Environment and Social Psychology

Data Science-Driven Mechanisms of Green Environments and Public Health: Modeling and Validation from a Social Psychology Perspective

Shengjie Yang

Wenzhou-Kean University, College of Business & Public Management, Zhejiang, 325060, China

Xu Lyu

Wenzhou-Kean University, College of Business & Public Management, Zhejiang, 325060, China，lvx@kean.edu

DOI: https://doi.org/10.59429/esp.v10i11.4209

Keywords: Data science; stress reduction; urbanization; public health; and mental health

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Abstract

Increased rate of urbanization has increased the importance of the green environment as a population health determinant. Even though the existing literature acknowledges such benefits as the decrease in mortality rates and improved mental well-being, the mechanisms of their mediation are poorly comprehended. This research combines the concept of social psychology and the data science modelling to examine how the access, quality and use of green-space affect the perceived health benefits and quality of life. A stratified survey (N 100) was conducted through stratified sampling to ensure demographic representativeness. The internal consistency of the constructs of the accessibility, environmental perceptions, psychological outcomes, and demographic variables were tested, and the Cronbach alpha value was above 0.80. Regression methods that were used included multiple regression, mediation analysis, and structural equation modeling (SEM). The results indicated that access and quality as independent variables were found to be weak predictors; the utilization frequency and perceived air quality as dependent variables were found to have a modest but statistically significant influence. The mediation analysis and SEM supported the stress alleviation and mood uplifting as the most significant mediating variables between the green-space exposure and the health outcomes (CFI equals 0.95, RMSEA equals 0.045). Majority of the explained variance was attributed to psychological restoration which is beyond just being proximate together. The research highlights the necessity of the need that urban planning must focus on design strategies that enhance social interaction and help in recovering the stress. Some of the weaknesses include the small sample size and limited generalizability, hence the recommendation of the inclusion of large, longitudinal datasets in future research.

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