Background: During the process of decision-making for long-term care, clients are often dependent on informal support and available information about quality ratings of care services. However, clients do not take ratings into account when considering preferred care, and need assistance to understand their preferences. A tool to elicit preferences for long-term care could be beneficial. Therefore, the aim of this qualitative descriptive study is to understand the user requirements and develop a web-based preference elicitation tool for clients in need of longterm care. Methods: We applied a user-centred design in which end-users influence the development of the tool. The included end-users were clients, relatives, and healthcare professionals. Data collection took place between November 2017 and March 2018 by means of meetings with the development team consisting of four users, walkthrough interviews with 21 individual users, video-audio recordings, field notes, and observations during the use of the tool. Data were collected during three phases of iteration: Look and feel, Navigation, and Content. A deductive and inductive content analysis approach was used for data analysis. Results: The layout was considered accessible and easy during the Look and feel phase, and users asked for neutral images. Users found navigation easy, and expressed the need for concise and shorter text blocks. Users reached consensus about the categories of preferences, wished to adjust the content with propositions about well-being, and discussed linguistic difficulties. Conclusion: By incorporating the requirements of end-users, the user-centred design proved to be useful in progressing from the prototype to the finalized tool ‘What matters to me’. This tool may assist the elicitation of client’s preferences in their search for long-term care.
Programmed control systems are ubiquitous in the present-day world. In current educational practice, however, these systems are hardly being addressed, and little is known about children’s spontaneous understandings about such systems. Therefore, we explored pupils’ understandings prior to instruction in three concrete settings: a car park, an elevator, and an autonomous robot. We analysed written responses from 49 Grade 3 (aged 7 to 10) and Grade 6 pupils (aged 10 to 13) to assess their understandings from two perspectives: the user and the system programmer perspective. Results indicate that most pupils were capable describing programmed systems from a user perspective point of view but found it hard to describe the system programmer perspective. Substantial differences were found between the contexts. The car park context evoked richer descriptions for the user perspective and the system programmer perspective in comparison to the elevator and autonomous robot contexts.
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The application of DC grids is gaining more attention in office applications. Especially since powering an office desk would not require a high power connection to the main AC grid but could be made sustainable using solar power and battery storage. This would result in fewer converters and further advanced grid utilization. In this paper, a sustainable desk power application is described that can be used for powering typical office appliances such as computers, lighting, and telephones. The desk will be powered by a solar panel and has a battery for energy storage. The applied DC grid includes droop control for power management and can either operate stand-alone or connected to other DC-desks to create a meshed-grid system. A dynamic DC nano-grid is made using multiple self-developed half-bridge circuit boards controlled by microcontrollers. This grid is monitored and controlled using a lightweight network protocol, allowing for online integration. Droop control is used to create dynamic power management, allowing automated control for power consumption and production. Digital control is used to regulate the power flow, and drive other applications, including batteries and solar panels. The practical demonstrative setup is a small-sized desktop with applications built into it, such as a lamp, wireless charging pad, and laptop charge point for devices up to 45W. User control is added in the form of an interactive remote wireless touch panel and power consumption is monitored and stored in the cloud. The paper includes a description of technical implementation as well as power consumption measurements.
De maatschappelijke discussies over de invloed van AI op ons leven tieren welig. De terugkerende vraag is of AI-toepassingen – en dan vooral recommendersystemen – een dreiging of een redding zijn. De impact van het kiezen van een film voor vanavond, met behulp van Netflix' recommendersysteem, is nog beperkt. De impact van datingsites, navigatiesystemen en sociale media – allemaal systemen die met algoritmes informatie filteren of keuzes aanraden – is al groter. De impact van recommendersystemen in bijvoorbeeld de zorg, bij werving en selectie, fraudedetectie, en beoordelingen van hypotheekaanvragen is enorm, zowel op individueel als op maatschappelijk niveau. Het is daarom urgent dat juist recommendersystemen volgens de waarden van Responsible AI ontworpen worden: veilig, eerlijk, betrouwbaar, inclusief, transparant en controleerbaar.Om op een goede manier Responsible AI te ontwerpen moeten technische, contextuele én interactievraagstukken worden opgelost. Op het technische en maatschappelijke niveau is al veel vooruitgang geboekt, respectievelijk door onderzoek naar algoritmen die waarden als inclusiviteit in hun berekening meenemen, en door de ontwikkeling van wettelijke kaders. Over implementatie op interactieniveau bestaat daarentegen nog weinig concrete kennis. Bekend is dat gebruikers die interactiemogelijkheden hebben om een algoritme bij te sturen of aan te vullen, meer transparantie en betrouwbaarheid ervaren. Echter, slecht ontworpen interactiemogelijkheden, of een mismatch tussen interactie en context kosten juist tijd, veroorzaken mentale overbelasting, frustratie, en een gevoel van incompetentie. Ze verhullen eerder dan dat ze tot transparantie leiden.Het ontbreekt ontwerpers van interfaces (UX/UI designers) aan systematische concrete kennis over deze interactiemogelijkheden, hun toepasbaarheid, en de ethische grenzen. Dat beperkt hun mogelijkheid om op interactieniveau aan Responsible AI bij te dragen. Ze willen daarom graag een pattern library van interactiemogelijkheden, geannoteerd met onderzoek over de werking en inzetbaarheid. Dit bestaat nu niet en met dit project willen we een substantiële bijdrage leveren aan de ontwikkeling ervan.
Alcohol Use Disorder (AUD) involves uncontrollable drinking despite negative consequences, a challenge amplified in festivals. ARise is a project using Augmented Reality (AR) to prevent AUD by helping festival visitors refuse alcohol and other substances. Based on the first Augmented Reality Exposure Therapy (ARET) for clinical AUD treatment, ARise uses a smartphone app with AR glasses to project virtual humans that tempt visitors to drink alcohol. Users interact in a safe and personalized way with these virtual humans through phone, voice, and gesture interactions. The project gathers festival feedback on user experience, awareness, usability, and potential expansion to other substances.Societal issueHelping treatment of addiction and stimulate social inclusion.Benefit to societyMore people less patients: decrease health cost and increase in inclusion and social happiness.Collaborative partnersNovadic-Kentron, Thalamusa
Alcohol use disorder (AUD) is a pattern of alcohol use that involves having trouble controlling drinking behaviour, even when it causes health issues (addiction) or problems functioning in daily (social and professional) life. Moreover, festivals are a common place where large crowds of festival-goers experience challenges refusing or controlling alcohol and substance use. Studies have shown that interventions at festivals are still very problematic. ARise is the first project that wants to help prevent AUD at festivals using Augmented Reality (AR) as a tool to help people, particular festival visitors, to say no to alcohol (and other substances). ARise is based on the on the first Augmented Reality Exposure Therapy (ARET) in the world that we developed for clinical treatment of AUD. It is an AR smartphone driven application in which (potential) visitors are confronted with virtual humans that will try to seduce the user to accept an alcoholic beverage. These virtual humans are projected in the real physical context (of a festival), using innovative AR glasses. Using intuitive phone, voice and gesture interactions, it allows users to personalize the safe experience by choosing different drinks and virtual humans with different looks and levels of realism. ARET has been successfully developed and tested on (former) AUD patients within a clinical setting. Research with patients and healthcare specialists revealed the wish to further develop ARET as a prevention tool to reach people before being diagnosed with AUD and to extend the application for other substances (smoking and pills). In this project, festival visitors will experience ARise and provide feedback on the following topics: (a) experience, (b) awareness and confidence to refuse alcohol drinks, (c) intention to use ARise, (d) usability & efficiency (the level of realism needed), and (e) ideas on how to extend ARise with new substances.
