Personal autonomy in discharge planning decision -making in mentally alert hospitalized elderly individuals: The social workers' perspective

This study was conducted to understand (a) hospital social workers' perspectives about patients' personal autonomy and self-determination, (b) their experiences, and (c) their beliefs and behaviors. The study used the maximum variation sampling strategy to select hospitals and hospital social work respondents. Individual interviews were conducted with 31 medical/surgical and mental health hospital social workers who worked in 13 hospitals. The data suggest the following four points. First, the hospital setting as an outside influence as it relates to illness and safety, and its four categories, mentally alert patients, family members, health care professionals, and social work respondents, seems to enhance or diminish patients' autonomy in discharge planning decision making. Second, respondents report they believe patients must be safe both inside and outside the hospital. In theory, respondents support autonomy and self-determination, respect patients' wishes, and believe patients are the decision makers. However, in practice, respondents respect autonomy and self-determination to a point. Third, a model, The Patient's Decision in Discharge Planning: A Continuum, is presented where a safe discharge plan is at one end of a continuum, while an unsafe discharge plan is at the other end. Respondents respect personal autonomy and the patient's self-determination to a point. This point is likely to be located in a gray area where the patient's decision crosses from one end of the continuum to the other. When patients decide on an unsafe discharge plan, workers' interventions range from autonomy to paternalism. And fourth, the hospital setting as an outside influence may not offer the best opportunity for patients to make decisions (a) because of beliefs family members and health care professionals hold about the value of patient self-determination, and (b) because patients may not feel free to make decisions in an environment where they are surrounded by family members, health care professionals, and social work respondents who have power and who think they know best. Workers need to continue to educate elderly patients about their right to self-determination in the hospital setting. ^

Information systems to support decision-making in *construction owner organizations: A data warehousing approach

Construction organizations typically deal with large volumes of project data containing valuable information. It is found that these organizations do not use these data effectively for planning and decision-making. There are two reasons. First, the information systems in construction organizations are designed to support day-to-day construction operations. The data stored in these systems are often non-validated, non-integrated and are available in a format that makes it difficult for decision makers to use in order to make timely decisions. Second, the organizational structure and the IT infrastructure are often not compatible with the information systems thereby resulting in higher operational costs and lower productivity. These two issues have been investigated in this research with the objective of developing systems that are structured for effective decision-making. ^ A framework was developed to guide storage and retrieval of validated and integrated data for timely decision-making and to enable construction organizations to redesign their organizational structure and IT infrastructure matched with information system capabilities. The research was focused on construction owner organizations that were continuously involved in multiple construction projects. Action research and Data warehousing techniques were used to develop the framework. ^ One hundred and sixty-three construction owner organizations were surveyed in order to assess their data needs, data management practices and extent of use of information systems in planning and decision-making. For in-depth analysis, Miami-Dade Transit (MDT) was selected which is in-charge of all transportation-related construction projects in the Miami-Dade county. A functional model and a prototype system were developed to test the framework. The results revealed significant improvements in data management and decision-support operations that were examined through various qualitative (ease in data access, data quality, response time, productivity improvement, etc.) and quantitative (time savings and operational cost savings) measures. The research results were first validated by MDT and then by a representative group of twenty construction owner organizations involved in various types of construction projects. ^

Essays in Environmental Economic Valuation and Decision Making in the Presence of an Environmental Disaster

The first essay developed a respondent model of Bayesian updating for a double-bound dichotomous choice (DB-DC) contingent valuation methodology. I demonstrated by way of data simulations that current DB-DC identifications of true willingness-to-pay (WTP) may often fail given this respondent Bayesian updating context. Further simulations demonstrated that a simple extension of current DB-DC identifications derived explicitly from the Bayesian updating behavioral model can correct for much of the WTP bias. Additional results provided caution to viewing respondents as acting strategically toward the second bid. Finally, an empirical application confirmed the simulation outcomes. The second essay applied a hedonic property value model to a unique water quality (WQ) dataset for a year-round, urban, and coastal housing market in South Florida, and found evidence that various WQ measures affect waterfront housing prices in this setting. However, the results indicated that this relationship is not consistent across any of the six particular WQ variables used, and is furthermore dependent upon the specific descriptive statistic employed to represent the WQ measure in the empirical analysis. These results continue to underscore the need to better understand both the WQ measure and its statistical form homebuyers use in making their purchase decision. The third essay addressed a limitation to existing hurricane evacuation modeling aspects by developing a dynamic model of hurricane evacuation behavior. A household’s evacuation decision was framed as an optimal stopping problem where every potential evacuation time period prior to the actual hurricane landfall, the household’s optimal choice is to either evacuate, or to wait one more time period for a revised hurricane forecast. A hypothetical two-period model of evacuation and a realistic multi-period model of evacuation that incorporates actual forecast and evacuation cost data for my designated Gulf of Mexico region were developed for the dynamic analysis. Results from the multi-period model were calibrated with existing evacuation timing data from a number of hurricanes. Given the calibrated dynamic framework, a number of policy questions that plausibly affect the timing of household evacuations were analyzed, and a deeper understanding of existing empirical outcomes in regard to the timing of the evacuation decision was achieved.

Information systems to support decision-making in construction owner organizations : a data warehousing approach

Construction organizations typically deal with large volumes of project data containing valuable information. It is found that these organizations do not use these data effectively for planning and decision-making. There are two reasons. First, the information systems in construction organizations are designed to support day-to-day construction operations. The data stored in these systems are often non-validated, nonintegrated and are available in a format that makes it difficult for decision makers to use in order to make timely decisions. Second, the organizational structure and the IT infrastructure are often not compatible with the information systems thereby resulting in higher operational costs and lower productivity. These two issues have been investigated in this research with the objective of developing systems that are structured for effective decision-making. A framework was developed to guide storage and retrieval of validated and integrated data for timely decision-making and to enable construction organizations to redesign their organizational structure and IT infrastructure matched with information system capabilities. The research was focused on construction owner organizations that were continuously involved in multiple construction projects. Action research and Data warehousing techniques were used to develop the framework. One hundred and sixty-three construction owner organizations were surveyed in order to assess their data needs, data management practices and extent of use of information systems in planning and decision-making. For in-depth analysis, Miami-Dade Transit (MDT) was selected which is in-charge of all transportation-related construction projects in the Miami-Dade county. A functional model and a prototype system were developed to test the framework. The results revealed significant improvements in data management and decision-support operations that were examined through various qualitative (ease in data access, data quality, response time, productivity improvement, etc.) and quantitative (time savings and operational cost savings) measures. The research results were first validated by MDT and then by a representative group of twenty construction owner organizations involved in various types of construction projects.

Decision-Making in the Primate Brain

Making decisions is fundamental to everything we do, yet it can be impaired in various disorders and conditions. While research into the neural basis of decision-making has flourished in recent years, many questions remain about how decisions are instantiated in the brain. Here we explored how primates make abstract decisions and decisions in social contexts, as well as one way to non-invasively modulate the brain circuits underlying decision-making. We used rhesus macaques as our model organism. First we probed numerical decision-making, a form of abstract decision-making. We demonstrated that monkeys are able to compare discrete ratios, choosing an array with a greater ratio of positive to negative stimuli, even when this array does not have a greater absolute number of positive stimuli. Monkeys’ performance in this task adhered to Weber’s law, indicating that monkeys—like humans—treat proportions as analog magnitudes. Next we showed that monkeys’ ordinal decisions are influenced by spatial associations; when trained to select the fourth stimulus from the bottom in a vertical array, they subsequently selected the fourth stimulus from the left—and not from the right—in a horizontal array. In other words, they begin enumerating from one side of space and not the other, mirroring the human tendency to associate numbers with space. These and other studies confirmed that monkeys’ numerical decision-making follows similar patterns to that of humans, making them a good model for investigations of the neurobiological basis of numerical decision-making.

We sought to develop a system for exploring the neuronal basis of the cognitive and behavioral effects observed following transcranial magnetic stimulation, a relatively new, non-invasive method of brain stimulation that may be used to treat clinical disorders. We completed a set of pilot studies applying offline low-frequency repetitive transcranial magnetic stimulation to the macaque posterior parietal cortex, which has been implicated in numerical processing, while subjects performed a numerical comparison and control color comparison task, and while electrophysiological activity was recorded from the stimulated region of cortex. We found tentative evidence in one paradigm that stimulation did selectively impair performance in the number task, causally implicating the posterior parietal cortex in numerical decisions. In another paradigm, however, we manipulated the subject’s reaching behavior but not her number or color comparison performance. We also found that stimulation produced variable changes in neuronal firing and local field potentials. Together these findings lay the groundwork for detailed investigations into how different parameters of transcranial magnetic stimulation can interact with cortical architecture to produce various cognitive and behavioral changes.

Finally, we explored how monkeys decide how to behave in competitive social interactions. In a zero-sum computer game in which two monkeys played as a shooter or a goalie during a hockey-like “penalty shot” scenario, we found that shooters developed complex movement trajectories so as to conceal their intentions from the goalies. Additionally, we found that neurons in the dorsolateral and dorsomedial prefrontal cortex played a role in generating this “deceptive” behavior. We conclude that these regions of prefrontal cortex form part of a circuit that guides decisions to make an individual less predictable to an opponent.

Social Decision-Making in Bonobos and Chimpanzees

Humans are natural politicians. We obsessively collect social information that is both observable (e.g., about third-party relationships) and unobservable (e.g., about others’ psychological states), and we strategically employ that information to manage our cooperative and competitive relationships. To what extent are these abilities unique to our species, and how did they evolve? The present dissertation seeks to contribute to these two questions. To do so, I take a comparative perspective, investigating social decision-making in humans’ closest living relatives, bonobos and chimpanzees. In Chapter 1, I review existing literature on theory of mind—or the ability to understand others’ psychological states—in these species. I also present a theoretical framework to guide further investigation of social cognition in bonobos and chimpanzees based on hypotheses about the proximate and ultimate origins of their species differences. In Chapter 2, I experimentally investigate differences in the prosocial behavior of bonobos and chimpanzees, revealing species-specific prosocial motivations that appear to be less flexible than those exhibited by humans. In Chapter 3, I explore through decision-making experiments bonobos’ ability to evaluate others based on their prosocial or antisocial behavior during third-party interactions. Bonobos do track the interactions of third-parties and evaluate actors based on these interactions. However, they do not exhibit the human preference for those who are prosocial towards others, instead consistently favoring an antisocial individual. The motivation to prefer those who demonstrate a prosocial disposition may be a unique feature of human psychology that contributes to our ultra-cooperative nature. In Chapter 4, I investigate the adaptive value of social cognition in wild primates. I show that the recruitment behavior of wild chimpanzees at Gombe National Park, Tanzania is consistent with the use of third-party knowledge, and that those who appear to use third-party knowledge receive immediate proximate benefits. They escape further aggression from their opponents. These findings directly support the social intelligence hypothesis that social cognition has evolved in response to the demands of competing with one’s own group-mates. Thus, the studies presented here help to better characterize the features of social decision-making that are unique to humans, and how these abilities evolved.

Valuation of Ecosystem Services for Environmental Decision Making in South Florida

The Greater Everglades system imparts vital ecosystem services (ES) to South Florida residents including high quality drinking water supplies and a habitat for threatened and endangered species. As a result of the altered Everglades system and regional dynamics, restoration may either improve the provision of these services or impose a tradeoff between enhanced environmental goods and services and competing societal demands. The current study aims at understanding public preferences for restoration and generating willingness to pay (WTP) values for restored ES through the implementation of a discrete choice experiment. A previous study (Milon et al., 1999) generated WTP values amongst Floridians of up to $3.42 -$4.07 billion for full restoration over a 10-year period. We have collected data from 2,905 respondents taken from two samples who participated in an online survey designed to elicit the WTP values for selected ecological and social attributes included in the earlier study (Milon et al. 1999). We estimate that the Florida general public is willing to pay up to $854.1- $954.1 million over 10 years to avoid restrictions on their water usage and up to $90.8- $183.7 million over 10 years to restore the hydrological flow within the Water Conservation Area.

Towards a knowledge-based approach for effective decision-making in railway safety

Purpose – This paper aims to contribute towards understanding how safety knowledge can be elicited from railway experts for the purposes of supporting effective decision-making. Design/methodology/approach – A consortium of safety experts from across the British railway industry is formed. Collaborative modelling of the knowledge domain is used as an approach to the elicitation of safety knowledge from experts. From this, a series of knowledge models is derived to inform decision-making. This is achieved by using Bayesian networks as a knowledge modelling scheme, underpinning a Safety Prognosis tool to serve meaningful prognostics information and visualise such information to predict safety violations. Findings – Collaborative modelling of safety-critical knowledge is a valid approach to knowledge elicitation and its sharing across the railway industry. This approach overcomes some of the key limitations of existing approaches to knowledge elicitation. Such models become an effective tool for prediction of safety cases by using railway data. This is demonstrated using passenger–train interaction safety data. Practical implications – This study contributes to practice in two main directions: by documenting an effective approach to knowledge elicitation and knowledge sharing, while also helping the transport industry to understand safety. Social implications – By supporting the railway industry in their efforts to understand safety, this research has the potential to benefit railway passengers, staff and communities in general, which is a priority for the transport sector. Originality/value – This research applies a knowledge elicitation approach to understanding safety based on collaborative modelling, which is a novel approach in the context of transport.

The thinking doctor: clinical decision making in contemporary medicine

Diagnostic errors are responsible for a significant number of adverse events. Logical reasoning and good decision-making skills are key factors in reducing such errors, but little emphasis has traditionally been placed on how these thought processes occur, and how errors could be minimised. In this article, we explore key cognitive ideas that underpin clinical decision making and suggest that by employing some simple strategies, physicians might be better able to understand how they make decisions and how the process might be optimised.

Effects of spoken cues on decision-making in netball: An eye movement study

Thirteen international netballers viewed static images of scenarios taken from netball open play. Two ‘team mates’, each marked by one opponent, could be seen in each image; each team mate-opponent pair was located on opposite sides of the vertical meridian, such that a binary response was required (‘left’ or ‘right’) from the participant, in order to select a team mate to whom they would pass the ball. For each trial, a spoken word (“left”/“right”) was presented monaurally at the onset of the visual image. Spatially invalid auditory cues (i.e., in the ear contralateral to the correct passing option), reduced performance accuracy relative to valid ones. Semantically invalid cues (e.g., a call of “left” when the target was right-located), increased response times relative to valid ones. However, there were no accompanying changes in visual attention to the team mates and their markers. The effects of auditory cues on covert attentional shifts and decision-making are discussed.

Awake examination versus DISE for surgical decision making in patients with OSA: A systematic review

OBJECTIVE: Traditionally, upper airway examination is performed while the patient is awake. However, in the past two decades, drug-induced sleep endoscopy (DISE) has been used as a method of tridimensional evaluation of the upper airway during pharmacologically induced sleep. This study aimed to systematically review the evidence regarding the usefulness of DISE compared with that of traditional awake examination for surgical decision making in patients with obstructive sleep apnea (OSA). DATA SOURCES: Scopus, PubMed, and Cochrane Library databases were searched. REVIEW METHODS: Only studies with a primary objective of evaluating the usefulness of DISE for surgical decision making in patients with OSA were selected. The included studies directly compared awake examination data with DISE outcome data in terms of possible influences on surgical decision making and operation success. RESULTS: A total of eight studies with 535 patients were included in this review. Overall, the surgical treatment changed after DISE in 50.24% (standard deviation 8.4) cases. These changes were more frequently associated with structures contributing to hypopharyngeal or laryngeal obstruction. However, these differences do not automatically indicate a higher success rate. CONCLUSION: This review emphasized the direct impact of DISE compared with that of awake examination on surgical decision making in OSA patients. However, it is also clear that the available published studies lack evidence on the association between this impact and surgical outcomes

Life Cycle Thinking for sustainability assessment and decision-making in selected food supply chains in Costa Rica

The Agenda 2030 contains 17 integrated Sustainable Development Goals (SDGs). SDG 12 for Sustainable Consumption and Production (SCP) promotes the efficient use of resources through a systemic change that decouples economic growth from environmental degradation. The Food Systems (FS) pillar in SDG 12 entails paramount relevance due to its interconnection to many other SDGs, and even when being a crucial world food supplier, the Latin American and Caribbean (LAC) Region struggles with environmental and social externalities, low investment in agriculture, inequity, food insecurity, poverty, and migration. Life Cycle Thinking (LCT) was regarded as a pertinent approach to identify hotspots and trade-offs, and support decision-making process to aid LAC Region countries as Costa Rica to diagnose sustainability and overcome certain challenges. This thesis aimed to ‘evaluate the sustainability of selected products from food supply chains in Costa Rica, to provide inputs for further sustainable decision-making, through the application of Life Cycle Thinking’. To do this, Life Cycle Assessment (LCA), Life Cycle Costing (LCC), and Social Life Cycle Assessment (S-LCA) evaluated the sustainability of food-waste-to-energy alternatives, and the production of green coffee, raw milk and leafy vegetables, and identified environmental, social and cost hotspots. This approach also proved to be a useful component of decision-making and policy-making processes together with other methods. LCT scientific literature led by LAC or Costa Rican researchers is still scarce; therefore, this research contributed to improve capacities in the use of LCT in this context, while offering potential replicability of the developed frameworks in similar cases. Main limitations related to the representativeness and availability of primary data; however, future research and extension activities are foreseen to increase local data availability, capacity building, and the discussion of potential integration through Life Cycle Sustainability Assessment (LCSA).

A decision-making Fokker-Planck model in computational neuroscience

Minimal models for the explanation of decision-making in computational neuroscience are based on the analysis of the evolution for the average firing rates of two interacting neuron populations. While these models typically lead to multi-stable scenario for the basic derived dynamical systems, noise is an important feature of the model taking into account finite-size effects and robustness of the decisions. These stochastic dynamical systems can be analyzed by studying carefully their associated Fokker-Planck partial differential equation. In particular, we discuss the existence, positivity and uniqueness for the solution of the stationary equation, as well as for the time evolving problem. Moreover, we prove convergence of the solution to the the stationary state representing the probability distribution of finding the neuron families in each of the decision states characterized by their average firing rates. Finally, we propose a numerical scheme allowing for simulations performed on the Fokker-Planck equation which are in agreement with those obtained recently by a moment method applied to the stochastic differential system. Our approach leads to a more detailed analytical and numerical study of this decision-making model in computational neuroscience.

Multicriteria analysis in decision making under information uncertainty

This paper presents results of research related to multicriteria decision making under information uncertainty. The Bell-man-Zadeh approach to decision making in a fuzzy environment is utilized for analyzing multicriteria optimization models (< X, M > models) under deterministic information. Its application conforms to the principle of guaranteed result and provides constructive lines in obtaining harmonious solutions on the basis of analyzing associated maxmin problems. This circumstance permits one to generalize the classic approach to considering the uncertainty of quantitative information (based on constructing and analyzing payoff matrices reflecting effects which can be obtained for different combinations of solution alternatives and the so-called states of nature) in monocriteria decision making to multicriteria problems. Considering that the uncertainty of information can produce considerable decision uncertainty regions, the resolving capacity of this generalization does not always permit one to obtain unique solutions. Taking this into account, a proposed general scheme of multicriteria decision making under information uncertainty also includes the construction and analysis of the so-called < X, R > models (which contain fuzzy preference relations as criteria of optimality) as a means for the subsequent contraction of the decision uncertainty regions. The paper results are of a universal character and are illustrated by a simple example. (c) 2007 Elsevier Inc. All rights reserved.