Adolescent social networks matter for suicidal trajectories: disparities across race/ethnicity, sex, sexual identity, and socioeconomic status

Abstract

Background Examining social networks, characterized by interpersonal interactions across family, peer, school, and neighborhoods, offer alternative explanations to suicidal behaviors and shape effective suicide prevention. This study examines adolescent social networks predicting suicide ideation and attempt trajectories transitioning to adulthood, while revealing differences across racial/ethnic, sex, sexual identity, and socioeconomic status. Methods Participants included 9421 high school students (Mage = 15.30 years; 54.58% females, baseline) from Waves I–IV of the National Longitudinal Study of Adolescent to Adult Health, 1994–2008. Latent class growth analyses were conducted to identify suicide ideation and attempt trajectories. Multivariate multinomial logistic regressions examined the relationships between social network characteristics during adolescence and suicidal trajectories. Interaction terms between social networks and sociodemographic characteristics were included to test moderation effects. Results Three suicidal ideation trajectories (low-stable, high-decreasing, moderate-decreasing-increasing) and two suicide attempt trajectories (low-stable, moderate-decreasing) were identified. Greater family cohesion significantly reduced the probability of belonging to high-decreasing (Trajectory 2) and moderate-decreasing-increasing (Trajectory 3) suicidal ideation trajectories, and moderate-decreasing (Trajectory 2) suicide attempt trajectory. Race/ethnicity, sex, and sexual identity significantly moderated the associations between social networks (household size, peer network density, family cohesion, peer support, neighborhood support) and suicidal trajectories. Conclusions Social networks during adolescence influenced the odds of belonging to distinct suicidal trajectories. Family cohesion protected youth from being in high-risk developmental courses of suicidal behaviors. Social networks, especially quality of interactions, may improve detecting adolescents and young adults at-risk for suicide behaviors. Network-based interventions are key to prevent suicidal behaviors over time and suicide intervention programming.

Family Factors Related to Suicidal Behavior in Adolescents

“…Some research has also found that families with adaptability problems are at higher risk of suicidal behaviors [ 83 ]. On the contrary, higher cohesion in the family is a protective factor for depressive symptoms in adolescents [ 84 ] and this has served as a basis for research studying family cohesion as a protective factor for suicidal behavior in young people [ 85 ]. However, more studies are still required in this field to deepen these associations.…”

Assessing Prevalence and Unique Risk Factors of Suicidal Ideation among First-Year University Students in China Using a Unique Multidimensional University Personality Inventor

“…It was demonstrated there was a causal pathway from social network strain (due to adverse childhood experiences) to suicidal ideation among middle-aged adults [ 24 ]. Social networks during adolescence influenced the odds of belonging to distinct suicidal trajectories [ 50 ]. Family cohesion protects youth from being in high-risk developmental courses of suicidal behaviors [ 50 ].…”

Social Determinants of Health and Suicidal Behaviors among Children: U.S. Longitudinal Adolescent Brain Cognitive Development (ABCD) Study

“…We used hierarchical agglomerative clustering because it is robust to different types of data distributions and typically produces a dendrogram that visualizes the data structure to help determine the optimal cluster number, and because it has shown promise in identifying underlying patterns from clinical profiles. [41][42][43][44][45] Besides producing the dendrogram, we calculated 14 measures of clustering models provided by 'NbClust' software 46 to determine the optimal number of clusters, i.e., patterns of SDoH. More details and rationale for these methods can be found in the eMethods 2 and 3 in the Supplemental Online Content.…”