Background: Increasing life expectancy is resulting in a growing demand for long-term care; however, there is a shortage of qualified health care professionals (HCPs) to deliver it. If used optimally, technology can provide a solution to this challenge. HCPs play an important role in the use of technology in long-term care. However, technology influences several core aspects of the work that HCPs do, and it is therefore important to have a good understanding of their viewpoint regarding the use of technology in daily practice of long-term care. Objective: The aim of this study was to identify the factors that HCPs consider as relevant for using technology in daily practice of long-term care. Methods: In this qualitative study, 11 focus groups were organized with 73 HCPs. The focus group discussions were guided by an innovative game, which was specifically developed for this study. The content of the game was categorized into 4 categories: health care technology and me; health care technology, the patient, and me; health care technology, the organization, and me; and facilitating conditions. The perspectives of HCPs about working with technology were discussed based on this game. The focus groups were recorded and transcribed, followed by an inductive thematic analysis using ATLAS.ti 9x (ATLAS.ti Scientific Software Development GmbH). Results: Overall, 2 main domain summaries were developed from the data: technology should improve the quality of care and acceptance and use of technology in care. The first factor indicates the need for tailored and personalized care and balance between human contact and technology. The second factor addresses several aspects regarding working with technology such as trusting technology, learning to work with technology, and collaboration with colleagues. Conclusions: HCPs are motivated to use technology in daily practice of long-term care when it adds value to the quality of care and there is sufficient trust, expertise, and collaboration with colleagues. Their perspectives need to be considered as they play a crucial part in the successful use of technology, transcending their role as an actor in implementation. On the basis of the findings from this study, we recommend focusing on developing technology for situations where both efficiency and quality of care can be improved; redefining the roles of HCPs and the impact of technology hereon; involving HCPs in the design process of technology to enable them to link it to their daily practice; and creating ambassadors in care teams who are enthusiastic about working with technology and can support and train their colleagues.
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Background: As more and more older adults prefer to stay in their homes as they age, there’s a need for technology to support this. A relevant technology is Artificial Intelligence (AI)-driven lifestyle monitoring, utilizing data from sensors placed in the home. This technology is not intended to replace nurses but to serve as a support tool. Understanding the specific competencies that nurses require to effectively use it is crucial. The aim of this study is to identify the essential competencies nurses require to work with AI-driven lifestyle monitoring in longterm care. Methods: A three round modified Delphi study was conducted, consisting of two online questionnaires and one focus group. A group of 48 experts participated in the study: nurses, innovators, developers, researchers, managers and educators. In the first two rounds experts assessed clarity and relevance on a proposed list of competencies, with the opportunity to provide suggestions for adjustments or inclusion of new competencies. In the third round the items without consensus were bespoken in a focus group. Findings: After the first round consensus was reached on relevance and clarity on n = 46 (72 %) of the competencies, after the second round on n = 54 (83 %) of the competencies. After the third round a final list of 10 competency domains and 61 sub-competencies was finalized. The 10 competency domains are: Fundamentals of AI, Participation in AI design, Patient-centered needs assessment, Personalisation of AI to patients’ situation, Data reporting, Interpretation of AI output, Integration of AI output into clinical practice, Communication about AI use, Implementation of AI and Evaluation of AI use. These competencies span from basic understanding of AIdriven lifestyle monitoring, to being able to integrate it in daily work, being able to evaluate it and communicate its use to other stakeholders, including patients and informal caregivers. Conclusion: Our study introduces a novel framework highlighting the (sub)competencies, required for nurses to work with AI-driven lifestyle monitoring in long-term care. These findings provide a foundation for developing initial educational programs and lifelong learning activities for nurses in this evolving field. Moreover, the importance that experts attach to AI competencies calls for a broader discussion about a potential shift in nursing responsibilities and tasks as healthcare becomes increasingly technologically advanced and data-driven, possibly leading to new roles within nursing.
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Not much is known about the favourable indoor air quality in long term care facilities (LTCFs), where older adults suffering from dementia live. Older adults, especially those who suffer from dementia, are more sensible to the indoor environment. However, no special requirements for the indoor air in long term care facilities exist. Due to the decrease in cognition function, it is hard to evaluate comfort and health in this group. Nevertheless, infectious diseases are a persistent problem. Based on literature an assessment methodology has been developed to analyse LTCFs to determine if differences in building characteristics and Heating, Ventilation and Air Conditioning (HVAC) systems influence the spread of airborne infectious diseases. The developed methodology is applied in seven long term care facilities in the Netherlands. After that, the methodology has been evaluated and its feasibility and applicability are discussed. From this study, it can be concluded that this method has potential to evaluate, compare LTCFs, and develop design guidelines for these buildings. However, some adjustments to the methodology are necessary to achieve this objective. Therefore, the relation between the indoor environment and infection risk is not yet analysed, but a consistent procedure to analyse this link is provided.
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A feeling of worry, anxiety, loneliness and anticipation are commonplace in both medical and non-medical arenas such as elderly care. An innovative solution such as the ‘simple and effective’ comfyhand would offer better patient care and improved care efficiency with a high chance of long-term, economic efficiency. ComfyHand is a start-up in the healthcare sector that aims to develop sustainable products to improve patient wellbeing in healthcare settings. It does this by emulating the experience of holding a hand which gives the person comfort and support in moments where real human contact is not possible. Right now the comfyhand is in the development phase, working on several prototypes for test trials in elderly care and hospitals. In this project we want to explore the use of 3D printing for producing a comfyhand. Desired properties for the prototype include optimal heat transfer, softness, regulation of sweat, durability and sustainability. The goal of this study is to develop a prototype to test in a trial with patients within Envida, a care centre. The trial itself is out of scope of this project. This proposal focuses on researching the material of choice and the processability. Building on knowledge gained in a previous Kiem GoChem project and a Use Case (Shape3Dup) of a currently running Raak MKB project (Enlighten) on 3D printing of breast prostheses, several materials, designs and printing parameters will be tested.
Jongeren met chronische aandoeningen worden vaak geconfronteerd met problemen in het dagelijks functioneren, waarbij vermoeidheid wordt genoemd als het meest invaliderend. De prevalentie van vermoeidheid onder jongeren met chronische aandoeningen varieert tussen de 51-75%. Vermoeidheid kan onafhankelijk ontstaan van het onderliggende pathologisch mechanisme; uit literatuur blijkt dat ziekte-specifieke benaderingen weinig of nauwelijks effect hebben op vermoeidheid. Vermoeidheid wordt bovendien te laat opgemerkt of blijft onbehandeld. Inzicht in de ziekte-overstijgende mechanismen van vermoeidheid is van belang om vroegtijdig opsporen en de ontwikkeling van passende interventies te faciliteren. Dit postdoc onderzoek richt zich op het ontrafelen van ziekte-overstijgende mechanismen van vermoeidheid vanuit het perspectief van jongeren, het gezin en de fysieke en sociale leefomgeving. Binnen een longitudinale cohortstudie gedurende 12 maanden worden 208 jongeren met verschillende chronische aandoeningen gemonitord. Naast traditionele onderzoeksmethodieken zoals vragenlijsten en fysieke testen, wordt gebruik gemaakt van remote sensoring, linked data en context mapping (=kwalitatieve methode). Studenten die participeren in het onderzoek zullen de mogelijkheden en beperkingen van zulke methoden ervaren. Dit kan o.a. bijdragen aan het integreren van zorgtechnologie in het dagelijks (kinder)fysiotherapeutisch handelen. We ontwikkelen een theoretisch raamwerk dat de basis legt voor betere vroegdetectie (op afstand en non-invasief) van vermoeidheid en voor het identificeren van mogelijke aangrijpingspunten voor behandeling (doelstelling 1 en 2). Verder draagt het postdoc onderzoek bij aan een beter inzicht in de rol van de sociale en fysieke leefomgeving bij de maatschappelijke participatie van jongeren met chronische aandoeningen (doelstelling 3). Studenten zullen in veldwerk ter plaatse metingen doen, de leefsituatie verkennen en samen met zorgprofessionals en docenten hun klinische blik verrijken. Doordat zij daadwerkelijk in de leefomgeving van jongeren zelf aanwezig zijn kan dit bijdragen aan bewustzijn over de rol van verschillende sociale en fysieke factoren op vermoeidheid en op de maatschappelijke participatie van jongeren met uiteenlopende chronische aandoeningen.
In the Netherlands, 125 people suffer a stroke every day, which annually results in 46.000 new stroke patients Stroke patients are confronted with combinations of physical, psychological and social consequences impacting their long term functioning and quality of live. Fortunately many patients recover to their pre-stroke level of functioning, however, almost half of them never will. Consequently, rehabilitation often means that patients need to adapt to a new reality in their lives, requiring not only physical but also psychosocial adjustments. Nurses play a key role during rehabilitation of stroke patients. However, when confronted with psychosocial problems, they often feel insecure about identifying the specific psycho-social needs of the individual patient and providing adequate care. In our project ‘Early Detection of Post-Stroke Depression’, (SIA RAAK; 2010-12-36P), we developed a toolkit focusing on early identification of depression after stroke continued with interventions nurses can use during hospitalisation. During this project it became clear that evidence regarding possible interventions is scarce and inclusive. Moreover feasibility of interventions is often not confirmed. Our project showed that during the period of hospital admission patients and health care providers strongly focus on surviving the stroke and on the physical rehabilitation. Therefore, we concluded that to make one step beyond we first have to go one step back. To strengthen psychosocial care for patients after stroke we have to add, reconsider and shape knowledge in context of health care practices in a systematic way, resulting in evidence based and practice informed stepping stones. With this project we aim to collect these stepping stones and develop a nursing care programme that improves psychosocial well-being of patients after stroke, is tailored to the particular concerns and needs of patients, and is considered feasible for use in the usual care process of nurses in the stroke rehabilitation pathway.
