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A Multidimensional, Neighborhood-Centered Approach to Understanding Low-Income Preschoolers’ School Communities

Wed, April 7, 1:10 to 2:40pm EDT (1:10 to 2:40pm EDT), Virtual

Abstract

For decades, developmental scientists have advanced nuanced theoretical frameworks for understanding how children’s neighborhoods shape their development (Burton & Jarrett, 2000; Leventhal & Brooks-Gunn, 2000). Nevertheless, most empirical studies have focused on differences in child outcomes based on neighborhood demographics, such as socioeconomic status or racial/ethnic composition (Leventhal, Dupere, & Shuey, 2015; Minh et al., 2017). Although this work has raised awareness regarding place-based developmental gaps, it is largely deficit-oriented and fails to reflect the complex milieu of neighborhood processes that theory suggests are jointly relevant for children’s wellbeing. The present study addresses these limitations by (1) using a “neighborhood-centered” approach for grouping preschool communities based on their institutional resources, social and organizational processes, and structural determinants of development, and (2) examining the extent to which attending preschool within these different neighborhood profiles is predictive of children’s development over the course of one school year.

Child-level data for this study were taken from the National Center for Research on Early Childhood Education—Professional Development Study (NCRECE PDS; Pianta & Burchinal, 2007-2011). Language/literacy skills (a composite of the Peabody Picture Vocabulary Test, the Test of Preschool Early Literacy, and the Woodcock Johnson), executive function (the Pencil Tap task), and approaches to learning (the teacher-reported Preschool Learning Behaviors Scale) were assessed in 1,230 low-income, sociodemographically diverse preschool-aged (M age = 4.18 years) children at both the beginning and the end of the preschool year. Addresses of the 192 participating preschools across 9 U.S. cities were geocoded and linked with census tract-level data from a variety of administrative sources (e.g., U.S. Census, InfoGroup, Washington Post) on positive resources, greenspace, homicides, residential mobility, income inequality, racial/ethnic segregation, and unaffordability. Google Street View was also used to code indicators of physical order in the block surrounding the school using the internet-based School Neighborhood Assessment Protocol (McCoy et al., 2020).

Results of latent profile analysis (Figure 1) revealed four distinct preschool community profiles: (1) average (58% of schools); (2) high resources, order, & income equality (18%); (3) high disorder & unaffordability (14%); and (4) high homicide, mobility, & segregation (11%). Results of multi-level models with children nested in school neighborhoods (Figure 2) showed particularly positive gains in all three child outcomes within Profile 3, and as well as gains in language/literacy and approaches to learning in Profile 2. Despite exposure to high levels of disadvantage, children in Profile 4 did not appear to show differences in developmental gains relative to those in the average profile (Profile 1).

These results suggest that low-income children’s school neighborhoods are characterized by unique combinations of institutional resources, social and organizational processes, and structural determinants, and that these various combinations predict development during the formative preschool years in nuanced ways. These findings push back against the largely monolithic, demographically-oriented conceptualizations of neighborhoods that have dominated the developmental literature. Implications for the use of novel administrative data sources and neighborhood-centered methods will be discussed, as will future directions for place-based intervention.

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