Evidence map›Paper›PMID 39833790›Full record

ArticleBMC nursing2025

Impact of the five-pattern personality traits of traditional Chinese medicine on workplace violence and depression among nurses.

ZhiHui Gu, ChenXin Yang, MengYao Li

Abstract read
In one paragraph

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 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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4 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

ZhiHui GuDepartment of Social Medicine, School of Health Management, China Medical University, Shenyang North New District, No. 77 Puhe Road, Shenyang, Liaoning, 110122, People's Republic of China.
ChenXin YangDepartment of Social Medicine, School of Health Management, China Medical University, Shenyang North New District, No. 77 Puhe Road, Shenyang, Liaoning, 110122, People's Republic of China.
MengYao LiDepartment of Social Medicine, School of Health Management, China Medical University, Shenyang North New District, No. 77 Puhe Road, Shenyang, Liaoning, 110122, People's Republic of China. myli@cmu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDepression seriously damage the health of nurses. It is not conducive to the provision of medical services and hospital management. Meanwhile, nurses are a highly vulnerable group to workplace violence (WPV), increasing the risk of depression. Nurses with different personalities may have various views and feelings towards WPV, and their impact on depression may also vary. This study aims to reveal the impact of the five-pattern personality traits of traditional Chinese medicine (TCM) on WPV and depression among nurses, providing a new perspective for managers to implement psychological interventions.

methodsA cross-sectional study was conducted. 2,788 valid questionnaires nationwide were collected based on Wenjuanxing from June to July 2024. We used Patient Health Questionnaire Depression Scale-9 item, The five- pattern Personality Traits of TCM Scale, and Workplace Violence Scale. We used latent class analysis, structural equation modeling, and simple slope analysis to analyze depression classes, mediating effects, and moderation effects, respectively.

resultsDepression is classified into three types: "Good mental health group" (34.2%), "Moderate depression group" (23.0%), and "Severe depression group" (42.8%). "Taiyang", "Shaoyang", and "Balance of Yin-Yang" personalities alleviate nurses' feelings of WPV, thereby reducing the impact of WPV on depression. The values of mediating effect are -0.402, -0.393, and -0.426, respectively (P < 0.05). "Taiyin" personality exacerbate nurses' perception of WPV, thereby increasing the impact of WPV on depression. The value of mediating effect is 0.418 (P < 0.05). "Taiyang" and "Shaoyang" personalities reduce the impact of WPV on depression of nurses, and the effect become more significant as the scores increase. The values of moderating effect are 0.033 and -0.0563 respectively (P < 0.05). "Taiyin" and "Shaoyin" personalities increase the impact of WPV on depression, and the effect become more significant as the scores increase. The values of moderating effect are -0.0444 and -0.0220 respectively (P < 0.05).

conclusionsThe prevalence of depression and WPV among Chinese nurses is serious. Excellent personality effectively improve the relationship between WPV and depression. Nursing managers should arrange suitable positions for nurses based on their different personality traits. At the same time, it is necessary to actively cultivate excellent personality traits in nurses to reduce the frequency of WPV and improve their mental health.

Indexed as

DepressionMediating effectModerating effectNurseThe five-pattern personality traits of traditional Chinese medicineWorkplace violence

Identifiers

PMID39833790
PMCPMC11749299

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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.