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.
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Objective: To explore the relationship between personal characteristics of older adults with multiple chronic conditions (MCCs) and perceived shared decision making (SDM) resp. decisional conflict. Methods: In a video-observational study (N = 213) data were collected on personal characteristics. The main outcomes were perceived level of SDM and decisional conflict. The mediating variable was participation in the SDM process. A twostep mixed effect multilinear regression and a mediation analysis were performed to analyze the data. Results: The mean age of the patients was 77.3 years and 56.3% were female. Health literacy (β.01, p < .001) was significantly associated with participation in the SDM process. Education (β = −2.43, p = .05) and anxiety (β = −.26, p = .058) had a marginally significant direct effect on the patients’ perceived level of SDM. Education (β = 12.12, p = .002), health literacy (β = −.70, p = .005) and anxiety (β = 1.19, p = .004) had a significant direct effect on decisional conflict. The effect of health literacy on decisional conflict was mediated by participation in SDM. Conclusion: Health literacy, anxiety and education are associated with decisional conflict. Participation in SDM during consultations plays a mediating role in the relationship between health literacy and decisional conflict. Practice Implications: Tailoring SDM communication to health literacy levels is important for high quality SDM.
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The initial trigger of this research about learning from video was the availability of log files from users of video material. Video modality is seen as attractive as it is associated with the relaxed mood of watching TV. The experiments in this research have the goal to gain more insight in viewing patterns of students when viewing video. Students received an awareness instruction about the use of possible alternative viewing behaviors to see whether this would enhance their learning effects. We found that:- the learning effects of students with a narrow viewing repertoire were less than the learning effects of students with a broad viewing repertoire or strategic viewers.- students with some basic knowledge of the topics covered in the videos benefited most from the use of possible alternative viewing behaviors and students with low prior knowledge benefited the least.- the knowledge gain of students with low prior knowledge disappeared after a few weeks; knowledge construction seems worse when doing two things at the same time.- media players could offer more options to help students with their search for the content they want to view again.- there was no correlation between pervasive personality traits and viewing behavior of students.The right use of video in higher education will lead to students and teachers that are more aware of their learning and teaching behavior, to better videos, to enhanced media players, and, finally, to higher learning effects that let users improve their learning from video.
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