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Random forest model combined with LASSO regression to analyze the influencing factors of aggressive behavior among high school students
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Yaxin LI, Qibi HU, Xingyu WANG, Xin LIU, Hongjuan CHANG*
Chinese Journal of School Health | 2025, 46(10) : 1437 - 1442
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Chinese Journal of School Health | 2025, 46(10): 1437-1442
• Mental Health •
Random forest model combined with LASSO regression to analyze the influencing factors of aggressive behavior among high school students
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Yaxin LI, Qibi HU, Xingyu WANG, Xin LIU, Hongjuan CHANG*
Affiliations
  • School of Medicine, Wuhan University of Science and Technology, Wuhan 430000, Hubei Province, China
Published: 2025-10-25 doi: 10.16835/j.cnki.1000-9817.2025292
Outline
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Objective

To analyze the influencing factors of aggressive behaviors in high school students, rank the importance of relevant variables with visual presentation, so as to provide new references for developing intervention strategies.

Methods

In December 2024, a convenience sampling method was used to select 5 330 students from 5 high schools in Wuhan for an online questionnaire survey. The survey included the Buss-Perry Aggression Questionnaire (BPAQ), Interaction Anxiety Scale (IAS), Emotion Regulation Ability Scale, Inventory of Parent and Peer Attachment (IPPA), and a self-designed general information questionnaire. Variables were screened using LASSO regression, followed by multivariate Logistic regression analysis. The Random Forest model was then employed to rank and visualize variable importance.

Results

Univariate analysis and LASSO regression results indicated that gender, emotion regulation capability, paternal attachment quality, maternal attachment quality, maternal parenting style, paternal parenting style, parenting consistency, monthly household income per capita, school climate, relationship with classmates, interaction anxiety, and academic ranking were all significant variables (all P < 0.01). Multivariate Logistic regression analysis identified the following as influencing factors of aggressive behaviors in high school students: emotional management ability (OR=0.38, 95%CI=0.34-0.43), gender (OR=0.83, 95%CI=0.75-0.93), mother attachment quality (OR=0.89, 95%CI=0.74-1.07), father attachment quality (OR=0.76, 95%CI=0.66-0.87), interaction anxiousness (OR=1.58, 95%CI=1.40-1.78), consistency of parenting styles of parents (OR=1.40, 95%CI=1.21-1.62), school atmosphere (OR=1.50, 95%CI=1.14-1.98), academic performance ranking (upper-middle: OR=0.76, 95%CI=0.61-0.93; middle: OR=0.70, 95%CI=0.57-0.86) were the influencing factors of aggressive behavior in high school students (all P < 0.05). The results of Random Forest showed that emotional management ability was the most important factor affecting aggressive behavior in high school students.

Conclusion

Emotion regulation capability is identified as the core predictor of adolescent aggressive behaviors, which can significantly reduce the incidence of aggressive behaviors through enhanced emotion management.

Models, statistical  /  Regression analysis  /  Aggression  /  Students
李亚昕, 胡旗碧, 汪星宇, 刘欣, 常红娟. 随机森林模型联合LASSO回归分析高中生攻击性行为影响因素. 中国学校卫生, 2025 , 46 (10) : 1437 -1442 . DOI: 10.16835/j.cnki.1000-9817.2025292
Yaxin LI, Qibi HU, Xingyu WANG, Xin LIU, Hongjuan CHANG. Random forest model combined with LASSO regression to analyze the influencing factors of aggressive behavior among high school students[J]. Chinese Journal of School Health, 2025 , 46 (10) : 1437 -1442 . DOI: 10.16835/j.cnki.1000-9817.2025292
Year 2025 volume 46 Issue 10
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Article Info
doi: 10.16835/j.cnki.1000-9817.2025292
  • Receive Date:2025-05-08
  • Online Date:2026-11-06
  • Published:2025-10-25
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  • Received:2025-05-08
  • Revised:2025-08-02
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    School of Medicine, Wuhan University of Science and Technology, Wuhan 430000, Hubei Province, China
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表12种不同金属材料的力学参数
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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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