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Updated: Aug 9, 2026

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Systematic Hearing Performance Evaluation Process for Adolescents with Cochlear Implantation at Early Ages
Published on: March 24, 2023
[Model oriented assessment of literacy performance in children with cochlear implants]
A Fiori1, K Reichmuth, P Matulat
1Klinik und Poliklinik für Phoniatrie und Pädaudiologie des Universitätsklinikums Münster. fiori@uni-muenster.de
Laryngo- Rhino- Otologie
|April 6, 2006
Summary
Written language abilities vary significantly in children with cochlear implants (CI). This study highlights the need for individualized assessment of literacy skills in CI recipients to tailor effective remediation strategies.
Area of Science:
- Linguistics
- Audiology
- Developmental Psychology
Background:
- Children with hearing impairments often face literacy challenges compared to their hearing peers.
- Literacy acquisition following cochlear implantation (CI) has been under-researched.
- Neurolinguistic models propose distinct lexical and sublexical strategies for written language processing.
Purpose of the Study:
- To investigate the written language abilities of school-aged children with cochlear implants.
- To determine if CI users establish both lexical and sublexical reading/writing strategies or require individualized approaches.
- To analyze performance using the Salzburger Lese-Rechtschreib-Test.
Main Methods:
- Studied 8 school-aged children with cochlear implants, noting their heterogeneity.
- Assessed written language performance using the Salzburger Lese-Rechtschreib-Test.
- Conducted detailed individual performance analysis.
Main Results:
- Substantial variation in performance was observed, from rudimentary to age-equivalent abilities.
- Three children showed severe qualitative differences in written language processing.
- Individual performance profiles were detailed, with remediation suggestions and a 12-month re-test.
Conclusions:
- Thorough written language assessment is crucial for evaluating language acquisition post-CI.
- Results indicate a highly heterogeneous performance landscape among CI users.
- Model-oriented testing can identify specific processing strategies, enabling tailored remediation programs.
