To face the challenges of an ageing population, many Western countries nowadays stimulate an ageing in place policy to empower older adults to grow old in their own homes with the highest degree of self‐reliance. However, many community‐living older adults experience limitations in (instrumental) activities of daily living ((I)ADLs), which may result in a need for home‐care services. Unfortunately, home‐care workers often provide support by taking over tasks, as they are used to doing things for older adults rather than with them, which undermines their possibilities to maintain their self‐care capabilities. In contrast, reablement focuses on capabilities and opportunities of older adults, rather than on disease and dependency. Consequently, older adults are stimulated to be as active as possible during daily and physical activities. The 'Stay Active at Home' programme was designed to train home‐care workers to apply reablement in practice. To explore the experiences of home‐care workers with this programme an exploratory study was conducting in the Netherlands, between April and July, 2017. In total, 20 participants were interviewed: nine nurses (including a district nurse), 10 domestic support workers and the manager of the domestic support workers. The semi‐structured interviews focused on the experienced improvements with regard to knowledge, skills, self‐efficacy and social support. Furthermore, the most and least appreciated programme components were identified. The study has shown that home‐care workers perceived the programme as useful to apply reablement. However, they also need more support with mastering particular skills and dealing with challenging situations. Future implementation of the 'Stay Active at Home' programme can potentially benefit from small adaptions. Furthermore, future research is needed to examine whether the programme leads to more (cost‐) effective home care.
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Purpose: To describe nurses' support interventions for medication adherence, and patients' experiences and desired improvements with this care. Patients and methods: A two-phase study was performed, including an analysis of questionnaire data and conducted interviews with members of the care panel of the Netherlands Patients Federation. The questionnaire assessed 14 types of interventions, satisfaction (score 0-10) with received interventions, needs, experiences, and desired improvements in nurses' support. Interviews further explored experiences and improvements. Data were analyzed using descriptive statistics and a thematic analysis approach. Results: Fifty-nine participants completed the questionnaire, and 14 of the 59 participants were interviewed. The satisfaction score for interventions was 7.9 (IQR 7-9). The most common interventions were: "noticing when I don't take medication as prescribed" (n = 35), "helping me to find solutions to overcome problems with using medications" (n = 32), "helping me with taking medication" (n = 32), and "explaining the importance of taking medication at the right moment" (n = 32). Fifteen participants missed ≥1 of the 14 interventions. Most mentioned the following: "regularly asking about potential problems with medication use" (33%), "regularly discussing whether using medication is going well" (29%), and "explaining the importance of taking medication at the right moment" (27%). Twenty-two participants experienced the following as positive: improved self-management of adequate medication taking, a professional patient-nurse relationship to discuss adherence problems, and nurses' proactive attitude to arrange practical support for medication use. Thirteen patients experienced the following as negative: insufficient timing of home visits, rushed appearance of nurses, and insufficient expertise about side effects and taking medication. Suggested improvements included performing home visits on time, more time for providing support in medication use, and more expertise about side effects and administering medication. Conclusion: Overall, participants were satisfied, and few participants wanted more interventions. Nurses' support improved participants' self-management of medication taking and enabled patients to discuss their adherence problems. Adequately timed home visits, more time for support, and accurate medication-related knowledge are desired.
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The European policy emphasis on providing informal care at home causes caregivers and home care professionals having more contact with each other, which makes it important for them to find satisfying ways to share care. Findings from the literature show that sharing care between caregivers and professionals can be improved. This study therefore examines to what degree and why caregivers’ judgements on sharing care with home care professionals vary. To improve our understanding of social inequities in caregiving experiences, the study adopts an intersectional perspective. We investigate how personal and situational characteristics attached to care judgements are interwoven. Using data of the Netherlands Institute for Social Research, we conducted bivariate and multivariate linear regression analysis (N = 292). We combined four survey questions into a 1–4 scale on ‘caregiver judgement’ (α = 0.69) and used caregivers’ personal (such as gender and health status) and situational characteristics (such as the care recipient's impairment and type of care) as determinants to discern whether these are related to the caregivers’ judgement. Using a multiplicative approach, we also examined the relationship between mutually constituting factors of the caregivers’ judgement. Adjusted for all characteristics, caregivers who provide care to a parent or child with a mental impairment and those aged between 45 and 64 years or with a paid job providing care to someone with a mental impairment are likely to judge sharing care more negatively. Also, men providing care with help from other caregivers and caregivers providing care because they like to do so who provide domestic help seem more likely to be less satisfied about sharing care. This knowledge is vital for professionals providing home care, because it clarifies differences in caregivers’ experiences and hence induce knowledge how to pay special attention to those who may experience less satisfaction while sharing care.
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Due to societal developments, like the introduction of the ‘civil society’, policy stimulating longer living at home and the separation of housing and care, the housing situation of older citizens is a relevant and pressing issue for housing-, governance- and care organizations. The current situation of living with care already benefits from technological advancement. The wide application of technology especially in care homes brings the emergence of a new source of information that becomes invaluable in order to understand how the smart urban environment affects the health of older people. The goal of this proposal is to develop an approach for designing smart neighborhoods, in order to assist and engage older adults living there. This approach will be applied to a neighborhood in Aalst-Waalre which will be developed into a living lab. The research will involve: (1) Insight into social-spatial factors underlying a smart neighborhood; (2) Identifying governance and organizational context; (3) Identifying needs and preferences of the (future) inhabitant; (4) Matching needs & preferences to potential socio-techno-spatial solutions. A mixed methods approach fusing quantitative and qualitative methods towards understanding the impacts of smart environment will be investigated. After 12 months, employing several concepts of urban computing, such as pattern recognition and predictive modelling , using the focus groups from the different organizations as well as primary end-users, and exploring how physiological data can be embedded in data-driven strategies for the enhancement of active ageing in this neighborhood will result in design solutions and strategies for a more care-friendly neighborhood.
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).
In de faculteit ‘Science en Engineering’ van de Rijksuniversiteit Groningen is kennis ontwikkeld op het gebied van verduurzaming en vergroening in de chemie. De ambitie is om toe te werken naar de transitie van synthetische chemische processen naar biobased chemische processen. Een expertisegebied betreft de inzet van biotechnologische enzymconversies als alternatief voor klassieke (fossiele) chemische omzettingen. De vakgroep ‘Product and Processes for Biotechnology’ heeft expertise op het gebied van de opschaling van enzymatische conversies. Het MKB-bedrijf CarbExplore Research B.V. werkt aan procesontwikkeling van enzymatische glucosylering. De methode kan worden toegepast bij de (duurzame) productie van ingrediënten (w.o. zoetstoffen en surfactanten) die nodig zijn voor zogenaamde Home & Personal care producten van de toekomst. Bij de opschaling van de technologie, ontstaan innovatievragen. Inzet van het praktijkgerichte onderzoek tussen de RUG en CarbExplore is het vinden van een efficiënte enzymatische opschalingsroute voor deze groene grondstoffen. In de relatie met CarbExplore wordt gewerkt aan de conversie van een Stevia zoetstof. In het vervolg kan de universiteit deze enzymatische opschalingsmethode toepassen in andere bioconversies, andere producten, en bij andere bedrijven. Zowel voor de universiteit, als voor het bedrijf CarbExplore, wordt een economisch potentieel gecreëerd. De uiteindelijke visie en einddoel is het toewerken naar een vergroening van de chemie door middel van enzymatische conversies.
