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TRUVACE RECORD VERSION
record: TRV-2026-0479
version: 1
kind: certified
reason: Certified into the record
timestamp: 2026-07-22T03:51:21.909823Z
status: published
lens: g_space
sector: health
headline: Artificial intelligence in nursing practice: a qualitative study of nurses’ perspectives on opportunities, challenges, and ethical implications
dek: BACKGROUND: The study aims to explore nurses' views on the effects of artificial intelligence (AI) in nursing, focusing on their understanding, practical applications, ethical considerations, and perceived opportunities and threats. METHODS: This qualitative study used semi[Formula: see text]structured interviews to gain comprehensive insights from clinical nurses, adhering to the Standards for Reporting Qualitative Research for methodological rigor. After obtaining ethical approval, researchers conducted semi[F…
gain_title: Clinical nurses perceived that AI applied in nursing practice could reduce workload and improve efficiency and patient care.
problem_title: (none)
trace_subject: (none)
gain_reading: Clinical nurses perceived that AI applied in nursing practice could reduce workload and improve efficiency and patient care.
gain_evidence: AI could reduce workload, enhance patient care, and improve efficiency
problem_reading: (none)
problem_evidence: (none)
quick_read: A qualitative study published October 14, 2025 interviewed 25 clinical nurses about artificial intelligence in nursing. Researchers coded responses into four themes covering how nurses conceptualize AI, perceived opportunities, perceived threats, and ethical and psychological concerns, finding a foundational understanding alongside mixed views on impact.

The findings matter because they show frontline nurses anticipate both practical help and serious professional and ethical risks from the same tools, suggesting adoption will depend on more than technical performance. Uncertainty remains about how these perceptions translate into measured outcomes, how different specialties or patient groups would view AI, and what training and policy would effectively address accountability, data security, and preservation of humanistic care.
limitation: Findings are based on a small qualitative sample of 25 clinical nurses and do not include patient and public perspectives, limiting generalizability to broader nursing populations and care contexts.
tag: Evidence-backed gain
key_points: Qualitative study conducted semi-structured interviews with 25 clinical nurses after ethical approval. | Analysis identified four themes: conceptualizations of AI, opportunities, threats, and ethical and psychological concerns. | Nurses reported foundational understanding of AI definitions and both positive and negative impacts on practice. | Authors concluded integration requires targeted training, institutional preparedness, and interdisciplinary collaboration in digital literacy and ethical reasoning.
rundown: By the publication date of 2025-10-14, researchers had interviewed 25 clinical nurses using semi-structured interviews adhering to Standards for Reporting Qualitative Research, exploring basic concepts, applications, ethical and social implications, and benefits and drawbacks.

Opportunities identified included workload reduction and efficiency gains, while threats included surveillance anxiety, unsuitability in psychiatric care contexts, risks of misuse or systemic bias, and concerns about emotional disconnection and dehumanizing the healthcare environment.
sources:
- peer_reviewed | BMC Nursing | https://doi.org/10.1186/s12912-025-03775-6 | 2025-10-14
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