Ook uit internationaal wetenschappelijk onderzoek blijkt dat er verschillen zijn tussen ouderen in de stad en op het platteland [3-5]. In de rijke delen van de Europese Unie hebben ouderen in de landelijke gebieden een hogere levenstevredenheid dan in de stad. Mensen lijken tevreden in een dorp, wellicht omdat het verwachtingspatroon geringer is. Als het op veroudering aankomt, biedt de hogere dichtheid van de stad een grotere nabijheid tot allerlei diensten die de kwaliteit van leven van ouderen vergroten. Door specifieke economische factoren kunnen deze diensten niet in dezelfde mate worden aangeboden in landelijke gebieden [6]. Woonomstandigheden, zo blijkt uit onderzoek [7], zijn beter voor onze ouderen in de stad dan op het platteland, hoewel de verschillen niet zo uitgesproken groot zijn. En dan heb je nog de gesegregeerde woonwijken voor ouderen, zoals in de Verenigde Staten. Denk daarbij aan Sun City Arizona en The Villages in Florida [8, 9]. Deze wijken bieden een eenheidsworst en zonderen ouderen af in een cocon van geboden comfort, waarbij zij verdwijnen uit het reguliere straatbeeld van omliggende steden. Een in vrijheid gekozen gevangenschap. Een echte seniorvriendelijke stad is een generatievriendelijke stad zoals u wilt, waar niet alleen ruimte is voor één generatie, maar voor alle generaties: van wieg tot graf.
BACKGROUND: Consideration of older adults' quality of life (QoL) is becoming increasingly important in the evaluation, quality improvement and allocation of health and social care services. While numerous definitions and theories of QoL have been proposed, an overall synthesis of the perspective of older adults themselves is lacking.METHODS: Qualitative studies were identified in PubMed, Ebsco/Psycinfo and Ebsco/CINAHL, through a search on 28 November 2018. Articles needed to meet all of the following criteria: (i) focus on perceptions of QoL, (ii) older adults living at home as main participants, (iii) use of qualitative methodology, (iv) conducted in a Western country and (v) published in English (vi) not focused on specific patient groups. A thematic synthesis was conducted of the selected studies, using the complete 'findings/results' sections from the papers.RESULTS: We included 48 qualitative studies representing the views of more than 3,400 older adults living at home in 11 Western countries. The QoL aspects identified in the synthesis were categorized into nine QoL domains: autonomy, role and activity, health perception, relationships, attitude and adaptation, emotional comfort, spirituality, home and neighbourhood, and financial security. The results showed that although different domains can be distinguished, these are also strongly connected.CONCLUSION: QoL can be expressed in a number of domains and related subthemes that are important for older adults living at home. The findings further support that the concept of QoL should be seen as a dynamic web of intertwined domains.
Leisure travelling is known to be a contributor to visitors’ well-being and quality of life yet only little is known about the influence of tourism on the destination residents’ quality of life. Given rising imbalances and perceived conflicts of use between visitors and residents particularly in an urban context, research interest in residents’ perspectives have increased and new measures such as the tourism acceptance score have been developed to measure perceived tourism impacts over time. While tourism intensity has been proposed to be an indicator for low tourism acceptance and decreasing quality of life, little empirical evidence is existing. This study examines the relationship between tourism acceptance and perceived quality of life and the moderating role of tourism intensity. The data base used consisted of representative samples in 11 German cities. Results demonstrate a positive relationship between personal tourism acceptance and the residents’ quality of live. This relationship is moderated by the tourism intensity and is generally stronger in cities with higher tourism intensity.
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Huntington’s disease (HD) and various spinocerebellar ataxias (SCA) are autosomal dominantly inherited neurodegenerative disorders caused by a CAG repeat expansion in the disease-related gene1. The impact of HD and SCA on families and individuals is enormous and far reaching, as patients typically display first symptoms during midlife. HD is characterized by unwanted choreatic movements, behavioral and psychiatric disturbances and dementia. SCAs are mainly characterized by ataxia but also other symptoms including cognitive deficits, similarly affecting quality of life and leading to disability. These problems worsen as the disease progresses and affected individuals are no longer able to work, drive, or care for themselves. It places an enormous burden on their family and caregivers, and patients will require intensive nursing home care when disease progresses, and lifespan is reduced. Although the clinical and pathological phenotypes are distinct for each CAG repeat expansion disorder, it is thought that similar molecular mechanisms underlie the effect of expanded CAG repeats in different genes. The predicted Age of Onset (AO) for both HD, SCA1 and SCA3 (and 5 other CAG-repeat diseases) is based on the polyQ expansion, but the CAG/polyQ determines the AO only for 50% (see figure below). A large variety on AO is observed, especially for the most common range between 40 and 50 repeats11,12. Large differences in onset, especially in the range 40-50 CAGs not only imply that current individual predictions for AO are imprecise (affecting important life decisions that patients need to make and also hampering assessment of potential onset-delaying intervention) but also do offer optimism that (patient-related) factors exist that can delay the onset of disease.To address both items, we need to generate a better model, based on patient-derived cells that generates parameters that not only mirror the CAG-repeat length dependency of these diseases, but that also better predicts inter-patient variations in disease susceptibility and effectiveness of interventions. Hereto, we will use a staggered project design as explained in 5.1, in which we first will determine which cellular and molecular determinants (referred to as landscapes) in isogenic iPSC models are associated with increased CAG repeat lengths using deep-learning algorithms (DLA) (WP1). Hereto, we will use a well characterized control cell line in which we modify the CAG repeat length in the endogenous ataxin-1, Ataxin-3 and Huntingtin gene from wildtype Q repeats to intermediate to adult onset and juvenile polyQ repeats. We will next expand the model with cells from the 3 (SCA1, SCA3, and HD) existing and new cohorts of early-onset, adult-onset and late-onset/intermediate repeat patients for which, besides accurate AO information, also clinical parameters (MRI scans, liquor markers etc) will be (made) available. This will be used for validation and to fine-tune the molecular landscapes (again using DLA) towards the best prediction of individual patient related clinical markers and AO (WP3). The same models and (most relevant) landscapes will also be used for evaluations of novel mutant protein lowering strategies as will emerge from WP4.This overall development process of landscape prediction is an iterative process that involves (a) data processing (WP5) (b) unsupervised data exploration and dimensionality reduction to find patterns in data and create “labels” for similarity and (c) development of data supervised Deep Learning (DL) models for landscape prediction based on the labels from previous step. Each iteration starts with data that is generated and deployed according to FAIR principles, and the developed deep learning system will be instrumental to connect these WPs. Insights in algorithm sensitivity from the predictive models will form the basis for discussion with field experts on the distinction and phenotypic consequences. While full development of accurate diagnostics might go beyond the timespan of the 5 year project, ideally our final landscapes can be used for new genetic counselling: when somebody is positive for the gene, can we use his/her cells, feed it into the generated cell-based model and better predict the AO and severity? While this will answer questions from clinicians and patient communities, it will also generate new ones, which is why we will study the ethical implications of such improved diagnostics in advance (WP6).
Smart city technologies, including artificial intelligence and computer vision, promise to bring a higher quality of life and more efficiently managed cities. However, developers, designers, and professionals working in urban management have started to realize that implementing these technologies poses numerous ethical challenges. Policy papers now call for human and public values in tech development, ethics guidelines for trustworthy A.I., and cities for digital rights. In a democratic society, these technologies should be understandable for citizens (transparency) and open for scrutiny and critique (accountability). When implementing such public values in smart city technologies, professionals face numerous knowledge gaps. Public administrators find it difficult to translate abstract values like transparency into concrete specifications to design new services. In the private sector, developers and designers still lack a ‘design vocabulary’ and exemplary projects that can inspire them to respond to transparency and accountability demands. Finally, both the public and private sectors see a need to include the public in the development of smart city technologies but haven’t found the right methods. This proposal aims to help these professionals to develop an integrated, value-based and multi-stakeholder design approach for the ethical implementation of smart city technologies. It does so by setting up a research-through-design trajectory to develop a prototype for an ethical ‘scan car’, as a concrete and urgent example for the deployment of computer vision and algorithmic governance in public space. Three (practical) knowledge gaps will be addressed. With civil servants at municipalities, we will create methods enabling them to translate public values such as transparency into concrete specifications and evaluation criteria. With designers, we will explore methods and patterns to answer these value-based requirements. Finally, we will further develop methods to engage civil society in this processes.
INXCES will use and enhance innovative 3D terrain analysis and visualization technology coupled with state-of-the-art satellite remote sensing to develop cost-effective risk assessment tools for urban flooding, aquifer recharge, ground stability and subsidence. INXCES will develop quick scan tools that will help decision makers and other actors to improve the understanding of urban and peri-urban terrains and identify options for cost effective implementation of water management solutions that reduce the negative impacts of extreme events, maximize beneficial uses of rainwater and stormwater for small to intermediate events and provide long-term resilience in light of future climate changes. The INXCES approach optimizes the multiple benefits of urban ecosystems, thereby stimulating widespread implementation of nature-based solutions on the urban catchment scale.INXCES will develop new innovative technological methods for risk assessment and mitigation of extreme hydroclimatic events and optimization of urban water-dependent ecosystem services at the catchment level, for a spectrum of rainfall events. It is widely acknowledged that extreme events such as floods and droughts are an increasing challenge, particularly in urban areas. The frequency and intensity of floods and droughts pose challenges for economic and social development, negatively affecting the quality of life of urban populations. Prevention and mitigation of the consequences of hydroclimatic extreme events are dependent on the time scale. Floods are typically a consequence of intense rainfall events with short duration. In relation to prolonged droughts however, a much slower timescale needs to be considered, connected to groundwater level reductions, desiccation and negative consequences for growing conditions and potential ground – and building stability.INXCES will take a holistic spatial and temporal approach to the urban water balance at a catchment scale and perform technical-scientific research to assess, mitigate and build resilience in cities against extreme hydroclimatic events with nature-based solutions.INXCES will use and enhance innovative 3D terrain analysis and visualization technology coupled with state-of-the-art satellite remote sensing to develop cost-effective risk assessment tools for urban flooding, aquifer recharge, ground stability and subsidence. INXCES will develop quick scan tools that will help decision makers and other actors to improve the understanding of urban and peri-urban terrains and identify options for cost effective implementation of water management solutions that reduce the negative impacts of extreme events, maximize beneficial uses of rainwater and stormwater for small to intermediate events and provide long-term resilience in light of future climate changes. The INXCES approach optimizes the multiple benefits of urban ecosystems, thereby stimulating widespread implementation of nature-based solutions on the urban catchment scale.
