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The 2019 coronavirus disease (COVID-19) is a public health emergency of international concern. In China, all schools were shut down and students were home quarantined to prevent disease spread; these steps could have potential negative effects on mental health of adolescents. This study aimed to examine changes in depression and anxiety among Chinese adolescents during the COVID-19 epidemic, and explore factors associated with depression and anxiety. Two survey administrations were conducted among Chinese adolescents between February 20 and February 27 and between April 11 and April 19, 2020, respectively. The Center for Epidemiological Studies-Depression Scale (CES-D) and the 7-item Generalized Anxiety Disorder (GAD-7) scale were used to assess depressive symptoms and anxiety symptoms, respectively. A total of 9554 and 3886 adolescents participated in the first and second surveys. During the initial survey, the prevalence of depression was 36.6% (95% CI: 35.6–37.6%) while the prevalence of anxiety was 19% (95% CI: 18.2–19.8%). Rates of depression and anxiety increased to 57.0% (95% CI: 55.4–58.6%) and 36.7% (95% CI: 35.2–38.2%), respectively, in the second survey. Multivariable logistic regression analyses revealed that group membership in the second survey, female gender, senior secondary school enrollment, and concerns about entering a higher grade were positively associated with both depression and anxiety. Conversely, a sleep duration of ≥6 h/day, an exercise duration ≥30 min/day, having the same as typical or higher study efficiency during the COVID-19 outbreak, and living in provinces with 1000–9999 confirmed COVID-19 cases were negatively associated with depression and anxiety. In conclusion, compared to figures reported during the COVID-19 outbreak, the prevalence of depression and anxiety in Chinese adolescents significantly increased after the initial outbreak. Regular screening and appropriate interventions are urgently needed to reduce the risk for emotional disturbances among adolescents during and after the initial COVID-19 outbreaks.

Network analysis is an effective approach for examining complex relationships between psychiatric symptoms. This study was designed to examine item-level relationships between depressive and anxiety symptoms using network analysis in an adolescent sample and identified the most central symptoms within the depressive-anxiety symptoms network model. Depressive and anxiety symptoms were assessed using the Patient Health Questionire-9 (PHQ-9) and Generalized Anxiety Disorder Screener (GAD-7), respectively. The structure of depressive and anxiety symptoms was characterized using “Strength” and “Bridge Strength” as centrality indices in the symptom network. Network stability was tested using a case-dropping bootstrap procedure. Finally, a Network Comparison Test (NCT) was conducted to examine whether network characteristics differed on the basis of gender, school grade and residence. Network analysis revealed that nodes PHQ2 (“Sad mood”), GAD6 (“Irritability”), GAD3 (“Worry too much”), and PHQ6 (“Guilty”) were central symptoms in the network model of adolescents. Additionally, bridge symptoms linking anxiety and depressive symptoms in this sample were nodes PHQ6 (“Guilty”), PHQ2 (“Sad mood”), and PHQ9 (“Suicide ideation”). Gender, school grade and residence did not significantly affect the network structure. Central symptoms (e.g., Sad mood, Irritability, Worry too much, and Guilty) and key bridge symptoms (e.g., Guilty, Sad mood, and Suicide ideation) in the depressive and anxiety symptoms network may be useful as potential targets for intervention among adolescents who are at risk for or suffer from depressive and anxiety symptoms.

The novel coronavirus disease (COVID-19) has been rapidly transmitted in China, Macau, Hong Kong, and other Asian and European counterparts. This COVID-19 epidemic has aroused increasing attention nationwide. Patients, health professionals, and the general public are under insurmountable psychological pressure which may lead to various psychological problems, such as anxiety, fear, depression, and insomnia. Psychological crisis intervention plays a pivotal role in the overall deployment of the disease control. The National Health Commission of China has summoned a call for emergency psychological crisis intervention and thus, various mental health associations and organizations have established expert teams to compile guidelines and public health educational articles/videos for mental health professionals and the general public alongside with online mental health services. In addition, mental health professionals and expert groups are stationed in designated isolation hospitals to provide on-site services. Experts have reached a consensus on the admission of patients with severe mental illness during the COVID-19 outbreak in mental health institutions. Nevertheless, the rapid transmission of the COVID-19 has emerged to mount a serious challenge to the mental health service in China.

Recent epidemiological data suggests 13.3% of Hong Kong residents suffered from Common Mental Disorders, most frequently mixed anxiety and depressive disorder. This study examines the weighted prevalence and associated risk factors of depression, anxiety and stress among Hong Kong nurses. A total of 850 nurses were invited to participate in this cross-sectional study. Participants completed the Depression, Anxiety and Stress Scale 21 and multiple logistic regression was used to determine significant relationships between variables. Chronic past-year illness and poor self-perceived mental health were significant correlates of past-week depression, anxiety and stress. It confirmed further positive correlations between depression and divorce, widowhood and separation, job dissatisfaction, disturbance with colleagues, low physical activity levels and sleep problems. Marital status; general medicine; sleep problems, and a lack of leisure significantly correlated with anxiety. Stress was significantly associated with younger age, clinical inexperience, past-year disturbance with colleagues, low physical activity, no leisure and drinking alcohol. Nurses were more depressed, anxious and stressed than the local general population, with over one-third of our respondents classified as subject to these disorders.

Mental health problems are common in college students even in the late stage of the coronavirus disease 2019 (COVID-19) outbreak. Network analysis is a novel approach to explore interactions of mental disorders at the symptom level. The aim of this study was to elucidate characteristics of depressive and anxiety symptoms network in college students in the late stage of the COVID-19 outbreak. A total of 3062 college students were included. The seven-item Generalized Anxiety Disorder Scale (GAD-7) and nine-item Patient Health Questionnaire (PHQ-9) were used to measure anxiety and depressive symptoms, respectively. Central symptoms and bridge symptoms were identified based on centrality and bridge centrality indices, respectively. Network stability was examined using the case-dropping procedure. The strongest direct relation was between anxiety symptoms “Nervousness” and “Uncontrollable worry”. “Fatigue” has the highest node strength in the anxiety and depression network, followed by “Excessive worry”, “Trouble relaxing”, and “Uncontrollable worry”. “Motor” showed the highest bridge strength, followed by “Feeling afraid” and “Restlessness”. The whole network was robust in both stability and accuracy tests. Central symptoms “Fatigue”, “Excessive worry”, “Trouble relaxing” and “Uncontrollable worry”, and critical bridge symptoms “Motor”, “Feeling afraid” and “Restlessness” were highlighted in this study. Targeting interventions to these symptoms may be important to effectively alleviate the overall level of anxiety and depressive symptoms in college students.

Recently, more than 300 Chinese patients with psychiatric disorders were diagnosed with the 2019 novel coronavirus disease (COVID-19). Possible reasons quoted in the report were the lack of caution regarding the COVID-19 outbreak in January and insufficient supplies of protective gear. We outlined major challenges for patients with psychiatric disorders and mental health professionals during the COVID-19 outbreak, and also discussed how to manage these challenges through further mental health service reform in China.

Background Nurses are especially vulnerable to violent and other forms of aggression in the workplace. Nonetheless, few population-based studies of workplace violence have been undertaken among working-age nurse professionals in Hong Kong in the last decade. Methods The study estimates the prevalence and examines the socio-economic and psychological correlates of workplace violence (WPV) among professional nurses in Hong Kong. The study uses a cross-sectional survey design. Multivariate logistic regression examines the weighted prevalence rates of WPV and its associated factors for a population of nurses. Results A total of 850 nurses participated in the study. 44.6% had experienced WPV in the preceding year. Male nurses reported more WPV than their female counterparts. The most common forms of WPV were verbal abuse/bullying (39.2%), then physical assault (22.7%) and sexual harassment (1.1%). The most common perpetrators of WPV were patients (36.6%) and their relatives (17.5%), followed by colleagues (7.7%) and supervisors (6.3%). Clinical position, shift work, job satisfaction, recent disturbances with colleagues, deliberate self-harm (DSH) and symptoms of anxiety were significantly correlated with WPV for nurses. Conclusions WPV remains a significant concern for healthcare worldwide. Hong Kong’s local health authority should put in place a raft of zero-tolerance measures to prevent WPV in healthcare settings.

In network theory depression is conceptualized as a complex network of individual symptoms that influence each other, and central symptoms in the network have the greatest impact on other symptoms. Clinical features of depression are largely determined by sociocultural context. No previous study examined the network structure of depressive symptoms in Hong Kong residents. The aim of this study was to characterize the depressive symptom network structure in a community adult sample in Hong Kong during the COVID-19 pandemic. A total of 11,072 participants were recruited between 24 March and 20 April 2020. Depressive symptoms were measured using the Patient Health Questionnaire-9. The network structure of depressive symptoms was characterized, and indices of “strength”, “betweenness”, and “closeness” were used to identify symptoms central to the network. Network stability was examined using a case-dropping bootstrap procedure. Guilt, Sad Mood, and Energy symptoms had the highest centrality values. In contrast, Concentration, Suicide, and Sleep had lower centrality values. There were no significant differences in network global strength (p = 0.259), distribution of edge weights (p = 0.73) and individual edge weights (all p values > 0.05 after Holm–Bonferroni corrections) between males and females. Guilt, Sad Mood, and Energy symptoms were central in the depressive symptom network. These central symptoms may be targets for focused treatments and future psychological and neurobiological research to gain novel insight into depression.

The health authorities reported that 3,019 Chinese health workers were infected with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), of whom, ten died. This article explored relevant reasons and offered suggestions to reduce the risk of infection and provide emergency psychological response for this population.

BackgroundSchizophrenia (SCZ) is a severe psychiatric disorder that involves inflammatory processes. The aim of this study was to explore the field of inflammation-related research in SCZ from a bibliometric perspective.MethodsRegular and review articles on SCZ- and inflammation-related research were obtained from the Web of Science Core Collection (WOSCC) database from its inception to February 19, 2022. R package “bibliometrix” was used to summarize the main findings, count the occurrences of the top keywords, visualize the collaboration network between countries, and generate a three-field plot. VOSviewer software was applied to conduct both co-authorship and co-occurrence analyses. CiteSpace was used to identify the top references and keywords with the strongest citation burst.ResultsA total of 3,596 publications on SCZ and inflammation were included. Publications were mainly from the USA, China, and Germany. The highest number of publications was found in a list of relevant journals. Apart from “schizophrenia” and “inflammatory”, the terms “bipolar disorder,” “brain,” and “meta-analysis” were also the most frequently used keywords.ConclusionsThis bibliometric study mapped out a fundamental knowledge structure consisting of countries, institutions, authors, journals, and articles in the research field of SCZ and inflammation over the past 30 years. The results provide a comprehensive perspective about the wider landscape of this research area.