2025 ILC Annual International Conference , 16th & 17 June, 2025, Genoa, Italy, Global Collaboration,Local Action for Fundamentals of Care Innovation. Zie bladzijde 81. An international group of experts has joined forces for the further development of Artificial Intelligence (AI) in relation to the Fundamentals of Care (FoC) framework. AI, or its categories like machine learning and deep learning, offers potential to identify patterns in healthcare data, develop clinical prediction models, and derive insights from large datasets. For example, algorithms can be created to detect the start of the palliative phase based on electronic health records, or to inform nursing decisions based on lifestyle monitoring data for older adults. These AI applications significantly influence nurses' roles, the nurse-client relationship and nurses’ professional identity. Consequently, nurses must take responsibility to ensure that AI applications align with person-centered fundamental care, professional ethics, equity, and social justice. Thus, nursing leadership is essential to lead the development and use of AI applications that support nursing care according to the FoC framework, and enhance patient outcomes. The aim of the current project is to explore nurses’ responsibility for how AI adds value to the FoC framework. Firstly, nurse leaders play a vital role in overseeing the quality and relevance of data collected in daily practice, as these data are foundational for AI algorithms. The elements as articulated in the FoC framework should be the building blocks for any algorithm. These building blocks can be linked to clinical and social conditions, and life stages, building from the basis of the individual's human needs. Secondly, it is crucial for nurses to participate in the interdisciplinary teams that develop AI algorithms. Their participation and expertise ensure that algorithms are co-created with an understanding of the needs of their clients, maximizing the potential for positive outcomes. In addition to education, policy, and regulation, a nurse-led, interdisciplinary research program is needed to investigate the relationship between AI applications, the FoC framework and it’s impact on nurse-client relationships, nurses’ professional identity, and patient outcomes.
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There is a wide range of literature suggesting that implicit learning is more effective than explicit learning when acquiring motor skills. However, the acquisition of nursing skills in educational settings continues to rely heavily on detailed protocols and explicit instructions. This study aimed to examine the necessity for comprehensive protocols in the acquisition of nursing skills. In the context of bandaging techniques, three studies were conducted to investigate whether students who practiced with an instruction card containing minimal instructions (implicit group) performed comparably to the students who practiced with a protocol containing step-by-step instructions (explicit group). Study 1 was designed to determine whether both groups performed equally well in applying a bandage during training. Study 2 and 3 were designed to determine if both groups performed equally well during a retention and transfer (multitasking) test, administered after a series of three training sessions. In comparison with the explicit group, the implicit group demonstrated comparable performance with their practice attempts in Study 1 and performed equally well during the retention and transfer test in Study 2. Furthermore, several results from Study 3 indicated better performance of the implicit group. In conclusion, the use of protocols with explicit step-by-step instructions may not be essential for the acquisition of nursing skills. Instead, instructional methods that facilitate implicit learning may be preferable, as students in the implicit group demonstrated at least comparable performance in all studies and tended towards greater consistency when multitasking.
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Most nurse leadership studies have concentrated on a classical, heroic, and hierarchical view of leadership. However, critical leadership studies have argued the need for more insight into leadership in daily nursing practices. Nurses must align their professional standards and opinions on quality of care with those of other professionals, management, and patients. They want to achieve better outcomes for their patients but also feel disciplined and controlled. To deal with this, nurses challenge the status quo by showing rebel nurse leadership. In this paper, we describe 47 nurses’ experiences with rebel nurse leadership from a leadership-as-practice perspective. In eight focus groups, nurses from two hospitals and one long-term care organization shared their experiences of rebel nurse leadership practices. They illustrated the differences between “bad” and “good” rebels. Knowledge, work experience, and patient-driven motivation were considered necessary for “good” rebel leadership. The participants also explained that continuous social influencing is important while exploring and challenging the boundaries set by colleagues and management. Credibility, trust, autonomy, freedom, and preserving relationships determined whether rebel nurses acted visibly or invisibly. Ultimately, this study refines the concept of rebel nurse leadership, gives a better understanding of how this occurs in nursing practice, and give insights into the challenges faced when studying nursing leadership practices.
MULTIFILE
To optimize patient care, it is vital to prevent infections in healthcare facilities. In this respect, the increasing prevalence of antibiotic-resistant bacterial strains threatens public healthcare. Current gold standard techniques are based on classical microbiological assays that are time consuming and need complex expensive lab environments. This limits their use for high throughput bacterial screening to perform optimal hygiene control. The infection prevention workers in hospitals and elderly nursing homes underline the urgency of a point-of-care tool that is able to detect bacterial loads on-site in a fast, precise and reliable manner while remaining with the available budgets. The aim of this proposal titled SURFSCAN is to develop a novel point-of-care tool for bacterial load screening on various surfaces throughout the daily routine of professionals in healthcare facilities. Given the expertise of the consortium partners, the point-of-care tool will be based on a biomimetic sensor combining surface imprinted polymers (SIPs), that act as synthetic bacterial receptors, with a thermal read-out strategy for detection. The functionality and performance of this biomimetic sensor has been shown in lab conditions and published in peer reviewed journals. Within this proposal, key elements will be optimized to translate the proof of principle concept into a complete clinical prototype for on-site application. These elements are essential for final implementation of the device as a screening and assessment tool for scanning bacterial loads on surfaces by hospital professionals. The research project offers a unique collaboration among different end-users (hospitals and SMEs), and knowledge institutions (Zuyd University of Applied Sciences, Fontys University of Applied Sciences and Maastricht Science Programme, IDEE-Maastricht University), which guarantees transfer of fundamental knowledge to the market and end-user needs.
