Development and deployment of the Computer Assisted Neighborhood Visual Assessment System (CANVAS) to measure health-related neighborhood conditions

Abstract

Public health research has shown that neighborhood conditions are associated with health behaviors and outcomes. Systematic neighborhood audits have helped researchers measure neighborhood conditions that they deem theoretically relevant but not available in existing administrative data. Systematic audits, however, are expensive to conduct and rarely comparable across geographic regions. We describe the development of an online application, the Computer Assisted Neighborhood Visual Assessment System (CANVAS), that uses Google Street View to conduct virtual audits of neighborhood environments. We use this system to assess the inter-rater reliability of 187 items related to walkability and physical disorder on a national sample of 150 street segments in the United States. We find that many items are reliably measured across auditors using CANVAS and that agreement between auditors appears to be uncorrelated with neighborhood demographic characteristics. Based on our results we conclude that Google Street View and CANVAS offer opportunities to develop greater comparability across neighborhood audit studies.

Keywords: Disorder; Google Street View; Neighborhood audit; Systematic social observation; Walkability.

Figure 1

Inter-rater reliability of items by category, kappas for categorical items plotted as circles and intraclass correlation coefficients for continuous items plotted as triangles

Figure 2

Kappa values of items measuring inter-rater reliability in the metropolitan sample compared to the central city sample. The dashed line indicates no difference between metropolitan and central-city values of IRR.