Yujia Qu

(1) Background: Rapid population aging in China intensifies physical and mental health challenges, including negative emotions and social barriers. Physical activity (PA) fosters resilience, adaptability, and successful aging through emotional and social benefits. This study examines the relationship between square-dancing exercise and psychological capital (PsyCap) in middle-aged and elderly individuals using cross-validation, subgroup analysis, and a cross-sequential design. (2) Methods: A cross-sectional study with 5714 participants employed a serial mediation model. Online questionnaires assessed square-dancing exercise, cognitive reappraisal, prosocial behavior tendencies, PsyCap, and interpersonal relationships. Statistical analyses were conducted using SPSS 27.0 and Mplus 8.3, incorporating correlation analysis, structural equation modeling, and subgroup comparisons. (3) Results: (a) Cognitive reappraisal and prosocial behavior mediated the link between square-dancing and PsyCap through three pathways; (b) model stability was confirmed across two random subsamples; (c) cross-group differences emerged in age and interpersonal relationships. Compared with secondary data, this study further validated PsyCap’s stability over six months post-pandemic. (4) Conclusions: The study, based on China’s largest square-dancing sample, establishes a robust serial mediation model. The findings strengthen theoretical foundations for PA-based interventions promoting psychological resilience in aging populations, highlighting structured exercise’s role in mental and social well-being.

China faces escalating aging challenges, including health decline and social isolation. Prosocial behavior, defined as situationally driven altruistic actions and inclinations, is increasingly apparent among middle-aged and older adults due to their higher levels of empathy. Based on the socio-ecological model, we examine a sports association for middle-aged and older people to deconstruct the network architecture and core components of prosocial behavior in a three-dimensional analytical framework. The adoption of a group-level perspective suggests new approaches for advancing theoretical frameworks and practical applications while offering valuable insights for empirical research on social engagement. A total of 3303 middle-aged and older participants from 52 sports organizations were surveyed. Prosocial behavior and physical activity were assessed using the Prosocial Tendencies Measure (PTM) and the Physical Activity Rating Scale-3 (PARS-3), respectively. Network models were constructed using “R language”, and Gaussian graphical models (GGMs) were used to analyze centrality and expected influence. In addition, we used network comparison tests (NCTs) to analyze group differences. (1) The prosocial behavior network demonstrated distinct clustering, with “Emotion” and “Urgency” as central dimensions and “Publicity” exhibiting a weaker influence. The key item-level nodes included “Anonymous-12” and “Altruistic-17”. (2) Significant structural differences emerged in prosocial behavior networks between the low- and high-income groups (p < 0.05) and across physical activity levels (p < 0.01). (3) No differences in global strength were observed between income groups (p ≥ 0.45), but physical activity levels significantly affected both network structure and strength (p < 0.05). This study is the first to investigate the prosocial behaviors of middle-aged and older groups in China from the perspective of network structure. This study pioneers the network analysis of prosocial behaviors among aging populations in China, uncovering three key insights: (1) Urgency and Emotion are central drivers; (2) income disparities shape behavioral pathways but do not alter overall prosocial intensity; and (3) physical activity enhances network synergy in a dose-dependent manner.