KMAN Publication Inc. (KMANPUB) Journal of Adolescent and Youth Psychological Studies (JAYPS) 2981-2526 7 Serial Number 41 2026 01 10 Neural Network Analysis of Adolescent Depression: The Interactive Roles of Loneliness, Family Communication Quality, and Digital Media Dependency Neural Network Analysis of Adolescent Depression: The Interactive Roles of Loneliness, Family Communication Quality, and Digital Media Dependency 1 9 10.61838/kman.jayps.4990 EN Journal Article 2025 09 27 <table> <tbody> <tr> <td> <p><strong>Objective:</strong> This study aimed to examine the nonlinear and interactive effects of loneliness, family communication quality, and digital media dependency on depressive symptoms among Indonesian adolescents using neural network modeling.</p> <p><strong>Methods and Materials: </strong>A cross-sectional design was implemented with 684 secondary school students aged 14–18 years selected via multistage cluster sampling from urban regions of Indonesia. Participants completed validated measures assessing depressive symptoms, loneliness, family communication quality, and digital media dependency. Data were analyzed using a multilayer perceptron neural network constructed in Python with TensorFlow. The dataset was partitioned into training, validation, and test sets. Model performance was evaluated using root mean square error, mean absolute error, and coefficient of determination. Predictor contributions and interaction effects were interpreted using SHAP values and partial dependence analyses.</p> <p><strong>Findings: </strong>The neural network demonstrated high predictive accuracy (R² = .79 on the test set). Loneliness emerged as the strongest predictor of depressive symptoms, followed by digital media dependency and family communication quality. Significant nonlinear interaction effects were observed, indicating that the combination of high loneliness, poor family communication, and elevated digital media dependency produced the highest levels of depressive symptoms. Family communication quality exerted a strong buffering effect that attenuated the impact of loneliness and digital dependency on depression.</p> </td> </tr> </tbody> </table> <p><strong>Conclusion: </strong>Adolescent depression is shaped by complex, interactive psychosocial and digital factors that are effectively captured through neural network modeling. Strengthening family communication and promoting healthy digital engagement may substantially reduce depressive risk among adolescents.</p> https://journals.kmanpub.com/index.php/jayps/article/download/4990/8999