In rapidly changing health care systems, digitalization, e-health and robotisation are gaining influence. Due to the existing global nurse shortage in Europe, a demand for healthcare and therewith nurses will continue to grow, whilst the supply of available nurses is projected to drop. Therefore, it is expected that the shortages will accelerate in the coming decade and will be more serious than the cyclical shortages of the past. This nursing shortage will ultimately constrain health system reform and innovation, and contribute to escalating costs. ICT, AI and robotization are one way to support health care professionals, enhance interprofessional cooperation and patients` safety. This introduction of ICT, robotisation and other technologies in nursing care will create a disruptive change in the provision of health and nursing care. Furthermore, research shows, that the usage of ICT is still limited within the health care professions and thus in nursing. For that external and internal factors have been identified, e.g. infrastructure not being suitable or the lack of interoperability of different computer and ICT systems, the limited awareness and understanding of ICT concepts. Health care professionals who use ICT complain about the lack of skills and tailored trainings for their needs. Usually nurses have to learn ICT related skills on the job within their working duties. As ICT is rapidly changing and developing towards robotization and AI, the resistance and skepticism towards technology among nursing professionals are expected to grow. The NursingAI project will analyze and forecast the types of skills and competencies needed by health care professionals, especially nurses. By gaining insight of needed competencies and skill, curriculums for trainings and education programs can be enhanced to the actual needs concerning ICT competencies. NursingAI will work towards an assessment and training tool for skills related to AI, robotisation, digitalization and e-health in nursing sectors of Germany, Hungary and the Netherlands. The tool prototype will be tested and evaluated in these countries in order to make them available for local and European VET curriculums and further education programs. These efforts are critical, since 1), nurses should be able to understand and work with novel AI and Information and Communication Technologies (ICT) in order to improve the general quality of care; 2) the current offer of assessment and training methods on AI, robotisation, digitalization and e-health skills in nursing in Europe is very limited, and 3) in order to have a significant amount of AI and robotization skilled nurses in place in 5-10 years time in Europe, investments and changes in the VET curricula need to be initiated now. With the transnationally project, needed competencies in future workplaces will be multiplied and progress made in VET and health care.
Context / Background There is a worldwide shortage of trained nurses (WHO, 2020), which is being aggravated by aging populations and the growing demand for healthcare. This development is compounded by the high fluctuation rate in nursing, based on job satisfaction levels. Even more now in the light of a possible mandatory COVID-19 vaccination, non vaccinated nurses might quit their job or will be put on non-active without salary and forced to leave. This situation is expected to further increase the shortage of nurses in both numbers and skills. In order to meet future and present challenges due to increasing demand, more complex diseases, and even worldwide pandemics, strategies need to be identified to optimize working conditions for nurses, so as to make this profession more interesting not only for future nurses but also for registered nurses, who currently tend to quit their jobs prematurely. New technologies have the potential to support nurses in their clinical practice (Graf & Klein 2018). Still, research has shown that nurses’ competencies in applying ICT within healthcare are still not being developed on a structural basis (Abbott & Coenen 2008) and we can speak of a complete ‘lack of’ or, or at least an insufficient involvement of nurses in the design of ICT applications. Also, it appears that the necessary ICT skills are often not included in the curriculum of vocational nurse education, due in part to the aforementioned incompatible computer and ICT systems which have been developed across health care organisations. Not only ICT, but also autonomous technologies, which are defined as technologies that interact with the environment independent of human influence, such as robotics and artificial intelligence (AI) can be an opportunity to assist nurses in their daily practice. Examples are serving robots, supportive systems for patient transfer, or sensory measurement. Still, more research on technology-based nurses’ competencies and the opportunities for technologies in nursing practice is needed (Maalouf et al. 2018). A framework is needed comprising the competencies, nurses need to not only leverage technology efficiently and effectively but also to participate in the design, development and evaluation of technologies in nursing practice. Objectives In order to address nurses’ competencies related to autonomous technologies, partners in the NursingAI project first developed a competency framework. With this in hand, an assessment tool to measure nurses’ self-assessed knowledge, skills and attitudes concerning autonomous technologies in nursing practice was developed and validated. Also on the basis of the Assessment and Training Framework and the lessons learned from the assessment prototype, a prototype intervention was developed with the aim to enhance those knowledge, skills, and attitudes. This prototype intervention was based on an immersive story-telling method, making it highly participatory and exploratory. Nurses, nursing students and technology experts were involved to interact with the concepts and skills in relation to AI and robotization described in the framework. Assessment and training were monitored and evaluated, in order to validate the assessment prototype and provide feedback on needed demand for advancements in vocational training. The results are also amenable to suggesting curriculum changes for VET in nursing. Number and type / profile of participants The competency framework, the assessment tool and the training intervention were developed by a group of experts in nursing, research, education and technologies from Hungary, Germany, and the Netherlands. The assessment prototype was distributed to registered hospital nurses and nursing undergraduates in the partner countries. A total of n=804 people completed the questionnaire. The prototype interventions were conducted in Germany, Hungary, and The Netherlands and a total of n=82 registered nurses, nursing researchers, and technology experts participated. A total of n=39 participants completed the pre- and post-intervention questionnaires for evaluation of the training intervention. Description of undertaken activities In order to develop the competency framework literature was reviewed in order to gain an overview of current efforts in assessing, evaluating, and educating competencies in nursing practice which are related to ICT, AI, and robotization. In order to gain insight into national and discipline-specific peculiarities, specific conditions and requirements were discussed within the project team. This analysis yielded the concrete assessment and training requirements for nursing VET, which is a necessity to prepare both nursing education and practice to implement and work with care related ICT and AI. Three existing frameworks for nurses’ ICT competencies, as well as the structure of the nursing process, formed the basis of the NursingAI framework for technology-related nursing competencies (TCNP). Thus, competency domains addressing assessment, planning, implementation, and evaluation of ICT and autonomous technologies in nursing practice were constructed. Based on the TCNP-framework, a prototype assessment tool was developed for the competencies identified as critical. Item generation and selections were based on culturing decentring principle by nursing experts in Germany, Hungary, and the Netherlands. Subsequently, this questionnaire was piloted among hospital nurses in these countries. The scale was validated by means of within item analysis, differential item functioning analysis, as well the evaluation of other relevant psychometric properties. Based on the preliminary results and experiences, a training intervention was developed according to the method of immersive story-telling. The aim of this intervention was to enable an exchange of ideas, worries, and needs for autonomous technologies with experts in nursing and experts in technology research. During this intervention, participants were assisted in developing their own narratives about AI in healthcare. The first version of the intervention was conducted in Germany and then adapted according to experiences gained. A script was developed that served as a basis for the interventions conducted in Hungary and the Netherlands. The interventions were evaluated with the help of the 16 items ATNP scale in a pre- post design. Results and impact attained The first output (IO1) was the development of a Technology-related Competency framework for Nursing Practice (TCNP). The impact attained is a validated competency framework for dissemination as an open license resource for implementation and use in both healthcare organisations and vocational institutes. Based on the TCNP-framework a questionnaire measuring nurses’ self-assessed competencies in dealing with Autonomous Technologies such as AI and robotics in Nursing Practice was developed (ATNP-scale), translated to German, Dutch, and Hungarian and revised with the help of cognitive interviews in all participating countries. The resulting 26 items addressed nurses’ self perceived confidence in dealing with aspects such as communication of ideas for technologies in nursing practice, identification of helpful technologies, successful application of technologies, and giving feedback on technologies in nursing practice, to name but a few. This scale was distributed to registered hospital nurses and nursing undergraduates in Germany, Hungary, and the Netherlands, resulting in a sample size of n=804. (Hungarian data n=700, German data n=104). Based on an evaluation of the psychometric properties of the scale, 10 items were deleted, resulting in a validated 16-items ATNP-scale. With this validated 16 item assessment tool ready for dissemination as an open license resource, nurses, as well as employers, will be able to assess nurses’ competencies. It can be implemented and used in healthcare organisations and vocational institutes and results can help innovate and update educational curricula. Furthermore, nurses completing the instrument get the opportunity to reflect on their own competencies and their role within the development and implementation processes of technologies in nursing practice. The training intervention (IO3) was developed with the help of a theatre pedagogical expert, who also moderated three of the four events (in Hungary with n=47 participants, in the Netherlands with n=29 participants, and within the final international event with n=40). With these events in three countries awareness of a broad group of professionals in the field of nursing, technology, and research was gained and exchange between nursing practitioners and technology researchers was enabled. Results of the pre-post-evaluation showed that a majority of participants perceived an improvement in terms of self-assessed technology-related competencies. References Abbott PA, Coenen, A. Globalization and advances in information and communication technologies: the impact on nursing and health. Nursing Outlook. 2008;56(5):238-246. Graf, B., & Klein, B. (2018). Robotik in Pflege und Krankenhaus - Einsatzfelder, Produkte und aktuelle Forschungsarbeiten. Zeitschrift für medizinische Ethik, 4(64), 327-343. Maalouf N, Sidaoui A, Elhajj IH, Asmar D. Robotics in Nursing: A Scoping Review. Journal of Nursing Scholarship. 2018;50(6):590-600. World Health Organisation. (2020). Nursing and Midwifery. Retrieved 03.03.2020 https://www.who.int/news-room/fact-sheets/detail/nursing-and-midwifery