Table 2.

Characterization of included studies.

Study/Year/Country	Objective	Type of Study	Contributions
Li et al., 2022 [23] China	Investigate the influence of leaders’ innovation expectation on nurses’ innovation behavior in conjunction with artificial intelligence, as well as explore the chain mediating effect of job control and creative self-efficacy between leaders’ innovation expectation and nurses’ innovation behavior.	Cross-sectional survey	Leaders’ innovation expectation helps to enhance nurses’ creative self-efficacy and job control, thereby enhancing nurses’ enthusiasm for innovation.
Chang et al., 2021 [24] China	Investigate how the use of robots can impact nurses’ engagement in professional tasks and reduce engagement in non-professional tasks, as well as analyze how these changes may influence job satisfaction, health perception, and nurses’ intention to turnover.	Cross-sectional survey	The use of robots reduces nurses’ engagement in non-professional tasks and increases their focus on professional tasks, which is positively related to overall job satisfaction and the perception of improved health among nurses.
Dong et al., 2021 [25] China	Develop an emergency nursing management system based on visual artificial intelligence, which aims to enhance clinical work efficiency and information management in hospital emergency environments.	Methodological	The emergency nursing management system based on visual artificial intelligence, once developed and tested, proved to be operational and capable of providing significant convenience for clinical work. The system enhances nurses’ efficiency by facilitating access to and management of medical information, such as patient data and medical orders.
Moreno-Fergusso et al., 2021 [26] Colombia	Provide tools to improve the key performance indicators of inpatient care management, including nurses’ workload, using AI.	Methodological	There are several processes inherent in compassionate nursing care that can be improved using technology. The proposed model presents an opportunity to make almost perfectly balanced nurse-to-patient assignments according to the number of patients and their health conditions using technology.
Ladios-Martin et al., 2022 [27] Spain	Create a model that detects the population at risk of falls by considering a fall prevention variable and assess the impact of this variable on the model’s performance.	Methodological	The demonstration that the inclusion of the fall prevention variable in a machine learning model significantly improves the ability to identify patients at risk of falls in hospital settings.
Courtney et al., 2008 [28] United States of America	Explore how the Nursing Practice Framework, from Novice to Expert, can shed light on the challenges and opportunities in implementing information technology such as clinical decision support systems in nursing practice.	Literature Review	Identification and analysis of the challenges and opportunities in the implementation of Clinical Decision Support Systems in nursing, with a particular focus on the application of the framework. Furthermore, these elements enable shaping the way decision support systems can be developed and implemented in nursing practice, aiming to enhance the quality of patient care.
Piscotty et al., 2015 [29] United States of America	Report the results of a study investigating the relationship between the use of electronic nursing care reminders and the occurrence of missed nursing care.	Cross-sectional survey	The frequent use of electronic nursing care reminders is associated with a reduction in reports of missed nursing care.
Roberty, 2019 [30] United States of America	Explore how artificial intelligence is transforming nursing practice, highlighting the tools and algorithms being used to enhance the delivery of healthcare services.	Literature Review	Artificial intelligence can transform nursing practice by enhancing the quality of care, emphasizing the importance of ethics and transparency in AI systems, and preparing nurses to critically and knowledgeably integrate these technologies into their clinical practice.
Gerich et al., 2022 [31] Finland	To synthesize currently available state-of-the-art research in artificial intelligence-based technologies applied in nursing practice.	Scoping review	Education on nurse informatics for all nursing professionals and students is imperative, and basic knowledge of AI-based technologies in nursing should be incorporated on all professional levels.
Ergin et al., 2022 [32] Turkey	Investigate the perceptions and opinions of nursing managers regarding the use of artificial intelligence and nurse robots in the context of healthcare.	Cross-sectional descriptive	Most nursing managers believe that artificial intelligence and robots can benefit the nursing profession by helping to reduce the workload of nurses, but they do not replace nursing professionals.