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.

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.