An abbreviated scoring algorithm for the baby and infant screen for children with autism traits

Paige E. Cervantes, Department of Psychology , Louisiana State University , Baton Rouge , LA , USA.
Johnny L. Matson, Department of Psychology , Louisiana State University , Baton Rouge , LA , USA.
W Jason Peters, Department of Psychology , Louisiana State University , Baton Rouge , LA , USA.

Abstract

PURPOSE: Autism spectrum disorder (ASD) screening is recommended for all children aged 18-24 months. However, healthcare providers may be burdened with the responsibility of conducting these screens in addition to necessary services. Therefore, developing a time-efficient screener with sound psychometric properties is essential. METHODS: This study sought to update the abbreviated scoring algorithm of the Baby and Infant Screen for Children with aUtIsm Traits (BISCUIT) and increase its clinical utility. Six thousand and three children with ASD or atypical development enrolled in an early intervention program participated. RESULTS: A 6-item algorithm with a cutoff score of 3 was found to be optimal and yielded a sensitivity of 0.960 and a specificity of 0.864. CONCLUSION: Sensitivity and specificity estimates were similar to that of the complete BISCUIT-Part 1; thus, the 6-item algorithm can reliably differentiate children at-risk for ASD requiring further assessment. The algorithm appears to be a promising tool for early identification.