Aug 2026· Nursing Reports· Vol 16, pp. 281· 0 citations· 43 references
Medicine
TL;DR
AI literacy and critical thinking disposition were significantly associated with clinical competence among nursing students with clinical practice experience and nursing education may consider strategies that address both competencies.
Abstract
Highlights What are the main findings? AI literacy and critical thinking disposition were significantly associated with clinical competence among nursing students with clinical practice experience. Satisfaction with clinical practice, critical thinking disposition, AI literacy, and academic year were identified as significant factors associated with clinical competence. What are the implications of the main findings? Nursing education may consider AI literacy as an emerging educational competency associated with clinical competence in rapidly changing healthcare environments. AI literacy and critical thinking disposition may be considered together in nursing education strategies related to clinical competence. Abstract Background/Objectives: As artificial intelligence (AI) becomes increasingly integrated into healthcare, AI literacy and critical thinking disposition are recognized as important competencies for nursing students in rapidly changing clinical environments. This study aimed to examine the associations of AI literacy and critical thinking disposition with clinical competence among nursing students. Methods: A descriptive cross-sectional study was conducted with 200 nursing students with clinical practice experience who were enrolled in nine nursing colleges located in D City and K Province, Republic of Korea. Data were collected using a structured questionnaire and analyzed using IBM SPSS/WIN 25.0. Statistical analyses included descriptive statistics, t-tests, analysis of variance (ANOVA), Scheffé post hoc tests, Pearson’s correlation coefficients, and multiple regression analysis. Results: Satisfaction with clinical practice (β = 0.35, p < 0.001), critical thinking disposition (β = 0.34, p < 0.001), AI literacy (β = 0.23, p = 0.001), and academic year (β = 0.15, p = 0.009) were significantly associated with clinical competence. The model explained 40% of the variance in clinical competence (R2 = 0.40, adjusted R2 = 0.39, F = 26.11, p < 0.001). Conclusions: The findings indicate that critical thinking disposition and AI literacy were significantly associated with clinical competence among nursing students. Nursing education may therefore consider strategies that address both competencies.
This study aimed to investigate the levels of digital literacy, critical thinking disposition, and AI ethical awareness among nursing students and to identify the relationships and influencing factors among these variables. This descriptive correlational study was conducted with 180 nursing students from universities located in D metropolitan city and C province. Data were collected using a structured self-report questionnaire assessing general characteristics, digital literacy, critical thinking disposition, and AI ethical awareness. The mean scores were 4.12 for digital literacy, 3.75 for critical thinking disposition, and 3.61 for AI ethical awareness. Students with AI-related educational experience showed higher levels of critical thinking disposition. Critical thinking disposition showed the strongest positive correlation with AI ethical awareness(r=.648, p<.001). Multiple regression analysis revealed that critical thinking disposition(β=.554, p<.001) was the strongest predictor of AI ethical awareness, and the explanatory power of the model was 46.6%. These findings suggest that integrated educational strategies to strengthen digital literacy and critical thinking are necessary to improve AI ethical awareness among nursing students. Nursing education should provide opportunities for reflective and ethical decision-making regarding AI in clinical practice.
Hyun Ji Kim· Forum of Public Safety and C...· 0 citations
It is indicated that both self-directed learning and AI acceptance are associated with perceived clinical competence, with AI acceptance acting as a mediating factor.
Boshra Karem Mohamed El-Sayed, Ayman Ateq Alamri, M. G. R. Asal et al.· BMC Medical Education· 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
Background: Being a key competency for nurses to deliver quality care to patients, clinical leadership is important for providing safe, high-quality, and patient-centered care. Nonetheless, information on the clinical leadership competencies specific to domains for nursing profession students has been scanty, especially in Indonesia.
Purpose: The purpose of this research is to ascertain the priority domains of competencies in clinical leadership among students of the nursing profession through CLCF and explore its implications in nursing education.
Methods: In the current research, a quantitative descriptive study with a cross-sectional design was carried out on 123 students of nursing profession in Jakarta, Indonesia, employing total sampling technique. Competence of clinical leadership was measured through 40 items Clinical Leadership Competency Framework (CLCF) which is made up of five domains. These domains include; Demonstrating Personal Qualities, Working with Others, Managing Services, Improving Services, and Setting Direction.
Results: The nursing students demonstrated moderate proficiency in the aspect of clinical leadership. The mean scores for the five domains of CLCF ranged from 2.33 to 2.67; the mean score of 2.67 was achieved in the domain of Managing Services, while 2.65 in Demonstrating Personal Qualities, 2.59 in Working with Others, 2.56 in Improving Services, and 2.33 in Setting Direction. None of the subjects demonstrated high proficiency in all five domains.
Conclusion: Clinical leadership proficiency is uneven in different domains and therefore calls for more emphasis on strategic leadership education. It would be useful to develop competencies in the aspect of Setting Direction through leadership learning and competency-based education.
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
Background: Artificial intelligence (AI) is increasingly embedded in critical care nursing through monitoring, decision support, and documentation systems, yet nurses’ readiness to use it remains uncertain, particularly in the Middle East region. Critical care nurses are central to AI implementation at the bedside, and their AI-related literacy and fears can influence safe and ethical integration into clinical practice. Aim: To assess AI-related literacy and fears among critical care nurses in Oman and the associated factors. Methods: A nationwide cross-sectional survey was conducted among critical care nurses (N = 477) working in tertiary hospitals in Oman. The Multidimensional Artificial Intelligence Literacy Scale and the Fear towards AI Scale were used to measure AI literacy and fears, respectively. Results: The participants had low overall AI literacy (146.62 ± 84.03), and low AI self-efficacy and AI self-competency. The lowest level of literacy was related to creating AI (2.43 ± 2.63). On the other hand, participants reported moderate overall fear towards AI and moderate levels of fear related to job issues and humanity and ethics. Age, marital status, levels of education, receipt of prior computer or information technology, AI-related training, and work experience, were significant predictors of AI literacy. The predictors of AI self-efficacy and AI competence are presented. Conclusions: Nurses working in critical care settings in Oman reported low levels of AI literacy, but moderate fears related to AI, and this provides an opportunity to build AI competencies and capacity. There is need for deliberate and structured continuing education programs to build capacity for AI utilization, competence, and self-efficacy among critical care nurses. Structured, hands-on AI training that integrates ethical reflection for older nurses with more experience but limited professional education is needed and essential to support safe and equitable AI utilization by critical care nurses in Oman.
Shreedevi Balachandran, J. Muliira, E. Lazarus et al.· The Scientist· 0 citations