Browsing by Subject "decision making"
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Item Charge Nurse Expertise: Implications for Decision Support of the Nurse-Patient Assignment Process(2019-05) Meyers, ElizabethEach day, across thousands of medical-surgical inpatient nursing units, charge nurses make decisions about which nurse will care for each patient. Recent attempts have been made to introduce health information technology (HIT) solutions to automate the nurse-patient assignment process. This research investigated charge nurse decision making during the nurse-patient assignment process as an exemplar of the larger question: How can we leverage information technology to improve decision making in healthcare, while respecting individual clinician expertise and the unique context of individualized patient care? Four primary questions were used to guide research of the process, decision factors, goals and context of nurse-patient assignments. A mixed-methods approach of qualitative interviews (N = 11) and quantitative surveys (N = 135) was used. Findings related to the charge nurse decision making process indicate that measurable, nurse-sensitive indicators of patient outcomes have not yet been standardized for nurse-patient assignments. HIT solutions and quality improvement efforts should define, collect and analyze measurable outcome criteria prior to attempting to improve or augment existing nurse-patient assignment practices to prevent unintended consequences. When clear outcome measurements have been identified, informatics researchers and professionals should investigate the ability of machine learning to recognize goal priorities and factor weighting from patient, nurse and environmental factors within existing HIT solutions. Until that time, HIT solutions augmenting the nurse-patient assignment process should be designed with flexible configurations, to enable goals, decision factors and factor weights can be varied by hospital, unit, charge nurse and shift, in order to best meet the needs of charge nurses.Item Facilitation Resources: Volume 5. Making Group Decisions.(St. Paul, MN: University of Minnesota Extension Service, 2001) Anderson, Marian; Anderson, Sharon Roe; Laeger-Hagemeister, Mary; Scheffert, Donna Rae; Steinberg, RogerFacilitation Resources Volume 5 of 8. This volume focuses on consensus building, determining support, and decision-making strategies and models.Item Information Processing in the Orbitofrontal Cortex and the Ventral Striatum in Rats Performing an Economic Decision-Making Task(2015-08) Stott, JeffreyThe orbitofrontal cortex (OFC) and ventral striatum (vStr) are key brain structures that represent information about value during decision-making tasks. Despite their very different anatomical properties, numerous studies have found similar patterns of value-related signaling in these structures. In particular, both structures are intimately involved in delay-discounting tasks, which involve a tradeoff between reward magnitude and delay to reward. However, the overlapping activity profiles of these brain regions makes it difficult to tease apart their specific contributions to delay-discounting behavior, and to economic decision-making more generally. In order to better understand the contributions of these two regions to value-based choice, we made simultaneous recordings in the OFC and vStr in rats performing a spatial variant of a traditional delay-discounting task. This allowed us to compare OFC and vStr activity directly in the same subjects while they engaged in a prototypical economic decision-making task, and additionally it allowed us to leverage the tools of spatial decoding analysis to measure non-local reward signaling. Chapter 1 provides an introduction to current theories of OFC and vStr function within the decision-making literature, in particular contrasting the concepts of neuroeconomics with the multiple decision-making systems framework. Chapter 2 describes the methods used in this thesis, including the design of the spatial delay-discounting task and the analysis of the neural data. Chapter 3 presents the results of single-unit and Bayesian decoding analyses from this dataset. We found that activity in the OFC and vStr was quite similar at the single-unit level, and inconsistent with the neuroeconomic account of value signaling in a common currency. Instead, when we looked specifically at moments of deliberative decision-making (as emphasized by the multiple systems account), we found important differences between the OFC and vStr. Both the OFC and the vStr showed covert reward signaling during deliberative, vicarious trial-and-error (VTE) behaviors. But vStr signals emerged earlier, before the moment of choice, while covert reward coding in the OFC appeared after the rats had committed to their decision. These analyses were extended to the level of local field potentials (LFPs), recorded from the same dataset. Local field potentials are a useful tool for studying local processing and interactions between brain regions. Chapter 4 describes the LFP results. Important among these was the finding that the vStr led the OFC at the LFP level (again showing temporal precedence), and furthermore, that the vStr was a stronger driver of OFC activity than vice versa, particularly during VTE. The implications of these results, along with those from the single-unit and Bayesian decoding analyses, are discussed in Chapter 5. Emphasis is placed on our emerging understanding of the role of the vStr in flexible behavior, and how the OFC and the vStr might cooperate to influence value-based choice.Item Item Northern Minnesota Logger Conservation Action: Social, Moral, and Business Norms and Profitability(2015-05) Fellows, SarahThis study explores the drivers of decision making and conservation action among northern Minnesota loggers, and in particular the relationship between perceived norms and profitability. Twenty interviews were conducted with loggers in northern Minnesota and analyzed using an adapted grounded theory approach. Study findings reveal that personal, business and social norms are powerful determinants of logger decision making. However, recent strains on profitability, as well as a perceived disconnect within the supply chain (i.e., wood suppliers, loggers and mills) constrain conservation action. This study adds to the growing body of research on conservation behaviors (e.g., recycling, energy consumption, and farming) of resources users through an inductive investigation of the conservation decisions of loggers, a relatively understudied social group. A better understanding of logger decision making will enable forest managers and policy makers to better evaluate and enhance conservation programming, timber sale policies, and forest management guidelines based on the experiences and perceptions of loggers.Item Sex differences and flexible decision making behavior in a mouse model of 16p11.2 hemideletion(2023) Merfeld, MadisonCompared with girls and women, boys and men have a higher rate of diagnosis and/or a greater level of impairment associated with neurodevelopmental conditions such as autism spectrum disorders and attention deficit hyperactivity disorder (ADHD). We know little about how sex mechanisms influence the impact of diagnosis-associated gene variants; one gene variant strongly associated with neurodevelopmental disorders is 16p11.2 hemideletion. Boys with 16p11.2 hemideletion have been repeatedly found to have more neurodevelopmental diagnoses than girls. The 16p11.2 region is highly syntenic across mammals, and mouse models of 16p11.2 hemideletion (abbreviated as 16p del) also show sex-biased impacts on flexible action selection. In a restless two-armed bandit decision making, I found that 16p del mice have sex-biased behavioral changes in the domain of flexible action selection.Item Time allocation and meta-cognition: A computational approach towards the organization of motivation(2019-01) Mussack, DominicHow do people allocate time and effort across tasks? This dissertation takes a computational psychology perspective, and puts forward the theory that motivation solves the meta-cognitive problem of allocating resources to different tasks by computing task priority. Motivation research has previously distinguished between two dissociable components of motivation: directing and energizing. These two components refer to different resources that must be allocated: time and effort. We explore the way humans allocate effort by taking advantage of simple decision making tasks and manipulating either task or background information. We develop a novel method that allows researchers to integrate an array of biometrics that capture how decision processes are modulated. We then extend work from optimal foraging theory to account for human tasks in order to analyze how humans allocate time. We derive various results that match time use behavior across domains. Finally, we apply the structural implications of this theory to make predictions in large scale time use data sets. Humans must often schedule mutually exclusive goals to fulfill mutually exclusive needs, which requires us to allocate time across tasks via a priority computation. Re-framing motivation from a resource allocation perspective, and highlighting the unique problem of time allocation, has implications across human decision making behavior, and we demonstrate its relevance in multiple domains.