Background: Augmented input (AI) refers to any visual or linguistic strategy used by
communication partners to increase the message comprehension of a person with
aphasia. Previous research has focused on the type of AI, such as high versus low
context images and linguistic versus visual supports, that can be used to facilitate
improved auditory and reading comprehension. The results of these studies have been
varied. To date, researchers have not evaluated the frequency of AI required to
improve auditory comprehension of persons with chronic aphasia.
Aims: The purpose of this study was to determine the effect of AI using no context
Picture Communication Symbols™ (PCS) images, presented at a frequency of 70%,
versus no AI on the accuracy of auditory comprehension of narratives for persons with
chronic aphasia.
Methods and procedures: A total of 12 participants with chronic aphasia listened to two
narratives, one in each of the conditions. Auditory comprehension was measured by
assessing participants’ accuracy in responding to 15 multiple choice cloze-type
statements related to the narratives.
Results: Of the 12 participants, 7 participants (58.33%) gave more accurate responses
to comprehension items in the AI condition, 4 participants (33.33%) gave more
accurate responses in the no AI condition and 1 participant scored the same in both
the conditions.
Conclusion: No context Picture Communication Symbols™ (PCS) images used as AI
improved the accuracy of responses to comprehension items based on narratives for
some persons with chronic aphasia. Continued research is necessary in order to
determine what forms and frequency of AI will lead to improved auditory
comprehension for persons with aphasia. / Mini Dissertation (M(AAC))--University of Pretoria, 2017. / National Research Foundation (NRF) / Centre for Augmentative and Alternative Communication (CAAC) / M(AAC) / Unrestricted
| Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:up/oai:repository.up.ac.za:2263/64959 |
| Date | January 2017 |
| Creators | Stockley, Nicola |
| Contributors | Dada, Shakila, nicolastockley1@gmail.com, Wallace, Sarah |
| Publisher | University of Pretoria |
| Source Sets | South African National ETD Portal |
| Language | English |
| Detected Language | English |
| Type | Mini Dissertation |
| Rights | © 2018 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria. |
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