Using Google Streetview to Measure Neighborhood Characteristics

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成果（最值得注意的是，犯罪和青少年犯罪）的决定因素。最近，随着越来越多的证据表明健康状况不佳往往在空间上聚集，人们的兴趣已经转移到邻里环境在形成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，集体效能和人口组成，可以使用调查问题或现有的人口普查来测量，但测量社区的物理方面，包括物理障碍和建筑环境，通常需要某种形式的系统性实地观察。派遣现场观察员到社区的高成本和后勤限制极大地限制了在健康分析中纳入社区物理特征的措施，大多数此类研究集中在单个城市，通常集中在城市内的选定社区。拟议的研究将评估使用新技术的可行性，可靠性和有效性，通过谷歌在线免费提供，以测量社区的物理障碍和建筑环境，成本仅为实地研究的一小部分。具体来说，我们将开发使用谷歌地球和谷歌街景来测量邻里身体障碍和建筑环境的程序，并评估这些程序的有效性，可靠性，成本效益和心理测量特性。此外，我们还将评估谷歌街景和地球框架内的替代邻里空间尺度和街区面采样策略的效率。我们建议开发的方法有可能改变邻里数据的收集方式，使上下文数据与地方和国家研究的联系非常便宜，并为研究上下文对健康和福祉的影响创造无与伦比的公共资源。这将是特别有用的大样本，多地点的研究，如新的国家儿童研究。 公共卫生相关性：拟议的研究将评估使用新技术的可行性，可靠性和有效性，通过谷歌在线免费提供，以测量社区的物理障碍和建筑环境，成本仅为实地研究的一小部分。我们提议开发的方法有可能改变邻里数据的收集方式，允许背景数据与地方和国家研究的联系非常便宜，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.