Evidence map›Paper›PMID 39529901›Full record

ArticleFrontiers in psychiatry2024

Interconnected mental health symptoms: network analysis of depression, anxiety, stress, and burnout among psychiatric nurses in the context of the COVID-19 pandemic.

Rui Tao, Song Wang, Qingfang Lu, Yunxiao Liu, Lei Xia, Daming Mo, Feng Geng, Tingfang Liu, Yuanli Liu, Feng Jiang and 2 more

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Article in Frontiers in psychiatry, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

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8citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

12 authors.

Rui Tao *Department of Psychiatry, Chaohu Hospital of Anhui Medical University, Hefei, China.
Song Wang *Department of Psychiatry, Chaohu Hospital of Anhui Medical University, Hefei, China.
Qingfang LuDepartment of Psychiatry and Psychology, Taihe Hospital of Traditional Chinese Medicine, Fuyang, China.
Yunxiao LiuDepartment of Psychiatry, Chaohu Hospital of Anhui Medical University, Hefei, China.
Lei XiaDepartment of Psychiatry, Chaohu Hospital of Anhui Medical University, Hefei, China.
Daming MoDepartment of Substance-Related Disorders, Hefei Fourth People's Hospital, Hefei, China.
Feng GengDepartment of Psychiatry, Second Affiliated Hospital of Anhui Medical University, Hefei, China.
Tingfang LiuResearch Department, School of Health Policy and Management, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Yuanli LiuResearch Department, School of Health Policy and Management, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Feng JiangResearch Department, School of International and Public Affairs, Shanghai Jiao Tong University, Shanghai, China.
Huan-Zhong LiuDepartment of Psychiatry, Chaohu Hospital of Anhui Medical University, Hefei, China.
Yi-Lang TangAddiction Psychiatry Fellowship Program, Department of Psychiatry and Behavioral Sciences, Emory University, Atlanta, GA, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Mental health symptoms such as anxiety, depression, stress, and burnout are common among healthcare workers. However, the interconnections among them remain under-explored. This study aimed to address the interrelationships among these symptoms in psychiatric nurses. Methods: We conducted a nationwide survey in the early stage of the COVID-19 pandemic (January to March 2021) to investigate the interconnectedness of depression, anxiety, stress, and burnout among psychiatric nurses. Using network analysis, we identified central symptoms, important bridge symptoms, and the correlations among these central symptoms. Results: Of the 9,224 psychiatric nurses (79.2% female) included in the statistical analyses, 27.6% reported clinically significant depression, 31.2% anxiety, 14.5% stress, and 23.8% burnout. Network analysis revealed that stress had the highest expected influence (EI) value (0.920) and the highest strength among all nodes. The node for depression scored the highest in both closeness and betweenness. Emotional exhaustion (EE) had the highest bridge expected influence (BEI) of 0.340, with the strongest intergroup association between EE and depression. No significant differences were found in gender or frontline work experience (all p > 0.05). Conclusions: Burnout, depression, anxiety, and stress are relatively common among psychiatric nurses in the context of the COVID-19 pandemic. While anxiety was the most prevalent, stress emerged as the core symptom, and depression as an important bridging node. Interventions targeting the core symptoms and bridging nodes may improve the mental health of psychiatric nurses.

Indexed as

anxietyburnoutdepressionnetwork analysispsychiatric nursesstress

Identifiers

PMID39529901
PMCPMC11550990

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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.