Artificial Intelligence Literacy Levels and Attitudes Toward Artificial Intelligence Technology Among Intensive Care Nurses: A Cross‐Sectional Study

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Authors: Vahide Semerci Çakmak, Cansu Yılmaz
Cited by: 1
References: 26

Abstract

ABSTRACT Background The artificial intelligence (AI) literacy of intensive care nurses and their behaviors in interacting with AI is crucial for evaluating the impact of AI on patient care and treatment. The aim of this study is to determine the AI literacy levels of intensive care nurses, their attitudes toward AI technologies, and the factors associated with these attitudes. Methods The sample for this cross‐sectional study consisted of 280 nurses working in the intensive care units of two hospitals. Data were collected face‐to‐face using a Personal Information Form, an Artificial Intelligence Literacy Scale (AILS), and an Artificial Intelligence Attitude Scale (AIAS‐4). Descriptive statistics, Pearson correlation, independent samples t ‐test, one‐way ANOVA, and multiple linear regression analyses were used to analyze the data. Results The mean age of the participants was 33.47 ± 7.12. 63.9% of the nurses were female, 48.9% were married, and 72.1% had a bachelor's degree or higher. The vast majority of nurses (96.4%) had not received any training in AI, and 50% had no experience in this field. The mean AIAS‐4 score of intensive care nurses was 6.26 ± 2.74 (min = 1, max = 10) and the mean AILS score was 39.87 ± 6.69 (min = 16, max = 60). The results indicated a strong, positive, and statistically significant correlation between AIAS‐4 and AILS ( r = 0.72, p < 0.05). Among the variables included in the model, AILS score, age, gender, marital status, and education level were found to be statistically significant predictors ( p < 0.05), explaining 64% of the variance (Adj. R 2 = 0.640; F = 100.383; p < 0.001). Conclusion In conclusion, the regression model revealed that age was a significant predictor, and individuals aged 36 and over had more negative attitudes toward AI technologies. In contrast, higher levels of AI literacy, male gender, being single, and having a bachelor's degree or higher were found to be significant positive predictors of attitudes toward AI technologies. It is recommended that practice‐based training programs emphasizing clinical benefits, aimed at improving AI literacy and attitudes toward AI technologies among intensive care nurses, be expanded.

Fields of Study & Subjects

Artificial Intelligence in Healthcare and Education AI in Service Interactions Ethics and Social Impacts of AI

Publication details

Journal / source
Journal of Evaluation in Clinical Practice
Publisher
Wiley
Volume
32
Issue
4
Pages
e70498–e70498
Publication date
1 June 2026
Language
EN