CatBoost Modeling of Parenting Effectiveness Based on Mindfulness, Emotional Intelligence, Psychological Flexibility, and Reflective Functioning - Aydemir, Selin; Chaisiri, Nattaporn; Kováčik, Andrej (Applied Family Therapy Journal (AFTJ), 2026)
Objective: The present study aimed to develop and evaluate a CatBoost machine learning model for predicting parenting effectiveness based on mindfulness, emotional intelligence, psychological flexibility, and reflective functioning among parents in Thailand. Methods and Materials: This cross-sectional predictive study was conducted among 742 parents recruited from Bangkok, Chiang Mai, Phuket, Khon Kaen, and Nakhon Ratchasima, Thailand. Participants completed the Parenting Sense of Competence Scale, Five Facet Mindfulness Questionnaire, Wong and Law Emotional Intelligence Scale, Acceptance and Action Questionnaire-II, and Reflective Functioning Questionnaire. Following data screening and preprocessing procedures, a CatBoost machine learning algorithm was implemented to predict parenting effectiveness. 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 squared error (RMSE), mean absolute error (MAE), and mean absolute percentage error (MAPE). SHAP (Shapley Additive Explanations) analyses were additionally conducted to examine feature importance and interpret predictor contributions. Findings: The results revealed significant positive associations between parenting effectiveness and mindfulness (r = .69, p < .001), emotional intelligence (r = .72, p < .001), psychological flexibility (r = .65, p < .001), and reflective functioning (r = .67, p < .001). The CatBoost model demonstrated strong predictive performance, explaining 84.2% of the variance in parenting effectiveness in the training dataset (R² = .842) and 81.6% in the testing dataset (R² = .816), with a cross-validation R² of .808. Feature importance analysis indicated that emotional intelligence was the strongest predictor (32.8%), followed by mindfulness (28.6%), reflective functioning (21.7%), and psychological flexibility (16.9%). SHAP analyses confirmed that higher levels of all four predictors contributed positively to parenting effectiveness predictions, with emotional intelligence exerting the greatest overall influence on model outputs. Conclusion: The findings demonstrate that parenting effectiveness is strongly influenced by emotional, cognitive, and self-regulatory psychological capacities. Emotional intelligence emerged as the most important determinant, followed by mindfulness, reflective functioning, and psychological flexibility. The high predictive accuracy of the CatBoost model highlights the utility of machine learning approaches for understanding complex parenting processes and identifying key psychological resources that may serve as targets for intervention. Strengthening these capacities may enhance parenting effectiveness and contribute to healthier family functioning and child development outcomes.