Prevalence of depression and its association with quality of life among guardians of hospitalized psychiatric patients during the COVID-19 pandemic: a network perspective.

Background: The COVID-19 pandemic has greatly affected treatment-seeking behaviors of psychiatric patients and their guardians. Barriers to access of mental health services may contribute to adverse mental health consequences, not only for psychiatric patients, but also for their guardians. This study explored the prevalence of depression and its association with quality of life among guardians of hospitalized psychiatric patients during the COVID-19 pandemic. Methods: This multi-center, cross-sectional study was conducted in China. Symptoms of depression and anxiety, fatigue level and quality of life (QOL) of guardians were measured with validated Chinese versions of the Patient Health Questionnaire - 9 (PHQ-9), Generalized Anxiety Disorder Scale - 7 (GAD-7), fatigue numeric rating scale (FNRS), and the first two items of the World Health Organization Quality of Life Questionnaire - brief version (WHOQOL-BREF), respectively. Independent correlates of depression were evaluated using multiple logistic regression analysis. Analysis of covariance (ANCOVA) was used to compare global QOL of depressed versus non-depressed guardians. The network structure of depressive symptoms among guardians was constructed using an extended Bayesian Information Criterion (EBIC) model. Results: The prevalence of depression among guardians of hospitalized psychiatric patients was 32.4% (95% CI: 29.7-35.2%). GAD-7 total scores (OR = 1.9, 95% CI: 1.8-2.1) and fatigue (OR = 1.2, 95% CI: 1.1-1.4) were positively correlated with depression among guardians. After controlling for significant correlates of depression, depressed guardians had lower QOL than non-depressed peers did [F(1, 1,101) = 29.24, p < 0.001]. "Loss of energy" (item 4 of the PHQ-9), "concentration difficulties" (item 7 of the PHQ-9) and "sad mood" (item 2 of the PHQ-9) were the most central symptoms in the network model of depression for guardians. Conclusion: About one third of guardians of hospitalized psychiatric patients reported depression during the COVID-19 pandemic. Poorer QOL was related to having depression in this sample. In light of their emergence as key central symptoms, "loss of energy," "concentration problems," and "sad mood" are potentially useful targets for mental health services designed to support caregivers of psychiatric patients.

Depression and anxiety among Macau residents during the COVID-19 outbreak: A network analysis perspective.

Background: The 2019 novel coronavirus disease (COVID-19) outbreak affected people's lifestyles and increased their risk for depressive and anxiety symptoms (depression and anxiety, respectively hereafter). We assessed depression and anxiety in residents of Macau during "the 6.18 COVID-19 outbreak" period and explored inter-connections of different symptoms from the perspective of network analysis. Methods: In this cross-sectional study, 1,008 Macau residents completed an online survey comprising the nine-item Patient Health Questionnaire (PHQ-9) and seven-item Generalized Anxiety Disorder Scale (GAD-7) to measure depression and anxiety, respectively. Central and bridge symptoms of the depression-anxiety network model were evaluated based on Expected Influence (EI) statistics, while a bootstrap procedure was used to test the stability and accuracy of the network model. Results: Descriptive analyses indicated the prevalence of depression was 62.5% [95% confidence interval (CI) = 59.47-65.44%], the prevalence of anxiety was 50.2% [95%CI = 47.12-53.28%], and 45.1% [95%CI = 42.09-48.22%] of participants experienced comorbid depression and anxiety. "Nervousness-Uncontrollable worry" (GADC) (EI = 1.15), "Irritability" (GAD6) (EI = 1.03), and "Excessive worry" (GAD3) (EI = 1.02) were the most central symptoms, while "Irritability" (GAD6) (bridge EI = 0.43), "restlessness" (GAD5) (bridge EI = 0.35), and "Sad Mood" (PHQ2) (bridge EI = 0.30) were key bridge symptoms that emerged in the network model. Conclusion: Nearly half of residents in Macau experienced comorbid depression and anxiety during the 6.18 COVID-19 outbreak. Central and bridge symptoms identified in this network analysis are plausible, specific targets for treatment and prevention of comorbid depression and anxiety related to this outbreak.

Prevalence of insomnia and its association with quality of life among Macau residents shortly after the summer 2022 COVID-19 outbreak: A network analysis perspective

Background The latest wave of the coronavirus disease 2019 (COVID-19) pandemic in Macau began on 18 June 2022 and was more serious than previous waves. Ensuing disruption from the wave is likely to have had a variety of negative mental health consequences for Macau residents including increased risk for insomnia. This study investigated the prevalence and correlates of insomnia among Macau residents during this wave as well as its association with quality of life (QoL) from a network analysis perspective. Methods A cross-sectional study was conducted between 26 July and 9 September 2022. Univariate and multivariate analyses explored correlates of insomnia. Analysis of covariance (ANCOVA) examined the relationship between insomnia and QoL. Network analysis assessed the structure of insomnia including "Expected influence” to identify central symptoms in the network, and the flow function to identify specific symptoms that were directly associated with QoL. Network stability was examined using a case-dropping bootstrap procedure. Results A total of 1,008 Macau residents were included in this study. The overall prevalence of insomnia was 49.0% (n = 494;95% CI = 45.9–52.1%). A binary logistic regression analysis indicated people with insomnia were more likely to report depression (OR = 1.237;P < 0.001) and anxiety symptoms (OR = 1.119;P < 0.001), as well as being quarantined during the COVID-19 pandemic (OR = 1.172;P = 0.034). An ANCOVA found people with insomnia had lower QoL (F(1,1,008) = 17.45, P < 0.001). "Sleep maintenance” (ISI2), "Distress caused by the sleep difficulties” (ISI7) and "Interference with daytime functioning” (ISI5) were the most central symptoms in the insomnia network model, while "Sleep dissatisfaction” (ISI4), "Interference with daytime functioning” (ISI5), and "Distress caused by the sleep difficulties” (ISI7) had the strongest negative associations with QoL. Conclusion The high prevalence of insomnia among Macau residents during the COVID-19 pandemic warrants attention. Being quarantined during the pandemic and having psychiatric problems were correlates of insomnia. Future research should target central symptoms and symptoms linked to QoL observed in our network models to improve insomnia and QoL.

Associations between post-traumatic stress symptoms and quality of life among psychiatric healthcare personnel in China during the COVID-19 pandemic: A network approach

Background Post-traumatic stress symptoms (PTSS) are commonly reported by psychiatric healthcare personnel during the coronavirus disease 2019 (COVID-19) pandemic and negatively affect quality of life (QOL). However, associations between PTSS and QOL at symptom level are not clear. This study examined the network structure of PTSS and its connection with QOL in psychiatric healthcare personnel during the COVID-19 pandemic. Methods This cross-sectional study was carried out between March 15 and March 20, 2020 based on convenience sampling. Self-report measures including the 17-item Post-Traumatic Stress Disorder Checklist – Civilian version (PCL-C) and World Health Organization Quality of Life Questionnaire - Brief Version (WHOQOL-BREF) were used to measure PTSS and global QOL, respectively. Network analysis was used to investigate the central symptoms of PTSS and pattern of connections between PTSS and QOL. An undirected network was constructed using an extended Bayesian Information Criterion (EBIC) model, while a directed network was established based on the Triangulated Maximally Filtered Graph (TMFG) method. Results Altogether, 10,516 psychiatric healthcare personnel completed the assessment. "Avoidance of thoughts” (PTSS-6), "Avoidance of reminders” (PTSS-7), and "emotionally numb” (PTSS-11) were the most central symptoms in the PTSS community, all of which were in the Avoidance and Numbing domain. Key bridge symptoms connecting PTSS and QOL were "Sleep disturbances” (PTSS-13), "Irritability” (PTSS-14) and "Difficulty concentrating” (PTSS-15), all of which were within the Hyperarousal domain. Conclusion In this sample, the most prominent PTSS symptoms reflected avoidance while symptoms of hyper-arousal had the strongest links with QOL. As such, these symptom clusters are potentially useful targets for interventions to improve PTSS and QOL among healthcare personnel at work under pandemic conditions.

Associations between post-traumatic stress symptoms and quality of life among psychiatric healthcare personnel in China during the COVID-19 pandemic: A network approach.

Background: Post-traumatic stress symptoms (PTSS) are commonly reported by psychiatric healthcare personnel during the coronavirus disease 2019 (COVID-19) pandemic and negatively affect quality of life (QOL). However, associations between PTSS and QOL at symptom level are not clear. This study examined the network structure of PTSS and its connection with QOL in psychiatric healthcare personnel during the COVID-19 pandemic. Methods: This cross-sectional study was carried out between March 15 and March 20, 2020 based on convenience sampling. Self-report measures including the 17-item Post-Traumatic Stress Disorder Checklist - Civilian version (PCL-C) and World Health Organization Quality of Life Questionnaire - Brief Version (WHOQOL-BREF) were used to measure PTSS and global QOL, respectively. Network analysis was used to investigate the central symptoms of PTSS and pattern of connections between PTSS and QOL. An undirected network was constructed using an extended Bayesian Information Criterion (EBIC) model, while a directed network was established based on the Triangulated Maximally Filtered Graph (TMFG) method. Results: Altogether, 10,516 psychiatric healthcare personnel completed the assessment. "Avoidance of thoughts" (PTSS-6), "Avoidance of reminders" (PTSS-7), and "emotionally numb" (PTSS-11) were the most central symptoms in the PTSS community, all of which were in the Avoidance and Numbing domain. Key bridge symptoms connecting PTSS and QOL were "Sleep disturbances" (PTSS-13), "Irritability" (PTSS-14) and "Difficulty concentrating" (PTSS-15), all of which were within the Hyperarousal domain. Conclusion: In this sample, the most prominent PTSS symptoms reflected avoidance while symptoms of hyper-arousal had the strongest links with QOL. As such, these symptom clusters are potentially useful targets for interventions to improve PTSS and QOL among healthcare personnel at work under pandemic conditions.

Network analysis of comorbid insomnia and depressive symptoms among psychiatric practitioners during the COVID-19 pandemic.

STUDY OBJECTIVES: Insomnia and depression are common mental health problems reported by mental health professionals during the COVID-19 pandemic. Network analysis is a fine-grained approach used to examine associations between psychiatric syndromes at a symptom level. This study was designed to elucidate central symptoms and bridge symptoms of a depression-insomnia network among psychiatric practitioners in China. The identification of particularly important symptoms via network analysis provides an empirical foundation for targeting specific symptoms when developing treatments for comorbid insomnia and depression within this population. METHODS: A total of 10,516 psychiatric practitioners were included in this study. The Insomnia Severity Index (ISI) and 9-item Patient Health Questionnaire (PHQ-9) were used to estimate prevalence rates of insomnia and depressive symptoms, respectively. Analyses also generated a network model of insomnia and depression symptoms in the sample. RESULTS: Prevalence rates of insomnia (ISI total score ≥8), depression (PHQ-9 total score ≥5) and comorbid insomnia and depression were 22.2% (95% confidence interval: 21.4-22.9%), 28.5% (95% confidence interval: 27.6-29.4%), and 16.0% (95% confidence interval: 15.3-16.7%), respectively. Network analysis revealed that "Distress caused by sleep difficulties" (ISI7) and "Sleep maintenance" (ISI2) had the highest strength centrality, followed by "Motor dysfunction" (PHQ8) and "Sad mood" (PHQ2). Furthermore, the nodes "Sleep dissatisfaction" (ISI4), "Fatigue" (PHQ4), and "Motor dysfunction" (PHQ8) had the highest bridge strengths in linking depression and insomnia communities. CONCLUSIONS: Both central and bridge symptoms (ie, Distress caused by sleep difficulties, Sleep maintenance, Motor dysfunction, Sad mood, Sleep dissatisfaction, and Fatigue) should be prioritized when testing preventive measures and specific treatments to address comorbid insomnia and depression among psychiatric practitioners during the COVID-19 pandemic. CITATION: Zhao N, Zhao Y-J, An F, et al. Network analysis of comorbid insomnia and depressive symptoms among psychiatric practitioners during the COVID-19 pandemic. J Clin Sleep Med. 2023;19(7):1271-1279.

Prevalence of depression and its association with quality of life in patients after pacemaker implantation during the COVID-19 pandemic: A network analysis.

Background: This study was designed to investigate the prevalence and predictors of depression in patients after pacemaker implantation during the COVID-19 pandemic in addition to identifying specific depressive symptoms associated with quality of life (QOL) using network analysis (NA). Methods: This cross-sectional, observational study was conducted in China between July 1, 2021, and May 17, 2022. Descriptive analysis was used to calculate depression prevalence. Univariate analyses were used to compare differences in demographic and clinical characteristics between depressed and non-depressed patients following pacemaker implantation. Binary logistic regression analysis was used to assess factors independently associated with depression. Network analysis "expected influence," and flow function indexes were used to identify symptoms central to the depression network of the sample and depressive symptoms that were directly associated with QOL, respectively. Network stability was examined using a case-dropping bootstrap procedure. Results: In total, 206 patients implanted with a pacemaker met the study entry criteria and completed the assessment. The overall prevalence of depression (PHQ-9 total score ≥ 5) was 39.92% [95% confidence interval (CI) = 29.37-42.47%]. A binary logistic regression analysis revealed that patients with depression were more likely to report a poor health status (p = 0.031), severe anxiety symptoms (p < 0.001), and fatigue (p < 0.001). In the network model for depression, "Sad mood," "Poor Energy," and "Guilt" were the most influential symptoms. "Fatigue" had the strongest negative association with QOL, followed by "Sad mood" and "Appetite". Conclusion: Depression is common among patients having undergone pacemaker implantation during the COVID-19 pandemic. Anxiety, central symptoms of depression (i.e., "Sad mood", "Poor Energy", and "Guilt") and depressive symptoms linked to QOL (i.e., "Sad mood", "Appetite", and "Fatigue") identified in this study are promising targets for interventions and preventive measures for depression in patients who have undergone pacemaker implants.

Prevalence of insomnia and its association with quality of life among Macau residents shortly after the summer 2022 COVID-19 outbreak: A network analysis perspective.

Background: The latest wave of the coronavirus disease 2019 (COVID-19) pandemic in Macau began on 18 June 2022 and was more serious than previous waves. Ensuing disruption from the wave is likely to have had a variety of negative mental health consequences for Macau residents including increased risk for insomnia. This study investigated the prevalence and correlates of insomnia among Macau residents during this wave as well as its association with quality of life (QoL) from a network analysis perspective. Methods: A cross-sectional study was conducted between 26 July and 9 September 2022. Univariate and multivariate analyses explored correlates of insomnia. Analysis of covariance (ANCOVA) examined the relationship between insomnia and QoL. Network analysis assessed the structure of insomnia including "Expected influence" to identify central symptoms in the network, and the flow function to identify specific symptoms that were directly associated with QoL. Network stability was examined using a case-dropping bootstrap procedure. Results: A total of 1,008 Macau residents were included in this study. The overall prevalence of insomnia was 49.0% (n = 494; 95% CI = 45.9-52.1%). A binary logistic regression analysis indicated people with insomnia were more likely to report depression (OR = 1.237; P < 0.001) and anxiety symptoms (OR = 1.119; P < 0.001), as well as being quarantined during the COVID-19 pandemic (OR = 1.172; P = 0.034). An ANCOVA found people with insomnia had lower QoL (F(1,1,008) = 17.45, P < 0.001). "Sleep maintenance" (ISI2), "Distress caused by the sleep difficulties" (ISI7) and "Interference with daytime functioning" (ISI5) were the most central symptoms in the insomnia network model, while "Sleep dissatisfaction" (ISI4), "Interference with daytime functioning" (ISI5), and "Distress caused by the sleep difficulties" (ISI7) had the strongest negative associations with QoL. Conclusion: The high prevalence of insomnia among Macau residents during the COVID-19 pandemic warrants attention. Being quarantined during the pandemic and having psychiatric problems were correlates of insomnia. Future research should target central symptoms and symptoms linked to QoL observed in our network models to improve insomnia and QoL.

Inter-relationships of depressive and anxiety symptoms with suicidality among adolescents: A network perspective.

BACKGROUND: Persons with suicidality including suicidal ideation (SI), suicide plans (SP) and/or suicide attempts (SA) are at higher risk for future suicide than those without suicidality. To reduce the risk of future suicide, it is important to understand symptoms of emotional distress that have the strongest links with SI, SP and SA. This network analysis examined item-level relations of depressive and anxiety symptoms with suicidality among adolescents during the COVID-19 pandemic. METHODS: Adolescents between 12 and 20 years of age were assessed with the Patient Health Questionnaire (PHQ-9), Generalized Anxiety Disorder Scale (GAD-7), and individual binary reponse (no/yes) items assessing SI, SP, and SA during the pandemic. The structure of depressive symptoms, anxiety symptoms and suicidality was characterized using "Expected Influence" and "Bridge Expected Influence" as centrality indices in the symptom network. Network stability was tested using a case-dropping bootstrap procedure. Node-specific predictive betweenness was computed to examine short paths of anhedonia, other depressive symptoms and anxiety symptoms with suicidality. A Network Comparison Test (NCT) was conducted to examine whether network characteristics differed based on gender. RESULTS: Prevalence rates of depressive symptoms, anxiety symptoms, and suicidality were 44.60 % (95% confidence interval (CI) = 41.53-47.67 %), 31.12 % (95%CI = 28.26-33.98 %), and 16.95 % (95%CI = 14.63-19.26 %), respectively, in the study sample. The network analysis identified GAD3 ("Worry too much") as the most central symptom, followed by GAD6 ("Irritability") and PHQ6 ("Guilt") in the sample. Additionally, PHQ6 ("Guilt"), GAD6 ("Irritability"), and PHQ2 ("Sad mood") were bridge nodes linking depressive and anxiety symptoms with suicidality. A flow network indicated that the connection between S ("Suicidality") and PHQ6 ("Guilt") reflected the strongest connection, followed by connections of S ("Suicidality") with GAD2 ("Uncontrollable worrying"), and S ("Suicidality") with PHQ2 ("Sad mood"). Finally, PHQ2 ("Sad mood") was the main bridge node linking anhedonia with other depressive and anxiety symptoms and suicidality in the sample. CONCLUSIONS: Findings highlight the potential importance of reducing specific depressive and anxiety symptoms as possible means of reducing suicidality among adolescents during the pandemic. Central symptoms and key bridge symptoms identified in this study should be targeted in suicide prevention for at-risk adolescents.

Suicide ideation and anhedonia among clinically stable adolescents with the recurrent depressive disorder during the COVID-19 pandemic: A network perspective.

BACKGROUND: Anhedonia is a suicide risk factor among adolescent patients with recurrent depressive disorder (depression hereafter). This study examined associations between suicidal ideation (SI) and residual depressive symptoms (RSD), including anhedonia, among clinically stable adolescents with depression. METHOD: A network analysis was performed to examine the association between RDS and SI among adolescents with depression. Node-specific predictive betweenness was computed to examine short paths between anhedonia and SI. Additionally, a Network Comparison Test (NCT) was conducted to examine gender differences in derived network model characteristics. RESULTS: The network analysis identified close associations of PHQ9 ("Suicide ideation") with PHQ1 ("Anhedonia") as well as some other RDS including PHQ6 ("Guilt"), PHQ2 ("Sad mood") and PHQ8 ("Motor disturbances"). Additionally, PHQ2 ("Sad mood") and PHQ4 ("Fatigue") were the main bridge nodes linking anhedonia and SI. Comparisons of network models did not find significant differences in network global strength or edge weights. LIMITATION: Causal relations between anhedonia and SI could not be determined due to the cross-sectional study design. CONCLUSIONS: SI was directly related to Anhedonia in addition to Guilt, Sad mood and Motor disturbances. Sad mood and Fatigue were the main bridge nodes linking Anhedonia and SI. To reduce the risk of SI among clinically stable adolescents with depression during the COVID-19 pandemic, specific RDS including Anhedonia, Guilt, Sad mood, Motor disturbances and Fatigue should be targeted in interventions.

COVID-19 vaccine acceptance and perceived stigma in patients with depression: a network perspective.

The association between coronavirus disease (COVID-19) vaccine acceptance and perceived stigma of having a mental illness is not clear. This study examined the association between COVID-19 vaccine acceptance and perceived stigma among patients with recurrent depressive disorder (depression hereafter) using network analysis. Participants were 1149 depressed patients (842 men, 307 women) who completed survey measures of perceived stigma and COVID-19 vaccine attitudes. T-tests, chi-square tests, and Kruskal-Wallis tests were used to compare differences in demographic and clinical characteristics between depressed patients who indented to accepted vaccines and those who were hesitant. Hierarchical multiple regression analyses assessed the unique association between COVID-19 vaccine acceptance and perceived stigma, independent of depression severity. Network analysis examined item-level relations between COVID-19 vaccine acceptance and perceived stigma after controlling for depressive symptoms. Altogether, 617 depressed patients (53.7%, 95 confidence intervals (CI) %: 50.82-56.58%) reported they would accept future COVID-19 vaccination. Hierarchical multiple regression analyses indicated higher perceived stigma scores predicted lower levels of COVID-19 vaccination acceptance (ß = -0.125, P < 0.001), even after controlling for depression severity. In the network model of COVID-19 vaccination acceptance and perceived stigma nodes, "Feel others avoid me because of my illness", "Feel useless", and "Feel less competent than I did before" were the most influential symptoms. Furthermore, "COVID-19 vaccination acceptance" had the strongest connections with illness stigma items reflecting social rejection or social isolation concerns ("Employers/co-workers have discriminated", "Treated with less respect than usual", "Sense of being unequal in my relationships with others"). Given that a substantial proportion of depressed patients reported hesitancy with accepting COVID-19 vaccines and experiences of mental illness stigma related to social rejection and social isolation, providers working with this group should provide interventions to reduce stigma concerns toward addressing reluctance in receiving COVID-19 vaccines.

Optimizing the dynamic zero-COVID policy in China.

There has been no consensus about the best public health strategy for managing COVID-19 due to differences in sociocultural, political and economic contexts between countries. The central government of China has emphasized the importance of maintaining the dynamic zero-COVID policy in combating resurgences of new variants. To optimize the dynamic zero-COVID policy for future COVID-19 outbreaks in China, this article outlines a comprehensive strategy that should be considered.

Associations between depressive symptoms and quality of life among residents of Wuhan, China during the later stage of the COVID-19 pandemic: A network analysis.

BACKGROUND: Various populations have experienced significant increases in depression and decreased quality of life (QOL) during the coronavirus disease 2019 (COVID-19) pandemic. This network analysis study was designed to elucidate interconnections between particular depressive symptoms and different aspects of QOL and identify the most clinically important symptoms in this network among adults in Wuhan China, the initial epicenter of the COVID-19 pandemic. METHODS: This cross-sectional, convenience-sampling study (N = 2459) was conducted between May 25 to June 18, 2020, after the lockdown policy had been lifted in Wuhan. Depressive symptoms and QOL were measured with the Patient Health Questionnaire-9 (PHQ-9) and first two items of the World Health Organization Quality of Life Questionnaire - brief version (WHOQOL-BREF), respectively. A network structure was constructed from the extended Bayesian Information Criterion (EBIC) model. Network centrality strength and bridge strength were evaluated along with the stability of the derived network model. RESULTS: Loss of energy (DEP-4) and Guilt feelings (DEP-6) were the two central symptoms with the highest strength as well as the two most prominent bridge symptoms connecting the clusters of depression and quality of life (QOL) in tandem with the two nodes from the QOL cluster. Network structure and bridge strengths remained stable after randomly dropping 75 % of the sample. CONCLUSION: Interventions targeting "Loss of energy" and "Guilt feelings" should be evaluated as strategies for reducing depressive symptoms and promoting improved QOL in COVID-19-affected populations.

Mapping post-traumatic stress disorder symptoms and quality of life among residents of Wuhan, China after the COVID-19 outbreak: A network perspective.

OBJECTIVES: The Coronavirus Disease 2019 (COVID-19) outbreak may have a long-term impact on mental health in the general population. This study examined inter-relationships between post-traumatic stress disorder symptoms (PTSS) and quality of life (QOL) in Wuhan residents after the COVID-19 outbreak using network approach. METHODS: A cross-sectional survey was conducted between May 25 and June 18, 2020. PTSS and QOL were measured using Chinese versions of the Post -Traumatic Stress Disorder Checklist - Civilian Version and the World Health Organization Quality of Life Questionnaire - brief version, respectively. RESULTS: A total of 2598 participants were included. A network analysis revealed "Avoiding reminders", "Feeling emotionally numb", "Avoiding thoughts", "Hypervigilance", and "Reliving experiences" as the most central (influential) nodes in PTSS network models both before and after controlling for covariates. The connection between "Avoiding thoughts" and "Avoiding reminders" had the strongest edge. Three symptom communities were detected and can be summarized as "re-experiencing and avoidance", "negative changes in thinking and mood", and "hyperarousal". The bridge symptoms connecting PTSS and QOL were "Sleep disturbances", "Irritability", and "Loss of interest". LIMITATIONS: Limitations included the cross-sectional study design, self-report measures in data collection, and lack of follow-ups beyond the initial phase of the pandemic. CONCLUSIONS: PTSS were common among Wuhan residents even after the initial COVID-19 outbreak had passed. Attention should be paid to lingering symptoms of avoiding reminders, emotional numbness, avoiding thoughts, hypervigilance, and reliving experiences in treating PTSS related to the COVID-19 outbreak.

Network analysis of depression, anxiety, insomnia and quality of life among Macau residents during the COVID-19 pandemic.

BACKGROUND: Although the Coronavirus Disease 2019 (COVID-19) has greatly impacted individuals' mental health and quality of life, network analysis studies of associations between symptoms of common syndromes during the pandemic are lacking, particularly among Macau residents. This study investigated the network structure of insomnia, anxiety, and depression and explored their associations with quality of life in this population. METHOD: This online survey was conducted in Macau between August 18 and November 9, 2020. Insomnia, anxiety, depressive symptoms, and quality of life were assessed with the Insomnia Severity Index, Generalized Anxiety Disorder Scale, Patient Health Questionnaire, and World Health Organization Quality of Life-brief version, respectively. Analyses were performed to identify central symptoms and bridge symptoms of this network and their links to quality of life. RESULTS: 975 participants enrolled in this survey. The prevalence of depressive, anxiety and insomnia symptoms were 38.5% (95% confidence interval (CI): 35.5%-41.5%), 28.8% (95%CI: 26.0%-31.7%), and 27.6% (95% CI: 24.8%-30.4%), respectively. "Sleep maintenance" had the highest expected influence centrality, followed by "Trouble relaxing", "Interference with daytime functioning", "Irritability", and "Fatigue". Five bridge symptoms were identified: "Sleep problems", "Restlessness", "Irritability", "Severity of sleep onset", and "Motor activity". The insomnia symptom, "Sleep dissatisfaction", had the strongest direct relation to quality of life. CONCLUSION: Insomnia symptoms played a critical role in the distress symptom network regarding node and bridge centrality as well as associations with quality of life among Macau residents. Close attention to these symptoms may be critical to reducing risk and preventing exacerbations in common forms of distress in this population.

Network analysis of depressive and anxiety symptoms in adolescents during the later stage of the COVID-19 pandemic.

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.

Prevalence of suicidality in clinically stable patients with major depressive disorder during the COVID-19 pandemic.

BACKGROUND: The COVID-19 pandemic is associated with an increased risk of mental health problems including suicide in many subpopulations, but its influence on stable patients with major depressive disorder (MDD) has been studied fleetingly. This study examined the one-year prevalence of suicidality including suicidal ideation (SI), suicide plans (SP), and suicide attempts (SA) as well as their correlates in clinically stable MDD patients during the COVID-19 pandemic. METHODS: A cross-sectional, observational study was conducted between October 1, 2020, and October 15, 2021, in six tertiary psychiatric hospitals. Socio-demographic information, clinical data and one-year prevalence of suicidality were recorded. RESULTS: Altogether, 1718 participants who met the eligibility criteria were included. The overall one-year prevalence of suicidality during the COVID-19 pandemic was 68.04% (95% confidence intervals (CI) =65.84-70.25%), with one-year SI prevalence of 66.4% (95%CI = 64.18-68.65%), SP prevalence of 36.26% (95%CI = 33.99-38.54%), and SA prevalence of 39.35% (95%CI = 37.04-41.66%). Binary logistic regression analyses revealed male gender, married marital status, college education level and above and age were negatively associated with risk of suicidality. Urban residence, unemployed work status, experiences of cyberbullying, a history of suicide among family members or friends, and more severe fatigue, physical pain, and residual depressive symptoms were positively associated with risk of suicidality. CONCLUSIONS: Suicidality is common among clinically stable MDD patients during the COVID-19 pandemic. Regular suicide screening and preventive measures should be provided to clinically stable MDD patients during the pandemic.