Predicting Persistent Developmental Stuttering Using a Cumulative Risk Approach

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 fact...

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Veröffentlicht in:Journal of speech, language, and hearing research language, and hearing research, 2022-01, Vol.65 (1), p.70-95
Hauptverfasser: Singer, Cara M, Otieno, Sango, Chang, Soo-Eun, Jones, Robin M
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container_issue 1
container_start_page 70
container_title Journal of speech, language, and hearing research
container_volume 65
creator Singer, Cara M
Otieno, Sango
Chang, Soo-Eun
Jones, Robin M
description 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.
doi_str_mv 10.1044/2021_JSLHR-21-00162
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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.</description><identifier>ISSN: 1092-4388</identifier><identifier>ISSN: 1558-9102</identifier><identifier>EISSN: 1558-9102</identifier><identifier>DOI: 10.1044/2021_JSLHR-21-00162</identifier><identifier>PMID: 34902288</identifier><language>eng</language><publisher>United States: American Speech-Language-Hearing Association</publisher><subject>Age Differences ; Articulation (Speech) ; At Risk Persons ; Background ; Child Development ; Child, Preschool ; Children ; Children &amp; youth ; Developmental Delays ; Families &amp; family life ; Gender Differences ; Humans ; Incidence ; Language ; Language Skills ; Longitudinal Studies ; Phonetics ; Physiological aspects ; Predictor Variables ; Preschool Children ; Risk factors ; Severity (of Disability) ; Speech ; Speech Production Measurement ; Speech Skills ; Speech therapists ; Standard scores ; Stuttering ; Stuttering - diagnosis ; Validity</subject><ispartof>Journal of speech, language, and hearing research, 2022-01, Vol.65 (1), p.70-95</ispartof><rights>COPYRIGHT 2022 American Speech-Language-Hearing Association</rights><rights>Copyright American Speech-Language-Hearing Association Jan 2022</rights><rights>Copyright © 2021 American Speech-Language-Hearing Association</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c591t-801f3291e33c5f1ab33762cf2bdac9715f50b507ea81e1fcbb540d946fed347e3</citedby><cites>FETCH-LOGICAL-c591t-801f3291e33c5f1ab33762cf2bdac9715f50b507ea81e1fcbb540d946fed347e3</cites><orcidid>0000-0003-1520-0606 ; 0000-0003-4448-9525</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>230,314,780,784,885,27923,27924</link.rule.ids><backlink>$$Uhttp://eric.ed.gov/ERICWebPortal/detail?accno=EJ1325505$$DView record in ERIC$$Hfree_for_read</backlink><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/34902288$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Singer, Cara M</creatorcontrib><creatorcontrib>Otieno, Sango</creatorcontrib><creatorcontrib>Chang, Soo-Eun</creatorcontrib><creatorcontrib>Jones, Robin M</creatorcontrib><title>Predicting Persistent Developmental Stuttering Using a Cumulative Risk Approach</title><title>Journal of speech, language, and hearing research</title><addtitle>J Speech Lang Hear Res</addtitle><description>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. 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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. 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source MEDLINE; EBSCOhost Education Source; Alma/SFX Local Collection
subjects Age Differences
Articulation (Speech)
At Risk Persons
Background
Child Development
Child, Preschool
Children
Children & youth
Developmental Delays
Families & family life
Gender Differences
Humans
Incidence
Language
Language Skills
Longitudinal Studies
Phonetics
Physiological aspects
Predictor Variables
Preschool Children
Risk factors
Severity (of Disability)
Speech
Speech Production Measurement
Speech Skills
Speech therapists
Standard scores
Stuttering
Stuttering - diagnosis
Validity
title Predicting Persistent Developmental Stuttering Using a Cumulative Risk Approach
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