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Predicting Persistent Developmental Stuttering Using a Cumulative Risk Approach

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Title: Predicting Persistent Developmental Stuttering Using a Cumulative Risk Approach
Language: English
Authors: Singer, Cara M. (ORCID 0000-0003-1520-0606), Otieno, Sango, Chang, Soo-Eun (ORCID 0000-0003-4448-9525), Jones, Robin M.
Source: Journal of Speech, Language, and Hearing Research. Jan 2022 65(1):70-95.
Availability: American Speech-Language-Hearing Association. 2200 Research Blvd #250, Rockville, MD 20850. Tel: 301-296-5700; Fax: 301-296-8580; e-mail: slhr@asha.org; Web site: http://jslhr.pubs.asha.org
Peer Reviewed: Y
Page Count: 26
Publication Date: 2022
Sponsoring Agency: National Institute on Deafness and Other Communication Disorders (NIDCD) (DHHS/NIH)
National Center for Advancing Translational Sciences (NCATS) (DHHS/NIH)
Contract Number: R01DC011277
R01DC000523
R56DC000523
R21DC016723
UL1TR00044506
Document Type: Journal Articles
Reports - Research
Descriptors: Stuttering, Child Development, Predictor Variables, At Risk Persons, Preschool Children, Gender Differences, Background, Incidence, Speech Skills, Language Skills, Age Differences, Severity (of Disability), Developmental Delays, Articulation (Speech)
Geographic Terms: Michigan, Tennessee (Nashville)
Assessment and Survey Identifiers: Goldman Fristoe Test of Articulation, Test of Early Language Development, Clinical Evaluation of Language Fundamentals
DOI: 10.1044/2021_JSLHR-21-00162
ISSN: 1092-4388
Abstract: Purpose: The purpose of this study was to explore how well a cumulative risk approach, based on empirically supported predictive factors, predicts whether a young child who stutters is likely to develop persistent developmental stuttering. In a cumulative risk approach, the number of predictive factors indicating a child is at risk to develop persistent stuttering is evaluated, and a greater number of indicators of risk are hypothesized to confer greater risk of persistent stuttering. Method: We combined extant data on 3- to 5-year-old children who stutter from two longitudinal studies to identify cutoff values for continuous predictive factors (e.g., speech and language skills, age at onset, time since onset, stuttering frequency) and, in combination with binary predictors (e.g., sex, family history of stuttering), used all-subsets regression and receiver operating characteristic curves to compare the predictive validity of different combinations of 10 risk factors. The optimal combination of predictive factors and the odds of a child developing persistent stuttering based on an increasing number of factors were calculated. Results: Based on 67 children who stutter (i.e., 44 persisting and 23 recovered) with relatively strong speech-language skills, the predictive factor model that yielded the best predictive validity was based on time since onset ([greater than or equal to] 19 months), speech sound skills ([less than or equal to] 115 standard score), expressive language skills ([less than or equal to] 106 standard score), and stuttering severity ([greater than or equal to] 17 Stuttering Severity Instrument total score). When the presence of at least two predictive factors was used to confer elevated risk to develop persistent stuttering, the model yielded 93% sensitivity and 65% specificity. As a child presented with a greater number of these four risk factors, the odds for persistent stuttering increased. Conclusions: Findings support the use of a cumulative risk approach and the predictive utility of assessing multiple domains when evaluating a child's risk of developing persistent stuttering. Clinical implications and future directions are discussed.
Abstractor: As Provided
Entry Date: 2022
Accession Number: EJ1325505
Database: ERIC
FullText Links:
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  Data: Predicting Persistent Developmental Stuttering Using a Cumulative Risk Approach
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  Data: <searchLink fieldCode="AR" term="%22Singer%2C+Cara+M%2E%22">Singer, Cara M.</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0003-1520-0606">0000-0003-1520-0606</externalLink>)<br /><searchLink fieldCode="AR" term="%22Otieno%2C+Sango%22">Otieno, Sango</searchLink><br /><searchLink fieldCode="AR" term="%22Chang%2C+Soo-Eun%22">Chang, Soo-Eun</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0003-4448-9525">0000-0003-4448-9525</externalLink>)<br /><searchLink fieldCode="AR" term="%22Jones%2C+Robin+M%2E%22">Jones, Robin M.</searchLink>
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  Data: <searchLink fieldCode="SO" term="%22Journal+of+Speech%2C+Language%2C+and+Hearing+Research%22"><i>Journal of Speech, Language, and Hearing Research</i></searchLink>. Jan 2022 65(1):70-95.
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  Data: American Speech-Language-Hearing Association. 2200 Research Blvd #250, Rockville, MD 20850. Tel: 301-296-5700; Fax: 301-296-8580; e-mail: slhr@asha.org; Web site: http://jslhr.pubs.asha.org
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  Data: 26
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  Data: National Institute on Deafness and Other Communication Disorders (NIDCD) (DHHS/NIH)<br />National Center for Advancing Translational Sciences (NCATS) (DHHS/NIH)
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  Data: <searchLink fieldCode="DE" term="%22Stuttering%22">Stuttering</searchLink><br /><searchLink fieldCode="DE" term="%22Child+Development%22">Child Development</searchLink><br /><searchLink fieldCode="DE" term="%22Predictor+Variables%22">Predictor Variables</searchLink><br /><searchLink fieldCode="DE" term="%22At+Risk+Persons%22">At Risk Persons</searchLink><br /><searchLink fieldCode="DE" term="%22Preschool+Children%22">Preschool Children</searchLink><br /><searchLink fieldCode="DE" term="%22Gender+Differences%22">Gender Differences</searchLink><br /><searchLink fieldCode="DE" term="%22Background%22">Background</searchLink><br /><searchLink fieldCode="DE" term="%22Incidence%22">Incidence</searchLink><br /><searchLink fieldCode="DE" term="%22Speech+Skills%22">Speech Skills</searchLink><br /><searchLink fieldCode="DE" term="%22Language+Skills%22">Language Skills</searchLink><br /><searchLink fieldCode="DE" term="%22Age+Differences%22">Age Differences</searchLink><br /><searchLink fieldCode="DE" term="%22Severity+%28of+Disability%29%22">Severity (of Disability)</searchLink><br /><searchLink fieldCode="DE" term="%22Developmental+Delays%22">Developmental Delays</searchLink><br /><searchLink fieldCode="DE" term="%22Articulation+%28Speech%29%22">Articulation (Speech)</searchLink>
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  Data: <searchLink fieldCode="DE" term="%22Michigan%22">Michigan</searchLink><br /><searchLink fieldCode="DE" term="%22Tennessee+%28Nashville%29%22">Tennessee (Nashville)</searchLink>
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  Data: 10.1044/2021_JSLHR-21-00162
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  Data: 1092-4388
– Name: Abstract
  Label: Abstract
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  Data: Purpose: The purpose of this study was to explore how well a cumulative risk approach, based on empirically supported predictive factors, predicts whether a young child who stutters is likely to develop persistent developmental stuttering. In a cumulative risk approach, the number of predictive factors indicating a child is at risk to develop persistent stuttering is evaluated, and a greater number of indicators of risk are hypothesized to confer greater risk of persistent stuttering. Method: We combined extant data on 3- to 5-year-old children who stutter from two longitudinal studies to identify cutoff values for continuous predictive factors (e.g., speech and language skills, age at onset, time since onset, stuttering frequency) and, in combination with binary predictors (e.g., sex, family history of stuttering), used all-subsets regression and receiver operating characteristic curves to compare the predictive validity of different combinations of 10 risk factors. The optimal combination of predictive factors and the odds of a child developing persistent stuttering based on an increasing number of factors were calculated. Results: Based on 67 children who stutter (i.e., 44 persisting and 23 recovered) with relatively strong speech-language skills, the predictive factor model that yielded the best predictive validity was based on time since onset ([greater than or equal to] 19 months), speech sound skills ([less than or equal to] 115 standard score), expressive language skills ([less than or equal to] 106 standard score), and stuttering severity ([greater than or equal to] 17 Stuttering Severity Instrument total score). When the presence of at least two predictive factors was used to confer elevated risk to develop persistent stuttering, the model yielded 93% sensitivity and 65% specificity. As a child presented with a greater number of these four risk factors, the odds for persistent stuttering increased. Conclusions: Findings support the use of a cumulative risk approach and the predictive utility of assessing multiple domains when evaluating a child's risk of developing persistent stuttering. Clinical implications and future directions are discussed.
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      – SubjectFull: Predictor Variables
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