Psychology research and behavior management
Ecological Correlates of Depressive Symptoms among Chinese Adolescents: A Random Forest and Nomogram Analysis of CFPS Data
By Mei S, Su Y, Yue J and 11 others.
Abstract
Background
Adolescence represents a critical developmental stage characterized by complex stressors, including academic pressure and interpersonal challenges, which significantly elevate the risk of depressive symptoms. While conventional research predominantly relies on linear methodologies focusing on isolated environmental determinants, the multi-level interactive effects of ecological environments on adolescent depressive symptoms remain under-explored.
Methods
Utilizing longitudinal data from the 2020 and 2022 China Family Panel Studies (CFPS), this study included a sample of 971 adolescents (aged 10-15). Baseline ecological variables and covariates were measured in 2020, while the outcome-depressive symptoms-was assessed in 2022 using the 8-item Center for Epidemiologic Studies Depression Scale (CES-D8). We integrated a machine learning framework (Random Forest, RF) to predict continuous CES-D8 scores and a nomogram model to predict binary depression risk (CES-D8 ≥ 9). The nomogram was internally validated using 1000 bootstrap resamples.