ArticleResearch on child and adolescent psychopathology2026
Heterogeneous Joint Trajectories of Dual-Factor Mental Health in Chinese Middle Adolescence: Integrating Emotional and Behavioral Indicators.
Article in Research on child and adolescent psychopathology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
The dual-factor model of mental health suggests that positive and negative aspects are distinct, allowing adolescents to be categorized into four groups: flourishing, languishing, symptomatic but content, and troubled, based on different combinations of strengths and difficulties. However, prior research has often focused solely on emotional indicators, neglecting behavioral dimensions in both positive and negative domains. In addition, most studies have been cross-sectional, leaving it unclear whether these patterns remain stable over time or how various factors predict adolescents' subgroup trajectories. To this end, this study used composite indicators of depressive symptoms, well-being, conduct problems and prosocial behavior to examine the heterogeneous developmental trajectories of mental health during middle adolescence, while also assessing the predictive roles of stress and emotion regulation. Using five waves of longitudinal data from 1,391 Chinese adolescents and parallel-process latent class growth model, we identified four distinct trajectories: "flourishing and improving"; "emotionally adaptive but behaviorally troubled"; "emotionally troubled but behaviorally adaptive"; and "Troubled". Moreover, stress (including daily and early-life stress) and emotion regulation (including cognitive reappraisal and expressive suppression) showed distinct associations with adolescents' trajectory membership. These findings support a developmental test of the dual-factor model by showing that both emotional and behavioral domains are crucial for distinguishing the heterogeneous mental health trajectories, as positive and negative indicators demonstrate greater independence across domains than within them. In addition, they highlight subgroup-specific predictors, providing guidance for targeted interventions.
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