KMAN Publication Inc. (KMANPUB) Journal of Adolescent and Youth Psychological Studies (JAYPS) 2981-2526 7 Serial Number 42 2026 02 10 Predictive Modeling of Cognitive Flexibility and Creative Problem-Solving in Adolescents Predictive Modeling of Cognitive Flexibility and Creative Problem-Solving in Adolescents 1 11 10.61838/kman.jayps.5090 EN Journal Article 2025 09 29 <table> <tbody> <tr> <td> <p><strong>Objective:</strong> The present study aimed to develop and test a predictive model examining the extent to which cognitive flexibility explains individual differences in creative problem-solving among adolescents beyond executive functioning and demographic variables.</p> <p><strong>Methods and Materials: </strong>This quantitative cross-sectional study was conducted with a sample of 438 adolescents aged 13–17 years recruited from secondary schools in Spain using multistage cluster random sampling. Cognitive flexibility was assessed using the Spanish adaptation of the Cognitive Flexibility Inventory, and creative problem-solving was measured through a combined performance-based task battery and self-report scale evaluating fluency, flexibility, originality, and elaboration. Executive functioning variables, including working memory and inhibitory control, were measured using standardized teacher-report instruments, and academic achievement data were obtained from school records. Data analysis included descriptive statistics, Pearson correlations, hierarchical multiple regression, and structural equation modeling. In addition, a machine learning random forest regression model with 10-fold cross-validation was applied to compare predictive accuracy with traditional regression approaches.</p> <p><strong>Findings: </strong>Cognitive flexibility demonstrated a strong positive association with creative problem-solving (p &lt; 0.001). Hierarchical regression analyses revealed that cognitive flexibility significantly increased the explained variance in creative problem-solving beyond demographic and executive control variables, with the final model accounting for 47 percent of the variance (ΔR² = 0.26, p &lt; 0.001). Both flexibility dimensions emerged as significant predictors (p &lt; 0.001). Structural equation modeling confirmed a strong latent path from cognitive flexibility to creative problem-solving (β = 0.68, p &lt; 0.001), with the overall model demonstrating excellent fit indices and explaining 52 percent of the variance. Machine learning analyses corroborated the dominant predictive contribution of cognitive flexibility.</p> <p><strong>Conclusion: </strong>The findings indicate that cognitive flexibility functions as a central and robust predictor of creative problem-solving in adolescence, integrating executive control processes and contributing substantial incremental validity.</p> </td> </tr> </tbody> </table> https://www.journals.kmanpub.com/index.php/jayps/article/download/5090/9181