Unravelling the contribution of urban public spaces to psychological well-being: a comprehensive study on seven types of public space in a metropolis
Published 30 Apr 2026 · Added to radar 5 Nov 2026
Source abstract
Although the connection between urban environments and mental health is well studied, a comprehensive outlook on the impacts of public spaces on psychological well-being has not been shared. Furthermore, few studies distinguish between different types of public spaces considering these impacts. Prior studies have focused on developed contexts and neglected how spatial, social, and natural components jointly shape users’ psychological experiences. A holistic approach to studying these components simultaneously is rare. Based on analyzing seven distinct types of urban public spaces in Tehran, an integrated model was developed linking natural components, environmental features, public space qualities to psychological well-being, with satisfaction as a mediating variable and socio-economic status as a moderator. Survey data from 700 participants were analyzed using regression, structural equation modeling (SEM), and ANOVA. Results indicate that satisfaction significantly mediates the relationship between environmental attributes and psychological well-being. Contact with nature, positive social indicators, environmental comfort, safety, and environmental health emerged as the strongest predictors. Multifunctional spaces, river valleys, and parks demonstrated significantly higher well-being outcomes compared with streets and plazas. Socioeconomic status moderated several environmental effects. These findings provide typologically sensitive evidence to inform the design of psychologically supportive public spaces in rapidly urbanizing cities.
Abstract metadata supplied by the research index; wording belongs to the original source.Structured record
- Source-reported findings
- Results indicate that satisfaction significantly mediates the relationship between environmental attributes and psychological well-being.
- Methods
- regression analysis, structural equation modelling, survey
- Data
- survey data