Study findings suggest that nursing education should integrate AI content and targeted training to strengthen students' AI awareness, critical evaluation, and ethical awareness, while providing tailored support for female students and boosting AI interest.
Abstract
Background
With the rapid integration of artificial intelligence (AI) into the nursing field, AI literacy has emerged as a critical competency for nursing students. However, evidence regarding the current status and influencing factors of AI literacy among Chinese nursing students remains limited.
Aim
This cross-sectional study aimed to examine AI literacy levels across four dimensions (Awareness, Application, Evaluation, Ethics) among Chinese nursing students, identify its independent influencing factors, and generate localized empirical evidence for AI curriculum construction in vocational nursing education.
Methods
A cross-sectional study was conducted between November 1, 2025 and January 20, 2026. The research institution has not set up an institutional ethics committee; the whole protocol was ethically reviewed by the supervisor team in line with the Declaration of Helsinki before recruitment. A total of 178 sophomore nursing students from Henan Vocational University of Science and Technology were enrolled via convenience sampling. Data were collected using the Artificial Intelligence Literacy Scale (AILS, Wang et al., 2023). This scale is publicly accessible for non-commercial academic research; the original authors have granted open-use permission for educational cross-sectional surveys without additional formal written authorization. After data cleaning, 155 valid questionnaires were included (effective response rate = 86.9%). Nonparametric tests and ordinal logistic regression were performed via IBM SPSS 27.0 for statistical analysis.
Results
Participants demonstrated a moderate level of overall artificial intelligence literacy (Median = 60.00, IQR = 21.00, SD = 13.18). The Application dimension scored highest. Gender and interest in AI were independent influencing factors. Strong positive correlations were identified among all four dimensions.
Conclusions
Study findings suggest that nursing education should integrate AI content and targeted training to strengthen students' AI awareness, critical evaluation, and ethical awareness, while providing tailored support for female students and boosting AI interest.
The integration of artificial intelligence (AI) technologies into clinical nursing is changing nursing practice and creating new competency requirements for nurses. Some nurses may still face difficulties in technical adaptation, ethical judgment, and practical use of AI tools in intelligent healthcare environments. Understanding nurses’ AI literacy and its relationship with thriving at work may help hospitals design more targeted support strategies.
This study aimed to investigate the current status of nurses’ artificial intelligence literacy, identify latent profiles of self-reported AI literacy, analyze factors associated with profile membership, and examine differences in thriving at work across AI literacy profiles.
A cross-sectional study.
In January 2026, 1000 nurses from 62 hospitals in Anhui Province, China were recruited by convenience sampling. Data were collected using a general information questionnaire, the Artificial Intelligence Literacy Scale, the Chinese version of the Thriving at Work Scale, a nine-item measure of attitudes toward AI in nursing, and the General Self-Efficacy Scale. Latent profile analysis was used to classify nurses’ AI literacy profiles. Factors associated with profile membership were examined using univariate analysis and multinomial logistic regression. Scores on the Thriving at Work Scale were compared across AI literacy profiles.
Three distinct latent profiles were identified: Ethical Awareness Deficit profile (
n
= 332, 33.20%), Cognition Practice Gap profile (
n
= 538, 53.80%), and Comprehensive Literacy Advantage profile (
n
= 130, 13.00%). Educational level, key nursing position/department management role, years of work experience, AI training experience, AI usage frequency in the past 6 months, attitude toward AI in nursing, and self-efficacy were associated with AI literacy profile membership (all
P
< 0.05). Scores on the Thriving at Work Scale differed significantly across the three profiles (
P
< 0.05).
This multicenter cross-sectional study identified three latent profiles of self-reported artificial intelligence literacy among nurses from hospitals in Anhui Province, China. Thriving at work differed significantly across these profiles. The findings may inform stratified educational and managerial strategies to support nurses’ AI literacy and thriving at work in similar clinical contexts.
Not applicable.
The findings indicate that nursing students had generally positive levels of AI literacy and attitudes toward AI, and higher AI literacy was associated with more positive attitudes toward AI.
M. Çil, Berna Eren Fidancı, D. Yildiz· Journal of Education and Res...· 0 citations
Nursing students had a wavier level of artificial intelligence literacy of knowledge, attitude and practice and its application in nursing learning, which foster effective integration of artificial intelligence in nursing education.
Haider Mohammed Majeed, Ali Hussein Alek Al-Ganmi, Ali Dhahir Abdulyemmah et al.· F1000Research· 0 citations
Initial evidence is provided that the NAIRS is a valid and reliable instrument for assessing nursing students' readiness for artificial intelligence across knowledge/awareness, willingness to use AI, self-efficacy, and ethical awareness domains and may be useful for educational needs assessment and curriculum planning in nursing education.
Sumeyye Akçoban, Gülay Koca, S. Berşe· BMC Nursing· 0 citations
Higher AI literacy was associated with lower AI anxiety, and this association was partly accounted for by AI attitudes and AI self-efficacy in the proposed serial mediation model, which suggests that more favorable attitudes may be linked to stronger self-efficacy, which may be related to lower anxiety.
Qin Zeng, Shenghua Zhang, Jiachen Hu et al.· Frontiers in Public Health· 0 citations
Background The rapid advancement of artificial intelligence is driving an unprecedented technological transformation in nursing. However, the successful integration of these technologies depends largely on the proficiency and perspectives of registered nurses. Consequently, there is an urgent need to examine the psychological and behavioral responses of this workforce. Methods A multi-center, cross-sectional survey was conducted from March to May 2026. a stratified convenience sampling method was employed to recruit 1,392 registered nurses from tertiary hospitals, secondary hospitals, and community health centers in Chongqing. Data collection instruments included a general demographic questionnaire, the Artificial Intelligence Literacy Scale, the Artificial Intelligence Anxiety Scale, and the General Attitudes Towards Artificial Intelligence Scale. Statistical analyses, including descriptive statistics, Spearman correlation, and multiple linear regression. Results A total of 1,392 registered nurses participated in the study, with a mean age of 34.69 ± 7.13 years. AI literacy scored 5.27 ± 0.90 (75.29% scoring rate). AI anxiety was moderate (51.29%), with the highest concerns appearing in socio-technical blindness (56.43%) and job replacement (55.14%). Overall, nurses maintained a positive attitude toward AI (74.00%). AI literacy was negatively correlated with anxiety (r = −0.338, p < 0.001) and significantly positively correlated with attitude (r = 0.551, p < 0.001), anxiety and attitude were negatively correlated (r = −0.541, p < 0.001). Regression analysis indicated that AI literacy was a significant associated factor for both anxiety levels (B = -0.453, p < 0.001) and attitudes (B = 0.377, p < 0.001), explaining 9.9 and 29.4% of the variance, respectively. Additionally, a lower frequency of electronic device use (p = 0.024) and lack of proficiency in device operation (p = 0.033) were associated with higher anxiety levels, whereas male nurses demonstrated more positive attitudes compared to female nurses (p = 0.011). Conclusion Nurses demonstrated high AI literacy and positive attitudes; however, anxiety remained prominent. Enhancing AI literacy may alleviate psychological anxiety, with device accessibility and usage patterns also playing critical roles. To facilitate the effective integration of artificial intelligence into clinical practice, administrators should strengthen institutional support mechanisms alongside providing facility resources and conventional education, thereby promoting the full utilization and translation of available resources.
Yi Dai, Xili Zhao, Xiaochong Pan et al.· Frontiers in Public Health· 0 citations