Authors: van der Merwe A
Title: A speech motor learning approach to treating apraxia of speech: Rationale and effects of intervention with an adult with acquired apraxia of speech
Source: Aphasiology 2011 25(10): 1174-1206
Year: 2011
Research Design: Single Case Design

Background: In this paper the rationale for a treatment of apraxia of speech, the speech motor learning (SML) approach, is described and the effects of its application explored. The SML approach endeavours to address the underlying inability to plan and program the production of different speech motor targets (SMTs) in changing phonetic contexts and in utterances exceeding a single word/nonword in length. Aims: The aims of the study were to determine (1) if treatment effects generalised to untreated nonwords and untreated real words with trained vowels and consonants, (2) if a learning effect was maintained, (3) if the treatment task hierarchy of the SML approach could be confirmed, and (4) if the number of speech errors judged perceptually declined across the treatment period on treated and untreated stages. Methods & Procedures: A multiple baseline single-participant design across behaviours and contexts was used to assess the effects of treatment with a speaker with chronic pure AOS. The first six stages of an eleven-stage treatment hierarchy were consecutively treated. The last five remained untreated. Outcomes & Results: During treatment, production of untrained nonwords and words containing trained and untrained SMTs improved. For three treated stages the improvement was greater during the treatment phase than during baseline, for words, nonwords, or both. Stage 4 vowels only improved once treatment commenced. Untreated consonant clusters of Stage 10 improved negligibly. Improvement was maintained 2 years post-treatment. The number of speech errors decreased across the treatment period. Conclusions: Preliminary evidence is provided supporting a general improvement in speech motor planning and programming ability for this participant. The relative value of components of the SML approach needs to be verified in future.

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