Background Amidst rural revitalization, parents in rural areas navigate the complex dual responsibilities of structural socio-economic transition and intensive family education. While subjective well-being (SWB) is a critical indicator of parental psychological health, the statistical pathways that may account for the association between external community resources and internal well-being—and the boundary conditions of this process—remained underexplored. Methods Drawing upon the Family Demands-Resources (FD-R) model and Conservation of Resources (COR) theory, this study proposed and tested an integrative model. We specified psychological resilience as a statistical mediator of the association between community embedded support and SWB, with parenting stress moderating the latter stage of this indirect association. A cross-sectional survey was conducted among 358 rural parents (males 30.45%, females 69.55%), utilizing validated psychometric instruments (WHO-5, CD-RISC, PSI-SF, and PCSQ). Structural equation modeling (SEM) was employed to examine the structural relationships. Results The findings indicated that CES was positively associated with SWB, with psychological resilience serving as a significant partial mediator. Furthermore, parenting stress moderated the latter stage of the indirect association. The index of moderated mediation was significant, and the conditional indirect association between CES and SWB through psychological resilience became weaker as parenting stress increased. This pattern was consistent with a resource-depletion explanation. Conclusion These findings highlight the joint relevance of community resources, psychological resilience, and parenting stress to rural parents’ SWB. Psychological resilience may help explain the association between CES and SWB, but this indirect association was weaker among parents reporting higher parenting stress.
L. Xing, Xue Wu· Frontiers in Psychology· 0 citations
Artificial intelligence (AI) is entering child nutrition through dietary assessment, malnutrition forecasting, clinical decision support, meal recommendation, conversational interventions, and food-environment monitoring. The consequences of these applications converge in everyday eating. This Mini Review synthesizes evidence on how AI measures nutritional states and mediates food choice, communication, sensory acceptance, family practice, and digital exposure. The evidence supports two connected functions. As nutritional intelligence, AI converts clinical, dietary, and environmental data into assessments or predictions. As gastronomic mediation, it participates in decisions about what foods are noticed, recommended, prepared, discussed, and accepted. Direct pediatric validation is strongest for bounded assessment and forecasting tasks. Child meal-planning studies and generative-AI evaluations based on standardized adolescent profiles reveal a gap between nutrient optimization, culinary coherence, and nutritional safety. A large adolescent chatbot trial combined scalable delivery with null intention-to-treat effects on diet quality and BMI trajectory. Co-design and behavioral studies further identify familiarity, texture, participation, and caregiver involvement as central design variables. We propose five iterative translational gates: technical validity, nutritional validity, behavioral acceptability, contextual legitimacy, and real-world effectiveness and implementation. Future research should combine age-specific nutritional constraints with sensory and cultural knowledge, evaluate performance across food cultures, preserve professional and caregiver oversight, and test outcomes in homes, schools, clinics, and digital food environments. AI can advance child-focused gastronomy by translating computational outputs into safe, culturally meaningful, and developmentally appropriate eating practices.
L. Xing, Xue Wu· Frontiers in Nutrition· 0 citations
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