In competence-based vocational education, personal professional theories, in which students integrate different types of knowledge and beliefs, are seen as important. Exactly how these theories can be measured is the main focus of this study, which uses a multi-method triangulation approach, an interview and a self-report. The latter (less-structured) matter seems to provide less insight into personal professional theories then the structured methods. Both structure and adequate prompts are important when personal professional theories are explicated.
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Aim and objectives: To provide an in-depth insight into the barriers, facilitators and needs of district nurses and nurse assistants on using patient outcomes in district nursing care. Background: As healthcare demands grow, particularly in district nursing, there is a significant need to understand how to systematically measure and improve patient outcomes in this setting. Further investigation is needed to identify the barriers and facilitators for effective implementation. Design: A multi-method qualitative study. Methods: Open-ended questions of a survey study (N = 132) were supplemented with in-depth online focus group interviews involving district nurses and nurse assistants (N = 26) in the Netherlands. Data were analysed using thematic analysis. Results: Different barriers, facilitators and needs were identified and compiled into 16 preconditions for using outcomes in district nursing care. These preconditions were summarised into six overarching themes: follow the steps of a learning healthcare system; provide patient-centred care; promote the professional's autonomy, attitude, knowledge and skills; enhance shared responsibility and collaborations within and outside organisational boundaries; prioritise and invest in the use of outcomes; and boost the unity and appreciation for district nursing care. Conclusions: The preconditions identified in this study are crucial for nurses, care providers, policymakers and payers in implementing the use of patient outcomes in district nursing practice. Further exploration of appropriate strategies is necessary for a successful implementation. Relevance to clinical practice: This study represents a significant step towards implementing the use of patient outcomes in district nursing care. While most research has focused on hospitals and general practitioner settings, this study focuses on the needs for district nursing care. By identifying 16 key preconditions across themes such as patient-centred care, professional autonomy and unity, the findings offer valuable guidance for integrating a learning healthcare system that prioritises the measurement and continuous improvement of patient outcomes in district nursing.
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A clubfoot is characterized by a three-dimensional deformity with an equinus, varus, cavus and adduction component. Nowadays the Ponseti method is the preferred treatment for clubfeet, aiming to achieve a normal appearing, functional and painless foot. The reoccurrence of clubfoot components in treated clubfeet, a relapse, is a known problem in clubfoot patients. 3Dgait analysis can be used in assessment of foot function and residual deviations in gait or possible relapses. Gait analysis is frequently used to analyse differences in gait between clubfoot and healthy controls. However, the usage of multisegment foot models is, although of importance considering the characteristics of the clubfoot, rare. In order to capture the full multi-planar and multi-joint nature of a clubfoot, it is highly important to implement multi-segment foot models in gait analysis. In order to improve treatment of individual relapse clubfoot kinematics differences in clinical relevant functional outcomes should be known.
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Nursing Leadership is an important competence to develop for providing quality of care and preventing attrition of nurses. This study looked into the perceptions and experiences of nurses on practising leadership related to performing bachelor nursing competencies. Next to that awareness of the development of nursing leadership was addressed.
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Key to reinforcement learning in multi-agent systems is the ability to exploit the fact that agents only directly influence only a small subset of the other agents. Such loose couplings are often modelled using a graphical model: a coordination graph. Finding an (approximately) optimal joint action for a given coordination graph is therefore a central subroutine in cooperative multi-agent reinforcement learning (MARL). Much research in MARL focuses on how to gradually update the parameters of the coordination graph, whilst leaving the solving of the coordination graph up to a known typically exact and generic subroutine. However, exact methods { e.g., Variable Elimination { do not scale well, and generic methods do not exploit the MARL setting of gradually updating a coordination graph and recomputing the joint action to select. In this paper, we examine what happens if we use a heuristic method, i.e., local search, to select joint actions in MARL, and whether we can use outcome of this local search from a previous time-step to speed up and improve local search. We show empirically that by using local search, we can scale up to many agents and complex coordination graphs, and that by reusing joint actions from the previous time-step to initialise local search, we can both improve the quality of the joint actions found and the speed with which these joint actions are found.
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Abstract Healthcare organizations operate within a network of governments, insurers, inspection services and other healthcare organizations to provide clients with the best possible care. The parties involved must collaborate and are accountable to each other for the care provided. This has led to a diversity of administrative processes that are supported by a multi-system landscape, resulting in administrative burdens among healthcare professionals. Management methods, such as Enterprise Architecture (EA), should help to develop and manage such landscapes, but they are systematic, while the network of healthcare parties is dynamic. The aim of this research is therefore to develop an EA framework that fits the dynamics of network organizations (such as long-term healthcare). This research proposal outlines the practical and scientific relevance of this research and the proposed method. The current status and next steps are also described.
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Pedagogy for gifted and talented students in higher education is the main topic of this study. Teachers of educational programmes designed for talented or highly motivated students in higher education (here called honours programmes) are challenged to stimulate students to increase the quality of their academic achievements. However, systematically acquired knowledge on effective teaching strategies for motivated and talented students above the age of 18 is limited (Heller, Mßnks, Sternberg & Subotnik, 2000). The aim of this study is to augment the existing body of knowledge. Firstly to reflect on this knowledge from different perspectives, secondly by a mix-method research, analysing multi-institutional data collected in the United States and the Netherlands about teachers perception on teaching strategies for gifted and motivated students in higher education. The theoretical perspectives behind this study focus on (1) theories about giftedness, (2) motivational theories and (3) on studies on honours programmes.
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The Heating Ventilation and Air Conditioning (HVAC) sector is responsible for a large part of the total worldwide energy consumption, a significant part of which is caused by incorrect operation of controls and maintenance. HVAC systems are becoming increasingly complex, especially due to multi-commodity energy sources, and as a result, the chance of failures in systems and controls will increase. Therefore, systems that diagnose energy performance are of paramount importance. However, despite much research on Fault Detection and Diagnosis (FDD) methods for HVAC systems, they are rarely applied. One major reason is that proposed methods are different from the approaches taken by HVAC designers who employ process and instrumentation diagrams (P&IDs). This led to the following main research question: Which FDD architecture is suitable for HVAC systems in general to support the set up and implementation of FDD methods, including energy performance diagnosis? First, an energy performance FDD architecture based on information embedded in P&IDs was elaborated. The new FDD method, called the 4S3F method, combines systems theory with data analysis. In the 4S3F method, the detection and diagnosis phases are separated. The symptoms and faults are classified into 4 types of symptoms (deviations from balance equations, operating states (OS) and energy performance (EP), and additional information) and 3 types of faults (component, control and model faults). Second, the 4S3F method has been tested in four case studies. In the first case study, the symptom detection part was tested using historical Building Management System (BMS) data for a whole year: the combined heat and power plant of the THUAS (The Hague University of Applied Sciences) building in Delft, including an aquifer thermal energy storage (ATES) system, a heat pump, a gas boiler and hot and cold water hydronic systems. This case study showed that balance, EP and OS symptoms can be extracted from the P&ID and the presence of symptoms detected. In the second case study, a proof of principle of the fault diagnosis part of the 4S3F method was successfully performed on the same HVAC system extracting possible component and control faults from the P&ID. A Bayesian Network diagnostic, which mimics the way of diagnosis by HVAC engineers, was applied to identify the probability of all possible faults by interpreting the symptoms. The diagnostic Bayesian network (DBN) was set up in accordance with the P&ID, i.e., with the same structure. Energy savings from fault corrections were estimated to be up to 25% of the primary energy consumption, while the HVAC system was initially considered to have an excellent performance. In the third case study, a demand-driven ventilation system (DCV) was analysed. The analysis showed that the 4S3F method works also to identify faults on an air ventilation system.
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A case study and method development research of online simulation gaming to enhance youth care knowlegde exchange. Youth care professionals affirm that the application used has enough relevance as an additional tool for knowledge construction about complex cases. They state that the usability of the application is suitable, however some remarks are given to adapt the virtual environment to the special needs of youth care knowledge exchange. The method of online simulation gaming appears to be useful to improve network competences and to explore the hidden professional capacities of the participant as to the construction of situational cognition, discourse participation and the accountability of intervention choices.
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