Jul 2026· International Journal of Nursing Studies Advances· Vol 11, pp. 100636· 0 citations· 44 references
Medicine
TL;DR
Nursing students in this Saudi sample demonstrated nuanced perspectives on artificial intelligence adoption, characterised by cautious optimism alongside critical awareness, suggesting deeper engagement fosters appreciation of both opportunities and challenges.
Abstract
Background : Artificial intelligence offers transformative potential for nursing practice, yet significant barriers hinder adoption. While existing research has documented challenges among practicing nurses, limited evidence exists regarding nursing students' perspectives; they are the generation that will shape artificial intelligence's future role in healthcare. Objective : To explore barriers and facilitators to artificial intelligence adoption among nursing students using a mixed-methods approach, examining relationships between technological readiness, ethical concerns, and perceived usefulness of artificial intelligence in nursing practice. Design : Explanatory sequential mixed-methods study combining quantitative surveys with qualitative semi-structured interviews. Setting College of Nursing, Taibah University, Medina, Saudi Arabia (November 2024–March 2025). Participants 348 nursing students across academic levels 3–8 participated in the quantitative phase (response rate: 72.5%), with 17 students purposively selected for qualitative interviews. Methods Validated instruments — the Technology Readiness Index 2.0, an adapted Perceived Usefulness Scale, and an Ethical Concerns Scale — were administered online. Kendall's tau correlation and partial proportional odds modeling identified predictors of perceived usefulness. Qualitative data underwent thematic analysis using Braun and Clarke's framework. Trustworthiness was addressed through investigator triangulation, an audit trail, reflexive memoing, and member-checking. Mixed-methods integration followed a joint-display framework to examine convergence between quantitative and qualitative findings. Results Technological optimism (Kendall's tau [τ] = 0.45, 95% confidence interval [CI]: 0.39 to 0.50, p < 0.001) and innovativeness (τ = 0.41, 95% CI: 0.35 to 0.47, p < 0.001) showed strong positive associations with perceived artificial intelligence utility. Paradoxically, moderate ethical concern predicted higher perceived usefulness (adjusted odds ratio for perceiving low utility = 0.19, 95% CI: 0.09 to 0.40, from the partial proportional odds model). From the qualitative analysis, we revealed universal concern about deskilling (100% of interviewees), data privacy risks (94%), and erosion of human connection in patient care. Participants proposed shared decision-making models where artificial intelligence provides recommendations while nurses retain final clinical authority. The lack of nursing-specific artificial intelligence tools emerged as a critical barrier. Conclusions Nursing students in this Saudi sample demonstrated nuanced perspectives on artificial intelligence adoption, characterised by cautious optimism alongside critical awareness. The paradoxical relationship between ethical concern and perceived utility challenges traditional technology acceptance models, suggesting deeper engagement fosters appreciation of both opportunities and challenges. We have underscored the importance of tailored educational strategies addressing technical competencies alongside ethical reasoning and professional identity formation. As this generation of digitally fluent students transitions into nursing practice, the perspectives of this sample offer insights for developing artificial intelligence integration approaches that preserve nursing's humanistic core while leveraging technological capabilities.
Community health nursing (CHN) is central to primary healthcare delivery, but undergraduate nursing students may encounter educational, organizational, resource-related, and sociocultural barriers that affect their readiness for community-based practice. This study aimed to identify and quantify perceived barriers to CHN practice among nursing students in Saudi Arabia and to examine their relationships with self-reported educational preparedness and organizational support.
A quantitative cross-sectional survey was conducted among nursing students enrolled in Saudi universities. A structured online questionnaire assessed perceived CHN practice barriers, educational preparedness, and organizational support. The instruments underwent cultural adaptation, forward-backward translation, expert-panel content validation, pilot testing, and internal-consistency assessment. Descriptive statistics, non-parametric tests, correlation analyses, and exploratory multiple linear regression were used.
A total of 139 nursing students completed the survey. Participants reported minor-to-moderate overall barriers (
M
= 2.69, SD = 0.96). Resource barriers were rated highest, with shortage of equipment (
M
= 2.93, SD = 1.38) and lack of educational materials (
M
= 2.86, SD = 1.32) identified as the most salient challenges. Educational preparedness (
M
= 3.25, SD = 0.98) and organizational support (
M
= 3.46, SD = 1.03) were rated moderately positive. Small-to-moderate positive correlations were observed between barriers and educational preparedness (
r
= 0.269,
p
= 0.001) and between barriers and organizational support (
r
= 0.242,
p
= 0.004); these findings were interpreted cautiously as potentially reflecting awareness effects, conceptual overlap, or shared-method variance. The multivariable regression model was not statistically significant and explained a small proportion of variance (
R
2
= 0.089,
p
= 0.052).
Nursing students in Saudi Arabia perceived meaningful, though not severe, barriers to effective CHN practice, with resource limitations and skills gaps as primary concerns. The findings support strengthened curriculum-practice integration, expanded simulation and community-immersion experiences, improved placement resources, and targeted faculty development aligned with healthcare transformation priorities.
This study aimed to examine the barriers that nurses encounter in fulfilling their professional roles and to explore solution-oriented suggestions through a phenomenological approach. Nursing is a discipline that encompasses multifaceted professional roles such as caregiver, educator, advocate, researcher, manager, and decision-maker. However, performing these roles effectively can be challenging for nurses due to various barriers arising at individual, institutional, and societal levels. The research was conducted with 18 participants, including nursing students and faculty members from a foundation university. Data were collected through semi-structured in-depth individual interviews and analyzed using thematic analysis. The findings were categorized under five main themes: individual-level barriers (e.g., lack of motivation, low self-confidence, language barriers), institutional-level barriers (e.g., excessive workload, staff shortages, lack of merit-based management), societal-level barriers (e.g., stereotypes, low professional prestige), role-specific implementation difficulties, and participant-suggested solutions. Participants emphasized the need for enhanced educational opportunities, stronger managerial support, increased public awareness, and institutional encouragement for professional development to improve the implementation of nursing roles. This study sheds light on the multidimensional nature of the barriers faced by nurses and, with its solution-oriented perspective, is expected to contribute to both health policy and nursing education.
Arzu Çağla Avcı, Fatih Özdemir, Eslem Gönen et al.· Turkish journal of health sc...· 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/Objectives: Nursing informatics (NI) competence is becoming increasingly essential for nursing students; however, previous research has largely relied on quantitative surveys and provided limited insights into why positive attitudes may not be accompanied by practical competence. This study examined Chinese undergraduate nursing students’ self-assessed NI competence and qualitatively explored their conceptual understanding, perceptions, and experiences related to NI and digital health. Methods: A convergent parallel mixed-methods design was employed in Guangzhou, China. Quantitative data were collected from 149 undergraduate nursing students across two nursing schools using the Chinese Self-Assessment of Nursing Informatics Competencies Scale (SANICS), whereas qualitative data were gathered from 23 students at one of the participating schools through six semi-structured focus groups. Quantitative data were analyzed using descriptive statistics and exploratory Spearman correlations, while qualitative data were analyzed thematically. Findings from both strands were integrated during interpretation using a joint display matrix. Results: The mean self-assessed NI competence score was 2.78 ± 0.54 (scale 1–5). Among the five SANICS subscales, attitudes toward NI scored highest (4.16 ± 0.76), whereas applied computer skills scored lowest (2.02 ± 0.80), confirming an attitude-competence paradox. Exploratory correlation analyses showed neither year of study nor clinical exposure was significantly associated with the total competence score, although both were negatively associated with attitudes. Three qualitative themes contextualized this paradox: (1) a fragmented conceptual understanding centered primarily on basic functions and tools; (2) positive but cautious perceptions that recognized the value of NI while expressing concerns about humanistic care; and (3) passive skill acquisition, limited hands-on learning, and insufficient awareness of higher-order informatics roles. Conclusions: In this two-school sample, students valued NI but reported limited applied and clinically situated competence. The findings suggest that curricula should move beyond generic computer courses and unstructured exposure toward practice-embedded NI education, including electronic health record simulation, digital documentation, data security, and clinically relevant digital skills.
Yan-Jing Lv, Minyi Li, Yang Yue et al.· Nursing Reports· 0 citations
To explore how nursing graduate students in China experience and navigate generative artificial intelligence use in their research practice, including the conditions under which such use becomes dependency, a differentiated, stage-sensitive artificial intelligence governance frameworks tailored to nursing graduate education is advocated.
Furong Chen, Jingjing Cai, Shaoxue Li et al.· International Journal of Nur...· 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