Developing a GIS-Based Online Survey Instrument to Elicit Perceived Neighborhood Geographies to Address the Uncertain Geographic Context Problem. Issue 3 (3rd July 2018)

• Record Type: Journal Article
• Authors: Shmool, Jessie L. C.; Johnson, Isaac L.; Dodson, Zan M.; Keene, Robert; Gradeck, Robert; Beach, Scott R.; Clougherty, Jane E.
• Is Part Of: Professional geographer. Volume 70:Issue 3(2018)
• Page Start: 423
• Page End: 433
• Publication Date: 2018-07-03
• Subjects: geographic information systems (GIS) -- mixed methods -- neighborhood scale -- uncertain geographic context problem (UGCoP); 地理信息系统 (GIS) -- 混合方法 -- 邻里尺度 -- 不确定地理脉络问题 (UGCoP)。; sistema de información geográfica (SIG) -- métodos mixtos -- escala vecinal -- problema del contexto geográfico incierto (UGCoP); Geography -- Periodicals; 910
• DOI: 10.1080/00330124.2017.1416299
• Languages: English
• ISSNs: 0033-0124

Abstract

Abstract : Although neighborhood factors have been consistently associated with health, technological difficulties in eliciting self-defined neighborhoods from large cohorts have compromised the interpretability of this research. Here, we offer a mixed-methods approach to elicit and validate self-defined neighborhoods. Participants used a customized Google.Maps interface to "draw" their neighborhood and answered questions about perceived map accuracy, neighborhood definition, and neighborhood activities. We compared geographic concordance of drawn and narrative neighborhood definitions, quantified differential accuracy by demographic characteristics, and examined factors influencing neighborhood definitions. We found similar geographic concordance between narrative and mapped boundaries in two cities, with no differences by neighborhood size. Self-reported neighborhoods had greater concordance with larger administrative areas (e.g., police precincts) than for smaller units (e.g., census tracts). To delineate their neighborhood boundaries, participants reported using administrative definitions, walking distance, their familiarity with people and structures, where they spend time, and physical landmarks. In New York City, participants also reported considering sociodemographic characteristics and transportation. Our method demonstrates the feasibility of collecting perceived (egocentric) neighborhoods through online mapping surveys, adaptable to many study settings.