Evidence map›Paper›PMID 42032700›Full record

ArticleBMC nursing2026

Nurse core competency cultivation using the checklist-based Kirkpatrick model under the "cross-departmental bed-sharing" mode.

Miyan Wang, Xiaohong Chen, Xiaochun He, Jianying Shang, Yuwei Yang, Zhoujian Yang, Wensha Cao, Yanli Bi, Shuai Xie, Huilin He and 1 more

Abstract read
In one paragraph

Article in BMC nursing, 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

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

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

11 authors.

Miyan Wang *School of Medicine, Mianyang Central Hospital, University of Electronic Science and Technology of China, Mianyang, 621000, PR China.
Xiaohong Chen *School of Medicine, Mianyang Central Hospital, University of Electronic Science and Technology of China, Mianyang, 621000, PR China.
Xiaochun He *School of Medicine, Mianyang Central Hospital, University of Electronic Science and Technology of China, Mianyang, 621000, PR China.
Jianying ShangSchool of Medicine, Mianyang Central Hospital, University of Electronic Science and Technology of China, Mianyang, 621000, PR China. 826257964@qq.com.
Yuwei YangSchool of Medicine, Mianyang Central Hospital, University of Electronic Science and Technology of China, Mianyang, 621000, PR China. yyw318@sc-mch.cn.
Zhoujian YangSchool of Medicine, Mianyang Central Hospital, University of Electronic Science and Technology of China, Mianyang, 621000, PR China.
Wensha CaoSchool of Medicine, Mianyang Central Hospital, University of Electronic Science and Technology of China, Mianyang, 621000, PR China.
Yanli BiSchool of Medicine, Mianyang Central Hospital, University of Electronic Science and Technology of China, Mianyang, 621000, PR China.
Shuai XieSchool of Medicine, Mianyang Central Hospital, University of Electronic Science and Technology of China, Mianyang, 621000, PR China.
Huilin HeSchool of Medicine, Mianyang Central Hospital, University of Electronic Science and Technology of China, Mianyang, 621000, PR China.
Guoxiu DengSchool of Medicine, Mianyang Central Hospital, University of Electronic Science and Technology of China, Mianyang, 621000, PR China.

Funding

Health Humanities Research Center of Zigong Federation of Social Sciences JKRWY25-22Hospital Management and Development Research Center of Sichuan Province SCYG2025-44Southwest Medical University JDJG2024052
6 · The paper itself

Abstract

BACKGROUND AND

objectiveThe concept of cross-departmental bed-sharing has been introduced to manage the sudden influx of some specialized patients, but concerns remain about whether professional care can be effectively applied. This study aims to evaluate the training effect of the Checklist-Based Kirkpatrick model program on the core competencies of nurses in the “cross-departmental bed-sharing” context.

methodsAll 76 surgical frontline nurses were included in this study, who were involved in the care of “cross-departmental bed-sharing” patients between January 2024 and June 2024. Based on their current implementation status of cross-departmental nursing, a checklist-based Kirkpatrick model core competency cultivation system was developed to support a six-month training program. The single-group pre-post study method was adopted to compare their scores of the cross-departmental theoretical test, the Competency Inventory for Registered Nurse (CIRN), and the Professional Identity Scale (PIS) before and after the training.

resultsOur checklist-based Kirkpatrick model core competency cultivation system could effectively improve the scores of cross-departmental theoretical tests (t = 24.753, P < 0.001), CIRN and its dimensions (t = 3.873 ~ 45.856, all P < 0.001), as well as PIS and its dimensions (t = 6.054 ~ 25.608, all P < 0.001). Both enter and stepwise analysis revealed that improved professional identity of nurses was positively correlated with increased scores of cross-departmental theoretical test (rpartial=0.316 and 0.340, P = 0.010 and 0.004), clinical care (rpartial=0.263 and 0.262, P = 0.034 and 0.026), teaching-coaching (rpartial=0.407 and 0.474, both P < 0.001), interpersonal relationships (rpartial=0.300 and 0.343, P = 0.015 and 0.003), and critical thinking & research aptitude (rpartial=0.433 and 0.426, both P < 0.001).

conclusionThis single-center study may offer innovative practical guidance and evaluation methods for fostering nurses’ core competencies in cross-departmental care, which holds potential value in promoting enhanced nursing quality across the hospital under the“cross-departmental bed-sharing” mode.

Indexed as

ChecklistHomogenized nursingInterdisciplinary admissionsKirkpatrick's four-level modelOn-the-job trainingProfessional competence

Identifiers

PMID42032700
PMCPMC13244612

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.