Evaluating Neighborhood Disorder and Signs of Care Virtual Auditing Techniques: A Comparative Study

Keywords: disorder, signs of care, built environment, Google Street View, neighborhood, urban health
Session Type: Virtual Paper Abstract
Day: Friday
Session Start / End Time: 2/25/2022 02:00 PM (Eastern Time (US & Canada)) - 2/25/2022 03:20 PM (Eastern Time (US & Canada))
Room: Virtual 30

Abstract

Virtual street audits to measure neighborhood conditions such as disorder and signs of care are emerging tools to investigate relationships with health and other outcomes associated with well-being. Specifically, neighborhood disorder is associated with higher crime and poorer mental health, where signs of care are associated with resident perceptions of control and crime prevention. Theoretically, signs of care are considered the inverse of neighborhood disorder. Empirical evidence of this relationship would support the use of both tools to evaluate existing neighborhood conditions. However, these features have not been empirically compared using virtual audit techniques. To fill this need, we compared the virtual audit coding for signs of care (a novel measure) and neighborhood disorder (LAND, a recently validated metric) for 71 lots in Detroit, Michigan. To assess the relationship, we used Pearson's Correlation coefficient to establish correlations between lot-level disorder and signs of care. Understanding the relationship between signs of care and neighborhood disorder highlights ways in which neighborhoods may be altered to improve health.