Aim: Remote patient management (RPM) effectively aids cardiovascular risk management, but its large-scale implementation remains challenging. Panel management may facilitate implementation by using comprehensive data to identify patients at risk of cardiovascular diseases and tailor interventions. This study evaluated the implementation strategies and clinical outcomes of a multi-component RPM intervention ‘Connect@Heart’. Methods: We conducted a mixed-methods study over six months in four primary care practices in the Netherlands, evaluating two patient groups: (i) patients with a BMI < 25 received a blood pressure monitor alone (BP Box), and (ii) patients with a BMI > 25 or cardiovascular disease received a combination of a BP monitor, a scale, and an activity tracker (Lifestyle Box). Baseline and six-month follow-up assessments were performed using linear mixed-effects models, and implementation outcomes were evaluated using the RE-AIM framework. Results: Our approach achieved high enrolment, with 189 out of 200 initially interested patients (94%) participating. The intervention was associated with a significant reduction in BP levels within both groups (BP Box systolic BP from 139 ± 21 mmHg at baseline to 132 ± 18 mmHg at follow-up, p < 0.001 and Lifestyle Box 142 ± 16 mmHg to 131 ± 14 mmHg at follow-up, p < 0.001), especially for those with uncontrolled hypertension. After six months, 66% of patients performed measurements weekly. All participating practices continued using the intervention post-study. Conclusion: This study demonstrates that proactively identifying patient panels at risk for CVD and tailoring multi-component RPM interventions to patient panels are promising implementation strategies for reaching favourable clinical outcomes at scale.

Introduction: eHealth seems promising in addressing challenges in the provision of care for Huntington’s disease (HD) across Europe. By harnessing information and communication technologies, eHealth can partially relocate care from specialized centers to the patients’ home, thereby increasing the availability and accessibility of specialty care services beyond regional borders. Previous research on eHealth (development) in HD is however limited, especially when it comes to including eHealth services specifically designed together with HD gene expansion carriers (HDGECs) and their partners to fit their needs and expectations. Methods: This article describes the qualitative human-centered design process and first evaluations of the Huntington Support App prototype: a web-app aimed to support the quality of life (QoL) of HDGECs and their partners in Europe. Prospective end-users, i.e., HDGECs, their partners, and healthcare providers (HCPs), from different countries were involved throughout the development process. Through interviews, we captured people’s experiences with the disease, quality of life (QoL), and eHealth. We translated their stories into design directions that were further co-designed and subsequently evaluated with the user groups. Results: The resulting prototype centralizes clear and reliable information on the disease, HD-related news and events, as well as direct contact possibilities with HCPs via an online walk-in hour or by scheduling an appointment. The app’s prototype was positively received and rated as (very) appealing, pleasant, easy to use and helpful by both HDGECs and partners. Discussion: By involving end-users in every step, we developed a healthcare app that meets relevant needs of individuals affected by HD and therefore may lead to high adoption and retention rates. As a result, the app provides low-threshold access to reliable information and specialized care for HD in Europe. A description of the Huntington Support App as well as implications for further development of the app’s prototype are provided.

The aim of this study was to quantify physical activity and sedentary behavior in older adults recovering from hip fracture and to identify groups based on movement patterns. In this cross-sectional cohort study, older adults (≥70 years) were included 3 months after surgery for proximal femoral fracture. Patients received an accelerometer for 7 days. Demographics and outcomes related to physical function, mobility, cognitive functions, quality of life, and hip fracture were assessed. In total, 43 patients with sufficient accelerometer wear time were included. Across all groups, participants engaged in very low levels of physical activity, spending an average of 11 hr/day in prolonged sedentary behavior. Based on the extracted components from a principal component analysis, three groups with substantial differences in levels of physical activity and sedentary behavior could be distinguished.

BACKGROUND: People with a low socioeconomic position (SEP) are less likely to benefit from eHealth interventions, exacerbating social health inequalities. Professionals developing eHealth interventions for this group face numerous challenges. A comprehensive guide to support these professionals in their work could mitigate these inequalities. OBJECTIVE: We aimed to develop a web-based guide to support professionals in the development, adaptation, evaluation, and implementation of eHealth interventions for people with a low SEP. METHODS: This study consisted of 2 phases. The first phase involved a secondary analysis of 2 previous qualitative and quantitative studies. In this phase, we synthesized insights from the previous studies to develop the guide's content and information structure. In the second phase, we used a participatory design process. This process included iterative development and evaluation of the guide's design with 11 professionals who had experience with both eHealth and the target group. We used test versions (prototypes) and think-aloud testing combined with semistructured interviews and a questionnaire to identify design requirements and develop and adapt the guide accordingly. RESULTS: The secondary analysis resulted in a framework of recommendations for developing the guide, which was categorized under 5 themes: development, reach, adherence, evaluation, and implementation. The participatory design process resulted in 16 requirements on system, content, and service aspects for the design of the guide. For the system category, the guide was required to have an open navigation strategy leading to more specific information and short pages with visual elements. Content requirements included providing comprehensible information, scientific evidence, a user perspective, information on practical applications, and a personal and informal tone of voice. Service requirements involved improving suitability for different professionals, ensuring long-term viability, and a focus on implementation. Based on these requirements, we developed the final version of "the inclusive eHealth guide." CONCLUSIONS: The inclusive eHealth guide provides a practical, user-centric tool for professionals aiming to develop, adapt, evaluate, and implement eHealth interventions for people with a low SEP, with the aim of reducing health disparities in this population. Future research should investigate its suitability for different end-user goals, its external validity, its applicability in specific contexts, and its real-world impact on social health inequality.

Objective: eHealth interventions can improve the health outcomes of people with a low socioeconomic position (SEP) by promoting healthy lifestyle behaviours. However, developing and implementing these interventions among the target group can be challenging for professionals. To facilitate the uptake of effective interventions, this study aimed to identify the barriers and facilitators anticipated or experienced by professionals in the development, reach, adherence, implementation and evaluation phases of eHealth interventions for people with a low SEP. Method: We used a Delphi method, consisting of two online questionnaires, to determine the consensus on barriers and facilitators anticipated or experienced during eHealth intervention phases and their importance. Participants provided open-ended responses in the first round and rated statements in the second round. The interquartile range was used to calculate consensus, and the (totally) agree ratings were used to assess importance. Results: Twenty-seven professionals participated in the first round, and 19 (70.4%) completed the second round. We found a consensus for 34.8% of the 46 items related to highly important rated barriers, such as the lack of involvement of low-SEP people in the development phase, lack of knowledge among professionals about reaching the target group, and lack of knowledge among lower-SEP groups about using eHealth interventions. Additionally, we identified a consensus for 80% of the 60 items related to highly important rated facilitators, such as rewarding people with a low SEP for their involvement in the development phase and connecting eHealth interventions to the everyday lives of lower-SEP groups to enhance reach. Conclusion: Our study provides valuable insights into the barriers and facilitators of developing eHealth interventions for people with a low SEP by examining current practices and offering recommendations for future improvements. Strengthening facilitators can help overcome these barriers. To achieve this, we recommend defining the roles of professionals and lower-SEP groups in each phase of eHealth intervention and disseminating this study's findings to professionals to optimize the impact of eHealth interventions for this group.

Objective: This study aimed to design a persuasive game, using objective adherence data, to motivate people with asthma to adhere to their medication regimen. Methods: A participatory user-centered design approach was employed, involving end-users and other stakeholders throughout the study. The approach consisted of four phases. Semi-structured interviews and a survey were conducted to understand user needs and reasons for poor adherence (Phase 1: define). Key themes were identified, leading to the formulation of behavior change strategies and design and game requirements. Several design directions were ideated, resulting in a concept for a serious game (Phase 2: ideate). Two rounds of user-tests were performed to evaluate a prototype of the serious game in terms of usability, perceived impact on medication adherence and motivation (Phase 3: prototype and Phase 4: evaluate). Results: Findings from semi-structured interviews (n = 6) and the online survey (n = 20) revealed that people’s non-adherence was often attributed to the perception of asthma as an episodic condition, the delayed experienced effect of maintenance inhalers, and lack of knowledge regarding difference of effect between maintenance and reliever inhalers. The study used behavior change strategies to translate these insights into design requirements for the development of the narrative-based persuasive game Ademgenoot. This six-week challenge-based game combines various behavior change strategies, including personal goal setting and continuous visual feedback, as well as persuasive game design elements, such as a narrative and rewards, with the aim of enhancing motivation to adhere to their medication regimen. User-testing (n = 8; round 1 and 2) showed that Ademgenoot is feasible in clinical practice and has the potential to support people with mild asthma in adherence to their maintenance medication. Discussion: Future efforts should be directed towards a larger evaluation to assess the impact on motivation and inhaler use behaviour. Plain Language Summary: The goal of this study was to create a serious game that encourages people with asthma to take their medication regularly. During the study, we worked closely with individuals who have asthma and other stakeholders throughout the study. We conducted interviews and surveys to understand why people have difficulties using their maintenance inhaler as prescribed by their doctor. Based on the feedback we received, we developed a serious game called “Ademgenoot”. The game uses information on inhaler use automatically collected with a device attached to the inhaler. The game includes features like personal goals and visual feedback on inhaler use to motivate users to take their medication consistently. We tested a prototype of the game with users to see if it was easy to use and if it motivated them to use their maintenance inhaler. The results showed that Ademgenoot is a viable option for helping individuals with mild asthma stay on track with their medication.

Background: Current eHealth interventions are poorly adopted by people with low health literacy (LHL) as they often fail to meet their needs, skills, and preferences. A major reason for this poor adoption is the generic, one-size-fits-all approach taken by designers of these interventions, without addressing the needs, skills, and preferences of disadvantaged groups. Participatory design approaches are effective for developing interventions that fit the needs of specific target groups; yet, very little is known about the practical implications of executing a participatory design project for and with people with LHL. Objective: This study aimed to demonstrate the application of participatory design activities specifically selected to fit the needs and skills of people with LHL and how these were manifested within an overarching eHealth design process. In addition, the study aims to present reflections and implications of these activities that could support future designers to engage people with LHL in their design processes. Methods: We used the design process of a smart asthma inhaler for people with asthma and LHL to demonstrate participatory design activities. The study was framed under 5 stages of design thinking: empathize, define, ideate, prototype, and test within 2 major iteration cycles. We integrated 3 participatory design activities deemed specifically appropriate for people with LHL: co-constructing stories, experience prototype exhibition, and video prototype evaluation. Results: Co-constructing stories was found to deepen the understanding of the participant’s motivation to use or not to use maintenance medication. This understanding informed and facilitated the subsequent development of diverse preliminary prototypes of possible interventions. Discussing these prototypes in the experience prototype exhibition helped provoke reactions, thoughts, and feelings about the interventions, and potential scenarios of use. Through the video prototype evaluation, we were able to clearly communicate the goal and functionality of the final version of our intervention and gather appropriate responses from our participants. Conclusions: This study demonstrates a participatory design approach for and with patients with asthma and LHL. We demonstrated that careful consideration and selection of activities can result in participants that are engaged and feel understood. This paper provides insight into the practical implications of participatory activities with people with LHL and supports and inspires future designers to engage with this disadvantaged target group.

Promoting health behaviors and preventing chronic diseases through a healthy lifestyle among those with a low socioeconomic status (SES) remain major challenges. eHealth interventions are a promising approach to change unhealthy behaviors in this target group. Objective: This review aims to identify key components, barriers, and facilitators in the development, reach, use, evaluation, and implementation of eHealth lifestyle interventions for people with a low SES. This review provides an overview for researchers and eHealth developers, and can assist in the development of eHealth interventions for people with a low SES. Methods: We performed a scoping review based on Arksey and O'Malley's framework. A systematic search was conducted on PubMed, MEDLINE (Ovid), Embase, Web of Science, and the Cochrane Library, using terms related to a combination of the following key constructs: eHealth, lifestyle, low SES, development, reach, use, evaluation, and implementation. There were no restrictions on the date of publication for articles retrieved upon searching the databases. Results: The search identified 1323 studies, of which 42 met our inclusion criteria. An update of the search led to the inclusion of 17 additional studies. eHealth lifestyle interventions for people with a low SES were often delivered via internet-based methods (eg, websites, email, Facebook, and smartphone apps) and offline methods, such as texting. A minority of the interventions combined eHealth lifestyle interventions with face-to-face or telephone coaching, or wearables (blended care). We identified the use of different behavioral components (eg, social support) and technological components (eg, multimedia) in eHealth lifestyle interventions. Facilitators in the development included iterative design, working with different disciplines, and resonating intervention content with users. Facilitators for intervention reach were use of a personal approach and social network, reminders, and self-monitoring. Nevertheless, barriers, such as technological challenges for developers and limited financial resources, may hinder intervention development. Furthermore, passive recruitment was a barrier to intervention reach. Technical difficulties and the use of self-monitoring devices were common barriers for users of eHealth interventions. Only limited data on barriers and facilitators for intervention implementation and evaluation were available. Conclusions: While we found large variations among studies regarding key intervention components, and barriers and facilitators, certain factors may be beneficial in building and using eHealth interventions and reaching people with a low SES. Barriers and facilitators offer promising elements that eHealth developers can use as a toolbox to connect eHealth with low SES individuals. Our findings suggest that one-size-fits-all eHealth interventions may be less suitable for people with a low SES. Future research should investigate how to customize eHealth lifestyle interventions to meet the needs of different low SES groups, and should identify the components that enhance their reach, use, and effectiveness.

Background: Healthy living is key in the prevention and rehabilitation of cardiovascular disease (CVD). Yet, supporting and maintaining a healthy lifestyle is exceptionally difficult and people differ in their needs regarding optimal support for healthy lifestyle interventions. Objective: The goals of this study were threefold: to uncover stakeholders’ needs and preferences, to translate these to core values, and develop eHealth technology based on these core values. Our primary research question is: What type of eHealth application to support healthy living among people with (a high risk of) CVD would provide the greatest benefit for all stakeholders? Methods: User-centered design principles from the CeHRes roadmap for eHealth development were followed to guide the uncovering of important stakeholder values. Data were synthesized from various qualitative studies (i.e., literature studies, interviews, think-aloud sessions, focus groups) and usability tests (i.e., heuristic evaluation, cognitive walkthrough, think aloud study). We also developed an innovative application evaluation tool to perform a competitor analysis on 33 eHealth applications. Finally, to make sure to take into account all end-users needs and preferences in eHealth technology development, we created personas and a customer journey. Results: We uncovered 10 universal values to which eHealth-based initiatives to support healthy living in the context of CVD prevention and rehabilitation should adhere to (e.g., providing social support, stimulating intrinsic motivation, offering continuity of care). These values were translated to 14 desired core attributes and then prototype designs. Interestingly, we found that the primary attribute of good eHealth technology was not a single intervention principle, but rather that the technology should be in the form of a digital platform disseminating various interventions, i.e., a ‘one-stop-shop’. Conclusion: Various stakeholders in the field of cardiovascular prevention and rehabilitation may benefit most from utilizing one personalized eHealth platform that integrates a variety of evidence-based interventions, rather than a new tool. Instead of a one-size-fits-all approach, this digital platform should aid the matchmaking between patients and specific interventions based on personal characteristics and preferences.