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步行行为的多层次建模:理解人与地点及时间相互作用方面的进展

Multilevel modeling of walking behavior: advances in understanding the interactions of people, place, and time.

作者信息

King Abby C, Satariano William A, Marti Jed, Zhu Weimo

机构信息

Department of Health Research and Policy and Stanford Prevention Research Center, Department of Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA.

出版信息

Med Sci Sports Exerc. 2008 Jul;40(7 Suppl):S584-93. doi: 10.1249/MSS.0b013e31817c66b7.

Abstract

It has become increasingly clear that the influences on walking as well as other forms of regular physical activity are complex and require an increased understanding of factors across multiple levels of influence. Ecological frameworks have provided the field with a heuristic means of capturing potential impacts on behavior across diverse domains, including personal, behavioral, social or cultural, and environmental. We discuss advances in both understanding and applying this framework through the inclusion of previously ignored dimensions of impact (e.g., time), the application of state-of-the-art statistical methods for understanding interactions among multiple domains (e.g., signal detection), and the development of computer technologies (e.g., agent-based modeling) aimed at simulating the complex relationships between multiple levels of impact and walking behavior. We conclude with suggestions for future research in this emerging field.

摘要

越来越明显的是,对步行以及其他形式的常规体育活动的影响是复杂的,需要对多个影响层面的因素有更深入的理解。生态框架为该领域提供了一种启发式方法,用于捕捉在包括个人、行为、社会或文化以及环境等不同领域对行为的潜在影响。我们讨论了在理解和应用这一框架方面取得的进展,包括纳入先前被忽视的影响维度(如时间)、应用最先进的统计方法来理解多个领域之间的相互作用(如信号检测),以及开发旨在模拟多个影响层面与步行行为之间复杂关系的计算机技术(如基于智能体的建模)。我们最后对这一新兴领域的未来研究提出了建议。

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