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.

COVID-19 and Sleep Problems: A Perspective from Bibliometric Analysis.

OBJECTIVES: The Coronavirus Disease 2019 (COVID-19) pandemic and the containment measures for COVID-19 have affected sleep quality in the population. This study explored sleep-related research from a bibliometric perspective to provide an overview of the research outputs in this field. METHODS: Original and review articles were retrieved from the Web of Science Core Collection (WOSCC) database from December 2019 to 7 Aug 2023. R package "bibliometrix" was used to summarize the number of articles of authors, institutions, and countries; count the citations of the articles, and generate a Three-Fields Plot. VOSviewer software was applied to visualize the collaboration network among authors and institutions, and to conduct a co-occurrence analysis of keywords. RESULTS: A total of 4,499 articles on COVID-19 and sleep, and 25,883 articles on non-COVID-19 and sleep were included. Sleep related articles were mainly published by authors from China, the USA, and Italy. For COVID-19 and sleep research, Huazhong University of Science was the most productive institution. The Psychiatry Research was the most influential journal across the different subject categories of this field. "Mental health", "anxiety", and "depression" were the most common keywords, while "sleep quality" and "quality of life" were the likely topic areas in terms of future research directions. CONCLUSIONS: Our findings provide a comprehensive perspective for researchers to understand the wider landscape of both COVID-19 and non-COVID-19 sleep-related research area.

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.

Schizophrenia and Inflammation Research: A Bibliometric Analysis.

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

Comparing the Self- and External Assessment Versions of the HCL-33 as Screening Instruments for Bipolar Disorder in Older Depressed Patients.

Objectives: The misdiagnosis of bipolar disorder (BD) as major depressive disorder (MDD) is common in depressed older adults. The self-rated HCL-33 and its external assessment version (HCL-33-EA) have been developed to screen for hypomanic symptoms. This study compared the screening ability of these two instruments to discriminate BD from MDD. Methods: A total of 215 patients (107 with BD and 108 with MDD) and their carers were recruited. Patients and their carers completed the HCL-33 and HCL-33-EA, respectively. The consistency of the total score and the positive response to each item between the two scales was calculated with the intraclass correlation coefficient (ICC) and Cohen's kappa coefficient separately. Receiver operating characteristics (ROC) curves were drawn for both instruments. The optimal cut-off points were determined according to the maximum Youden's Index. The areas under the ROC curve (AUC) of the HCL-33 and HCL-33-EA were calculated separately and compared. The sensitivity and specificity at the optimal cut-off values were also calculated separately for the HCL-33 and HCL-33-EA. Results: The intraclass correlation coefficient (ICC) between the total scores of the HCL-33 and HCL-33-EA was 0.823 (95% CI = 0.774-0.862). The positive response rate on all items showed high agreement between the two instruments. ROC curve analysis demonstrated that the total scores of both HCL-33 and HCL-33-EA differentiated well between MDD and BD, while there was no significant difference in the AUCs between the two scales (Z = 0.422, P = 0.673). The optimal cutoff values for the HCL-33 and HCL-33-EA were 14 and 12, respectively. With the optimal cutoff value, the sensitivities of the HCL-33 and HCL-33-EA were 88.8% and 93.5%, and their specificities were 82.4% and 79.6%. Conclusion: Both the HCL-33 and HCL-33-EA had good screening ability for discriminating BD from MDD in depressed older adults.

Anxiety and depressive symptoms in college students during the late stage of the COVID-19 outbreak: a network approach.

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

Reliability and Validity of the Quick Inventory of Depressive Symptomatology-Self-Report Scale in Older Adults With Depressive Symptoms.

Background: Depressive symptoms are common in older adults. Developing rapid self-report tools is essential to measure the presence and severity of depressive symptoms in older adults. This study evaluated the psychometric properties of the Quick Inventory of Depressive Symptomatology-Self-Report (QIDS-SR) scale for use in depressed older adults. Methods: A total of 238 depressed older adults were included in the study. The Montgomery-Asberg Depression Rating Scale (MADRS) and the QIDS-SR were administered to assess the severity of depressive symptoms. Cronbach's alpha coefficient, Spearman rank correlations, and principal component analysis were performed to estimate the internal consistency, convergent validity, and factorial structure of the QIDS-SR, respectively. Results: The Cronbach's alpha for the QIDS-SR was acceptable (α = 0.64). Item-total correlation analyses showed that the items of concentration/decision-making, involvement, energy level, and agitation/retardation had high correlation with the QIDS-SR total score (all correlation coefficients ≥0.60). The QIDS-SR total score was significantly correlated with the MADRS total score (r = 0.53, p < 0.001), demonstrating acceptable convergent validity. Factor analysis revealed the unidimensional structure of the QIDS-SR. Conclusions: The QIDS-SR appears to be a reliable and valid self-report scale for estimating the severity of depressive symptoms in depressed older adults.

Prevalence of Suicidality in Major Depressive Disorder: A Systematic Review and Meta-Analysis of Comparative Studies.

Background: Suicidality is common in major depressive disorder (MDD), but there has been no systematic review published about all aspects of suicidality. This meta-analysis and systematic review compared the prevalence of the whole range of suicidality comprising suicidal ideation (SI), suicide plan (SP), suicide attempt (SA), and completed suicide (CS), between patients with MDD and non-MDD controls. Methods: Major international (PubMed, PsycINFO, Web of Science, EMBASE) and Chinese (Chinese Nation Knowledge Infrastructure and WANFANG) databases were systematically and independently searched from their inception until January 12, 2021. Results: Fifteen studies covering 85,768 patients (12,668 in the MDD group and 73,100 in the non-MDD group) were included in the analyses. Compared to non-MDD controls, the odds ratios (ORs) for lifetime, past month, past year, and 2-week prevalence of SI in MDD were 2.88 [95% confidence interval (CI) = 0.30-27.22, p = 0.36], 49.88 (95% CI = 2-8.63, p < 0.001), 13.97 (95% CI = 12.67-15.41, p < 0.001), and 24.81 (95% CI = 15.70-39.22, p < 0.001), respectively. Compared to non-MDD controls, the OR for lifetime SP in MDD was 9.51 (95% CI = 7.62-11.88, p < 0.001). Compared to non-MDD controls, the ORs of lifetime and past-year prevalence of SA were 3.45 (95% CI = 1.58-7.52, p = 0.002), and 7.34 (95% CI = 2.14-25.16, p = 0.002), respectively, in MDD patients. No difference in the prevalence of CS between MDD and controls was found (OR = 0.69, 95% CI = 0.23-2.02, p = 0.50). Conclusions: MDD patients are at a higher risk of suicidality, compared to non-MDD controls. Routine screening for a range of suicidality should be included in the management of MDD, followed by timely treatment for suicidal patients. Systematic Review Registration: Identifier [INPLASY202120078].

Prevalence of Depression in Older Nursing Home Residents in High and Low Altitude Regions: A Comparative Study.

Objective: Depressive symptoms (depression hereafter) is common in older adults, and closely associated with environmental factors. This study compared the prevalence of depression in older adults living in high-altitude and low-altitude regions, and their association with quality of life (QOL). Method: A total of 632 older nursing home residents were included, with 425 participants living in low-altitude and 207 participants living in high-altitude regions. Depression and QOL were assessed using standardized instruments. Results: The prevalence of depression was 26.9% (95% CI: 23.43-30.37%) in the whole sample of older nursing home residents, with 11.1% (95% CI: 8.01-14.05%) in those living in low-altitude and 59.4% (95% CI: 52.68-66.17%) in those living in high-altitude regions. Multiple logistic regression analysis revealed that living in low-altitude region (P < 0.001, OR = 0.07, 95% CI: 0.04-0.12) was associated with lower risk of depression, while perception of poor health status (P < 0.001, OR = 3.86, 95% CI: 1.98-7.54) and having insomnia (P < 0.001, OR = 4.76, 95% CI: 2.99-7.56) were associated with higher risk of depression. QOL was significantly lower in physical (F (1,632) = 35.421, P < 0.001), psychological (F (1,632) = 20.777, P < 0.001), social (F (1,632) = 8.169, P < 0.001) and environmental domains (F (1,632) = 11.861, P < 0.001) in those with depression. Conclusion: Depression was common in older nursing home residents especially those living in the high-altitude region. Considering the negative impact of depression on QOL and functional outcomes, routine screening and timely treatment of depression should be implemented in this population.

Prevalence of depression and its relationship with quality of life among university students in Macau, Hong Kong and mainland China.

There is compelling evidence that depressive symptoms (depression hereafter) are common in university students and are considerably influenced by the given socioeconomic context. Being former European colonies, Macau and Hong Kong are China's special administrative regions, with different sociocultural and economic background compared to mainland China. This study compared the prevalence of depression in university students between Macau, Hong Kong and mainland China and examined the association between depression and quality of life (QOL). The Beck Depression Inventory-II and the World Health Organization Quality of Life-Brief Version (WHOQOL-BREF) were used to measure depression and QOL, respectively. Altogether, 2,312 university students participated in this study. The overall prevalence of depression was 28.9%; 35.2% in Macau, 41.0% in Hong Kong, and 16.8% in mainland China. Compared to the "No depression" group, students with depression had significantly lower QOL scores in the physical, psychological, social and environmental domains. Factors associated with depression were different between the three study sites. Sleep disturbances and high academic pressure were positively associated with depression in all the three samples. In mainland China, male students (OR = 1.68; 95% CI: 1.10-2.56) were more likely to have depression while those who were interested in their major (OR = 0.45; 95% CI: 0.29-0.69) were less likely to have depression. In Macau, students in Grade 3 (OR = 0.56; 95% CI: 0.36-0.89) and those who were interested in their major (OR = 0.58; 95% CI: 0.42-0.81) or had optimistic perspective about their future (OR = 0.51; 95% CI: 0.36-0.73) were less likely to have depression. Nursing students (OR = 1.86; 95% CI: 1.21-2.87) and students with the average score on major subject less than 65 (OR = 3.13; 95% CI: 1.70-5.78) were more likely to have depression. In Hong Kong, students with optimistic perspective about their future (OR = 0.44; 95% CI: 0.22-0.91) were less prone to have depression. Depression is common among Chinese university students, particularly in Macau and Hong Kong. Considering the negative impact of depression on QOL, regular screening and effective treatments should be offered to this population.

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.

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.

The prevalence of depression in menopausal women in China: A meta-analysis of observational studies.

OBJECTIVE: Depressive symptoms (depression thereafter) are common among menopausal women but findings across studies have been inconsistent. This meta-analysis examined the pooled prevalence of depression among Chinese menopausal women. METHODS: Two investigators independently searched both international (PubMed, EMBASE and PsycINFO) and Chinese (CNKI, WanFang, SinoMed and VIP) databases from their inception date until 9 April 2019. Studies that reported the prevalence of depression as measured by the Hamilton Depression Scale (HAMD) were pooled using a random-effects model. RESULTS: Twenty-three cross-sectional studies were included in the meta-analysis. The pooled prevalence of depression in menopausal Chinese women was 36.3% (95% CI: 27.5-45.1%), with mild depression of 18.6% (95% CI: 13.4-23.8%), moderate depression of 15.3% (95% CI: 9.4-21.3%), and severe depression of 3.7% (95% CI: 1.9-5.5%). Meta-regression analyses revealed that older age (B = 0.12, z = 8.18, p < 0.001) and better study quality (B = 0. 24, z = 8.33, p < 0.001) was significantly associated with higher depression prevalence. CONCLUSIONS: Depression is common among menopausal Chinese women. Due to its negative impact on health, regular screening and effective treatments should be developed for this population.

Prevalence of sleep disturbances in Chinese university students: a comprehensive meta-analysis.

This is a meta-analysis of the pooled prevalence of sleep disturbances and its associated factors in Chinese university students. English (PubMed, PsycINFO, Embase) and Chinese (SinoMed, Wan Fang Database and Chinese National Knowledge Infrastructure) databases were systematically and independently searched from inception until 16 August 2016. The prevalence of sleep disturbances was pooled using random-effects model. Altogether 76 studies involving 112 939 university students were included. The overall pooled prevalence of sleep disturbances was 25.7% (95% CI: 22.5-28.9%). When using the screening scales Pittsburgh Sleep Quality Index, Athens Insomnia Scale and Self-Rating Sleeping State Scale, and the diagnostic criteria of the Chinese Classification of Mental Disorders (Second Edition), the pooled prevalence of sleep disturbances was 24.1% (95% CI: 21.0-27.5%) and 18.1% (95% CI: 16.4-20.0%), respectively. The percentages of students dissatisfied with sleep quality and those suffering from insomnia symptoms were 20.3% (95% CI: 13.0-30.3%) and 23.6% (95% CI: 18.9-29.0%), respectively. Subgroup analyses revealed that medical students were more vulnerable to sleep disturbances than other student groups. There was no significant difference between males and females, and across geographic locations. Sleep disturbances are common in Chinese university students. Appropriate strategies for prevention and treatment of sleep disturbances in this population need greater attention.