Related Experiment Video
Updated: Feb 3, 2026

Assessment and Evaluation of the High Risk Neonate: The NICU Network Neurobehavioral Scale
Published on: August 25, 2014
Who is most at risk, and when? Gender-differentiated patterns and risk heterogeneity of adolescent depression in
Chengxi Hu1, Yiqiao Qi2, Wenfei Winnie Wang2
1Department of Psychological and Cognitive Sciences, Tsinghua University, Beijing, China.
Abstract:
Adolescent depression is a major public health concern involving well-documented gender differences that may vary across cultural contexts. In China's academically intensive educational environment, questions regarding when depression risk peaks across adolescence, how behavioral and social factors relate to depression differentially by gender, and how risks cluster into distinct vulnerability profiles remain underexplored. This cross-sectional study analyzed data from a nationwide survey of 414,175 Chinese adolescents. We used generalized additive models and latent profile analysis to examine gender-differentiated age patterns and behavioral-social risk configurations. Results showed that girls reported higher depression scores than boys. Age patterns differed by gender: girls exhibited persistently elevated depression between ages 14-18, whereas boys showed na less pronounced inverted U-shaped pattern with resurgence in late adolescence. Behavioral risks (substance use, screen time) were more strongly associated with depression among girls, whereas physical activity and perceived socioeconomic resources were stronger protective factors for girls. Latent profile analysis identified three subgroups-"Active Advantaged," "Inactive Disadvantaged," and "Screen-Dependent"-with girls in the Screen-Dependent profile (10 %; high screen time, low physical activity) showing markedly higher depression levels. The findings highlight the need for continuous mental health monitoring for girls throughout mid-to-late adolescence (ages 14-18), increased support for boys approaching late adolescence (ages 16-18), and targeted interventions addressing clustered risks in high-screen-use, low-activity subgroups.
More Related Videos
08:42Design and Implementation of an fMRI Study Examining Thought Suppression in Young Women with, and At-risk, for Depression
Published on: May 19, 2015
05:52Handwriting Analysis Indicates Spontaneous Dyskinesias in Neuroleptic Naïve Adolescents at High Risk for Psychosis
Published on: November 21, 2013
Related Concept Videos
Relative Risk
Factors Affecting the Risk of Infection
The integrity and count of the white blood cells help the body resist pathogens and fight infection. When impaired, it reduces the body's resistance to pathogens. The acidic pH levels of the gastrointestinal, genitourinary tracts, and skin...
The Evidence for Evolution
Design Example: Analyzing Capacity Contours for Flood Risk Assessment
National Nursing Organizations I
Long-term Depression