20,783 research outputs found

    Designing an organization in a hypothesis testing framework

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    Caption title.Includes bibliographical references (p. 12-13).Supported by the Office of Naval Research. ONR/N00014-84-K-0519 (NR 649-003)by Jason D. Papastavrou, Javed Pothiawala and Michael Athans

    Clinical experience as evidence in evidence-based practice

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    Background. This paper's starting point is the recognition (descriptive not normative) that, for the vast majority of day-to-day clinical decision-making situations, the 'evidence' for decision-making is experiential knowledge. Moreover, reliance on this knowledge base means that nurses must use cognitive shortcuts or heuristics for handling information when making decisions. These heuristics encourage systematic biases in decision-makers and deviations from the normative rules of 'good' decision-making. Aims. The aim of the paper is to explore three common heuristics and the biases that arise when handling complex information in clinical decision-making (overconfidence, hindsight and base rate neglect) and, in response to these biases, to illustrate some simple techniques for reducing the negative influence of heuristics. Discussion. Nurses face a limited range of types of uncertainty in their clinical decisions and draw primarily on experiential knowledge to handle these uncertainties. This paper argues that experiential knowledge is a necessary but not sufficient basis for clinical decision-making. It illustrates how overconfidence in one's knowledge base, being correct 'after the event' or with the benefit of hindsight, and ignoring the base rates associated with events, conditions or health states, can impact on professional judgements and decisions. The paper illustrates some simple strategies for minimizing the impact of heuristics on the real-life clinical decisions of nurses. Conclusion. The paper concludes that more research knowledge of the impact of heuristics and techniques to combat them in nursing decisions is needed

    A model for providing emotion awareness and feedback using fuzzy logic in online learning

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    Monitoring users’ emotive states and using that information for providing feedback and scaffolding is crucial. In the learning context, emotions can be used to increase students’ attention as well as to improve memory and reasoning. In this context, tutors should be prepared to create affective learning situations and encourage collaborative knowledge construction as well as identify those students’ feelings which hinder learning process. In this paper, we propose a novel approach to label affective behavior in educational discourse based on fuzzy logic, which enables a human or virtual tutor to capture students’ emotions, make students aware of their own emotions, assess these emotions and provide appropriate affective feedback. To that end, we propose a fuzzy classifier that provides a priori qualitative assessment and fuzzy qualifiers bound to the amounts such as few, regular and many assigned by an affective dictionary to every word. The advantage of the statistical approach is to reduce the classical pollution problem of training and analyzing the scenario using the same dataset. Our approach has been tested in a real online learning environment and proved to have a very positive influence on students’ learning performance.Peer ReviewedPostprint (author's final draft

    Using the Oxford cognitive screen to detect cognitive impairment in stroke patients. A comparison with the Mini-Mental State Examination

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    Background: The Oxford Cognitive Screen (OCS) was recently developed with the aim of describing the cognitive de cits after stroke. The scale consists of 10 tasks encom- passing ve cognitive domains: attention and executive function, language, memory, number processing, and praxis. OCS was devised to be inclusive and un-confounded by aphasia and neglect. As such, it may have a greater potential to be informative on stroke cognitive de cits of widely used instruments, such as the Mini-Mental State Examination (MMSE) or the Montreal Cognitive Assessment, which were originally devised for demented patients. Objective: The present study compared the OCS with the MMSE with regards to their ability to detect cognitive impairments post-stroke. We further aimed to examine perfor- mance on the OCS as a function of subtypes of cerebral infarction and clinical severity. Methods: 325 rst stroke patients were consecutively enrolled in the study over a 9-month period. The OCS and MMSE, as well as the Bamford classi cation and NIHSS, were given according to standard procedures. results: About a third of patients (35.3%) had a performance lower than the cutoff (<22) on the MMSE, whereas 91.6% were impaired in at least one OCS domain, indicating higher incidences of impairment for the OCS. More than 80% of patients showed an impairment in two or more cognitive domains of the OCS. Using the MMSE as a standard of clinical practice, the comparative sensitivity of OCS was 100%. Out of the 208 patients with normal MMSE performance 180 showed impaired performance in at least one domain of the OCS. The discrepancy between OCS and MMSE was particularly strong for patients with milder strokes. As for subtypes of cerebral infarction, fewer patients demonstrated widespread impairments in the OCS in the Posterior Circulation Infarcts category than in the other categories. conclusion: Overall, the results showed a much higher incidence of cognitive impairment with the OCS than with the MMSE and demonstrated no false negatives for OCS vs MMSE. It is concluded that OCS is a sensitive screen tool for cognitive de cits after stroke. In particular, the OCS detects high incidences of stroke-specific cognitive impairments, not detected by the MMSE, demonstrating the importance of cognitive pro ling.Background: The Oxford Cognitive Screen (OCS) was recently developed with the aim of describing the cognitive deficits after stroke. The scale consists of 10 tasks encompassing five cognitive domains: attention and executive function, language, memory, number processing, and praxis. OCS was devised to be inclusive and un-confounded by aphasia and neglect. As such, it may have a greater potential to be informative on stroke cognitive deficits of widely used instruments, such as the Mini-Mental State Examination (MMSE) or the Montreal Cognitive Assessment, which were originally devised for demented patients. Objective: The present study compared the OCS with the MMSE with regards to their ability to detect cognitive impairments post-stroke. We further aimed to examine performance on the OCS as a function of subtypes of cerebral infarction and clinical severity. Methods: 325 first stroke patients were consecutively enrolled in the study over a 9-month period. The OCS and MMSE, as well as the Bamford classification and NIHSS, were given according to standard procedures. Results: About a third of patients (35.3%) had a performance lower than the cutoff(< 22) on the MMSE, whereas 91.6% were impaired in at least one OCS domain, indicating higher incidences of impairment for the OCS. More than 80% of patients showed an impairment in two or more cognitive domains of the OCS. Using the MMSE as a standard of clinical practice, the comparative sensitivity of OCS was 100%. Out of the 208 patients with normal MMSE performance 180 showed impaired performance in at least one domain of the OCS. The discrepancy between OCS and MMSE was particularly strong for patients with milder strokes. As for subtypes of cerebral infarction, fewer patients demonstrated widespread impairments in the OCS in the Posterior Circulation Infarcts category than in the other categories. Conclusion: Overall, the results showed a much higher incidence of cognitive impairment with the OCS than with the MMSE and demonstrated no false negatives for OCS vs MMSE. It is concluded that OCS is a sensitive screen tool for cognitive deficits after stroke. In particular, the OCS detects high incidences of stroke-specific cognitive impairments, not detected by the MMSE, demonstrating the importance of cognitive profiling. © 2018 Mancuso, Demeyere, Abbruzzese, Damora, Varalta, Pirrotta, Antonucci, Matano, Caputo, Caruso, Pontiggia, Coccia, Ciancarelli, Zoccolotti and The Italian OCS Grou

    Does Consistency Predict Accuracy of Beliefs?: Economists Surveyed About PSA

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    Subjective beliefs and behavior regarding the Prostate Specific Antigen (PSA) test for prostate cancer were surveyed among attendees of the 2006 meeting of the American Economic Association. Logical inconsistency was measured in percentage deviations from a restriction imposed by Bayes’ Rule on pairs of conditional beliefs. Economists with inconsistent beliefs tended to be more accurate than average, and consistent Bayesians were substantially less accurate. Within a loss function framework, we look for and cannot find evidence that inconsistent beliefs cause economic losses. Subjective beliefs about cancer risks do not predict PSA testing decisions, but social influences do.logical consistency, predictive accuracy, elicitation, non-Bayesian, ecological rationality

    Does consistency predict accuracy of beliefs?: Economists surveyed about PSA

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    Subjective beliefs and behavior regarding the Prostate Specific Antigen (PSA) test for prostate cancer were surveyed among attendees of the 2006 meeting of the American Economic Association. Logical inconsistency was measured in percentage deviations from a restriction imposed by Bayes’ Rule on pairs of conditional beliefs. Economists with inconsistent beliefs tended to be more accurate than average, and consistent Bayesians were substantially less accurate. Within a loss function framework, we look for and cannot find evidence that inconsistent beliefs cause economic losses. Subjective beliefs about cancer risks do not predict PSA testing decisions, but social influences do.logical consistency, predictive accuracy, elicitation, non-Bayesian, ecological rationality

    Metacognition and Reflection by Interdisciplinary Experts: Insights from Cognitive Science and Philosophy

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    Interdisciplinary understanding requires integration of insights from different perspectives, yet it appears questionable whether disciplinary experts are well prepared for this. Indeed, psychological and cognitive scientific studies suggest that expertise can be disadvantageous because experts are often more biased than non-experts, for example, or fixed on certain approaches, and less flexible in novel situations or situations outside their domain of expertise. An explanation is that experts’ conscious and unconscious cognition and behavior depend upon their learning and acquisition of a set of mental representations or knowledge structures. Compared to beginners in a field, experts have assembled a much larger set of representations that are also more complex, facilitating fast and adequate perception in responding to relevant situations. This article argues how metacognition should be employed in order to mitigate such disadvantages of expertise: By metacognitively monitoring and regulating their own cognitive processes and representations, experts can prepare themselves for interdisciplinary understanding. Interdisciplinary collaboration is further facilitated by team metacognition about the team, tasks, process, goals, and representations developed in the team. Drawing attention to the need for metacognition, the article explains how philosophical reflection on the assumptions involved in different disciplinary perspectives must also be considered in a process complementary to metacognition and not completely overlapping with it. (Disciplinary assumptions are here understood as determining and constraining how the complex mental representations of experts are chunked and structured.) The article concludes with a brief reflection on how the process of Reflective Equilibrium should be added to the processes of metacognition and philosophical reflection in order for experts involved in interdisciplinary collaboration to reach a justifiable and coherent form of interdisciplinary integration. An Appendix of “Prompts or Questions for Metacognition” that can elicit metacognitive knowledge, monitoring, or regulation in individuals or teams is included at the end of the article

    Designing for cyber security risk-based decision making.

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    Techniques for determining and applying cyber security decisions typically follow risk- based analytical approaches where alternative options are put forward based on goals and context, and weighed in accordance to risk severity metrics. These decision making approaches are however difficult to apply in risk situations bounded by uncertainty as decision alternatives are either unknown or unclear. This problem is further compounded by the rarity of expert security decision makers and the far-reaching repercussions of un-informed decision making. The nature of operations in cyber security indicates that only a handful of systems are independent of the human operators, exposing the majority of organisations to risk from security threats and risks as a product of human decision making limitations. Addressing the problem requires considering factors contributing to risk and uncertainty during the early stages of system design, motivating the development of systems that are not only usable and secure, but that facilitate informed decision making as a central goal. The thesis investigates this by posing the question; what system design techniques should be taken into consideration to facilitate cyber security decision making during situations of risk and uncertainty? The research was approached qualitatively with interviews as the main data elicitation approach. Grounded Theory was applied to five security decision making studies to inductively elicit, model, and validate design requirements for Risk-based Decision Making in cyber security. Contributions arising from thesis work are: an identification of factors contributing to security analysts’ risk practices and understanding, a model for communicating and tracing risk rationalisation by cyber security decision makers, a conceptual model illustrating the various concepts in cyber security decision making and their relationship, and guidelines and suggested implementation techniques guiding the specification of requirements for systems deployed in cyber security Risk-based Decision Making. The thesis is validated by applying the proposed design guidelines to inform an approach used to design a charity’s secure data handling policy
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