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BACKGROUND: The end-users' acceptance is a core concept in the development, implementation and evaluation of new systems like robotic systems in daily nursing practice. So far, studies have shown various findings concerning the acceptance of systems that are intended to assist people with support or care needs. Not much has been reported on the acceptance of robots that provide direct physical assistance to nurses in bedside care. Therefore, this study aimed to investigate the acceptance along with ethical implications of the prototype of an assistive robotic arm aiming to support nurses in bedside care, from the perspective of nurses, care recipients and their relatives. METHODS: A cross-sectional survey design was applied at an early stage in the technological development of the system. Professional nurses, care recipients and relatives were recruited from a university hospital and a nursing home in Germany. The questionnaire was handed out following either a video or a live demonstration of the lab prototype and a subsequent one-to-one follow-up discussion. Data analysis was performed descriptively. RESULTS: A total of 67 participants took part in the study. The rejection of specified ethical concerns across all the respondents was 77%. For items related to both perceived usefulness and intention to use, 75% of ratings across all the respondents were positive. In the follow-up discussions, the participants showed interest and openness toward the prototype, although there were varying opinions on aspects such as size, appearance, velocity, and potential impact on workload. CONCLUSIONS: Regarding the current state of development, the acceptance among the participants was high, and ethical concerns were relatively minor. Moving forward, it would be beneficial to explore the acceptance in further developmental stages of the system, particularly when the usability is tested.
RESUMO
Artificial intelligence (AI) in the domain of healthcare is increasing in prominence. Acceptance is an indispensable prerequisite for the widespread implementation of AI. The aim of this integrative review is to explore barriers and facilitators influencing healthcare professionals' acceptance of AI in the hospital setting. Forty-two articles met the inclusion criteria for this review. Pertinent elements to the study such as the type of AI, factors influencing acceptance, and the participants' profession were extracted from the included studies, and the studies were appraised for their quality. The data extraction and results were presented according to the Unified Theory of Acceptance and Use of Technology (UTAUT) model. The included studies revealed a variety of facilitating and hindering factors for AI acceptance in the hospital setting. Clinical decision support systems (CDSS) were the AI form included in most studies (n = 21). Heterogeneous results with regard to the perceptions of the effects of AI on error occurrence, alert sensitivity and timely resources were reported. In contrast, fear of a loss of (professional) autonomy and difficulties in integrating AI into clinical workflows were unanimously reported to be hindering factors. On the other hand, training for the use of AI facilitated acceptance. Heterogeneous results may be explained by differences in the application and functioning of the different AI systems as well as inter-professional and interdisciplinary disparities. To conclude, in order to facilitate acceptance of AI among healthcare professionals it is advisable to integrate end-users in the early stages of AI development as well as to offer needs-adjusted training for the use of AI in healthcare and providing adequate infrastructure.
RESUMO
User-oriented needs assessment of the potential use of assistive robots in direct nursing care: A mixed methods study Abstract. Background: So far, hardly any robots have been used in nursing that take over patient-related activities and thereby reduce the physical strain on the caregivers. Using user-centered design approaches, the interdisciplinary project "PfleKoRo" was therefore developing a robotic assistance system that can be used in the direct care of bedridden patients requiring intensive or very intensive care. Aim: The aim of this study was to identify nursing activities with the greatest support potential for an assistant robot for the direct care of bedridden patients. Method: Focus groups (n = 3) with nursing professionals (n = 14) from acute and long-term care were conducted first in an explorative mixed method design and then evaluated by means of content analysis. A selection of nursing activities was then prioritized by the participants of the focus groups (n = 10) with regard to their potential for support from an assistant robot in a standardized survey. Results: The highest priority was given to turning and holding patients in a lateral position as well as holding their legs in order to perform nursing tasks. Further support was needed, among other things, for repositioning the patient to the head of the bed and for tasks such as the transfer of patients. Conclusion: Turning patients and holding them in a lateral position as well as holding the leg are seen as target activities with the greatest support potential for "PfleKoRo", presenting the starting point for further development.
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BACKGROUND: As robotics in nursing care is still in an early explorative research phase, it is not clear which changes robotic systems will ultimately bring about in the long term. According to the approach of "Responsible Research and Innovation", the research project "PfleKoRo" aims to anticipate and mitigate ethical risks that might be expected when starting to develop a robot. The robot under investigation is intended to be a hands-on support in nursing care in due course. Therefore, the question is which ethical risks and requirements must be considered when developing the robot. METHODS: Guided by the British Standard for the design of robotic systems, ethical risks related to the robot's use were identified at the outset (Step 1). This was followed by the definition of the requirements needed to mitigate ethical risks (Step 2). Professional nurses, patients and relatives were involved in focus groups and interviews in Step 1. The transcribed interviews and focus groups were then analysed using content analysis. The available literature and expert guidance were taken into account in both steps. Finally, validation and verification methods were defined (Step 3). RESULTS: Sixteen professional nurses participated in three focus groups. Individual interviews were held with a total of eight patients and relatives. Ethical risks and requirements could be defined in the context of dignity, autonomy, privacy, human relationships and safety in the project. Professional nurses feared most issues relating to safety and that the robot would lead to more workload instead of relief, whereas patients and relatives frequently raised the issue of the staffing ratio. Despite the focus on possible negative consequences, participants also made uncritical or optimistic comments regarding the robot's use in the future. CONCLUSION: Focus groups, individual interviews and existing literature revealed to some extent different ethical issues. Along with identified risks, the results suggest a general open-mindedness of nurses, patients and relatives towards the introduced robot. When investigating the ethical implications of robots for nursing care, one should include multiple perspectives and, in particular, potentially affected individuals.
