Inter-relationships between suicidality and depressive symptoms among children and adolescents experiencing crisis: A network perspective.

OBJECTIVES: Suicidality and depressive symptoms have emerged as major mental health issues reported among children and adolescents experiencing crises. In light of these concerns, this study was conducted to elucidate interrelationships between depressive symptoms and suicidality at an item level within this population during the COVID-19 pandemic, a worldwide public health crisis affecting children and adolescents. METHOD: A cross-sectional study design was used. Primary and secondary school students completed the Children's Depression Inventory - Short Version (CDI-S) and two standard suicidality questions tapping suicidal ideation and suicide plans, respectively. A network analysis was performed to examine inter-connections between depressive symptoms and suicidality. RESULTS: A total of 5380 students participated in the study. Prevalence of suicidal ideation and suicide plans were 12.8 % (95 % CI = 11.9 %-13.7 %) and 9.9 % (95 % CI = 9.2 %-10.8 %), respectively; the prevalence of depressive symptoms was 41.2 % (95%CI = 39.8 %-42.5 %). The network analysis identified CDI4 (self-hatred) as the most influential node with the highest centrality, followed by CDI8 (loneliness), CDI5 (crying), and CDI1 (sadness). Additionally, CDI5 (crying), CDI1 (sadness), CDI4 (self-hatred), and CDI10 (feeling unloved) were the most meaningful nodes linking depressive symptoms with suicidality. CONCLUSIONS: Critical depressive symptoms linked with suicidality among children and adolescents living through the COVID-19 pandemic included self-hatred, loneliness, crying, and sadness. Interventions that target these depressive symptoms may have increased utility in reducing the risk of suicidality within this population.

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.