Abstract: Data-Driven Outreach to Opportunity Youth: Understanding and Addressing Youth Disconnection Via Population Data and GIS Technology (Society for Social Work and Research 24th Annual Conference - Reducing Racial and Economic Inequality)

287P Data-Driven Outreach to Opportunity Youth: Understanding and Addressing Youth Disconnection Via Population Data and GIS Technology

Friday, January 17, 2020
Marquis BR Salon 6 (ML 2) (Marriott Marquis Washington DC)
* noted as presenting author
Kristin Ferguson, PhD, Associate Professor, Arizona State University, Phoenix, AZ
Elizabeth Hatch Mody, MSW, MPA, Research Specialist, Arizona State University, Phoenix, AZ
Chuyuan Wang, PhD, Postdoctoral Research Associate, Arizona State University, Phoenix, AZ
Dan Hunting, MA, Senior Policy Analyst, Arizona State University, Phoenix, AZ
Background and Purpose:

Opportunity youth (i.e., youth ages 16-24 who are neither working nor in school) are a population that is difficult to engage in services. Population-level data and Geographic Information Systems (GIS) play a critical role in helping community practitioners understand where target populations reside and which characteristics are most salient to their service needs. Despite the benefits of using geospatial data and GIS to guide decision-making, these tools remain uncommon in social work compared to other disciplines. This case study answered three research questions: 1) How many opportunity youth live in the Greater Phoenix Metro Area and what are their demographic characteristics? 2) Where in the Greater Phoenix Metro Area do opportunity youth live and what are the hot spots? and 3) How can population-level data and GIS technology be used to engage opportunity youth and the social service organizations working with them?


We used the 2017 American Community Survey (ACS) Public Use Microdata Samples (PUMS) data (1-year estimates) for the State of Arizona that were obtained from the U.S. Census Bureau. We first identified OY records in each Public Use Microdata Areas (PUMAs) region using the ACS variables of age, school enrollment, and employment status recode. We then used the variable person’s weight to produce OY population estimates by calculating the sum of all the person weights of OY records within each PUMAs region. We calculated population density using OY population divided by the area of a PUMAs region, which has a unit of population per square mile. ESRI ArcGIS software was used to produce choropleth maps that display OY population density. Finally, we performed a hot-spot analysis using Getis-Ord General G for OY population density to identify statistically significant spatial clusters of high values (hot spots).


Analyses indicate there are 75,200 OY in the Greater Phoenix Metro Area, of whom 34% have limited English proficiency, 30% have a disability, and 29% live at or below 130% of the Federal Poverty Level. Hot-spot analysis identified three statistically significant regions as hot spots: Maryvale East (296.4 OY per mi2), Maryvale West (219.0 OY per mi2), and Phoenix Uptown (157.8 OY per mi2). Community partner organizations of the Opportunities for Youth (OFY) Coalition use these findings to guide outreach of both OY and youth-serving organizations, to better understand the spatial dependency of the distribution of OY density, and to examine the socio-demographic and economic factors that are associated with these hot-spot regions.

Conclusions and Implications:

Population-level data and digital mapping techniques have enhanced the OFY Coalition’s understanding of where OY live, what salient sociodemographic characteristics could be barriers to –or facilitators of—service use, and how to better reach OY through culturally informed outreach strategies. This data-driven approach also has experienced challenges, such as competing data sources, underinvestment in low population density areas, and lack of trained community practitioners needed to sustain this approach. The authors propose strategies for training community practitioners to replicate this data-driven approach in other geographic areas and with other hard-to-reach populations.