In dit document is het logopedisch onderzoek bij broddelen beschreven waarover internationaal consensus bestaat. Dit document is gepresenteerd op de website van de International Cluttering Association
Objectives: Goal setting and motivational interviewing (MI) may increase well-being by promoting healthy behavior. Since we failed to show improved well-being in a proactive assessment service for community-dwelling older adults applying these techniques, we studied whether implementation processes could explain this. Methods: Goals set during the comprehensive geriatric assessment were evaluated on their potential for behavior change. MI and goal setting adherence wasassessed by reviewing audiotaped interactions and interviewing care professionals. Results: Among the 280 goals set with 230 frail older adults (mean age 77 ± 6.9 years, 59% women), more than 90% had a low potential for behavior change. Quality thresholds for MI were reached in only one of the 11 interactions. Application was hindered by the context and the limited proficiency of care professionals. Discussion: Implementation was suboptimal for goal setting and MI. This decreased the potential for improved well-being in the participating older adults.
MULTIFILE
A growing number of higher education programmes in the Netherlands has implemented programmatic assessment. Programmatic assessment is an assessment concept in which the formative and summative function of assessment is intertwined. Although there is consensus about the theoretical principles of programmatic assessment, programs make various specific design choices, fitting with their own context. In this factsheet we give insight into the design choices Dutch higher education programmes make when implementing programmatic assessment.
Due to the existing pressure for a more rational use of the water, many public managers and industries have to re-think/adapt their processes towards a more circular approach. Such pressure is even more critical in the Rio Doce region, Minas Gerais, due to the large environmental accident occurred in 2015. Cenibra (pulp mill) is an example of such industries due to the fact that it is situated in the river basin and that it has a water demanding process. The current proposal is meant as an academic and engineering study to propose possible solutions to decrease the total water consumption of the mill and, thus, decrease the total stress on the Rio Doce basin. The work will be divided in three working packages, namely: (i) evaluation (modelling) of the mill process and water balance (ii) application and operation of a pilot scale wastewater treatment plant (iii) analysis of the impacts caused by the improvement of the process. The second work package will also be conducted (in parallel) with a lab scale setup in The Netherlands to allow fast adjustments and broaden evaluation of the setup/process performance. The actions will focus on reducing the mill total water consumption in 20%.
Circular BIOmass CAScade to 100% North Sea Region (NSR) economic activity and growth are mostly found in urban areas. Rural NSR regions experience population decline and negative economic growth. The BIOCAS project expects revitalizing and greening of rural areas go hand in hand. BIOCAS will develop rural areas of the NSR into smart specialized regions for integrated and local valorization of biomass. 13 Commercial running Bio-Cascade-Alliances (BCA’s) will be piloted, evaluated and actively shared in the involved regions. These proven concepts will accelerate adoption of high to low value bio-cascading technologies and businesses in rural regions. The project connects 18 regional initiatives around technologies, processes, businesses for the conversion of biomass streams. The initiatives collaborate in a thematic approach: Through engineering, value chain assessments, BCA’s building, partners tackle challenges that are shared by rural areas. I.e. unsustainable biomass use, a mineral surplus and soil degradation, deprivation of potentially valuable resources, and limited involvement of regional businesses and SMEs in existing bio-economy developments. The 18 partners are strongly embedded in regional settings, connected to many local partners. They will align stakeholders in BCA’s that would not have cooperated without BIOCAS interventions. Triple helix, science, business and governmental input will realize inclusive lasting bio cascade businesses, transforming costly waste to resources and viable business.Interreg IVB North Sea Region Programme: €378,520.00, fEC % 50.00%1/07/17 → 30/06/21
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).
