Login / Signup

Direct and indirect pathways linking gentrification to adolescent reading and math achievement via educational aspirations and psychological distress.

Jane LeerRick H HoyleCandice L Odgers
Published in: Developmental psychology (2024)
This study examined how living in a gentrifying neighborhood may impact adolescents' reading and math achievement via educational aspirations and psychological distress and asked whether these pathways differ according to socioeconomic status and race. A framework combining theories of adolescent development and neighborhood effects was empirically tested using a racially diverse sample of adolescents living in urban neighborhoods in North Carolina matched to administrative school records and census data ( N = 1,045, M age = 12, 8% American Indian, 4% Asian, 32% Black, 62% White, 15% multiracial, 16% Latinx, categories not mutually exclusive). At the population level, structural equation models found no relation between the extent of gentrification occurring in youths' neighborhood of residence and reading and math achievement, educational aspirations, or psychological distress. However, moderated mediation models revealed a positive association between gentrification and psychological distress among youth with low (but not high) subjective family economic status, leading to a small negative indirect effect of gentrification on math achievement. The link between gentrification and increased psychological distress was largest among Black youth with low subjective family economic status, who may face both heightened racism and classism-related social stressors as their neighborhood gentrifies. Findings have theoretical and policy implications, as they challenge the assumption that living in proximity to higher income, higher educated peers will benefit youth from disadvantaged neighborhoods. (PsycInfo Database Record (c) 2024 APA, all rights reserved).
Keyphrases
  • physical activity
  • sleep quality
  • mental health
  • young adults
  • working memory
  • healthcare
  • public health
  • depressive symptoms
  • emergency department
  • electronic health record
  • social support
  • machine learning
  • tertiary care