Literature DB >> 23773664

Screening school-aged children for risk of stuttering.

Peter Howell1.   

Abstract

OBJECTIVES: Howell and Davis's (2011) model that predicts whether stuttering in eight-year old children will persist or recover by teenage was adapted for screening school-aged children for risk of stuttering. Stuttering-severity scores were used to predict whether children belonged to fluent or stuttering groups. Predicted group assignments were compared for models in which severity measures were made with whole-word repetitions excluded or included. The best model for distinguishing children who stutter (CWS) from fluent children was validated across a wide range of ages.
DESIGN: Stuttering-severity scores from CWS (222 for development, and 272 for validation, of the models) and fluent children (103 for development, and 25 for validation, of the models) were employed. Models were developed that predicted prognosis and screened CWS and fluent children. All these analyses were conducted both with whole-word repetitions excluded and included in the stuttering-severity scores. The model that screened fluent children from all CWS which excluded whole-word repetitions was validated for children across a range of ages.
RESULTS: All models achieved around 80% specificity and sensitivity. Models in which whole-word repetitions were excluded were always better than those which included them. Validation of the screening for fluency with whole-word repetitions excluded classified 84.4% of fluent children, and 88.0% of CWS, correctly. Some of these children differed in age from those used to develop the model.
CONCLUSION: Howell and Davis's risk factor model for predicting persistence/recovery can be extended to screen school-aged children for fluency. EDUCATIONAL
OBJECTIVES: After reading this article, participants will be able to: (1) describe the difference between finding group differences and risk factor modeling in stuttering research; (2) summarize the strengths and weaknesses of stuttering severity instrument version three; (3) discuss how validation of diagnostic and screening models for fluency can be performed; (4) see how risk models have potential applications for screening for communication disorders in general.
Copyright © 2012. Published by Elsevier Inc.

Entities:  

Mesh:

Year:  2012        PMID: 23773664     DOI: 10.1016/j.jfludis.2012.09.002

Source DB:  PubMed          Journal:  J Fluency Disord        ISSN: 0094-730X            Impact factor:   2.538


  5 in total

1.  Speech sound articulation abilities of preschool-age children who stutter.

Authors:  Chagit E Clark; Edward G Conture; Tedra A Walden; Warren E Lambert
Journal:  J Fluency Disord       Date:  2013-10-09       Impact factor: 2.538

2.  The disfluent speech of bilingual spanish-english children: considerations for differential diagnosis of stuttering.

Authors:  Courtney T Byrd; Lisa M Bedore; Daniel Ramos
Journal:  Lang Speech Hear Serv Sch       Date:  2015-01       Impact factor: 2.983

3.  Planum temporale asymmetry in people who stutter.

Authors:  Patricia M Gough; Emily L Connally; Peter Howell; David Ward; Jennifer Chesters; Kate E Watkins
Journal:  J Fluency Disord       Date:  2017-06-16       Impact factor: 2.538

4.  Does Working-Memory Training Given to Reception-Class Children Improve the Speech of Children at Risk of Fluency Difficulty?

Authors:  Peter Howell; Li Ying Chua; Kaho Yoshikawa; Hannah Hau Shuen Tang; Taniya Welmillage; John Harris; Kevin Tang
Journal:  Front Psychol       Date:  2020-11-17

5.  Identifying Stuttering in Arabic Speakers Who Stutter: Development of a Non-word Repetition Task and Preliminary Results.

Authors:  Roaa Alsulaiman; John Harris; Sarah Bamaas; Peter Howell
Journal:  Front Pediatr       Date:  2022-03-11       Impact factor: 3.418

  5 in total

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