This thesis presents the development and evaluation of a computerized physician-parent decision support tool for a neonatal intensive care unit (NICU), known as Physician and Parent Decision Support (PPADS). The NICU is a specialized hospital unit that treats very-ill neonates. Many difficult care decisions are made daily for this vulnerable population. The PPADS tool aims to augment current NICU decision-making by helping parents and physicians make more informed decisions, improving physician-parent communication, increasing parent decision-making satisfaction, decreasing conflict, and increasing decision efficiency. The development of the PPADS tool followed a five-step methodology: assessing the clinical environment, establishing the design criteria, developing the system design, implementing the system, and performing usability testing. Usability testing of the PPADS tool was performed on neonatologists and on parents of neonates who have graduated (survived) from a tertiary level NICU. The usability testing demonstrated the usefulness and ease of use of the tool.

Thesis (PhD)--Macquarie University (Macquarie Graduate School of Management), 2006. / Bibliography: leaves 243-283. / Introduction -- Literature on entrepreneurship, self-regulation and decision making -- Literature on decision making by entrepreneurs -- Methodology -- Results -- Discussion of empirical findings. / This thesis explores the role of self-regulation in decision making by entrepreneurs. It builds on prior research which has focussed on the cognitive aspects of key decisions made by entrepreneurs. Among these key decisions are career choice, opportunity evaluation and opportunity exploitation. One area of this ongoing reearch program is the exploration of social congition and self-regulatory factors in decision making. Hower, this area is still in its infancy, significant gaps remain and there are no coherent theories about such phenomena in the field of entrepreneurship. The purpose of this thesis is to contribute to theory development on these topics. / Mode of access: World Wide Web. / viii, 283 leaves ill

Thesis (M. Div.)--Emmanuel School of Religion, 2006. / Vita. Includes bibliographical references (leaves 68-72).

Humans can often report a subjective sense of confidence in a decision before knowing its outcome. Such confidence judgements are positively correlated to accuracy in perceptual and memory tasks, but the strength of this relationship (known as metacognitive accuracy) differs across people and contexts. Computationally, confidence judgements are believed to relate to the strength of evidence favouring each option, but it has been suggested that confidence also captures information from other sources, such as response time. This thesis explores the pragmatics of confidence: what factors influence confidence judgements, how accurate confidence judgements are, and how they might influence future behaviour. Our knowledge of the antecedents of confidence is extended by this work in two ways, by introducing novel predictors of confidence and by increasing our understanding of well-known ones. I find that bilinguals have worse metacognitive accuracy than monolinguals. This bilingual deficiency in metacognitive accuracy cannot be explained by response time and stimulus strength, suggesting that there is at least one important predictor of confidence that remains unaccounted for. I introduce such a predictor in a new eye tracking correlate of confidence: Gaze-shift-frequency, the number of saccades between options, negatively predicts subsequent confidence in perceptual and value-based decisions. In the value domain, the total value of the options is shown to positively relate to confidence despite being negatively related to accuracy, the first such dissociation to be recorded, as far as I am aware. The dissertation extends our understanding of response time as a predictor of confidence by showing that it influences confidence more for judgements that are made after a choice, relative to those made simultaneously with the choice. This differential influence of response time explains the higher metacognitive accuracy of sequential confidence reports. I explore the consequences of confidence judgements in the context of value-based choice. Lower levels of confidence are associated with changes of mind when the same options recur in subsequent trials. To test whether these changes of mind are rational, I approximate choice accuracy in the value domain. I propose a novel method based on the transitivity of the full choice set, so that choices that violate the most transitive ordering of the items can be treated as errors. I find that participants who were more metacognitively accurate showed a decrease in transitivity violations over time. These results extend prior work linking confidence judgements to error correction in the perceptual domain.

Processing decision information is a constitutive part in a number of applicationsin Computer Science fields. In general, decision information can be used to deduce the relationship between a certain context and a certain decision. Decision information is represented by a decision model that captures this information. Frequently used examples of decision models are decision tables and decision trees. The choice of an appropriate decision model has an impact on application performance in terms of memory consumption and execution time. High memory expenses can possibly occur due to redundancy in a decision model; and high execution time is often a consequence of an unsuitable decision model. Applications in different domains try to overcome these problems by introducing new data structures or algorithms for implementing decision models. These solutions are usually domain-specificand hard to transfer from one domain to another. Different application domains of Computer Science often process decision information in a similar way and, hence, have similar problems. We should thus be able to present a unifying approach that can be applicable in all application domains for capturing and manipulating decision information. Therefore, the goal of this thesis is (i) to suggest a general structure(Decision Algebra) which provides a common theoretical framework that captures decision information and defines operations (signatures) for storing, accessing, merging, approximating, and manipulating such information along with some general algebraic laws regardless of the used implementation. Our Decision Algebra allows defining different construction strategiesfor decision models and data structures that capture decision information as implementation variants, and it simplifies experimental comparisons between them. Additionally, this thesis presents (ii) an implementation of Decision Algebra capturing the information in a non-redundant way and performing the operations efficiently. In fact, we show that existing decision models that originated in the field of Data Mining and Machine Learning and variants thereof as exploited in special algorithms can be understood as alternative implementation variants of the Decision Algebra by varying the implementations of the Decision Algebra operations. Hence, this work (iii) will contribute to a classification of existing technology for processing decision information in different application domains of Computer Science. / <p>A thesis for the Degree of Licentiate of Philosophy in Computer Science.</p>

FSCN-rapport; R-02-33

Abstract Intelligent field technology is being developed for the management of industrial processes, but its development and diffusion have met with problems. This research looks at the problem area from the perspective of industrial decision-makers and end users. The lowest level of process management consists of various electrical, pneumatic and hydraulic devices, using analog and digital signals. In this research the term 'field technology' refers to instrumentation and electrical devices, the communication between them, alarm and registration devices, programs, functions and process management methods. Important concepts in this connection are distribution, availability performance, usability, feasibility and degree of automation. Decision-making and hermeneutical methodologies have been used as research strategies. The leading idea is to provide support to industrial decision-makers and end users involved in the design and planning of processes, field technology and management systems. The research strategy is applied in all parts of the research: methods, historical review, decision-making support model and criteria, and when studying the diffusion of innovations. The objective is to experimentally verify the decision-making models. This was accomplished by means of multiple-choice questionnaires, example and case process surveys, and by collecting information on intelligent field technology. The target group of the research consisted of 50 decision-makers and end users from 20 factories, and the response percentage varied from 28% to 47%. The study of the example and case processes contains contributions from 13 key persons from the factories. Field technology knowledge has been obtained from a number of experts and sources. The results have been employed to verify the current multivariable decision-making model and its technological and economic subcriteria and decision-making criteria (1), as well as the expanded multivariable decision-making model based on the features of intelligent field technology (2). The most significant parameters of the example processes are described (3). The typical characteristics, operations, input and output materials of the case processes and their parameters are examined and assessed (4). A proposal for intelligent field technology solutions will also be made (5). The decision-making support model is an excellent tool in situations involving technological changes. The current set of decision-making criteria will have to change and expand due to the concepts, operations and changes introduced by new, intelligent field technology. Changes will occur in the communication protocol interfaces, in the data processing of field devices, in diagnostic operations and operation management. Suitable decision-making tools include development and decision databases, lifelong learning, human and electronic information networks, the decision-making support model, and benchmarking. In the future, investments will focus on the acquisition and maintenance of field technology. Intelligent field technology is more expensive, and thus automation design requires more economic and human resources during the diffusion phase; its economic benefits will become more apparent when it gains more ground and the users' skills and expertise increase. Industrial enterprises must actively seek to promote the diffusion of innovations. The current research has also brought up numerous topics that would merit further research.

Decision makers have long relied on experts to inform their decision making. Expert judgment analysis is a way to elicit and combine the opinions of a group of experts to facilitate decision making. The use of expert judgment is most appropriate when there is a lack of data for obtaining reasonable statistical results. The experts are asked for advice by one or more decision makers who face a specific real decision problem. The decision makers are outside the group of experts and are jointly responsible and accountable for the decision and committed to finding solutions that everyone can live with. The emphasis is on the decision makers learning from the experts. The focus of this thesis is an overview and comparison of the various elicitation and combination methods available. These include the traditional committee method, the Delphi method, the paired comparisons method, the negative exponential model, Cooke’s classical model, the histogram technique, using the Dirichlet distribution in the case of a set of uncertain proportions which must sum to one, and the employment of overfitting. The supra Bayes approach, the determination of weights for the experts, and combining the opinions of experts where each opinion is associated with a confidence level that represents the expert’s conviction of his own judgment are also considered.

This thesis presents the development and evaluation of a computerized physician-parent decision support tool for a neonatal intensive care unit (NICU), known as Physician and Parent Decision Support (PPADS). The NICU is a specialized hospital unit that treats very-ill neonates. Many difficult care decisions are made daily for this vulnerable population. The PPADS tool aims to augment current NICU decision-making by helping parents and physicians make more informed decisions, improving physician-parent communication, increasing parent decision-making satisfaction, decreasing conflict, and increasing decision efficiency. The development of the PPADS tool followed a five-step methodology: assessing the clinical environment, establishing the design criteria, developing the system design, implementing the system, and performing usability testing. Usability testing of the PPADS tool was performed on neonatologists and on parents of neonates who have graduated (survived) from a tertiary level NICU. The usability testing demonstrated the usefulness and ease of use of the tool.

Ph.D. (Business Management) / Please refer to full text to view abstract