Predicting child development and school readiness, at age 5, for Aboriginal and non-Aboriginal children in

Abel Fekadu Dadi1, Vincent He1, Georgina Nutton2

  • 1Menzies School of Health Research, Charles Darwin University, Darwin, Northern Territory, Australia.

Plos One
|December 20, 2023
PubMed

Insights

Predictive models identified factors influencing early child development in Aboriginal and non-Aboriginal children. Early interventions can be better targeted by understanding these complex, stage-specific influences on school readiness.

Area of Science:

  • Child Development
  • Public Health
  • Predictive Modeling

Background:

  • Positive early development is crucial for lifelong health and well-being.
  • Identifying at-risk children enables targeted early interventions.
  • This study aimed to develop a predictive model for early support of vulnerable children.

Purpose of the Study:

  • To develop and validate predictive models for early child development.
  • To identify key factors influencing development in Aboriginal and non-Aboriginal children.
  • To inform early support strategies for vulnerable populations.

Main Methods:

  • Analysis of linked administrative records for 2,380 Northern Territory children.
  • Utilized the Australian Early Development Census (AEDC) data.
  • Employed Partial Least Square Structural Equation Modeling (PLS-SEM) to assess pre-pregnancy, pregnancy, birth, and child-related factors.

Main Results:

  • Separate predictive models were developed for Aboriginal and non-Aboriginal children.
  • For Aboriginal children, socioeconomic status, gestational diabetes, maternal smoking, English as a second language, and preschool attendance were significant predictors.
  • For non-Aboriginal children, maternal age, socioeconomic status, parity, and primary carer's occupation were key predictors.

Conclusions:

  • The developed models offer insights into the interplay of developmental factors.
  • Findings can inform service and policy responses for early intervention programs.
  • Recommendations include strengthening the AEDC measurement to capture all developmental domains equally.
Abstract