Background and objectives: Adolescent depression and anxiety are becoming increasingly prevalent in China, with rates reaching 20%–30%, driven largely by intense academic pressure and the cultural tendency toward somatization. Traditional screening tools, such as the Patient Health Questionnaire-9 (PHQ-9) and Generalized Anxiety Disorder-7 (GAD-7), often suffer from subjective bias, recall errors, and underreporting due to social stigma. This study developed an AI-based intelligent diagnosis system (IDS) using multitask deep learning to non-intrusively predict comorbid depression and anxiety severity based on the spontaneous textual expressions of Chinese adolescents. Methods: Textual responses from approximately 1,275 adolescents were collected and labeled with clinician-assessed PHQ-9 and GAD-7 scores. Preprocessing involved jieba segmentation and variational autoencoder (VAE)-based data augmentation to address class imbalance, resulting in an expanded test set of 308 samples. The IDS architecture utilizes a Chinese-optimized BERT encoder with self-attention and dual-feature fusion (combining pooled [CLS] tokens and global pooling) to extract shared representations. These are processed through multitask heads for regression (MSE loss) and classification (weighted cross-entropy). The model was trained using an 8:1:1 split with AdamW optimization, cosine annealing, and regularization, supported by ablation studies to validate individual components. Results: On the test set, the IDS achieved Pearson correlation coefficients of 0.706 for PHQ-9 and 0.693 for GAD-7, with AUC values of 0.877 and 0.902, respectively. Binary classification yielded F1-scores of 0.762 (PHQ-9) and 0.863 (GAD-7). Ablation analysis confirmed that the multitask learning framework improved F1-scores by 6.2%–7.8% and reduced MSE by 14.2%–18.4%. Furthermore, adaptations for somatization and data augmentation for severe cases significantly enhanced the system’s sensitivity. Conclusion: The IDS offers a robust, culturally sensitive, and scalable tool for adolescent mental health screening. By outperforming single-task baselines, it provides a proactive, privacy-preserving alternative to traditional self-reports. Future research will focus on longitudinal validation, multimodal integration, and ethical deployment strategies to maximize the system’s utility in educational and clinical settings.

Although previous studies have extensively explored the relationship between urban green spaces and residents’ well-being, research on how nature-based sports venues enhance urban well-being through multiple emotional mechanisms remains relatively limited. Drawing on environmental psychology, place attachment theory, and the principles of biophilic design, this study constructs a dual-mediation model incorporating Connectedness to Nature (CN) and Place Attachment (PA) to examine the pathways through which natural design features—including Natural Visibility (NV), Spatial Integration (SI), and Human–Nature Interactivity (HNI)—influence individuals’ urban well-being. Using ten representative nature-integrated sports venues in China as research sites, a total of 856 valid questionnaires were collected, and structural equation modeling (SEM) was applied for empirical analysis. The results show that (1) NV, SI, and HNI all exert significant positive effects on CN and PA; (2) CN significantly promotes both PA and Urban Well-being (UWB); (3) PA has a significant positive effect on UWB; and (4) both CN and PA serve as significant mediators between natural design features and UWB, with an evident serial mediation effect from CN to PA. These findings reveal the multilayered psychological mechanisms through which nature-based sports venues enhance residents’ well-being, enrich the theoretical framework of nature-oriented design and urban sustainability, and provide empirical evidence for the health-oriented and emotion-responsive design of urban sports facilities.

With the increasing depth of research on built environments, theories of restorative environments and concepts of biophilic design have garnered widespread attention in the field of architecture. Based on Attention Restoration Theory (ART) and Flow Theory, this study systematically investigates how the architectural environment of aquatic centers influences users’ learning engagement in sports through psychological mechanisms. Analysis of cross-sectional data from 865 users revealed that all four core dimensions of restorative environments (being away, extent, fascination, and compatibility) significantly positively affect users’ learning engagement in aquatic centers. Psychological flow was found to mediate the relationship between these restorative dimensions and learning engagement. Building on previous research, this study constructs a theoretical framework of “restorative design–flow experience–learning behavior”, integrating the architectural features of aquatic centers with users’ psychological experiences. This approach addresses the gap in existing research where architectural elements and user psychological experiences have been studied in isolation, providing a theoretical basis for optimizing user experience through environmental interventions in sports architecture. The findings extend the application of environmental psychology in sports architecture and offer practical guidance for designing aquatic environments that promote learning engagement.