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Entropy-based risk network identification in adolescent self-injurious behavior using machine learning and network

Zheng Zhang1, Honghui Chen2,3, Yanyue Ye1

  • 1Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China.

Translational Psychiatry
|August 20, 2025
PubMed
Summary
This summary is machine-generated.

Adolescent self-injurious behavior (SIB) is predicted by factors like loneliness, anxiety, and internet addiction. Understanding these interconnected risks is key for early intervention and prevention strategies.

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Area of Science:

  • Psychiatry
  • Psychology
  • Public Health

Background:

  • Adolescent self-injurious behavior (SIB) affects 13.7% globally, necessitating early identification and intervention to prevent suicide and self-harm.
  • Rising awareness of SIB highlights the critical need for robust prediction mechanisms.

Purpose of the Study:

  • To explore the multidimensional risk factors for adolescent SIB using Psychopathological Network Theory.
  • To develop a precise risk assessment approach by integrating network analysis and machine learning.

Main Methods:

  • Survey of 2047 adolescents (aged 11-17) in China, analyzing 19 physiological, psychological, and social variables.
  • Application of machine learning, network analysis, and the Entropy Weight Method (EWM) for risk evaluation.

Main Results:

  • Identified key risk factors: loneliness, ADHD symptoms, internet addiction, anxiety, depression, affinity for solitude, autistic traits, and bullying.
  • Revealed a complex network structure where these factors interact, directly and indirectly influencing SIB.
  • EWM, network analysis, and machine learning integration offered a more precise adolescent SIB risk assessment.

Conclusions:

  • Findings provide insights into SIB's causal mechanisms, emphasizing interconnected risk factors.
  • Highlights the importance of targeted prevention and intervention strategies for adolescent SIB.
  • The integrated approach offers a more accurate method for assessing SIB risk in adolescents.