Differential Analysis of Adolescent Mental Health Early Warning Levels via Machine Learning

Abstract

Drawing on the citywide survey of 95 545 adolescents reported by Zhao et al., we find that school bullying is a key driver of deteriorating youth mental health. The pression, anxiety, stress-related symptoms and psychotic-like experiences are all rising, while the age of first depressive episode keeps falling. To quantify these links, the current study conducts a differential analysis of mental health early warning levels across middle and high school, systematically comparing alternative baseline distribution and multi-dimensional features to produce an evidence-based metric linking risk influential factors to graded alert thresholds. These results demonstrate that proactive bullying prevention and early intervention strategies are critical to reversing the trajectory of declining adolescent mental health and reducing the incidence of early-onset depression.