Evidence map›Paper›PMID 41088159›Full record

ArticleBMC nursing2025

Artificial intelligence in nursing practice: a qualitative study of nurses' perspectives on opportunities, challenges, and ethical implications.

Gonul Bodur, Hanife Cakir, Suzan Turan, Arzu Kader Harmanci Seren, Polat Goktas

Abstract read
In one paragraph

Article in BMC nursing, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed, 3 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

30 citing papers in PubMed, 3 syntheses or guidelines pooled it.

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  12. [Latent profile analysis of nursesZhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Gonul BodurFlorence Nightingale Faculty of Nursing, Department of Nursing Education, Istanbul University-Cerrahpasa, Istanbul, Turkey. gnlbodur@iuc.edu.tr.ORCID https://orcid.org/0000-0002-2811-534X
Hanife CakirIstanbul Provincial Directorate of Health, Health Services Department, Training and Registration Unit, Istanbul, Turkey.ORCID https://orcid.org/0000-0001-5813-814X
Suzan TuranIstanbul Provincial Directorate of Health Mehmet Akif Ersoy Thoracic and Cardiovascular Surgery Training and Research Hospital, Istanbul, Turkey.ORCID https://orcid.org/0000-0001-9207-7977
Arzu Kader Harmanci SerenFaculty of Health Sciences, Department of Nursing, Fenerbahçe University, Istanbul, Turkey.ORCID https://orcid.org/0000-0002-4478-7234
Polat GoktasUCD School of Computer Science, University College Dublin, Belfield, Dublin, Ireland.ORCID https://orcid.org/0000-0001-7183-6890

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe 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.

methodsThis 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[Formula: see text]structured interviews with 25 clinical nurses. The interviews explored nurses' perceptions of AI, including its basic concepts, applications in nursing practice, ethical and social implications, and potential benefits and drawbacks.

resultsThe analysis identified four overarching themes: (1) Nurses' Conceptualizations of Artificial Intelligence, (2) Opportunities of AI in Nursing Practice, (3) Threats of AI in Nursing Practice, and (4) Ethical and Psychological Concerns in AI-Based Nursing Practice. The findings revealed that nurses had a foundational understanding of AI and its definitions. They acknowledged both the positive and negative impacts of AI technologies on their practice. Nurses expressed that AI could reduce workload, enhance patient care, and improve efficiency. However, they also articulated significant threats, including concerns over professional redundancy, emotional disconnection in caregiving, de-skilling, and the risk of dehumanizing the healthcare environment. Additionally, ethical and psychological concerns emerged, such as ambiguity in accountability, threats to data security and patient safety, unsuitability in psychiatric care contexts, staff surveillance anxiety, and risks of misuse or systemic bias.

conclusionThe study concluded that while nurses possess a basic understanding of AI, the effective and ethical integration of AI technologies in nursing requires targeted training, institutional preparedness, and robust interdisciplinary collaboration. To ensure AI complements rather than compromises nursing values, it is imperative to equip nurses with skills in digital literacy, ethical reasoning, and critical engagement with AI tools. The findings highlight the necessity of structured education programs and policy development that address both the technological and humanistic dimensions of AI use in healthcare. Future research should actively incorporate patient and public voices to ensure that AI-driven transformations in care remain aligned with the principles of patient-centeredness and human dignity.

Indexed as

Artificial intelligenceMachine learningNursingNursing practiceQualitative research

Identifiers

PMID41088159
PMCPMC12522738

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.