| 其他摘要 | Introduction: The mental health of rural children has always attracted much attention, and depression is one of the most common psychological distresses. In the past, the classical theory, the disease entity theory, regarded psychological problems as the underlying entity behind various symptoms, and determined whether a person was depressed or not by stacking scores on a scale. However, this approach ignores the group differences and symptom heterogeneity behind the scores. In recent years, a new perspective has emerged, such as the symptom-centered network theory of mental illness, which regards depression as a mental health problem as a network composed of symptoms and their interactions, with weak connections in healthy people and strong connections in mental illnesses. This method makes up for the shortcomings of the disease entity theory. Domestic scholars prefer to study the adolescent group, which is indeed the peak of the disease, but ignore the latent stage of the disease - childhood. There are few studies on rural children, and there is also the problem of group ambiguity. This paper will explore the following questions: (1) what are the core symptoms of depression in rural children, and the possible causal relationship of depression symptoms in rural children; (2) Peer relationship - what are the bridge symptoms of depression in children, and the possible causal path between peer relationship and childhood depression symptoms.
Methods: Using the Child Depression Scale, Peer Relationship Scale and demographic questionnaire, 16 rural primary schools were selected from 7 provinces of Anhui, Gansu, Guangdong, Heilongjiang, Hubei, Hunan and Sichuan provinces, covering rural children aged 5-15 years, with 2292 effective responses. The network analysis software package of Rstudio was mainly used to construct Gaussian model and Bayesian model.
Results:
Study 1: Depression Network. In the Gaussian model, the edge connection strength of "disobedience" and "fighting" is the strongest, and the partial correlation coefficient is 0.21. The core symptoms were "self-hatred" (strength=1.20, EI=1.20), "sadness" (strength=1.20, EI=1.20), "loneliness" (strength=1.10, EI=1.10), and "self-deprecation" (strength=1.00, EI=1.00). In the Bayesian model,"self-hatred" is at the very top, and nodes "self-blame", "academic difficulties" ,"pessimism" , and "social withdrawal" are at the very bottom of the network system.
Study 2: Peer Relationship-Depression Network. In the Gaussian network, "good at" (bridge strength = 0.37, BEI = -0.37), "mutual aid" (bridge strength = 0.37, BEI = -0.37), "acceptance" (bridge strength = 0.34, BEI = - 0.34) and "want to make friends" (bridge strength = 0.32, BEI=-0.32) is the bridge node. Bridge symptoms of the depression network were "lack of friends" (bridge strength = 0.27, BEI = -0.27), "feeling unloved" (bridge strength = 0.28, BEI = -0.28), and "anhedonia" (bridge strength = 0.32, BEI = -0.32). In the Bayesian model, "loneliness" and "want to make friends" are at the top of the whole joint network, which are the triggering symptoms, and no other nodes point to them. "Pessimism" ,"Difficulty in Schoolwork" , "Self-blame", and "Feeling Unloved" are the end nodes of the entire federated network.
The most typical symptoms of depression are "self-hatred", "sadness", "loneliness" and "self-deprecation" in rural children in the East, West and central regions, and external stress events may activate the entire depression network by inducing "self-hatred", and eventually point to the symptoms of "self-blame", "schoolwork difficulties", "pessimism" and "social withdrawal" in rural children. "Acceptance", "good at", "mutual help" and "want to make friends" are important nodes that may directly activate the symptoms of "lack of friends", "feeling unloved" and "anhedonia". |
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