Evidence map›Paper›PMID 40243390›Full record

SynthesisInternational nursing review2025

A systematic review and sequential explanatory synthesis: Artificial intelligence in healthcare education, a case of nursing.

S Aslı Bozkurt, Sinan Aydoğan, Fatma Dursun Ergezen, Aykut Türkoğlu

Abstract readSystematic Review
PubMed Full text at PMC Publisher
In one paragraph

Synthesis in International nursing review, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
18citing 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

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

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  7. AI-Based Learning Experiences of Nursing Students: A Qualitative Study.Journal of evaluation in clinical practice · 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

4 authors.

S Aslı BozkurtMassachusetts College of Pharmacy and Health Sciences University, Boston, Massachusetts, USA.
Sinan AydoğanBurdur Mehmet Akif Ersoy University, Burdur, Turkey.
Fatma Dursun ErgezenAkdeniz University, Antalya, Turkey.ORCID https://orcid.org/0000-0002-4707-060X
Aykut TürkoğluBoston University, Boston, Massachusetts, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimThis review aims to explore the impact of artificial intelligence (AI) on knowledge acquisition, skills development, and attitudes among nursing students.

backgroundAI offers hopeful opportunities to enhance learning experiences and prepare future healthcare professionals.

methodsThis was a sequential explanatory mixed-method systematic review. This review was conducted in line with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. A comprehensive electronic database was searched to identify relevant studies. Eligibility criteria were studies examining the impacts of AI interventions on nursing students' knowledge, skills, or attitudes. The methodological quality of the studies was assessed using the mixed-method appraisal tool.

resultsNine research articles were included in the review. These studies utilized both quantitative and qualitative methodologies to examine the impact of AI on nursing students. Quantitative studies found positive relations between AI interventions and knowledge acquisition, skills development, and attitudes toward AI among nursing students. Qualitative findings revealed the positive outcomes of AI in fostering learning engagement, self-efficacy, and confidence.

conclusionsAI shows potential for supporting knowledge acquisition, skills development, and fostering positive attitudes among nursing students. IMPLICATIONS FOR NURSING PRACTICE AND NURSING POLICY: AI-driven interventions enhance nursing education by improving clinical decision-making, confidence, and knowledge acquisition. By integrating AI, nurse educators can develop more interactive, personalized, and impactful learning environments that may help students with the complexities of contemporary healthcare. Policies, standardized guidelines, and faculty development programs may be developed that can promote ethical AI integration, equitable access, and faculty training. These changes can be considered essential to maximize AI's benefits.

Indexed as

Artificial IntelligenceEducation, NursingStudents, NursingAdultClinical CompetenceEducation, Nursing, BaccalaureateFemaleHumansMaleartificial intelligenceattitudeknowledge acquisitionlearningnursing educationskill developmentsystematic review

Identifiers

PMID40243390
PMCPMC12005066

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.