Data-Driven Subclassification of Speech Sound Disorders in Preschool Children

Abstract

Purpose The purpose of the study was to determine whether distinct subgroups of preschool children with speech sound disorders (SSD) could be identified using a subgroup discovery algorithm (SUBgroup discovery via Alternate Random Processes, or SUBARP). Of specific interest was finding evidence of a subgroup of SSD exhibiting performance consistent with atypical speech motor control. Method Ninety-seven preschool children with SSD completed speech and nonspeech tasks. Fifty-three kinematic, acoustic, and behavioral measures from these tasks were input to SUBARP. Results Two distinct subgroups were identified from the larger sample. The 1st subgroup (76%; population prevalence estimate = 67.8%–84.8%) did not have characteristics that would suggest atypical speech motor control. The 2nd subgroup (10.3%; population prevalence estimate = 4.3%–16.5%) exhibited significantly higher variability in measures of articulatory kinematics and poor ability to imitate iambic lexical stress, suggesting atypical speech motor control. Both subgroups were consistent with classes of SSD in the Speech Disorders Classification System (SDCS; Shriberg et al., 2010a). Conclusion Characteristics of children in the larger subgroup were consistent with the proportionally large SDCS class termed speech delay; characteristics of children in the smaller subgroup were consistent with the SDCS subtype termed motor speech disorder—not otherwise specified. The authors identified candidate measures to identify children in each of these groups. Supplemental Material https://doi.org/10.23641/asha.6170468