While (big) data promises immense opportunity, initiatives focused on using data to pursue insight have mixed outcomes. The Management Support Systems (MSS) model summarises what we currently understand within Information Systems (IS) about the implementation and use of systems to improve organisations’ use of data. Adopting an ethnographic approach to observe how practitioners in two contrasting organisations actually generate insight from data, this research challenges the implicit information processing and implementation logics of the MMS model. The pragmatic messiness of pursuing insight is described in two monographs, which reveal the socially constructed nature of data in relation to phenomena, and the importance of data engagement to produce insight. Given that this PhD study also seeks to generate insight from data, it is compared and contrasted reflexively to the two cases observed. While the inquiry logic pursued in this study was made explicit, and was regularly reviewed and challenged, the two cases left this largely implicit. The use of tools is shown to facilitate and constrain inquiry, with related data acting as boundary objects between the different practitioner groups involved. An explanatory framework is presented and used to suggest various enhancements to the MSS model. First, the Problem Space is reframed to reflect the distinct, though interdependent logics involved in inquiry versus realising envisaged benefits from insights. Second, the MSS artefact itself is contextualised and Data Engagement rather than MSS or Tool Use is positioned as central. Third, Data are disentangled from the wider MSS artefact, as a critical, distinct construct. Fourth, an Alignment construct is introduced to address the boundary spanning nature of data initiatives. The thesis also highlights the value of using Wenger’s (1998) Communities of Practice (CoP) situated learning framework to study data initiatives, and the related value of mapping groups as a technique for further development. Some questions are provided for practitioners to gain a better understanding of data initiatives. Wider implications are also noted for the socio-material theorising of Data, and distinguishing between Data, Information and Knowledge concepts within the IS discipline.

Intervening early in the course of psychotic illness (e.g. schizophrenia) may significantly improve prospects for the recovery, both in medical and psychosocial terms, of the individuals who experience these conditions. Engaging such individuals in care, however, remains a challenge. One barrier to engagement is lack of insight, or the low illness awareness that is considered to be a typical characteristic of people who experience psychotic illnesses, particularly in their early phases. The dominant view of this phenomenon is that it is primarily related to the illness itself and thus is biologically based. There is reason to believe, however, that understanding the psychosis experience is also an interpretive process, and that the meaning of this experience for the individual arises out of dialogue between the person, mental health professionals and significant others. There is also reason to believe that the relationship between insight and recovery may not be as straightforward as presumed. While the dominant view sees insight as a crucial condition for recovery, emerging evidence suggests that insight once gained may lead to depression and demoralization. Insight thus may be understood as an interpretive, dialogical process that is fundamentally narrative in nature, the consequences of which may be divergent. Using qualitative methods (constructivist grounded theory complemented by narrative analysis), the present study sought to understand the process by which insight developed in early psychosis, and sought to explore the relationship between insight and the early stages of illness management and recovery, as reflected by the written and oral accounts of twelve individuals who were within the first three years of illness. Overall, the results suggest that insight development in early psychosis can be conceptualized as the process of coming to an acceptable, adaptive explanation. More specifically, the results first of all suggest that insight development involves finding or negotiating an account of illness that fits or can be accommodated with the individual’s own story of the psychosis experience. The process also involves finding an account of illness and its treatment that can be envisioned as a helpful rather than disruptive aspect of the individual’s future biography. / Graduate and Postdoctoral Studies / Graduate

This thesis deals with cryptocurrencies and the underlying principles they are based on. It describes the blockchain technology and explores various cryptocurrencies that utilize it with the focus on their similarities and differences. The next part analyzes InsightAPI, the existing tool for real-time Bitcoin blockchain exploration. It then describes the proposed solution for the Ethereum blockchain explorer, highlights the implementation details, and shows results of its testing. The created tool allows the user to quickly gather information about desired blocks, users, and transactions of the Ethereum blockchain.

Indiana University-Purdue University Indianapolis (IUPUI) / Objective: Social functioning encompasses interactions with people across situations of varying complexity. Given the frequency of observed social impairments in individuals with schizophrenia, there is a need to identify mechanisms that influence social functioning impairments. One proposed mechanism is metacognition, a mental process that enables the integration and interpretation of mental states and experiences. Impaired metacognition can inhibit one’s ability to engage and navigate through our social world. In individuals with schizophrenia, both social functioning and metacognitive deficits are profound. This study examined three hypotheses. Following Metacognitive Reflection and Insight Therapy (MERIT), (1) individuals will show improvements in social functioning; (2) individuals will show improvements in metacognitive abilities; and (3) improvements in social functioning will be associated with improved metacognitive abilities. Method: Using secondary data from a MERIT therapy feasibility study, data collected from the active condition groups (e.g., individuals with schizophrenia, n =16) at pre-and post-assessment were analyzed using paired samples t-tests for primary outcomes and hierarchical linear regressions to assess metacognition as an underlying mechanism of change. Results: Paired samples t-tests found no significant improvement in social functioning or metacognition. In contrast to the hypothesis, metacognitive abilities significantly declined. When subscales were examined, two subscales (self-reflectivity and awareness of others) significantly decreased. The post-hoc analysis found significant improvements in overall symptoms and disorganization. Lastly, metacognition did not significantly predict post-intervention social functioning. Conclusions: Measurement modality and the length of intervention may help explain the null findings observed in this study. The improvement in overall and disorganized symptoms could indicate that symptom reductions precede social functioning and metacognition changes. Given that the results from this trial were not aligned with previous studies, further research is needed to determine the effectiveness of MERIT on social functioning and metacognition in schizophrenia.

No description available.

The primary purpose of this integrative review of the literature is to describe healthcare provider’s recognition of anosognosia in individuals with comorbid mental health disorders, as a differentiating diagnosis needing preeminent early intervention. The secondary purpose is to examine how anosognosia influences outcomes in the population of individuals with severe mental illness. It is expected that early recognition by clinicians and implementation of additional interventions to address anosognosia as the most influential comorbidity of schizophrenia, will decrease exacerbations and improve treatment and patient outcomes. A literature review exploring clinician’s acknowledgement of anosognosia was performed using various databases. Search terms included: Anosognosia, Lack of Insight, Denial of Illness, and Schizophrenia. The data was conformed into tables and synthesized the relationships to identify consistent findings as well as gaps in the current literature. Initial review of the articles retrieved 73 articles relevant to the topic and 18 articles that met inclusion criteria. The studies suggest that mental health conditions with anosognosia have increased rates of adverse outcomes. Anosognosia is a difficult disorder to identify. While many studies have explored the biological basis of anosognosia, the studies performed on safety with mental illness fail to acknowledge anosognosia as a co-morbid condition. Evaluation and clinical guidelines remain inconsistent with research to support the need for recognition of this co-morbidity.

Pathway diagrams, similar to the graph diagrams using a node-link representation, are used by biologists to represent complex interactions at the molecular level in living cells. The recent shift towards data-intensive bioinformatics and systems-level science has created a strong need for advanced pathway visualization tools that support exploratory data analysis. User studies suggest that an important requirement for biologists is the need to associate microarray data to pathway diagrams. A design space for visualization tools that allow analysis of microarray data in pathway context was identified for a systematic evaluation of the visualization alternatives. The design space is divided into two dimensions. Dimension 1 is based on the method used to overlay data attributes onto pathway nodes. The three possible approaches are: overlay of data on pathway nodes one data attribute at a time by manipulating a visual property (e.g. color) of the node, along with sliders or some such mechanism to animate the pathway for other timepoints. In another approach data from all the attributes in data can be overlaid simultaneously by embedding small charts (e.g., line charts or heatmap) into pathway nodes. The third approach uses miniature version of the pathways-as-glyph view for each attribute in the data. Dimension 2 decides if additional view besides pathway diagrams were used. These pathway visualizations are often linked to other type of visualization methods (e.g., parallel co-ordinates) using the concept of brushing and linking. The visualization alternatives from pathway + microarray data design space were evaluated by conducting two independent user studies. Both the studies used timeseries datasets. The first study used visualization alternatives from both dimension 1 and dimension 2. The results suggest that the method to overlay multidimensional data on pathway nodes has a non trivial influence on accuracy of participants' responses, whereas the number of visualizations affect participants' performance time for pre-selected tasks. The second study used visualization alternatives from dimension 1 that focuses on method used to overlay data attributes on pathway nodes. The study suggests that participants using pathway visualization that display data one attribute at a time on nodes have more controlled performance for all type of tasks as compared to the participants using other alternatives. Participants using pathway visualization that display data in node-as-glyphs view have better performance for tasks that require analysis for a single node, and identifying outlier nodes. Whereas, pathway visualizations with pathways-as-glyph view provide better performance on tasks that require analysis of overall changes in the pathway, and identifying interesting timepoints in the data. An insight-based method was designed to evaluate visualization tools for real world biologists' data analysis scenarios. The insight-based method uses different quantifiable characteristics of an "insight" that can be measured uniformly across participants. These characteristics were identified based on observations of the participants analyzing microarray data in a pilot study. The insight-based method provides an alternative to traditional task-based methods. This is especially helpful for evaluating visualization tools on large and complicated datasets where designing tasks can be difficult. Though, the insight-based method was developed to empirically evaluate visualization tools for short term studies, the method can also be used in real world longitudinal studies that analyzes the usage of visualization tools by the intended end-users. / Ph. D.

Data Visualization is used to help humans perceive high dimensional data, but it is unable to be applied in real time to data intensive computing applications. Attempts to process and apply traditional information visualization techniques to such applications result in slow or non-responsive applications. For such applications, sampling is often used to reduce big data to smaller data so that the benefits of data visualization can be brought to data intensive applications. Sampling allows data visualization to be used as an interface between humans and insights contained in the big data of data intensive computing. However, sampling introduces error. The objective of sampling is to reduce the amount of data being processed without introducing too much error into the results of the data intensive application. To determine an adequate level of sampling one can use statistical measures like standard error. However, such measures do not translate well for cases involving data visualization. Knowing the standard error of a sample can tell you very little about the visualization of that data. What is needed is a measure that allows system users to make an informed decision on the level of sampling needed to speed up a data intensive application. In this work we introduce an insight based measure for the impact of sampling on the results of visualized data. We develop a framework for the quantification of the level of insight, model the relationship between the level of insight and the amount of sampling, use this model to provide data intensive computing users with the ability to control the amount of sampling as a function of user provided insight requirements, and we develop a prototype that utilizes our framework. This work allows users to speed up data intensive applications with a clear understanding of how the speedup will impact the insights gained from the visualization of this data. Starting with a simple one dimensional data intensive application we apply our framework and work our way to a more complicated computational fluid dynamics case as a proof concept of the application of our framework and insight error feedback measure for those using sampling to speedup data intensive computing. / Doctor of Philosophy / Data Visualization is used to help humans perceive high dimensional data, but it is unable to be applied in real time to computing applications that generate or process vast amounts of data, also known as data intensive computing applications. Attempts to process and apply traditional information visualization techniques to such data result in slow or non-responsive data intensive applications. For such applications, sampling is often used to reduce big data to smaller data so that the benefits of data visualization can be brought to data intensive applications. Sampling allows data visualization to be used as an interface between humans and insights contained in the big data of data intensive computing. However, sampling introduces error. The objective of sampling is to reduce the amount of data being processed without introducing too much error into the results of the data intensive application. This error results from the possibility that a data sample could exclude valuable information that was included in the original data set. To determine an adequate level of sampling one can use statistical measures like standard error. However, such measures do not translate well for cases involving data visualization. Knowing the standard error of a sample can tell you very little about the visualization of that data. What is needed is a measure that allows one to make an informed decision of how much sampling to use in a data intensive application, as a result of knowing how sampling impacts how people gain insights from a visualization of the sampled data. In this work we introduce an insight based measure for the impact of sampling on the results of visualized data. We develop a framework for the quantification of the level of insight, model the relationship between the level of insight and the amount of sampling, use this model to provide data intensive computing users with an insight based feedback measure for each arbitrary sample size they choose for speeding up data intensive computing, and we develop a prototype that utilizes our framework. Our prototype applies our framework and insight based feedback measure to a computational fluid dynamics (CFD) case, but our work starts off with a simple one dimensional data application and works its way up to the more complicated CFD case. This work allows users to speed up data intensive applications with a clear understanding of how the speedup will impact the insights gained from the visualization of this data.

Yes / Discrepancy scores reflecting the difference between parallel ratings made by people living with dementia (PwD) in the mild-to-moderate stages and by their informants provide a way to investigate awareness of functional ability in relation to activities of daily living (ADL). Methods: Two measures of ADL (Functional Activities Questionnaire; Dependence Scale) were completed by 1,227 PwD and their informants in the IDEAL cohort study baseline assessment. Self-rated and informant-rated scores were used to calculate discrepancies, which were used as an indicator of awareness of functional ability. Smaller discrepancy scores were considered to reflect greater awareness on the part of PwD. PwD completed questionnaires on depression, personality, comorbidities, neuropsychiatric symptoms, and completed a measure of cognition. Informants provided ratings of stress. Univariable and multiple regressions were used to investigate factors related to ADL discrepancy. Results: A similar pattern of associations were found for both ADL discrepancy scores. Smaller discrepancy scores were associated with higher levels of depression, higher neuroticism, fewer neuropsychiatric symptoms, higher comorbidity, lower carer stress, and receipt of less than 1 hour of care per day from the informant. Discussion/Conclusion: There was a clear pattern of factors that were associated with greater awareness for both measures of functional ability. These factors associated with smaller discrepancy scores could be used to identify PwD who might benefit from targeted interventions to support their independence. / Economic and Social Research Council (ESRC) and the National Institute for Health and Care Research (NIHR) grant ES/L001853/2; Alzheimer’s Society as a Centre of Excellence, grant number 348, AS-PR2-16-001

A resolução de problemas é uma metodologia de investigação utilizada pela Psicologia experimental desde sua fundação. Um debate na área é quais os efeitos de variáveis de treino sobre a resolução de problemas, e como ocorre um tipo específico de resolução, a chamada resolução súbita, tradicionalmente descrita como Insight. O presente trabalho teve por objetivo averiguar a resolução de problemas a partir do treino independente de habilidades pré-requisito em diferentes tarefas de recombinação de repertórios com diferentes espécies. Adicionalmente, foram feitos testes de entendimento de propriedades funcionais de objetos e repertórios treinados. No Experimento I, dois pombos (Columba livia) foram testados no procedimento padrão de deslocamento de caixa. Os sujeitos aprenderam: a) empurrar uma caixa em direção a um alvo, e b) subir e bicar outro alvo. O teste final requeria que o animal empurrasse a caixa para debaixo de um alvo, subisse e o bicasse. Os dois sujeitos resolveram a tarefa final. No Experimento II, quatro pombos passaram por histórias assimétricas de treino das duas habilidades pré-requisito também da tarefa de deslocamento de caixa. Apenas um dos sujeitos resolveu o problema, e sem a mesma fluidez apresentada pelos sujeitos do Experimento I. O Experimento III manipulou a consequência utilizada no treino de cada habilidade pré-requisito, também na tarefa de deslocamento de caixas. Empurrar em direção a uma luz foi treinado com alimento como consequência, e subir e bicar foi treinado com água como consequência. Nenhum dos quatro pombos resolveu a tarefa em sua primeira tentativa. Todos os sujeitos que resolveram a tarefa nos Experimentos I, II ou III apresentaram resultados similares nos testes de entendimento de propriedades funcionais, que indicaram que pequenas mudanças na situação de teste dificultam a resolução. No Experimento IV, com ratos (Rattus norvegicus), uma nova tarefa foi desenvolvida, que envolvia a recombinação de a) cavar maravalha, e b) subir escadas. Na tarefa final os ratos deveriam cavar a maravalha, encontrar uma passagem escondida que dava acesso a um segundo ambiente no qual haviam escadas que levavam a um pedaço de alimento. Dois ratos aprenderam os dois repertórios e resolveram a tarefa, de forma súbita. Outros quatro ratos que aprenderam somente um dos repertórios não resolveram a tarefa. O Experimento V testou os efeitos da quantidade de treino (Experimento II), tipo de consequência (Experimento III) e contexto de treino e teste, em uma tarefa específica com corvos da Nova Caledônia (Corvus moneduloides). Todos os animais resolveram a tarefa final, entretanto, de forma não súbita. Os dados indicam que a resolução súbita, a partir da recombinação de repertórios aprendidos independentemente é passível do efeito de uma série de variáveis de treino e teste até então pouco estudadas, como a quantidade de treino, tipo de consequência e contexto de treino e teste / Experimental Psychology utilizes problem-solving methodology since its inception. Much was debated about the effects of training variables upon the solution of a problem, especially concerning the sudden solution of specific problem, called Insight. The present work aimed to investigate the solution of different problem in different species after the independent training of pre-requisite repertoires. Additionally, tests regarding the understanding of functional properties of stimuli were made. In Experiment I, two pigeons (Columba livia) were tested in the box-displacement test. The subjects learned to, a) push a box towards a target, and b) to climb and peck another target. The final task required to subjects to push one box towards a target hanging in the ceiling, climb the box and then peck the target. The two subjects solved the final task. In Experiment II, four pigeons had an asymmetric training of the two abilities. Only one of the subjects solved the final task, not as fluidly as the subjects from Experiment I. In Experiment III, the consequence used during the training of each ability was different. Pushing towards a target was reinforced with food, and to climb and peck with water. None of the four birds solved the task in its first presentation. All the subjects that solved the tasks in Experiments I, II and III showed similar performances in the tests regarding the understanding of functional properties of stimuli, suggesting that even minima changes in the test situation can impair the solution. Experiment IV employed a new task, with rats (Rattus norvegicus). Subjects learned to a) digg shavings, and b) climb stairs. In the final task, the rats had to digg and find a passage leading to another ambient containing stairs that lead to food. Two rats that learned the two abilities solved the problem, suddenly. Other four rats that learned only one of the two abilities (dig or climb) didnt solved the problem. Experiment V tested the effects of quantities of training (Experiment II), consequences of trained abilities (Experiment III), and context of training and testing with new caledonian crows (Corvus moneduloides). All four crows solved the problem, but not suddenly. The data of all experiments suggests that the sudden solution, when acquired through the interconnection of repertoires is more subtle then it is usualy regarded, and that variables of training and testing are crucial for the solution of a problem