A Diagnostic Marker to Discriminate Childhood Apraxia of Speech From Speech Delay: II. Validity Studies of the Pause Marker

Shriberg, Lawrence D.; Strand, Edythe A.; Fourakis, Marios; Jakielski, Kathy J.; Hall, Sheryl D.; Karlsson, Heather B.; Mabie, Heather L.; McSweeny, Jane L.; Tilkens, Christie M.; Wilson, David L.

doi:10.1044/2016_jslhr-s-15-0297

Cited by 23 publications

(21 citation statements)

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“…Findings reported in PM II, PM III (Shriberg et al, 2017b(Shriberg et al, , 2017c, and the present article are interpreted to be consistent with six of the seven attributes of valued diagnostic markers described in PM I (Table 1; Shriberg et al, 2017a): accuracy, reliability, coherence, discreteness, parsimony, and generality. The psychometric findings and findings discussed below that presently constrain the external validity of the PM warrant classification of the PM as a "near conclusive" rather than conclusive diagnostic marker to discriminate CAS from SD.…”

Section: Resultssupporting

confidence: 58%

“…In summary, construct validity and psychometric support for the PM was reported in the second article in this series (PM II; Shriberg et al, 2017b), and its theoretical coherence with speech processing deficits in CAS was addressed in the third article in this series (PM III; Shriberg et al, 2017c). The goal of the present research was to assess one feature of the generality of the PM (see PM I, Table 1; Shriberg et al, 2017a): its ability to scale severity of CAS.…”

Section: Rationale and Methodsmentioning

confidence: 99%

“…As described and referenced in the three previous articles (Shriberg et al, 2017a(Shriberg et al, , 2017b(Shriberg et al, , 2017c, a PM score is the percentage of occurrence of four types of inappropriate between-words pauses in a continuous speech sample. A PM score is calculated by dividing the number of such pauses in a continuous speech sample by the number of between-words pause opportunities.…”

Section: The Pmmentioning

confidence: 99%

“…Severity findings for the 4 classifications and retrospective longitudinal findings from 8 participants with CAS supported the validity and stability of the PMI. Conclusion: Findings support research and clinical use of the PMI to scale the severity of CAS.A four-article series (Shriberg et al, 2017a(Shriberg et al, , 2017b(Shriberg et al, , 2017c, and the present article) to develop and assess the theoretical and clinical utility of a singlesign, behavioral marker of childhood apraxia of speech (CAS) poses the following three questions: …”

mentioning

confidence: 99%

“…A four-article series (Shriberg et al, 2017a(Shriberg et al, , 2017b(Shriberg et al, , 2017c, and the present article) to develop and assess the theoretical and clinical utility of a singlesign, behavioral marker of childhood apraxia of speech (CAS) poses the following three questions:…”

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confidence: 99%

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A Diagnostic Marker to Discriminate Childhood Apraxia of Speech From Speech Delay: IV. The Pause Marker Index

Shriberg

Strand

Fourakis

et al. 2017

J Speech Lang Hear Res

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Purpose: Three previous articles provided rationale, methods, and several forms of validity support for a diagnostic marker of childhood apraxia of speech (CAS), termed the pause marker (PM). Goals of the present article were to assess the validity and stability of the PM Index (PMI) to scale CAS severity. Method: PM scores and speech, prosody, and voice precision-stability data were obtained for participants with CAS in idiopathic, neurogenetic, and complex neurodevelopmental disorders; adult-onset apraxia of speech consequent to stroke and primary progressive apraxia; and idiopathic speech delay. Three studies were completed including criterion and concurrent validity studies of the PMI and a temporal stability study of the PMI using retrospective case studies. Results: PM scores were significantly correlated with other signs of CAS precision and stability. The best fit of the distribution of PM scores to index CAS severity was obtained by dividing scores into 4 ordinal severity classifications: mild, mild-moderate, moderate-severe, and severe. Severity findings for the 4 classifications and retrospective longitudinal findings from 8 participants with CAS supported the validity and stability of the PMI. Conclusion: Findings support research and clinical use of the PMI to scale the severity of CAS.A four-article series (Shriberg et al., 2017a(Shriberg et al., , 2017b(Shriberg et al., , 2017c, and the present article) to develop and assess the theoretical and clinical utility of a singlesign, behavioral marker of childhood apraxia of speech (CAS) poses the following three questions: 1.Do findings from construct and criterion validity studies support the diagnostic accuracy of a behavioral marker, the pause marker (PM), to discriminate CAS from speech delay (SD)?2. Do findings from the PM and other measures support the hypothesis of core representational and transcoding deficits in CAS, and is the PM theoretically coherent with those deficits?3. Do findings from cross-sectional and retrospective longitudinal case studies support an ordinal scale of PM scores, the Pause Marker Index (PMI), to quantify the severity of CAS for research and clinical applications?The short-term goal of the PM is to provide a behavioral marker of CAS for research and clinical practice. A longer term goal of the PM is to provide quantitative inclusionary and exclusionary criteria to identify participants who are true positive for CAS in studies to identify and validate a biomarker of CAS. The present article addresses both goals. As proposed in the first article in this series (PM I; Shriberg et al., 2017a, Table 1), a highly valued attribute of diagnostic markers is generality, that is, a marker has research and clinical utility beyond identifying presence or absence of a disorder. In the present context, a behavioral marker of CAS has research and clinical generality when in addition to being diagnostically sensitive to and specific for a prior, active, and/or future disorder, it also quantifies the severity of the disorder. The three...

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Section: Resultssupporting

confidence: 58%

Section: Rationale and Methodsmentioning

confidence: 99%

Section: The Pmmentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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A Diagnostic Marker to Discriminate Childhood Apraxia of Speech From Speech Delay: IV. The Pause Marker Index

Shriberg

Strand

Fourakis

et al. 2017

J Speech Lang Hear Res

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Voice Pathology Detection Using Artificial Neural Networks and Support Vector Machines Powered by a Multicriteria Optimization Algorithm

Areiza-Laverde

Castro-Ospina

Peluffo-Ordóñez

2018

Communications in Computer and Information Science

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The efficacy of acoustic-based articulatory phenotyping for characterizing and classifying four divergent neurodegenerative diseases using sequential motion rates

et al. 2022

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Despite the impacts of neurodegeneration on speech function, little is known about how to comprehensively characterize the resulting speech abnormalities using a set of objective measures. Quantitative phenotyping of speech motor impairments may have important implications for identifying clinical syndromes and their underlying etiologies, monitoring disease progression over time, and improving treatment efficacy. The goal of this research was to investigate the validity and classification accuracy of comprehensive acoustic-based articulatory phenotypes in speakers with distinct neurodegenerative diseases. Articulatory phenotypes were characterized based on acoustic features that were selected to represent five components of motor performance: Coordination, Consistency, Speed, Precision, and Rate. The phenotypes were first used to characterize the articulatory abnormalities across four progressive neurologic diseases known to have divergent speech motor deficits: amyotrophic lateral sclerosis (ALS), progressive ataxia (PA), Parkinson's disease (PD), and the nonfluent variant of primary progressive aphasia and progressive apraxia of speech (nfPPA+PAOS). We then examined the efficacy of articulatory phenotyping for disease classification. Acoustic analyses were conducted on audio recordings of 217 participants (i.e., 46 ALS, 52 PA, 60 PD, 20 nfPPA+PAOS, and 39 controls) during a sequential speech task. Results revealed evidence of distinct articulatory phenotypes for the four clinical groups and that the phenotypes demonstrated strong classification accuracy for all groups except ALS. Our results highlight the phenotypic variability present across neurodegenerative diseases, which, in turn, may inform (1) the differential diagnosis of neurological diseases and (2) the development of sensitive outcome measures for monitoring disease progression or assessing treatment efficacy.

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A Diagnostic Marker to Discriminate Childhood Apraxia of Speech From Speech Delay: II. Validity Studies of the Pause Marker

Cited by 23 publications

References 14 publications

A Diagnostic Marker to Discriminate Childhood Apraxia of Speech From Speech Delay: IV. The Pause Marker Index

A Diagnostic Marker to Discriminate Childhood Apraxia of Speech From Speech Delay: IV. The Pause Marker Index

Voice Pathology Detection Using Artificial Neural Networks and Support Vector Machines Powered by a Multicriteria Optimization Algorithm

The efficacy of acoustic-based articulatory phenotyping for characterizing and classifying four divergent neurodegenerative diseases using sequential motion rates

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