Jan 2026· Journal of Nursing Management· Vol 2026· 0 citations· 80 references
Medicine
TL;DR
The findings reveal that the study does not directly affect the AI literacy, but it affects how the nurse feels about the interpersonal relationship in the workplace as well as her ability to cope with the demands of the AI technology.
Abstract
Aim To investigate the relationship between inclusive leadership and artificial intelligence (AI) literacy among nurses, with a specific emphasis on whether psychological safety and AI readiness mediate this relationship sequentially. Methods A longitudinal study was conducted between September 2025 and March 2026 with the use of a three‐wave survey on 1334 clinical nurses. The selected hospitals were stratified by cluster random sampling at 10 tertiary hospitals in China. In T1, the level of inclusive leadership was measured, and in T2, the psychological safety as well as AI readiness was also tested. At T3, the AI literacy was assessed based on the tools that had been validated before. SPSS 25.0 and PROCESS 4.1 were used to test mediating effects. Results All the important factors were positively correlated. The study also did not have any direct correlation between AI literacy and inclusive leadership. Nevertheless, it was passed through a number of indirect ways. The psychological safety (indirect effect = 0.258, 95% confidence interval [CI] [0.205, 0.315]) and the AI readiness (indirect effect = 0.082, 95% CI [0.051, 0.115]) were significant mediators in the relationship. Also, a sequential path was indicated by the data: as more inclusive leaders were observed to be, the more psychologically safe they became, which would then result in increased AI readiness, and finally, this resulted in AI literacy among nurses (indirect effect = 0.049, 95% CI [0.030, 0.070]). Conclusions The psychological safety and the AI readiness are two of the factors that can be used to explain why inclusive leadership is associated with the AI literacy among nurses. Our findings reveal that our study does not directly affect the AI literacy, but it affects how the nurse feels about the interpersonal relationship in the workplace as well as her ability to cope with the demands of the AI technology. That is, the impact of the inclusive leadership on the AI literacy of the nurses will be clearer when the nurses are psychologically safe and prepared to use the AI. Implications for Nursing Management Our results can be used to determine that leadership behavior is a very important part of the organization, and it should provide open communication and learning in the workplace. The development of AI literacy will occur when the managers in the nursing field are able to establish psychological safety and enable nurses to have an increased level of confidence in the use of new technologies. These outcomes can also be enhanced through organizational initiatives like the education and skill building programs on AI.
Nursing curricula may benefit from structured AI education that integrates guided GenAI practice, case-based learning, and faculty feedback that integrates guided GenAI practice, case-based learning, and faculty feedback.
Shinhi Han, H. Kang, P. Gimber et al.· Nursing Reports· 0 citations
Background AI literacy is increasingly recognized as a core competency that enables nurses to improve work efficiency and reduce workload. Therefore, enhancing AI literacy represents a promising strategy to strengthen occupational resilience. However, current research has not yet elucidated the direct relationship and underlying mechanisms between nurses’ AI literacy and occupational resilience. Aim To investigate the impact of nurses’ artificial intelligence literacy on their occupational resilience and examine the chain mediating effects of psychological capital and burnout. Methods Data were collected from December 2025 to January 2026 using self‐report electronic questionnaires completed by nurses in 10 medical institutions across China. Descriptive analysis, correlation analysis, and chain mediation analysis were performed on all study variables. Results Correlation analysis showed that nurses’ artificial intelligence literacy was significantly positively correlated with occupational resilience (r = 0.351, p < 0.001) and psychological capital (r = 0.356, p < 0.001) and significantly negatively correlated with burnout (r = −0.130, p < 0.05). Bootstrap analysis revealed that psychological capital served as the primary mediating pathway (effect = 0.377, 95% CI = [0.283, 0.475]), and a sequential chain mediation via psychological capital and burnout also existed between artificial intelligence literacy and occupational resilience (effect = 0.036, 95% CI = [0.019, 0.057]). Conclusion Artificial intelligence literacy enhances occupational resilience through the chain mediation effects of psychological capital and burnout. Occupational resilience among nurses can be strengthened by implementing artificial intelligence skills training and psychological capital interventions for nursing staff. Implication for Nursing Management Nursing managers should implement hierarchical artificial intelligence training, regularly assess nurses’ psychological capital and burnout and offer targeted interventions. Meanwhile, healthcare institutions should upgrade digital infrastructure, adopt artificial intelligence–enabled nursing technologies, and establish guidelines for intelligent nursing applications to systematically enhance nurses’ occupational resilience.
Qing-Zhu Qin, Wen-Jing Sun, Hengyu Hu et al.· Journal of Nursing Managemen...· 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
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
AIM
To examine the relationship between emotional intelligence (EI) and leadership style among nurse managers, and how the relationship is shaped by professional experience, hierarchical position, and healthcare facility size. The study explores whether EI functions as a conditional mechanism linking experience to leadership across hierarchical levels.
DESIGN
A cross-sectional quantitative study.
METHODS
A total of 1243 nurse managers from public healthcare facilities participated in a survey conducted between November 2022 and January 2023. Emotional intelligence was measured using the Trait Emotional Intelligence Questionnaire-Short Form (TEIQue-SF), and leadership style using the Multifactor Leadership Questionnaire (MLQ). Differences across hierarchical levels were examined using repeated measures ANOVA. A conditional process analysis (PROCESS Model 59) tested the mediating role of EI and the moderating effect of hierarchical position, controlling for gender and facility size.
RESULTS
Transformational and transactional leadership were more pronounced among higher-level managers, whereas passive leadership was more prevalent among front-line managers. Emotional intelligence was positively associated with transformational and transactional leadership and negatively associated with passive leadership. EI demonstrated a conditional and partial mediating role in the relationship between professional experience and leadership, with effects varying across hierarchical levels. Hierarchical position moderated both the relationship between experience and EI and the association between EI and transformational leadership. Managers in larger healthcare facilities reported higher EI and lower passive leadership.
CONCLUSION
Leadership in nursing management is shaped by the interaction between emotional competencies and organisational structure. Emotional intelligence operates as a context-dependent capacity, whose development and expression are conditioned by hierarchical position and organisational environment.
IMPACT
This study highlights that emotionally intelligent leadership is not solely an individual attribute but is structurally enabled or constrained. Supporting nurse managers requires organisational interventions, including supervisory time, mentorship, and conditions that sustain emotional regulation and reflective capacity.
PATIENT OR PUBLIC CONTRIBUTION
No patient or public contribution.
Paschalina Ntotsi, M. Gouva, M. Lavdaniti et al.· Journal of Advanced Nursing· 0 citations
Hospital-level resources, older age, and longer work experience were the factors most strongly associated with nurses’ AI training acceptance and AI tool usage, with work experience showing the strongest association with tool usage.
Linlin Guo, Qin Ding, M. Tang et al.· Frontiers in Public Health· 0 citations
