Evidence map›Paper›PMID 42532581›Full record

ArticleChild health nursing research2026

Development and pilot evaluation of an AI-based pediatric medication safety virtual simulation program for nursing students: a quasi-experimental study in South Korea.

In Young Cho, Soohyeon Cho, Min Yeong Im, Hui Jung Jeong, Jimin Choi, In Hyeong Choi, Hee Young Kim

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Article in Child health nursing research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

In Young ChoAssociate Professor, College of Nursing, Chonnam National University, Gwangju, Korea.
Soohyeon ChoUndergraduate Student, College of Nursing, Chonnam National University, Gwangju, Korea.
Min Yeong ImUndergraduate Student, College of Nursing, Chonnam National University, Gwangju, Korea.
Hui Jung JeongUndergraduate Student, College of Engineering, Chonnam National University, Gwangju, Korea.
Jimin ChoiUndergraduate Student, College of Philosophy, Chonnam National University, Gwangju, Korea.
In Hyeong ChoiRegistered Nurse, Department of Nursing, Chonnam National University Hospital, Gwangju, Korea.
Hee Young KimDoctoral Student, Department of Nursing, Chonnam National University, Gwangju, Korea. hee0xox@naver.com.

Funding

Chonnam National University 2025-1017-01
6 · The paper itself

Abstract

purposeThis study aimed to develop an artificial intelligence (AI)-based pediatric medication safety competence (PMSC) virtual simulation program and evaluate its effectiveness among nursing students.

methodsThis quasi-experimental study used a nonequivalent control group pretest-posttest design and was conducted in December 2025. The AI-based PMSC virtual simulation program was developed based on Kolb's experiential learning theory, following its 4-stage cycle of concrete experience, reflective observation, abstract conceptualization, and active experimentation. Participants were 48 third-year nursing students in South Korea who were assigned to either the experimental group (n=24) or the control group (n=24) through a nonrandomized allocation procedure. The experimental group participated in the PMSC virtual simulation program. Outcomes included PMSC, medication calculation confidence (MCC), Simulation Task Load Index (SIM-TLX), and learning immersion (LI). Data were collected before and after the intervention using validated instruments, and statistical tests were used to evaluate program effectiveness.

resultsCompared with the control group, the experimental group showed significant improvement in PMSC (t=2.48, p=.017). No significant between-group differences were observed in MCC (t=-0.87, p=.389) or LI (t=0.97, p=.336). In addition, SIM-TLX scores decreased significantly from pretest to posttest in the experimental group (t=-2.61, p=.016).

conclusionThe AI-based PMSC virtual simulation program may help strengthen PMSC among nursing students and may be suitable for use in pediatric nursing education. Future research should refine the program to better address individual learning needs and integrate complementary simulation-based strategies into pediatric medication nursing education.

Indexed as

Artificial intelligenceNursing studentsPatient safetyPediatric nursingSimulation training

Identifiers

PMID42532581
PMCPMC13434462

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LicenceCC BY-NC-ND
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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.