Bridging Implementation Gaps: The Critical Role of Institutional Ecosystems in AI Integration for Nursing Education

Awareness, knowledge and attitudes towards artificial intelligence among nursing students: a systematic review protocol

Introduction Internationally, nursing students’ awareness and familiarity with artificial intelligence (AI) remain a challenge as evidenced by the current literature. Interestingly, the Gulf Cooperation Council (GCC) region has earned a strong standing for driving national digital transformation; however, this ambition has not been translated into research. Despite growing interest in AI-driven healthcare, empirical studies examining nursing students’ readiness in these countries to operate in healthcare environments remain limited, representing a critical gap in the literature. Our initial literature review found a high degree of heterogeneity among study designs, measurement tools and theoretical framing and highlighted an unequivocal need for a rigorous and systematic synthesis to uncover consistent patterns, methodological gaps and contextual factors that shape nursing students’ engagement with AI. This protocol aims to provide a structured plan for combining the current evidence on nursing students’ awareness, knowledge and attitudes regarding AI applications in nursing education. Methods and analysis This protocol is prepared in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analysis Protocols (PRISMA-P) 2015 guidelines, and it is registered with the international Prospective Register of Systematic Reviews (PROSPERO). A comprehensive and systematic search of the literature will be undertaken across four key electronic databases: PubMed, CINAHL, Scopus and Web of Science, using Boolean search strings constructed from Medical Subject Headings-controlled terms and free-text keywords encompassing six predefined thematic domains: AI applications in nursing education, student awareness, attitudes, technology acceptance, adoption, ethical considerations and regional context. All studies published in English between January 2020 and June 2026 including cross-sectional, cohort, quasiexperimental and qualitative studies will be included in this review. The primary outcome is nursing students’ awareness of and attitudes toward AI; secondary outcomes include AI-related knowledge, behavioural intention and ethical concerns. A 41-item standardised form will be used for data extraction across all included studies, systematically capturing study characteristics, instruments, theoretical frameworks, barriers, facilitators and the outcomes of interest. To assess the studies’ quality, we will use the Joanna Briggs Institute (JBI) Critical Appraisal Tools for quantitative and qualitative studies, ensuring a comprehensive and methodologically consistent appraisal process across all included studies. Narrative synthesis will be performed complemented by meta-analysis where applicable, organised by the construct domains and geographic regions. This protocol provides an in-depth, systematic review plan that will report the most thorough synthesis to date regarding nursing students’ awareness, knowledge levels and perceptions of the utilisation of AI within nursing education. The review will identify validated instruments for cross-cultural adaptation, establish benchmarks and estimate prevalence of awareness, knowledge and attitude. We will describe the theoretical and contextual contrived factors associated with these constructs in nursing students. Ethics and dissemination As this systematic review is based exclusively on published literature and does not involve the collection of primary data from human participants or animals, formal ethical approval is not required. Findings from this review will be disseminated through publication in a peer-reviewed journal and presented at relevant national and international nursing and healthcare conferences. The review is expected to generate evidence-based insights that will inform nursing curricula, guide institutional policy on AI integration and highlight the critical evidence gap in the GCC region, including Oman, thereby contributing to the advancement of AI-ready nursing education internationally. A key focus will be mapping geographic variation, with particular attention to the GCC region where empirical evidence remains sparse. PROSPERO registration number CRD420261320108.

Shortcomings of modeling interprofessional collaboration competence in nurse education: A protocol for a scoping review of empirical research

Interprofessional collaboration is recognized as central to improving healthcare outcomes. The digital transformation further reshapes collaboration demands, extending the traditional notion of interprofessional collaboration beyond nursing and healthcare. Therefore, interprofessional collaboration competence (ICC) constitutes a key outcome in nurse education. This knowledge-user-informed protocol registered with OSF (https://osf.io/8rbv7) outlines a scoping review aiming to identify shortcomings in (1) how competence facets, conceptualized as a continuum (Blömeke et al. 2015), are represented; (2) how nursing students’ ICC is theoretically elaborated, as reflected in the extent of theory talk; and (3) how ICC is empirically modeled in nurse education research. Guided by the JBI methodology and the PRISMA-ScR 2020 guidelines, this scoping review will systematically search the following seven databases to ensure coverage of nursing, educational research, and psychology: (i) Web of Science Core Collection, (ii) Scopus, (iii) ProQuest, (iv) MEDLINE, (v) Education Source, (vi) Cochrane Library, and (vii) APA PsycArticles. By synthesizing the eligible publications, the review seeks to provide a structured overview of research on modeling nursing students’ ICC, thereby enabling the identification of research shortcomings. Completion of the proposed scoping review is anticipated within the period from May to November 2027.• The proposed review maps which facets of competence-as-a-continuum are addressed in modeling nursing students’ ICC within empirical research.• It identifies shortcomings in the theoretical and empirical modeling of nursing students’ ICC.• The findings will provide a basis for future research, informing the development of more effective educational interventions for the ICC of nursing students, and others.

Educators' Perspectives on Generative AI Use in Nursing Education: Friend or Foe?

AIM This study explores nursing educators' perspectives on the challenges and benefits of integrating generative artificial intelligence (AI) into nursing education. There is little empirical evidence on how educators perceive these technologies and how such perceptions influence their integration into curriculum design, teaching practices, assessment, and student research and learning. DESIGN Exploratory-descriptive qualitative study underpinned by the Actor-Network Theory. METHODS Four focus group sessions were conducted with ten nursing educators across Australia, New Zealand, Austria and Hong Kong. Data were collected via Zoom, transcribed verbatim, and analysed thematically using Braun and Clarke's six-step reflexive framework. RESULTS The nurse educators included five women and five men. Ages ranged between 25 and 64 years and a mean 8.75 [SD ±6.36] years of experience as an educator. Three main themes were constructed based on focus group discussions: (1) The AI Dilemma, revealing tensions surrounding academic integrity, policy ambiguity and ethical concerns; (2) The AI Toolkit, identifying pedagogical benefits alongside challenges to critical thinking development; and (3) Educator's AI Odyssey, exposing disparities in institutional preparedness and educator competence. Whilst AI was recognised for enhancing engagement and efficiency, substantive concerns persisted regarding equity, ethical implementation and organisational readiness. CONCLUSION Generative AI presents a paradox in nursing education. Whilst it enables innovation and personalised learning, it poses risks to academic integrity and deep learning when implementation lacks ethical consideration and pedagogical rigour. IMPLICATIONS FOR PROFESSION AND PATIENT CARE AI-enhanced nursing education must safeguard fundamental nursing values, critical thinking capabilities, ethical reasoning and clinical judgement to ensure the delivery of safe, competent patient care. IMPACT Educational and institutional policies must facilitate balanced, ethical and equitable integration of AI in nursing education. REPORTING METHOD The Consolidated Criteria for Reporting Qualitative Research (COREQ). PATIENT OR PUBLIC CONTRIBUTION No patient or public contribution.

AI-driven Design Thinking and Service-Learning enhance nursing students’ evidence-based competencies in family healthcare delivery

Introduction: The integration of Evidence-Based Practice (EBP) into nursing education faces challenges in linking theory to clinical application in complex family health contexts. Students struggle with efficiently accessing, appraising, and applying evidence influenced by sociocultural factors. Artificial intelligence (AI) offers transformative potential but requires pedagogical design to foster critical thinking and ethical use beyond technical skills.Method: An action research with mixed methods was conducted with 100 nursing students. The intervention had four phases: participatory family diagnosis, AI-assisted evidence retrieval and validation, community educational workshops design and execution, and multi-level evaluation.Results: A significant shift in AI use from basic to strategic, with a 40% reduction in literature search time. Qualitative data revealed enhanced critical awareness and ethical reasoning, while quantitative results indicated 90% of students improved critical appraisal skills and 70% felt more confident in evidence-based decisions. The project impacted 100 families, with 90% trusting evidence-based recommendations.Conclusions: Integrating AI in experiential pedagogies like Design Thinking and Service-Learning effectively develops nursing competencies, ensuring technology adoption supports context-sensitive family health learning outcomes.

Genomics in Nursing Curricula: A Qualitative Study of Portuguese Educators' Views.

BACKGROUND Genomics is reshaping healthcare and is increasingly recognized as essential to nursing. Although international organizations call for aligned genomic competencies, integration in undergraduate education remains limited. Curriculum-mapping studies show what is taught, but little is known about how educators interpret genomic relevance or navigate institutional constraints. AIM To explore how nursing educators in Portuguese higher education institutions understand, value, and operationalize genomics within nursing education programs. METHODOLOGY A qualitative, exploratory study grounded in interpretivist and reflexive epistemology was conducted through online focus groups with ten nursing educators. Data were generated through dialogic discussions and analyzed using reflexive thematic analysis. RESULTS Three themes captured shared meanings. Educators viewed genomics as aligned with holistic and person-centered nursing. However, its curricular presence was described as fragmented, implicit, and predominantly taught through biomedical lenses. Structural constraints, such as curriculum saturation, regulatory rigidity, uneven faculty expertise, and reduced contact hours, were perceived as barriers to systematic integration. Participants also constructed feasible pathways to achieve integration, including transversal embedding, case-based pedagogies, flexible initiatives, and interprofessional collaboration. DISCUSSION Educators' interpretations illustrate how global recommendations are adapted within local realities. They also highlight pragmatic strategies that can support incremental and context-sensitive integration of genomics into nursing education. CONCLUSION Purposeful integration requires coordinated action across pedagogical design, faculty development, and system-level structures. IMPLICATIONS FOR NURSING Strengthening faculty preparation and embedding genomic concepts across curricula can enhance genomic literacy. IMPLICATIONS FOR HEALTH POLICY Aligning educational standards and regulatory frameworks with genomic competencies is key to preparing a genomics-ready nursing workforce.

[The Paradox and Integration of Digital Therapeutics: The Perspectives of Nursing Care and Care Ethics].