# Leveraging Telehealth to Identify Infants at Elevated Likelihood for Autism in the First Year of life

> **NIH NIH R01** · UNIVERSITY OF CALIFORNIA AT DAVIS · 2024 · $630,903

## Abstract

Project Summary
Despite many decades of research in early identification of autism, there remain lengthy gaps between parents’
first concerns and formal diagnosis and subsequent access to specialized services. Challenges in reducing this
gap include long waitlists, lack of specialized providers in many communities, and the lack of validated screening
tools for infants under 18 months of age. Due to methodological challenges in recruiting sufficient numbers of
infants with early specific concern for autism in any one geographic area, most studies of early development
have focused on infant siblings of children with autism. Telehealth offers the opportunity to expand the scope of
early identification studies and conduct the crucial foundational work needed to determine the developmental
trajectories and outcomes of infants with early developmental concerns in community settings throughout the
United States. We have previously demonstrated the initial feasibility of this approach in our preliminary work
developing the Telehealth Evaluation of Development for Infants (TEDI; R21 HD100372 and R21 HD 105161, PI
Talbott). Behavioral measures obtained via TEDI are reliable, valid, and highly satisfactory to families.
Importantly, we have also found that the majority of infants in our sample have elevated scores on early
measures of autism traits, developmental challenges in communication, language, and motor skills, and elevated
likelihood of autism relative to general population norms. This preliminary work indicates the need for more
thorough examination of this group of infants. We propose to prospectively follow a group of 100 infants ages 6
– 12 months with early parent concerns. We will evaluate them using the TEDI telehealth protocol at four visits
each 3 months apart. At 36 months, we will conduct an outcome visit via telehealth to generate clinical best
estimate outcomes. The project will address 3 specific aims. In Aim 1, we will determine the proportion and
predictors of autism outcomes. Under Aim 2, we seek to characterize the development of a community-based
sample of infants later diagnosed with autism by examining differences in developmental trajectories between
outcome groups, as well as predictors of developmental outcomes across groups. Finally, in Aim 3, we will
identify best practices for supporting family engagement and satisfaction with telehealth-based assessments,
and the cultural appropriateness of the TEDI for diverse communities, which will directly support the
implementation of telehealth screening and assessment in community settings beyond the COVID-19
pandemic. Successful completion of these aims has the potential to significantly increase families’ access to
specialized evaluations and increase the capacity for early identification of infants in need of services. It will
also lay the groundwork for future efforts to conduct screening and intervention trials and may ultimately help to
increase access to high-quality interve...

## Key facts

- **NIH application ID:** 10907667
- **Project number:** 5R01HD112362-02
- **Recipient organization:** UNIVERSITY OF CALIFORNIA AT DAVIS
- **Principal Investigator:** Meagan Ruth Talbott
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $630,903
- **Award type:** 5
- **Project period:** 2023-08-15 → 2028-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10907667

## Citation

> US National Institutes of Health, RePORTER application 10907667, Leveraging Telehealth to Identify Infants at Elevated Likelihood for Autism in the First Year of life (5R01HD112362-02). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10907667. Licensed CC0.

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