Development of a critical item algorithm for the Baby and Infant Screen for Children with aUtIsm Traits

Autism is defined by impairments in socialization, communication, with the presence of stereotyped behavior. It is also associated with various medical conditions, intellectual disability, comorbid psychopathology, and problem behavior. This is a concerning finding in that there may be a true increase in the disorder's prevalence and that it is associated with poor long-term outcomes. Fortunately, effective treatments exist that can alter the course of the disorder if administered early in a child's life. A method to facilitate early intervention is through the early screening of autism with instruments such as the Baby and Infant Screen for Children with aUtIsm Traits (BISCUIT). The primary purpose of the current investigation was to further develop the utility of the BISCUIT by creating an abbreviated scoring algorithm. Participants included 2168 children ages 17–37 with an autism spectrum disorder or atypical development enrolled in an early intervention program. Discriminant function analysis (DFA) and receiver operating characteristic (ROC) analysis were conducted resulting in a 5 item scoring algorithm with comparable diagnostic accuracy to the existing scoring procedure. Implications for these data and directions for further research are discussed.

► Early diagnosis of autism spectrum disorders is a major priority in developmental disabilities.
► The BISCUIT is the most psychometrically sound measures for diagnosing autism spectrum disorders in 17–36 month old children.
► The current study describes a 5 item algorithm from the BISCUIT that is similar to results from the 62 item full scale BISCUIT.