AUTHOR=Li Miaomiao , Lv Jing , Li Shaoxiong , Liu Congcong , Wang Ziyan , Liu Zheng , Liu Huan , Liu Xuan , Du Yuru , Li Youdong 

TITLE=Directionality of causal association between adolescent mental health and attention deficit: an empirical analysis using a hybrid network model

JOURNAL=Frontiers in Psychology

VOLUME=Volume 16 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/psychology/articles/10.3389/fpsyg.2025.1658007

DOI=10.3389/fpsyg.2025.1658007

ISSN=1664-1078

ABSTRACT=ObjectiveBy constructing undirected and Bayesian network models, this study overcomes the limitations of traditional correlation analyses, revealing the underlying causal relationships and operational mechanisms between adolescent mental health and attention deficits.MethodsA total of 19,157 valid responses (effective response rate: 96.92%) were collected from adolescents aged 11–20 (<0.1% aged 20) at secondary schools in a Hebei Province region via the Wenjuanxing platform. Mental health (10 dimensions) and attention problems (3 dimensions) were assessed using the Mental Health Scale for Secondary School Students in China (MSSMHS; 60 items, α = 0.976) and the Swanson, Nolan, and Pelham Rating Scale-IV (SNAP-IV-26; 26 items, α = 0.942). In R Studio, an undirected network was constructed using the EBICglasso algorithm (with regularization and 1,000 bootstrap tests), and centrality analysis identified core variables. A directed acyclic graph (DAG) was generated via Bayesian network analysis (hill-climbing algorithm) with 50 random restarts, 100 perturbations, and 100 bootstrap validations (edge stability threshold: 0.85; edges retained only if present in ≥85% of subsamples), elucidating causal pathways between mental health and attention deficits.ResultsUndirected network analysis revealed the strongest associations between depression and anxiety, hyperactivity/impulsivity and oppositional defiant behavior, and paranoia and interpersonal sensitivity. Centrality metrics showed anxiety with the highest strength centrality, paranoia with the highest closeness centrality and betweenness centrality. In the Bayesian DAG, interpersonal sensitivity, anxiety, and paranoia occupied the top hierarchical level, connecting to intermediate nodes (e.g., hostility, emotional instability, sense of academic pressure) and ultimately to terminal nodes (attention deficit, oppositional defiant behavior, psychological imbalance, hyperactivity/impulsivity).ConclusionThis study demonstrates that adolescent mental health influences attention deficits through multiple distinct causal pathways: ① interpersonal sensitivity, anxiety, emotional instability, and hostility lead to inattention; ② anxiety, paranoia, depression, and hostility contribute to hyperactivity/impulsivity; ③ interpersonal sensitivity, hostility, depression, emotional instability, and sense of academic pressure result in oppositional defiant behaviors. These findings identify precise intervention targets for distinct dimensions of attention deficits in adolescents and provide mechanistic empirical evidence for understanding the multidimensional causal architecture through which psychological symptoms impact behavioral outcomes.