Light therapy is applied as treatment for a variety of problems related to health and ageing, including dementia. Light therapy is administered via light boxes, light showers, and ambient bright light using ceiling-mounted luminaires. Long-term care facilities are currently installing dynamic lighting systems with the aim to improve the well-being of residents with dementia and to decrease behavioural symptoms. The aim of this chapter is to provide an overview of the application of ceiling-mounted dynamic lighting systems as a part of intelligent home automation systems found in healthcare facilities. Examples of such systems are provided and their implementation in practice is discussed. The available, though limited, knowledge has not yet been converted into widespread implementable lighting solutions, and the solutions available are often technologically unsophisticated and poorly evaluated from the perspective of end-users. New validated approaches to the design and application of ambient bright light are needed.
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Section snippetsClosing observationsThe overview of the articles presented in this special issue demonstrates that sport psychology does indeed represent a very broad domain of investigation and application. When reading the articles, one will observe that a spectrum of different approaches are applied, ranging from approaches that lean toward the ‘hard’ sciences (such as the experimental study of perceptual anticipation), to approaches that lean toward the ‘soft’ sciences (such as the descriptive study of problems facingPeter Jan Beek, Ph.D., is Full Professor of Coordination Dynamics and the Dean of the Faculty of Behavioural and Movement Sciences at the Vrije Universiteit Amsterdam. His research focuses on the control and coordination of human movement and changes therein as a function of development, learning and rehabilitation. Recurrent topics in his research are the perceptual guidance of movements and the role of practice, feedback and instruction in skill acquisition.
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Complex interventions are criticized for being a “black box”, which makes it difficult to determine why they succeed or fail. Recently, nine proactive primary-care programs aiming to prevent functional decline in older adults showed inconclusive effects. The aim of this study was to systematically unravel, compare, and synthesize the development and evaluation of nine primary-care programs within a controlled trial to further improve the development and evaluation of complex interventions. A systematic overview of all written data on the nine proactive primary-care programs was conducted using a validated item list.
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Abstract from article: The Dutch healthcare system has changed towards a system of regulated competition to contain costs and to improve efficiency and quality of care. This paper provides: (1) a brief as-is overview of the changes for primary care, based on explorative literature reviews; (2) provides noteworthy remarks as for the way primary and secondary healthcare is organised; (3) an example of an E-health portal illustrating implemented processes within the Dutch context and (4) a proposed research agenda on various e-health topics. Noteworthy remarks are: (1) government, insurer, healthcare provider and patient are main actors within the Dutch healthcare system; (2) general practitioners (GP’s) are gatekeepers to secondary and other care providers; (3) the illustrated portal with a patient oriented design, provides access to applications implemented at care providers resulting in increased electronic availability and increased patient satisfaction; (4) a variety of fragmented information systems at health care providers exists, which leaves room for standardisation and increased efficiency. We end with suggestions for future research.
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This extended abstract introduces the work of the Netherlands AI Media and Democracy lab, especially focusing on the research performed from an AI/computer science perspective at CWI, the Netherlands National Research Center for Mathematics and Computer Science in Amsterdam. We first provide an overview of the general aims and set-up of the lab, and then focuses in on the research areas of the 3 research groups at CWI, outlining there are of research and expected research contributions in the areas between AI and media & democracy
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In Western societies, the vast majority of people with dementia live at home and wish to remain doing so for as long as possible. Aging in place can be facilitated through a variety of environmental interventions, including home modifications. This article provides an overview of existing design principles and design goals, and environmental interventions implemented at home, based on literature study and additional focus group sessions. There is a multitude of design principles, design goals, and environmental interventions available to assist with activities of daily living and functions, although few systematic studies have been conducted on the efficacy of these goals and interventions. The own home seems to be a largely ignored territory in research and government policies, which implies that many problems concerning aging in place and environmental interventions for dementia are not adequately dealt with.
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Inaugural address of Frederike Praasterink, Professor Future Food Systems 22 February 2018. Three important principles contribute to the transformation of food systems: - Redesign food systems from ‘less bad’ to ‘net positive’ - Reconnect consumers, producers, youth - Revalue food through true cost accounting and new business models
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This document combines four reports on existing regional business support programmes for inclusion or understanding of circular economy (CE) objectives, deliverable DT3.1.2 from the transform-CE project. Besides a general overview on national and regional level, the focus is on a selection of national and regional programmes aimed at the plastics industry. After explaining the format to structure the programmes, the results for the four regions are presented: Greater Manchester (UK), Rhineland Palatinate and North-Rhine Westphalia (DE), Wallonia (BE), Central Netherlands (NL).
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Background: Although physical activity (PA) has positive effects on health and well-being, physical inactivity is a worldwide problem. Mobile health interventions have been shown to be effective in promoting PA. Personalizing persuasive strategies improves intervention success and can be conducted using machine learning (ML). For PA, several studies have addressed personalized persuasive strategies without ML, whereas others have included personalization using ML without focusing on persuasive strategies. An overview of studies discussing ML to personalize persuasive strategies in PA-promoting interventions and corresponding categorizations could be helpful for such interventions to be designed in the future but is still missing. Objective: First, we aimed to provide an overview of implemented ML techniques to personalize persuasive strategies in mobile health interventions promoting PA. Moreover, we aimed to present a categorization overview as a starting point for applying ML techniques in this field. Methods: A scoping review was conducted based on the framework by Arksey and O’Malley and the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) criteria. Scopus, Web of Science, and PubMed were searched for studies that included ML to personalize persuasive strategies in interventions promoting PA. Papers were screened using the ASReview software. From the included papers, categorized by the research project they belonged to, we extracted data regarding general study information, target group, PA intervention, implemented technology, and study details. On the basis of the analysis of these data, a categorization overview was given. Results: In total, 40 papers belonging to 27 different projects were included. These papers could be categorized in 4 groups based on their dimension of personalization. Then, for each dimension, 1 or 2 persuasive strategy categories were found together with a type of ML. The overview resulted in a categorization consisting of 3 levels: dimension of personalization, persuasive strategy, and type of ML. When personalizing the timing of the messages, most projects implemented reinforcement learning to personalize the timing of reminders and supervised learning (SL) to personalize the timing of feedback, monitoring, and goal-setting messages. Regarding the content of the messages, most projects implemented SL to personalize PA suggestions and feedback or educational messages. For personalizing PA suggestions, SL can be implemented either alone or combined with a recommender system. Finally, reinforcement learning was mostly used to personalize the type of feedback messages. Conclusions: The overview of all implemented persuasive strategies and their corresponding ML methods is insightful for this interdisciplinary field. Moreover, it led to a categorization overview that provides insights into the design and development of personalized persuasive strategies to promote PA. In future papers, the categorization overview might be expanded with additional layers to specify ML methods or additional dimensions of personalization and persuasive strategies.
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The transition from institutional to community care for vulnerable people has been shaping the welfare system in Europe over the last decades. For the period of 2014-20 deinstitutionalization became one of the highlighted priorities of the European Commission in order to promote reforms in disability and mental health care in the convergence regions, too. Between 2007 and 2013, Estonia as many other Eastern European countries has implemented the first wave of deinstitutionalization and during the new EU budget period a second wave will be occurred in order to continue and hopefully complete the transition. In this study, we try to give an overview on the experiences of different European countries highlighting good practices and possible pitfalls. This study has been conducted at the request of the Estonian Ministry of Social Affairs.
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