The findings highlight the need for a supportive educational environment with guidance to enable nursing students to use artificial intelligence appropriately and responsibly when needed, particularly among vocational college students and those from socioeconomically disadvantaged backgrounds.
Abstract
Background
Artificial intelligence (AI) is rapidly transforming healthcare. Current and future healthcare workforce, including nursing students, require sufficient understanding of responsible AI use. However, data about knowledge, attitudes, practices and ethics regarding AI use in this population is scarce. This national study comprehensively assessed AI-related knowledge, attitudes, practices and ethics among nursing students in China, including the socio-demographic and educational factors associated with these professional domains.
Methods
A cross-sectional survey was conducted between June and August 2025 across 32 provinces, autonomous regions and municipalities in China. A total of 10,268 nursing undergraduates and vocational college students completed a newly developed 22-item Knowledge, Attitudes, Practices and Ethics questionnaire covering four domains (Cronbach's α = 0.79-0.96). Univariable analyses and multiple linear regression were used to examine socio-demographic factors of AI-related knowledge, attitudes, practices and ethics.
Results
Nursing students reported moderate level of AI knowledge (18.17 ± 4.90, total score 24), moderately positive attitudes (11.96 ± 2.49, total score 20), relatively good ethical awareness (11.60 ± 3.27, total score 16), but only limited engagement in practice (8.29 ± 5.04, total score 28). Of the participants, only 6.8%-9.6% reported "often" and "always" using AI tools for academic and personal tasks. In multivariable models, male gender, urban residence, higher economic status, and intention to pursue nursing as a career were independently associated with higher scores across the knowledge, attitude, and ethics domains (all P < 0.05). Compared with vocational college students, undergraduates had significantly higher scores on attitude, practice and ethics domains (all P < 0.05). Age was positively associated with all domains, although only the 19-20-year group had significantly higher scores in the practice domain (P < 0.001).
Conclusion
The findings highlight the need for a supportive educational environment with guidance to enable nursing students to use artificial intelligence appropriately and responsibly when needed, particularly among vocational college students and those from socioeconomically disadvantaged backgrounds. Integrating AI competencies into nursing education and linking them to future career development and clinical practice may help bridge the gap between positive attitudes and limited practical use.
Abstract Background In recent years, artificial intelligence (AI) has ushered in a promising era in medicine, particularly in medical education. However, studies assessing the knowledge, attitudes, and practices related to AI among medical students in Vietnam remain limited. Objective This study aimed to evaluate AI knowledge, attitudes, and practices among Vietnamese medical students in learning and research, and to identify factors associated with their AI practices. Methods A cross-sectional study was conducted among medical students at Thai Binh University of Medicine and Pharmacy from November to December 2025. Data were collected using an online structured questionnaire covering demographic characteristics and AI knowledge, attitudes, and practices. The main outcome of interest was AI practices in learning and research. Descriptive statistics and multivariable linear regression were used to examine associated factors. Regression coefficients (β), 95% CIs, and P values are reported. Results A total of 1002 medical students (mean age 21.00, IQR 19.00-23.00 years; n=596, 59.5% female) were included. The median percentage of maximum possible (POMP) score of AI knowledge was 66.67 (IQR 33.33‐83.33), with a high level of familiarity with common tools (n=798, 79.6%). AI attitudes were generally positive (median POMP score 70.00, IQR 53.33‐76.67). AI-related practices were lower (median POMP score 50.00, IQR 46.88-71.88), with AI being used primarily for information retrieval and literature research support. In the multivariable analysis, knowledge POMP score (β=0.12, 95% CI 0.08-0.16) and attitudes POMP score (β=0.42, 95% CI 0.34-0.51) were significantly associated with AI practices POMP score (P<.001). Age, gender, major, grade point average classification, and having participated in an AI seminar or training were not associated with AI practices. Conclusions Medical students showed favorable knowledge and positive attitudes, but their AI practices remained limited. Integrating AI into medical curricula, including fundamentals, applications, and ethical aspects, is essential to prepare future physicians for AI-driven health care.
Minh Tien Bui, H. Le, Thị Hoài Khanh Lương et al.· JMIR Formative Research· 0 citations
Healthcare students had unsatisfactory awareness of AI, and their overall attitude was negative, highlighting an urgent need for an integrated AI curriculum tailored to their actual needs.
Waghachavare Vivek B., Dhobale Randhir V., Gore Alka D. et al.· International journal of com...· 0 citations
BACKGROUND
Artificial intelligence (AI) has emerged as one of the most rapidly evolving technologies in recent years and is increasingly being integrated into healthcare, education, and everyday life. Examining university students' attitudes toward this technology is important for understanding their future professional orientations and adaptation to technological change. This study aimed to identify medical students' attitudes toward artificial intelligence and the determinants of these attitudes, and to develop educational implications for medical training based on the findings.
METHODOLOGY
This descriptive cross-sectional study was conducted between January 22 and May 28, 2025, among 198 final-year medical students at Pamukkale University Faculty of Medicine in Denizli, Türkiye. Data were collected using a Descriptive Information Form, which assessed students' sociodemographic characteristics and their knowledge and experiences regarding AI, and the General Attitudes toward Artificial Intelligence Scale (GAAIS, Turkish version). Since the negative subscale is reverse-coded, higher scores in both indicate more positive attitudes toward AI. Data were analyzed using SPSS v25 with descriptive statistics, Mann-Whitney U, Kruskal-Wallis, and multiple linear regression analyses.
RESULTS
The mean age of participants was 24.47 ± 0.98 years; 56.1% were female. A total of 74.2% of the participants reported general knowledge about AI, and 76.3% reported experience using AI in daily life. A total of 63.1% viewed AI developments positively, 69.7% believed AI changes work and daily life, and 52.0% felt emotionally unaffected by it. The mean positive attitude score was 45.01 ± 9.17, and the negative attitude score was 26.41 ± 6.22. Multiple linear regression analysis showed that positive attitudes toward artificial intelligence were significantly associated with father's education level (university vs. primary school), having an interest in technology, perceptions regarding developments in artificial intelligence, and the belief that AI has an emotional impact (p < 0.05). For the negative attitude subscale, only perceptions regarding developments in artificial intelligence were found to be significantly associated (p < 0.05).
CONCLUSION
Medical students demonstrated generally positive attitudes toward AI. Higher paternal education, technological interest, perceiving AI as emotionally influential, and evaluating AI developments positively were predictors of favorable attitudes. In addition, more positive evaluations of AI-related developments were also associated with higher scores on the reverse-coded negative attitude subscale, indicating lower negative attitudes toward AI. These findings suggest that students' attitudes toward AI are shaped not only by technological interest but also by perceptual factors related to AI. Therefore, integrating clinically oriented AI content and awareness-building activities into medical education may support the development of more balanced and informed attitudes toward AI.
Batuhan Horasan, A. Ergin, Eda Şenarabacı· BMC Medical Education· 0 citations
The weak negative correlation between knowledge and attitudes suggests that greater awareness of AI may be accompanied by increased concerns regarding its use, and further educational initiatives are needed to enhance nurses’ preparedness for AI integration in clinical practice.
R. Elsayed, A. Nagy, Eman Sobhy El-Said Hussein et al.· BMC Nursing· 1 citation
In recent times, nursing students have been utilizing artificial intelligence (AI) technology, as they perceive it boosts learning outcomes and academic performance and transforms several facets of healthcare. This study aimed to explore nursing students' knowledge, attitudes and perceptions concerning the adoption of AI in their academic and clinical areas. It applied an exploratory study design to cover the study population of all undergraduate students, including interns from selected private nursing colleges in Tamil Nadu, India (N = 440). A self-designed online questionnaire was distributed via Google Forms to the target population and 317 responded. The results showed that 81.3% were familiar with the term "AI" (81.3%). 76.3% recognized that AI would revolutionize the nursing field. Most nursing students consented that AI should be included in undergraduate (67.2%) and postgraduate (71.3%) nursing curricula. 77.9% perceived that AI would be helpful for their future career. A significant variation was observed in nursing students' knowledge, attitude and perception scores across age categories, but not for gender and year of study. This study concluded that female nursing students, especially those aged 17-19, demonstrated strong knowledge, an optimistic attitude and had a better perception of AI. The findings suggest that nursing students in India possess adequate knowledge about AI, indicating a positive perception that AI plays a transformative function in nursing education and practice, with a need for more focused training and integration into the curriculum.
Arul Valan, Latha S Kannan, A. Subbarayalu et al.· International Research Journ...· 0 citations
Aims and Objectives To investigate the mediating role of nursing students’ artificial intelligence (AI) ethics awareness between the association of attitudes toward AI technology and perceived AI utilization. Background A paucity of studies exists about the role of AI ethics awareness between attitudes toward AI technology and perceived AI utilization, particularly among nursing students. Methods A multisite cross‐sectional, correlational research participated by nursing students (n = 765) that were consecutively recruited from four nursing colleges (two private and two public owned) in Saudi Arabia. Three standardized self‐report scales were utilized to collect data, and covariance‐based structural equation modeling, using maximum likelihood estimation and bias‐corrected bootstrap method, and mediation analyses were employed for data analyses. Results The mean age of participants was 23.98 years old (SD = 4.40), and majority were females (78.90%), were second year students (33.85%), and had a mean grade point average of 4.16 (SD = 0.65). AI technology attitudes were positively associated with AI ethics awareness (β = 0.84, p = 0.001, and 95% CI = 0.76–0.94) and AI utilization (β = 0.55, p = 0.010, and 95% CI = 0.13–0.97). AI ethics awareness was positively associated with AI utilization (β = 0.41, p = 0.043, and95% CI = 0.01–0.84). Mediation analysis showed that AI technology attitudes were indirectly associated with AI utilization (β = 0.36, p = 0.013, and 95% CI = 0.05–0.68) via the mediation of AI ethics awareness. AI technology attitudes measured 72.05% of the R 2 of AI ethics awareness, while both AI ethics awareness and AI technology attitudes measured 87.94% of the R 2 of AI utilization. Conclusion Nursing students’ AI technology attitudes and AI ethics awareness were positively associated with AI utilization, whereas AI ethics mediated between AI technology attitudes and AI utilization. Policymakers, nursing educational institutions, and educators could integrate AI ethics into nursing curricula to cultivate positive AI attitudes and responsible AI usage, preparing future nurses for an AI‐integrated healthcare environment. Implications for Nursing Management Nurse administrators in the nursing educational institutions and nurse managers in affiliated clinical training centers should provide a conducive learning environment (i.e., adequate resources, teaching/learning materials, and AI‐trained staff) where students can learn AI‐integrated technologies through practical or simulated activities.
D. J. Berdida, Noura Alhudaib, R. A. N. Grande et al.· Journal of Nursing Managemen...· 0 citations