# Unpacking treatment mechanisms: Combining evidence from three early intervention models for Autism Spectrum Disorder (ASD)

> **NIH NIH R01** · WEILL MEDICAL COLL OF CORNELL UNIV · 2020 · $410,095

## Abstract

Abstract
“Unpacking Treatment Mechanisms: Combining Evidence from Three Early Intervention Models for ASD”
 Though randomized control trials (RCTs) of early intervention for children with autism spectrum disorders
(ASD) have shown evidence for the effectives of various treatment models, we know little about the
mechanisms of treatment. Specifically, many early intervention models include parent coaching as a core
strategy to increase the use of effective interactive strategies in parents to promote social communication in
children. However, our knowledge about links between changes in parents' behaviors and changes in
children's behaviors are still very limited. Therefore, the primary aim of this project is to combine evidence for
treatment effects of early intervention and mediation of changes in parent behaviors on changes in child
behaviors across the three RCTs of Early Start Denver Model (ESDM), Early Social Intervention (ESI), and
Joint Attention Symbolic Play Engagement and Regulation (JASPER) treatment using innovative statistical
techniques. The behaviors of the children and parents over the course of treatment will be measured based on
approximately 1200 parent-child interaction videos that are already available over the course of three RCTs.
Core ASD symptoms in children will be rated blindly using a newly validated treatment outcome measure, the
Brief Observation of Social Communication Change (BOSCC), and parents' use of interactive strategies will be
coded using a newly developed coding system of parent strategy use. Leveraging the recent advancement of
the Behavioral Signal Processing (BSP) approach, we will also implement novel, objective automated acoustic
measures to rate changes in children's and parents' behaviors in response to treatment. Combining data from
the three RCTs will result in a sample size of 286 toddlers and young preschoolers from 1 to 4 years of age
followed over the course of the three RCTs. The large sample size will increase the power of statistical tests to
examine the moderators of treatment and mediation effects. Analyses of the combined data from 3 different
studies and 5 different sites will enhance the generalizability of the inferences that can be drawn from our
findings. Through this study, we hope to provide insight regarding for whom, how, and why early interventions
can change behaviors and trajectories in autism. Findings will inform future development and dissemination of
cost-effective early treatment models as well as service and policy level decision making to make the best use
of resources for young children with ASD and their families.

## Key facts

- **NIH application ID:** 9827580
- **Project number:** 5R01MH114925-03
- **Recipient organization:** WEILL MEDICAL COLL OF CORNELL UNIV
- **Principal Investigator:** So Hyun Kim
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $410,095
- **Award type:** 5
- **Project period:** 2017-12-04 → 2022-11-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9827580

## Citation

> US National Institutes of Health, RePORTER application 9827580, Unpacking treatment mechanisms: Combining evidence from three early intervention models for Autism Spectrum Disorder (ASD) (5R01MH114925-03). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/9827580. Licensed CC0.

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