Examining Clinics for Children with Autism: The Autism Translating To Treatment Study

Abstract

Objectives:

Certain clinical providers specialize in providing complementary and integrative medicine (CIM) therapies for children with autism spectrum disorder (ASD). Because many of these providers and their patients/families have reported substantial improvement, the authors developed an online platform to carefully examine these clinical practices. The initial goal was to examine the feasibility of prospective data collection in this setting. The larger goals were to characterize the tests and treatments used in these clinics; examine associations between specific treatments, biomarkers, and improved outcomes; and identify promising treatments for future study.

Design:

Prospective cohort study.

Setting:

Four CIM clinics specializing in treating children with ASD.

Patients:

Children with ASD age 2–8 years.

Interventions:

The study protocol provided no interventions, but all interventions provided by the CIM clinical providers were recorded.

Outcome measures:

Aberrant Behavior Checklist (ABC); Social Responsiveness Scale (SRS); and instruments that assessed sensory sensitivity, language, gastrointestinal (GI) symptoms, pediatric quality of life, and caregiver strain.

Results:

Fourteen children were enrolled (mean age, 4.4 years). Over 3 months, the total behavior score (ABC) decreased (improved) from 110.8 to 103.8 (change, −7.0; 95% confidence interval [CI], −27.9 to 13.9), and the total social responsiveness score (SRS) decreased (improved) from 133.8 to 127.2 (change, −6.6; 95% CI, −30.5 to 17.3), but these changes were not statistically significant. Similarly, caregiver strain and pediatric quality of life decreased (improved) but by a nonsignificant amount. More severe GI symptoms and more severe ASD symptoms were associated with lower quality of life (p < 0.001).

Conclusions:

Barriers to successful data collection were identified. Despite these challenges, this study could confirm interesting associations between data elements, highlighting the future value of similar systems for improving evidence-based care in this population.