A Cross-Lagged Prospective Network Analysis of Suicide Potential, Risk Factors, and Protective Factors Among Children and Adolescents in Hong Kong

Background: Measures such as social distancing and school closure brought about by the COVID pandemic may cause considerable psychological distress and family distress and hinder the mental health of children and adolescents. These psychosocial stressors may increase the problems of self-injury and suicide. However, there is still a lack of systematic longitudinal research exploring the suicidal potential and the risk versus protective factors in children and adolescents. Hence, this study aimed to examine the influence of risk and protective factors on suicidal potential in the system and the unique longitudinal relationship using a cross-lagged panel network analysis.

Methods: Data were collected from July to September 2020 (T1) and July to September 2021 (T2), respectively. Students in grade 3 to grade 5 in four primary schools and students in grade 1 to grade 5 in four secondary schools in Hong Kong were invited to participate in the survey. Before completing the questionnaire, we obtained informed consent from principals, parents, and students themselves. Suicidal potential, self-efficacy, resilience, subjective happiness, interpersonal needs, hopelessness were measured. Finally, 1744 questionnaires were collected in T1. Among them, 1615 participants (820 females, mean age = 10.93, SD = 1.135, range = 9-15) completed the second wave survey in T2.

The cross-lagged panel network analysis was performed and visualized in R. The graphical least absolute shrinkage and selection operator estimation algorithm with Extended Bayesian Information Criterion in the Gaussian Graphical Model was used to estimate the network. The networks of T1 and T2 were compared. The least absolute shrinkage and selection operator regularization with a 10-fold cross-validation method was used in the cross-lagged analysis. Gender, age, religion, and parental marital were set as covariates.

Results: The results identified the centrality role of hopelessness in T1 (strength = 1.29) and anxiety-impulsive depression (strength = 1.32) in T2 in the suicidal system and the bridging effects of self-efficacy and hopelessness on suicidal potential. The strongest undirected edges across constructs were self-efficacy-hopelessness (r = -0.35), self-efficacy-family distress (r = -0.10), anxious-impulsive depression-perceived burdensomeness (r = 0.18), and suicide ideation or acts-perceived burdensomeness (r = 0.19). The network invariance and global strength showed that the network in T1 and T2 did not differ significantly in overall structure and connectivity. The higher levels of subjective happiness (β = -0.40) and self-efficacy (β = -0.16) were prospectively associated with future lower anxious-impulsive depression. The higher subjective happiness (β = -0.13) and lower perceived burdensomeness (β = 0.14) were prospectively associated with future lower suicide ideation or acts. The prediction results found the critical risk effect of hopelessness and the protective effect of subjective happiness on suicidal potential.

Implications: The cross-lagged network analysis indicated that COVID did not directly affect suicidal potential outcomes but did affect the position of influencing factors in the suicidal system. Research findings implicated that interventions on hopelessness, improving subjective happiness, and reducing perceived burdensomeness can contribute to preventing and reducing suicide ideation or acts among children and adolescents.