Journal of Cognition (Jul 2024)

Risk and Protective Factors for Executive Function in Vulnerable South African Preschool-Age Children

  • Caylee J. Cook,
  • Steven J. Howard,
  • Hleliwe Makaula,
  • Rebecca Merkley,
  • Mbulelo Mshudulu,
  • Nosibusiso Tshetu,
  • Gaia Scerif,
  • Catherine E. Draper

DOI
https://doi.org/10.5334/joc.377
Journal volume & issue
Vol. 7, no. 1
pp. 58 – 58

Abstract

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Executive function (EF) theory and research continues to under-represent the contexts in which the majority of the world’s children reside, despite their potential to support, refute, or refine our current understandings. The current study sought to contribute to our understanding of EF in low-income settings in South Africa by investigating longitudinal associations of context-specific risk and protective factors for EF development in three- to five-year-old children who had limited access to ECCE services before the age of five. Child-caregiver dyads (N = 171) participated in two rounds of data collection (approximately seven months apart) during which child EF was assessed using the Early Years Toolbox; context-specific risk and protective factors were assessed through a caregiver questionnaire. Hierarchical linear regressions revealed that after controlling for age, attending ECCE services at time 2 (β = 0.30, p < 0.001), and diversity of caregivers at time 1 (β = 0.14, p = 0.041) were the only factors positively associated with EF at time 2. Other factors commonly associated with EF such as caregiver education, and household income were not significant, while resources in the home were significantly associated with EF (β = –0.18, p = 0.007) but in the opposite direction to what was expected. These results add to accumulating evidence that predictors of EF established in Minority World contexts may not be consistent across contexts, emphasising the need to broaden the EF evidence base. For instance, future studies could incorporate qualitative and ethnographic methods to better capture the cultural and contextual nuances relating to EF, to better inform our statistical and theoretical models.

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