Interconnected mental health symptoms: network analysis of depression, anxiety, stress, and burnout among psychiatric nurses in the context of the COVID-19 pandemic
BackgroundMental 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.MethodsWe conducted a n...
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Frontiers Media S.A.
2024-10-01
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| Series: | Frontiers in Psychiatry |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fpsyt.2024.1485726/full |
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| author | Rui Tao Rui Tao Rui Tao Song Wang Song Wang Song Wang Qingfang Lu Yunxiao Liu Yunxiao Liu Yunxiao Liu Lei Xia Lei Xia Lei Xia Daming Mo Feng Geng Tingfang Liu Yuanli Liu Feng Jiang Feng Jiang Feng Jiang Feng Jiang Huan-Zhong Liu Huan-Zhong Liu Huan-Zhong Liu Huan-Zhong Liu Yi-lang Tang Yi-lang Tang |
| author_facet | Rui Tao Rui Tao Rui Tao Song Wang Song Wang Song Wang Qingfang Lu Yunxiao Liu Yunxiao Liu Yunxiao Liu Lei Xia Lei Xia Lei Xia Daming Mo Feng Geng Tingfang Liu Yuanli Liu Feng Jiang Feng Jiang Feng Jiang Feng Jiang Huan-Zhong Liu Huan-Zhong Liu Huan-Zhong Liu Huan-Zhong Liu Yi-lang Tang Yi-lang Tang |
| author_sort | Rui Tao |
| collection | DOAJ |
| description | BackgroundMental 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.MethodsWe 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.ResultsOf 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).ConclusionsBurnout, 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. |
| format | Article |
| id | doaj-art-6d0fbeadaf524019bfb558c4f6f29a74 |
| institution | OA Journals |
| issn | 1664-0640 |
| language | English |
| publishDate | 2024-10-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Psychiatry |
| spelling | doaj-art-6d0fbeadaf524019bfb558c4f6f29a742025-08-20T02:11:16ZengFrontiers Media S.A.Frontiers in Psychiatry1664-06402024-10-011510.3389/fpsyt.2024.14857261485726Interconnected mental health symptoms: network analysis of depression, anxiety, stress, and burnout among psychiatric nurses in the context of the COVID-19 pandemicRui Tao0Rui Tao1Rui Tao2Song Wang3Song Wang4Song Wang5Qingfang Lu6Yunxiao Liu7Yunxiao Liu8Yunxiao Liu9Lei Xia10Lei Xia11Lei Xia12Daming Mo13Feng Geng14Tingfang Liu15Yuanli Liu16Feng Jiang17Feng Jiang18Feng Jiang19Feng Jiang20Huan-Zhong Liu21Huan-Zhong Liu22Huan-Zhong Liu23Huan-Zhong Liu24Yi-lang Tang25Yi-lang Tang26Department of Psychiatry, Chaohu Hospital of Anhui Medical University, Hefei, ChinaDepartment of Psychiatry, School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, ChinaDepartment of Psychiatry, Anhui Psychiatric Center, Hefei, ChinaDepartment of Psychiatry, Chaohu Hospital of Anhui Medical University, Hefei, ChinaDepartment of Psychiatry, School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, ChinaDepartment of Psychiatry, Anhui Psychiatric Center, Hefei, ChinaDepartment of Psychiatry and Psychology, Taihe Hospital of Traditional Chinese Medicine, Fuyang, ChinaDepartment of Psychiatry, Chaohu Hospital of Anhui Medical University, Hefei, ChinaDepartment of Psychiatry, School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, ChinaDepartment of Psychiatry, Anhui Psychiatric Center, Hefei, ChinaDepartment of Psychiatry, Chaohu Hospital of Anhui Medical University, Hefei, ChinaDepartment of Psychiatry, School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, ChinaDepartment of Psychiatry, Anhui Psychiatric Center, Hefei, ChinaDepartment of Substance-Related Disorders, Hefei Fourth People’s Hospital, Hefei, ChinaDepartment of Psychiatry, Second Affiliated Hospital of Anhui Medical University, Hefei, ChinaResearch Department, School of Health Policy and Management, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, ChinaResearch Department, School of Health Policy and Management, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, ChinaResearch Department, School of International and Public Affairs, Shanghai Jiao Tong University, Shanghai, ChinaResearch Department, Institute of Healthy Yangtze River Delta, Shanghai Jiao Tong University, Shanghai, China0Institute of Health Policy, Shanghai Jiao Tong University, Shanghai, China1Institute of Grand Health, Wenzhou Medical University, Wenzhou, ChinaDepartment of Psychiatry, Chaohu Hospital of Anhui Medical University, Hefei, ChinaDepartment of Psychiatry, School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, ChinaDepartment of Psychiatry, Anhui Psychiatric Center, Hefei, China2Department of Psychiatry, Huizhou Second People’s Hospital, Huizhou, China3Addiction Psychiatry Fellowship Program, Department of Psychiatry and Behavioral Sciences, Emory University, Atlanta, GA, United States4Mental Health Service Line, Joseph Maxwell Cleland Atlanta VA Medical Center, Decatur, GA, United StatesBackgroundMental 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.MethodsWe 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.ResultsOf 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).ConclusionsBurnout, 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.https://www.frontiersin.org/articles/10.3389/fpsyt.2024.1485726/fullnetwork analysisburnoutstressdepressionanxietypsychiatric nurses |
| spellingShingle | Rui Tao Rui Tao Rui Tao Song Wang Song Wang Song Wang Qingfang Lu Yunxiao Liu Yunxiao Liu Yunxiao Liu Lei Xia Lei Xia Lei Xia Daming Mo Feng Geng Tingfang Liu Yuanli Liu Feng Jiang Feng Jiang Feng Jiang Feng Jiang Huan-Zhong Liu Huan-Zhong Liu Huan-Zhong Liu Huan-Zhong Liu Yi-lang Tang Yi-lang Tang Interconnected mental health symptoms: network analysis of depression, anxiety, stress, and burnout among psychiatric nurses in the context of the COVID-19 pandemic Frontiers in Psychiatry network analysis burnout stress depression anxiety psychiatric nurses |
| title | Interconnected mental health symptoms: network analysis of depression, anxiety, stress, and burnout among psychiatric nurses in the context of the COVID-19 pandemic |
| title_full | Interconnected mental health symptoms: network analysis of depression, anxiety, stress, and burnout among psychiatric nurses in the context of the COVID-19 pandemic |
| title_fullStr | Interconnected mental health symptoms: network analysis of depression, anxiety, stress, and burnout among psychiatric nurses in the context of the COVID-19 pandemic |
| title_full_unstemmed | Interconnected mental health symptoms: network analysis of depression, anxiety, stress, and burnout among psychiatric nurses in the context of the COVID-19 pandemic |
| title_short | Interconnected mental health symptoms: network analysis of depression, anxiety, stress, and burnout among psychiatric nurses in the context of the COVID-19 pandemic |
| title_sort | interconnected mental health symptoms network analysis of depression anxiety stress and burnout among psychiatric nurses in the context of the covid 19 pandemic |
| topic | network analysis burnout stress depression anxiety psychiatric nurses |
| url | https://www.frontiersin.org/articles/10.3389/fpsyt.2024.1485726/full |
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