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Background Across Europe, young carers (YCs) and their need for support receive limited attention in the media, policy and empirical research, even though, similar to adult carers, they also provide care to ill family members. The Delphi study, a qualitative research methodology, which provides the focus for this article, had the overall aim of exploring existing successful strategies to support YCs. Compared to YCs, even less is known about adolescent young carers (AYCs), a group that is in a critical life transition phase. The study forms part of an EU Horizon 2020 funded research project on AYCs aged 15–17 years old. Methods A two-round Delphi study was conducted with 66 experts on YCs from 10 European countries. Topics included: (i) visibility and awareness-raising of YCs at local, regional, and national levels, (ii) current interventions to support YCs, and (iii) future strategies to support YCs. Results Experts reported a lack of visibility and awareness about YCs in general, and AYCs in particular. Although awareness is slowly increasing in most countries, with the UK ranked highest, experts acknowledged that it remains challenging to identify YCs in many countries. Furthermore, the level and type of support available for YCs differs, with most countries mainly offering support on a local level. Diverse views were expressed regarding future strategies to support YCs. Experts highlighted the importance of specific legislation to formalise the rights of YCs, and the issue of whether young people should be safeguarded from caregiving or if this should be considered part of regular family life. They also emphasised the relevance of available integrated support services for YCs, including schools, family, health and social care. Conclusions In most European countries, there is a lack of awareness and visibility on YCs. Identification of YCs is a crucial first step and there is need for a common definition of YCs, together with greater opportunities for young adults to identify themselves as YCs.

The field of Alzheimer disease (AD) has been moving toward earlier detection, personalized assessment of dementia risk, and dementia prevention. In the near future, a gap is expected between the growing demand for Alzheimer-related health care and a shrinking workforce. Responsibility is increasingly assigned to individuals to take an active role in their own brain health management and dementia prevention. Digital tools are thought to offer support regarding these processes. The aim of this scoping review is to create an overview of digital tools published in scientific literature in the context of AD and dementia aimed at people without an AD or dementia diagnosis as primary end users interacting with these digital tools. Additionally, we aim to gain insight into study sample diversity, the stage of maturity and evaluation of these tools, and recommended future directions. PubMed, IEEE Xplore, Ovid, and Web of Science were searched in January 2023, using terms related to AD and dementia, (pre-)disease stages, digital tools, and various purposes of digital tools. Two independent reviewers screened the titles and abstracts of 2811 records and subsequently 408 full-text articles, based on inclusion and exclusion criteria. Articles on tools targeting those with an AD or dementia diagnosis were excluded. Data extraction included information on the sample characteristics, the digital tool, stage of maturity and evaluation, and future (research) directions. We included 39 articles, which were aimed at primary prevention (14/39, 36%), secondary prevention (11/39, 28%), daily life support (8/39, 21%), self-administered screening (4/39, 10%), or decision-making (2/39, 5%). Variation in the study sample emerged regarding cognitive abilities (healthy: 11/39, 28%; mild cognitive impairment: 12/39, 31%; [subjective] cognitive impairment: 9/39, 23%; \"no dementia\": 1/39, 3%; and variation of cognitive abilities: 6/39, 15%). Less variation was found regarding sex (>50% female: 27/39, 69%), education (>50% high education: 13/39, 33%), and age (>50% >60 y: 23/39, 59%). Few articles reported on ethnicity (12/39, 31%) and digital literacy (11/39, 28%). Most tools were in an early evaluation and maturity stage (31/39, 80%), comprising preprototyping (1/35, 3%), prototyping (15/35, 43%), pilot testing (19/35, 54%), efficacy testing (18/40, 45%), usability testing (12/40, 30%), and feasibility testing (10/40, 25%). Future (research) directions comprised the need for further tool development, attention to diversity, and study advancements, such as large-scale longitudinal studies. Almost 80% of tools as reported on in academic literature are in early development comprising early stages of maturity and evaluation. Studies and evidence gathered for digital tools developed in the context of AD or dementia aimed at people without an AD or dementia diagnosis are thus preliminary and further development, research, and policy are required before these tools can be implemented for assessing, supporting, and preventing cognitive decline.

This paper examines the health-related quality of life (HRQL) and mental health of adolescent young carers (AYCs) aged 15–17 in Switzerland, based on data collected within the Horizon 2020 project ‘Psychosocial support for promoting mental health and well-being among AYCs in Europe’ (ME-WE). It addresses the following questions: (1) Which characteristics of AYCs are associated with lower HRQL and with higher level of mental health problems? (2) Do AYCs who are less visible and less supported report a lower HRQL and more mental health issues than other AYCs? A total of 2343 young people in Switzerland, amongst them 240 AYCs, completed an online survey. The results show that female AYCs and AYCs with Swiss nationality more often reported having mental health issues than their male and non-Swiss counterparts. Furthermore, the findings show a significant association between receiving support for themselves and visibility from their school or employer and the HRQL. Moreover, AYCs who reported that their school or employer knew about the situation also reported fewer mental health issues. These findings can inform recommendations for policy and practice to develop measures aimed at raising the visibility of AYCs, which is the first step for planning AYC tailored support.

Previous work has shown that technology can facilitate the communication of emotions, social touch, and social presence through haptic devices, meaning devices that provide a haptic stimulation. However, for special user groups living in long-term care facilities, such as people with dementia, the applications of these haptic devices are not apparent. The aim of this study is to understand how haptic devices can be used in intramural care facilities in times of social isolation, focusing on haptic devices that utilize haptic sensation. Five haptic devices were tested at three care facilities. Insights from this study highlight the potential of haptic devices to enhance sensory, affective, and social experiences during video calling between residents and their relatives. Moreover, the importance of the tactile sensation and form factor of haptic devices in the care context is addressed, along with insights on how to create the appropriate atmosphere during video calling.

Although the use of artificial intelligence (AI)-based technologies, such as AI-based decision support systems (AI-DSSs), can help sustain and improve the quality and efficiency of care, their deployment creates ethical and social challenges. In recent years, a growing prevalence of high-level guidelines and frameworks for responsible AI innovation has been observed. However, few studies have specified the responsible embedding of AI-based technologies, such as AI-DSSs, in specific contexts, such as the nursing process in long-term care (LTC) for older adults. Prerequisites for responsible AI-assisted decision-making in nursing practice were explored from the perspectives of nurses and other professional stakeholders in LTC. Semistructured interviews were conducted with 24 care professionals in Dutch LTC, including nurses, care coordinators, data specialists, and care centralists. A total of 2 imaginary scenarios about AI-DSSs were developed beforehand and used to enable participants articulate their expectations regarding the opportunities and risks of AI-assisted decision-making. In addition, 6 high-level principles for responsible AI were used as probing themes to evoke further consideration of the risks associated with using AI-DSSs in LTC. Furthermore, the participants were asked to brainstorm possible strategies and actions in the design, implementation, and use of AI-DSSs to address or mitigate these risks. A thematic analysis was performed to identify the opportunities and risks of AI-assisted decision-making in nursing practice and the associated prerequisites for responsible innovation in this area. The stance of care professionals on the use of AI-DSSs is not a matter of purely positive or negative expectations but rather a nuanced interplay of positive and negative elements that lead to a weighed perception of the prerequisites for responsible AI-assisted decision-making. Both opportunities and risks were identified in relation to the early identification of care needs, guidance in devising care strategies, shared decision-making, and the workload of and work experience of caregivers. To optimally balance the opportunities and risks of AI-assisted decision-making, seven categories of prerequisites for responsible AI-assisted decision-making in nursing practice were identified: (1) regular deliberation on data collection; (2) a balanced proactive nature of AI-DSSs; (3) incremental advancements aligned with trust and experience; (4) customization for all user groups, including clients and caregivers; (5) measures to counteract bias and narrow perspectives; (6) human-centric learning loops; and (7) the routinization of using AI-DSSs. The opportunities of AI-assisted decision-making in nursing practice could turn into drawbacks depending on the specific shaping of the design and deployment of AI-DSSs. Therefore, we recommend considering the responsible use of AI-DSSs as a balancing act. Moreover, considering the interrelatedness of the identified prerequisites, we call for various actors, including developers and users of AI-DSSs, to cohesively address the different factors important to the responsible embedding of AI-DSSs in practice.

Young carers are children and adolescents who provide care to other family members or friends, taking over responsibilities that are usually associated with adulthood. There is emerging but still scarce knowledge worldwide about the phenomenon of young carers and the impact of a caring role on their health, social and personal development spheres. This paper provides an overview of the main results from the ME-WE project, which is the first European research and innovation project dedicated to adolescent young carers (AYCs) (15–17 years). The project methods relied on three main activities: (1) a systematization of knowledge (by means of a survey to AYCs, country case studies, Delphi study, literature review); (2) the co-design, implementation and evaluation of a primary prevention intervention addressing AYCs’ mental health (by means of Blended Learning Networks and a clinical trial in six European countries); (3) the implementation of knowledge translation actions for dissemination, awareness, advocacy and lobbying (by means of national and international stakeholder networks, as well as traditional and new media). Project results substantially contributed to a better understanding of AYCs’ conditions, needs and preferences, defined tailored support intervention (resilient to COVID-19 related restrictions), and significant improvements in national and European policies for AYCs.

In Italy, many people aged over 65 cannot live independently, causing an overall decrease in their quality of life and a need for social and health care. Due to the lack of both formal and informal caregivers, technological solutions become of paramount importance in this scenario. This article describes the user-centered development of the GUARDIAN ecosystem, consisting of a social robot integrated with two mobile applications which aim to monitor, coach, and keep the older user company in order to prolong his/her independence at home. In particular, the advancements from the alpha to the beta prototype of the ecosystem are described, achieved through the feedback collected from 41 end users—older people and their carers—that have tested the system for 6 weeks. By enhancing human–robot interaction, a positive improvement in terms of usability and acceptability of the system was retrieved. However, to increase the perceived usefulness and the impact on older users’ lives, it is necessary to make the entire system more customizable, and more capable in providing support for daily activities.

Emerging technologies such as artificial intelligence (AI) require an early-stage assessment of potential societal and ethical implications to increase their acceptability, desirability, and sustainability. This paper explores and compares 2 of these assessment approaches: the responsible innovation (RI) framework originating from technology studies and the co-design approach originating from design studies. While the RI framework has been introduced to guide early-stage technology assessment through anticipation, inclusion, reflexivity, and responsiveness, co-design is a commonly accepted approach in the development of technologies to support the care for older adults with frailty. However, there is limited understanding about how co-design contributes to the anticipation of implications. This paper empirically explores how the co-design process of an AI-based decision support system (DSS) for dementia caregivers is complemented by explicit anticipation of implications. This case study investigated an international collaborative project that focused on the co-design, development, testing, and commercialization of a DSS that is intended to provide actionable information to formal caregivers of people with dementia. In parallel to the co-design process, an RI exploration took place, which involved examining project members' viewpoints on both positive and negative implications of using the DSS, along with strategies to address these implications. Results from the co-design process and RI exploration were analyzed and compared. In addition, retrospective interviews were held with project members to reflect on the co-design process and RI exploration. Our results indicate that, when involved in exploring requirements for the DSS, co-design participants naturally raised various implications and conditions for responsible design and deployment: protecting privacy, preventing cognitive overload, providing transparency, empowering caregivers to be in control, safeguarding accuracy, and training users. However, when comparing the co-design results with insights from the RI exploration, we found limitations to the co-design results, for instance, regarding the specification, interrelatedness, and context dependency of implications and strategies to address implications. This case study shows that a co-design process that focuses on opportunities for innovation rather than balancing attention for both positive and negative implications may result in knowledge gaps related to social and ethical implications and how they can be addressed. In the pursuit of responsible outcomes, co-design facilitators could broaden their scope and reconsider the specific implementation of the process-oriented RI principles of anticipation and inclusion.

Dementia is a syndrome characterized by a wide spectrum of symptoms and needs. There is no cure for this syndrome, which represents a major challenge to society in terms of quality of life for those affected and in terms of workload and stress burden for those who take care of them. The Healthy Ageing Ecosystem for People With Dementia (HAAL) aimed to improve the quality of life of both people with dementia and their formal caregivers (FCs) and informal caregivers (ICs) by providing a personalized set of devices to the person with dementia, along with a dashboard designed for caregivers to monitor and manage the older person. The HAAL platform comprises a dashboard that integrates, aggregates, and analyzes heterogeneous data gathered from an ecosystem of devices designed for and tested with people with dementia. The study was designed as a technical feasibility pilot to test the HAAL ecosystem in 3 countries: Italy, Taiwan, and the Netherlands, where older people with initial, moderate, and severe dementia were enrolled, respectively. The study was run in 2 stages: the alpha and beta pilot studies aimed to test the second and third prototypes of the platform, respectively. The alpha test was conducted from March to May 2023, involving 41 end users, of which 13 were people with dementia, 13 were ICs, and 15 were FCs. The beta test was conducted from September 2023 to February 2024, involving 83 end users, of which 26 were people with dementia, 20 were ICs, and 37 were FCs. The results have been elaborated and are supposed to be published by 2026. The HAAL pilot study was an innovative feasibility study whose primary objectives were to assess reduction in care load for FCs, stress relief for FCs and ICs, and improvement in the perceived quality of life for ICs and people with dementia. The study also evaluated the usability and the acceptance of the platform. Preliminary analyses of the results showed that the HAAL platform partially relieved caregivers' stress and that the quality of life of people with dementia did not worsen over the test period. RR1-10.2196/59860.

Integrated care means doing justice to life in all its facets and supporting it where that is necessary for the client. This advocates the coordination of different forms of care and support and the integrated use of data that is available on these different facets of life. It can be challenging to provide the necessary care, in particular when different people are involved and decisions need to be based on care plans, reports, and other types of information originating from different individuals. However, there is a common understanding that technology is an important facilitator in tackling this challenge. Technology already supports care processes and complements the role of people in many ways. For instance, it takes over tasks and helps to save time, obtain new insights and simplify complexity. Most of the time, using technology comes down to creating, collecting, analyzing and applying big data, or combinations of these. In fact, all our actions - in healthcare, as in society in general - are directed by subjective and objective data, which is often hidden in the minds of people, but also increasingly collected digitally. Until now, the use of different technologies and data is too often not integrated in the organization and put away in separate silos as the use of a technical instrument in care processes is often initiated for specific reasons that do not affect the entire organization or client population. Meanwhile though, more and more opportunities are coming up to connect the different data flows that exist in healthcare, and to utilize the data both organization-transcending as for the individual client. Developments in intelligent software systems AI, amongst others, offer the possibility to rapidly collect, integrate, exchange, edit and analyze large amounts of data. This allows people to respond more proactively to incidents, gain new insights about health, provide customized care and support and improve the cooperation between individuals and disciplines. However, many long-term care organizations in The Netherlands experience these opportunities as something elusive and find it hard to take advantage of them. Though many organizations in Dutch long-term care are interested in the exploration of data-driven healthcare, a common challenge is that enthusiastic innovators within care organizations often have limited time to invest in data-driven care, and do so alone or with the support of only few colleagues. Therefore, innovators from different organizations regularly come together within networks where they share experiences and experiment. At the same time, despite the promises of data-driven healthcare, there are many dilemmas around privacy, security, access to data, risk of stigmatization and medicalization and the increasing dependence on technology, for instance. When experimenting, the dilemmas should be taken seriously and in co-creation between multiple organizations, codes of conduct on these issues can be developed step-by-step. This paper will share some experiences and lessons learned, both by individual organizations and in workshops in which they collaborated. The approach is that by creating room for experimenting, starting small and sharing experiences with other parties, ‘big data’ can be made small.