Delineation of Sensorimotor Subtypes Underlying Residual Speech Errors

Study Summary

Children with speech sound disorder show diminished accuracy and intelligibility in spoken communication and may thus be perceived as less capable or intelligent than peers, with negative consequences for both socioemotional and socioeconomic outcomes. While most speech errors resolve by the late school-age years, between 2-5% of speakers exhibit residual speech errors (RSE) that persist through adolescence or even adulthood, reflecting about 6 million cases in the US. Both affected children/families and speech-language pathologists (SLPs) have highlighted the critical need for research to identify more effective forms of treatment for children with RSE. In a series of single-case experimental studies, research has found that treatment incorporating technologically enhanced sensory feedback (visual-acoustic biofeedback, ultrasound biofeedback) can improve speech in individuals with RSE who have not responded to previous intervention. Further research is needed to understand heterogeneity across individuals in the magnitude of response to biofeedback treatment. The overall objective of this proposal is to conduct clinical research that will guide the evidence-based management of RSE while also providing novel insights into the sensorimotor underpinnings of speech. The central hypothesis is that individual deficit profiles will predict relative response to visual-acoustic vs ultrasound biofeedback. From the larger population of children with RSE evaluated as part of C-RESULTS-RCT (Correcting Residual Errors With Spectral, Ultrasound, Traditional Speech Therapy Randomized Controlled Trial), a subset of 8 children will be selected who show a deficit in one domain (auditory or somatosensory) and intact perception in the other. Single-case methods will be used to test the hypothesis that sensory deficit profiles differentially predict response to visual-acoustic vs ultrasound biofeedback.

Primary Outcome

During treatment, one trial in each block of 10 was flagged for measurement and the first three formants (F1, F2, F3) were extracted from the center of the /r/ interval. The distance between the second and third formants (F3-F2) was converted to z-scores relative to normative data from age-matched children with typical speech (Lee et al., 1999). A z-score of 0 represents the mean F3-F2 distance for typical children; a z-score of 1 indicates one standard deviation of the normative sample above th

Interventions

• BEHAVIORAL Visual-acoustic biofeedback
• BEHAVIORAL Ultrasound biofeedback