyses found this effect likely to be driven by the specific decision scenario, showing a significant effect, with younger adults choosing the risky option more often in small-amount financial and large-amount mortality-based scenarios. For negatively framed items, the current review found no overall age difference in risky decision making, confirming the results from the prior meta-analysis. Moderator variable analyses conducted to address heterogeneity found younger adults to be more likely than older adults to choose the risky option for negatively framed high-amount mortality-based decision scenarios. Practical implications for older adults are discussed. (c) 2015 APA, all rights reserved).

Embedded performance validity testing in neuropsychological assessment: Potential clinical tools.

PubMed

Rickards, Tyler A; Cranston, Christopher C; Touradji, Pegah; Bechtold, Kathleen T

2018-01-01

The article aims to suggest clinically-useful tools in neuropsychological assessment for efficient use of embedded measures of performance validity. To accomplish this, we integrated available validity-related and statistical research from the literature, consensus statements, and survey-based data from practicing neuropsychologists. We provide recommendations for use of 1) Cutoffs for embedded performance validity tests including Reliable Digit Span, California Verbal Learning Test (Second Edition) Forced Choice Recognition, Rey-Osterrieth Complex Figure Test Combination Score, Wisconsin Card Sorting Test Failure to Maintain Set, and the Finger Tapping Test; 2) Selecting number of performance validity measures to administer in an assessment; and 3) Hypothetical clinical decision-making models for use of performance validity testing in a neuropsychological assessment collectively considering behavior, patient reporting, and data indicating invalid or noncredible performance. Performance validity testing helps inform the clinician about an individual's general approach to tasks: response to failure, task engagement and persistence, compliance with task demands. Data-driven clinical suggestions provide a resource to clinicians and to instigate conversation within the field to make more uniform, testable decisions to further the discussion, and guide future research in this area.

Goal-directed, habitual and Pavlovian prosocial behavior

PubMed Central

Gęsiarz, Filip; Crockett, Molly J.

2015-01-01

Although prosocial behaviors have been widely studied across disciplines, the mechanisms underlying them are not fully understood. Evidence from psychology, biology and economics suggests that prosocial behaviors can be driven by a variety of seemingly opposing factors: altruism or egoism, intuition or deliberation, inborn instincts or learned dispositions, and utility derived from actions or their outcomes. Here we propose a framework inspired by research on reinforcement learning and decision making that links these processes and explains characteristics of prosocial behaviors in different contexts. More specifically, we suggest that prosocial behaviors inherit features of up to three decision-making systems employed to choose between self- and other- regarding acts: a goal-directed system that selects actions based on their predicted consequences, a habitual system that selects actions based on their reinforcement history, and a Pavlovian system that emits reflexive responses based on evolutionarily prescribed priors. This framework, initially described in the field of cognitive neuroscience and machine learning, provides insight into the potential neural circuits and computations shaping prosocial behaviors. Furthermore, it identifies specific conditions in which each of these three systems should dominate and promote other- or self- regarding behavior. PMID:26074797

Effective behavioral modeling and prediction even when few exemplars are available

NASA Astrophysics Data System (ADS)

Goan, Terrance; Kartha, Neelakantan; Kaneshiro, Ryan

2006-05-01

While great progress has been made in the lowest levels of data fusion, practical advances in behavior modeling and prediction remain elusive. The most critical limitation of existing approaches is their inability to support the required knowledge modeling and continuing refinement under realistic constraints (e.g., few historic exemplars, the lack of knowledge engineering support, and the need for rapid system deployment). This paper reports on our ongoing efforts to develop Propheteer, a system which will address these shortcomings through two primary techniques. First, with Propheteer we abandon the typical consensus-driven modeling approaches that involve infrequent group decision making sessions in favor of an approach that solicits asynchronous knowledge contributions (in the form of alternative future scenarios and indicators) without burdening the user with endless certainty or probability estimates. Second, we enable knowledge contributions by personnel beyond the typical core decision making group, thereby casting light on blind spots, mitigating human biases, and helping maintain the currency of the developed behavior models. We conclude with a discussion of the many lessons learned in the development of our prototype Propheteer system.

Understanding consumer decisions using behavioral economics.

PubMed

Zandstra, Elizabeth H; Miyapuram, Krishna P; Tobler, Philippe N

2013-01-01

Consumers make many decisions in everyday life involving finances, food, and health. It is known from behavioral economics research that people are often driven by short-term gratification, that is, people tend to choose the immediate, albeit smaller reward. But choosing the delayed reward, that is, delaying the gratification, can actually be beneficial. How can we motivate consumers to resist the "now" and invest in their future, leading to sustainable or healthy habits? We review recent developments from behavioral and neuroimaging studies that are relevant for understanding consumer decisions. Further, we present results from our field research that examined whether we can increase the perceived value of a (delayed) environmental benefit using tailored communication, that is, change the way it is framed. More specifically, we investigated whether we can boost the value of an abstract, long-term "green" claim of a product by expressing it as a concrete, short-term benefit. This is a new application area for behavioral economics. Copyright © 2013 Elsevier B.V. All rights reserved.

Reward value-based gain control: divisive normalization in parietal cortex.

PubMed

Louie, Kenway; Grattan, Lauren E; Glimcher, Paul W

2011-07-20

The representation of value is a critical component of decision making. Rational choice theory assumes that options are assigned absolute values, independent of the value or existence of other alternatives. However, context-dependent choice behavior in both animals and humans violates this assumption, suggesting that biological decision processes rely on comparative evaluation. Here we show that neurons in the monkey lateral intraparietal cortex encode a relative form of saccadic value, explicitly dependent on the values of the other available alternatives. Analogous to extra-classical receptive field effects in visual cortex, this relative representation incorporates target values outside the response field and is observed in both stimulus-driven activity and baseline firing rates. This context-dependent modulation is precisely described by divisive normalization, indicating that this standard form of sensory gain control may be a general mechanism of cortical computation. Such normalization in decision circuits effectively implements an adaptive gain control for value coding and provides a possible mechanistic basis for behavioral context-dependent violations of rationality.

Foundations of translational ecology

USGS Publications Warehouse

Enquist, Carolyn A. F.; Jackson, Stephen T.; Garfin, Gregg M.; Davis, Frank W.; Gerber, Leah R.; Littell, Jeremy; Tank, Jennifer L.; Terando, Adam; Wall, Tamara U.; Halpern, Benjamin S.; Morelli, Toni L.; Hiers, J. Kevin; McNie, Elizabeth; Stephenson, Nathan L.; Williamson, Matthew A.; Woodhouse, Connie A.; Yung, Laurie; Brunson, Mark W.; Hall, Kimberly R.; Hallett, Lauren M.; Lawson, Dawn M.; Moritz, Max A.; Nydick, Koren R.; Pairis, Amber; Ray, Andrea J.; Regan, Claudia M.; Safford, Hugh D.; Schwartz, Mark W.; Shaw, M. Rebecca

2017-01-01

Ecologists who specialize in translational ecology (TE) seek to link ecological knowledge to decision making by integrating ecological science with the full complement of social dimensions that underlie today's complex environmental issues. TE is motivated by a search for outcomes that directly serve the needs of natural resource managers and decision makers. This objective distinguishes it from both basic and applied ecological research and, as a practice, it deliberately extends research beyond theory or opportunistic applications. TE is uniquely positioned to address complex issues through interdisciplinary team approaches and integrated scientist–practitioner partnerships. The creativity and context‐specific knowledge of resource managers, practitioners, and decision makers inform and enrich the scientific process and help shape use‐driven, actionable science. Moreover, addressing research questions that arise from on‐the‐ground management issues – as opposed to the top‐down or expert‐oriented perspectives of traditional science – can foster the high levels of trust and commitment that are critical for long‐term, sustained engagement between partners.

Collective decision dynamics in the presence of external drivers

NASA Astrophysics Data System (ADS)

Bassett, Danielle S.; Alderson, David L.; Carlson, Jean M.

2012-09-01

We develop a sequence of models describing information transmission and decision dynamics for a network of individual agents subject to multiple sources of influence. Our general framework is set in the context of an impending natural disaster, where individuals, represented by nodes on the network, must decide whether or not to evacuate. Sources of influence include a one-to-many externally driven global broadcast as well as pairwise interactions, across links in the network, in which agents transmit either continuous opinions or binary actions. We consider both uniform and variable threshold rules on the individual opinion as baseline models for decision making. Our results indicate that (1) social networks lead to clustering and cohesive action among individuals, (2) binary information introduces high temporal variability and stagnation, and (3) information transmission over the network can either facilitate or hinder action adoption, depending on the influence of the global broadcast relative to the social network. Our framework highlights the essential role of local interactions between agents in predicting collective behavior of the population as a whole.

Information systems: the key to evidence-based health practice.

PubMed Central

Rodrigues, R. J.

2000-01-01

Increasing prominence is being given to the use of best current evidence in clinical practice and health services and programme management decision-making. The role of information in evidence-based practice (EBP) is discussed, together with questions of how advanced information systems and technology (IS&T) can contribute to the establishment of a broader perspective for EBP. The author examines the development, validation and use of a variety of sources of evidence and knowledge that go beyond the well-established paradigm of research, clinical trials, and systematic literature review. Opportunities and challenges in the implementation and use of IS&T and knowledge management tools are examined for six application areas: reference databases, contextual data, clinical data repositories, administrative data repositories, decision support software, and Internet-based interactive health information and communication. Computerized and telecommunications applications that support EBP follow a hierarchy in which systems, tasks and complexity range from reference retrieval and the processing of relatively routine transactions, to complex "data mining" and rule-driven decision support systems. PMID:11143195

Data Science and its Relationship to Big Data and Data-Driven Decision Making.

PubMed

Provost, Foster; Fawcett, Tom

2013-03-01

Companies have realized they need to hire data scientists, academic institutions are scrambling to put together data-science programs, and publications are touting data science as a hot-even "sexy"-career choice. However, there is confusion about what exactly data science is, and this confusion could lead to disillusionment as the concept diffuses into meaningless buzz. In this article, we argue that there are good reasons why it has been hard to pin down exactly what is data science. One reason is that data science is intricately intertwined with other important concepts also of growing importance, such as big data and data-driven decision making. Another reason is the natural tendency to associate what a practitioner does with the definition of the practitioner's field; this can result in overlooking the fundamentals of the field. We believe that trying to define the boundaries of data science precisely is not of the utmost importance. We can debate the boundaries of the field in an academic setting, but in order for data science to serve business effectively, it is important (i) to understand its relationships to other important related concepts, and (ii) to begin to identify the fundamental principles underlying data science. Once we embrace (ii), we can much better understand and explain exactly what data science has to offer. Furthermore, only once we embrace (ii) should we be comfortable calling it data science. In this article, we present a perspective that addresses all these concepts. We close by offering, as examples, a partial list of fundamental principles underlying data science.

Exploring sales data during a healthy corner store intervention in Toronto: the Food Retail Environments Shaping Health (FRESH) project.

PubMed

Minaker, Leia M; Lynch, Meghan; Cook, Brian E; Mah, Catherine L

2017-10-01

Population health interventions in the retail food environment, such as corner store interventions, aim to influence the kind of cues consumers receive so that they are more often directed toward healthier options. Research that addresses financial aspects of retail interventions, particularly using outcome measures such as store sales that are central to retail decision making, is limited. This study explored store sales over time and across product categories during a healthy corner store intervention in a lowincome neighbourhood in Toronto, Ontario. Sales data (from August 2014 to April 2015) were aggregated by product category and by day. We used Microsoft Excel pivot tables to summarize and visually present sales data. We conducted t-tests to examine differences in product category sales by "peak" versus "nonpeak" sales days. Overall store sales peaked on the days at the end of each month, aligned with the issuing of social assistance payments. Revenue spikes on peak sales days were driven predominantly by transit pass sales. On peak sales days, mean sales of nonnutritious snacks and cigarettes were marginally higher than on other days of the month. Finally, creative strategies to increase sales of fresh vegetables and fruits seemed to substantially increase revenue from these product categories. Store sales data is an important store-level metric of food environment intervention success. Furthermore, data-driven decision making by retailers can be important for tailoring interventions. Future interventions and research should consider partnerships and additional success metrics for retail food environment interventions in diverse Canadian contexts.

Bridge damage detection using spatiotemporal patterns extracted from dense sensor network

NASA Astrophysics Data System (ADS)

Liu, Chao; Gong, Yongqiang; Laflamme, Simon; Phares, Brent; Sarkar, Soumik

2017-01-01

The alarmingly degrading state of transportation infrastructures combined with their key societal and economic importance calls for automatic condition assessment methods to facilitate smart management of maintenance and repairs. With the advent of ubiquitous sensing and communication capabilities, scalable data-driven approaches is of great interest, as it can utilize large volume of streaming data without requiring detailed physical models that can be inaccurate and computationally expensive to run. Properly designed, a data-driven methodology could enable fast and automatic evaluation of infrastructures, discovery of causal dependencies among various sub-system dynamic responses, and decision making with uncertainties and lack of labeled data. In this work, a spatiotemporal pattern network (STPN) strategy built on symbolic dynamic filtering (SDF) is proposed to explore spatiotemporal behaviors in a bridge network. Data from strain gauges installed on two bridges are generated using finite element simulation for three types of sensor networks from a density perspective (dense, nominal, sparse). Causal relationships among spatially distributed strain data streams are extracted and analyzed for vehicle identification and detection, and for localization of structural degradation in bridges. Multiple case studies show significant capabilities of the proposed approach in: (i) capturing spatiotemporal features to discover causality between bridges (geographically close), (ii) robustness to noise in data for feature extraction, (iii) detecting and localizing damage via comparison of bridge responses to similar vehicle loads, and (iv) implementing real-time health monitoring and decision making work flow for bridge networks. Also, the results demonstrate increased sensitivity in detecting damages and higher reliability in quantifying the damage level with increase in sensor network density.

Exploring sales data during a healthy corner store intervention in Toronto: the Food Retail Environments Shaping Health (FRESH) project

PubMed Central

Leia M., Minaker; Meghan, Lynch; Brian E., Cook; Catherine L., Mah

2017-01-01

Abstract Introduction: Population health interventions in the retail food environment, such as corner store interventions, aim to influence the kind of cues consumers receive so that they are more often directed toward healthier options. Research that addresses financial aspects of retail interventions, particularly using outcome measures such as store sales that are central to retail decision making, is limited. This study explored store sales over time and across product categories during a healthy corner store intervention in a lowincome neighbourhood in Toronto, Ontario. Methods: Sales data (from August 2014 to April 2015) were aggregated by product category and by day. We used Microsoft Excel pivot tables to summarize and visually present sales data. We conducted t-tests to examine differences in product category sales by “peak” versus “nonpeak” sales days. Results: Overall store sales peaked on the days at the end of each month, aligned with the issuing of social assistance payments. Revenue spikes on peak sales days were driven predominantly by transit pass sales. On peak sales days, mean sales of nonnutritious snacks and cigarettes were marginally higher than on other days of the month. Finally, creative strategies to increase sales of fresh vegetables and fruits seemed to substantially increase revenue from these product categories. Conclusion: Store sales data is an important store-level metric of food environment intervention success. Furthermore, data-driven decision making by retailers can be important for tailoring interventions. Future interventions and research should consider partnerships and additional success metrics for retail food environment interventions in diverse Canadian contexts. PMID:29043761

Two-Stage Fracturing Wastewater Management in Shale Gas Development

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

Zhang, Xiaodong; Sun, Alexander Y.; Duncan, Ian J.

Here, management of shale gas wastewater treatment, disposal, and reuse has become a significant environmental challenge, driven by an ongoing boom in development of U.S. shale gas reservoirs. Systems-analysis based decision support is helpful for effective management of wastewater, and provision of cost-effective decision alternatives from a whole-system perspective. Uncertainties are inherent in many modeling parameters, affecting the generated decisions. In order to effectively deal with the recourse issue in decision making, in this work a two-stage stochastic fracturing wastewater management model, named TSWM, is developed to provide decision support for wastewater management planning in shale plays. Using the TSWMmore » model, probabilistic and nonprobabilistic uncertainties are effectively handled. The TSWM model provides flexibility in generating shale gas wastewater management strategies, in which the first-stage decision predefined by decision makers before uncertainties are unfolded is corrected in the second stage to achieve the whole-system’s optimality. Application of the TSWM model to a comprehensive synthetic example demonstrates its practical applicability and feasibility. Optimal results are generated for allowable wastewater quantities, excess wastewater, and capacity expansions of hazardous wastewater treatment plants to achieve the minimized total system cost. The obtained interval solutions encompass both optimistic and conservative decisions. Trade-offs between economic and environmental objectives are made depending on decision makers’ knowledge and judgment, as well as site-specific information. In conclusion, the proposed model is helpful in forming informed decisions for wastewater management associated with shale gas development.« less

Two-Stage Fracturing Wastewater Management in Shale Gas Development

DOE PAGES

Zhang, Xiaodong; Sun, Alexander Y.; Duncan, Ian J.; ...

2017-01-19

Here, management of shale gas wastewater treatment, disposal, and reuse has become a significant environmental challenge, driven by an ongoing boom in development of U.S. shale gas reservoirs. Systems-analysis based decision support is helpful for effective management of wastewater, and provision of cost-effective decision alternatives from a whole-system perspective. Uncertainties are inherent in many modeling parameters, affecting the generated decisions. In order to effectively deal with the recourse issue in decision making, in this work a two-stage stochastic fracturing wastewater management model, named TSWM, is developed to provide decision support for wastewater management planning in shale plays. Using the TSWMmore » model, probabilistic and nonprobabilistic uncertainties are effectively handled. The TSWM model provides flexibility in generating shale gas wastewater management strategies, in which the first-stage decision predefined by decision makers before uncertainties are unfolded is corrected in the second stage to achieve the whole-system’s optimality. Application of the TSWM model to a comprehensive synthetic example demonstrates its practical applicability and feasibility. Optimal results are generated for allowable wastewater quantities, excess wastewater, and capacity expansions of hazardous wastewater treatment plants to achieve the minimized total system cost. The obtained interval solutions encompass both optimistic and conservative decisions. Trade-offs between economic and environmental objectives are made depending on decision makers’ knowledge and judgment, as well as site-specific information. In conclusion, the proposed model is helpful in forming informed decisions for wastewater management associated with shale gas development.« less

Investigating the application of Rasch theory in measuring change in middle school student performance in physical science

NASA Astrophysics Data System (ADS)

Cunningham, Jessica D.

Newton's Universe (NU), an innovative teacher training program, strives to obtain measures from rural, middle school science teachers and their students to determine the impact of its distance learning course on understanding of temperature. No consensus exists on the most appropriate and useful method of analysis to measure change in psychological constructs over time. Several item response theory (IRT) models have been deemed useful in measuring change, which makes the choice of an IRT model not obvious. The appropriateness and utility of each model, including a comparison to a traditional analysis of variance approach, was investigated using middle school science student performance on an assessment over an instructional period. Predetermined criteria were outlined to guide model selection based on several factors including research questions, data properties, and meaningful interpretations to determine the most appropriate model for this study. All methods employed in this study reiterated one common interpretation of the data -- specifically, that the students of teachers with any NU course experience had significantly greater gains in performance over the instructional period. However, clear distinctions were made between an analysis of variance and the racked and stacked analysis using the Rasch model. Although limited research exists examining the usefulness of the Rasch model in measuring change in understanding over time, this study applied these methods and detailed plausible implications for data-driven decisions based upon results for NU and others. Being mindful of the advantages and usefulness of each method of analysis may help others make informed decisions about choosing an appropriate model to depict changes to evaluate other programs. Results may encourage other researchers to consider the meaningfulness of using IRT for this purpose. Results have implications for data-driven decisions for future professional development courses, in science education and other disciplines. KEYWORDS: Item Response Theory, Rasch Model, Racking and Stacking, Measuring Change in Student Performance, Newton's Universe teacher training

Building a Public Health Response to the Flint Water Crisis: Implications for Policy and Decision-Making

NASA Astrophysics Data System (ADS)

Furr-Holden, D.

2017-12-01

Flint, MI has experienced a recent, man-made public health crisis. The Flint Water Crisis, caused by a switch in the municipal water supply and subsequent violation of engineering and regulatory standards to ensure water quality lead to a large portion of the city being exposed to excess metals (including lead), bacteria and other water-borne pathogens. The data used to initially rebut the existence of the crisis were ecologically flawed as they included large numbers of people who were not on the Flint water supply. Policy-makers, municipal officials, the medical community, and public health professionals were at odds over the existence of a problem and the lack of data only fueled the debate. Pediatricians, lead by Dr. Mona Hannah-Attisha, began testing children in the Hurley Children's Medical Center for blood-lead levels and observed a 2-fold increase in elevated blood lead levels in Flint children compared to children in the area not on the Flint municipal water supply, where no increases in elevated lead were observed. Subsequent geospatial analyses revealed spatial clustering of cases based on where children live, go to school and play. These data represented the first step in data driven decision making leading to the subsequent switch of the municipal water supply and launch of subsequent advocacy efforts to remediate the effect of the Water Crisis. Since that time, a multi-disciplinary team of scientists including engineers, bench scientists, physicians and public health researchers have mounted evidence to promote complete replacement of the city's aging water infrastructure, developed a data registry to track cases and coordinate care and services for affected residents, and implemented a community engagement model that puts residents and community stakeholders at the heart of the planning and implementation efforts. The presentation will include data used at various stages to mount a public health response to the Flint Water Crisis and establish the link between data-driven decisions and subsequent policies to mediate long term consequences.

Life support decision making in critical care: Identifying and appraising the qualitative research evidence.

PubMed

Giacomini, Mita; Cook, Deborah; DeJean, Deirdre

2009-04-01

The objective of this study is to identify and appraise qualitative research evidence on the experience of making life-support decisions in critical care. In six databases and supplementary sources, we sought original research published from January 1990 through June 2008 reporting qualitative empirical studies of the experience of life-support decision making in critical care settings. Fifty-three journal articles and monographs were included. Of these, 25 reported prospective studies and 28 reported retrospective studies. We abstracted methodologic characteristics relevant to the basic critical appraisal of qualitative research (prospective data collection, ethics approval, purposive sampling, iterative data collection and analysis, and any method to corroborate findings). Qualitative research traditions represented include grounded theory (n = 15, 28%), ethnography or naturalistic methods (n = 15, 28%), phenomenology (n = 9, 17%), and other or unspecified approaches (n = 14, 26%). All 53 documents describe the research setting; 97% indicate purposive sampling of participants. Studies vary in their capture of multidisciplinary clinician and family perspectives. Thirty-one (58%) report research ethics board review. Only 49% report iterative data collection and analysis, and eight documents (15%) describe an analytically driven stopping point for data collection. Thirty-two documents (60%) indicated a method for corroborating findings. Qualitative evidence often appears outside of clinical journals, with most research from the United States. Prospective, observation-based studies follow life-support decision making directly. These involve a variety of participants and yield important insights into interactions, communication, and dynamics. Retrospective, interview-based studies lack this direct engagement, but focus on the recollections of fewer types of participants (particularly patients and physicians), and typically address specific issues (communication and stress). Both designs can provide useful reflections for improving care. Given the diversity of qualitative research in critical care, room for improvement exists regarding both the quality and transparency of reported methodology.

Positioning Model-Supported, Participatory, Water Management Decision Making under Uncertainty within the Western Philosphical Discourse on Knowledge and Governance

NASA Astrophysics Data System (ADS)

Purkey, D. R.; Escobar, M.; Mehta, V. K.; Forni, L.

2016-12-01

Two important trends currently shape the manner in which water resources planning and decision making occurs. The first relates to the increasing reliance on participatory stakeholder processes as a forum for evaluating water management options and selecting the appropriate course of action. The second relates to the growing recognition that earlier deterministic approaches to this evaluation of options may no longer be appropriate, nor required. The convergence of these two trends poses questions as to the proper role of data, information, analysis and expertise in the inherently social and political process of negotiating water resources management agreements and implementing water resources management interventions. The question of how to discover the best or optimal option in the face of deep uncertainty related to climate change, demography, economic development, and regulatory reform is compelling. More fundamentally the question of whether the "perfect" option even exits to be discovered is perhaps more critical. While this existential question may be new to the water resource management community, it is not new to western political theory. This paper explores early classical philosophical writing related to issues of knowledge and governance as captured in the work of Plato and Aristotle; and then attempts to place a new approach to analysis-supported, stakeholder-driven water resources planning and decision making within this philosophical discourse. Using examples from river systems in California and the Andes, where the theory of Robust Decision Making has been used as an organizing construct for stakeholder processes, it is argued that the expectation that analysis will lead to the discovery of the perfect option is not warranted when stakeholders are engaged in the process of discovering a consensus option. This argument will touch upon issue of the diversity of values, model uncertainty and creditability, and the visualization of model output required to explore the implications of various management options across a range of inherently unknowable future conditions.

If We Know So Much, Why Do We Make Such Crummy Decisions?

NASA Astrophysics Data System (ADS)

Davis, M.

2017-12-01

If We Know So Much, Why Do We Make Such Crummy Decisions?Mark Davis Senior Research Fellow Director, Tulane Institute on Water Resources Law and Policy Director, ByWater Institute at Tulane University A Presentation to American Geophysical Union Translational Hydrology: Moving from Science to Decisions Panel December 2017 For much of human history, water management and science have not been on a first name basis. Waters have been dammed, diverted, pumped and filled for many reasons, occasionally even in ways that reflected a deep respect for hydrology and even less occasionally for ecology. But the simple fact is that water management decisions have long been rooted in utilitarian relations to power and property and not in science-and for the most part still are. Over the past 50 years or state and federal laws have grafted science driven concerns into a wide range of governmental decisions through acts like the National Environmental Policy Act, the Endangered Species Act, the Clean Water Act and others. As a result, science influences decisions but does not compel them; for the most part, there is no actual pathway from science to decisions. Science is not its own advocate and even the best information does not compel action without help from factors rooted in law, policy, property, and power. Understanding this basic fact and the architecture of decision-making for a given action are key to ensuring that the connections between science and decisions are robust. An example of this can be seen in the plans to counter sea level rise and coastal land loss in Louisiana. Extensive plans with a strong science and engineering foundation have been drawn that call for a complex system of public works projects that would essentially reconnect the coast with the rivers that built and nurtured it. What those plans do not do is say how those projects would be authorized or financed. They do not say what rights they have to redirect waters or the even how what rights the State has to those waters. And they do not say how competing right to use and access water will be reconciled. Without those things even the best plan is more a prayer than a prelude to action.

Humans in Biogeophysical Models: Colonial Period Human-Environment Interactions in the Northeastern United States

NASA Astrophysics Data System (ADS)

Parolari, A.; Greco, F.; Green, M.; Lally, M.; Hermans, C.

2008-12-01

Earth system models increasingly require representation of human activities and the important role they play in the environment. At the most fundamental level, human decisions are driven by the need to acquire basic resources - nutrients, energy, water, and space - each derived from the biogeophysical setting. Modern theories in Ecological Economics place these basic resources at the base of a consumption hierarchy (from subsistence to luxury resources) on which societies and economies are built. Human decisions at all levels of this hierarchy are driven by dynamic environmental, social, and economic factors. Therefore, models merging socio-economic and biogeophysical dynamics are required to predict the evolving relationship between humans and the hydrologic cycle. To provide an example, our study focuses on changes to the hydrologic cycle during the United States colonial period (1600 to 1800). Both direct, intentional, human water use (e.g. water supply, irrigation, or hydropower) and indirect, unintentional effects resulting from the use of other resources (e.g. deforestation or beaver trapping) are considered. We argue that water was not the limiting resource to either the Native or Colonist population growth. However, food and tobacco production and harvesting of beaver pelts led to indirect interventions and consequent changes in the hydrologic cycle. The analysis presented here suggests the importance of incorporating human decision- making dynamics with existing geophysical models to fully understand trajectories of human-environment interactions. Predictive tools of this type are critical to characterizing the long-term signature of humans on the landscape and hydrologic cycle.

Perceived Maternal Behavioral Control, Infant Behavior, and Milk Supply: A Qualitative Study.

PubMed

Peacock-Chambers, Elizabeth; Dicks, Kaitlin; Sarathy, Leela; Brown, Allison A; Boynton-Jarrett, Renée

Disparities persist in breastfeeding exclusivity and duration despite increases in breastfeeding initiation. The objective of this study was to examine factors that influence maternal decision making surrounding infant feeding practices over time in a diverse inner-city population. We conducted a prospective qualitative study with 20 mothers recruited from 2 urban primary care clinics. Participants completed open-ended interviews and demographic questionnaires in English or Spanish administered at approximately 2 weeks and 6 months postpartum. Transcripts were analyzed using a combined technique of inductive (data-driven) and deductive (theory-driven, based on the Theory of Planned Behavior) thematic analysis using 3 independent coders and iterative discussion to reach consensus. All women initiated breastfeeding, and 65% reported perceived insufficient milk (PIM). An association between PIM and behavioral control emerged as the overarching theme impacting early breastfeeding cessation and evolved over time. Early postpartum, PIM evoked maternal distress-strong emotional responses to infant crying and need to control infant behaviors. Later, mothers accepted a perceived lack of control over milk supply with minimal distress or as a natural process. Decisions to stop breastfeeding occurred through an iterative process, informed by trials of various strategies and observations of subsequent changes in infant behavior, strongly influenced by competing psychosocial demands. Infant feeding decisions evolve over time and are influenced by perceptions of control over infant behavior and milk supply. Tailored anticipatory guidance is needed to provide time-sensitive strategies to cope with challenging infant behaviors and promote maternal agency over breastfeeding in low-income populations.

Taking chances in the face of threat: romantic risk regulation and approach motivation.

PubMed

Cavallo, Justin V; Fitzsimons, Gráinne M; Holmes, John G

2009-06-01

Four studies examine the hypothesis that goals adopted by high and low self-esteem people (HSEs and LSEs) to manage risk in romantic relationships may reflect global shifts in approach motivation and subsequently affect risk taking in nonsocial domains. In Studies 1 and 2, threats to participants' romantic relationships heightened HSEs' self-reported general approach motivation while lowering LSEs' approach motivation. In Studies 2 through 4, HSEs exhibited riskier decision making (i.e., a greater tendency to pursue rewards and ignore risks) in nonsocial domains following a relationship threat manipulation whereas LSEs made more conservative decisions. These results suggest that the romantic risk regulation may be inherently linked to a broader approach and avoidance system and that specific risk regulation behaviors may be driven by global motivational shifts to a greater degree than previously theorized.

A translation table for patient-centered comparative effectiveness research: guidance to improve the value of research for clinical and health policy decision-making.

PubMed

Tunis, Sean R; Messner, Donna A; Mohr, Penny; Gliklich, Richard E; Dubois, Robert W

2012-05-01

This article provides background and context for a series of papers stemming from a collaborative effort by Outcome Sciences, Inc., the National Pharmaceutical Council and the Center for Medical Technology Policy to use a stakeholder-driven process to develop a decision tool to select appropriate methods for comparative effectiveness research. The perceived need and origins of the 'translation table' concept for method selection are described and the legislative history and role of the Patient-Centered Outcomes Research Institute are reviewed. The article concludes by stressing the significance of this effort for future health services and clinical research, and the importance of consulting end-users--patients, providers, payers and policy-makers--in the process of defining research questions and approaches to them.

Risk, regulation and biotechnology: the case of GM crops.

PubMed

Smyth, Stuart J; Phillips, Peter W B

2014-07-03

The global regulation of products of biotechnology is increasingly divided. Regulatory decisions for genetically modified (GM) crops in North America are predictable and efficient, with numerous countries in Latin and South America, Australia and Asia following this lead. While it might have been possible to argue that Europe's regulations were at one time based on real concerns about minimizing risks and ensuring health and safety, it is increasingly apparent that the entire European Union (EU) regulatory system for GM crops and foods is now driven by political agendas. Countries within the EU are at odds with each other as some have commercial production of GM crops, while others refuse to even develop regulations that could provide for the commercial release of GM crops. This divide in regulatory decision-making is affecting international grain trade, creating challenges for feeding an increasing global population.

A practical approach for active camera coordination based on a fusion-driven multi-agent system

NASA Astrophysics Data System (ADS)

Bustamante, Alvaro Luis; Molina, José M.; Patricio, Miguel A.

2014-04-01

In this paper, we propose a multi-agent system architecture to manage spatially distributed active (or pan-tilt-zoom) cameras. Traditional video surveillance algorithms are of no use for active cameras, and we have to look at different approaches. Such multi-sensor surveillance systems have to be designed to solve two related problems: data fusion and coordinated sensor-task management. Generally, architectures proposed for the coordinated operation of multiple cameras are based on the centralisation of management decisions at the fusion centre. However, the existence of intelligent sensors capable of decision making brings with it the possibility of conceiving alternative decentralised architectures. This problem is approached by means of a MAS, integrating data fusion as an integral part of the architecture for distributed coordination purposes. This paper presents the MAS architecture and system agents.

Control fast or control smart: When should invading pathogens be controlled?

PubMed

Thompson, Robin N; Gilligan, Christopher A; Cunniffe, Nik J

2018-02-01

The intuitive response to an invading pathogen is to start disease management as rapidly as possible, since this would be expected to minimise the future impacts of disease. However, since more spread data become available as an outbreak unfolds, processes underpinning pathogen transmission can almost always be characterised more precisely later in epidemics. This allows the future progression of any outbreak to be forecast more accurately, and so enables control interventions to be targeted more precisely. There is also the chance that the outbreak might die out without any intervention whatsoever, making prophylactic control unnecessary. Optimal decision-making involves continuously balancing these potential benefits of waiting against the possible costs of further spread. We introduce a generic, extensible data-driven algorithm based on parameter estimation and outbreak simulation for making decisions in real-time concerning when and how to control an invading pathogen. The Control Smart Algorithm (CSA) resolves the trade-off between the competing advantages of controlling as soon as possible and controlling later when more information has become available. We show-using a generic mathematical model representing the transmission of a pathogen of agricultural animals or plants through a population of farms or fields-how the CSA allows the timing and level of deployment of vaccination or chemical control to be optimised. In particular, the algorithm outperforms simpler strategies such as intervening when the outbreak size reaches a pre-specified threshold, or controlling when the outbreak has persisted for a threshold length of time. This remains the case even if the simpler methods are fully optimised in advance. Our work highlights the potential benefits of giving careful consideration to the question of when to start disease management during emerging outbreaks, and provides a concrete framework to allow policy-makers to make this decision.

Economic inequality increases risk taking

PubMed Central

Payne, B. Keith; Brown-Iannuzzi, Jazmin L.; Hannay, Jason W.

2017-01-01

Rising income inequality is a global trend. Increased income inequality has been associated with higher rates of crime, greater consumer debt, and poorer health outcomes. The mechanisms linking inequality to poor outcomes among individuals are poorly understood. This research tested a behavioral account linking inequality to individual decision making. In three experiments (n = 811), we found that higher inequality in the outcomes of an economic game led participants to take greater risks to try to achieve higher outcomes. This effect of unequal distributions on risk taking was driven by upward social comparisons. Next, we estimated economic risk taking in daily life using large-scale data from internet searches. Risk taking was higher in states with greater income inequality, an effect driven by inequality at the upper end of the income distribution. Results suggest that inequality may promote poor outcomes, in part, by increasing risky behavior. PMID:28416655

Skin cancer screening: recommendations for data-driven screening guidelines and a review of the US Preventive Services Task Force controversy

PubMed Central

Johnson, Mariah M; Leachman, Sancy A; Aspinwall, Lisa G; Cranmer, Lee D; Curiel-Lewandrowski, Clara; Sondak, Vernon K; Stemwedel, Clara E; Swetter, Susan M; Vetto, John; Bowles, Tawnya; Dellavalle, Robert P; Geskin, Larisa J; Grossman, Douglas; Grossmann, Kenneth F; Hawkes, Jason E; Jeter, Joanne M; Kim, Caroline C; Kirkwood, John M; Mangold, Aaron R; Meyskens, Frank; Ming, Michael E; Nelson, Kelly C; Piepkorn, Michael; Pollack, Brian P; Robinson, June K; Sober, Arthur J; Trotter, Shannon; Venna, Suraj S; Agarwala, Sanjiv; Alani, Rhoda; Averbook, Bruce; Bar, Anna; Becevic, Mirna; Box, Neil; E Carson, William; Cassidy, Pamela B; Chen, Suephy C; Chu, Emily Y; Ellis, Darrel L; Ferris, Laura K; Fisher, David E; Kendra, Kari; Lawson, David H; Leming, Philip D; Margolin, Kim A; Markovic, Svetomir; Martini, Mary C; Miller, Debbie; Sahni, Debjani; Sharfman, William H; Stein, Jennifer; Stratigos, Alexander J; Tarhini, Ahmad; Taylor, Matthew H; Wisco, Oliver J; Wong, Michael K

2017-01-01

Melanoma is usually apparent on the skin and readily detected by trained medical providers using a routine total body skin examination, yet this malignancy is responsible for the majority of skin cancer-related deaths. Currently, there is no national consensus on skin cancer screening in the USA, but dermatologists and primary care providers are routinely confronted with making the decision about when to recommend total body skin examinations and at what interval. The objectives of this paper are: to propose rational, risk-based, data-driven guidelines commensurate with the US Preventive Services Task Force screening guidelines for other disorders; to compare our proposed guidelines to recommendations made by other national and international organizations; and to review the US Preventive Services Task Force's 2016 Draft Recommendation Statement on skin cancer screening. PMID:28758010

Non-Equlibrium Driven Dynamics of Continuous Attractors in Place Cell Networks

NASA Astrophysics Data System (ADS)

Zhong, Weishun; Kim, Hyun Jin; Schwab, David; Murugan, Arvind

Attractors have found much use in neuroscience as a means of information processing and decision making. Examples include associative memory with point and continuous attractors, spatial navigation and planning using place cell networks, dynamic pattern recognition among others. The functional use of such attractors requires the action of spatially and temporally varying external driving signals and yet, most theoretical work on attractors has been in the limit of small or no drive. We take steps towards understanding the non-equilibrium driven dynamics of continuous attractors in place cell networks. We establish an `equivalence principle' that relates fluctuations under a time-dependent external force to equilibrium fluctuations in a `co-moving' frame with only static forces, much like in Newtonian physics. Consequently, we analytically derive a network's capacity to encode multiple attractors as a function of the driving signal size and rate of change.

Sustainability in Health care by Allocating Resources Effectively (SHARE) 2: identifying opportunities for disinvestment in a local healthcare setting.

PubMed

Harris, Claire; Allen, Kelly; King, Richard; Ramsey, Wayne; Kelly, Cate; Thiagarajan, Malar

2017-05-05

This is the second in a series of papers reporting a program of Sustainability in Health care by Allocating Resources Effectively (SHARE) in a local healthcare setting. Rising healthcare costs, continuing advances in health technologies and recognition of ineffective practices and systematic waste are driving disinvestment of health technologies and clinical practices that offer little or no benefit in order to maximise outcomes from existing resources. However there is little information to guide regional health services or individual facilities in how they might approach disinvestment locally. This paper outlines the investigation of potential settings and methods for decision-making about disinvestment in the context of an Australian health service. Methods include a literature review on the concepts and terminology relating to disinvestment, a survey of national and international researchers, and interviews and workshops with local informants. A conceptual framework was drafted and refined with stakeholder feedback. There is a lack of common terminology regarding definitions and concepts related to disinvestment and no guidance for an organisation-wide systematic approach to disinvestment in a local healthcare service. A summary of issues from the literature and respondents highlight the lack of theoretical knowledge and practical experience and provide a guide to the information required to develop future models or methods for disinvestment in the local context. A conceptual framework was developed. Three mechanisms that provide opportunities to introduce disinvestment decisions into health service systems and processes were identified. Presented in order of complexity, time to achieve outcomes and resources required they include 1) Explicit consideration of potential disinvestment in routine decision-making, 2) Proactive decision-making about disinvestment driven by available evidence from published research and local data, and 3) Specific exercises in priority setting and system redesign. This framework identifies potential opportunities to initiate disinvestment activities in a systematic integrated approach that can be applied across a whole organisation using transparent, evidence-based methods. Incorporating considerations for disinvestment into existing decision-making systems and processes might be achieved quickly with minimal cost; however establishment of new systems requires research into appropriate methods and provision of appropriate skills and resources to deliver them.

The Decision to Engage Cognitive Control Is Driven by Expected Reward-Value: Neural and Behavioral Evidence

PubMed Central

Dixon, Matthew L.; Christoff, Kalina

2012-01-01

Cognitive control is a fundamental skill reflecting the active use of task-rules to guide behavior and suppress inappropriate automatic responses. Prior work has traditionally used paradigms in which subjects are told when to engage cognitive control. Thus, surprisingly little is known about the factors that influence individuals' initial decision of whether or not to act in a reflective, rule-based manner. To examine this, we took three classic cognitive control tasks (Stroop, Wisconsin Card Sorting Task, Go/No-Go task) and created novel ‘free-choice’ versions in which human subjects were free to select an automatic, pre-potent action, or an action requiring rule-based cognitive control, and earned varying amounts of money based on their choices. Our findings demonstrated that subjects' decision to engage cognitive control was driven by an explicit representation of monetary rewards expected to be obtained from rule-use. Subjects rarely engaged cognitive control when the expected outcome was of equal or lesser value as compared to the value of the automatic response, but frequently engaged cognitive control when it was expected to yield a larger monetary outcome. Additionally, we exploited fMRI-adaptation to show that the lateral prefrontal cortex (LPFC) represents associations between rules and expected reward outcomes. Together, these findings suggest that individuals are more likely to act in a reflective, rule-based manner when they expect that it will result in a desired outcome. Thus, choosing to exert cognitive control is not simply a matter of reason and willpower, but rather, conforms to standard mechanisms of value-based decision making. Finally, in contrast to current models of LPFC function, our results suggest that the LPFC plays a direct role in representing motivational incentives. PMID:23284730

Improvements in agricultural water decision support using remote sensing

NASA Astrophysics Data System (ADS)

Marshall, M. T.

2012-12-01

Population driven water scarcity, aggravated by climate-driven evaporative demand in dry regions of the world, has the potential of transforming ecological and social systems to the point of armed conflict. Water shortages will be most severe in agricultural areas, as the priority shifts to urban and industrial use. In order to design, evaluate, and monitor appropriate mitigation strategies, predictive models must be developed that quantify exposure to water shortage. Remote sensing data has been used for more than three decades now to parametrize these models, because field measurements are costly and difficult in remote regions of the world. In the past decade, decision-makers for the first time can make accurate and near real-time evaluations of field conditions with the advent of hyper- spatial and spectral and coarse resolution continuous remote sensing data. Here, we summarize two projects representing diverse applications of remote sensing to improve agricultural water decision support. The first project employs MODIS (coarse resolution continuous data) to drive an evapotranspiration index, which is combined with the Standardized Precipitation Index driven by meteorological satellite data to improve famine early warning in Africa. The combined index is evaluated using district-level crop yield data from Kenya and Malawi and national-level crop yield data from the United Nations Food and Agriculture Organization. The second project utilizes hyper- spatial (GeoEye 1, Quickbird, IKONOS, and RapidEye) and spectral (Hyperion/ALI), as well as multi-spectral (Landsat ETM+, SPOT, and MODIS) data to develop biomass estimates for key crops (alfalfa, corn, cotton, and rice) in the Central Valley of California. Crop biomass is an important indicator of crop water productivity. The remote sensing data is combined using various data fusion techniques and evaluated with field data collected in the summer of 2012. We conclude with a brief discussion on implementation of these tools into two new decision support systems: FEWSNET Early Warning Explorer (http://earlywarning.usgs.gov/fews/ewxindex.php) and the NASA Terrestrial Observation and Prediction System (http://ecocast.arc.nasa.gov/) for the first and second project respectively.

Development of a Policy-Relevant Child Maltreatment Research Strategy

PubMed Central

MacMillan, Harriet L; Jamieson, Ellen; Wathen, C Nadine; Boyle, Michael H; Walsh, Christine A; Omura, John; Walker, Jason M; Lodenquai, Gregory

2007-01-01

Child maltreatment is associated with a huge burden of suffering, yet there are serious gaps in knowledge about its epidemiology and approaches to intervention. This article describes the development of a proposed national research framework in child maltreatment, as requested by the Department of Justice, Canada, based on (1) a review of the literature, (2) consultation with experts, and (3) application of evaluation criteria for considering research priorities. The article identifies gaps in knowledge about child maltreatment in Canada and proposes a research agenda to make evidence-based policy decisions more likely. Although this work was driven by gaps in Canada's knowledge about child maltreatment, the international scope of the review and consultation process could make the findings useful to broader research and policy audiences. PMID:17517119

Fleet DNA (Presentation)

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

Walkokwicz, K.; Duran, A.

2014-06-01

The Fleet DNA project objectives include capturing and quantifying drive cycle and technology variation for the multitude of medium- and heavy-duty vocations; providing a common data storage warehouse for medium- and heavy-duty vehicle fleet data across DOE activities and laboratories; and integrating existing DOE tools, models, and analyses to provide data-driven decision making capabilities. Fleet DNA advantages include: for Government - providing in-use data for standard drive cycle development, R&D, tech targets, and rule making; for OEMs - real-world usage datasets provide concrete examples of customer use profiles; for fleets - vocational datasets help illustrate how to maximize return onmore » technology investments; for Funding Agencies - ways are revealed to optimize the impact of financial incentive offers; and for researchers -a data source is provided for modeling and simulation.« less

Performance enhancement using a balanced scorecard in a Patient-centered Medical Home.

PubMed

Fields, Scott A; Cohen, Deborah

2011-01-01

Oregon Health & Science University Family Medicine implemented a balanced scorecard within our clinics that embraces the inherent tensions between care quality, financial productivity, and operational efficiency. This data-driven performance improvement process involved: (1) consensus-building around specific indicators to be measured, (2) developing and refining the balanced scorecard, and (3) using the balanced scorecard in the quality improvement process. Developing and implementing the balanced scorecard stimulated an important culture shift among clinics; practice members now actively use data to recognize successes, understand emerging problems, and make changes in response to these problems. Our experience shows how Patient-centered Medical Homes can be enhanced through use of information technology and evidence-based tools that support improved decision making and performance and help practices develop into learning organizations.

Improving decision making in crisis.

PubMed

Higgins, Guy; Freedman, Jennifer

2013-01-01

The most critical activity during emergencies or crises is making decisions about what to do next. This paper provides insights into the challenges that people face in making decisions at any time, but particularly during emergencies and crises. It also introduces the reader to the concept of different sense-making/decision-making domains, the human behaviours that can adversely affect decision making - decision derailers - and ways in which emergency responders can leverage this knowledge to make better decisions. While the literature on decision making is extensive, this paper is focused on those aspects that apply particularly to decision making in emergencies or times of crisis.

An ontology-based telemedicine tasks management system architecture.

PubMed

Nageba, Ebrahim; Fayn, Jocelyne; Rubel, Paul

2008-01-01

The recent developments in ambient intelligence and ubiquitous computing offer new opportunities for the design of advanced Telemedicine systems providing high quality services, anywhere, anytime. In this paper we present an approach for building an ontology-based task-driven telemedicine system. The architecture is composed of a task management server, a communication server and a knowledge base for enabling decision makings taking account of different telemedical concepts such as actors, resources, services and the Electronic Health Record. The final objective is to provide an intelligent management of the different types of available human, material and communication resources.

Reinforcement Learning and Savings Behavior.

PubMed

Choi, James J; Laibson, David; Madrian, Brigitte C; Metrick, Andrew

2009-12-01

We show that individual investors over-extrapolate from their personal experience when making savings decisions. Investors who experience particularly rewarding outcomes from saving in their 401(k)-a high average and/or low variance return-increase their 401(k) savings rate more than investors who have less rewarding experiences with saving. This finding is not driven by aggregate time-series shocks, income effects, rational learning about investing skill, investor fixed effects, or time-varying investor-level heterogeneity that is correlated with portfolio allocations to stock, bond, and cash asset classes. We discuss implications for the equity premium puzzle and interventions aimed at improving household financial outcomes.

A time for change: for the road to excellence for health care professionals.

PubMed

Nichols, D H

2001-01-01

This article addresses the changes affecting all of health care. Change should first be driven by data--data are what will be used to make clinical and business decisions that will result in better quality care. Employees should be held accountable for results, and celebrations should be provided for these changes. Customers have needs and goals that must be met, and if we do not meet the needs, our competition will. Management must understand the principles of quality and must encourage growth in employees. To bring change to your health care organization, you must embrace and encourage change.