Jul 2026· International Journal For Multidisciplinary Research· Vol 8· 0 citations· 8 references
TL;DR
Nursing students showed a favorable perception toward AIHTs but emphasized the need for structured training programs within nursing curricula, which will enhance preparedness for future clinical practice and promote effective utilization of AI-based healthcare systems.
Abstract
Background: Artificial Intelligence Health Technologies (AIHTs) are rapidly transforming healthcare delivery systems worldwide. Nursing students, as future healthcare professionals, must be prepared to adapt to emerging AI-driven clinical environments. Evaluating their awareness, perceptions, readiness, and expected professional impact is essential for strengthening nursing education and practice. Objectives: This study aimed to evaluate the foresighted effects of Artificial Intelligence Health Technologies on nursing students in terms of knowledge, attitude, readiness, perceived benefits, and anticipated challenges in clinical practice.
Methods: A descriptive cross-sectional study was conducted among undergraduate nursing students using a structured questionnaire. Data were collected regarding demographic variables, awareness of AIHTs, perceived usefulness, expected professional impact, and concerns regarding ethical and technical challenges. Statistical analysis included descriptive and inferential methods.
Results: The study findings revealed that most nursing students demonstrated moderate awareness of AIHTs and expressed positive attitudes toward integrating AI technologies into healthcare settings. Students perceived AI as beneficial for improving patient care accuracy, reducing workload, and supporting clinical decision-making. However, concerns regarding reduced human interaction, ethical issues, and lack of technical training were also reported.
Conclusion: Nursing students showed a favorable perception toward AIHTs but emphasized the need for structured training programs within nursing curricula. Integrating AI education into nursing programs will enhance preparedness for future clinical practice and promote effective utilization of AI-based healthcare systems.
: Artificial intelligence (AI) is increasingly transforming healthcare and creating new competency requirements for future nurses. This narrative review examines the applications, benefits, challenges, and curriculum implications of integrating AI into nursing education. Current evidence shows that AI can support personalised learning, intelligent tutoring, automated feedback, teaching preparation, virtual patients, and simulation-based training. These applications may improve students’ knowledge acquisition, engagement, communication, clinical reasoning, decision-making, and readiness for practice. However, AI integration also raises concerns about inaccurate or fabricated information, algorithmic bias, patient privacy, data security, academic integrity, accountability, and excessive dependence on automated tools. Differences in faculty readiness, institutional resources, and access to technology may further limit effective and equitable implementation. Preparing future nurses for AI-enabled healthcare therefore requires more than technical skills. Nursing students need AI literacy, critical evaluation skills, information verification ability, ethical awareness, data protection knowledge, and strong clinical judgement. AI content should be progressively integrated into nursing informatics, ethics, research, clinical, and simulation courses, supported by faculty development, clear institutional policies, and assessment methods that evaluate students’ reasoning processes. Future research should use longitudinal, experimental, and multicentre designs to examine the long-term effects of AI on clinical competence, patient safety, and professional practice. AI should ultimately enhance rather than replace nurses’ clinical judgement, ethical responsibility, communication, and compassionate care.
Zhang Nan· Advances in Vocational and T...· 0 citations
Background: Artificial intelligence (AI) has emerged as a transformative technology in healthcare, offering significant opportunities to improve clinical decision-making, patient care, and healthcare efficiency. As AI applications continue to expand across healthcare settings, nursing students must develop adequate awareness and readiness to effectively utilize these technologies in future professional practice.
Aim: This study aimed to assess the level of awareness and readiness toward artificial intelligence among nursing students and to identify the factors associated with AI readiness.
Methods: A quantitative cross-sectional survey was conducted among 396 nursing students at Riyadh Elm University, Saudi Arabia. Data were collected using a structured questionnaire consisting of demographic characteristics, the Artificial Intelligence Awareness Scale, and the Artificial Intelligence Readiness Scale. Descriptive statistics, independent t-test, one-way ANOVA with Tukey HSD post hoc analysis, Pearson correlation, and multiple linear regression were performed using SPSS version 27. Statistical significance was set at p < 0.05.
Results: Nursing students demonstrated a moderate level of AI awareness (mean = 3.43 ± 0.44, 68.57%) and a high level of AI readiness (mean = 3.93 ± 0.45, 78.52%). Significant differences in AI awareness were observed according to academic level and self-rated computer skills. AI readiness was significantly associated with age, academic level, previous use of AI-related tools, and self-rated computer skills. A strong positive correlation was found between AI awareness and AI readiness (r = 0.685, p < 0.001). Multiple linear regression analysis identified AI awareness as the strongest independent predictor of AI readiness (B = 0.681, p < 0.001), with the model explaining 56.9% of the variance in AI readiness (R² = 0.569).
Conclusion: Nursing students demonstrated positive readiness toward artificial intelligence despite having only moderate awareness. Integrating AI-related education, practical training, and digital competency development into undergraduate nursing curricula may enhance students' awareness and strengthen their readiness to effectively utilize AI technologies in future nursing practice.
Saada Taktikh Alshammary, Fatimah Salman Zoghbi, D. Alanazi et al.· International Journal of Adv...· 0 citations
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
Dedicated time for AI education for CHNs is needed to address how recommendations are generated and the significance to give to AI recommendations, clear policies and guidelines need to be established to inform CHNs use of AI.
M. H. Betkus, D. Banner, L. Currie et al.· The Canadian journal of nurs...· 0 citations
Undergraduate medical students show moderate awareness of AI in healthcare but lack formal training and in-depth understanding, highlighting the need for structured AI education within medical curricula and further research on its long-term impact.
Sonali Sharma, Smriti Kayat, N. Saboo et al.· Nigerian Medical Journal· 0 citations
Artificial intelligence (AI) is increasingly integrated into healthcare education worldwide, yet disparities in access, training, and institutional readiness remain evident, particularly in low-resource and conflict-affected settings. Understanding how health sciences students engage with AI technologies and the barriers they encounter is essential for guiding the development of AI-ready curricula in Palestinian universities. This study aimed to examine the adoption patterns, perceived barriers, and determinants of artificial intelligence use among health sciences students at Palestine Polytechnic University in Palestine. A descriptive cross-sectional study was conducted among 666 undergraduate students from the Colleges of Nursing, Medicine and Health Sciences, and Dentistry. Data were collected using a validated self-administered questionnaire assessing demographic characteristics, AI knowledge, attitudes, practice behaviors, and perceived barriers. Descriptive statistics summarized usage patterns. Mann–Whitney U tests, Kruskal–Wallis tests, and chi-square analyses examined group differences. Multivariate logistic regression identified predictors of AI adoption. Statistical significance was set at p ≤ .05. The result of the study. AI use was highly prevalent, with 93.4% of students reporting active engagement. AI was primarily used for study and learning (87.7%), written assignments (57.5%), and personal purposes (54.2%). Significant differences in AI usage were observed across academic disciplines (χ² = 17.292, p = .008), with dentistry students reporting longer daily use. Major barriers included limited curriculum integration (48.2%), ethical and privacy concerns (47.9%), and insufficient training centers (40.4%). Multivariate analysis showed that college affiliation and knowledge score significantly predicted AI adoption, whereas gender, academic year, and previous AI training were not significant predictors. The Conclusion. Despite widespread exposure to AI technologies, students’ engagement remains largely informal and constrained by curricular, infrastructural, and ethical barriers. Institutional strategies including curriculum reform, faculty development, and improved digital infrastructure are necessary to support responsible AI integration in health sciences education in Palestine.
N. Alqaissi, Mohammad Qtait· PLOS Digital Health· 0 citations
