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. 2025 Apr 29:16:1557351.
doi: 10.3389/fpsyt.2025.1557351. eCollection 2025.

Network analysis of core factors related to non-suicidal self-injury in adolescents with mood disorders

Wenyan Zhang  1 , Xiaohui Song  2 , Xianbin Wang  1 , Zhongliang Jiang  1 , Yuebing Zhang  3 , Yonghua Cui  1
Affiliations

Network analysis of core factors related to non-suicidal self-injury in adolescents with mood disorders

Wenyan Zhang et al. Front Psychiatry. .

Abstract

Introduction: Adolescents with mood disorders are at an exceptionally high risk for non-suicidal self-injury (NSSI); however, the understanding of the core factors underlying this vulnerability remains limited. This knowledge gap significantly hampers the effectiveness of targeted prevention and intervention strategies.

Methods: A total of 263 adolescents with mood disorders completed a series of self-report surveys, covering demographic, personal, and social factors related to NSSI. We first used least absolute shrinkage and selection operator (LASSO) regression to identify the core related factors. Then, we employed network analysis to construct the network structure of these core factors.

Results: Our findings indicate that depressive and anxiety symptoms are the strongest influencing factors for NSSI among adolescents with mood disorders. Life events and the specific functions of NSSI are identified as personalized factors within this group. Additionally, objective social support and education level emerged as potential protective factors against NSSI. These factors are not independent but interact with each other.

Conclusion: By identifying and intervening in these key factors, more effective prevention strategies and personalized treatment plans can be developed, ultimately improving the quality of life and psychological well-being of adolescents with mood disorders.

Keywords: adolescents; machine learning; mood disorders; network analysis; non-suicidal self-injury.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Recruitment and data collection process of adolescents with mood disorder.
Figure 2
Figure 2
(A) shows the trend of mean squared error with changes in λ, and (B) shows the trend of regression coefficients with changes in λ. LASSO regression identified λ = 1.3476 at one standard error of the minimum mean squared error (1se), resulting in 8 selected independent variables.
Figure 3
Figure 3
Network structure of core factors related to NSSI in adolescents with mood disorders. Within these network representations, blue lines signify positive associations, while red lines indicate negative ones. The magnitude of the correlation is visually captured by the line thickness.
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