Evidence map›Paper›PMID 40264108›Full record

ArticleBMC nursing2025

Preliminary validation of the Suicide Management Competency Scale in a Chinese nurse population: a cross-sectional study.

Yuxiu Liu, Wei Wu, Shuzhen Li, Xin Wang, Lan Zhang

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Article in BMC nursing, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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2 citing papers in PubMed.

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5 · Who and what money

Authors and funding

5 authors.

Yuxiu LiuDepartment of Nursing, First Affiliated Hospital of Jinzhou Medical University, Liaoning, Jinzhou, China.
Wei WuHeze Home Economics College, Heze, China.
Shuzhen LiHeze Home Economics College, Heze, China.
Xin WangDepartment of Nursing, Huaian Hospital of Huaian City, Huaian, Jiangsu, 223200, China.
Lan ZhangDepartment of Nursing, First Affiliated Hospital of Jinzhou Medical University, Liaoning, Jinzhou, China. zhang800519@126.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSuicide represents a significant public health concern at the global level and is a major area of concern for mental health professionals. Nurses are positioned to identify and manage individuals at risk of suicide or suicidal ideation. It is widely acknowledged that ensuring nurses are adequately trained to assess and manage suicidal patients is of paramount importance in the prevention of suicide. The objective of this study was to examine the reliability and structural validity of the Suicide Management Competency Scale (SMCS) in clinical nurses population.

methodsA total of 452 clinical nurses in a third-class hospital in Liaoning Province were selected using convenience sampling. The survey was conducted using the general demographic questionnaire and the Suicide Management Competency Scale (SMCS). The reliability and acceptability of the scale were assessed by checking the consistency of the scale part, the split-half reliability coefficient, and the correlation between each item and the score of the total scale. Confirmatory factor analysis, convergent validity and discriminant validity were used to determine the dimensional structure and validity of the scale.

resultsThe internal consistency of the scale, as indicated by the Cronbach's α coefficient, was 0.902. The split-half reliability coefficient was 0.771. The results of the confirmatory factor analysis were as follows: CMIN/DF = 2.609, RMSEA = 0.060, RMR = 0.040, CFI = 0.957, GFI = 0.930, NFI = 0.933, TLI = 0.949, IFI = 0.958. All of the model fitting indexes were within the acceptable range. The average variance extracted (AVE) of the three subscales ranged from 0.500 to 0.583. The combined reliability values (CR) range from 0.848 to 0.888, indicating that the SMCS scale exhibits good convergence validity. The analysis of the correlation coefficient between the subscale and the total scale revealed that the AVE square root value of each subscale is between 0.707 and 0.763, which is greater than the correlation coefficient between the two indicators. This indicates that there are significant differences between the subscales of the SMCS, that the internal structure of the questionnaire is highly differentiated, and that the discrimination validity is good.

conclusionTo the best of our knowledge, this is the inaugural study to report the utilisation of the Suicide Management Competency Scale (SMCS) in the context of clinical nursing. The findings offer preliminary support for the utilisation of the SMCS in clinical nurses. In the future, nursing managers will be able to effectively evaluate clinical nurses' ability to manage and prevent suicide, as well as train nurses in this area, with the ultimate goal of saving as many lives as possible.

Indexed as

CompetenceNursingReliabilitySuicideValidity

Identifiers

PMID40264108
PMCPMC12016330

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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.