Attitudes of nurses toward artificial intelligence: A multicenter comparison

BackgroundArtificial intelligence (AI) is transforming medical practices with rapidly developing technologies and the innovative solutions it provides. In order for this transformation to be successfully integrated into healthcare services, healthcare professionals must have positive attitudes towards this technology.ObjectiveThe present study was conducted with the aim of comparing the attitudes of nurses working in different provinces towards artificial intelligence.MethodsThe study was planned in a descriptive cross-sectional design. The study population consisted of 1453 nurses working in 3 state hospitals (inpatient hospitals providing secondary health care services) located in the city centers of Muş, Bingöl and Adıyaman provinces in eastern Turkey. While the sample size was 698 nurses in total, the study was completed with 737 nurses. The data were collected through the Introductory Information Form and the General Attitudes toward Artificial Intelligence Scale (GAAIS). ANOVA test and multiple regression were used to analyse the data.ResultsIt was found that the nurses had highly positive attitudes towards artificial intelligence. When the nurses' scores from the Positive GAAIS sub-dimension were compared, it was determined that there was a significant difference (p < 0.05) between the provinces. A statistically significant difference (p < 0.01) was found between the provinces in the Negative GAAIS sub-dimension, as well. Demographic characteristics were found to be effective on both Positive GAAIS and Negative GAAIS.ConclusionsAlthough there were differences between the provinces, the nurses generally had positive attitudes towards artificial intelligence technologies. The majority of the participants continue to use artificial intelligence technologies although they state that artificial intelligence will replace humans in the future. Longitudinal studies on the factors affecting attitudes towards artificial intelligence are recommended.