This project builds upon a collaboration which has been established since 15 years in the field of social work between teachers and lecturers of Zuyd University, HU University and Elte University. Another network joining this project was CARe Europe, an NGO aimed at improving community care throughout Europe. Before the start of the project already HU University, Tallinn Mental Health Centre and Kwintes were participating in this network. In the course of several international meetings (e.g. CARe Europe conference in Prague in 2005, ENSACT conferences in Dubrovnik in 2009, and Brussels in April 2011, ESN conference in Brussels in March 2011), and many local meetings, it became clear that professionals in the social sector have difficulties to change current practices. There is a great need to develop new methods, which professionals can use to create community care.
Objective: To evaluate the preliminary effectiveness of a goal-directed movement intervention using a movement sensor on physical activity of hospitalized patients. Design: Prospective, pre-post study. Setting: A university medical center. Participants: Patients admitted to the pulmonology and nephrology/gastro-enterology wards. Intervention: The movement intervention consisted of (1) self-monitoring of patients' physical activity, (2) setting daily movement goals and (3) posters with exercises and walking routes. Physical activity was measured with a movement sensor (PAM AM400) which measures active minutes per day. Main measures: Primary outcome was the mean difference in active minutes per day pre- and post-implementation. Secondary outcomes were length of stay, discharge destination, immobility-related complications, physical functioning, perceived difficulty to move, 30-day readmission, 30-day mortality and the adoption of the intervention. Results: A total of 61 patients was included pre-implementation, and a total of 56 patients was included post-implementation. Pre-implementation, patients were active 38 ± 21 minutes (mean ± SD) per day, and post-implementation 50 ± 31 minutes per day (Δ12, P = 0.031). Perceived difficulty to move decreased from 3.4 to 1.7 (0-10) (Δ1.7, P = 0.008). No significant differences were found in other secondary outcomes. Conclusions: The goal-directed movement intervention seems to increase physical activity levels during hospitalization. Therefore, this intervention might be useful for other hospitals to stimulate inpatient physical activity.
Background: Up to one third of all stroke patients suffer fromone or more psychosocial impairments. Recognition and treatment of these impairments are essential in improving psychosocial well-being after stroke. Although nurses are ideally positioned to address psychosocial well-being, they often feel insecure about providing the needed psychosocial care. Therefore, we expect that providing nurses with better knowledge to deliver this care could lead to an improvement in psychosocialwell-being after stroke. Currently it is not knownwhich interventions are effective and what aspects of these interventions are most effective to improve psychosocial wellbeing after stroke. Objective: To identify potentially effective interventions – and intervention components – which can be delivered by nurses to improve patients' psychosocial well-being after stroke. Methods: A systematic review and data synthesis of randomized controlled trials and quasi experimental studies was conducted. Papers were included according to the following criteria: 1) before-after design, 2) all types of stroke patients, 3) interventions that can be delivered by nurses, 4) the primary outcome(s) were psychosocial. PubMed, Embase, PsychInfo, CINAHL and Cochrane library were searched (August 2019–April 2022). Articles were selected based on title, abstract, full text and quality. Quality was assessed by using Joanna Briggs Institute checklists and a standardized data extraction form developed by Joanna Brigss Institute was used to extract the data. Results: In total 60 studies were included, of which 52 randomized controlled trials, three non-randomized controlled trials, four quasi-experimental studies, and one randomized cross-over study. Nineteen studies had a clear psychosocial content, twenty-nine a partly psychosocial content, and twelve no psychosocial content. Thirty-nine interventions that showed positive effects on psychosocial well-being after stroke were identified. Effective intervention topics were found to be mood, recovery, coping, emotions, consequences/problems after stroke, values and needs, risk factors and secondary prevention, self-management, andmedicationmanagement. Active information and physical exercise were identified as effective methods of delivery. Discussion: The results suggest that interventions to improve psychosocial well-being should include the intervention topics and methods of delivery that were identified as effective. Since effectiveness of the intervention can depend on the interaction of intervention components, these interactions should be studied. Nurses and patients should be involved in the development of such interventions to ensure it can be used by nurses and will help improve patients' psychosocial well-being.
The focus of this project is on improving the resilience of hospitality Small and Medium Enterprises (SMEs) by enabling them to take advantage of digitalization tools and data analytics in particular. Hospitality SMEs play an important role in their local community but are vulnerable to shifts in demand. Due to a lack of resources (time, finance, and sometimes knowledge), they do not have sufficient access to data analytics tools that are typically available to larger organizations. The purpose of this project is therefore to develop a prototype infrastructure or ecosystem showcasing how Dutch hospitality SMEs can develop their data analytic capability in such a way that they increase their resilience to shifts in demand. The one year exploration period will be used to assess the feasibility of such an infrastructure and will address technological aspects (e.g. kind of technological platform), process aspects (e.g. prerequisites for collaboration such as confidentiality and safety of data), knowledge aspects (e.g. what knowledge of data analytics do SMEs need and through what medium), and organizational aspects (what kind of cooperation form is necessary and how should it be financed).
Currently, many novel innovative materials and manufacturing methods are developed in order to help businesses for improving their performance, developing new products, and also implement more sustainability into their current processes. For this purpose, additive manufacturing (AM) technology has been very successful in the fabrication of complex shape products, that cannot be manufactured by conventional approaches, and also using novel high-performance materials with more sustainable aspects. The application of bioplastics and biopolymers is growing fast in the 3D printing industry. Since they are good alternatives to petrochemical products that have negative impacts on environments, therefore, many research studies have been exploring and developing new biopolymers and 3D printing techniques for the fabrication of fully biobased products. In particular, 3D printing of smart biopolymers has attracted much attention due to the specific functionalities of the fabricated products. They have a unique ability to recover their original shape from a significant plastic deformation when a particular stimulus, like temperature, is applied. Therefore, the application of smart biopolymers in the 3D printing process gives an additional dimension (time) to this technology, called four-dimensional (4D) printing, and it highlights the promise for further development of 4D printing in the design and fabrication of smart structures and products. This performance in combination with specific complex designs, such as sandwich structures, allows the production of for example impact-resistant, stress-absorber panels, lightweight products for sporting goods, automotive, or many other applications. In this study, an experimental approach will be applied to fabricate a suitable biopolymer with a shape memory behavior and also investigate the impact of design and operational parameters on the functionality of 4D printed sandwich structures, especially, stress absorption rate and shape recovery behavior.
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.
