Presentatie gegeven over de review in Brussel Objectives: In the past decades many psychosocial interventions for elderly people with dementia have been developed and implemented. Relatively little research has been done on the extent to which these interventions were implemented in the daily care. The aim of this study was to obtain insight into strategies for successful implementation of psychosocial interventions in the daily residential dementia care. Using a modified RE-AIM framework, the indicators that are considered important for effective and sustainable implementation were defined.
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Person-centered care interventions can improve the quality of life and decrease behavioral problems of people with dementia. Although not convincingly proven, person-centered care interventions may benefit the caregivers as well. This study aims to gain insight into how working with the Veder Contact Method (VCM) – a new person-centered care method – influences the job satisfaction of caregivers.
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People with dementia are confronted with many decisions. However, they are often not involved in the process of the decision-making. Shared Decision-Making (SDM) enables involvement of persons with dementia in the decision-making process. In our study, we develop a supportive IT application aiming to facilitate the decision-making process in care networks of people with dementia. A key feature in the development of this SDM tool is the participation of all network members during the design and development process, including the person with dementia. In this paper, we give insight into the first phases of this design and development process in which we conducted extensive user studies and translated wishes and needs of network members into user requirements
Wat dragen creatieve onderzoeksmethodes bij aan vernieuwing binnen de zorg? We onderzoeken dit binnen tien projecten van het Create Health-programma van ZonMw. In deze projecten wordt kennis ontwikkeld over de toegevoegde waarde van creatieve manieren van werken bij e-health innovatie.
Wat dragen creatieve onderzoeksmethodes bij aan vernieuwing binnen de zorg? We onderzoeken dit binnen tien projecten van het Create Health-programma van ZonMw. In deze projecten wordt kennis ontwikkeld over de toegevoegde waarde van creatieve manieren van werken bij e-health innovatie. Informatie over de onderzoeksresultaten is te vinden op de website: husite.nl/creatieve-onderzoeksmethodes en het artikel: CHIWaWA maakt samenwerking in create-health onderzoek inzichtelijk | Hogeschool Utrecht (hu.nl)Doel Het Create Health programma heeft tot doel om bij te dragen aan maatschappelijke uitdagingen rondom gezond en actief ouder worden. CHIWaWA werkt daarbij toe naar een conceptueel model dat manieren van werken in kaart brengt in create health projecten – gekoppeld aan theorie over boundary crossing en research impact – met betrekking tot projectuitkomsten en kennis-, persoonlijke-, en systeemontwikkeling van betrokken actoren. Resultaten onderzoek Kennis die zowel online als offline te raadplegen is, in een boek, in wetenschappelijke artikelen en op een website. Deze kennis bevat: Inzicht in kansen om impact van e-health innovatie in ‘create health’-samenwerking te vergroten; Projectnarratieven met ‘best practices’ voor interdisciplinaire samenwerking waarbij onderzoekers, creatieve industrie en zorgprofessionals betrokken zijn; Guidelines voor ontwikkelaars van e-health applicaties m.b.t. samenwerking met de creatieve industrie; Guidelines voor beleidsmakers m.b.t. het stimuleren van samenwerking tussen zorg en creatieve industrie en het gebruik van creatieve manieren van werken om onderzoek naar de praktijk te krijgen; Aanpak Vanuit een service-dominant logic perspectief wordt bekeken hoe toegepaste kennis en skills worden gedeeld tussen actoren die betrokken zijn bij de verschillende ‘create health’-projecten, wat de meerwaarde daarvan is en wat actoren van die uitwisseling – als proces – leren. De focus ligt op co-creatie van waarde, die door samenwerking en uitwisseling tot stand komt. Door middel van procesonderzoek wordt er toegewerkt naar bijdragen aan theorieontwikkeling op het gebied van boundary crossing en contribution mapping. Resultaten Eindpublicatie: Create Health: Samenwerking tussen zorg, wetenschap en creatieve industrie (2023) Boek: Create Ways of Working. Insights from ten ehealth Innovation research projects (2022) Website www.creatieveonderzoeksmethodes.nl (2022) Bijdragen aan conferenties en symposia Co-design in de anderhalvemetermaatschappij (whitepaper), Dutch Design Week 2020. Download de presentatieslides. Collaborating in complexity. Strategies for interdisciplinary collaboration n design work, Design4Health conference 2020 Grounding Practices. How researchers ground their work in create-health collaborations for designing e-health solutions, Design4Health conference 2020 Seven ways to foster interdisciplinary collaboration in research involving healthcare and creative research disciplines, DementiaLab conference 2019 Posterpresentatie: Health x Design, DementiaLab conference 2019 Meer informatie over het Create Health programma Het ZonMw programma Create Health heeft als doel om bij te dragen aan de maatschappelijke uitdaging rondom gezond en actief ouder worden. Binnen het programma worden activiteiten uitgezet waarbij de samenwerking tussen de creatieve industrie en zorg en welzijn voorop staat. Het gaat hierbij om publiek-private samenwerking (PPS).
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).
