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 SRCLD Presentation Details 

  Title  
       
    Narrative Analysis: To reveal neurocognitive impairments, count errors not desirable features  
Author(s)
John Thorne - University of Washington, Dept. of Speech and Hearing Sciences
Truman Coggins - University of Washington, Dept. of Speech and Hearing Sciences

SRCLD Info
SRCLD Year: 2010
Presentation Type: Poster Presentation
Poster Number:
Presentation Time: (na)
Categories
- Assessment
- Developmental Disabilities
- Language Impairment, School Age
Abstract
Rationale

Neurocognitive impairments impede narrative performance in two ways: 1) by reducing the rate at which desirable features occur and/or 2) by increasing the rate of errors. Here, we explore the prediction that error counts involving obligatory forms will be more revealing of impairment than counts of desirable features because they do not involve factors of motivation and creative choice.

Methods

53 school-age children were classified according to impairment risk using existing records. Predictive accuracy of two narrative measures were compared using signal detection methodology: Number of Different Words (NDW), which quantifies a desirable feature, and the rate of Nominal Reference Errors (rNRE), which quantifies errors in obligatory marking of “new vs. known” distinctions.

Results

With better sensitivity, and accuracy, rNRE (AUC = 0.84) showed significantly greater predictive potential than NDW (AUC = 0.65).

Conclusion

A narrative measure that quantifies erroneous markings of obligatory forms has greater potential for revealing underlying neurocognitive impairments in school-age children than a measure that counts a desirable feature of the narrative.
Supported in part by: NIDCD and NICHD, NIH, R13 DC001677, Susan Ellis Weismer, Principal Investigator
University of Wisconsin-Madison - Department of Communication Sciences and Disorders