Identifying Effective Intervention Targets for Depressive Symptoms Across Adolescence: A Network-Based Simulated Intervention

Depressive symptoms are prevalent and demonstrate distinct developmental trajectories throughout adolescence. Although previous research has suggested central symptoms as possible intervention targets, few studies have explored the effects of targeting these symptoms on global network states. Utilizing the Ising model and the NodeIdentifyR algorithm, this study aimed to identify effective intervention targets and examine their associations with central symptoms across different stages of adolescence. A total of 46,842 participants completed the Center for Epidemiologic Studies Depression Scale and provided demographic information. Participants were categorized into early (n = 15,299), middle (n = 15,596), and late (n = 15,547) adolescence. The Ising model identified “feeling sad” and “feeling depressed” as the symptoms with the highest expected influence in early and middle-to-late adolescence, respectively. The expected influence value of “feeling depressed” increased from early to late adolescence. Simulated interventions projected that decreasing the thresholds of “feeling bad” (early adolescence) and “feeling depressed” (middle and late adolescence) would yield the greatest reduction in network activation, identifying them as effective treatment targets. Worsening “feeling sad” and “feeling depressed” (early adolescence) and “feeling blue” (middle and late adolescence) was projected to result in the greatest increase in network activation, making them the effective prevention targets. The most central symptoms were not necessarily congruent with the effective intervention targets identified by simulations. These findings may help practitioners optimize treatment and prevention efforts for adolescents with depressive symptoms across distinct developmental stages.