In dit artikel wordt eerst beschreven wat het verschil is tussen Evidence Based Practice (EBP) en Practice Based Evidence (PBE). Vervolgens wordt ingegaan op het toepassen van EBP en PBE in de praktijk. Dit gebeurt met behulp van de begrippen normativiteit en contextualiteit. Tot slot worden, in het licht van het voorafgaande, de rollen beschreven die de professional kan innemen ten aanzien van het verbeteren en ontwikkelen van zijn handelen. Aan bod komen de 'reflective practitioner', de 'evidence based practitioner' en de 'scientist practitioner'.
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Praktijkonderzoek over integratie van practice based evidence en evidence based practice, nderzoeksresultaten toepassen in de praktijk,verbeteren in en door de praktijk.
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Evidence-based practice krijgt in Groot-Brittannië net als in Nederland, steeds meer aandacht in de gezondheidszorg in het algemeen en in de verpleging in het bijzonder. Deze aandacht voor evidence-based practice (EBP) is vaak gericht op de betekenis van experimenteel onderzoek (Randomized Clinical Trials) voor de praktijk. Langzamerhand komt er ook meer aandacht voor andere onderzoeksdesigns. In onderzoek wordt ook steeds meer aandacht besteed aan de implementatie van EBP. Uit deze onderzoeken blijkt steeds weer dat implementatie van EBP een complexe aangelegenheid is. Niet alleen blijkt de beschikbare evidence van belang te zijn maar ook de wijze van facilitering en de context waarin de evidence geïmplementeerd moet worden. Minder aandacht is er echter voor de invloed van factoren op organisatie- en managementniveau en politieke factoren.
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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%.
Lectoraat, onderdeel van NHL Stenden Hogeschool
