INTRODUCTION: The conceptual ambiguity of the integrated care concept precludes a full understanding of what constitutes a well-integrated health system, posing a significant challenge in measuring the level of integrated care. Most available measures have been developed from a disease-specific perspective and only measure certain aspects of integrated care. Based on the Rainbow Model of Integrated Care, which provides a detailed description of the complex concept of integrated care, a measurement tool has been developed to assess integrated care within a care system as a whole gathered from healthcare providers' and managerial perspectives. This paper describes the methodology of a study seeking to validate the Rainbow Model of Integrated Care measurement tool within and across the Singapore Regional Health System. The Singapore Regional Health System is a recent national strategy developed to provide a better-integrated health system to deliver seamless and person-focused care to patients through a network of providers within a specified geographical region.METHODS: The validation process includes the assessment of the content of the measure and its psychometric properties.CONCLUSION: If the measure is deemed to be valid, the study will provide the first opportunity to measure integrated care within Singapore Regional Health System with the results allowing insights in making recommendations for improving the Regional Health System and supporting international comparison.
A review has been completed for a verification and validation (V&V) of the (Excel) BioGas simulator or EBS model. The EBS model calculates the environmental impact of biogas production pathways using Material and Energy Flow Analysis, time dependent dynamics, geographic information, and Life Cycle analysis. Within this article a V&V method is researched, selected and applied to validate the EBS model. Through the use of the method described within this article: mistakes in the model are resolved, the strengths and weaknesses of the model are found, and the concept of the model is tested and strengthened. The validation process does not only improve the model but also helps the modelers in widening their focus and scope. This article can, therefore, also be used in the validation process of similar models. The main result from the V&V process indicates that the EBS model is valid; however, it should be considered as an expert model and should only be used by expert users.
This study explores the psychometric qualities of the Relevance of History Measurement Scale (RHMS), a questionnaire designed to measure students’ beliefs about the relevance of history. Participants were 1459 Dutch secondary school students aged between 12 and 18. Data analysis revealed three reliable factors, compliant with our theoretical framework which defines three strands of relevance of history: relevance for building a personal identity, for citizenship, and for insight into ‘the human condition’. The convergent and known-groups validity of the RHMS was demonstrated. The collected data show that students find history more relevant as they grow older, with most progress taking place between 14 and 16. Out of the three strands of relevance, building a personal identity scores lowest in students’ appraisals. This study shows that the RHMS is psychometrically sound and can be used to evaluate effects of lesson interventions directed at enhancing the relevance of history to students.
Following the Samen met Muziek pilot research project in 2023-2024 in ZINN Zorg Short Stay rehabilitation departments in the locations De Brink and De Dilgt, REVA BEATS is a co-research project between the research group Music in Context and ZINN Zorg Short Stay departments revalidation of the location De Brink. In this mixed methods research, multiple research foci included: 1) aspects of care innovation and impact measurements will be researched by ZINN Zorg, and 2) aspects of musical expression, communication and wellbeing of musicians and participants, the entrepreneurial skills and development of musicians, and the learning and experiencing of collaborating care professionals will be explored by research group Music in Context. Additionally, there is a PhD-fellow from the HKU researching the practice through the lens of care ethics. The REVA BEATS project will run between February 2025-January 2027, and includes in total 12 music projects, while the preparational work of the projects has started in June 2024.
In het forensisch werkveld staan drie vragen centraal. Het gaat dan om “wie is het”, “wat is er gebeurd” en “wanneer is het gebeurd”. Alle informatie die bijdraagt aan het beantwoorden van deze vragen is waardevol in zaakonderzoeken. Vaak wordt er wel een biologisch spoor gevonden, maar is er geen “match” met de databank. In dit geval kan profileringsinformatie helpen bij het zoeken naar de juiste persoon. Met profilering wordt hier bedoeld een serie stoffen, ook markers genoemd, die informatie geven over de levensstijl van mensen. De levensstijl kan bestaan uit kenmerken, voeding, gewoonten en activiteiten. Een recent voorbeeld van een profileringsmethode is het analyseren van de buitenzijde van mobiele telefoons. Door het hanteren van de telefoon laten mensen zweet en stoffen achter die gekarakteriseerd kunnen worden. Het profiel van deze stoffen geeft een beschrijving van de levensstijl van de eigenaar. In veel zaken zijn er echter geen mobiele telefoon aanwezig, maar wel andere sporen zoals haar. Daarom is er behoefte aan een methode om haar te gebruiken voor profilering. Bovendien geeft haar een indicatie van tijd en gebeurtenissen uit het verleden omdat het langzaam groeit. In principe kan er dan informatie over de drie vragen (wie, wat, wanneer) verzameld worden. Haren worden op dit moment vooral gebruikt voor het meten van drugs, alcohol gebruik, cortisol en nicotine. Er is echter behoefte aan een breder palet van stoffen dat in één keer in haar kan worden gemeten. Het doel van dit onderzoek is daarom het ontwikkelen van een methode waarmee in één analysegang een profiel van circa 15 uiteenlopende markers kan worden gemeten.
Post-earthquake structural damage shows that wall collapse is one of the most common failure mechanisms in unreinforced masonry buildings. It is expected to be a critical issue also in Groningen, located in the northern part of the Netherlands, where human-induced seismicity has become an uprising problem in recent years. The majority of the existing buildings in that area are composed of unreinforced masonry; they were not designed to withstand earthquakes since the area has never been affected by tectonic earthquakes. They are characterised by vulnerable structural elements such as slender walls, large openings and cavity walls. Hence, the assessment of unreinforced masonry buildings in the Groningen province has become of high relevance. The abovementioned issue motivates engineering companies in the region to research seismic assessments of the existing structures. One of the biggest challenges is to be able to monitor structures during events in order to provide a quick post-earthquake assessment hence to obtain progressive damage on structures. The research published in the literature shows that crack detection can be a very powerful tool as an assessment technique. In order to ensure an adequate measurement, state-of-art technologies can be used for crack detection, such as special sensors or deep learning techniques for pixel-level crack segmentation on masonry surfaces. In this project, a new experiment will be run on an in-plane test setup to systematically propagate cracks to be able to detect cracks by new crack detection tools, namely digital crack sensor and vision-based crack detection.
