TY - JOUR PY - 2019// TI - Development and validation of a Google Street View pedestrian safety audit tool JO - Epidemiology A1 - Mooney, Stephen J. A1 - Wheeler-Martin, Katherine A1 - Fiedler, Laura M. A1 - LaBelle, Celine M. A1 - Lampe, Taylor A1 - Ratanatharathorn, Andrew A1 - Shah, Nimit N. A1 - Rundle, Andrew G. A1 - Dimaggio, Charles J. SP - ePub EP - ePub VL - ePub IS - ePub N2 - BACKGROUND: Assessing aspects of intersections that may affect the risk of pedestrian injury is critical to developing child pedestrian injury prevention strategies, but visiting intersections to inspect them is costly and time-consuming. Several research teams have validated the use of Google Street View to conduct virtual neighborhood audits that remove the need for field teams to conduct in-person audits.

METHODS: We developed a 38-item virtual audit instrument to assess intersections for pedestrian injury risk and tested it on intersections within 700 meters of 26 schools in New York City using the Computer Assisted Neighborhood Visual Assessment System (CANVAS) with Google Street View imagery.

RESULTS: Six trained auditors tested this instrument for inter-rater reliability on 111 randomly selected intersections and for test-retest reliability on 264 other intersections. Inter-rater kappa scores ranged from -0.01 to 0.92, with nearly half falling above 0.41, the conventional threshold for moderate agreement. Test-retest kappa scores were slightly higher than but highly correlated with inter-rater scores (Spearman rho=0.83). Items that were highly reliable included presence of a pedestrian signal (K=0.92), presence of an overhead structure such as an elevated train or a highway (K=0.81), and intersection complexity (K=0.76).

CONCLUSIONS: Built environment features of intersections relevant to pedestrian safety can be reliably measured using a virtual audit protocol implemented via CANVAS and Google Street View.

Language: en

LA - en SN - 1044-3983 UR - http://dx.doi.org/10.1097/EDE.0000000000001124 ID - ref1 ER -