Keywords
nature-relatedness
NDVI
urban greenness
well-being
How to Cite
Abstract
Green social prescriptions (GSPs) are interventions designed to combat sedentary behavior and preventable diseases by leveraging the benefits of nature-based physical activity. As these programs are still evolving, there is limited data regarding the likelihood of participation from an international perspective. This study examined factors influencing participation likelihood in GSPs across various geographic contexts, levels of greenness, nature-relatedness, well-being, and socio-demographic variables.
We conducted an online, cross-sectional survey with 2,467 participants from Australia, India, Singapore, the United Kingdom, and the United States in September 2022. Participants reported their likelihood of participating in GSPs with four distinct outcomes, and we calculated an aggregate participation likelihood score. We used linear regression models to analyze associations between variables and participation likelihood, including models stratified by gender and country.
Results showed that nature-relatedness was the strongest predictor of participation likelihood. Positive associations were found with educational attainment, financial comfort, and time spent in greenspace, while male gender and better well-being were linked to lower participation likelihood. An interaction between urban setting and greenness indicated that individuals in greener urban areas, particularly males, were less likely to feel the need for GSPs.
These findings highlight the importance of considering nature-relatedness in GSPs and suggest that targeted interventions may be useful for individuals with lower connections to nature. Further research should explore cultural differences and the impact of health status on GSP participation. Understanding these factors can inform more equitable and effective GSP implementation, addressing health disparities and reaching diverse populations.
References
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Copyright (c) 2024 Nicole Odell, J. Aaron Hipp, Katarzyna Olcoń, Deepti Adlakha, Michelle Kondo, Thomas Astell-Burt, Xiaoqi Feng