期刊：
Journal of Affective Disorders,2022年301:463-471 ISSN：0165-0327
通讯作者：
Yu-Tao Xiang
作者机构：
[Liu, Rui; Qi, Han; Zhang, Ling; Chen, Xu; Feng, Yuan] Capital Med Univ, Natl Clin Res Ctr Mental Disorders, Beijing, Peoples R China.;[Liu, Rui; Qi, Han; Zhang, Ling; Chen, Xu; Feng, Yuan] Capital Med Univ, Beijing Key Lab Mental Disorders, Beijing Anding Hosp, Beijing, Peoples R China.;[Liu, Rui; Qi, Han; Zhang, Ling; Chen, Xu; Feng, Yuan] Capital Med Univ, Adv Innovat Ctr Human Brain Protect, Beijing, Peoples R China.;[Liu, Rui; Xiang, Yu-Tao] Univ Macau, Fac Hlth Sci, Inst Translat Med, Unit Psychiat,Dept Publ Hlth & Med Adm, Macau, Peoples R China.;[Liu, Rui; Xiang, Yu-Tao] Univ Macau, Ctr Cognit & Brain Sci, Macau, Peoples R China.
通讯机构：
[Yu-Tao Xiang] U;Unit of Psychiatry, Department of Public Health and Medicinal Administration, Institute of Translational Medicine, Faculty of Health Sciences, University of Macau, Macao SAR, China<&wdkj&>Center for Cognitive and Brain Sciences, University of Macau, Macao SAR, China<&wdkj&>Institute of Advanced Studies in Humanities and Social Sciences, University of Macau, Macao SAR, China
摘要：
BACKGROUND: This study examined the extent to which the network structure of anxiety and depression among adolescents identified during the peak of the COVID-19 pandemic could be cross-validated in a sample of adolescents assessed after the COVID-19 peak. METHODS: Two cross-sectional surveys were conducted between February 20 and 27, 2020 and between April 11 and 19, 2020, respectively. Depressive and anxiety symptoms were assessed using the 20-item Center for Epidemiological Studies-Depression and 7-item Generalized Anxiety Disorder, respectively. Anxiety-depression networks of the first and second assessments were estimated separately using a sparse Graphical Gaussian Model combined with the graphical least absolute shrinkage and selection operator method. A Network Comparison Test was conducted to assess differences between the two networks. RESULTS: The most central symptoms in the first and second survey networks were Depressed affect and Nervousness. Compared with connections in the first survey network, connections in the second survey network analysis between Relax-Nervousness-Depressed affect-Interpersonal problems (diff, contrast: second survey-first survey. diff=-0.04, P=0.04; diff=-0.03, P=0.03; diff=-0.03, P=0.04), and Irritability-Somatic complaints (diff=-0.04, P=0.02) were weaker while connections of Somatic complaints-Nervousness (diff=0.05, P<0.001), Somatic complaints-Depressed affect (diff=0.03, P=0.009), and Irritability-Control worry-Restlessness (diff=0.02, P=0.03; diff=0.05, P=0.02) were stronger. CONCLUSIONS: Depressed affect emerged as a robust central symptom and bridge symptom across Anxiety-Depression networks. Considering the negative impact of depression and anxiety on daily life, timely interventions targeting depressed affect should be implemented to reduce the co-occurrence of anxious and depressive symptoms among adolescents during the COVID-19 pandemic.
通讯机构：
[Zhihua Li] C;College of Education, Department of Applied Psychology, Hunan University of Science & Technology, Xiangtan, China
关键词：
Children from low-income families;Multiple risk factors;Psychological adaptation;Latent class analysis
摘要：
Based on the ecological systems theory, this study examined the multiple risk factors experienced by children from low-income families in China and their subsequent impact on children's psychological adaptation. A cumulative ecological risk questionnaire was constructed to examine the exploratory and descriptive risk factors most commonly exposed to children in families, schools and communities. The study sample consisted of 428 children from low-income families (N = 428; M-age = 12.35, SD = 2.51) from 20 ordinary primary and secondary schools across China. We conducted an exploratory latent class analysis using the responses from the cumulative ecological risk questionnaire. The results showed that a three-group solution fit the data best, with the following breakdown: "low-risk" = 41.1%, "family-risk" = 21.7%, and "school-risk" = 37.2%. The three groups showed significant differences in terms of psychological adaptation. The "low-risk" group exhibited fewer problem behaviors and higher prosocial behavior than the other groups. The "family-risk" group showed more significant adaptation difficulties, while the "school-risk" group showed lower levels of prosocial behavior. The results suggest that the ecological risks experienced by children from low-income families had significant group heterogeneity, which may further affect their psychological adaptation.
作者机构：
[Liu, Wenli; Yang, Zilu; Peng, Shenli] Department of Applied Psychology, College of Education, Hunan Agricultural University, Hunan Province, Changsha, 410128, China;[Liu, Chang Hong] Department of Psychology, Bournemouth University, Poole, United Kingdom
通讯机构：
[Shenli Peng] D;Department of Applied Psychology, College of Education, Hunan Agricultural University, Changsha, People’s Republic of China
