Objective: To explore the decision making approaches used by nurses who chose to work in critical care and factors influencing the process of decision making. Design and methods Qualitative descriptive methods using semi-structured interviews with nurses who had chosen to work in critical care within the past year. Results Ten nurses weighed staying in their current positions with moving to critical care. Two nurses considered two or more specialty units. The nurses used rational-intuitive and satisficing decision making approaches in making their employment decision. Limited knowledge and unrealistic expectations of work life in critical care, pressure from others, and inadequate professional support made nurses’ employment decisions more difficult. Social support, personal values for growth and learning, and paid educational incentives within employment offers facilitated their employment decisions. Conclusions Several factors negatively influenced nurses’ decision making approaches to making an employment decision. Findings revealed the need for decision support interventions focused on making employment choices for nurses.

This study is concerned with understanding decision-making in relation to out-of-authority educational placements for pupils with an Autistic Spectrum Condition (ASC) in one Local Authority (LA). The aims of this research were twofold. The first was to explore what factors have the greatest impact on the decision to educate pupils with an ASC outside the local authority. The second was to explore the perceptions of key informants about the process for deciding those placements. The study involved examining 24 pupil cases where out-of-authority ASC placements had been agreed and interviews with case-informants contributing to those placement decisions in order to analyse their beliefs and understandings about the processes of decision-making. The literature review highlights the limited research with regard to decision-making about pupils with Special Educational Needs (SEN) and draws examples from medical decision-making frameworks. Data analysis showed that two factors, complexity and range of pupil need and lack of LA provision to match the needs identified had the greatest influence on the decision to educate pupils outside the local authority. The response of the LA’s own schools, professionals and parents to those presenting needs as well as the consequent impact on the child/young person and others were recognised secondary factors. Case-informants offered a strong impression that for the majority of these pupils successful inclusion in their own LA would require increased and more integrated services in order to meet their identified needs. Data from the qualitative interviews provides a sense of the range of informants’ experiences relating to decision-making processes and the factors determining those perceptions. These related to whether the processes had been experienced as planned, were evidenced-based, child-focused and involved effective working with parents and other agencies. The findings, in part, reflect government concerns about the current statutory SEN framework and the case for change as made in the recent Green Paper (DfE, 2011). At a local level informants identified the need for a more explicit model of decision-making, ethically grounded with an emphasis for decision-making to be based on the holistic needs of the child and viewed that this would be better facilitated by having improved joint-working between services and stronger partnership engagement between the LA and parents/carers. Clinical professional-patient shared decision-making is discussed as a potential model which might be usefully applied to better understand and develop current SEN decision making.

Many analytics problems in Operations Research and the Management Sciences can be framed as decision-making problems containing uncertain input parameters to be estimated from data. For example, inventory optimization problems often require forecasts of future demand, and product recommendation systems (e.g., movies, sporting goods) depend on models for predicting customer responses to the feasible recommendations. Therefore, a question central to many analytics problems is how to optimally build models from data which estimate the uncertain inputs for the decision problems of interest. We argue that most common approaches for this task either (a) focus on the wrong objectives in training the models for the decision problem, or (b) focus on the right objectives but only study how to do so with prohibitively simple machine learning models (e.g. linear and logistic regression). In this work, we study how to train decision tree models for predicting uncertain parameters for analytical decision-making problems. Unlike other machine learning models such as linear and logistic regression, decision trees are both nonparameteric and interpretable, allowing them the capability of modeling highly complex relationships between data and predictions while also being easily visualized and interpreted. We propose tractable algorithms for decision tree training in the context of three problem domains relevant to Operations Research. First, we study how to train decision trees for delivering real-time personalized recommendations of products in settings where little prior data is available for training purposes. This problem is known in the literature as the contextual bandit problem and requires careful navigation of the so-called "exploration-exploitation trade-off" in utilizing the decision tree models. Second, we propose a new framework which we call Market Segmentation Trees (MSTs) for training decision tree models for the purposes of market segmentation and personalization. We explore several applications of MSTs relevant to personalized advertising, including recommending hotels to Expedia users as a function of their search queries and segmenting ad auctions according to the distribution of bids that they receive. Finally, we propose a general framework for training decision tree models for uncertain optimization problems which we call "SPO Trees" (SPOTs). In contrast to the typical objective of maximizing predictive accuracy, the SPOT framework trains decision trees to maximize the quality of the solutions found in the uncertain optimization problem, therefore yielding better decisions in several analytics problems of interest.

Purpose: To explore the decision-making experiences of and the supports provided to the parents of children with life-limiting conditions. Qualitative Study: A qualitative interpretive description study guided by the Ottawa Decision Support Framework was conducted. Interviews with parents and healthcare professionals revealed that parents made difficult healthcare decisions for their child and were prone to experiencing decisional conflict. Participants described a need for interprofessional support, guided decision support, and a preference for formal and informal support networks. Scoping Review: A scoping review was conducted. The three eligible studies revealed that parents require early and timely decision support provided by an interprofessional team of healthcare professionals and aided by a structured decision support intervention. Conclusions: Decisions made by parents of children with life-limiting conditions are complex. Healthcare professionals are required to facilitate appropriate decision support interventions for parents including a parent based support network.

A thesis submitted in fulfilment for the degree Doctor of Education in the Department of Educational Psychology and Special Education in the Faculty of Education at the University of Zululand, 2004. / This study examined the practice of participative decision making (POM) at South African universities. The first aim was to investigate the extent to which these institutions practice participative decision making. The second aim was to establish whether certain managers' characteristics influence the practice of participative decision making. The third aim sought to determine whether there is any difference among institutions in the practice of participative decision making. Finally, the fourth aim was to determine whether there is any association among ranks assigned by adjudicators/respondents to six participative decision making (POM) steps. To this end a research instrument called a questionnaire, was designed and used to achieve these aims. Moreover, this research instrument, after construction by the researcher, was validated by means of factor analysis (FA). The research instrument was first administered as a pilot sample of one hundred and twenty managers at the University of Zululand's main and Ourban-Umlazi Campuses. The final instrument was administered to a sample of managers at universities in the whole country. Two hundred and twenty-six (226) managers completed and returned iv questionnaires. The two hundred and twenty-six questionnaires were to be correctly analyzed. Each of the aims was tied to a null hypothesis and an alternative one. All in all, eight hypotheses were formulated. The Chi-square (x2) one sample test was employed to test for managers' perceptions about participative decision making (PDM). The outcome was that managers hold negative perceptions about participative decision making. This leads to the conclusion that university managers do not practice participative decision making (PDM). The difference between those who hold positive perception (52.20/0) and negative perception (47.480/0) were not statistically significant. The second hypothesis which addressed the second aim was tested by means of a Chi-square one sample test as well as in all variables of this aim. It was found that gender has a positive relationship with regards to decision making, as perceived by the managers. So, gender was found to be statistically significant. However, the rest, such as, age, experience, religion, rank, and type of institution, were perceived by managers to have no relationship with the practice of participative decision making (POM). v / University of Zululand

Decision making and decision changes were studied in late adolescents regarding post-high school choices. A branching questionnaire was constructed and mailed to 1239 late adolescents who during the preceding year had indicated on the American College Test (ACT) that Utah State University (USU) was their first choice for college attendance, but whose names did not appear on the USU Registrar's list of enrolled freshmen, Fall 1969. 62% of the questionnaires were returned. Questions were asked concerning post-high school decision making and decision change: What alternatives to attendance at USU were chosen? Was the alternative chosen college-related or was the change made to a non-college alternative? Who most influenced the decision to change alternatives? Was the change of decision permanent or was future attendance at USU planned? What factors were most important and least important in making the decision to change to a college-related alternative? What factors were most important and least important in making the decision to change to a non-college alternative? Were future plans, following the present course of action, decided or undecided? What effect did location have on college decision plans? To what extent were the college decision changes rational? It was found that the 768 late adolescents who changed their decision to attend USU in the fall of 1969, chose a variety of alternative courses of action. Nearly half of these Ss chose to attend another college or university, while another one fourth chose to enroll at USU at a later date. Thus, nearly three fourths of the Ss remained within the domain of their original decision, that being to attend college. The Ss most often saw themselves as being the primary influencers of their decisions, with friends and fathers being less frequently mentioned influencers. Religious advisors, recruiters, and employers were least frequent primary influencers. It was seen that nearly 4d% of the decision changes not to enroll at USU were permanent, while another approximate 40% were temporary -- the Ss having already enrolled or planning to enroll at USU in the future. Expenses, location, and financial aid were the leading factors determining college choice, and housing, social opportunities, and recruitment were least important factors. The most important factors leading to the selection of non-college alternatives were basic indecision and doubt about college attendance, and financial and practical considerations. As to continued future planning in the development of these late adolescents, it was found that approximately 70% did have definite plans for the future, whereas 30% were undecided or gave no response. Two thirds of the Ss who changed colleges chose to attend another college located within the state of Utah, with the remaining choices covering a wide geographical area. Considerable variation in the degree of rationality in these decisions was implied by the factors that did or did not influence their decisions. The model of Koontz and O'Donnell for rational decision making was applied, but adult models may not be appropriate for the late adolescent stage of development. The results were discussed in relation to the literature reviewed and recommendations were made for future research.

The purpose of this study was to validate the problem behavior evaluation section of an expert system computer program, Class.BD. Class.BD was developed to assist special education personnel 1n determining whether students qualify for special education services as behaviorally disordered/severely emotionally disturbed students. The subjects were six Utah who regularly individuals from 1) work with the state of behaviorally disordered/severely emotionally disturbed students and 2) participate in multidisciplinary assessment teams. Three of the subjects were special educators, and three were school psychologists. Specifically, this study investigated the impact of five behavioral factors on the subjects' ratings of the seriousness of problem behaviors. The five behavioral factors were 1) the severity or nature of the problem behavior, 2) the frequency with which the problem behavior occurs, 3) the duration over which the problem behavior has been occurring, 4) the generality of the problem behavior or the number of school environments the behavior occurs in, and 5) the percentage of the student's peers who engage in the same behavior. For each behavioral factor, three levels of that factor were determined: high, moderate, and low. Problem behavior descriptions were which presented developed by the researcher, each of the five behavioral factors at a predetermined combination of levels. Of 65 problem behavior descriptions, 33 described externalized problem behaviors and 32 described internalized problem behaviors. Subjects were asked to rate the seriousness of each problem behavior description on an 11 point scale, where 1=mild and 11=severe. The results showed high levels of agreement among subjects on ratings of seriousness of problem behaviors. There was also high agreement between the subjects' ratings system. and ratings generated by the Class.BD expert. Thus, Class.BD was validated. Further, the subjects gave highly similar ratings to descriptions of externalized and internalized problem behaviors. The results also indicated that the severity of the problem behaviors had the most impact on subjects' ratings. Subjects discriminated three levels of severity but only two levels of frequency, duration, generality, and percentage of peers. Finally, the results provided support for the use of analysis of variance as a viable method of knowledge engineering, i.e., extracting information about how experts make decisions. Its superiority over traditional interview methods is discussed.

This study attempted to replicate and extend the study of Doherty, Mynatt, Tweney, and Schiavo (1979), which introduced what is here called the Bayesian conditionals selection paradigm. The present study used this paradigm (and a script similar to that used by Doherty et al.) to explore confirmation bias and related errors that can appear in both search and integration in probability revision. Despite selection differences and weak manipulations, this study provided information relevant to four important questions. First, by asking participants to estimate the values of the conditional probabilities they did not learn, this study was able to examine the use of "intuitive conditionals". This study found evidence that participants used intuitive conditionals and that their intuitive conditionals were affected by the size of the actual conditionals. Second, by examining both phases in the same study, this study became the first to look for inter-phase interactions. A strong correlation was found between the use of focal search strategies and focal integration strategies (r=.81, p

Subjective information is a valuable resource; however, decisionmakers often ignore it because of difficulties in eliciting it from assessors. This thesis is on Bayesian inquiry and it presents an approach to eliciting subjective information from assessors. Based on the concepts of cascaded inference and Bayesian statistics, the approach is designed to reveal to the decision-maker the way in which the assessor considers his options and the reasons he has for selecting particular alternatives. Unlike previous works on cascaded inferences, the approach here focuses on incoherency. Specifically, it employs the use of additional information to revise and check the estimates. The reassessment may be done directly or indirectly. The indirect procedure uses a second order probability or type II distribution. An algorithm utilizing this approach is also presented. The methodology is applicable to any number of assessors. Procedures for aggregating and deriving surrogate distributions are also proposed.

京都大学 / 0048 / 新制・課程博士 / 博士(医学) / 甲第21631号 / 医博第4437号 / 新制||医||1034(附属図書館) / 京都大学大学院医学研究科医学専攻 / (主査)教授 川上 浩司, 教授 松田 文彦, 教授 黒田 知宏 / 学位規則第4条第1項該当 / Doctor of Medical Science / Kyoto University / DFAM