The longitudinal network of peer problems and emotional symptoms among Australian adolescents: Bayesian structure learning of directed acyclic graphs

Introduction: Adolescence is a period in which peer problems and emotional symptoms markedly increase in prevalence. However, the causal mechanisms regarding how peer problems cause emotional symptoms at a behavioural level and vice-versa remain largely unknown. To address this gap, the current study investigated the longitudinal network of peer problems and emotional symptoms among Australian adolescents aged 12 to 14 years. Methods: Data was from the national Longitudinal Study of Australian Children (LSAC). The complete case samples included adolescents who participated in the LSAC Baby (n=2,694) or Kindergarten (n=3,144) Cohorts at two study follow-ups (at ages 12 and 14). Peer problems and emotional symptoms were measured with the self-report Strengths and Difficulties Questionnaire. The analytical steps were: (1) a causal discovery algorithm, namely Bayesian structure learning of Directed Acyclic Graphs (DAGs), was used to identify the longitudinal network in the LSAC K Cohort; (2) the DAG discovered was evaluated (with Bayesian Structural Equation Modeling) in an independent sample (the LSAC B Cohort) and also compared against an expert DAG, established by two researchers with expertise in adolescent well-being; and (3) in the best fitting DAG from step (2), network communities, intervention targets and the contemporaneous network were investigated. Results: The empirically discovered DAG provided a better explanation of independent data than the expert DAG. Based on the discovered DAG, key intervention targets such as excessive worries were identified. Conclusion: The current study provides new insights into potential causal effects established between peer problems and emotional symptoms among Australian adolescents aged 12 to 14 years.