Aims and objectives: To describe the process of implementing evidence-based practice (EBP) in a clinical nursing setting. Background: EBP has become a major issue in nursing, it is insufficiently integrated in daily practice and its implementation is complex. Design: Participatory action research. Method: The main participants were nurses working in a lung unit of a rural hospital. A multi-method process of data collection was used during the observing, reflecting, planning and acting phases. Data were continuously gathered during a 24-month period from 2010 to 2012, and analysed using an interpretive constant comparative approach. Patients were consulted to incorporate their perspective. Results: A best-practice mode of working was prevalent on the ward. The main barriers to the implementation of EBP were that nurses had little knowledge of EBP and a rather negative attitude towards it, and that their English reading proficiency was poor. The main facilitators were that nurses wanted to deliver high-quality care and were enthusiastic and open to innovation. Implementation strategies included a tailored interactive outreach training and the development and implementation of an evidence-based discharge protocol. The academic model of EBP was adapted. Nurses worked according to the EBP discharge protocol but barely recorded their activities. Nurses favourably evaluated the participatory action research process. Conclusions: Action research provides an opportunity to empower nurses and to tailor EBP to the practice context. Applying and implementing EBP is difficult for front-line nurses with limited EBP competencies. Relevance to clinical practice: Adaptation of the academic model of EBP to a more pragmatic approach seems necessary to introduce EBP into clinical practice. The use of scientific evidence can be facilitated by using pre-appraised evidence. For clinical practice, it seems relevant to integrate scientific evidence with clinical expertise and patient values in nurses’ clinical decision making at the individual patient level.
This thesis describes an Action Research (AR) project aimed at the implementation of Evidence Based Practice in a mental health nursing setting in the Netherlands. The main research question addressed in this thesis is: In what way is Action Research with an empowering appropriate to implement Evidence Based Practice in a mental health nursing setting in the Netherlands and what is the effect of this implementation on the care experienced by the client, the nursing interventions and the context in this setting compared to a comparative setting? To answer this main research question, the following questions derived from it were addressed: What is Evidence Based Practice? What is known about implementing evidence-based practice in nursing through Action Research? Which factors have to be dealt with in a mental health nursing setting, so the implementation of EBP with AR with an empowering intent will be more successful? Which factors have to be dealt with in a mental health nursing setting, so the implementation of EBP with AR with an empowering intent will be successful? How is EBP implemented through AR with an empowering intent and what are the outcomes for the use of evidence, the context and the facilitation in the setting? What is the effect of the implementation of EBP in mental health nursing using AR with an empowering intent on the care experienced by the client, the nursing interventions and the context compared to a comparison setting? The first two questions were answered by a search of the literature while the remaining questions were answered during the AR study conducted in two mental health organisations in the Netherlands.
Producing evidence that can be used in court is a central goal of criminal investigations. Forensic science focuses with considerable success on the production of pieces of evidence from specific sources. However, less is known about how a team of investigating police officers progressively produces a body of evidence during the course of a criminal investigation. This literature review uses Weickian sensemaking to analyse what is known about this process in criminal investigations into organised crime. Focusing on the criminal investigation team, collective sensemaking is used as a lens through which to place the reasoning processes used in constructing evidence in a social context. In addition to describing three constituent parts of collective sensemaking relevant for criminal investigations, six factors are identified that influence the quality of collective sensemaking. Building on these results, nine focal points are presented for analysing the sensemaking processes in a criminal investigation team, aimed at advancing knowledge about the production of evidence in criminal investigations of organised crime. Furthermore, a definition of evidence is developed that is suitable for studying sensemaking in the context of an ongoing criminal investigation.
Developing a framework that integrates Advanced Language Models into the qualitative research process.Qualitative research, vital for understanding complex phenomena, is often limited by labour-intensive data collection, transcription, and analysis processes. This hinders scalability, accessibility, and efficiency in both academic and industry contexts. As a result, insights are often delayed or incomplete, impacting decision-making, policy development, and innovation. The lack of tools to enhance accuracy and reduce human error exacerbates these challenges, particularly for projects requiring large datasets or quick iterations. Addressing these inefficiencies through AI-driven solutions like AIDA can empower researchers, enhance outcomes, and make qualitative research more inclusive, impactful, and efficient.The AIDA project enhances qualitative research by integrating AI technologies to streamline transcription, coding, and analysis processes. This innovation enables researchers to analyse larger datasets with greater efficiency and accuracy, providing faster and more comprehensive insights. By reducing manual effort and human error, AIDA empowers organisations to make informed decisions and implement evidence-based policies more effectively. Its scalability supports diverse societal and industry applications, from healthcare to market research, fostering innovation and addressing complex challenges. Ultimately, AIDA contributes to improving research quality, accessibility, and societal relevance, driving advancements across multiple sectors.
Horse riding falls under the “Sport for Life” disciplines, where a long-term equestrian development can provide a clear pathway of developmental stages to help individuals, inclusive of those with a disability, to pursue their goals in sport and physical activity, providing long-term health benefits. However, the biomechanical interaction between horse and (disabled) rider is not wholly understood, leaving challenges and opportunities for the horse riding sport. Therefore, the purpose of this KIEM project is to start an interdisciplinary collaboration between parties interested in integrating existing knowledge on horse and (disabled) rider interaction with any novel insights to be gained from analysing recently collected sensor data using the EquiMoves™ system. EquiMoves is based on the state-of-the-art inertial- and orientational-sensor system ProMove-mini from Inertia Technology B.V., a partner in this proposal. On the basis of analysing previously collected data, machine learning algorithms will be selected for implementation in existing or modified EquiMoves sensor hardware and software solutions. Target applications and follow-ups include: - Improving horse and (disabled) rider interaction for riders of all skill levels; - Objective evidence-based classification system for competitive grading of disabled riders in Para Dressage events; - Identifying biomechanical irregularities for detecting and/or preventing injuries of horses. Topic-wise, the project is connected to “Smart Technologies and Materials”, “High Tech Systems & Materials” and “Digital key technologies”. The core consortium of Saxion University of Applied Sciences, Rosmark Consultancy and Inertia Technology will receive feedback to project progress and outcomes from a panel of international experts (Utrecht University, Sport Horse Health Plan, University of Central Lancashire, Swedish University of Agricultural Sciences), combining a strong mix of expertise on horse and rider biomechanics, veterinary medicine, sensor hardware, data analysis and AI/machine learning algorithm development and implementation, all together presenting a solid collaborative base for derived RAAK-mkb, -publiek and/or -PRO follow-up projects.
Due to the existing pressure for a more rational use of the water, many public managers and industries have to re-think/adapt their processes towards a more circular approach. Such pressure is even more critical in the Rio Doce region, Minas Gerais, due to the large environmental accident occurred in 2015. Cenibra (pulp mill) is an example of such industries due to the fact that it is situated in the river basin and that it has a water demanding process. The current proposal is meant as an academic and engineering study to propose possible solutions to decrease the total water consumption of the mill and, thus, decrease the total stress on the Rio Doce basin. The work will be divided in three working packages, namely: (i) evaluation (modelling) of the mill process and water balance (ii) application and operation of a pilot scale wastewater treatment plant (iii) analysis of the impacts caused by the improvement of the process. The second work package will also be conducted (in parallel) with a lab scale setup in The Netherlands to allow fast adjustments and broaden evaluation of the setup/process performance. The actions will focus on reducing the mill total water consumption in 20%.
