Background: Although physical activity (PA) has positive effects on health and well-being, physical inactivity is a worldwide problem. Mobile health interventions have been shown to be effective in promoting PA. Personalizing persuasive strategies improves intervention success and can be conducted using machine learning (ML). For PA, several studies have addressed personalized persuasive strategies without ML, whereas others have included personalization using ML without focusing on persuasive strategies. An overview of studies discussing ML to personalize persuasive strategies in PA-promoting interventions and corresponding categorizations could be helpful for such interventions to be designed in the future but is still missing. Objective: First, we aimed to provide an overview of implemented ML techniques to personalize persuasive strategies in mobile health interventions promoting PA. Moreover, we aimed to present a categorization overview as a starting point for applying ML techniques in this field. Methods: A scoping review was conducted based on the framework by Arksey and O’Malley and the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) criteria. Scopus, Web of Science, and PubMed were searched for studies that included ML to personalize persuasive strategies in interventions promoting PA. Papers were screened using the ASReview software. From the included papers, categorized by the research project they belonged to, we extracted data regarding general study information, target group, PA intervention, implemented technology, and study details. On the basis of the analysis of these data, a categorization overview was given. Results: In total, 40 papers belonging to 27 different projects were included. These papers could be categorized in 4 groups based on their dimension of personalization. Then, for each dimension, 1 or 2 persuasive strategy categories were found together with a type of ML. The overview resulted in a categorization consisting of 3 levels: dimension of personalization, persuasive strategy, and type of ML. When personalizing the timing of the messages, most projects implemented reinforcement learning to personalize the timing of reminders and supervised learning (SL) to personalize the timing of feedback, monitoring, and goal-setting messages. Regarding the content of the messages, most projects implemented SL to personalize PA suggestions and feedback or educational messages. For personalizing PA suggestions, SL can be implemented either alone or combined with a recommender system. Finally, reinforcement learning was mostly used to personalize the type of feedback messages. Conclusions: The overview of all implemented persuasive strategies and their corresponding ML methods is insightful for this interdisciplinary field. Moreover, it led to a categorization overview that provides insights into the design and development of personalized persuasive strategies to promote PA. In future papers, the categorization overview might be expanded with additional layers to specify ML methods or additional dimensions of personalization and persuasive strategies.
The in-depth assessment of the situation of the European textile and clothing sector is composed by six independent reports with a close focus on key aspects useful to understand the dynamics and the development of the textile and clothing industry, drivers of change – most notably the impact of the financial crisis – and identification of policy responses and best practices. This has been done in six specific tasks leading to the six reports: Task 1 Survey on the situation of the EU textile and clothing sector Task 2 Report on research and development Task 3 Report on SME situation Task 4 Report on restructuring Task 5 Report on training and Education Task 6 Report on innovation practices The aim of Task 1 was to provide insight into the trends and drivers of change in the Textile and Clothing (T&C hereafter) industry and to provide input to the remaining Tasks.
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The in-depth assessment of the situation of the European textile and clothing sector is composed by six independent reports with a close focus on key aspects useful to understand the dynamics and the development of the textile and clothing industry, drivers of change – most notably the impact of the financial crisis – and identification of policy responses and best practices. This has been done in six specific tasks leading to the six reports: Task 1 Survey on the situation of the EU textile and clothing sector Task 2 Report on research and development Task 3 Report on SME situation Task 4 Report on restructuring Task 5 Report on training and Education Task 6 Report on innovation practices The aim of Task 2 was to analyse in detail how specialised research an innovation centres liaise with textile/clothing enterprises and analyse the process of transforming textile/clothing research innovations into new products/processes available in the market.
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In het kader van het Hoogwaterbeschermingsprogramma (HWBP) neemt de vraag naar klei voor het versterken van dijken toe, echter is het aanbod beperkt. Dit voorstel richt zich op ontwikkelen van nieuwe duurzame en kosteneffectieve technieken die het mogelijk maken om zout sediment uit estuaria in te kunnen zetten voor de dijkversterkingsopgave. Gebiedseigen materiaal, met name het zoute slib, kan worden ingezet voor klei productie in lokale dijkverzwaring en draagt bij aan duurzaam grondstoffenverbruik, klimaatadaptatie en de ecologische kwaliteit van estuaria. Met het project “Ontzouten rijpend slib voor Deltabescherming” gaan het lectoraat Sustainable River Management van de HAN, Ecoshape, Netics in samenwerking met partijen verenigd in het interbestuurlijk project IBP-VLOED onderzoeken hoe zout slib (kosten)effectief kan worden ontdaan van het zout, zodat het gebruikt kan worden in de regionale dijkversterkingsopgave. In IBP-Vloed zijn alle relevante nationale en regionale (semi)overheden, kennisinstellingen en belangenorganisaties vertegenwoordigd die zich richten op hergebruik van slib uit het Eems-Dollard estuarium. Beoogd wordt om een geschikte kosteneffectieve en schaalbare ontzoutingsmethode (strategie) te ontwikkelen die rekening houdt met de samenhang van de governing parameters en de heterogeniteit in samenstelling en structuur van het zoute slib uit estuaria zoals het Eems-Dollard gebied. De resultaten worden gepresenteerd tijdens een workshop en gebundeld in de vorm van best practices.
