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ORIGINAL RESEARCH article

Front. Psychol.

Sec. Human Developmental Psychology

Volume 16 - 2025 | doi: 10.3389/fpsyg.2025.1658007

This article is part of the Research TopicPsychopathological and behavioral trajectories in transitional-age youth: Innovative approaches and paradigmsView all 11 articles

Directionality of Causal Association Between Adolescent Mental Health and Attention Deficit: An Empirical Analysis Using a Hybrid Network Model

Provisionally accepted
Miaomiao  LiMiaomiao Li1,2Jing  LvJing Lv1,2Shaoxiong  LiShaoxiong Li1Congcong  LiuCongcong Liu1Ziyan  WangZiyan Wang1Zheng  LiuZheng Liu1Huan  LiuHuan Liu1,2Xuan  LiuXuan Liu1,2Yuru  DuYuru Du1*Youdong  LiYoudong Li1,2*
  • 1The First Hospital of Hebei Medical University, Shijiazhuang, China
  • 2Hebei Normal University, Shijiazhuang, China

The final, formatted version of the article will be published soon.

Objective By 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. Methods A 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. Results Undirected 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). Conclusions This study demonstrates that adolescent mental health influences attention deficits through multiple distinct causal pathways: ①Interpersonal sensitivity, anxiety, emotional instability, This is a provisional file, not the final typeset article and hostility lead to inattention; ②Anxiety, paranoia, depression, and hostility contribute to hyperactivity/impulsivity; ③Interpersonal 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.

Keywords: adolescent mental health1, attention deficit2, Bayesian network3, psychologicalnetwork4, anxiety5, paranoia6, interpersonal sensitivity7

Received: 03 Jul 2025; Accepted: 01 Oct 2025.

Copyright: © 2025 Li, Lv, Li, Liu, Wang, Liu, Liu, Liu, Du and Li. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence:
Yuru Du, 59003890@hebmu.edu.cn
Youdong Li, 56601658@hebmu.edu.cn

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