In de openbare geestelijke gezondheidszorg is bemoeizorg al een tijdje bekend. Hulpverleners proberen daarbij in contact te komen met ‘zorgwekkende zorgmijders’; een risicogroep van mensen met vaak complexe en meervoudige problematiek die zelf niet om hulp vragen.
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Depression is a highly prevalent and seriously impairing disorder. Evidence suggests that music therapy can decrease depression, though the music therapy that is offered is often not clearly described in studies. The purpose of this study was to develop an improvisational music therapy intervention based on insights from theory, evidence and clinical practice for young adults with depressive symptoms. The Intervention Mapping method was used and resulted in (1) a model to explain how emotion dysregulation may affect depressive symptoms using the Component Process Model (CPM) as a theoretical framework; (2) a model to clarify as to how improvisational music therapy may change depressive symptoms using synchronisation and emotional resonance; (3) a prototype Emotion-regulating Improvisational Music Therapy for Preventing Depressive symptoms (EIMT-PD); (4) a ten-session improvisational music therapy manual aimed at improving emotion regulation and reducing depressive symptoms; (5) a program implementation plan; and (6) a summary of a multiple baseline study protocol to evaluate the effectiveness and principles of EIMT-PD. EIMT-PD, using synchronisation and emotional resonance may be a promising music therapy to improve emotion regulation and, in line with our expectations, reduce depressive symptoms. More research is needed to assess its effectiveness and principles.
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This article presents a variety of treatment approaches based on an understanding of four components of communication, and describes cluttering intervention focusing on problem identification, speech rate reduction, appropriate pausing, appropriate monitoring, and addressing story narrating skills. Therapeutic considerations, taking into account the specific characteristics of cluttering, will also be presented. Finally, building clients’ confidence, emotional skills, and sense of accomplishment will turn the therapeutic process into awareness of realistic expectations and motivation to pursue challenging goals. Cluttering is a disorder of speech fluency in which people are not capable of adequately adjusting their speech rate to the syntactical or phonological demands of the moment (van Zaalen, 2009). When language production is relatively easy, people with cluttering (PWC) are capable of producing fluent and intelligible speech. When language production demands are more complex, the speech rate should be adjusted to the language complexity. PWC tend to have difficulties doing so. This reduced ability of PWC to control their speech rate results in either a higher than normal frequency of disfluencies or multiple speech errors. This article presents various intervention approaches based on an understanding of four components of communication: cognitive, emotional, verbal-motor, and communicative. The article focuses on problem identification, speech rate reduction, appropriate pausing, and addressing monitoring and story narrating skills. Therapeutic considerations, taking into account the specific characteristics of cluttering, will also be presented.
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De inzet van blended care in de zorg neemt toe. Hierbij wordt fysieke begeleiding (face-to-face) met persoonlijke aandacht door een zorgprofessional afgewisseld met digitale zorg in de vorm van een platform of mobiele applicatie (eHealth). De digitale zorg versterkt de mogelijkheden van cliënten om in hun eigen omgeving te werken aan gezondheidsdoelen en handvatten tijdens de face-to-face momenten. Een specifieke groep die baat kan hebben bij blended care zijn ouderen die na revalidatie in de geriatrische revalidatiezorg (GRZ) thuis verder revalideren. Focus op zowel bewegen (door fysio- en oefentherapeut) en voedingsgedrag (door diëtist) is hierbij essentieel. Echter, na een intensieve zorgperiode tijdens hun opname wordt revalidatie veelal thuis afgeschaald en overgenomen door een ambulant begeleidingstraject of de eerste lijn. Een groot gedeelte van de ouderen ervaart een terugval in fysiek functioneren en zelfredzaamheid bij thuiskomt en heeft baat bij intensieve zorg omtrent voeding en beweging. Een blended interventie die gezond beweeg- en voedingsgedrag combineert biedt kansen. Hierbij is maatwerk voor deze kwetsbare ouderen vereist. Ambulante en eerste lijn diëtisten, fysio- en oefentherapeuten erkennen de meerwaarde van blended care maar missen handvatten en kennis over hoe blended-care ingezet kan worden bij kwetsbare ouderen. Het doel van het huidige project is ouderen én hun behandelaren te ondersteunen bij het optimaliseren van fysiek functioneren in de thuissituatie, door een blended voeding- en beweegprogramma te ontwikkelen en te testen in de praktijk. Ouderen, professionals en ICT-professionals worden betrokken in verschillende co-creatie sessies om gebruikersbehoefte, acceptatie en technische eisen te verkennen als mede inhoudelijke eisen zoals verhouding face-to-face en online. In samenspraak met gebruikers wordt de blended BITE-IT interventie ontwikkeld op basis van een bestaand platform, waarbij ook gekeken wordt naar het gebruik van bestaande en succesvolle applicaties. De BITE-IT interventie wordt uitgebreid getoetst op haalbaarheid en eerste effectiviteit in de praktijk.
The main objective is to write a scientific paper in a peer-reviewed Open Access journal on the results of our feasibility study on increasing physical activity in home dwelling adults with chronic stroke. We feel this is important as this article aims to close a gap in the existing literature on behavioral interventions in physical therapy practice. Though our main target audience are other researchers, we feel clinical practice and current education on patients with stroke will benefit as well.
The increasing amount of electronic waste (e-waste) urgently requires the use of innovative solutions within the circular economy models in this industry. Sorting of e-waste in a proper manner are essential for the recovery of valuable materials and minimizing environmental problems. The conventional e-waste sorting models are time-consuming processes, which involve laborious manual classification of complex and diverse electronic components. Moreover, the sector is lacking in skilled labor, thus making automation in sorting procedures is an urgent necessity. The project “AdapSort: Adaptive AI for Sorting E-Waste” aims to develop an adaptable AI-based system for optimal and efficient e-waste sorting. The project combines deep learning object detection algorithms with open-world vision-language models to enable adaptive AI models that incorporate operator feedback as part of a continuous learning process. The project initiates with problem analysis, including use case definition, requirement specification, and collection of labeled image data. AI models will be trained and deployed on edge devices for real-time sorting and scalability. Then, the feasibility of developing adaptive AI models that capture the state-of-the-art open-world vision-language models will be investigated. The human-in-the-loop learning is an important feature of this phase, wherein the user is enabled to provide ongoing feedback about how to refine the model further. An interface will be constructed to enable human intervention to facilitate real-time improvement of classification accuracy and sorting of different items. Finally, the project will deliver a proof of concept for the AI-based sorter, validated through selected use cases in collaboration with industrial partners. By integrating AI with human feedback, this project aims to facilitate e-waste management and serve as a foundation for larger projects.
Lectorate, part of NHL Stenden Hogeschool
