CatBoost Prediction of Social Anxiety Among Students with Specific Learning Disabilities: Contributions of Rejection Sensitivity, Self-Compassion, and Peer Victimization

Abstract

The present study aimed to develop and evaluate a CatBoost machine learning model for predicting social anxiety among students with specific learning disabilities based on rejection sensitivity, self-compassion, and peer victimization, while determining the relative contribution of each predictor to model performance. This cross-sectional predictive study was conducted among 428 students with specific learning disabilities enrolled in secondary schools in Santiago, Chile. Participants completed standardized measures assessing social anxiety, rejection sensitivity, self-compassion, and peer victimization. Following data preprocessing and preliminary statistical analyses, a CatBoost machine learning algorithm was implemented to predict social anxiety levels. The dataset was divided into training (80%) and testing (20%) subsets, and hyperparameter optimization was performed using five-fold cross-validation. Model performance was evaluated using the coefficient of determination (R²), root mean square error (RMSE), mean absolute error (MAE), and mean absolute percentage error (MAPE). Feature importance analysis and SHAP (Shapley Additive Explanations) values were calculated to identify the relative influence and directional effects of the predictors. The CatBoost model demonstrated strong predictive performance, accounting for 81.2% of the variance in social anxiety scores within the testing dataset (R² = .812). The model yielded low prediction errors (RMSE = 5.08, MAE = 3.94, MAPE = 8.46%), indicating high accuracy and generalizability. Feature importance analysis revealed that rejection sensitivity was the strongest predictor of social anxiety (41.82%), followed by peer victimization (34.67%) and self-compassion (23.51%). SHAP analyses showed that higher levels of rejection sensitivity and peer victimization were associated with increased social anxiety, whereas higher self-compassion was associated with lower social anxiety. Correlational analyses further indicated significant positive associations between social anxiety, rejection sensitivity, and peer victimization, alongside a significant negative association between social anxiety and self-compassion. The findings demonstrate that social anxiety among students with specific learning disabilities is strongly influenced by interpersonal vulnerability factors and psychological resilience resources. Rejection sensitivity and peer victimization represent significant risk factors, whereas self-compassion serves as an important protective factor. CatBoost modeling provides an effective and interpretable approach for identifying students at risk and may support the development of targeted school-based prevention and intervention programs aimed at improving emotional well-being and social functioning.