Background: The target group of this study concerns young people with a mild intellectual disability. The central research question is: What evidence can be found in the literature for common and specific factors for a play therapy intervention for young people with a mild intellectual disability struggling with aggression regulation. Method: The criteria used for selecting articles are presented according to the PRISMA, and the PRISMA guidelines for writing a review have been applied. Results: Common factors have been found in the literature that relate to the relationship between therapist and client and the therapeutic skills of the play therapist. Clues have also been found for specific factors of play therapy, such as the use of play as a language and a connection with the child's inner world. In addition, certain factors have been found that are specific to the target group of this article. The non-verbal element of play therapy is an active part of this.
A symbiotic relationship between human factors and safety scientists is needed to ensure the provision of holistic solutions for problems emerging in modern socio-technical systems. System Theoretic Accident Model and Processes (STAMP) tackles both interactions and individual failures of human and technological elements of systems. Human factors topics and indicative models, tools and methods were reviewed against the approach of STAMP. The results showed that STAMP engulfs many human factors subjects, is more descriptive than human factors models and tools, provides analytical power, and might be further improved by including more aspects of human factors. STAMP can serve in minimizing the gap between human factors and safety engineering sciences, which can collectively offer inclusive solutions to the industry.
This chapter is about the development of tourism in the Dutch Wadden Sea Region in combination with nature conservation. The main question is whether they have a common future. There are some future points stated:- Nature and landscape of the Wadden Sea are the main pull factors for the tourism development. - Future tourism development requires a clear strategy that is supported by various stakeholders- Raising awareness about the natural values results in more visitors and public support for nature conservation- The World Heritage status facilitates cooperation between local entrepreneurs and nature conservation organisationsOverall the conclusion can be drawn that, stimulated by the World Heritage status of the Wadden Sea and facilitated by a trilateral Sustainable Tourism Strategy, tourism development and nature conservation and can mutually benefit. Raising awareness about the natural values of the Wadden Sea will result in more visitors to the region and contributes to an emotional attachment to the protected area and public support for the conservation programs.
The transition to a circular, resource efficient construction sector is crucial to achieve climate neutrality in 2050. Construction stillaccounts for 50% of all extracted materials, is responsible for 3% of EU’s waste and for at least 12% of Green House Gas emissions.However, this transition is lagging, the impact of circular building materials is still limited.To accelerate the positive impact of circulair building materials Circular Trust Building has analyzed partners’ circular initiatives andidentified 4 related critical success factors for circularity, re-use of waste, and lower emissions:1. Level of integration2. Organized trust3. Shared learning4. Common goalsScaling these success factors requires new solutions, skills empowering stakeholders, and joint strategies and action plans. Circular TrustBuilding will do so using the innovative sociotechnical transition theory:1.Back casting: integrating stakeholders on common goals and analyzing together what’s needed, what’s available and who cancontribute what. The result is a joint strategy and xx regional action plans.2.Agile development of missing solutions such a Circular Building Trust Framework, Regional Circular Deals, connecting digitalplatforms matching supply and demand3.Increasing institutional capacity in (de-)construction, renovation, development and regulation: trained professionals move thetransition forward.Circular Trust Building will demonstrate these in xx pilots with local stakeholders. Each pilot will at least realize a 25% reduction of thematerial footprint of construction and renovation
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 societies where physical activity levels are declining, stimulating sports participation in youth is vital. While sports offer numerous benefits, injuries in youth are at an all-time high with potential long-term consequences. Particularly, women football's popularity surge has led to a rise in knee injuries, notably anterior cruciate ligament (ACL) injuries, with severe long-term effects. Urgent societal attention is warranted, supported by media coverage and calls for action by professional players. This project aims to evaluate the potential of novel artificial intelligence-based technology to enhance player monitoring for injury risk, and to integrate these monitoring pathways into regular training practice. Its success may pave the way for broader applications across different sports and injuries. Implementation of results from lab-based research into practice is hindered by the lack of skills and technology needed to perform the required measurements. There is a critical need for non-invasive systems used during regular training practice and allowing longitudinal monitoring. Markerless motion capture technology has recently been developed and has created new potential for field-based data collection in sport settings. This technology eliminates the need for marker/sensor placement on the participant and can be employed on-site, capturing movement patterns during training. Since a common AI algorithm for data processing is used, minimal technical knowledge by the operator is required. The experienced PLAYSAFE consortium will exploit this technology to monitor 300 young female football players over the course of 1 season. The successful implementation of non-invasive monitoring of football players’ movement patterns during regular practice is the primary objective of this project. In addition, the study will generate key insights into risk factors associated with ACL injury. Through this approach, PLAYSAFE aims to reduce the burden of ACL injuries in female football players.
