Leveraging Telehealth to Assess Autism Likelihood in the First Year of Life

• In Event: Using computer technology to expand detection and intervention for children with developmental disorders

Abstract

Background: Maximizing the benefits of early intervention for supporting the development of individuals on the autism spectrum (ASD) requires widespread and efficacious early screening and identification practices. Despite decades of effort to identify infants with behavioral markers of ASD, there remain significant gaps throughout the identification-to-services pipeline. This is in part due to variable and protracted onset, with some infants’ behavioral markers emerging between 6 and 12 months, and others not meeting criteria for a diagnosis until 36 months or later (Ozonoff et al., 2010, 2015; Zwaigenbaum et al., 2015). Parent concerns as early as 6 months have been associated with subsequent ASD diagnoses (Sacrey et al., 2016, 2015). However, families with early concerns typically face long waitlists and often must travel long distances to centers with appropriate expertise. We have previously published initial feasibility for our novel telehealth-based behavioral assessment designed to fill this gap, the Telehealth Evaluation of Development for Infants (TEDI; Talbott et al., 2019). Here, we expand these findings in a larger group of infants to ask whether infants with significant early ASD symptoms can be identified via a telehealth evaluation.

Methods: Infants aged 6-12 months whose parents had concerns about social communication development or ASD were recruited nationally across two cohorts. Infants were assessed using the TEDI protocol, wherein parents are coached through a series of semi-structured interactions via synchronous telehealth. Examiner-coded measures included the Autism Observation Scale for Infants (AOSI; Bryson et al., 2008) and examiners’ clinical best estimate of ASD risk. Coders naïve to parent concerns scored the Early Communication Index (ECI; Greenwood et al., 2010). Parents completed Ages and Stages Questionnaires (3rd Edition and Social-Emotional 2nd Edition), and satisfaction questionnaires.

Results: 25 infants (ncohort 1 = 11; ncohort 2 = 14) enrolled and were evaluated (Mean age = 9.68 months, SD=2.32). The majority of infants’ scores fell into the “Refer for Assessment” range on at least one domain of the ASQ-3 (18 infants, 72% of the sample) and the ASQ-SE2 (14/15 infants, 93%). AOSI Total Scores were elevated (M = 13.52, SD = 6.30) compared to the suggested cut-off score of 7. A one-sample Wilcoxon signed rank test comparing mean AOSI Total Score to the cut-off indicates observed scores were significantly higher (Z = 304 p <.001). Overall CBE ratings indicated "high likelihood for ASD" 20/25 infants. A one-sample Wilcoxon signed rank test comparing Mean Parent Overall Satisfaction Ratings to a neutral rating indicates significant parent satisfaction with the TEDI (Cohort 1: Z = 66, p = .003; Cohort 2: Z = 105, p = .001).

Discussion: These findings support the feasibility of conducting an informative developmental assessment via telehealth to detect infants with significant ASD markers in the first year of life. Recruitment and behavioral coding of ASD diagnostically-relevant behaviors (e.g. gestures, play, joint attention) is ongoing, and infants will be followed prospectively until toddlerhood to determine diagnostic and developmental outcomes. Further demonstration of the validity and clinical utility of this telehealth tool has the potential to increase services for many underserved infants and their families.

Authors

• Meagan Talbott, University of California - Davis
  Presenting Author

• Sarah Dufek, University of California, Davis
  Non-Presenting Author

• Gregory Young, University of California, Davis
  Non-Presenting Author

• Sally J Rogers, UCDavis
  Non-Presenting Author