Potential pathways of association from green space to smartphone addiction.

Environmental pollution (Barking, Essex : 1987)(2023)

引用 0|浏览5
暂无评分
摘要
Green space is increasingly known to improve physical and mental health. Based on these benefits, green space might also be expected to help mitigate related harmful behavioral patterns, such as obsessive Internet use and relevant addictions. In response, we conducted a study on smartphone addiction, a new form of Internet addiction. We carried out a cross-sectional investigation in August 2022. We recruited 1011 smartphone users across China in August 2022, measured the Normalized Difference Vegetation Index (NDVI) in their residential neighborhoods (in 1, 2, and 3 km buffers), and captured data on smartphone addiction via the Smartphone Addiction Scale - Short version (SAS-SV). Potential mediators between green space and smartphone addiction, including physical activity, stress, and loneliness, were also reported by participants using the Physical Activity Rating Scale-3 (PRS-3), Depression, Anxiety and Stress Scale-21 (DASS-21), and 8-items UCLA Loneliness Scale (ULS-8). Multiple linear regression was employed to examine the relationships between green space and smartphone addiction. Structural equation modeling was performed to examine the potential pathways between these variables. Unexpectedly, NDVI in 1 km buffers was positively associated with smartphone addiction. By contrast, population density, an indicator of urbanization, was associated with lower levels of smartphone addiction in all NDVI buffer sizes. Meanwhile, we found NDVI was strongly associated with population density as well as other indicators of urbanization. Our findings are unexpected and suggest that greenness may serve as an indicator of urbanization at national levels and that urbanization may buffer against smartphone addiction. During the hot summer, green space and indoor facilities may have competitive land uses, so future research should examine whether this association exists in other seasons and scenarios. We also recommend alternative models to systematically evaluate the effects of different components of residential environments.
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要