Objective:To deeply understand the views of nurses on nursing robots, so as to provide reference for standardizing the application of nursing robots and promoting innovation in smart nursing service models.Methods:From March to June 2023, purposive sampling was used to select 15 registered nurses from two ClassⅢ general hospitals in Shanghai as research subjects for semi-structured interviews. Colaizzi 7-step analysis method was used to analyze interview data.Results:Three themes were extracted, including the perceived multiple benefits of nursing robots (obtaining work assistants, facilitating nursing safety, and promoting professional value recognition), the perceived multiple risks of nursing robots affecting patients (concerns about affecting patient safety, concerns about triggering negative emotions in patients, and concerns about functional limitations), and the perceived multiple dilemmas in the application of nursing robots (concerns about academic burden, concerns about changes in work patterns, concerns about unclear responsibilities, and concerns about affecting nursing positions) .Conclusions:Although nurses hold a positive attitude towards nursing robots and expect them to reduce their workload, nurses are also concerned that they may not be able to fully adapt to the clinical environment, pose potential risks to the physical and mental health of patients, and pose new challenges to nursing staff and work models. In the face of intelligent nursing, efforts should be made to strengthen professional training for nurses in information technology, improve nursing work models and processes, and perfect the rules and regulations for the application of intelligent products. Multiple parties should cooperate to create a smart nursing application ecosystem.

This study summarized the determination methods and principles of 2019 novel coronavirus(severe acute respiratory syndrome coronavirus 2,SARS-CoV-2). The advantages and limitations of several methods was compared, which can provide a basis for the selection of 2019 novel coronavirus clinical diagnosis methods.
Betacoronavirus ; Clinical Laboratory Techniques ; Coronavirus Infections ; diagnosis ; Humans ; Pandemics ; Pneumonia, Viral ; diagnosis