ArticleBMC nursing2024
Leading with AI in critical care nursing: challenges, opportunities, and the human factor.
Article in BMC nursing, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers, 5 of them syntheses that pooled it.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
38 citing papers in PubMed, 5 syntheses or guidelines pooled it.
- Reimagining nursing practice in the era of AI: a qualitative systematic review and meta-synthesis of nurses' lived experiences.Journal of health, population, and nutrition · 2026Pooled it
- Registered nurses' experiences with generative artificial intelligence: a meta-synthesis of qualitative studies.Frontiers in public health · 2026Pooled it
- Stakeholder experience with artificial intelligence in healthcare: a bibliometric study of satisfaction, trust, acceptance, and patient engagement.Frontiers in digital health · 2026Pooled it
- A bibliometric analysis of artificial intelligence research in critical illness: a quantitative approach and visualization study.Frontiers in medicine · 2025Pooled it
- Integrative review of artificial intelligence applications in nursing: education, clinical practice, workload management, and professional perceptions.Frontiers in public health · 2025Pooled it
- When Care Becomes Digital: Shared Experiences in Psychiatric Nursing-A Phenomenological Study.Journal of psychiatric and mental health nursing · 2026Article
- Artificial Intelligence (AI) in Home-Care and Community Nursing: A Scoping Review.Healthcare (Basel, Switzerland) · 2026Review
- The Role of Machine Learning and Artificial Intelligence in Enhancing Critical Care Nursing Practice: A Scoping Review.Nursing in critical care · 2026Article
- Work autonomy mediates associations between medical AI readiness and well being in a three wave nurse study.Scientific reports · 2026Article
- Technology use in pediatric cardiovascular surgery intensive care nursing: a qualitative study.BMC nursing · 2026Article
- Artificial Intelligence Literacy Levels and Attitudes Toward Artificial Intelligence Technology Among Intensive Care Nurses: A Cross-Sectional Study.Journal of evaluation in clinical practice · 2026Article
- Application of the Technology Acceptance Model to Predict Nursing Students' Intention to Use Informatics: Cross-Sectional Study.JMIR nursing · 2026Article
- Explainable Artificial Intelligence in Healthcare: Current Landscape, Challenges, and Future Directions.Health science reports · 2026Review
- An Explanation User Interface for Artificial Intelligence-Supported Mechanical Ventilation Optimization for Clinicians: User-Centered Design and Formative Usability Study.JMIR formative research · 2026Article
- Review
- Attitudes of psychiatric nurses towards the integration of artificial intelligence applications to clinical care: a qualitative study in China.BMC nursing · 2026Article
- The relationship between nurses' anxiety and attitudes towards artificial intelligence and examination of influencing factors.BMC nursing · 2026Article
- A Six-Month Observational Study of Nursing Workload in 14 Latvian Intensive Care Units Using the Nursing Activities Score.Healthcare (Basel, Switzerland) · 2026Article
- Impact of Hospital Hierarchy on Nurses' Attitudes Toward Artificial Intelligence: Mediating Roles of Artificial Intelligence Literacy and Anxiety.Journal of nursing management · 2026Article
- Intention to Use Large Language Models Among Clinical Nurses in China With Prior Familiarity With or Experience Using LLMs: A Qualitative Study.Journal of nursing management · 2026Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionThe integration of artificial intelligence (AI) in intensive care units (ICUs) presents both opportunities and challenges for critical care nurses. This study delves into the human factor, exploring how nurses with leadership roles perceive the impact of AI on their professional practice.
objectiveTo investigate how nurses perceive the impact of AI on their professional identity, ethical considerations surrounding its use, and the shared meanings they attribute to trust, collaboration, and communication when working with AI systems.
methodsAn interpretive phenomenological analysis was used to capture the lived experiences of critical care nurses leading with AI. Ten nurses with leadership roles in various ICU specializations were interviewed through purposive sampling. Semi-structured interviews explored nurses' experiences with AI, challenges, and opportunities. Thematic analysis identified recurring themes related to the human factor in leading with AI.
findingsThematic analysis revealed two key themes which are leading with AI: making sense of challenges and opportunities and the human factor in leading with AI. The two main themes have six subthemes which revealed that AI offered benefits like task automation, but concerns existed about overreliance and the need for ongoing training. New challenges emerged, including adapting to new workflows and managing potential bias. Clear communication and collaboration were crucial for successful AI integration. Building trust in AI hinged on transparency, and collaboration allowed nurses to focus on human-centered care while AI supported data analysis. Ethical considerations included maintaining patient autonomy and ensuring accountability in AI-driven decisions.
conclusionWhile AI presents opportunities for automation and data analysis, successful integration hinges on addressing concerns about overreliance, workflow adaptation, and potential bias. Building trust and fostering collaboration are fundamentals for AI integration. Transparency in AI systems allows nurses to confidently delegate tasks, while collaboration empowers them to focus on human-centered care with AI support. Ultimately, dealing with the ethical concerns of AI in ICU care requires prioritizing patient autonomy and ensuring accountability in AI-driven decisions.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.