Uncovering the symptom relationship between anxiety, depression, and internet addiction among left-behind children: A large-scale purposive sampling network analysis

X. Shen, X. Zhou, H.-P. Liao, D. McDonnell, J.-L. Wang

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

Facing long-term separation from their parents, left-behind children are at risk of the co-occurrence of internalizing and externalizing problems. Although previous research has gained substantial information examining the relationship between anxiety, depression, and internet addiction at the aggregate level of variables, little is known about the heterogeneity and interactions between these components at the symptom level with a large-scale purposive sample. Adopting the network approach, two network pathways, depression and anxiety, and associations between these variables and internet addiction were constructed. Our sample included 5367 left-behind children (M age = 13.57; SD age = 1.37; 50.07% females). Relevant bridging, central symptoms, and network stability were identified. Two relatively stable networks were obtained. For the network of anxiety and depression, sleep problems and tachycardia were vital bridging symptoms. Central symptoms, including tachycardia, restlessness, fatigue, and emptiness, were symptoms of depression. For the network of symptoms of anxiety, depression, and internet addiction, the bridging symptoms remained the same, and the central symptoms included tachycardia, restlessness, loss of control, and emptiness. By identifying relevant bridging and central symptoms, those with higher levels of these symptoms could be regarded as intervention targets, providing a reference for the current issue of valuing diagnosis over prevention in left-behind children.

Original languageEnglish
Pages (from-to)43-51
Number of pages9
JournalJournal of Psychiatric Research
Volume171
DOIs
Publication statusPublished - 16 Jan 2024

Keywords

  • Anxiety
  • Depression
  • Internet addiction
  • Left-behind children
  • Network analysis

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