Background and objective Public involvement in palliative care is challenging and difficult, because people in need of palliative care are often not capable of speaking up for themselves. Patient representatives advocate for their common interests. The aim of our study was to examine in depth the current practice of public involvement in palliative care. Setting and sample The study was conducted in the province of Limburg in the Netherlands, with six palliative care networks. Study participants were 16 patient representatives and 12 professionals. Method This study had a descriptive design using qualitative methods: 18 in-depth interviews and three focus groups were conducted. The critical incident technique was used. The data were analysed using an analytical framework based on Arnstein’s involvement classification and the process of decision making. Impact categories as well as facilitators and barriers were analysed using content analysis. Findings and conclusion The perceived impact of public involvement in palliative care in terms of citizen control and partnership is greatest with regard to quality of care, information development and dissemination, and in terms of policymaking with regard to the preparation and implementation phases of decision making. The main difference in perceived impact between patient representatives and professionals relates to the tension between operational and strategic involvement. Patient representatives experienced more impact regarding short-term solutions to practical problems, while professionals perceived great benefits in long-term, strategic processes. Improving public involvement in palliative care requires positive attitudes, open communication, sufficient resources and long-term support, to build a solid basis for pursuing meaningful involvement in the entire decision-making process.
MULTIFILE
Background: after hospitalisation for cardiac disease, older patients are at high risk of readmission and death. Objective: the cardiac care bridge (CCB) transitional care programme evaluated the impact of combining case management, disease management and home-based cardiac rehabilitation (CR) on hospital readmission and mortality. Design: single-blind, randomised clinical trial. Setting: the trial was conducted in six hospitals in the Netherlands between June 2017 and March 2020. Community-based nurses and physical therapists continued care post-discharge. Subjects: cardiac patients ≥ 70 years were eligible if they were at high risk of functional loss or if they had had an unplanned hospital admission in the previous 6 months. Methods: the intervention group received a comprehensive geriatric assessment-based integrated care plan, a face-to-face handover with the community nurse before discharge and follow-up home visits. The community nurse collaborated with a pharmacist and participants received home-based CR from a physical therapist. The primary composite outcome was first all-cause unplanned readmission or mortality at 6 months. Results: in total, 306 participants were included. Mean age was 82.4 (standard deviation 6.3), 58% had heart failure and 92% were acutely hospitalised. 67% of the intervention key-elements were delivered. The composite outcome incidence was 54.2% (83/153) in the intervention group and 47.7% (73/153) in the control group (risk differences 6.5% [95% confidence intervals, CI -4.7 to 18%], risk ratios 1.14 [95% CI 0.91-1.42], P = 0.253). The study was discontinued prematurely due to implementation activities in usual care. Conclusion: in high-risk older cardiac patients, the CCB programme did not reduce hospital readmission or mortality within 6 months.
The aim of this study is to investigate Dutch citizens’ care attitudes by looking at care-giving norms and citizens’ welfare state orientation and to explore to what extent these attitudes can be explained by combinations of diversity characteristics. We combined two datasets (2016 and 2018, N = 5,293) containing citizens’ opinions regarding society and conducted multivariate linear and ordered probit regression analyses. An intersectional perspective was adopted to explore the influence of combinations of diversity characteristics. Results show that citizens’ care-giving norms are relatively strong, meaning they believe persons in need of care should receive help from their families or social networks. However, citizens consider the government responsible for care as well. Men, younger people, people in good health and people of non-Western origin have stronger care-giving norms than others, and younger people assign relatively more responsibility to the family than the government. Level of education and religiosity are also associated with care attitudes. Primary diversity dimensions are more related to care attitudes than secondary, circumstantial dimensions. Some of the secondary dimensions interact with primary dimensions. These insights offer policy makers, social workers and (allied) health professionals the opportunity to align with citizens’ care attitudes, as results show that people vary to a large extent in their care-giving norms and welfare state orientation.
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).
Dit projectvoorstel is gericht op de ontwikkeling van nieuwe moleculen om zelf, thuis infectieziekten te diagnosticeren. Om de diagnose van infectieziektes te bevorderen, met name in afgelegen gebieden, is de innovatieve strategie van point-of-care (POC), een snelle, accurate en sensitieve diagnostische test die door een patiënt zelf kan worden uitgevoerd, uitermate geschikt. Een simpel en klein toestel dat enzymatische activiteit uit microben kan meten is in ontwikkeling bij Enzyre B.V. Dit voorstel gaat over de ontwikkeling van nieuwe lichtgevende moleculen die de detectie van infectieziektes kunnen aantonen door middel van het Enzyre platform. Hiervoor wordt een nieuwe chemisch aanpak om dit soort lichtgevende moleculen te maken ontwikkeld. Dit is relevant voor de preventie en het monitoren controle van potentiële pandemieën zoals bijvoorbeeld de recente uitbraak van SARS-Cov-2, maar ook MERS, SARS, HIV, Ebola en meerdere influenza pandemieën uit het verleden
