| Speech disorders of unknown origin are highly prevalent and addressing them clinically requires substantial resources, yet consensus regarding disorder subtypes has been elusive. Several divergent views describe subtypes based on different speech related aspects, for example error types and motor vs. linguistic processing. In order to provide accurate diagnoses and effective therapy for children with primary speech disorders, it is imperative to understand the heterogeneity within this population and any associated features, whether speech-related or otherwise, of potential disorder subtypes. Towards the goal of a data-based classification system, a self-classifying model using unlabeled, multivariate data would be instrumental. This dissertation focuses on the question how primary speech disorders can be classified in a clinically and statistically valid way.; Twelve children with primary speech disorders and 12 age- and gender-matched controls, age 4;7 to 6;6 (years;months), participated in a wide array of tasks including articulation and phonology testing, language testing, nonword imitation tasks, and timed hand tasks. Twelve variables were derived from these tasks, including standardized speech and language test scores, and perceptual and acoustic measures of temporal accuracy. Statistical analyses focused on the interaction between the variables and on multivariate clustering of participants into groups with similar profiles.; Results indicated that the performance scores in all tested areas were highly correlated. Clustering procedures, using hierarchical agglomerative and k-means algorithms, generated three distinct clusters. One cluster was characterized by low articulation and phonological skill scores but average to above-average scores in all language and most timing accuracy measures. A second cluster consisted of participants with low articulation and phonology scores but average language scores and intermediate timing accuracy scores. A third cluster was characterized by overall low scores, where expressive language scores showed clinical deficits and timing accuracy scores were extremely low. Results from a verification task, not part of the clustering input variables, showed that movement speed was associated with overall performance. An ancillary finding was that undetermined handedness was associated with the construct of childhood apraxia of speech. Together, these findings are consistent with a broad neurophysiologic locus of impairment in severe speech disorders and raise new question regarding treatment approaches. |
