Anxiety, depression and post-traumatic stress disorder and related factors among Chinese population during the COVID-19 pandemic: A cross-sectional study.

The sudden outbreak of coronavirus disease 2019 (COVID-19) has deep and wide negative mental impacts on the public, and studies on the impact of COVID-19 on social and mental well-being are necessary. This study aimed to evaluate mental distress, including anxiety, depression, and post-traumatic stress disorder (PTSD), and its related risk factors in Chinese adults in the early stages of the COVID-19 pandemic. This study used a large-scale cross-sectional design. A total of 2067 adult participants completed the online survey via REDcap from 1st to 15th of March 2020 during the COVID-19 outbreak in China. Anxiety, depression, PTSD, and related risk factors, including self-efficacy, coping style, and social support, were measured using valid and reliable instruments. The data were analyzed using multiple linear regression. We found that 201 (9.7%) participants reported moderate-to-severe anxiety, 669 (33.8%) reported depression, and 368 (17.8%) reported symptoms of PTSD. Self-efficacy, coping style, and social support significantly affected anxiety, depression, and PTSD symptoms. Participants' sociodemographic characteristics, COVID-19 pandemic-related factors, low self-efficacy, low social support, and negative coping were predictors of mental distress during the COVID-19 pandemic. Our study will help healthcare professionals carry out early predictions and identification of high-risk groups and provide appropriate interventions to target groups during public health emergencies that plague the world.

Anxiety, depression and post-traumatic stress disorder and related factors among Chinese population during the COVID-19 pandemic: A cross-sectional study

The sudden outbreak of coronavirus disease 2019 (COVID-19) has deep and wide negative mental impacts on the public, and studies on the impact of COVID-19 on social and mental well-being are necessary. This study aimed to evaluate mental distress, including anxiety, depression, and post-traumatic stress disorder (PTSD), and its related risk factors in Chinese adults in the early stages of the COVID-19 pandemic. This study used a large-scale cross-sectional design. A total of 2067 adult participants completed the online survey via REDcap from 1st to 15th of March 2020 during the COVID-19 outbreak in China. Anxiety, depression, PTSD, and related risk factors, including self-efficacy, coping style, and social support, were measured using valid and reliable instruments. The data were analyzed using multiple linear regression. We found that 201 (9.7%) participants reported moderate-to-severe anxiety, 669 (33.8%) reported depression, and 368 (17.8%) reported symptoms of PTSD. Self-efficacy, coping style, and social support significantly affected anxiety, depression, and PTSD symptoms. Participants' sociodemographic characteristics, COVID-19 pandemic-related factors, low self-efficacy, low social support, and negative coping were predictors of mental distress during the COVID-19 pandemic. Our study will help healthcare professionals carry out early predictions and identification of high-risk groups and provide appropriate interventions to target groups during public health emergencies that plague the world.

A Machine Learning-Based Risk Prediction Model for Post-Traumatic Stress Disorder during the COVID-19 Pandemic.

Background and Objectives: The COVID-19 pandemic has caused global public panic, leading to severe mental illnesses, such as post-traumatic stress disorder (PTSD). This study aimed to establish a risk prediction model of PTSD based on a machine learning algorithm to provide a basis for the extensive assessment and prediction of the PTSD risk status in adults during a pandemic. Materials and Methods: Model indexes were screened based on the cognitive-phenomenological-transactional (CPT) theoretical model. During the study period (1 March to 15 March 2020), 2067 Chinese residents were recruited using Research Electronic Data Capture (REDCap). Socio-demographic characteristics, PTSD, depression, anxiety, social support, general self-efficacy, coping style, and other indicators were collected in order to establish a neural network model to predict and evaluate the risk of PTSD. Results: The research findings showed that 368 of the 2067 participants (17.8%) developed PTSD. The model correctly predicted 90.0% (262) of the outcomes. Receiver operating characteristic (ROC) curves and their associated area under the ROC curve (AUC) values suggested that the prediction model possessed an accurate discrimination ability. In addition, depression, anxiety, age, coping style, whether the participants had seen a doctor during the COVID-19 quarantine period, and self-efficacy were important indexes. Conclusions: The high prediction accuracy of the model, constructed based on a machine learning algorithm, indicates its applicability in screening the public mental health status during the COVID-19 pandemic quickly and effectively. This model could also predict and identify high-risk groups early to prevent the worsening of PTSD symptoms.

A cross-sectional examination of the relationship between nurses' experiences of skin lesions and anxiety and depression during the COVID-19 pandemic: Exploring the mediating role of fear and resilience.

AIM: To explore the mediating role of fear and resilience on the relationship between clinical nurses' reporting of skin lesions and their anxiety and depression during the coronavirus disease 2019 (COVID-19) pandemic. BACKGROUND: Prolonged personal protective equipment wearing may cause severe skin lesions among clinical nurses. The possible relationship between clinical nurses' reporting of skin lesions and their anxiety and depression remains unknown. Moreover, little is known about what factors could mediate such a relationship. METHODS: This is a cross-sectional online survey. CHERRIES was used to report results. RESULTS: Of 2014 participants, 94.8% (n = 1910) reported skin lesions. Skin lesions were positively related to anxiety (p < .001, ß = .228, SE = .099) and depression (p < .001, ß = .187, SE = .093). Fear activated while resilience buffered the relationship between clinical nurses' reporting of skin lesions and anxiety and between skin lesions and depression. CONCLUSION: Reduced fear and enhanced resilience level were related to decreased levels of anxiety and depression among clinical nurses. IMPLICATIONS FOR NURSING MANAGEMENT: Nurse managers should evaluate the occurrence and severity of clinical nurses' skin lesions, arrange reasonable working duration to relieve skin lesions, provide appropriate psychological support to reduce clinical nurses' fear and implement various strategies to enhance their resilience, thereby decreasing their anxiety and depression. CLINICAL TRIAL REGISTRATION NUMBER: ChiCTR2000030290.

Frontline nurses' willingness to work during the COVID-19 pandemic: A mixed-methods study.

AIM: Frontline nurses' willingness to work has significant implications for maintaining workforce stability and quality of care during the COVID-19 pandemic; however, few studies have investigated their willingness and the corresponding reasons. This study aims to examine frontline nurses' willingness to work, identify its predictors and explore its corresponding reasons. DESIGN: A mixed-methods design was conducted. METHODS: Based on a multilevel behavioural-diagnostic model, a questionnaire survey was used to collect quantitative and qualitative data concurrently from 13 February to 24 February 2020 to explore frontline nurses' willingness to work and the corresponding reasons in two hospitals in Wuhan, China. One was a designated hospital which only received COVID-19 patients, and the other was built up temporarily for COVID-19 patients. RESULTS: Of the 2014 participants, most (n = 1950, 96.8%) indicated their willingness to work, and a few (n = 64, 3.2%) expressed their unwillingness. Binary logistic regression analysis identified five predictors of participants' willingness to work, including monthly family income, average working hours per shift, belief in their colleagues' preparedness, belief in their hospitals' preparedness and levels of depression. These indicators explained 27% of the variance (p < .05). Frontline nurses' willingness to work mainly arose from professional commitment, patriotism and faith, while unwillingness to do so primarily stemmed from safety concerns and family responsibility. CONCLUSION: Most frontline nurses were willing to work and showed great professional commitment. IMPACT: Professional commitment and patriotism were two important individual-level factors affecting frontline nurses' willingness to work during a pandemic. Strategies should be implemented, such as appreciating and acknowledging their contribution, rewarding their valuable work, arranging reasonable working hours, enhancing colleagues' and hospitals' preparedness, and providing emotional support. Moreover, adequate personal protective equipment, self-protection training and social support should be ensured to address frontline nurses' safety concerns and family responsibility.

The breadth of concomitant virological features in a family cluster outbreak of COVID-19 pneumonia.

An outbreak of a novel coronavirus disease (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) had emerged in 2019 and rapidly posed a global epidemic. Here, we report the breadth of concomitant virological features of a family cluster with COVID-19. The period of virus shedding is significantly different between upper respiratory and feces samples. Even the SARS-CoV-2 virus titers were undetectable in feces, it could be positive again soon and likely related to fluctuated inflammation levels (interleukin-6, etc.) and lowered immune responses (CD4 + T lymphocyte, etc.). Our findings expand the novel understanding of the breadth of concomitant virological features during a non-severe family cluster of COVID-19.

Epidemiological and clinical characteristics of 1663 hospitalized patients infected with COVID-19 in Wuhan, China: a single-center experience.

BACKGROUND: The COVID-19 outbreak in late December 2019 has quickly emerged into pandemic in 2020. We aimed to describe the epidemiology and clinical characteristics of hospitalized COVID-19 patients, and to investigate the potential risk factors for COVID-19 severity. METHOD: 1663 hospitalized patients with laboratory-confirmed diagnosed COVID-19 from Tongji Hospital between January 14, 2020, and February 28, 2020 were included in the present study. Demographic information, exposure history, medical history, comorbidities, signs and symptoms, chest computed tomography (CT) scanning, severity of COVID-19 and laboratory findings on admission were collected from electronic medical records. Multivariable logistic regression was used to explore the association between potential risk factors with COVID-19 severity. RESULTS: In the present study, the majority (79%) of 1663 COVID-19 patients were aged over 50 years old. A total of 2.8% were medical staff, and an exposure history of Huanan seafood market was document in 0.7%, and 7.4% were family infection. Fever (85.8%), cough (36.0%), fatigue (23.6%) and chest tightness (11.9%) were the most common symptoms in COVID-19 patients. As of February 28, 2020, of the 1663 patients included in this study, 26.0% were discharged, 10.2% were died, and 63.8% remained hospitalized. More than 1/3 of the patients had at least one comorbidity. Most (99.8%) patients had abnormal results Chest CT, and the most common manifestations of chest CT were local patchy shadowing (70.7%) and ground-glass opacity (44.8%). On admission, lymphocytopenia was present in 51.1% of the patients, mononucleosis in 26.6%, and erythrocytopenia in 61.3%. Most of the patients had increased levels of C-reactive protein (80.4%) and D-dimer (64.4%). Compared with non-severe patients, severe patients had more obvious abnormal laboratory results related to inflammation, coagulation disorders, liver and kidney damage (all P < 0.05). Older age (OR = 2.37, 95% CI: 1.47-3.83), leukocytosis (OR = 2.37, 95% CI: 1.47-3.83), and increased creatine kinase (OR = 2.37, 95% CI: 1.47-3.83) on admission were significantly associated with COVID-19 severity. CONCLUSION: Timely medical treatment and clear diagnosis after the onset might be beneficial to control the condition of COVID-19. Severe patients were more likely to be to be elder, and tended to have higher proportion of comorbidities and more prominent laboratory abnormalities. Older age, leukocytosis, and increased creatine kinase might help clinicians to identify severe patients with COVID-19.

Immunological and inflammatory profiles in mild and severe cases of COVID-19.

COVID-19 is associated with 5.1% mortality. Although the virological, epidemiological, clinical, and management outcome features of COVID-19 patients have been defined rapidly, the inflammatory and immune profiles require definition as they influence pathogenesis and clinical expression of COVID-19. Here we show lymphopenia, selective loss of CD4+ T cells, CD8+ T cells and NK cells, excessive T-cell activation and high expression of T-cell inhibitory molecules are more prominent in severe cases than in those with mild disease. CD8+ T cells in patients with severe disease express high levels of cytotoxic molecules. Histochemical studies of lung tissue from one fatality show sub-anatomical distributions of SARS-CoV-2 RNA and massive infiltration of T cells and macrophages. Thus, aberrant activation and dysregulation of CD8+ T cells occur in patients with severe COVID-19 disease, an effect that might be for pathogenesis of SARS-CoV-2 infection and indicate that immune-based targets for therapeutic interventions constitute a promising treatment for severe COVID-19 patients.

Frontline nurses' burnout, anxiety, depression, and fear statuses and their associated factors during the COVID-19 outbreak in Wuhan, China: A large-scale cross-sectional study.

BACKGROUND: During the Coronavirus Disease 2019 (COVID-19) pandemic, frontline nurses face enormous mental health challenges. Epidemiological data on the mental health statuses of frontline nurses are still limited. The aim of this study was to examine mental health (burnout, anxiety, depression, and fear) and their associated factors among frontline nurses who were caring for COVID-19 patients in Wuhan, China. METHODS: A large-scale cross-sectional, descriptive, correlational study design was used. A total of 2,014 eligible frontline nurses from two hospitals in Wuhan, China, participated in the study. Besides sociodemographic and background data, a set of valid and reliable instruments were used to measure outcomes of burnout, anxiety, depression, fear, skin lesion, self-efficacy, resilience, and social support via the online survey in February 2020. FINDINGS: On average, the participants had a moderate level of burnout and a high level of fear. About half of the nurses reported moderate and high work burnout, as shown in emotional exhaustion (n = 1,218, 60.5%), depersonalization (n = 853, 42.3%), and personal accomplishment (n = 1,219, 60.6%). The findings showed that 288 (14.3%), 217 (10.7%), and 1,837 (91.2%) nurses reported moderate and high levels of anxiety, depression, and fear, respectively. The majority of the nurses (n = 1,910, 94.8%) had one or more skin lesions, and 1,950 (96.8%) nurses expressed their frontline work willingness. Mental health outcomes were statistically positively correlated with skin lesion and negatively correlated with self-efficacy, resilience, social support, and frontline work willingness. INTERPRETATION: The frontline nurses experienced a variety of mental health challenges, especially burnout and fear, which warrant attention and support from policymakers. Future interventions at the national and organisational levels are needed to improve mental health during this pandemic by preventing and managing skin lesions, building self-efficacy and resilience, providing sufficient social support, and ensuring frontline work willingness.

Effectiveness of Arbidol for COVID-19 Prevention in Health Professionals.

Background: Frontline health professionals are a COVID-19-susceptible population during the outbreak of COVID-19, but prophylactic drugs against SARS-CoV-2 infection are to be explored. Method: Frontline health professionals diagnosed with COVID-19 before February 9, 2020 in Tongji Hospital, Wuhan, China and the same amount of controls in the uninfected group were included in this study. Clinical and laboratory data were collected with standardized forms. Results: A total of 164 subjects were included in this study, 82 cases in the infected group and 82 controls in the uninfected group, with a median age of 37 years, including 63 males and 101 females. Nineteen (23.2%) patients in the infected group were administered oral arbidol, and 48 (58.5%) in the uninfected group (OR = 0.214, 95% CI 0.109-0.420). The cumulative uninfected rate of health professionals in the arbidol group was significantly higher than that of individuals in the non-arbidol group (log-rank test, χ2 = 98.74; P < 0.001). Forty-eight patients (58.5%) in the infection group were hospitalized, with a median age of 39 (31-49) years, of whom 7 (14.6%) were prophylactically administered arbidol. Thirty-four patients (41.5%) with mild symptoms were treated outside the hospital, among which the median age was 34 (30-39) years, and twelve patients (35.3%) took prophylactic oral arbidol. The hospitalization rate was significantly associated with age (P = 0.024) and oral arbidol administration (OR = 0.313, 95% CI 0.108-0.909). In the age-matched case-control study, the hospitalization rate was not significantly associated with arbidol administration (P = 0.091). Conclusion: Prophylactic oral arbidol was associated with a lower incidence of SARS-CoV-2 infection but not hospitalization rate in health professionals, providing a basis for the selection of prophylactic drugs for high-risk populations.

Clinical Characteristics, Associated Factors, and Predicting COVID-19 Mortality Risk: A Retrospective Study in Wuhan, China.

INTRODUCTION: COVID-19 has become a serious global pandemic. This study investigates the clinical characteristics and the risk factors for COVID-19 mortality and establishes a novel scoring system to predict mortality risk in patients with COVID-19. METHODS: A cohort of 1,663 hospitalized patients with COVID-19 in Wuhan, China, of whom 212 died and 1,252 recovered, were included in this study. Demographic, clinical, and laboratory data on admission were collected from electronic medical records between January 14, 2020 and February 28, 2020. Clinical outcomes were collected until March 26, 2020. Multivariable logistic regression was used to explore the association between potential risk factors and COVID-19 mortality. The receiver operating characteristic curve was used to predict COVID-19 mortality risk. All analyses were conducted in April 2020. RESULTS: Multivariable regression showed that increased odds of COVID-19 mortality was associated with older age (OR=2.15, 95% CI=1.35, 3.43), male sex (OR=1.97, 95% CI=1.29, 2.99), history of diabetes (OR=2.34, 95% CI=1.45, 3.76), lymphopenia (OR=1.59, 95% CI=1.03, 2.46), and increased procalcitonin (OR=3.91, 95% CI=2.22, 6.91, per SD increase) on admission. Spline regression analysis indicated that the correlation between procalcitonin levels and COVID-19 mortality was nonlinear (p=0.0004 for nonlinearity). The area under the receiver operating curve of the COVID-19 mortality risk was 0.765 (95% CI=0.725, 0.805). CONCLUSIONS: The independent risk factors for COVID-19 mortality included older age, male sex, history of diabetes, lymphopenia, and increased procalcitonin, which could help clinicians to identify patients with poor prognosis at an earlier stage. The COVID-19 mortality risk score model may assist clinicians in reducing COVID-19-related mortality by implementing better strategies for more effective use of limited medical resources.

Clinical characteristics of 80 hospitalized frontline medical workers infected with COVID-19 in Wuhan, China.

More than 1,000 medical workers have been infected with COVID-19 in China. The 80 hospitalized patients included 57 SARS-CoV-2 confirmed and 23 clinically diagnosed. The median age was 39 years, 49 (61.25%) were women, and one patient died. The most common symptoms at onset were fever (65, 81.25%), cough (47, 58.75%), fatigue (28, 35%), myalgia (19, 23.75%), expectoration (19, 23.75%), and diarrhea (15, 18.75%). Patients of frontline medical workers at a single-center hospital showed some unique clinical and laboratory findings compared with other patients in Wuhan and outside of Wuhan. This study provides our experience for other frontline medical workers.