Clinical Forum  |   January 2010
Using Language Sample Databases
Author Notes
  • Contact author: John J. Heilmann, Department of Communication Sciences and Disorders, Mail Stop #668, East Carolina University, Greenville, NC 27858-4353. E-mail: heilmannj@ecu.edu.
Development / School-Based Settings / Research Issues, Methods & Evidence-Based Practice / Normal Language Processing / Language Disorders / Attention, Memory & Executive Functions / Clinical Forum
Clinical Forum   |   January 2010
Using Language Sample Databases
Language, Speech, and Hearing Services in Schools January 2010, Vol.41, 84-95. doi:10.1044/0161-1461(2009/08-0075)
History: Accepted 18 Feb 2009 , Received 03 Jul 2008 , Revised 22 Dec 2008
Language, Speech, and Hearing Services in Schools January 2010, Vol.41, 84-95. doi:10.1044/0161-1461(2009/08-0075)
History: Accepted 18 Feb 2009 , Received 03 Jul 2008 , Revised 22 Dec 2008

Purpose: Over the past 50 years, language sample analysis (LSA) has evolved from a powerful research tool that is used to document children’s linguistic development into a powerful clinical tool that is used to identify and describe the language skills of children with language impairment. The The Systematic Analysis of Language Transcripts (SALT; J. F. Miller & A. Iglesias, 2008) Software Project has developed several databases of language samples from more than 6,000 typical speakers. This article presents an overview of the SALT databases and then demonstrates the power of these databases in classifying children with language impairment.

Method: Conversational language samples were elicited from 244 children with language impairment who were between 3 and 13 years of age. Language production measures generated from these transcripts were compared to measures from 244 transcripts in the SALT conversational database. A series of discriminant function analyses were completed to document the sensitivity and specificity of the language sample measures.

Results: The language sample measures were effective in classifying children based on their language status, with correct identification of 78% of the children with language impairment and 85% of the children who were typically developing.

Conclusion: The SALT databases provide a useful tool for the clinical management of children with language impairment.

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