Year of Award
Master of Science (MS)
College of Education & Allied Health
Communication Disorders and Deaf Education
numbers, lexical, linguistic, deficit, syntactic, dyscalculia
Background: Numerical skills such as counting, transcoding (the process of converting a number from the digital form to alphanumeric form, or vice versa), reading numerals aloud or writing them to dictation are hypothesized to rely heavily on language skills (Delazer & Bartha, 2001). As such, it is frequently observed that people with aphasia (PWA) present with deficits in numerical skills. Unfortunately, research on numerical skills in aphasia is limited and there is a lack of attention towards the clinical assessment and rehabilitation of these skills post-stroke (Delazer & Bartha. 2001). Previous single case and group studies present more questions than answers for professionals. Unfortunately, the absence of research and appointed professionals to evaluate and rehabilitate these skills leads to difficulty in completion of activities of daily living for the aphasic population. The primary aim of the study is to identify error rates based on transcoding task (alphanumeric ->digit or digits alphanumeric) or response type (written/oral) in PWA. The researcher hypothesized that there would be a statistically significant difference in error rates based on transcoding task and response type. The secondary aim was to determine the effect of Aphasia subtype, classified as Fluent and Non-fluent. on error rates based on transcoding task or response type. It was hypothesized that aphasia subtype would have an effect on error rates based on transcoding task and response type. Furthermore, descriptive data consisting of frequency of each error type was analyzed for each aphasia subtype. It was hypothesized that participants with fluent aphasia would demonstrate lexical/sematic errors whereas participants with non-fluent aphasia would demonstrate syntax errors. PWA (ages 31- 82, M= 59.1) were classified by aphasia subtype, either fluent or non-fluent, to dissociate error patterns associated with linguistic characteristics of each subtype. Participants were presented with number stimuli and were instructed to transcode the numerical values in digital code or alphanumeric code. Responses were provided in written form and verbal form. Errors were classified as semantic, syntactic, unit or mixed. Results: There was no statistically significant difference in error rates among transcoding task or error type. However, there is an effect of aphasia subtype on error rates per transcoding task. A statistically significant difference among digital transcoding exists among people with Non-Fluent aphasia (M=14.71) and people with Fluent aphasia (M=62.67). Additionally, an effect of aphasia subtype exists among response type. A statistically significant difference was found among error rates for people with NonFluent (M=29.52) and Fluent aphasia (M=70) when responses were provided verbally. Descriptive data suggested a high frequency of unit errors in both people with fluent and nonfluent aphasia. Conclusions: Findings indicate that while neither presentation style nor response type are advantageous for increasing accuracy of transcoding, the high degree of unit errors emphasizes the importance of teaching rules of number concatenation, specifically use of unit words, to improve transcoding skills.
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Atwater, Aubrey, "Aphasia and Transcoding: When 145 is Said, "154"" (2018). All Theses, Dissertations, and Capstone Projects. 113.
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