Hope During the COVID-19 Epidemic Decreased Anxiety and Depression Symptoms Mediated by Perceived Stress: Coping Style Differences Among Patients with COVID-19.

OBJECTIVE: This study aimed to investigate whether perceived stress mediated the relationship between hope and anxiety/depression symptoms among patients with COVID-19 during the epidemic. In addition, the potential moderating effect of coping styles was examined. METHODS: From February 26 to March 10, 2020, patients with COVID-19 were asked to complete a questionnaire online, which included demographic characteristics, as well as the SCL-90-Anxiety, SCL-90-Depression, Chinese Perceived Stress Scale (CPSS), Herth Hope Index (HHI), and Trait Coping Style Questionnaire (TCSQ). Hierarchical linear regression was performed to explore independent factors of anxiety/depression. A multi-group structural equation modeling with the collected data from patients in the Negative Coping style (NC) group and Positive Coping style (PC) group was used to test the hypothesized mechanism. RESULTS: In total, 382 valid questionnaires of patients were obtained, including 96 from NC patients and 286 from PC patients. In the hierarchical linear regression, hope and perceived stress were independent risk factors for both anxiety and depression in the total sample and PC group. However, hope was not independently related to anxiety/depression in the NC group. As hypothesized, the hope of patients had significant and negative indirect effects on both anxiety and depression that were mediated by perceived stress, However, the direct effect from stress on anxiety and depression was stronger for NC patients than for PC patients. Besides, hope had significant direct effects on anxiety/depression in PC patients, but not in NC patients. CONCLUSION: During the COVID-19 epidemic, perceived stress could mediate the relationship between hope and anxiety/depression symptoms among COVID-19 patients, with coping style moderating this cultivation process.

Major Impact of Coping Styles on Anxiety and Depression Symptoms in Healthcare Workers During the Outbreak of COVID-19

Background In the early days of COVID-19 outbreak, the normally orderly health system was severely challenged by large numbers of feverish patients and shortage of healthcare workers. The outbreak played a harmful role in the mental health of these healthcare workers. Objective We aim to assess the prevalence of moderate or severe anxiety and depression symptoms (ADSs) of healthcare workers in different regions during COVID-19 disaster and identify the potential risk factors. Methods We did a cross-sectional study on ADS of healthcare workers in epicenter-Hubei province and regions in lower epidemic-other provinces by questionnaire online. The data of ADS, the demographic characteristics, occupational exposure, physical condition, family situation, and coping styles were collected and analyzed. Results A total of 24.68% of the respondents had experienced moderate or severe ADS. Moderate or severe ADSs were in a higher prevalence in Hubei (32.39%) than other provinces (18.22%). Suspicious symptoms on their own and in family members were independent risk factors of moderate or severe ADS of all health workers. Working on the frontline was the independent risk factor for participants in Hubei province, whereas quarantine was the independent risk factor for those in other provinces. Moreover, among all participants, those with negative coping style were more than four times more likely to have moderate or severe ADS than those with positive coping style. Conclusion Moderate or severe ADSs were in a higher prevalence in healthcare workers of Hubei province during COVID-19 outbreak. The coping style may have major impact on ADS in such situation.

Alternation of the Autonomic Nervous System Is Associated With Pulmonary Sequelae in Patients With COVID-19 After Six Months of Discharge.

Previous studies suggest that autonomic dysfunction is associated with disease severity in acute phase in patients with coronavirus disease 2019 (COVID-19). However, the association between autonomic dysfunction and pulmonary sequelae in patients with COVID-19 is unknown. We conducted a prospective study to investigate the association between autonomic dysfunction and pulmonary sequelae in patients with COVID-19 discharged for 6 months. We included 40 eligible participants and collected the following indicators: heart rate variability (HRV), pulmonary function tests (PFTs), lung X-ray computed tomography (CT), routine blood parameters, liver function parameters, and lymphocyte subsets. We found that at 6 months post-discharge, HRV still had a tight correlation with pulmonary fibrosis. There was a significant difference in HRV between patients with and without diffusion dysfunction, but HRV did not differ between patients with or without ventilatory dysfunction. Diffusion dysfunction and pulmonary fibrosis were tightly associated, and HRV index changes in patients with diffusion dysfunction had the same trend as that of patients with pulmonary fibrosis. They had a lower standard deviation of NN intervals (SDNN), the standard deviation of the average NN intervals (SDANN), and the triangular index, but a higher ratio between LF and HF power (LF/HF). In addition, WBC, neutrophils, and CD4/CD8 were correlated with pulmonary fibrosis and HRV. We concluded that autonomic dysfunction is closely associated with pulmonary fibrosis and diffusion dysfunction, and immune mechanisms may potentially contribute to this process.

Reliable and Interpretable Mortality Prediction With Strong Foresight in COVID-19 Patients: An International Study From China and Germany.

Cohort-independent robust mortality prediction model in patients with COVID-19 infection is not yet established. To build up a reliable, interpretable mortality prediction model with strong foresight, we have performed an international, bi-institutional study from China (Wuhan cohort, collected from January to March) and Germany (Würzburg cohort, collected from March to September). A Random Forest-based machine learning approach was applied to 1,352 patients from the Wuhan cohort, generating a mortality prediction model based on their clinical features. The results showed that five clinical features at admission, including lymphocyte (%), neutrophil count, C-reactive protein, lactate dehydrogenase, and α-hydroxybutyrate dehydrogenase, could be used for mortality prediction of COVID-19 patients with more than 91% accuracy and 99% AUC. Additionally, the time-series analysis revealed that the predictive model based on these clinical features is very robust over time when patients are in the hospital, indicating the strong association of these five clinical features with the progression of treatment as well. Moreover, for different preexisting diseases, this model also demonstrated high predictive power. Finally, the mortality prediction model has been applied to the independent Würzburg cohort, resulting in high prediction accuracy (with above 90% accuracy and 85% AUC) as well, indicating the robustness of the model in different cohorts. In summary, this study has established the mortality prediction model that allowed early classification of COVID-19 patients, not only at admission but also along the treatment timeline, not only cohort-independent but also highly interpretable. This model represents a valuable tool for triaging and optimizing the resources in COVID-19 patients.

COVID-19 Outbreak Can Change the Job Burnout in Health Care Professionals.

Background: The outbreak of COVID-19 in China was a sudden bio-disaster, which may bring a negative impact on the job burnout of health care professionals (HCPs). Objective: We aim to find out the association factors, especially those closely related to this outbreak, of job burnout in Chinese HCPs. Method: The cross-sectional survey about HCPs' job burnout based on a network platform was conducted in high and low infection regions during the COVID-19 outbreak in China. The demographic characteristics, medical-work-related factors, risk of getting infected due to occupational exposure, and family factors were collected by the self-reported questionnaire. The Chinese version of the Maslach Burnout Inventory (CMBI) and the Trait Coping Style Questionnaire (TCSQ) were employed in this study to evaluate the job burnout and coping style, respectively. Furthermore, statistical analysis was done to find out the associated factors of job burnout. Results: We collected 880 complete questionnaires from doctors and nurses from February 9, 2020 to February 11, 2020. In this study, the positive rates of three dimensions of burnout (emotional exhaustion, depersonalization, and reduced personal accomplishment) and overall burnout were 9.09, 50.57, 56.59, and 73.98%, respectively. After the statistical analysis, we found that several factors can independently affect the dimensions. Working in the high infection region and negative coping styles can affect all three dimensions at once. More night shift quantity and having symptoms could increase emotional exhaustion and depersonalization, while higher work intensity and senior title could increase emotional exhaustion and reduce personal accomplishment, respectively. Conclusion: The rate of moderate and severe burnout had increased due to the outbreak. More attention should be paid to burnout in HCPs, especially those with negative coping. There were some potential ways to reduce burnout, such as reducing their workload and providing better protection from the virus.

Risk factors for depression and anxiety in healthcare workers deployed during the COVID-19 outbreak in China.

PURPOSE: This study was conducted to evaluate the status of depression and anxiety of healthcare workers and to explore the risk factors during the outbreak of COVID-19 in China. METHODS: A cross-sectional study was designed using convenience sampling to obtain a sample of healthcare workers. A structured questionnaire was designed to collect the information of the basic characteristics, workload, and the health condition. Burnout, coping style, anxiety, and depression were measured by specific scales. Multiple logistic regression model was performed to explore the risk factors of anxiety or depression. RESULTS: There were 902 questionnaires received between February 9, 2020 and February 11, 2020. The proportion of healthcare workers with symptoms of moderate/severe anxiety and moderate/severe depression were 16.63% and 18.29%, respectively. There were 24.50% healthcare workers experiencing moderate/severe anxiety and depression at the same time. The increased workload, respiratory symptoms, digestive symptoms, having done specific test(s) related to COVID-19, having family member needs to be taken care of, negative coping style, and job burnout were the independent risk factors of anxiety. Furthermore, the increased workload, respiratory symptoms, digestive symptoms, having done specific test(s) related to COVID-19, negative coping style, and job burnout were the independent risk factors of depression. CONCLUSION: More attention should be paid to the mental health of frontline healthcare workers at the outbreak of COVID-19 in China. Taking steps to reduce the intensity of the work and burnout will be effective to stabilize the mental state of them.