Background: Due to multimorbidity and geriatric problems, older people often require both psychosocial and medical care. Collaboration between medical and social professionals is a prerequisite to deliver high-quality care for community-living older people. Effective, safe, and person-centered care relies on skilled interprofessional collaboration and practice. Little is known about interprofessional education to increase interprofessional collaboration in practice (IPCP) in the context of community care for older people. This study examines the feasibility of the implementation of an IPCP program in three community districts and determines its potential to increase interprofessional collaboration between primary healthcare professionals caring for older people. Method: A feasibility study was conducted to determine the acceptability and feasibility of data collection and analysis regarding interprofessional collaboration in network development. A questionnaire was used to measure the learning experience and the acquisition of knowledge and skills regarding the program. Network development was assessed by distributing a social network survey among professionals attending the program as well as professionals not attending the program at baseline and 5.5 months after. Network development was determined by calculating the number, reciprocity, value, and diversity of contacts between professionals using social network analysis. Results: The IPCP program was found to be instructive and the knowledge and skills gained were applicable in practice. Social network analysis was feasible to conduct and revealed a spill-over effect regarding network development. Program participants, as well as non-program participants, had larger, more reciprocal, and more diverse interprofessional networks than they did before the program. Conclusions: This study showed the feasibility of implementing an IPCP program in terms of acceptability, feasibility of data collection, and social network analysis to measure network development, and indicated potential to increase interprofessional collaboration between primary healthcare professionals. Both program participants and non-program participants developed a larger, more collaborative, and diverse interprofessional network.
Data collection is crucial in modern automotive engineering. Yet, the focus on technological development often overlooks legal, ethical, and privacy aspects. This feasibility study aims to bridge this knowledge gap for SMEs and research entities by examining the technical, legal, and ethical aspects impacting vehicle data collection. It provides a guide for organisations within the European context with a global perspective. The crucial importance of each aspect is highlighted within the modern context of connected vehicles, increasing cyber-attacks and the legal demands of handling and processing data. This report provides guidelines for hardware selection, software development, data handling and storage, cybersecurity, and privacy and legal compliance. It discusses the considerations for choosing data collection hardware, outlines the software methodologies for data acquisition and cloud synchronization, and provides an overview of cybersecurity in the context of automotive applications. The report also covers the handling and storage of both low-throughput and high-throughput data, with a focus on data types, retrieval, and storage options. It concludes with a discussion on legal aspects, particularly data ownership, protection under GDPR, and liability implications. The importance of these topics in the modern context of IoT connectivity, edge computing and the application of various AI technologies cannot be understated. The broad applications of such technologies encourages the use of data standards and interoperability for modern connected and autonomous vehicles. This document serves as a guide for SMEs and research entities involved in automotive data collection, providing information so they may better navigate and understand the complexities of modern automotive data collection, ensuring they consider all aspects. It highlights the importance of interdisciplinary expertise for modern automotive data collection and bridges the gaps in knowledge that organisations may have within a number of important topics for data collection. By bridging knowledge gaps, the report empowers organisations to make informed decisions about automotive data collection, ensuring accuracy, efficiency, and legal compliance.
Just-in-time adaptive intervention (JITAI) has gained attention recently and previous studies have indicated that it is an effective strategy in the field of mobile healthcare intervention. Identifying the right moment for the intervention is a crucial component. In this paper the reinforcement learning (RL) technique has been used in a smartphone exercise application to promote physical activity. This RL model determines the ‘right’ time to deliver a restricted number of notifications adaptively, with respect to users’ temporary context information (i.e., time and calendar). A four-week trial study was conducted to examine the feasibility of our model with real target users. JITAI reminders were sent by the RL model in the fourth week of the intervention, while the participants could only access the app’s other functionalities during the first 3 weeks. Eleven target users registered for this study, and the data from 7 participants using the application for 4 weeks and receiving the intervening reminders were analyzed. Not only were the reaction behaviors of users after receiving the reminders analyzed from the application data, but the user experience with the reminders was also explored in a questionnaire and exit interviews. The results show that 83.3% reminders sent at adaptive moments were able to elicit user reaction within 50 min, and 66.7% of physical activities in the intervention week were performed within 5 h of the delivery of a reminder. Our findings indicated the usability of the RL model, while the timing of the moments to deliver reminders can be further improved based on lessons learned.
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).
Students in Higher Music Education (HME) are not facilitated to develop both their artistic and academic musical competences. Conservatoires (professional education, or ‘HBO’) traditionally foster the development of musical craftsmanship, while university musicology departments (academic education, or ‘WO’) promote broader perspectives on music’s place in society. All the while, music professionals are increasingly required to combine musical and scholarly knowledge. Indeed, musicianship is more than performance, and musicology more than reflection—a robust musical practice requires people who are versed in both domains. It’s time our education mirrors this blended profession. This proposal entails collaborative projects between a conservatory and a university in two cities where musical performance and musicology equally thrive: Amsterdam (Conservatory and University of Amsterdam) and Utrecht (HKU Utrechts Conservatorium and Utrecht University). Each project will pilot a joint program of study, combining existing modules with newly developed ones. The feasibility of joint degrees will be explored: a combined bachelor’s degree in Amsterdam; and a combined master’s degree in Utrecht. The full innovation process will be translated to a transferable infrastructural model. For 125 students it will fuse praxis-based musical knowledge and skills, practice-led research and academic training. Beyond this, the partners will also use the Comenius funds as a springboard for collaboration between the two cities to enrich their respective BA and MA programs. In the end, the programme will diversify the educational possibilities for students of music in the Netherlands, and thereby increase their professional opportunities in today’s job market.
Size measurement plays an essential role for micro-/nanoparticle characterization and property evaluation. Due to high costs, complex operation or resolution limit, conventional characterization techniques cannot satisfy the growing demand of routine size measurements in various industry sectors and research departments, e.g., pharmaceuticals, nanomaterials and food industry etc. Together with start-up SeeNano and other partners, we will develop a portable compact device to measure particle size based on particle-impact electrochemical sensing technology. The main task in this project is to extend the measurement range for particles with diameters ranging from 20 nm to 20 um and to validate this technology with realistic samples from various application areas. In this project a new electrode chip will be designed and fabricated. It will result in a workable prototype including new UMEs (ultra-micro electrode), showing that particle sizing can be achieved on a compact portable device with full measuring range. Following experimental testing with calibrated particles, a reliable calibration model will be built up for full range measurement. In a further step, samples from partners or potential customers will be tested on the device to evaluate the application feasibility. The results will be validated by high-resolution and mainstream sizing techniques such as scanning electron microscopy (SEM), dynamic light scattering (DLS) and Coulter counter.
