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.

Background Clients facing decision-making for long-term care are in need of support and accessible information. Construction of preferences, including context and calculations, for clients in long-term care is challenging because of the variability in supply and demand. This study considers clients in four different sectors of long-term care: the nursing and care of the elderly, mental health care, care of people with disabilities, and social care. The aim is to understand the construction of preferences in real-life situations. Method Client choices were investigated by qualitative descriptive research. Data were collected from 16 in-depth interviews and 79 client records. Interviews were conducted with clients and relatives or informal caregivers from different care sectors. The original client records were explored, containing texts, letters, and comments of clients and caregivers. All data were analyzed using thematic analysis. Results Four cases showed how preferences were constructed during the decision-making process. Clients discussed a wide range of challenging aspects that have an impact on the construction of preferences, e.g. previous experiences, current treatment or family situation. This study describes two main characteristics of the construction of preferences: context and calculation. Conclusion Clients face diverse challenges during the decision-making process on long-term care and their construction of preferences is variable. A well-designed tool to support the elicitation of preferences seems beneficial.

Background Self-monitoring of blood glucose levels, food intake, and physical activity supports self-management of patients with type 2 diabetes mellitus (T2DM). There has been an increase in the development and availability of mobile health apps for T2DM. Objective The aim of this study is to explore the actual use of mobile health apps for diabetes among patients with T2DM and the main barriers and drivers among app users and nonusers. Methods An explanatory sequential design was applied, starting with a web-based questionnaire followed by semistructured in-depth interviews. Data were collected between July and December 2020. Questionnaire data from 103 respondents were analyzed using IBM SPSS Statistics (version 25.0). Descriptive statistics were performed for the actual use of apps and items of the Unified Theory of Acceptance and Use of Technology (UTAUT). The UTAUT includes 4 key constructs: performance expectancy (the belief that an app will help improve health performance), effort expectancy (level of ease associated with using an app), social influence (social support), and facilitating conditions (infrastructural support). Differences between users and nonusers were analyzed using chi-square tests for individual items. Independent 2-tailed t tests were performed to test for differences in mean scores per the UTAUT construct. In total, 16 respondents participated in the interviews (10 users and 6 nonusers of apps for T2DM). We performed content analysis using a deductive approach on all transcripts, guided by the UTAUT. Results Regarding actual use, 55.3% (57/103) were nonusers and 44.7% (46/103) were users of apps for T2DM. The main driver for the use of apps was the belief that using apps for managing diabetes would result in better personal health and well-being. The time and energy required to keep track of the data and understand the app were mentioned as barriers. Mean scores were significantly higher among users compared with nonusers of apps for T2DM for the constructs performance expectancy (4.06, SD 0.64 vs 3.29, SD 0.89; P<.001), effort expectancy (4.04, SD 0.62 vs 3.50, SD 0.82; P<.001), social influence (3.59, SD 0.55 vs 3.29, SD 0.54; P=.007), and facilitating conditions (4.22, SD 0.48 vs 3.65, SD 0.70; P<.001). On the basis of 16 in-depth interviews, it was recognized that health care professionals play an important role in supporting patients with T2DM in using apps. However, respondents noticed that their health care professionals were often not supportive of the use of apps for managing diabetes, did not show interest, or did not talk about apps. Reimbursement by insurance companies was mentioned as a missing facilitator. Conclusions Empowering health care professionals’ engagement is of utmost importance in supporting patients with T2DM in the use of apps. Insurance companies can play a role in facilitating the use of diabetes apps by ensuring reimbursement.

Background Mobile health apps are promising tools to help patients with type 2 diabetes mellitus (T2DM) improve their health status and thereby achieve diabetes control and self-management. Although there is a wide array of mobile health apps for T2DM available at present, apps are not yet integrated into routine diabetes care. Acceptability and acceptance among patients with T2DM is a major challenge and prerequisite for the successful implementation of apps in diabetes care. Objective This study provides an in-depth understanding of the perceptions of patients with T2DM before use (acceptability) and after use (acceptance) regarding 4 different mobile health apps for diabetes control and self-management. Methods A descriptive qualitative research design was used in this study. Participants could choose 1 of the 4 selected apps for diabetes control and self-management (ie, Clear.bio in combination with FreeStyle Libre, mySugr, MiGuide, and Selfcare). The selection was based on a systematic analysis of the criteria for (functional) requirements regarding monitoring, data collection, provision of information, coaching, privacy, and security. To explore acceptability, 25 semistructured in-depth interviews were conducted with patients with T2DM before use. This was followed by 4 focus groups to discuss the acceptance after use. The study had a citizen science approach, that is, patients with T2DM collaborated with researchers as coresearchers. All coresearchers actively participated in the preparation of the study, data collection, and data analysis. Data were collected between April and September 2021. Thematic analysis was conducted using a deductive approach using AtlasTi9. Results In total, 25 coresearchers with T2DM participated in this study. Of them, 12 coresearchers tested Clear, 5 MiGuide, 4 mySugr, and 4 Selfcare. All coresearchers participated in semistructured interviews, and 18 of them attended focus groups. Personal health was the main driver of app use. Most coresearchers were convinced that a healthy lifestyle would improve blood glucose levels. Although most coresearchers did not expect that they need to put much effort into using the apps, the additional effort to familiarize themselves with the app use was experienced as quite high. None of the coresearchers had a health care professional who provided suggestions on using the apps. Reimbursement from insurance companies and the acceptance of apps for diabetes control and self-management by the health care system were mentioned as important facilitating conditions. Conclusions The research showed that mobile health apps provide support for diabetes control and self-management in patients with T2DM. Integrating app use in care as usual and guidelines for health care professionals are recommended. Future research is needed on how to increase the implementation of mobile health apps in current care pathways. In addition, health care professionals need to improve their digital skills, and lifelong learning is recommended.

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 long-term 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.