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<p>This study investigates the multidimensional structure and ecological correlates of Korean adolescents’ socio-emotional skills using a person-centered, data-driven approach grounded in the OECD Social and Emotional Skills (SSES) framework. Utilizing nationally representative data from the Korean Children and Youth Panel Survey (KCYPS; <i>N</i> = 2,275), latent profile analysis (LPA) identified three distinct subgroups with satisfactory classification quality: (1) Holistically Competent and Well-Adjusted (20.1%), (2) Emotionally Sensitive but Socially Withdrawn (47.5%), and (3) Cognitively Engaged but Low Empathic Engagement (32.4%). To identify ecological factors predictive of subgroup membership, a stacked ensemble machine learning model based on cross-validation accuracy–weighted probabilistic ensemble (CAWPE) was employed, integrating individual-, family-, and school-level variables. Model performance was evaluated on a held-out validation set, yielding a one-vs-rest multiclass AUC of 0.879, indicating high discriminative ability. The most influential predictors included parental cognitive empathy and creativity, adolescents’ self-esteem, peer and teacher relationships, household income, and engagement in leisure and career-related activities. Findings reveal that socio-emotional development in early adolescence is not a linear process but reflects a multidimensional interplay of psychological, relational, and contextual factors within proximal ecological systems. By empirically operationalizing the OECD SSES framework using large-scale national data, this study provides a novel cross-level validation of socio-emotional skill indicators and demonstrates how person-centered and predictive analytics can inform evidence-based, developmentally targeted interventions and policy design.</p>

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Ecological and Predictive Indicators of Social and Emotional Skills among Korean Adolescents: A Person-Centered Analysis within the OECD SSES Framework

  • 期刊论文

  • 发表日期：

    2026年3月13日

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  • Nayoung Kim

摘要

This study investigates the multidimensional structure and ecological correlates of Korean adolescents’ socio-emotional skills using a person-centered, data-driven approach grounded in the OECD Social and Emotional Skills (SSES) framework. Utilizing nationally representative data from the Korean Children and Youth Panel Survey (KCYPS; N = 2,275), latent profile analysis (LPA) identified three distinct subgroups with satisfactory classification quality: (1) Holistically Competent and Well-Adjusted (20.1%), (2) Emotionally Sensitive but Socially Withdrawn (47.5%), and (3) Cognitively Engaged but Low Empathic Engagement (32.4%). To identify ecological factors predictive of subgroup membership, a stacked ensemble machine learning model based on cross-validation accuracy–weighted probabilistic ensemble (CAWPE) was employed, integrating individual-, family-, and school-level variables. Model performance was evaluated on a held-out validation set, yielding a one-vs-rest multiclass AUC of 0.879, indicating high discriminative ability. The most influential predictors included parental cognitive empathy and creativity, adolescents’ self-esteem, peer and teacher relationships, household income, and engagement in leisure and career-related activities. Findings reveal that socio-emotional development in early adolescence is not a linear process but reflects a multidimensional interplay of psychological, relational, and contextual factors within proximal ecological systems. By empirically operationalizing the OECD SSES framework using large-scale national data, this study provides a novel cross-level validation of socio-emotional skill indicators and demonstrates how person-centered and predictive analytics can inform evidence-based, developmentally targeted interventions and policy design.