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ARTIFICIAL INTELLIGENCE AND ROBOT NURSES: FROM NURSE MANAGERS’ PERSPECTIVE: A DESCRIPTIVE CROSS-SECTIONAL STUDY

J Nurs Manag. 2022 Apr 27. doi: 10.1111/jonm.13646. Online ahead of print.

ABSTRACT

AIM: This research was planned to identify nurse managers’ opinions on artificial intelligence and robot nurses.

BACKGROUND: As the concepts of artificial intelligence and robot nurses are becoming widespread in Turkey, nurse managers are expected to guide and cooperate with nurses in the future in regards to these technologies.

METHODS: The sample of the study consisted of 326 manager nurses, who were reached via the online questionnaire during the period of September-November 2021. Nurse Managers Information Form and Question Form on Artificial Intelligence and Robot Nurses were used to collect data. Data in this cross-sectional descriptive study was collected between September 2021 and November 2021 by the online survey method. The descriptive statistics of the data were analyzed with numbers and percentages. The difference between the knowledge of artificial intelligence and robot nurses and demographic characteristics was analyzed with the Chi-square test.

RESULTS: According to the findings, 66.9% of the nurse managers reported having heard the concepts of artificial intelligence and robot nurses previously. 67.2% stated that they thought that robot nurses would benefit the nursing profession, but 86.2% voiced disbelief that robots would replace nurses.

CONCLUSIONS: The majority of the participating nurse managers reported that artificial intelligence and robot nurses would not replace nurses but would be beneficial for nurses and would reduce their workload.

IMPLICATIONS FOR NURSING MANAGEMENT: It should be ensured that the nurse managers plan the areas in the hospital where artificial intelligence and robot nurses will be used and determine the possible risks. Awareness should be increased with in-service trainings and patient safety and ethical problems regarding the use of artificial intelligence and robot nurses should be identified.

PMID:35474366 | DOI:10.1111/jonm.13646

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