Prevalence of insomnia and its association with quality of life in caregivers of psychiatric inpatients during the COVID-19 pandemic: a network analysis.

BACKGROUND: Studies on sleep problems among caregivers of psychiatric patients, especially during the COVID-19 pandemic, are limited. This study examined the prevalence and correlates of insomnia symptoms (insomnia hereafter) among caregivers of psychiatric inpatients during the COVID-19 pandemic as well as the association with quality of life (QoL) from a network analysis perspective. METHODS: A multi-center cross-sectional study was conducted on caregivers of inpatients across seven tertiary psychiatric hospitals and psychiatric units of general hospitals. Network analysis explored the structure of insomnia using the R program. The centrality index of "Expected influence" was used to identify central symptoms in the network, and the "flow" function was adopted to identify specific symptoms that were directly associated with QoL. RESULTS: A total of 1,101 caregivers were included. The overall prevalence of insomnia was 18.9% (n = 208; 95% CI = 16.7-21.3%). Severe depressive (OR = 1.185; P < 0.001) and anxiety symptoms (OR = 1.099; P = 0.003), and severe fatigue (OR = 1.320; P < 0.001) were associated with more severe insomnia. The most central nodes included ISI2 ("Sleep maintenance"), ISI7 ("Distress caused by the sleep difficulties") and ISI1 ("Severity of sleep onset"), while "Sleep dissatisfaction" (ISI4), "Distress caused by the sleep difficulties" (ISI7) and "Interference with daytime functioning" (ISI5) had the strongest negative associations with QoL. CONCLUSION: The insomnia prevalence was high among caregivers of psychiatric inpatients during the COVID-19 pandemic, particularly in those with depression, anxiety and fatigue. Considering the negative impact of insomnia on QoL, effective interventions that address insomnia and alteration of sleep dissatisfaction should be developed.

Oral health in patients with dementia: A meta-analysis of comparative and observational studies.

OBJECTIVE: Poor oral health is common in dementia, but findings of epidemiological studies have been inconsistent. This meta-analysis examined oral health in patients with dementia diagnosed according to standardized diagnostic criteria. METHODS: Six international databases (PubMed, EMBASE, PsycINFO, Medline, Cochrane Library, and Web of Science) were searched from their commencement date until 8 November 2018. Oral health was measured by the Remaining Teeth (RT) and Decayed, Missing, and Filled Teeth (DMFT) Index. The mean differences (MD) and 95% confidence intervals (CI) of DMFT Index total and component scores were calculated using a random-effect model. RESULTS: Twenty-four studies were included for analyses. The pooled DMFT Index was 23.48 (95% CI: 22.34, 24.62), while the pooled score for each component was 2.38 (95% CI: 1.56, 3.20) in decayed teeth (DT), 18.39 (95% CI: 15.92, 20.87) in missing teeth (MT), 2.29 (95% CI: 0.62, 3.95) in filled teeth (FT), and 11.59 (95% CI: 9.14, 14.05) in RT. Compared to controls, people with dementia had significantly a higher DMFT Index total score (MD = 3.80, 95% CI: 2.21, 5.39, p < 0.00,001), and significantly lower number of RT (MD = -3.15, 95% CI: -4.23, -2.06, p < 0.00,001). Subgroup analyses revealed that higher DMFT Index score was significantly associated with year of survey (>2010), study design (case-control study), percentage of females (≤54.3), and the Mini Mental State Examination score (≤18.2). Higher MT score was significantly associated with study design (cross-sectional study), and lower FT score was significantly associated with year of survey (>2010). CONCLUSIONS: Oral health was significantly poorer in people with dementia compared with controls. Regular screening and effective treatment should be implemented for this population.

Prevalence of problematic Internet use and its association with quality of life among undergraduate nursing students in the later stage of COVID-19 pandemic era in China.

BACKGROUND AND OBJECTIVES: The prevalence of problematic Internet use (PIU) in the post-COVID-19 pandemic era is not known. This cross-sectional study aimed to determine the prevalence of PIU among baccalaureate nursing students (hereafter: nursing students) in the post-COVID-19 era. METHODS: A total of 1070 nursing students were consecutively invited to participate in this study from the nursing schools of five universities. PIU and quality of life (QOL) were assessed using the Internet Addiction Test (IAT) and the World Health Organization Quality of Life Scale Brief Version (WHOQOL-BREF), respectively. t Tests, χ2 , tests, and Kruskal-Wallis tests were used to compare basic demographic and clinical characteristics between participants with and without PIU. Binary logistic regression analysis was used to examine independent correlates. RESULTS: The prevalence of PIU was 23.3% (95% confidence interval [CI]: 20.7%-25.8%). Multiple logistic regression analysis revealed that second- (p = .024) and third-year (p = .012) students were more likely to suffer from PIU compared with first year students. Students with more severe depressive (p = .014) and anxiety symptoms (p = .011) were independently and significantly associated with more severe PIU. After controlling for covariates, nursing students with PIU had a lower overall QOL score (p = .002). CONCLUSION AND SCIENTIFIC SIGNIFICANCE: Problematic Internet use (PIU) was common among nursing students in the post-COVID-19 era. Considering the negative impact of PIU on QOL and academic performance, regular screening should be conducted and effective interventions implemented for nursing students with PIU. This was the first study on the prevalence of PIU among nursing students in the post-COVID-19 era. The findings of this study could help health professionals and education authorities to understand the patterns of PIU and its influence on QOL among nursing students and to allocate health resources and develop effective measures to reduce the risk of PIU in this population.

The Prevalence of Burnout and its Associations with Demographic Correlates and Quality of Life among Psychiatric Nurses in China.

This study examined the prevalence of burnout and its association with quality of life (QOL) among psychiatric nurses in China.Ten psychiatric hospitals were included. Burnout and QOL were measured using standardized instruments. Altogether, 1449 nurses completed the assessment. The mean scores of emotional exhaustion (EE), depersonalization (DP) and personal accomplishment (PA) were 11.87 (SD = 6.72), 6.98 (SD = 5.71) and 22.06 (SD = 8.67), respectively. Of the participants, 59.8% (95% CI: 57-62%) experienced burnout; with 23.3% (95% CI: 21-25%) in EE, 14.6% (95% CI: 13-16%) in DP and 45.1% (95% CI: 43-48%) in PA. Psychiatric nurses who reported burnout had lower QOL in social (F (1, 1448) = 86.20, P < 0.001), physical (F (1, 1448) = 170.46, P < 0.001), psychological (F (1, 1448) = 205.63, P < 0.001), and environmental (F (1, 1448) = 120.24, P < 0.001) domains. Multiple logistic regression analysis revealed that alcohol users (P = 0.04; OR = 1.29, 95%CI: 1.01-1.64 in model 1 and P = 0.03; OR = 1.32, 95%CI: 1.04-1.69 in model 2) were significantly more susceptible to burnout, while senior nurses (P = 0.007; OR = 0.70, 95%CI: 0.53-0.91) and nurses with longer work experience (P = 0.02; OR = 0.70, 95%CI: 0.53-0.91) were less likely to develop burnout. Burnout is common in psychiatric nurses in China. In light of its negative impact on health and QOL, there is an urgent need for regular screening as well as effective preventive measures and interventions to reduce burnout within this at-risk occupational group.

Prevalence of Poor Sleep Quality in Nursing Staff: A Meta-Analysis of Observational Studies.

Objective: Poor sleep quality is common in nursing staff. This meta-analysis aimed to examine the pooled prevalence of poor sleep quality in nursing staff. Methods: A systematic search in PubMed, EMBASE, PsycINFO, and Web of Science databases was performed. Studies that reported sleep quality measured by the Pittsburgh Sleep Quality Index (PSQI) were synthesized using a random-effects model. Results: Fifty-three studies were analyzed. The pooled prevalence of poor sleep quality was 61.0% (95% CI: 55.8-66.1%). The pooled total PSQI score was 7.13 ± 0.18 (95% CI: 6.78-7.50). The pooled component scores were 1.47 ± 0.20 (95% CI of mean score: 1.08-1.85) in sleep latency, 0.91 ± 0.15 (95% CI of mean score: 0.61-1.21) in sleep duration, 1.59 ± 0.13 (95% CI of mean score: 1.35-1.84) in overall sleep disturbances, 0.33 ± 0.18 (95% CI of mean score: 0-0.67) in sleeping medication, 1.21 ± 1.20 (95% CI of mean score: 0.83-1.60) in daytime dysfunction, 1.39 ± 0.14 (95% CI of mean score: 1.11-1.67) in subjective sleep quality, and 0.66 ± 0.11 (95% CI of mean score: 0.44-0.87) in habitual sleep efficiency. Subgroup and meta-regression analyses found that PSQI cutoff values, mean age, body mass index (BMI), sample size, study quality, and work experience moderated the prevalence of poor sleep quality. Conclusions: Poor sleep quality appears to be common in nursing staff. Considering its negative impact on health, effective measures should be taken to improve poor sleep quality in this population. Longitudinal studies should be conducted to examine the contributing factors of nurses' poor sleep quality.

Prevalence of sexual harassment toward psychiatric nurses and its association with quality of life in China.

OBJECTIVE: This study aimed to examine the prevalence of sexual harassment (SH) toward Chinese psychiatric nurses and its association with quality of life (QOL). METHODS: A total of 2124 psychiatric nurses were consecutively recruited from 10 psychiatric hospitals distributed across 10 provinces of China; of them, 1,449 were included for analyses. Participants' socio-demographic characteristics, experiences of workplace SH in the past year, and QOL were recorded. RESULTS: Overall, 21.5% (n = 311) of participants reported SH, with 8.4% (n = 121) reporting once, 7.1% (n = 103) reporting twice and 6.0% (n = 87) reporting three times or more. Psychiatric nurses who experienced SH had lower QOL in physical, psychological, social, and environmental domains. Multiple logistic regression analysis found that nurses with shorter clinical experience were more likely to experience SH. CONCLUSIONS: Workplace SH toward psychiatric nurses is common in mental health treatment settings in China. Considering its deleterious impact on nurses' well-being and care quality, effective staff training on the management of SH and a zero tolerance policy against SH should be developed for this population.

Treatment Rate of Schizophrenia in China: a Meta-Analysis of Epidemiological Studies.

Effective and prompt medication treatment is essential for schizophrenia patients to alleviate psychotic symptoms and improve prognosis. The treatment rate of schizophrenia usually varies greatly across studies. This is a meta-analysis that examined the overall treatment rate of schizophrenia in China. Both international (PubMed, EMBASE, PsycINFO, Web of Science) and Chinese (CNKI, WanFang and Sinomed) databases were searched. The random effects model was used to analyze the data. Fifteen studies with 1,219,472 patients were included. This meta-analysis found that 73% (95%CI: 66%, 80%) of schizophrenia patients received treatment in any type of medical institutions, while 31.0% (95%CI = 21.0%, 41.0%) received treatment in psychiatric institutions. Studies conducted in middle region of China (76.8% for any type of medical institutions; 42.6% for psychiatric institutions) and those published before 2007 (74.6% for any type of medical institutions; 31.3% for psychiatric institutions) reported significantly higher treatment rates. Studies using combined diagnostic instruments had a higher treatment rate of schizophrenia (72.0%) in any type of medical institutions, while using the Chinese classification of Mental Disorders (47.7%) and including both rural and urban areas (35.7%) had higher treatment rates of schizophrenia in psychiatric institutions. The treatment rate of schizophrenia was relatively high in China, but most treatments were delivered in non-psychiatric medical institutions. Greater efforts should be made to improve the provision of accessible mental health services for schizophrenia patients in this part of the world.

Sleep duration and self-rated health in Chinese university students.

PURPOSE: Little is known about the association between sleep duration and health status in Chinese university students. This study examined the association between sleep duration and self-rated health in university students in China. METHODS: Altogether, 2312 subjects (928 in Macao, 446 in Hong Kong, and 938 in mainland China) were recruited. Standardized measures of sleep and self-reported health were administered. Sleep duration was categorized in the following way: < 6 h/day, 6 to < 7 h/day, 7-9 h/day, and > 9 h/day. RESULTS: Overall, 71% of university students reported poor health, 53% slept 7-9 h/day, 14% slept less than 6 h/day, 32% slept 6 to < 7 h/day, and 1% slept > 9 h/day. Univariate analysis revealed that compared to students with medium sleep duration (7-9 h/day), those with short sleep duration (< 6 h/day and 6 to < 7 h/day) were more likely to report poor health. Multivariate logistic regression analysis found that after controlling for age, gender, body mass index, university location, being a single child, religious beliefs, interest in academic major, academic pressure, nursing major, pessimism about the future, and depression, sleep duration of less than 6 h/day (odds ratio (OR) 1.98, 95% confidence interval (CI) 1.34-2.92, p < 0.01) was independently and significantly associated with poor self-reported health. CONCLUSIONS: Poor health status is common in Chinese university students, which appears to be closely associated with short sleep duration. Further longitudinal studies are warranted to gain a better understanding of the interaction between sleep patterns and health status in university students.

Prevalence of verbal and physical workplace violence against nurses in psychiatric hospitals in China.

OBJECTIVE: Workplace violence (WPV) is common in mental health services in China, but its multi-center prevalence measured using standardized rating scales has rarely been reported. This study aimed to explore the prevalence of verbal and physical violence against nurses working in psychiatric hospitals and examine its independent socio-demographic correlates in China. METHODS: This was a cross-sectional study conducted in 11 major psychiatric hospitals in China using a 9-item self-reported workplace violence scale. RESULTS: A total of 1906 psychiatric nurses were recruited to participate in this study. The one-year prevalence of verbal and/or physical workplace violence (WPV) was 84.2% (95% CI: 82.4-85.8). The prevalence rates of verbal abuse, threats and physical violence were 79.3% (95% CI: 77.4-81.1), 70.9% (95% CI: 68.8-73.0) and 57.9% (95% CI: 55.7-60.2), respectively. Multiple logistic regression analysis revealed that working in department of psychiatry (OR = 3.42, P < 0.001), having moderate (OR = 2.05, P = 0.009), severe (OR = 2.04, P = 0.015) or extremely severe (OR = 3.21, P < 0.001) anxiety level of WPV and working in hospitals with a WPV reporting system (OR = 1.88, P < 0.001) were significantly associated with WPV. CONCLUSION: WPV against nurses is a serious occupational and public health concern in Chinese psychiatric hospitals. Appropriate preventive measures should be undertaken to reduce the risk of WPV in healthcare settings.

Treatment Rate for Major Depressive Disorder in China: a Meta-Analysis of Epidemiological Studies.

Major depressive disorder (MDD) is a common psychiatric disorder in China, but its reported treatment rate varies largely across different studies. The objective of this meta-analysis was to determine the pooled treatment rate for people with MDD in China and its associated factors. Both English (PubMed, Cochrane Library, PsycINFO, Web of Science) and Chinese (Chinese National Knowledge Infrastructure, WanFang and SinoMed) databases were searched from their commencement date to November 13, 2018. Epidemiological studies that reported the treatment rate of MDD were included and synthesized using a random effects model. Fifteen studies covering 609,054 participants were included. The pooled treatment rate for MDD in China was 19.5% (95% CI: 10.7%-28.4%). Among the 15 studies, 9 reported the number of patients who received treatments in psychiatric hospitals with a pooled treatment rate of 5.2% (95% CI: 2.8%-7.5%). Meta-regression found that study quality (ß = 0.131, P = 0.028) and male gender (ß = 0.006, P = 0.039) were significantly associated with a higher treatment rate for MDD. In China, the treatment rate for MDD, particularly in psychiatric hospitals, was low. Effective public education and increasing access to mental health services will probably increase the number of people seeking and receiving treatment.

Hyperprolactinemia, prolactin-related side effects and quality of life in Chinese psychiatric patients.

PURPOSE: To examine the frequency of hyperprolactinemia and the socio-demographic, clinical, and quality of life (QOL) correlates. The frequency of prolactin-related side effects and associated subjective experiences were also examined. METHODS: A cohort of 1364 psychiatric inpatients were consecutively recruited and evaluated. Basic socio-demographic and clinical data were collected. Psychopathology, prolactin-related side effects were measured using standardized instruments. QOL was assessed using the Medical Outcomes Study Short Form 12. RESULTS: The frequency of hyperprolactinemia was 61.3% in the whole sample; 61.6% in female and 60.8% in male patients. There was no significant association between hyperprolactinemia and any QOL domain. In the whole sample, 15.1% of patients reported moderately severe breast symptoms and lactation, and 53.9% reported moderate or severe discomfort. Nearly a third of female patients (30.4%) reported at least moderate menstrual changes and 50.2% moderate or severe discomfort, while 24.2% of male patients reported at least moderate erectile dysfunction and 52.6% moderate or severe discomfort. Multiple logistic regression analysis revealed that patients with hyperprolactinemia were less likely to be married, diagnosed with mood disorders, or treated with clozapine, aripiprazole, or antidepressants but more likely to receive risperidone. CONCLUSIONS: Effective measures to lower the frequency of hyperprolactinemia and the related side effects should be considered in Chinese psychiatric facilities.

Prevalence of nurses' smoking habits in psychiatric and general hospitals in China.

This study determined the prevalence of lifetime and current smoking and the correlates of current smoking in nurses working in psychiatric and general hospitals in China. Of 807 distributed questionnaires, 799 nurses who were working in two psychiatric hospitals (n=387, 48.4%), and one general hospital (n=412, 51.6%) had analyzable data. Socio-demographic, alcohol use and smoking data were collected with a self-reported questionnaire. Work-related stress was evaluated with the Nurse Stress Inventory. In the whole sample, the lifetime smoking prevalence was 7.6% (females=2.1% vs. males=48.9%, p<0.0001; psychiatric nurses=14.5% vs. non-psychiatric nurses=1.2%, p<0.0001). The prevalence of current smoking was 7.1% (females=2.1% vs. males=44.7%, p<0.0001; psychiatric nurses=13.4% vs. non-psychiatric nurses=1.2%, p<0.0001). In a multiple logistic regression analysis, age 30 years or older, male gender, having children, being a psychiatric nurse and alcohol consumption were positively associated with smoking, while being a nursing officer was negatively associated with smoking (r(2) = 0.513, p<0.0001). Considering the harmful effects of smoking as well as second-hand smoking in the presence of children, effective measures to promote smoking cessation for male, older and psychiatric nurses and those with children are warranted.

The Inter-Relationships Between Depressive Symptoms and Suicidality Among Macau Residents After the "Relatively Static Management" COVID-19 Strategy: A Perspective of Network Analysis.

Background: Suicidality is a global public health problem which has increased considerably during the coronavirus disease 2019 (COVID-19) pandemic. This study examined the inter-relationships between depressive symptoms and suicidality using network analysis among Macau residents after the "relatively static management" COVID-19 strategy. Methods: An assessment of suicidal ideation (SI), suicide plan (SP), suicide attempt (SA) and depressive symptoms was conducted with the use of individual binary response items (yes/no) and Patient Health Questionnaire (PHQ-9). In the network analysis, central and bridge symptoms were identified in the network through "Expected Influence" and "Bridge Expected Influence", and specific symptoms that were directly associated with suicidality were identified via the flow function. Network Comparison Tests (NCT) were conducted to examine the gender differences in network characteristics. Results: The study sample included a total of 1008 Macau residents. The prevalence of depressive symptoms and suicidality were 62.50% (95% CI = 59.4-65.5%) and 8.9% (95% CI = 7.2-10.9%), respectively. A network analysis of the sample identified SI ("Suicidal ideation") as the most central symptom, followed by SP ("Suicide plan") and PHQ4 ("Fatigue"). SI ("Suicidal ideation") and PHQ6 ("Guilt") were bridge nodes connecting depressive symptoms and suicidality. A flow network revealed that the strongest connection was between S ("Suicidality") and PHQ6 ("Guilt"), followed by S ("Suicidality") and PHQ 7 ("Concentration"), and S ("Suicidality") and PHQ3 ("Sleep"). Conclusion: The findings indicated that reduction of specific depressive symptoms and suicidal thoughts may be relevant in decreasing suicidality among adults. Further, suicide assessment and prevention measures should address the central and bridge symptoms identified in this study.

A comparison of psychiatric symptoms between mental health professionals with and without post-infection sequelae of COVID-19.

Post-infection sequelae of COVID-19 (PISC) have raised public health concerns. However, it is not clear whether infected mental health professionals (MHPs) with PISC have experienced more psychiatric symptoms than MHPs without PISC do. This study examined differences in the prevalence of self-reported depression, anxiety, insomnia and suicidality as well as the network structures of these symptoms between these two groups. Participants completed questionnaire measures of psychiatric symptoms and demographics. Expected influence was used to measure centrality of symptoms and network comparison tests were adopted to compare differences in the two network models. The sample comprised 2,596 participants without PISC and 2,573 matched participants with PISC. MHPs with PISC had comparatively higher symptom levels related to depression (55.2% vs. 23.5 %), anxiety (32.0% vs. 14.9 %), insomnia (43.3% vs. 17.3 %), and suicidality (9.6% vs. 5.3 %). PHQ4 ("Fatigue"), PHQ6 ("Guilt"), and GAD2 ("Uncontrollable Worrying") were the most central symptoms in the "without PISC" network model. Conversely, GAD3 ("Worry too much"), GAD5 ("Restlessness"), and GAD4 ("Trouble relaxing") were more central in the "with PISC" network model. In sum, MHPs with PISC experienced comparatively more psychiatric symptoms and related disturbances. Network results provide foundations for the expectation that MHPs with PISC may benefit from interventions that address anxiety-related symptoms, while those without PISC may benefit from interventions targeting depression-related symptoms.

Depression, anxiety and suicidality among Chinese mental health professionals immediately after China's dynamic zero-COVID policy: A network perspective.

BACKGROUND: Using network analysis, the interactions between mental health problems at the symptom level can be explored in depth. This study examined the network structure of depressive and anxiety symptoms and suicidality among mental health professionals after the end of China's Dynamic Zero-COVID Policy. METHODS: A total of 10,647 mental health professionals were recruited nationwide from January to February 2023. Depression and anxiety were assessed using the 9-item Patient Health Questionnaire (PHQ-9) and 7-item Generalized Anxiety Disorder Scale (GAD-7), respectively, while suicidality was defined by a 'yes' response to any of the standard questions regarding suicidal ideation (SI), suicide plan (SP) and suicide attempt (SA). Expected Influence (EI) and Bridge Expected Influence (bEI) were used as centrality indices in the symptom network to characterize the structure of the symptoms. RESULTS: The prevalence of depression, anxiety, and suicidality were 45.99 %, 28.40 %, and 7.71 %, respectively. The network analysis identified GAD5 ("Restlessness") as the most central symptom, followed by PHQ4 ("Fatigue") and GAD7 ("Feeling afraid"). Additionally, PHQ6 ("Guilt"), GAD5 ("Restlessness"), and PHQ8 ("Motor disturbance") were bridge nodes linking depressive and anxiety symptoms with suicidality. The flow network indicated that the strongest connections of S ("Suicidality") was with PHQ6 ("Guilt"), GAD7 ("Feeling afraid"), and PHQ2 ("Sad mood"). CONCLUSIONS: Depression, anxiety, and suicidality among mental health professionals were highly prevalent after China's Dynamic Zero-COVID Policy ended. Effective measures should target central and bridge symptoms identified in this network model to address the mental health problems in those at-risk.

Prevalence and network structure of depression, insomnia and suicidality among mental health professionals who recovered from COVID-19: a national survey in China.

Psychiatric syndromes are common following recovery from Coronavirus Disease 2019 (COVID-19) infection. This study investigated the prevalence and the network structure of depression, insomnia, and suicidality among mental health professionals (MHPs) who recovered from COVID-19. Depression and insomnia were assessed with the Patient Health Questionnaire (PHQ-9) and Insomnia Severity Index questionnaire (ISI7) respectively. Suicidality items comprising suicidal ideation, suicidal plan and suicidal attempt were evaluated with binary response (no/yes) items. Network analyses with Ising model were conducted to identify the central symptoms of the network and their links to suicidality. A total of 9858 COVID-19 survivors were enrolled in a survey of MHPs. The prevalence of depression and insomnia were 47.10% (95% confidence interval (CI) = 46.09-48.06%) and 36.2% (95%CI = 35.35-37.21%), respectively, while the overall prevalence of suicidality was 7.8% (95%CI = 7.31-8.37%). The key central nodes included "Distress caused by the sleep difficulties" (ISI7) (EI = 1.34), "Interference with daytime functioning" (ISI5) (EI = 1.08), and "Sleep dissatisfaction" (ISI4) (EI = 0.74). "Fatigue" (PHQ4) (Bridge EI = 1.98), "Distress caused by sleep difficulties" (ISI7) (Bridge EI = 1.71), and "Motor Disturbances" (PHQ8) (Bridge EI = 1.67) were important bridge symptoms. The flow network indicated that the edge between the nodes of "Suicidality" (SU) and "Guilt" (PHQ6) showed the strongest connection (Edge Weight= 1.17, followed by "Suicidality" (SU) - "Sad mood" (PHQ2) (Edge Weight = 0.68)). The network analysis results suggest that insomnia symptoms play a critical role in the activation of the insomnia-depression-suicidality network model of COVID-19 survivors, while suicidality is more susceptible to the influence of depressive symptoms. These findings may have implications for developing prevention and intervention strategies for mental health conditions following recovery from COVID-19.

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.

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.

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.

Prevalence, correlates, and network analysis of depression and its associated quality of life among ophthalmology nurses during the COVID-19 pandemic.

Background: Nurses in Ophthalmology Department (OD) had a high risk of infection during the novel coronavirus disease 2019 (COVID-19) pandemic. This study examined the prevalence, correlates, and network structure of depression, and explored its association with quality of life (QOL) in Chinese OD nurses. Methods: Based on a cross-sectional survey, demographic and clinical data were collected. Depression was measured with the 9-item Self-reported Patient Health Questionnaire (PHQ-9), and QOL was measured using the World Health Organization Quality of Life Questionnaire-brief version (WHOQOL-BREF). Univariate analyses, multivariate logistic regression analyses, and network analyses were performed. Results: Altogether, 2,155 OD nurses were included. The overall prevalence of depression among OD nurses was 32.71% (95%CI: 30.73-34.70%). Multiple logistic regression analysis revealed that having family or friends or colleagues who were infected (OR = 1.760, p = 0.003) was significantly associated with higher risk of depression. After controlling for covariates, nurses with depression reported lower QOL (F(1, 2,155) = 596.784, p < 0.001) than those without depression. Network analyses revealed that 'Sad Mood', 'Energy Loss' and 'Worthlessness' were the key central symptoms. Conclusion: Depression was common among OD nurses during the COVID-19 pandemic. Considering the negative impact of depression on QOL and daily life, regular screening for depression, timely counselling service, and psychiatric treatment should be provided for OD nurses, especially those who had infected family/friends or colleagues. Central symptoms identified in network analysis should be targeted in the treatment of depression.