Using Google Streetview to Measure Neighborhood Characteristics

描述(由申请人提供)：社区的种族、民族和经济特征长期以来一直被社会学家视为社会经济成就和社会结果(最显著的是犯罪和犯罪)的决定因素。最近，随着越来越多的证据表明，不良的健康结果往往在空间上聚集，人们的兴趣转向了社区环境在塑造健康和健康差距方面的作用。虽然社区的社会属性，如社会凝聚力、集体效能和人口构成，可以使用调查问题或现有的人口普查来衡量，但衡量社区的物理方面，包括身体紊乱和建成环境，通常需要某种形式的系统实地观察。向社区派遣现场观察员的高昂成本和后勤限制极大地限制了在健康分析中纳入社区身体特征的衡量标准，大多数此类研究侧重于单个城市，而且往往是城市中选定的社区。这项拟议的研究将评估使用新技术的可行性、可靠性和有效性，这些新技术可以通过谷歌在线免费获得，以现场研究费用的一小部分来测量社区的身体紊乱和建筑环境。具体地说，我们将制定使用谷歌地球和谷歌街景来衡量社区身体紊乱和建筑环境的程序，并评估这些程序的有效性、可靠性、成本效益和心理测量学特性。此外，我们将评估谷歌街景和地球框架内其他社区空间尺度和块人脸采样策略的效率。我们建议开发的方法有可能改变收集邻里数据的方式，允许以非常低的成本将背景数据与地方和国家研究联系起来，并为研究背景对健康和福祉的影响创造无与伦比的公共资源。它将对大样本、多地点的研究特别有用，例如新的国家儿童研究。 与公共健康相关：拟议的研究将评估使用新技术的可行性、可靠性和有效性，新技术可通过谷歌在线免费获得，以现场研究费用的一小部分来测量社区的身体紊乱和建筑环境。我们建议开发的方法有可能改变收集邻里数据的方式，允许以非常低的成本将背景数据与地方和国家研究联系起来，并为研究背景对健康和福祉的影响创造无与伦比的公共资源。

DESCRIPTION (provided by applicant): Racial, ethnic, and economic characteristics of neighborhoods have long been viewed by sociologists as determinants of socioeconomic attainment and social outcomes (most notably, crime and delinquency). More recently, interest has shifted to the role of neighborhood environments in shaping health and health disparities, following mounting evidence that poor health outcomes tend to cluster spatially. While social attributes of neighborhoods, such as social cohesion, collective efficacy, and demographic composition, can be measured using survey questions or existing censuses, measuring physical aspects of neighborhoods, including physical disorder and the built environment, usually require some form of systematic field observation. The high costs and logistical constraints of sending field observers to neighborhoods have greatly limited the inclusion of measures of neighborhood physical characteristics in analyses of health, with most such studies focusing on single cities and often on selected neighborhoods within cities. The proposed research will assess the feasibility, reliability, and validity of using new technology, freely available online via Google, to measure neighborhood physical disorder and built environment at a fraction of the cost of field studies. Specifically, we will develop procedures for using Google Earth and Google Street View to measure neighborhood physical disorder and the built environment, and evaluate the validity, reliability, cost- effectiveness, and psychometric properties of these procedures. Furthermore, we will assess the efficiency of alternative neighborhood spatial scales and block face sampling strategies within the Google Street View and Earth frameworks. The methodology we propose to develop has the potential to transform the way neighborhood data are collected, allowing the linkage of contextual data to local and national studies very inexpensively and creating unparalleled public resources for studying contextual influences on health and well-being. It will be particularly useful for large-sample, multi-site studies such as the new National Children's Study. PUBLIC HEALTH RELEVANCE: The proposed research will assess the feasibility, reliability, and validity of using new technology, freely available online via Google, to measure neighborhood physical disorder and built environment at a fraction of the cost of field studies. The methodology we propose to develop has the potential to transform the way neighborhood data are collected, allowing the linkage of contextual data to local and national studies very inexpensively and creating unparalleled public resources for studying contextual influences on health and well- being.