Network analysis of suicidality and internet addiction symptoms among Chinese primary and secondary school students

Background: The COVID-19 pandemic has increased the risk of both Internet addiction and suicide across various populations, especially among children and adolescents. This study aimed to assess the inter-relationships between Internet addiction symptoms and suicidality among primary and secondary school students from the perspective of network analysis. Methods: This was a cross-sectional, multicenter study. The Internet Addiction Test (IAT) was used to assess internet addiction symptoms. Participants were also asked about having any suicidal ideation and suicide plan. Univariate analyses and network analysis were subsequently conducted. Results: Altogether, 5380 primary and secondary school students participated in the study. Among them, 3161 (58.8 %, 95 % CI = 57.4 %–60.1 %) students reported having Internet addiction symptoms and 798 (14.8 %, 95 % CI = 13.9 %–15.8 %) reported having suicidal ideation or suicide plan in the past two weeks. Network analysis revealed that IAT16 (‘Request an extension for longer time spent online’; node strength = 1.223) was the most central symptom in the Suicidality-Internet addiction network model, while the edge suicidality-IAT4 (‘Form new relationship with online users’; edge weight = 0.055) was the strongest edge linking both communities. Conclusions: Internet addiction symptoms were common among primary and secondary school students during the COVID-19 school closure period in China and were significantly associated with suicidality. Targeted strategies such as strengthening self-control, sense of belonging and connectedness may be important in reducing the risk of both suicidality and Internet addiction among primary and secondary school students.