The transition taking place within the Dutch healthcare system has been a central theme in politics and public debate for decades. The recent changes again demand the full attention of researchers and educators in the field. In this article, we reflect on the current ideology and goals of the transition and link these to the range of ideas that lie behind the ideal of “community care”. Additionally, we pose the question of what these changes may mean for research and education within the social care domain in general and for our research group in particular. The AUAS Community Care Research Group covers a variety of research topics that are clustered into three “streams”: informal care, social inclusion and network strengthening. Within these streams, we focus on care by society and link this to professional caregiving. We will also explain why our research interests are specifically relevant in the context of the transition of the healthcare system, as this transition explicitly accentuates the importance of a “caring society” and thus a change in role for the care professional. We will also reflect on how we can best translate our research results into the curriculum of education programmes for students who will soon work as professionals in the social and/or care domains.
The ageing of people with intellectual disabilities, with associated morbidity like dementia, calls for new types of care. Person-centered methods may support care staff in providing this, an example being Dementia Care Mapping (DCM). DCM has been shown to be feasible in ID-care. We examined the experiences of ID-professionals in using DCM. We performed a mixed-methods study, using quantitative data from care staff (N = 136) and qualitative data (focus-groups, individual interviews) from care staff, group home managers and DCM-in-intellectual disabilities mappers (N = 53). ageing, dementia, Dementia Care Mapping, intellectual disability, mixed-methods, personcentred care
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Transitions in health care and the increasing pace at which technological innovations emerge, have led to new professional approach at the crossroads of health care and technology. In order to adequately deal with these transition processes and challenges before future professionals access the labour market, Fontys University of Applied Sciences is in a transition to combining education with interdisciplinary practice-based research. Fontys UAS is launching a new centre of expertise in Health Care and Technology, which is a new approach compared to existing educational structures. The new centre is presented as an example of how new initiatives in the field of education and research at the intersection of care and technology can be shaped.
Receiving the first “Rijbewijs” is always an exciting moment for any teenager, but, this also comes with considerable risks. In the Netherlands, the fatality rate of young novice drivers is five times higher than that of drivers between the ages of 30 and 59 years. These risks are mainly because of age-related factors and lack of experience which manifests in inadequate higher-order skills required for hazard perception and successful interventions to react to risks on the road. Although risk assessment and driving attitude is included in the drivers’ training and examination process, the accident statistics show that it only has limited influence on the development factors such as attitudes, motivations, lifestyles, self-assessment and risk acceptance that play a significant role in post-licensing driving. This negatively impacts traffic safety. “How could novice drivers receive critical feedback on their driving behaviour and traffic safety? ” is, therefore, an important question. Due to major advancements in domains such as ICT, sensors, big data, and Artificial Intelligence (AI), in-vehicle data is being extensively used for monitoring driver behaviour, driving style identification and driver modelling. However, use of such techniques in pre-license driver training and assessment has not been extensively explored. EIDETIC aims at developing a novel approach by fusing multiple data sources such as in-vehicle sensors/data (to trace the vehicle trajectory), eye-tracking glasses (to monitor viewing behaviour) and cameras (to monitor the surroundings) for providing quantifiable and understandable feedback to novice drivers. Furthermore, this new knowledge could also support driving instructors and examiners in ensuring safe drivers. This project will also generate necessary knowledge that would serve as a foundation for facilitating the transition to the training and assessment for drivers of automated vehicles.
