BACKGROUND: To evaluate the effects of nurse-led multifactorial care to prevent disability in community-living older people.METHODS: In a cluster randomized trail, 11 practices (n = 1,209 participants) were randomized to the intervention group, and 13 practices (n = 1,074 participants) were randomized to the control group. Participants aged ≥ 70 years were at increased risk of functional decline based on a score ≥ 2 points on the Identification of Seniors at Risk- Primary Care, ISAR-PC. Participants in the intervention group received a systematic comprehensive geriatric assessment, and individually tailored multifactorial interventions coordinated by a trained community-care registered nurse (CCRN) with multiple follow-up home visits. The primary outcome was the participant's disability as measured by the modified Katz activities of daily living (ADL) index score (range 0-15) at one year follow-up. Secondary outcomes were health-related quality of life, hospitalization, and mortality.RESULTS: At baseline, the median age was 82.7 years (IQR 77.0-87.1), the median modified Katz-ADL index score was 2 (IQR 1-5) points in the intervention group and 3 (IQR 1-5) points in the control group. The follow-up rate was 76.8% (n = 1753) after one year and was similar in both trial groups. The adjusted intervention effect on disability was -0.07 (95% confidence interval -0.22 to 0.07; p = 0.33). No intervention effects were found for the secondary outcomes.CONCLUSIONS: We found no evidence that a one-year individualized multifactorial intervention program with nurse-led care coordination was better than the current primary care in community-living older people at increased risk of functional decline in The Netherlands.TRIAL REGISTRATION: Netherlands Trial Register NTR2653.
MULTIFILE
The ageing of people with intellectual disabilities, with associated morbidity like dementia, calls for new types of care. Person-centered methods may support care staff in providing this, an example being Dementia Care Mapping (DCM). DCM has been shown to be feasible in ID-care. We examined the experiences of ID-professionals in using DCM. We performed a mixed-methods study, using quantitative data from care staff (N = 136) and qualitative data (focus-groups, individual interviews) from care staff, group home managers and DCM-in-intellectual disabilities mappers (N = 53). ageing, dementia, Dementia Care Mapping, intellectual disability, mixed-methods, personcentred care
MULTIFILE
Intensive collaboration between different disciplines is often not without obstacles—healthcare and creative professionals come from different worlds that are not automatically aligned. This study investigates the research question: how do project partners in Create-Health innovation collaborate across boundaries, and how does it add value to interdisciplinary collaboration? It addresses the close collaborations between researchers and practice partners from creative industry and healthcare sector within ten research projects on eHealth innovation. It describes the way that Create-Health collaboration took shape across disciplinary boundaries and provides examples of boundary crossing from the ten projects, with the objective of stimulating learning in the creative and health sectors on creative ways of working on interdisciplinary projects. Findings focus on the way partners from various backgrounds work together across disciplinary boundaries and on the benefits that such collaborations bring for a project.
Effectiveness of Supported Education for students with mental health problems, an experimental study.The onset of mental health problems generally occurs between the ages of 16 and 23 – the years in which young people follow postsecondary education, which is a major channel in ourso ciety to prepare for a career and enhance life goals. Several studies have shown that students with mental health problems have a higher chance of early school leaving. Supported Education services have been developed to support students with mental health to remain at school. The current project aims to study the effect of an individually tailored Supported Education intervention on educational and mental health outcomes of students with mental health problems at a university of applied sciences and a community college. To that end, a mixed methods design will be used. This design combines quantitative research (Randomized Controlled Trial) with qualitative research (focus groups, monitoring, interviews). 100 students recruited from the two educational institutes will be randomly allocated to either the intervention or control group.
-Chatbots are being used at an increasing rate, for instance, for simple Q&A conversations, flight reservations, online shopping and news aggregation. However, users expect to be served as effective and reliable as they were with human-based systems and are unforgiving once the system fails to understand them, engage them or show them human empathy. This problem is more prominent when the technology is used in domains such as health care, where empathy and the ability to give emotional support are most essential during interaction with the person. Empathy, however, is a unique human skill, and conversational agents such as chatbots cannot yet express empathy in nuanced ways to account for its complex nature and quality. This project focuses on designing emotionally supportive conversational agents within the mental health domain. We take a user-centered co-creation approach to focus on the mental health problems of sexual assault victims. This group is chosen specifically, because of the high rate of the sexual assault incidents and its lifetime destructive effects on the victim and the fact that although early intervention and treatment is necessary to prevent future mental health problems, these incidents largely go unreported due to the stigma attached to sexual assault. On the other hand, research shows that people feel more comfortable talking to chatbots about intimate topics since they feel no fear of judgment. We think an emotionally supportive and empathic chatbot specifically designed to encourage self-disclosure among sexual assault victims could help those who remain silent in fear of negative evaluation and empower them to process their experience better and take the necessary steps towards treatment early on.
In this project, we explore how healthcare providers and the creative industry can collaborate to develop effective digital mental health interventions, particularly for survivors of sexual assault. Sexual assault victims face significant barriers to seeking professional help, including shame, self-blame, and fear of judgment. With over 100,000 cases reported annually in the Netherlands the need for accessible, stigma-free support is urgent. Digital interventions, such as chatbots, offer a promising solution by providing a safe, confidential, and cost-effective space for victims to share their experiences before seeking professional care. However, existing commercial AI chatbots remain unsuitable for complex mental health support. While widely used for general health inquiries and basic therapy, they lack the human qualities essential for empathetic conversations. Additionally, training AI for this sensitive context is challenging due to limited caregiver-patient conversation data. A key concern raised by professionals worldwide is the risk of AI-driven chatbots being misused as therapy substitutes. Without proper safeguards, they may offer inappropriate responses, potentially harming users. This highlights the urgent need for strict design guidelines, robust safety measures, and comprehensive oversight in AI-based mental health solutions. To address these challenges, this project brings together experts from healthcare and design fields—especially conversation designers—to explore the power of design in developing a trustworthy, user-centered chatbot experience tailored to survivors' needs. Through an iterative process of research, co-creation, prototyping, and evaluation, we aim to integrate safe and effective digital support into mental healthcare. Our overarching goal is to bridge the gap between digital healthcare and the creative sector, fostering long-term collaboration. By combining clinical expertise with design innovation, we seek to develop personalized tools that ethically and effectively support individuals with mental health problems.
