830 resultados para confidence in policing


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Signatur des Originals: S 36/G03792

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Hierarchical linear growth model (HLGM), as a flexible and powerful analytic method, has played an increased important role in psychology, public health and medical sciences in recent decades. Mostly, researchers who conduct HLGM are interested in the treatment effect on individual trajectories, which can be indicated by the cross-level interaction effects. However, the statistical hypothesis test for the effect of cross-level interaction in HLGM only show us whether there is a significant group difference in the average rate of change, rate of acceleration or higher polynomial effect; it fails to convey information about the magnitude of the difference between the group trajectories at specific time point. Thus, reporting and interpreting effect sizes have been increased emphases in HLGM in recent years, due to the limitations and increased criticisms for statistical hypothesis testing. However, most researchers fail to report these model-implied effect sizes for group trajectories comparison and their corresponding confidence intervals in HLGM analysis, since lack of appropriate and standard functions to estimate effect sizes associated with the model-implied difference between grouping trajectories in HLGM, and also lack of computing packages in the popular statistical software to automatically calculate them. ^ The present project is the first to establish the appropriate computing functions to assess the standard difference between grouping trajectories in HLGM. We proposed the two functions to estimate effect sizes on model-based grouping trajectories difference at specific time, we also suggested the robust effect sizes to reduce the bias of estimated effect sizes. Then, we applied the proposed functions to estimate the population effect sizes (d ) and robust effect sizes (du) on the cross-level interaction in HLGM by using the three simulated datasets, and also we compared the three methods of constructing confidence intervals around d and du recommended the best one for application. At the end, we constructed 95% confidence intervals with the suitable method for the effect sizes what we obtained with the three simulated datasets. ^ The effect sizes between grouping trajectories for the three simulated longitudinal datasets indicated that even though the statistical hypothesis test shows no significant difference between grouping trajectories, effect sizes between these grouping trajectories can still be large at some time points. Therefore, effect sizes between grouping trajectories in HLGM analysis provide us additional and meaningful information to assess group effect on individual trajectories. In addition, we also compared the three methods to construct 95% confident intervals around corresponding effect sizes in this project, which handled with the uncertainty of effect sizes to population parameter. We suggested the noncentral t-distribution based method when the assumptions held, and the bootstrap bias-corrected and accelerated method when the assumptions are not met.^

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This document provides a general description of the telematic voting scenario designed by the author?s research group. This scenario reinforces verification procedures as key elements to achieve full acceptance of the system on the part of voters. To frame this work, a general overview of electronic voting is given and the conditions entailed by these systems are specified.

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The objective of the current work is to present the results of several numerical simulations of pulsatile blood flow in healthy and diseased arteries and compare with clinical expectations. Different realistic and physiological aspects such as blood flow interaction with arterial walls, effect of heart movement, cardiovascular autoregulation, arterial walls' hyperelasticity and cardiovascular disorders have been incorporated in the models thanks to a direct coupling of Abaqus and STAR-CCM+. Comparisons of implicit and explicit coupling methods in cardiovascular simulations have been discussed. An in-house methodology combined with explicit FSI coupling has reduced considerably calculation time while the simulations stay realistic and reliable for clinicians

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Los servicios basados en las Tecnologías de la Información y las Comunicaciones (TIC) están cada vez más presentes en la vida de las personas. El avance de las TIC en términos técnicos y de aceptación social ha dado lugar la creación de nuevos modelos de provisión de servicios. Estos modelos de servicio implican una mayor integración con las actividades de las personas de forma que ya no solo están presentes en su ámbito profesional o de espacio ciudadano sino también en un ámbito más íntimo relacionado con su propia identidad. Así en la actualidad es común encontrar servicios conocedores del estado de salud de las personas, sus hábitos domésticos, su ideología, etc. Por tanto el análisis de los servicios actuales no puede limitarse a una componente técnica sino que es más necesario que nunca la inclusión de aspectos más relacionados con la forma de ser y sentir de sus usuarios. De esta forma no solo se garantizará la corrección técnica de sus funcionalidades sino que también se fomentará la generación de soluciones cívicamente seguras y respetuosas tanto con los derechos como con la forma de ser y sentir de sus usuarios. Desde el punto de vista de ingeniería, la perspectiva del usuario se ha englobado históricamente bajo el concepto de aceptación tecnológica. Dentro de este ámbito se puede interpretar que soluciones respetuosas y adaptadas a los usuarios fomentarán la aceptación por parte de éstos. La aceptación de una solución es algo deseable si bien es difícil de asegurar. Esta dificultad es debida al desconocimiento del número de variables que afectan a la aceptación de soluciones tecnológicas y a la dificultad de optimización de las variables conocidas. En esta tesis doctoral se estudia y caracteriza una de las variables que afecta a la aceptación de los servicios actuales: la confianza. Se define la confianza en términos psicológicos caracterizándola para permitir su uso en los métodos propios de la ingeniería. Además se proponen distintas herramientas que facilitan la optimización de la confianza en servicios cuya complejidad convierte a esta variable en una cuestión básica para mejorar la aceptación. Como contexto de trabajo para la tesis se ha escogido un servicio de salud desplegado en un hogar. Este escenario presenta una serie de restricciones de aceptación relativas a la tecnología utilizada para la creación de los servicios y la forma en que éstos gestionan la información adquirida del usuario. Se trata de servicios altamente sensibles y deslocalizados que pueden afectar a la percepción del usuario sobre el entorno, el hogar, y generar temores o rechazos que impidan su adopción final como solución válida. Una vez definido el marco genérico de trabajo, el objetivo principal de esta tesis doctoral se concreta en contribuir al fomento de la aceptación de nuevos servicios de salud pervasivos y personalizados y su despliegue en entornos inteligentes domésticos mediante un marco de diseño que promueva un estado psicológico de confianza en los usuarios. Para lograr abordar correctamente este objetivo se han proporcionado una serie de resultados tanto a nivel conceptual como tecnológico y experimental. En concreto se ha ofrecido una caracterización completa del sentimiento de confianza desde un punto de vista de ingeniería y una definición del concepto de servicio sensible deslocalizado o pervasivo. Además se ofrece un método para la inclusión del Diseño de Interacción, herramienta muy relacionada con la mejora de las variables de aceptación de tecnología, en los procesos de ingeniería de este tipo de servicios mediante un conjunto de patrones de interacción Persona – Entorno Inteligente. Finalmente se ha proporcionado el desarrollo de una arquitectura software para garantizar el correcto despliegue de estos servicios sensibles pervasivos en espacios inteligentes de una forma confiable. La discusión de los resultados obtenidos sugiere la extensión del modelo a diferentes servicios de la Sociedad de la Información que manejen datos sensibles tanto en el contexto del Hogar Digital como otros contextos donde el usuario realice actividades cotidianas, como los espacios de trabajo o los centros educativos. Las líneas de trabajo futuras contemplan la necesidad inminente de aplicar los resultados a desarrollos en curso, dentro de proyectos de investigación en los que participa el autor así como el desarrollo de nuevas líneas de investigación orientadas a la generación de nuevos espacios y tecnologías de interacción como el Colegio Digital, juguetes del futuro, sistemas de visualización confiables o sistemas de seguridad basados en el estado de las personas.

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Purpose/Objectives: To evaluate the impact of a cancer nursing education course on RNs. Design: Quasi-experimental, longitudinal, pretest/post-test design, with a follow-up assessment six weeks after the completion of the nursing education course. Setting: Urban, nongovernment, cancer control agency in Australia. Sample: 53 RNs, of whom 93% were female, with a mean age of 44.6 years and a mean of 16.8 years of experience in nursing; 86% of the nurses resided and worked in regional areas outside of the state capital. Methods: Scales included the Intervention With Psychosocial Needs: Perceived Importance and Skill Level Scale, Palliative Care Quiz for Nurses, Breast Cancer Knowledge, Preparedness for Cancer Nursing, and Satisfaction With Learning. Data were analyzed using multiple analysis of variance and paired t tests. Main Research Variables: Cancer nursing-related knowledge, preparedness for cancer nursing, and attitudes toward and perceived skills in the psychosocial care of patients with cancer and their families. Findings: Compared to nurses in the control group, nurses who attended the nursing education course improved in their cancer nursing-related knowledge, preparedness for cancer nursing, and attitudes toward and perceived skills in the psychosocial care of patients with cancer and their families. Improvements were evident at course completion and were maintained at the six-week follow-up assessment. Conclusions: The nursing education course was effective in improving nurses' scores on all outcome variables. Implications for Nursing: Continuing nursing education courses that use intensive mode timetabling, small group learning, and a mix of teaching methods, including didactic and interactive approaches and clinical placements, are effective and have the potential to improve nursing practice in oncology.

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The manner in which elements of clinical history, physical examination and investigations influence subjectively assessed illness severity and outcome prediction is poorly understood. This study investigates the relationship between clinician and objectively assessed illness severity and the factors influencing clinician's diagnostic confidence and illness severity rating for ventilated patients with suspected pneumonia in the intensive care unit (ICU). A prospective study of fourteen ICUs included all ventilated admissions with a clinical diagnosis of pneumonia. Data collection included pneumonia type - community-acquired (CAP), hospital-acquired (HAP) and ventilator-associated (VAP), clinician determined illness severity (CDIS), diagnostic methods, clinical diagnostic confidence (CDC), microbiological isolates and antibiotic use. For 476 episodes of pneumonia (48% CAP, 24% HAP, 28% VAP), CDC was greatest for CAP (64% CAP, 50% HAP and 49% VAP, P < 0.01) or when pneumonia was considered life-threatening (84% high CDC, 13% medium CDC and 3% low CDC, P < 0.001). Life-threatening pneumonia was predicted by worsening gas exchange (OR 4.8, CI 95% 2.3-10.2, P < 0.001), clinical signs of consolidation (OR 2.0, CI 95% 1.2-3.2, P < 0.01) and the Sepsis-Related Organ Failure Assessment (SOFA) Score (OR 1.1, CI 95% 1.1-1.2, P < 0.001). Diagnostic confidence increased with CDIS (OR 163, CI 95% 8.4-31.4, P < 0.001), definite pathogen isolation (OR 3.3, CI 95% 2.0-5.6) and clinical signs of consolidation (OR 2.1, CI 95% 1.3-3.3, P = 0.001). Although the CDIS, SOFA Score and the Simplified Acute Physiologic Score (SAPS II) were all associated with mortality, the SAPS II Score was the best predictor of mortality (P = 0.02). Diagnostic confidence for pneumonia is moderate but increases with more classical presentations. A small set of clinical parameters influence subjective assessment. Objective assessment using SAPS II Scoring is a better predictor of mortality.