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.

Antidepressants for COVID-19: A systematic review.

OBJECTIVE: To systematically examine the efficacy and safety of antidepressants for the treatment of coronavirus disease 2019 (COVID-19). METHODS: A systematic search was performed independently by two researchers based on Chinese Journal Net, WanFang, PsycINFO, Cochrane Library, PubMed, and EMBASE. RESULTS: Seven studies (n = 92,947) including three retrospective studies (n = 91,083), two randomized clinical trials (RCTs, n = 1649), two prospective cohort study (n = 215) involving (n = 92,947) patients with COVID-19 were examined. For RCTs, fluvoxamine outperformed placebo in reducing clinical deterioration and hospitalisation for COVID-19 patients. For retrospective studies, antidepressants (2 studies) and fluoxetine (1 study) possibly reduced the risk of mortality in patients with COVID-19. Results from two remaining studies supported the superiority of fluvoxamine in reducing risk of mortality in COVID-19 patients. The two RCTs that examined the safety of fluvoxamine for COVID-19 patients found inconsistent results but no significant group differences in the dropout rate. CONCLUSION: This systematic review found emerging evidence for fluvoxamine in reducing the risk of mortality and hospitalisation in COVID-19 patients, but inconsistent evidence for the safety of fluvoxamine in COVID-19 patients. More studies are needed to determine the efficacy and safety of antidepressants for the treatment of COVID-19.

The backbone symptoms of depression: a network analysis after the initial wave of the COVID-19 pandemic in Macao.

Background: The coronavirus disease 2019 (COVID-19) pandemic disrupted the working lives of Macau residents, possibly leading to mental health issues such as depression. The pandemic served as the context for this investigation of the network structure of depressive symptoms in a community sample. This study aimed to identify the backbone symptoms of depression and to propose an intervention target. Methods: This study recruited a convenience sample of 975 Macao residents between 20th August and 9th November 2020. In an electronic survey, depressive symptoms were assessed with the Patient Health Questionnaire-9 (PHQ-9). Symptom relationships and centrality indices were identified using directed and undirected network estimation methods. The undirected network was constructed using the extended Bayesian information criterion (EBIC) model, and the directed network was constructed using the Triangulated Maximally Filtered Graph (TMFG) method. The stability of the centrality indices was evaluated by a case-dropping bootstrap procedure. Wilcoxon signed rank tests of the centrality indices were used to assess whether the network structure was invariant between age and gender groups. Results: Loss of energy, psychomotor problems, and guilt feelings were the symptoms with the highest centrality indices, indicating that these three symptoms were backbone symptoms of depression. The directed graph showed that loss of energy had the highest number of outward projections to other symptoms. The network structure remained stable after randomly dropping 50% of the study sample, and the network structure was invariant by age and gender groups. Conclusion: Loss of energy, psychomotor problems and guilt feelings constituted the three backbone symptoms during the pandemic. Based on centrality and relative influence, loss of energy could be targeted by increasing opportunities for physical activity.

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.

Sleep Disturbances and Their Association With Quality of Life in Older Psychiatric Patients During the COVID-19 Pandemic.

AIMS: The negative effect of the COVID-19 pandemic on sleep quality of clinically stable psychiatric patients is unknown. This study examined the prevalence of sleep disturbances and their association with quality of life (QOL) in clinically stable older psychiatric patients during the COVID-19 pandemic. METHODS: This multicenter, cross-sectional study involved older patients attending maintenance treatment at outpatient departments of four major psychiatric hospitals in China. Patients' socio-demographic and clinical characteristics were collected. Sleep disturbances, depressive symptoms, and QOL were assessed with the Insomnia Severity Index, the 9-item Patient Health Questionnaire, and 2 items of the World Health Organization Quality of Life-Brief version, respectively. Binary logistic regression analysis was conducted to examine the independent associations of socio-demographic and clinical variables with sleep disturbances, while the association between sleep disturbances and QOL was explored with analysis of covariance. RESULTS: A total of 941 patients were recruited. The prevalence of sleep disturbances was 57.1% (95% CI: 53.9-60.2%). Analysis of covariance revealed that QOL was significantly lower in patients with sleep disturbances compared to those without. Multivariate logistic regression analysis showed that sleep disturbances were positively and independently associated with more severe depressive symptoms (OR = 1.32, 95% CI: 1.26-1.37). Compared to patients with major depressive disorder, those with other psychiatric diagnoses had a significantly higher prevalence of sleep disturbances (OR = 1.44, 95% CI: 1.00-2.08). CONCLUSION: Sleep disturbances were common among clinically stable older psychiatric patients during the COVID-19 pandemic. Considering the negative association with QOL, this subpopulation needs regular assessment and timely treatment to reduce their sleep disturbances and improve their QOL.

Network Analysis of Depression, Anxiety, Posttraumatic Stress Symptoms, Insomnia, Pain, and Fatigue in Clinically Stable Older Patients With Psychiatric Disorders During the COVID-19 Outbreak.

OBJECTIVES: The Coronavirus Disease 2019 (COVID-19) pandemic has profound negative effects on the mental health of clinically stable older patients with psychiatric disorders. This study examined the influential nodes of psychiatric problems and their associations in this population using network analysis. METHODS: Clinically stable older patients with psychiatric disorders were consecutively recruited from four major psychiatric hospitals in China from May 22 to July 15, 2020. Depressive and anxiety syndromes (depression and anxiety hereafter), insomnia, posttraumatic stress symptoms (PTSS), pain, and fatigue were measured using the Patient Health Questionnaire, General Anxiety Disorder, Insomnia Severity Index, Posttraumatic Stress Disorder Checklist - Civilian Version, and Numeric Rating Scales for pain and fatigue, respectively. RESULTS: A total of 1063 participants were included. The network analysis revealed that depression was the most influential node followed by anxiety as indicated by the centrality index of strength. In contrast, the edge connecting depression and anxiety was the strongest edge, followed by the edge connecting depression and insomnia, and the edge connecting depression and fatigue as indicated by edge-weights. The network structure was invariant by gender based on the network structure invariance test (M = .14, P = .20) and global strength invariance tests (S = .08, P = .30). CONCLUSIONS: Attention should be paid to depression and its associations with anxiety, insomnia, and fatigue in the screening and treatment of mental health problems in clinically stable older psychiatric patients affected by the COVID-19 pandemic.

Prevalence of Suicidality and its Association with Quality of Life in Older Patients with Clinically Stable Psychiatric Disorders in China During the COVID-19 Pandemic.

AIMS: The pattern of suicidality in older patients with psychiatric disorders during the COVID-19 pandemic is not clear. This study examined the prevalence of suicidality and its association with quality of life (QOL) among older clinically stable patients with psychiatric disorders during the COVID-19 pandemic. METHODS: A multicenter, cross-sectional study was conducted from May 22 to July 15, 2020, among four major tertiary psychiatric hospitals in China. Suicidality was assessed by asking 3 standardized questions. Depressive symptoms, pain, and QOL were assessed with the 9-item Patient Health Questionnaire (PHQ-9), the numeric pain rating scale (NPRS), and the World Health Organization Quality of Life Questionnaire-brief version, respectively. RESULTS: A total of 1063 clinically stable patients participated and completed the assessment. The prevalence of suicidality was 11.8% (95% CI: 9.9%-13.7%) during the COVID-19 pandemic. Multiple logistic regression analysis revealed that poor treatment adherence (P = .009, OR = 1.86, 95% CI: 1.17-2.96) and perceived illness worsening during the COVID-19 outbreak (P = .02, OR = 2.07, 95% CI: 1.15-3.73), being diagnosed with major depressive disorder (P < .001, OR = 2.79, 95% CI: 1.68-4.64), PHQ-9 total score (P < .001, OR = 1.20, 95% CI: 1.15-1.24) and NPRS total score (P = .002, OR = 1.17, 95% CI: 1.06-1.29) were associated with higher risk of suicidality. After controlling for covariates, older psychiatric patients with suicidality had lower QOL compared to those without (F(1, 1063) =16.5, P<.001). CONCLUSIONS: Suicidality was common in older patients with clinically stable psychiatric disorders during the COVID-19 pandemic. Considering its negative impact on QOL and personal suffering, routine screening and preventive suicide measures should be implemented for older psychiatric patients.

Network Analysis of Insomnia in Chinese Mental Health Professionals During the COVID-19 Pandemic: A Cross-Sectional Study.

PURPOSE: The coronavirus disease 2019 (COVID-19) pandemic is associated with increased risk of insomnia symptoms (insomnia hereafter) in health-care professionals. Network analysis is a novel approach in linking mechanisms at the symptom level. The aim of this study was to characterize the insomnia network structure in mental health professionals during the COVID-19 pandemic. PATIENTS AND METHODS: A total of 10,516 mental health professionals were recruited from psychiatric hospitals or psychiatric units of general hospitals nationwide between March 15 and March 20, 2020. Insomnia was assessed with the insomnia severity index (ISI). Centrality index (ie, strength) was used to identify symptoms central to the network. The stability of network was examined using a case-dropping bootstrap procedure. The network structures between different genders were also compared. RESULTS: The overall network model showed that the item ISI7 (interference with daytime functioning) was the most central symptom in mental health professionals with the highest strength. The network was robust in stability and accuracy tests. The item ISI4 (sleep dissatisfaction) was connected to the two main clusters of insomnia symptoms (ie, the cluster of nocturnal and daytime symptoms). No significant gender network difference was found. CONCLUSION: Interference with daytime functioning was the most central symptom, suggesting that it may be an important treatment outcome measure for insomnia. Appropriate treatments, such as stimulus control techniques, cognitive behavioral therapy and relaxation training, could be developed. Moreover, addressing sleep satisfaction in treatment could simultaneously ameliorate daytime and nocturnal symptoms.

Prevalence of Post-traumatic Stress Symptoms and Its Associations With Quality of Life, Demographic and Clinical Characteristics in COVID-19 Survivors During the Post-COVID-19 Era.

Background: The prevalence of post-traumatic stress symptoms (PTSS) in COVID-19 survivors is unclear. This study examined the prevalence of PTSS and its association with quality of life (QOL) among COVID-19 survivors during the post-COVID-19 era in China. Methods: This was a comparative, cross-sectional study. PTSS, depressive symptoms, and QOL were assessed with standardized instruments. Results: A total of 134 COVID-19 survivors and 214 non-infected controls (healthy controls hereafter) were recruited. Among COVID-19 survivors, the PTSS prevalence was 18.66% (95%CI: 11.98-25.34%), which was significantly higher than that (5.61%, 95%CI: 2.50-8.71%) of healthy controls (P < 0.001). After controlling for covariates, an analysis of covariance (ANCOVA) showed that COVID-19 survivors had a higher PTSS total score than did healthy controls [F (1,348) = 4.664, P = 0.032]. A separate ANCOVA revealed there were no significant differences in overall QOL between COVID-19 survivors with and without PTSS [F (1,348) = 1.067, P = 0.304]. A multiple logistic regression analysis showed that more severe depressive symptoms were significantly associated with PTSS in COVID-19 survivors (OR = 1.425, P < 0.001). Conclusions: PTSS were more severe in COVID-19 survivors compared to healthy controls in the post-COVID-19 era. Considering their negative impact on daily life and functional outcomes, regular assessment and appropriate treatments of PTSS should be conducted in COVID-19 survivors.

COVID-19-related stigma and its sociodemographic correlates: a comparative study.

BACKGROUND: Coronavirus disease 2019 (COVID-19) is closely associated with physical and mental health problems; however, little is known about the severity of stigma caused by COVID-19 among its survivors. Thus, the aim of this study was to compare differences in stigma experiences of COVID-19 survivors versus healthy controls after the COVID-19 outbreak peak in China. METHODS: This cross-sectional study comprised 154 COVID-19 survivors and 194 healthy controls recruited through consecutive and convenience sampling methods, respectively. COVID-19 related stigma was measured by the Social Impact Scale (SIS). Stigma differences between the two groups were compared with analysis of covariance (ANCOVA) and a generalized linear model (GLM) was used to identify independent correlates of COVID-19-related stigma in this study. RESULTS: Compared with healthy controls, COVID-19 survivors reported more overall stigma (F(1,347) = 60.82, p < 0.001), and stigma in domains of social rejection (F(1,347) = 56.54, p < 0.001), financial insecurity (F(1,347) = 19.96, p < 0.001), internalized shame (F(1,347) = 71.40, p < 0.001) and social isolation (F(1,347) = 34.73, p < 0.001). Status as a COVID-19 survivor, having family members infected with COVID-19, being married, economic loss during the COVID-19 pandemic, and depressive symptoms were positively associated with higher overall stigma levels (all p values < 0.05). CONCLUSION: COVID-19-related stigma is commonly experienced among COVID-19 survivors even though the outbreak has been well-contained in China. Routine assessment of stigma experiences should be conducted on COVID-19 survivors and appropriate psychological assistance, public education, and anti-stigma campaigns and policies should be enforced to reduce stigma within this vulnerable subpopulation.

Should people with severe mental illness be prioritized for the COVID-19 vaccination?

The coronavirus disease-19 (COVID-19) has spread throughout the world, affecting many vulnerable populations including patients with severe mental illness (SMI). Recent studies have found that patients with SMI compared to the general population could have a greater risk of morbidity and mortality from COVID-19 due to cognitive impairment, poor awareness of risk, and difficulties in complying with infection control measures. Although some researchers have suggested that patients with SMI should be prioritized for COVID-19 vaccination to reduce the risk of infection, this issue remains controversial.

Prevalence of depression and its impact on quality of life in frontline otorhinolaryngology nurses during the COVID-19 pandemic in China.

OBJECTIVE: Exposure to the coronavirus disease 2019 (COVID-19) was associated with high risk of mental health problems among frontline nurses. This study examined the prevalence of depressive symptoms (depression hereafter) and its impact on quality of life (QOL) in otorhinolaryngology (ENT) nurses during the COVID-19 pandemic in China. METHODS: An online study was conducted between March 15 and March 20, 2020. Depression and QOL were assessed using standardized instruments. RESULTS: A total of 1,757 participants were recruited. The prevalence of depression was 33.75% (95% CI: 31.59%-35.97%). Results emerging from multiple logistic regression analysis showed that direct care of COVID-19 patients (OR: 1.441, 95% CI: 1.031-2.013, P = 0.032), and current smoking (OR: 2.880, 95% CI: 1.018-8.979, P = 0.048) were significantly associated with depression. After controlling for covariates, ENT nurses with depression had a lower overall QOL compared to those without depression (F(1, 1757)= 536.80, P < 0.001). CONCLUSIONS: Depression was common among ENT nurses during the COVID-19 pandemic in China. Considering the negative impact of depression on QOL and care quality, regular screening for depression should be conducted in ENT nurses and treatment should be provided.

The prevalence of psychiatric comorbidities during the SARS and COVID-19 epidemics: a systematic review and meta-analysis of observational studies.

The coronavirus disease 2019 (COVID-19) and Severe Acute Respiratory Syndrome (SARS) are associated with various psychiatric comorbidities. This is a systematic review and meta-analysis comparing the prevalence of psychiatric comorbidities in all subpopulations during the SARS and COVID-19 epidemics. A systematic literature search was conducted in major international (PubMed, EMBASE, Web of Science, PsycINFO) and Chinese (China National Knowledge Internet [CNKI] and Wanfang) databases to identify studies reporting prevalence of psychiatric comorbidities in all subpopulations during the SARS and COVID-19 epidemics. Data analyses were conducted using the Comprehensive Meta-Analysis Version 2.0 (CMA V2.0). Eighty-two studies involving 96,100 participants were included. The overall prevalence of depressive symptoms (depression hereinafter), anxiety symptoms (anxiety hereinafter), stress, distress, insomnia symptoms, post-traumatic stress symptoms (PTSS) and poor mental health during the COVID-19 epidemic were 23.9% (95% CI: 18.4%-30.3%), 23.4% (95% CI: 19.9%-27.3%), 14.2% (95% CI: 8.4%-22.9%), 16.0% (95% CI: 8.4%-28.5%), 26.5% (95% CI: 19.1%-35.5%), 24.9% (95% CI: 11.0%-46.8%), and 19.9% (95% CI: 11.7%-31.9%), respectively. Prevalence of poor mental health was higher in general populations than in health professionals (29.0% vs. 11.6%; Q=10.99, p=0.001). The prevalence of depression, anxiety, PTSS and poor mental health were similar between SARS and COVID-19 epidemics (all p values>0.05). Psychiatric comorbidities were common in different subpopulations during both the SARS and COVID-19 epidemics. Considering the negative impact of psychiatric comorbidities on health and wellbeing, timely screening and appropriate interventions for psychiatric comorbidities should be conducted for subpopulations affected by such serious epidemics.

Depression and its relationship with quality of life in frontline psychiatric clinicians during the COVID-19 pandemic in China: a national survey.

This was a national survey that determined the prevalence of depressive symptoms (depression thereafter) and its relationship with quality of life (QOL) in frontline clinicians working in psychiatric hospitals in China during the COVID-19 pandemic. Depression and QOL were assessed using the Patient Health Questionnaire nine items (PHQ-9) and the World Health Organization Quality of Life Questionnaire-brief version (WHOQOL-BREF), respectively. Multivariable logistic regression analyses and analysis of covariance were used. A total of 10,516 frontline clinicians participated in this study, of which, 28.52% (n=2,999) met screening criteria for depression. Compared to those without depression, clinicians with depression had a lower quality of life (F(1, 10515) =2874.66, P<0.001). Higher educational level (OR=1.225, P=0.014), if the number of COVID-19 patients in the hospital catchment area surpassed 500 (OR=1.146, P=0.032), having family/friends/colleagues who were infected (OR=1.695, P<0.001), being a current smoker (OR=1.533, P<0.001), and longer working hours (OR=1.020, P=0.022) were independently associated with higher risk of depression. Living with family members (OR=0.786, P<0.001), and being junior clinicians (OR=0.851, P=0.011) were independently associated with lower odds of depression. The results showed that depression was common in frontline psychiatric clinicians during the COVID-19 pandemic. Timely assessment and effective interventions of depression for frontline clinicians in psychiatric hospitals were warranted.