Explainable machine learning unveils the key role of cooperation ability in school bullying and its gender-differentiated impact on cooperative atmosphere - Scorecard - MDSpire
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Explainable machine learning unveils the key role of cooperation ability in school bullying and its gender-differentiated impact on cooperative atmosphere
Clinical Scorecard: Utilizing Explainable Machine Learning to Highlight the Importance of Cooperative Skills in School Bullying and Its Gender-Specific Effects on Collaborative Environments
At a Glance
Category
Detail
Condition
School Bullying
Key Mechanisms
Association between school bullying and social-emotional skills, particularly cooperation ability.
Target Population
Adolescents aged 10–16 years in Suzhou, China.
Care Setting
Educational environments.
Key Highlights
50.8% of adolescents experienced bullying.
Cooperation Ability is the most predictive social-emotional dimension related to bullying.
XGBoost model showed the best predictive performance for Cooperation Atmosphere.
Gender-specific analysis revealed distinct predictive patterns for males and females.
Key predictors include school belonging, competitive climate, and peer support.
Guideline-Based Recommendations
Diagnosis
Assess social-emotional skills using the OECD’s framework.
Management
Implement targeted interventions to improve cooperation ability and school climate.
Monitoring & Follow-up
Regularly evaluate the cooperation atmosphere and bullying incidents.
Risks
Involvement in bullying is linked to long-term psychological and educational harm.
Patient & Prescribing Data
Chinese adolescents aged 10–16 years.
Focus on enhancing cooperation skills and supportive school environments.
Clinical Best Practices
Foster a supportive cooperation atmosphere in schools.
Encourage collaborative behaviors among students.
Address gender-specific needs in bullying interventions.
