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Gou Z, Ma Z. Dynamic structure of posttraumatic growth among victims of the 2021 Henan floods: A 6-month, three-wave longitudinal study. Appl Psychol Health Well Being 2023; 15:1372-1390. [PMID: 36882997 DOI: 10.1111/aphw.12442] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2022] [Accepted: 02/20/2023] [Indexed: 03/09/2023]
Abstract
Posttraumatic growth (PTG) following traumatic events is a dynamic and transformational process. However, its dynamic structure is currently unknown. The study aimed to estimate the dynamic structure of PTG at the nuance level based on PTG measurement items using network analysis. A three-wave longitudinal study was conducted from July 20, 2021, to January 30, 2022, among the victims experiencing the 2021 Henan floods. The final sample (n = 297) completed reports of PTG after 0, 3, and 6 months of the disaster. We employed the graphical vector autoregressive model approach to estimate extended network models. Contemporaneous network results revealed strong positive associations between domains of PTG in the same measurement window, especially between new possibilities and personal strength. Moreover, temporal network results-the internal interplays among PTG items across measurement windows-revealed that the domain of relating to others plays a central role in the dynamics of PTG. Although other domains predicted an increase in relating to others, relating to others inhibited the development of other domains, especially new possibilities and personal strength. Our study identifies the culture-specific process of PTG and provides empirical evidence on the explanatory models of PTG and the Janus-Face model of PTG.
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Affiliation(s)
- Zepeng Gou
- Computational Communication Collaboratory, School of Journalism and Communication, Nanjing University, Nanjing, 210023, China
| | - Zhihao Ma
- Computational Communication Collaboratory, School of Journalism and Communication, Nanjing University, Nanjing, 210023, China
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Sun H, Liu H, Ma C, Chen Z, Wei Y, Tang X, Xu L, Hu Y, Xie Y, Chen T, Lu Z, Wang J, Zhang T. Psychiatric emergency department visits during the coronavirus disease-2019 pandemic. Front Psychiatry 2023; 14:1236584. [PMID: 37701092 PMCID: PMC10493317 DOI: 10.3389/fpsyt.2023.1236584] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/07/2023] [Accepted: 08/07/2023] [Indexed: 09/14/2023] Open
Abstract
Background Previous research has demonstrated the negative impact of the coronavirus disease-2019 (COVID-19) pandemic on mental health. Aims To examine changes in the Chinese psychiatric emergency department (PED) visits for mental health crises that occurred during the pandemic. Methods Before and during the COVID-19 pandemic, PED visit counts from the largest psychiatric hospital in China between 2018 and 2020 were investigated. Electronic medical records of 2020 PED visits were extracted during the COVID-19 pandemic period and compared for the same period of 2018 and 2019. Results Overall, PED visits per year increased from 1,767 in 2018 to 2210 (an increase of 25.1%) in 2019 and 2,648 (an increase of 49.9%) in 2020. Compared with 2 years before the epidemic, during the COVID-19 pandemic, the proportion of PED visits among patients with stress disorders, sleep disorders, and anxiety disorders increased significantly. In terms of the distribution of demographic characteristics, age shows a younger trend, while the gender difference is not significant. Conclusion These findings suggest that PED care-seeking increases during the COVID-19 pandemic, highlighting the need to integrate mental health services for patients with stress, sleep, anxiety, and obsessive-compulsive disorders during public health crises.
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Affiliation(s)
- HaiMing Sun
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai Engineering Research Center of Intelligent Psychological Evaluation and Intervention, Shanghai, China
| | - HaiChun Liu
- Department of Automation, Shanghai Jiao Tong University, Shanghai, China
| | - ChunYan Ma
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai Engineering Research Center of Intelligent Psychological Evaluation and Intervention, Shanghai, China
| | - Zheng Chen
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai Engineering Research Center of Intelligent Psychological Evaluation and Intervention, Shanghai, China
| | - YanYan Wei
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai Engineering Research Center of Intelligent Psychological Evaluation and Intervention, Shanghai, China
| | - XiaoChen Tang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai Engineering Research Center of Intelligent Psychological Evaluation and Intervention, Shanghai, China
| | - LiHua Xu
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai Engineering Research Center of Intelligent Psychological Evaluation and Intervention, Shanghai, China
| | - YeGang Hu
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai Engineering Research Center of Intelligent Psychological Evaluation and Intervention, Shanghai, China
| | - YuOu Xie
- The First Clinical Medical College of Nanjing Medical University, Nanjing, China
| | - Tao Chen
- Big Data Research Lab, University of Waterloo, Waterloo, ON, Canada
- Labor and Worklife Program, Harvard University, Cambridge, MA, United States
| | - Zheng Lu
- Department of Psychiatry, Tongji Hospital, Tongji University School of Medicine, Shanghai, China
| | - JiJun Wang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai Engineering Research Center of Intelligent Psychological Evaluation and Intervention, Shanghai, China
- Center for Excellence in Brain Science and Intelligence Technology (CEBSIT), Chinese Academy of Science, Shanghai, China
- Institute of Psychology and Behavioral Science, Shanghai Jiao Tong University, Shanghai, China
| | - TianHong Zhang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai Engineering Research Center of Intelligent Psychological Evaluation and Intervention, Shanghai, China
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Zhang T, Chen Z, Xiao X, Zhou L, Hu Y, Xu L, Wei Y, Tang X, Liu H, Chen T, Wu H, Wu X, Wang J. Increased anxiety and stress-related visits to the Shanghai psychiatric emergency department during the COVID-19 pandemic in 2020 compared to 2018-2019. Front Psychiatry 2023; 14:1146277. [PMID: 37032917 PMCID: PMC10076584 DOI: 10.3389/fpsyt.2023.1146277] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/19/2023] [Accepted: 03/08/2023] [Indexed: 04/11/2023] Open
Abstract
Background The coronavirus disease 2019 (COVID-19) pandemic has had a significant and far-reaching impact on mental health. The psychiatric emergency department (PED) is pivotal in the management of acute and severe mental illnesses, especially anxiety-and stress-related disorders. Aims This study aimed to evaluate whether changes in the frequency or patients' demographics of visiting the PED occurred during the COVID-19 pandemic among individuals with anxiety and stress-related disorders. Methods This cross-sectional study used data on PED visit counts from the largest psychiatric hospital in China between 2018 and 2020 (before and during the COVID-19 pandemic). Data from 2020, representing the COVID-19 pandemic period, were extracted from electronic medical records and compared using descriptive statistics for the same periods in 2018 and 2019. Results The number of PED visits related to anxiety and stress disorders per year increased from 83 in 2018 to 136 (63.9% increase) in 2019 and 239 (188.0% increase) in 2020. Compared to that in 2018 and 2019, the proportion of PED visits in 2020 among patients with anxiety and stress disorders increased significantly. Patients with anxiety-and stress-related disorders during PED visits in 2020 were younger than those in 2018 and 2019 (three-year groups: F = 9.124, df = 2, p < 0.001). Conclusion Despite the epidemic-policy barriers against PED visits, PED care seeking has increased, thereby underscoring the need for crisis prevention services for patients with stress and anxiety disorders.
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Affiliation(s)
- TianHong Zhang
- Shanghai Intelligent Psychological Evaluation and Intervention Engineering Technology Research Center (20DZ2253800), Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai, China
- *Correspondence: TianHong Zhang,
| | - Zheng Chen
- Shanghai Intelligent Psychological Evaluation and Intervention Engineering Technology Research Center (20DZ2253800), Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - XuDong Xiao
- Shanghai Intelligent Psychological Evaluation and Intervention Engineering Technology Research Center (20DZ2253800), Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - LinLin Zhou
- Shanghai Intelligent Psychological Evaluation and Intervention Engineering Technology Research Center (20DZ2253800), Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - YeGang Hu
- Shanghai Intelligent Psychological Evaluation and Intervention Engineering Technology Research Center (20DZ2253800), Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - LiHua Xu
- Shanghai Intelligent Psychological Evaluation and Intervention Engineering Technology Research Center (20DZ2253800), Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - YanYan Wei
- Shanghai Intelligent Psychological Evaluation and Intervention Engineering Technology Research Center (20DZ2253800), Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - XiaoChen Tang
- Shanghai Intelligent Psychological Evaluation and Intervention Engineering Technology Research Center (20DZ2253800), Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - HaiChun Liu
- Department of Automation, Shanghai Jiao Tong University, Shanghai, China
| | - Tao Chen
- Big Data Research Lab, University of Waterloo, Waterloo, ON, Canada
- Labor and Worklife Program, Harvard University, Cambridge, MA, United States
| | - HaiSu Wu
- Shanghai Intelligent Psychological Evaluation and Intervention Engineering Technology Research Center (20DZ2253800), Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai, China
- HaiSu Wu,
| | - XuMing Wu
- Nantong Fourth People's Hospital and Nantong Brain Hospital, NanTong, Jiangsu, China
- XuMing Wu,
| | - JiJun Wang
- Shanghai Intelligent Psychological Evaluation and Intervention Engineering Technology Research Center (20DZ2253800), Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai, China
- Center for Excellence in Brain Science and Intelligence Technology (CEBSIT), Chinese Academy of Science, Shanghai, China
- Brain Science and Technology Research Center, Shanghai Jiao Tong University, Shanghai, China
- JiJun Wang,
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Liu N, Ma Z. Psychiatric reactions among the non-exposed population who viewed disaster-related short videos: Evidence from the 2021 Henan floods. J Psychiatr Res 2022; 150:21-33. [PMID: 35344924 DOI: 10.1016/j.jpsychires.2022.03.036] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/01/2021] [Revised: 02/10/2022] [Accepted: 03/21/2022] [Indexed: 01/13/2023]
Abstract
Media-triggered mental disorders are common when people experience traumatic events. However, few studies have examined the underlying mechanism of how viewing disaster-related short videos triggers psychiatric reactions among non-exposed populations in the context of today's media ecology. Moreover, limited studies have employed psychological network analysis to comprehensively disentangle the associations between diverse forms of media exposure and psychological symptoms. To fill these research gaps, we conducted a survey on a non-exposed population (N = 516) during the 2021 Henan floods to test the effects of short video exposure on its mental status. Short video exposure behaviors were measured under 12 different scenarios, and the participants' mental status (i.e., depression, anxiety, and post-traumatic stress disorder [PTSD]) was measured using the nine-item Patient Health Questionnaire (PHQ-9), seven-item Generalized Anxiety Disorder (GAD-7) scale, and PTSD Check List-Civilian version (PCL-C). We employed both correlation and psychological network analyses to make estimations. The descriptive results revealed that short video exposure behaviors among almost all scenarios were positively associated with the scores of PHQ-9, GAD-7, and PCL-C. The network analysis revealed that both depression and anxiety were associated with the "Support (SVP)" scenario, whereas PTSD was directly linked to the "Help Seeking (SVP)" scenario. Among the three networks, "Help Seeking (SVP)" was the most central among the 12 scenarios of short video exposure. The central symptoms for depression, anxiety, and PTSD were "Concentration," "Relax," and "Reliving Trauma," respectively. The shortest paths between the central short video exposure item and central symptom among the three networks consisted of only two or three steps. This study's findings could assist researchers and policymakers in undertaking novel disaster-related practical activities worldwide.
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Affiliation(s)
- Nan Liu
- Institute of Communication Studies, Communication University of China, Beijing, 100024, China
| | - Zhihao Ma
- Computational Communication Collaboratory, School of Journalism and Communication, Nanjing University, Nanjing, 210023, China.
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