Evidence map›Paper›PMID 41834487›Full record

ArticleJournal of nursing management2026

Structural Model of Medication Errors in Clinical Nursing: A Structural Equation Model Based on the Ecological Systems Theory.

Junekyu Kim, Yeoungsuk Song

Abstract readMulticenter Study
In one paragraph

Article in Journal of nursing management, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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

What it found

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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

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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

1 citing paper in PubMed.

  1. Article
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

2 authors.

Junekyu KimDepartment of Nursing, Kyungil University, Gyeongsan, South Korea, kiu.ac.kr.ORCID https://orcid.org/0000-0003-4665-7537
Yeoungsuk SongCollege of Nursing, Research Institute of Nursing Innovation, Kyungpook National University, Daegu, South Korea, knu.ac.kr.ORCID https://orcid.org/0000-0003-2299-1450

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMedication errors remain a critical patient safety issue. Although prior research has examined individual and environmental determinants, few studies have investigated their complex interrelationships within an integrated theoretical framework, particularly in clinical nursing practice.

aimTo examine the structural relationships among the nursing work environment, communication with health professionals, fatigue, and medication errors among clinical nurses, grounded in Bronfenbrenner's ecological systems theory.

methodsA cross-sectional study was conducted involving 230 clinical nurses from four tertiary hospitals in South Korea. Data were collected using validated self-report questionnaires measuring the nursing work environment, communication with health professionals, fatigue, and medication errors. Structural equation modeling, supported by confirmatory factor analysis, was used to evaluate direct and indirect pathways and to assess overall model fit.

resultsThe proposed model demonstrated acceptable fit (χ

conclusionA supportive nursing work environment facilitates effective interprofessional communication, which in turn mitigates fatigue and reduces medication errors. Communication functions as a key mediating mechanism within this structural pathway. IMPLICATIONS FOR NURSING MANAGEMENT: To reduce medication errors, nurse managers should prioritize fostering positive work environments, implementing structured communication protocols, and establishing systematic fatigue management strategies. Such organizational initiatives may enhance communication efficiency and strengthen patient safety outcomes.

Indexed as

Medication ErrorsNursing Staff, HospitalSystems TheoryWorking ConditionsAdultCross-Sectional StudiesFactor Analysis, StatisticalFemaleHumansInterdisciplinary CommunicationLatent Class AnalysisMaleMental FatigueOccupational DiseasesRepublic of KoreaSurveys and Questionnairescommunicationfatiguemedication errornursespatient safetyprofessional practice

Identifiers

PMID41834487
PMCPMC13140185

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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.