A network examination of risky behaviours in a state‐level and national epidemiological sample of high school students. Issue 6 (2nd January 2021) - Christian, Caroline; Keshishian, Ani C.; Levinson, Cheri A.; Peiper, Nicholas C.
Abstract: Aim: Engagement in risky behaviours, including substance use, disordered eating, suicidal behaviour, and peer victimization/violence, during adolescence is becoming increasingly prevalent. These risky behaviours are highly comorbid and associated with long‐term consequences for health, relationships, and socioeconomic status, representing an important public health concern. Past research has primarily investigated risky behaviours in adolescence using latent variable models, which are based on assumptions that may limit insight into the complex reality of these behaviours. Methods: The current study uses network analysis to examine adolescent substance use, disordered eating, suicide risk, and peer victimization/violence in a national ( N = 29 008) and state‐level (Kentucky; N = 3455) epidemiological dataset. We calculated central and bridge symptoms and compared network structure based on demographic factors (race, sex, grade) and sample (state vs. nation). Results: The most central symptoms were suicidal ideation and attempts, stimulant drug use, and prescription drug misuse. The most central bridge symptoms were depression, methamphetamine use, peer violence, and suicide attempts. There were no differences in network structure between samples or across demographic factors in the Kentucky sample. There were differences in network structure across sex and race in the national dataset. Conclusions: These findings suggest stimulant use, suicidal ideation, depression, and peer violence may contribute to the high rates and co‐occurrence of risky behaviours in adolescence. Based on network theory, these symptoms may represent important targets for intervention. Due to network differences, special considerations may be necessary to adapt such interventions to meet the needs of students from different backgrounds.