This study provides an illustration of a research design complementary to randomized controlled trial to evaluate program effects, namely, participatory peer research (PPR). The PPR described in current study was carried out in a small sample (N = 10) of young adults with mild intellectual disabilities (MID) and severe behavioral problems. During the PPR intervention, control and feedback to individuals is restored by training them to become participant-researchers, who collaborate in a small group of people with MID. Their research is aimed at the problems the young adults perceive and/or specific subjects of their interest. The study was designed as a multiple case study with an experimental and comparison group. Questionnaires and a semistructured interview were administered before and after the PPR project. Results of Reliable Change Index (RCI) analyses showed a decrease in self-serving cognitive distortions in the PPR group, but not in the comparison group. These results indicate that PPR helps to compensate for a lack of adequate feedback and control, and in turn may decrease distorted thinking and thereby possibly later challenging behavior.
Teaching students with behavioral problems is a challenge for many teachers in inclusive education. To assess a teacher's quality in teaching students with behavioral problems and to explore what differentiates them from less effective teachers, this study aimed to validate a method for measuring this type of teacher quality. Based on classroom observations, special needs support teachers (n = 12) rated the extent to which teachers met the need for competence, autonomy, and relatedness of students with behavioral problems. Primary school teachers (n = 137) completed a self-efficacy questionnaire related to teaching students with behavioral problems. Head teachers (n = 12) and the same teachers participated in a nomination procedure. Factor, reliability, descriptive, correlation, and cluster analyses were performed. Significant positive not fully overlapping correlations were found between the instruments. A group of 10–15 expert teachers of students with behavioral problems were selected. Future directions for research are discussed.
This systematic review evaluates the implementation of treatment integrity procedures in outcome studies of youth interventions targeting behavioral problems. The Implementation of Treatment Integrity Procedures Scale (ITIPS), developed by Perepletchikova, Treat, and Kazdin (2007), was adapted (ITIPS-A) and used to evaluate 32 outcome studies of evidence-based interventions for youths with externalizing behavioral problems. Integrity measures were found to be still rare in these studies. Of the studies that took integrity into account, 80% approached adequacy in implementing procedures for treatment integrity. The ITIPS-A is recommended as an instrument to guide development of integrity instruments and the implementation of treatment integrity procedures in youth care.
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).
Our world is changing rapidly as a result of societal and technological developments that create new opportunities and challenges. Extended Realities (XR) could provide solutions for the problems the world is facing. In this project we apply these novel solutions in food and hospitality. It aims to tackle fundamental questions on how to stimulate a healthy and vital society that is based on a sustainable and innovative economy. This project aims to answer the question: How can Extended Reality (XR) technologies be integrated in the design of immersive food experiences to stimulate sustainable consumption behavior? A multidisciplinary approach, that has demonstrated its strength in the creative industry, will be applied in the hospitality and food sector. The project investigates implications and design considerations for immersion through XR technology that can stimulate sustainable consumption behavior. Based on XR prototypes, physiological data will be collected using biometric measuring devices in combination with self-reports. The effect of stimuli on sustainable consumption behavior during the immersive experience will be tested to introduce XR implementations that can motivate long-term behavioral change in food consumption. The results of the project contribute towards developing innovations in the hospitality sector that can tackle global societal challenges by exploiting the impact of new technology and understanding of consumer behavior to promote a healthy lifestyle and economy. Next to academic publications and conference contributions, the project will develop a handbook for hospitality professionals. It will outline steps and design criteria for the implementation of XR technologies to create immersive experiences that can stimulate sustainable consumption behavior. The knowledge generated in the project will contribute to the development of the curriculum at the Academy for Hotel and Facility at Breda University of Applied Sciences by introducing a technology-driven experience design approach for the course Sustainable Strategic Business Design.
YOUNG-D is a European project on the prevention and management of anxiety, stress and sleep problems in people with early onset dementia (OED).The overall aim of this project is to increase awareness and knowledge of (future) health care providers in the included EU-partners on psychosocial and behavioral program YOUNG-D in people with early onset dementia in order to prevent and manage anxiety, stress and sleep problems, which in turn increases heart rate variability, wellbeing and quality of life.ErasmusprojectThis project aims to educate and sensitize health care providers, organisations and health care students and -lecturers about early onset dementia. More specifically, this project focuses on knowledge transfer about aspects in the prevention and management of anxiety, stress and sleep problems in people with early onset dementia by means of a psychosocial and behavioural program. Activities to implement(1) the development and organisation of a train-the-trainer course for professional health caregivers and organisations.; (2) the health care organisation partner in each European country (partner) will enroll the six week psychosocial and behavioural program in its own setting; (3) knowledge transfer towards future health care students and lecturers will be provided per country by means of a blended learning module. Planned results: (1) Development of the train-the-trainer course: a syllabus and a joint report(2) Implementation of the six week program in each health care setting in the included health care partners and a joint report (3) development of blended learning course and a joint report
