We Must Consider Infrastructure when Attempting to Scale up Autism EBIs: A Case Example from Early Intervention

Katherine Pickard1, Sarah R Edmunds2, Quentin Wedderburn2

  • 1Department of Pediatrics, Division of Autism and Related Disabilities, Emory School of Medicine, 1920 Briarcliff Road, Atlanta, GA, 30329, Georgia. katherine.e.pickard@emory.edu.

Insights

Scaling up evidence-based interventions (EBIs) for young autistic children in public Early Intervention systems requires addressing factors like workforce capacity and leadership support. This ensures sustainable public health impact for autism services.

Area of Science:

  • Developmental Psychology
  • Public Health Systems
  • Autism Spectrum Disorder Research

Background:

  • Increasing interest in translating evidence-based interventions (EBIs) for young autistic children within public systems.
  • Public Early Intervention (EI) systems, mandated under Part C of IDEA, serve children birth to three with developmental delays.
  • Current research on training EI providers for autism EBIs is small-scale, lacking focus on system alignment and scalability.

Purpose of the Study:

  • To review factors impacting EBI scale-up across public systems.
  • To extend these factors to the implementation of autism EBIs within public EI systems.
  • To identify implications for autism researchers and EI providers.

Main Methods:

  • Review of factors uniformly impacting EBI scale-up in diverse public systems (citing Fagan, 2019).
  • Framework extension to analyze implementation of autism EBIs in public EI systems.
  • Discussion of specific impacts on scaling autism EBIs for toddlers and young autistic children.

Main Results:

  • Identified key factors for EBI scale-up: developer/funder capacity, public awareness/support, leadership support, community engagement, skilled workforce, and data monitoring.
  • These factors are critical for aligning autism EBIs with EI systems' infrastructure.
  • Challenges exist in scaling training and sustaining public health impact.

Conclusions:

  • Successful scale-up of autism EBIs in EI systems depends on addressing identified systemic factors.
  • A skilled workforce and robust data monitoring are crucial for effective implementation.
  • Further research is needed to optimize autism EBI delivery within public EI systems for young children.

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