Nurses’ Views on Artificial Intelligence and Professional Values: A Gap in Ethical Sensitivity
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By
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Gizem Kubat Bakir
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Nermin Ocaktan
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October 9, 2026
Clinical Report: Nurses’ Views on AI and Professional Values
Overview
The article frames AI in surgical nursing as both a source of potential operational benefits and a challenge to humanistic care, professional identity, and ethical practice. It describes an exploratory sequential mixed-methods study examining relationships among surgical nurses’ attitudes toward AI, ethical sensitivity, and professional nursing values; the supplied material does not report study results.
Background
AI-supported tools are being used in healthcare for decision support, care planning, monitoring, and data analysis, including in technologically intensive surgical settings. The source notes potential benefits such as improved time management, accuracy, and patient safety, alongside concerns about privacy, confidentiality, accountability, and the human connection in nursing. Professional nursing values in the study are defined through caring, professionalism, activism, justice, and loyalty. Ethical sensitivity is described as recognizing ethical aspects of care and moral conflict in clinical decisions.
Data Highlights
The supplied article excerpt describes the study design and constructs but provides no sample size, numerical results, or statistical estimates.
Key Findings
- The study uses an exploratory sequential mixed-methods design to examine surgical nurses’ attitudes toward AI, ethical sensitivity, and professional nursing values.
- The article identifies potential AI-related benefits in clinical decision-making, workload, patient monitoring, time management, accuracy, and traceability.
- Concerns described include data privacy, patient confidentiality, accountability for algorithm-based decisions, and possible loss of human touch and individualized care.
- Professional nursing values are operationalized as caring, professionalism, activism, justice, and loyalty.
- The article states that nurses’ adaptation to AI depends partly on knowledge and technical competence, and that targeted educational interventions have been reported to improve knowledge and attitudes.
- Related article titles supplied concern nursing students’ ethical awareness and AI attitudes, student knowledge and barriers to AI integration, and perceived data risks in AI-enabled nursing research; no findings from those articles are provided in the supplied context.
Clinical Implications
The source identifies structured preparation, ethical guidance, and organizational support as relevant to AI implementation in nursing, and describes education that addresses technical, ethical, and emotional dimensions. It does not provide study results or specific clinical recommendations in the supplied excerpt.
Conclusion
The supplied material presents AI in surgical nursing as a developing practice context involving both operational opportunities and ethical and humanistic concerns. The study’s stated aim is to examine how nurses’ AI attitudes relate to ethical sensitivity and professional values; its findings are not included here.
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- Position Statement: Artificial Intelligence in Health Care - American Academy of Nursing
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- Real-time surveillance system for patient deterioration: a pragmatic cluster-randomized controlled trial - PubMed
- Generative AI-enabled clinical decision support system in primary care: a pragmatic, cluster-randomized trial | Nature Medicine
- Nurses' knowledge, attitudes, literacy, anxiety, and readiness towards artificial intelligence in clinical practice: An international scoping review - ScienceDirect
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- Frontiers | Registered nurses’ experiences with generative artificial intelligence: a meta-synthesis of qualitative studies
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Based on findings from:
Artificial intelligence attitudes and nursing values: Ethical sensitivity gap
Gizem Kubat Bakir, Nermin Ocaktan. Digital Health, 2026.
https://journals.sagepub.com/doi/abs/10.1177/20552076261483888
This content is an AI-generated, fully rewritten summary based on a published scholarly article. It does not reproduce the original text and is not a substitute for the original publication. Readers are encouraged to consult the source for full context, data, and methodology.