Evidence map›Paper›PMID 38183036›Full record

ArticleBMC medical education2024

Integrated virtual simulation and face-to-face simulation for clinical judgment training among undergraduate nursing students: a mixed-methods study.

Jian Yang, Wen Jie Zhou, Si Chen Zhou, Dan Luo, Qian Liu, Ai-Ling Wang, Si-Hong Yu, Xiao-Ping Zhu, Xue Yu He, Fen Hu and 2 more

Abstract read
In one paragraph

Article in BMC medical education, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
–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

14 citing papers in PubMed.

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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

12 authors.

Jian Yang *Department of Thoracic Surgery, Zhongnan Hospital of Wuhan University, No. 169 Donghu Road, Wuchang District, Wuhan, 430071, Hubei, China.
Wen Jie Zhou *Department of Cardiology, Renmin Hospital of Wuhan University, No. 238 Jiefang Road, Wuchang District, Wuhan, 430060, Hubei, China.
Si Chen ZhouSchool of Nursing, Wuhan University, No. 115 Donghu Road, Wuchang District, Wuhan, 430071, Hubei, China.
Dan LuoSchool of Nursing, Wuhan University, No. 115 Donghu Road, Wuchang District, Wuhan, 430071, Hubei, China.
Qian LiuSchool of Nursing, Wuhan University, No. 115 Donghu Road, Wuchang District, Wuhan, 430071, Hubei, China.
Ai-Ling WangSchool of Nursing, Wuhan University, No. 115 Donghu Road, Wuchang District, Wuhan, 430071, Hubei, China.
Si-Hong YuSchool of Nursing, Wuhan University, No. 115 Donghu Road, Wuchang District, Wuhan, 430071, Hubei, China.
Xiao-Ping ZhuHospital Quality and Safety Management Office, Zhongnan Hospital of Wuhan University, No. 169 Donghu Road, Wuchang District, Wuhan, 430071, Hubei, China.
Xue Yu HeDepartment of Thoracic Surgery, Zhongnan Hospital of Wuhan University, No. 169 Donghu Road, Wuchang District, Wuhan, 430071, Hubei, China. 1097422706@qq.com.
Fen HuDepartment of Critical Care Medicine, Zhongnan Hospital of Wuhan University, No. 169 Donghu Road, Wuchang District, Wuhan, 430071, Hubei, China. hufen@znhospital.cn.
Bing Xiang YangSchool of Nursing, Wuhan University, No. 115 Donghu Road, Wuchang District, Wuhan, 430071, Hubei, China. 00009312@whu.edu.cn.
Jie ChenFlorida State University College of Nursing, 98 Varsity Way, Tallahassee, FL, 32306, USA. jc22db@fsu.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundVirtual simulation and face-to-face simulation are effective for clinical judgment training. Rare studies have tried to improve clinical judgment ability by applying virtual simulation and face-to-face simulation together. This study aimed to evaluate the effect of an integrated non-immersive virtual simulation and high-fidelity face-to-face simulation program on enhancing nursing students' clinical judgment ability and understanding of nursing students' experiences of the combined simulation.

methodsA sequential exploratory mixed-methods study was conducted in a nursing simulation center of a university in Central China. Third-year nursing students (n = 122) taking clinical training in ICUs were subsequentially assigned to the integrated non-immersive virtual simulation and high-fidelity face-to-face simulation program arm (n = 61) or the face-to-face simulation-only arm (n = 61) according to the order in which they entered in ICU training. Clinical judgment ability was measured by the Lasater Clinical Judgment Rubric (LCJR). Focus group interviews were conducted to gather qualitative data.

resultsStudents in both arms demonstrated significant improvement in clinical judgment ability scores after simulation, and students in the integrated arm reported more improvement than students in the face-to-face simulation-only arm. The qualitative quotes provided a context for the quantitative improvement measured by the LJCR in the integrated arm. Most of the quantitative findings were confirmed by qualitative findings, including the domains and items in the LJCR. The findings verified and favored the effect of the combination of non-immersive virtual simulation and high-fidelity face-to-face simulation integrated program on enhancing nursing students' clinical judgment ability.

conclusionsThe integrated virtual simulation and face-to-face simulation program was feasible and enhanced nursing students' self-reported clinical judgment ability. This integrated non-immersive virtual simulation and high-fidelity face-to-face simulation program may benefit nursing students and newly graduated nurses in the ICU more than face-to-face simulation only.

Indexed as

Education, Nursing, BaccalaureateStudents, NursingChinaClinical ReasoningHumansJudgmentClinical judgmentFocus groupsNursing educationPatient simulationQuasi-experimental studyVirtual reality

Identifiers

PMID38183036
PMCPMC10768231

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LicenceCC BY
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Registered trials

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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.