Two major global trends shaping 21st-century society are population aging and urbanization. Consequently, the living conditions of older adults have become an increasing focus of societal attention. Social–Emotional Responses play a crucial role in the mental health, emotional well-being, and social identity of older adults. Urban streets, as key sites for walking and social activity among older adults, can be seen as extensions of their homes—places where they regularly interact with neighbors and build new connections. Compared to built environments often termed “gray spaces,” exposure to green spaces has been shown to offer greater benefits to residents’ well-being. Among streetscape features, the Spatial Openness Level is closely associated with the psychological well-being of elderly individuals. Visual-spatial features correlate with an EEG-derived proxy for emotional state during exposure to street scenes. The Gray-Green space Exposure Ratio (GER) and Spatial Openness Level (SOL) serve as key indicators for evaluating streetscape quality. Designing age-friendly streets requires evidence-based tools that link visual features to emotional well-being. This study provides such a tool by combining EEG measurements with configurational analysis of street visual dimensions: SOL and GER. In this study, conducted in Wuhan City, objective physiological monitoring of brainwave activity was employed to examine the responses of older adults to variations in GER and SOL. The results indicate that SOL significantly influences the emotional states of older adults (correlation coefficient R2 = 0.7262, p 0.01). These results allow us to rank the nine tested scenes. For example, Scene L-3 (open space with abundant vegetation) scored highest on emotional well-being, while Scene H-1 (enclosed gray space) scored lowest. The difference is explained by the configurational logic: greenery delivers emotional benefits only when combined with sufficient openness. The findings will enable EEG data to extend beyond serving as a unique standalone outcome and integrate into a more comprehensive explanatory model. This model aims to elucidate how urban morphology influences the micro-foundations of social activity in later life. Furthermore, it seeks to equip urban designers and policymakers with an evidence-based tool for creating age-friendly environments, facilitating a shift from intuition-driven to evidence-based design. Future research should incorporate additional environmental factors to establish a more comprehensive assessment framework for age-friendly urban spaces.
Min et al. (Wed,) studied this question.