Background: The worldwide increase in community-dwelling people with dementia underscores the need for innovative eHealth technologies that aim to provide support to both patients and their informal caregivers in the home setting. However, sustainable implementation of eHealth technologies within this target group can be difficult. Objective: The goal of this study was to gain a thorough understanding of why it is often difficult to implement eHealth technologies in practice, even though numerous technologies are designed to support people with dementia and their informal caregivers at home. In particular, our study aimed to (1) provide an overview of technologies that have been used and studied in the context of informal dementia care and (2) explore factors influencing the implementation of these technologies. Methods: Following an umbrella review design, five different databases were searched (PubMed, PsycINFO, Medline, Scopus, and Cochrane) for (systematic) reviews. Among 2205 reviews retrieved, 21 were included in our analysis based on our screening and selection procedure. A combination of deductive and inductive thematic analyses was performed, using the Nonadoption, Abandonment, Scale-Up, Spread, and Sustainability (NASSS) framework for organizing the findings. Results: We identified technologies designed to be used “by informal caregivers,” “by people with dementia,” and “with people with dementia.” Within those groups, most of the represented technologies included, respectively: (i) devices for in-home monitoring of lifestyle, health, and safety; (ii) technologies for supporting memory, orientation, and day structure; and (iii) technologies to facilitate communication between the informal caregiver and person with dementia. Most of the identified factors influencing implementation related to the condition of dementia, characteristics of the technology, expected/perceived value of users, and characteristics of the informal caregiver. Considerably less information has been reported on factors related to the implementing organization and technology supplier, wider institutional and sociocultural context of policy and regulations, and continued adaptation of technology over time. Conclusions: Our study offers a comprehensive overview of eHealth technologies in the context of informal dementia care and contributes to gaining a better understanding of a broad range of factors influencing their implementation. Our results uncovered a knowledge gap regarding success factors for implementation related to the organizational and broader context and continuous adaptation over the long term. Although future research is needed, the current findings can help researchers and stakeholders in improving the development and implementation of eHealth technologies to support informal dementia care.

(1) Background: The COVID-19 pandemic forced people from all around the globe to strongly modify their daily routines, putting a significant strain on the social aspects of daily lives. While the first wave of the pandemic was a very challenging time in all countries, it is still uncertain whether various lockdown intensities and infection rates differed regarding their psychosocial impact. This work therefore aimed to investigate (i) the psychosocial effects of home confinement in two European countries that underwent different lockdown intensities: Italy and the Netherlands and (ii) the role of communication technology in relation to feelings of loneliness. (2) Methods: A cross-sectional online survey inquiring about different psychosocial variables and the use of and satisfaction towards communication technology was circulated among the general public during the first wave of the COVID-19 pandemic. In total, 629 participants (66% female, 68% from the Netherlands) answered each question twice, referring to “before” and “during” the pandemic. (3) Results: We found significant negative effects of COVID-19 home confinement on depressive feelings (p < 0.001, %∆ = +54%), loneliness (p < 0.001, %∆ = +37.3%), life satisfaction (p < 0.001, %∆ = −19.8%) and mental wellbeing (p < 0.001, %∆ = −10.6%) which were accompanied with a significantly increased need for psychosocial support (p < 0.001, %∆ = +17.3%). However, the magnitude of psychosocial impact did not significantly differ between residents undergoing a more intense (Italy) versus a less intense (Netherlands) lockdown, although the decrease in social participation was found to be significantly different for both countries (z = −7.714, p < 0.001). Furthermore, our findings demonstrate that the increase in loneliness was associated with the adoption of new digital communication tools (r = 0.21, p < 0.001), and significantly higher for individuals who started to adopt at least one new digital communication tool during confinement than for those who did not (z = −4.252, p < 0.001). (4) Conclusions: This study highlights that, although COVID-19 home confinement significantly impacted psychosocial wellbeing during the first wave of the pandemic, this impact did not differ based on lockdown intensity. Recognizing the increasing adoption of digital communication technology in an attempt to reduce lockdown loneliness, future studies should investigate what is needed from the technology to achieve this effect.

Introduction: Informal caregivers offer continuous unpaid support to loved ones who are unable to live independently. Providing care can be a very burdensome commitment, that heavily impacts informal caregivers’ mental health. eMental health is a possible, yet challenging, solution to improve caregivers’ mental health and their overall experience of caregiving. In fact, eMental health technologies often face challenges of implementation. The present work gathers knowledge on how to best deal with these challenges by collecting testimonies of implementation experts of eight eMental health technologies for informal caregivers with the aim of comparing them and extracting lessons learned.Methods: For this multiple case study, technologies were selected (through informal suggestions and independent search) according to the following inclusion criteria: they were intended for informal caregivers as main user group, were aimed at improving informal caregivers’ mental wellbeing and caregiving experience and were available and running in real life settings in Europe. Ten interviews were conducted (two pilots and eight included cases). The interviewees were asked to provide a description of the technology and its aims and their implementation approach, method and frameworks used. Finally, determinants of implementation, the influence of the Covid-19 pandemic on implementation processes and lessons learned were investigated.Results: The results highlight key differences between technologies developed within academia and the industry regarding efficacy testing and use and use and choice of frameworks. Also, similarities in terms of recognized barriers such as financing are illustrated.Discussion: Possible ways to overcome main barriers and examples of best practices, such as structuring a business model and discussing tool maintenance and long-term hosting in advance, are discussed.

Background: Although eMental health interventions are a viable solution to address disparities in access to mental healthcare and increase its efficiency, they still face challenges of implementation. Literature highlights numerous barriers such as diffusion of responsibility and unclear expectations of what implementation entails might hinder this process. While research mostly focuses on analyzing these barriers, there is an urgent need to increase uptake in practice. In turn, commercial companies focus mostly on increasing uptake, while overlooking research outputs. To bridge the gap between research and practice, attention to how implementation occurs in practice is required. This study investigates “Make it Happen” (MiH), the implementation model developed by the eMental Health company Minddistrict, aiming to gain more insight into operationalizing implementation frameworks by 1) describing MiH and its conceptual underpinnings, and 2) gaining lessons learned from the development of MiH. Ultimately, this work aims at improving existing scientific frameworks by extending them with knowledge from practice. Methods: First, individual interviews and focus groups with Minddistrict implementation managers were performed. Second, individual interviews with project leads in mental healthcare organizations that were involved in the implementation of Minddistrict were conducted. Within Minddistrict, 7 implementation managers and account managers were involved, in addition to 11 project leads from mental healthcare organizations. Data were elaborated with thematic analysis. Results: A comprehensive description of MiH and its 5 main phases was achieved. During the 1) Onboarding phase, implementing organizations are guided by Minddistrict to build a team responsible for implementation, which then 2) designs patient and client journeys, 3) builds, tailors and configures their offer, 4) trains key-users and, 5) evaluates the success of implementation. All participants had extensive and aligned definitions and articulated expectations on implementation. Points of improvement for the model such as role ambiguity and excessive workload were identified. As strengths, internal motivation and good relationships with the provider were valued. Conclusion: The present study highlights the importance of clear role division and stakeholder engagement in implementation processes, and suggest that a strong collaboration between companies and academia could optimize implementation efforts and ensure a better fit between humans, context, and technologies.

BACKGROUND The worldwide increase in community-dwelling people with dementia underscores the need for innovative eHealth technologies that aim to provide support to both patients and their informal caregivers in the home setting. However, sustainable implementation of eHealth technologies within this target group can be difficult. OBJECTIVE The goal of this study was to gain a thorough understanding of why it is often difficult to implement eHealth technologies in practice, even though numerous technologies are designed to support people with dementia and their informal caregivers at home. In particular, our study aimed to (1) provide an overview of technologies that have been used and studied in the context of informal dementia care and (2) explore factors influencing the implementation of these technologies. METHODS Following an umbrella review design, five different databases were searched (PubMed, PsycINFO, Medline, Scopus, and Cochrane) for (systematic) reviews. Among 2205 reviews retrieved, 21 were included in our analysis based on our screening and selection procedure. A combination of deductive and inductive thematic analyses was performed, using the Nonadoption, Abandonment, Scale-Up, Spread, and Sustainability (NASSS) framework for organizing the findings. RESULTS We identified technologies designed to be used “by informal caregivers,” “by people with dementia,” and “with people with dementia.” Within those groups, most of the represented technologies included, respectively: (i) devices for in-home monitoring of lifestyle, health, and safety; (ii) technologies for supporting memory, orientation, and day structure; and (iii) technologies to facilitate communication between the informal caregiver and person with dementia. Most of the identified factors influencing implementation related to the condition of dementia, characteristics of the technology, expected/perceived value of users, and characteristics of the informal caregiver. Considerably less information has been reported on factors related to the implementing organization and technology supplier, wider institutional and sociocultural context of policy and regulations, and continued adaptation of technology over time. CONCLUSIONS Our study offers a comprehensive overview of eHealth technologies in the context of informal dementia care and contributes to gaining a better understanding of a broad range of factors influencing their implementation. Our results uncovered a knowledge gap regarding success factors for implementation related to the organizational and broader context and continuous adaptation over the long term. Although future research is needed, the current findings can help researchers and stakeholders in improving the development and implementation of eHealth technologies to support informal dementia care.

Background: With the growing need of support for informal caregivers (ICs) and care recipients (CRs) during COVID-19, the uptake of digital care collaboration platforms such as Caren increased. Caren is a platform designed to (1) improve communication and coordination between ICs and health care professionals, (2) provide a better overview of the care process, and (3) enhance safe information sharing within the care network. Insights on the impact of COVID-19 on the implementation and use of informal care platforms such as Caren are still lacking. Objective: This study aimed to (1) identify technology developers’ lessons learned from the continued implementation of Caren during COVID-19 and (2) examine pre-post COVID-19 changes in usage behavior and support functionality use of Caren. Methods: A focus group with developers of the Caren platform (N=3) was conducted to extract implementation lessons learned. Focus group data were first analyzed deductively, using the Consolidated Framework for Implementation Research domains (ie, individual characteristics, intervention characteristics, inner setting, and outer setting). Later, inductive analysis of overarching themes was performed. Furthermore, survey data were collected in 2019 (N=11,635) and 2022 (N=5573) among Caren platform users for comparing usage behavior and support functionality use. Data were analyzed using descriptive and inferential statistics. Results: Several lessons from the continued implementation of Caren during COVID-19 were identified. Those included, for example, alternative ways to engage with end users, incorporating automated user support and large-scale communication features, considering the fluctuation of user groups, and addressing data transparency concerns in health care. Quantitative results showed that the number of ICs and CRs who used Caren several times per day increased significantly (P<.001 for ICs and CRs) between 2019 (ICs: 23.8%; CRs: 23.2%) and 2022 (ICs: 35.2%; CRs: 37%), as well as the use of certain support functionalities such as a digital agenda to make and view appointments, a messaging function to receive updates and communicate with formal and informal caregivers, and digital notes to store important information. Conclusions: Our study offers insights into the influence of the COVID-19 pandemic on the usage and implementation of the digital informal care support platform Caren. The study shows how platform developers maintained the implementation during COVID-19 and which support functionalities gained relevance among ICs and CRs throughout the pandemic. The findings can be used to improve the design and implementation of current and future digital platforms to support informal care toward the “new digital normal.”