Gender differences in behavioral and emotional problems among school children and adolescents in China: National survey findings from a comparative network perspective.

BACKGROUND: Behavioral and emotional problems are common and often co-occur during childhood and adolescence. The aim of this study was to assess gender differences in the network structures of behavioral and emotional problems of children and adolescents in China based on a national survey. METHODS: The Parent version of Achenbach' s Child Behavior Checklist (CBCL) was used to assess behavioral and emotional problems. To account for potential confounding factors in comparisons between boys and girls, propensity score matching was utilized. Network model differences were assessed using Network Comparison Test (NCT). RESULTS: Data from 60,715 children and adolescents were included for analyses. Boys exhibited more severe total behavioral and emotional problems compared to girls. While several edges showed significant differences between boys and girls, the strongest association was consistently found between "Attention problems" (CBCL6) and "Aggressive behavior"(CBCL8) in both boys and girls, regardless of age. Network centrality was higher among adolescents compared to children. The most central problems commonly found across different genders and age groups were "Aggressive behavior" (CBCL8) (centrality values were 1.142 for boys aged 6-11 years, 1.051 for boys aged 12-16 years, 1.148 for girls aged 6-11 years, and 1.028 for girls aged 12-16 years), "Anxious/depressed" (CBCL1) (centrality values of 0.892 for boys aged between 6 and 11 years, 1.031 for boys aged 12-16 years, 0.951 for girls aged 6-11 years, and 1.099 for girls aged 12-16 years) and "Social problems" (CBCL4) (centrality values of 1.080 for boys aged 6-11 years, 0.978 for boys aged 12-16 years, 1.086 for girls aged between 6 and 11 years, and 0.929 for girls aged 12-16 years). CONCLUSION: Testing effective interventions that address aggressive behavior, anxiety/depression, and social problems may be beneficial for reducing risk of psychopathology among children and adolescents.

Comparing network structures of depressive and anxiety symptoms between demographically-matched heart disease and heart disease free samples using propensity score matching: Findings from the Chinese Longitudinal Healthy Longevity Survey (CLHLS).

BACKGROUND: Older adults with heart disease often experience higher rates of comorbid anxiety and depression. This study examined depression and anxiety network structures among older adults with heart disease and their heart disease free peers. METHODS: Network analyses of secondary cross-sectional data from the 2017 to 2018 wave of CLHLS were used to construct groups of older adults with and without heart disease using propensity score matching. Depression and anxiety symptoms were assessed using Center for Epidemiological Studies Depression Scale and Generalized Anxiety Disorder Scale, respectively. Central symptoms and bridge symptoms were identified using expected influence. RESULTS: 1689 older adults with heart disease and matched control sample of 1689 older adults without heart disease were included. The prevalence and severity of depression and anxiety were significantly higher in older adults with heart disease compared to the control group. There was no significant difference in overall structures of depression and anxiety network models between two the groups. Key central symptoms and bridge symptoms within these groups were highly similar; GAD 2 "Uncontrollable worrying" and GAD 4 "Trouble relaxing" were identified as the most central symptoms, while GAD 1 "Nervousness" and CESD 1 "Feeling bothered" were identified as key bridge symptoms across both network models. CONCLUSION: Depression and anxiety are more prevalent in older adults with heart disease than demographically-matched heart disease free controls. However, network structures of these symptoms do not differ between two groups. Accordingly, depression and anxiety psychosocial interventions developed for older adults without heart disease may also benefit older adults with heart disease.

A network analysis of the interrelationships between depression, anxiety, insomnia and quality of life among fire service recruits.

Background: Research on the mental health and quality of life (hereafter QOL) among fire service recruits after the end of the COVID-19 restrictions is lacking. This study explored the network structure of depression, anxiety and insomnia, and their interconnections with QOL among fire service recruits in the post-COVID-19 era. Methods: This cross-sectional study used a consecutive sampling of fire service recruits across China. We measured the severity of depression, anxiety and insomnia symptoms, and overall QOL using the nine-item Patient Health Questionnaire (PHQ-9), seven-item Generalized Anxiety Disorder scale (GAD-7), Insomnia Severity Index (ISI) questionnaire, and World Health Organization Quality of Life-brief version (WHOQOL-BREF), respectively. We estimated the most central symptoms using the centrality index of expected influence (EI), and the symptoms connecting depression, anxiety and insomnia symptoms using bridge EI. Results: In total, 1,560 fire service recruits participated in the study. The prevalence of depression (PHQ-9 ≥ 5) was 15.2% (95% CI: 13.5-17.1%), while the prevalence of anxiety (GAD-7 ≥ 5) was 11.2% (95% CI: 9.6-12.8%). GAD4 ("Trouble relaxing") had the highest EI in the whole network model, followed by ISI5 ("Interference with daytime functioning") and GAD6 ("Irritability"). In contrast, PHQ4 ("Fatigue") had the highest bridge EI values in the network, followed by GAD4 ("Trouble relaxing") and ISI5 ("Interference with daytime functioning"). Additionally, ISI4 "Sleep dissatisfaction" (average edge weight = -1.335), which was the central symptom with the highest intensity value, had the strongest negative correlation with QOL. Conclusion: Depression and anxiety were important mental health issues to address among fire service recruits in the post-COVID-19 era in China. Targeting central and bridge symptoms identified in network analysis could help address depression and anxiety among fire service recruits in the post-COVID-19 era.

The network structures of mental and behavioral problems among children and adolescents in China using propensity score matching: A comparison between one-child and multi-child families based on a nationwide survey.

BACKGROUND: Exploring networks of mental and behavioral problems in children and adolescents may identify differences between one-child and multi-child families. This study compared the network structures of mental and behavioral problems in children and adolescents in one-child families versus multi-child families based on a nationwide survey. METHODS: Propensity score matching (PSM) was used to match children and adolescents from one-child families with those from multi-child families. Mental and behavioral problems were assessed using the Achenbach's Child Behavior Checklist (CBCL) with eight syndromal subscales. In the network analysis, strength centrality index was used to estimate central symptoms, and case-dropping bootstrap method was used to assess network stability. RESULTS: The study included 39,648 children and adolescents (19,824 from one-child families and 19,824 from multi-child families). Children and adolescents from multi-child families exhibited different network structure and higher global strength compared to those from one-child families. In one-child families, the most central symptoms were "Social problems", "Anxious/depressed" and "Withdrawn/depressed", while in multi-child families, the most central symptoms were "Social problems", "Rule-breaking behavior" and "Anxious/depressed". CONCLUSION: Differences in mental and behavioral problems among children and adolescents between one-child and multi-child families were found. To address these problems, interventions targeting "Social problems" and "Anxious/depressed" symptoms should be developed for children and adolescents in both one-child and multi-child families, while other interventions targeting "Withdrawn/depressed" and "Rule-breaking behavior" symptoms could be useful for those in one-child and multi-child families, respectively.

Mental health status among children and adolescents in one-child and multichild families: a meta-analysis of comparative studies.

PURPOSE OF REVIEW: Controversy remains about the difference in mental health status among children and adolescents between one-child and multichild families in China. Thus, we conducted a meta-analysis of studies comparing mental health status between both groups and explored their potential moderating factors. RECENT FINDINGS: Totally, 113 eligible studies encompassing 237 899 participants (one-child families: 83 125; multichild families: 154 774) were included. The pooled SMD of SCL-90 total score was -0.115 [95% confidence interval (95% CI): -0.152; -0.078; I2  = 86.9%]. Specifically, children and adolescents from one-child families exhibited lower scores in terms of somatization (SMD = -0.056; 95% CI: -0.087; -0.026), obsessive-compulsive symptoms (SMD = -0.116; 95% CI: -0.154; -0.079), interpersonal sensitivity (SMD = -0.140; 95% CI: -0.171; -0.109), depression (SMD = -0.123; 95% CI: -0.159; -0.088); anxiety (SMD = -0.121; 95% CI: -0.151; -0.092); phobic anxiety (SMD = -0.124; 95% CI: -0.166; -0.081); paranoid ideation (SMD = -0.040; 95% CI: -0.070; -0.009); and psychoticism (SMD = -0.119; 95% CI: -0.148; -0.089). Study publication year was significantly associated with differences in mental health status between both groups ( P  = 0.015). SUMMARY: Children and adolescents from one-child families had better mental health status compared to those from multichild families in China. Future studies should investigate the underlying factors contributing to such mental health differences, and the potential interventions that could address these mental health problems.

Health-Related Quality of Life and Influencing Factors in Coronary Heart Disease Based on the Scale QLICD-CHD (V2.0): A Cross-Sectional Study.

Purpose: Coronary heart disease (CHD) is difficult to cure, so more attention should be paid to improving patients' health-related quality of life (HRQoL). This paper focuses on identifying factors that affect HRQoL. Patients and Methods: Overall, 189 in-patients with coronary heart disease were investigated at the Affiliated Hospital of Guangdong Medical University between 2015 and 2016. The scale Quality of Life Instruments for Chronic Diseases-Coronary heart disease (QLICD-CHD V2.0) was used to evaluate HRQoL and collect demographic information. Medical records were applied to collect patients' clinical indicators. A simple correlation analysis, Student's t-test, and a one-way analysis of variance were first performed to filter factors that might associate with HRQoL, and multiple linear regression was applied to finally identify related factors. Results: Findings from multiple linear regression showed that the total score was related to family economy, treatment, indirect bilirubin, and albumin with regression coefficient B=5.209, -6.615, 0.378, and 0.548, respectively. The physical functions were related to treatment, albumin, globular proteins, chloride, and red blood cell count with B=-9.031, 1.000, 0.612, 1.320, and 5.161, respectively. The psychological function was in association with family economy, clinical course, serum phosphorus, and percentage of lymphocyte population with B=7.487, 6.411, -16.458, and 0.090, respectively. The social function was associated with family economy, blood urea nitrogen, serum creatinine, and platelet distribution width with B=7.391, 1.331, -0.060, and -0.929, respectively. The special module was in association with treatment, indirect bilirubin, and serum calcium with B=-7.791, 0.414, and 23.017, respectively. Conclusion: Clinical indicators including albumin, globular proteins, chloride, red blood cell count, serum phosphorus, percentage of lymphocyte population, blood urea nitrogen, serum creatinine, platelet distribution width, indirect bilirubin, and serum calcium, as well as socio-demographic factors including the family economy, clinical course, and treatment, may affect coronary heart disease patients' HRQoL.