New graduate nurses' developmental trajectories for capability beliefs concerning core competencies for healthcare professionals : A national cohort study on patient-centered care, teamwork and evidence-based practice.

Background: This study aimed to describe the developmental trajectories of registered nurses' capability beliefs during their first 3 years of practice. The focus was on three core competencies for health professionals-patient-centered care, teamwork, and evidence-based practice. Methods: A national cohort of registered nurses (n = 1,205) was recruited during their nursing education and subsequently surveyed yearly during the first 3 years of working life. The survey included 16 items on capability beliefs divided into three subscales for the assessment of patient-centered care, teamwork, and evidence-based practice, and the data were analyzed with linear latent growth modeling. Results: The nurses' capability beliefs for patient-centered care increased over the three first years of working life, their capability beliefs for evidence-based practice were stable over the 3 years, and their capability beliefs for teamwork showed a downward trend. Linking evidence to action: Through collaboration between nursing education and clinical practice, the transition to work life could be supported and competence development in newly graduated nurses could be enhanced to help them master the core competencies. Future research should focus on determining which factors impact the development of capability beliefs in new nurses and how these factors can be developed by testing interventions.

Optical Characterization and Optimization of Display Components : Some Applications to Liquid-Crystal-Based and Electrochromics-Based Devices

This dissertation is focused on theoretical and experimental studies of optical properties of materials and multilayer structures composing liquid crystal displays (LCDs) and electrochromic (EC) devices. By applying spectroscopic ellipsometry, we have determined the optical constants of thin films of electrochromic tungsten oxide (WOx) and nickel oxide (NiOy), the films’ thickness and roughness. These films, which were obtained at spattering conditions possess high transmittance that is important for achieving good visibility and high contrast in an EC device. Another application of the general spectroscopic ellipsometry relates to the study of a photo-alignment layer of a mixture of azo-dyes SD-1 and SDA-2. We have found the optical constants of this mixture before and after illuminating it by polarized UV light. The results obtained confirm the diffusion model to explain the formation of the photo-induced order in azo-dye films. We have developed new techniques for fast characterization of twisted nematic LC cells in transmissive and reflective modes. Our techniques are based on the characteristics functions that we have introduced for determination of parameters of non-uniform birefringent media. These characteristic functions are found by simple procedures and can be utilised for simultaneous determination of retardation, its wavelength dispersion, and twist angle, as well as for solving associated optimization problems. Cholesteric LCD that possesses some unique properties, such as bistability and good selective scattering, however, has a disadvantage – relatively high driving voltage (tens of volts). The way we propose to reduce the driving voltage consists of applying a stack of thin (~1µm) LC layers. We have studied the ability of a layer of a surface stabilized ferroelectric liquid crystal coupled with several retardation plates for birefringent color generation. We have demonstrated that in order to accomplish good color characteristics and high brightness of the display, one or two retardation plates are sufficient.

Predictive models for chronic renal disease using decision trees, naïve bayes and case-based methods

Data mining can be used in healthcare industry to “mine” clinical data to discover hidden information for intelligent and affective decision making. Discovery of hidden patterns and relationships often goes intact, yet advanced data mining techniques can be helpful as remedy to this scenario. This thesis mainly deals with Intelligent Prediction of Chronic Renal Disease (IPCRD). Data covers blood, urine test, and external symptoms applied to predict chronic renal disease. Data from the database is initially transformed to Weka (3.6) and Chi-Square method is used for features section. After normalizing data, three classifiers were applied and efficiency of output is evaluated. Mainly, three classifiers are analyzed: Decision Tree, Naïve Bayes, K-Nearest Neighbour algorithm. Results show that each technique has its unique strength in realizing the objectives of the defined mining goals. Efficiency of Decision Tree and KNN was almost same but Naïve Bayes proved a comparative edge over others. Further sensitivity and specificity tests are used as statistical measures to examine the performance of a binary classification. Sensitivity (also called recall rate in some fields) measures the proportion of actual positives which are correctly identified while Specificity measures the proportion of negatives which are correctly identified. CRISP-DM methodology is applied to build the mining models. It consists of six major phases: business understanding, data understanding, data preparation, modeling, evaluation, and deployment.