{"id":{"repo_id":"fsu-retro","oai_identifier":"oai:diginole.lib.fsu.edu:fsu_928077"},"canonical_url":"https://search.dev.ndltd.org/etd/fsu-retro/oai:diginole.lib.fsu.edu:fsu_928077","repository":{"repo_id":"fsu-retro","name":"Florida State University","base_url":"https://repository.lib.fsu.edu/oai2"},"display":{"title":"Evaluation of a Screening Battery for Developmental Language Disorder","abstract":"Students with developmental language disorder (DLD) have difficulty understanding and using oral language, and these difficulties negatively impact academic achievement. DLD has a prevalence of 7-8% of school-age students, yet research has shown that less than half of those students are receiving services. Implementation of a screening tool in early elementary school has the potential to improve identification challenges of DLD in schools. The purpose of this study was to evaluate a comprehensive language screening battery that included seven language measures. The study aimed to identify what language measures were most predictive of overall language ability and determine what language measures resulted in the highest diagnostic accuracy for DLD. One hundred and twenty-six students were administered a screening battery that included sentence repetition, nonword repetition, listening comprehension, expressive vocabulary, receptive vocabulary, synonyms, and paired associate learning. All students were then administered the Core Language subtests from the Clinical Evaluation of Language Fundamentals-5th Edition (CELF-5). The CELF-5 served as the reference standard to evaluate the screening battery. A dominance analysis was performed to determine the relative importance of all measures as well as determine what models explained the most variance in the outcome. A series of logistic regressions were then used to determine what measures predicted DLD. Predicted probabilities from the logistic regressions were entered into ROC curve analyses to analyze diagnostic accuracy of various models. Results of the dominance analysis revealed that sentence repetition was the most dominant predictor of language ability. Adding additional measures to sentence repetition slightly increased the amount of variance explained, but the changes in R2 were not significant. Results of the logistic regression revealed that sentence repetition was the only consistent predictor of DLD. Preliminary results indicate that including additional measures with a sentence repetition task increases diagnostic accuracy. However, results related to diagnostic accuracy should be interpreted cautiously due to the small sample size of students with DLD (n=17).","abstract_html":"Students with developmental language disorder (DLD) have difficulty understanding and using oral language, and these difficulties negatively impact academic achievement. DLD has a prevalence of 7-8% of school-age students, yet research has shown that less than half of those students are receiving services. Implementation of a screening tool in early elementary school has the potential to improve identification challenges of DLD in schools. The purpose of this study was to evaluate a comprehensive language screening battery that included seven language measures. The study aimed to identify what language measures were most predictive of overall language ability and determine what language measures resulted in the highest diagnostic accuracy for DLD. One hundred and twenty-six students were administered a screening battery that included sentence repetition, nonword repetition, listening comprehension, expressive vocabulary, receptive vocabulary, synonyms, and paired associate learning. All students were then administered the Core Language subtests from the Clinical Evaluation of Language Fundamentals-5th Edition (CELF-5). The CELF-5 served as the reference standard to evaluate the screening battery. A dominance analysis was performed to determine the relative importance of all measures as well as determine what models explained the most variance in the outcome. A series of logistic regressions were then used to determine what measures predicted DLD. Predicted probabilities from the logistic regressions were entered into ROC curve analyses to analyze diagnostic accuracy of various models. Results of the dominance analysis revealed that sentence repetition was the most dominant predictor of language ability. Adding additional measures to sentence repetition slightly increased the amount of variance explained, but the changes in R2 were not significant. Results of the logistic regression revealed that sentence repetition was the only consistent predictor of DLD. Preliminary results indicate that including additional measures with a sentence repetition task increases diagnostic accuracy. However, results related to diagnostic accuracy should be interpreted cautiously due to the small sample size of students with DLD (n=17).","abstract_has_math":false,"creators":[],"institution":"Florida State University","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":["Summy, Sarah Rebecca Adams (author)","Catts, Hugh W. 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DLD has a prevalence of 7-8% of school-age students, yet research has shown that less than half of those students are receiving services. Implementation of a screening tool in early elementary school has the potential to improve identification challenges of DLD in schools. The purpose of this study was to evaluate a comprehensive language screening battery that included seven language measures. The study aimed to identify what language measures were most predictive of overall language ability and determine what language measures resulted in the highest diagnostic accuracy for DLD. One hundred and twenty-six students were administered a screening battery that included sentence repetition, nonword repetition, listening comprehension, expressive vocabulary, receptive vocabulary, synonyms, and paired associate learning. All students were then administered the Core Language subtests from the Clinical Evaluation of Language Fundamentals-5th Edition (CELF-5). The CELF-5 served as the reference standard to evaluate the screening battery. A dominance analysis was performed to determine the relative importance of all measures as well as determine what models explained the most variance in the outcome. A series of logistic regressions were then used to determine what measures predicted DLD. Predicted probabilities from the logistic regressions were entered into ROC curve analyses to analyze diagnostic accuracy of various models. Results of the dominance analysis revealed that sentence repetition was the most dominant predictor of language ability. Adding additional measures to sentence repetition slightly increased the amount of variance explained, but the changes in R2 were not significant. Results of the logistic regression revealed that sentence repetition was the only consistent predictor of DLD. Preliminary results indicate that including additional measures with a sentence repetition task increases diagnostic accuracy. However, results related to diagnostic accuracy should be interpreted cautiously due to the small sample size of students with DLD (n=17).","A Dissertation submitted to the School of Communication Science and Disorders in partial fulfillment of the requirements for the degree of Doctor of Philosophy.","June 22, 2023.","Developmental language disorder, Screening","Includes bibliographical references.","Hugh Catts, Professor Directing Dissertation; Nicole Patton Terry, University Representative; Kelly Farquharson, Committee Member; Carla Wood, Committee Member."]},{"key":"dc:format","label":"Dc Format","values":["computer","online resource","1 online resource (73 pages)","application/pdf"]},{"key":"dc:title","label":"Title","values":["Evaluation of a Screening Battery for Developmental Language Disorder"]}]}],"canonical_facts":{"dc:contributor":["Summy, Sarah Rebecca Adams (author)","Catts, Hugh W. (Hugh William), 1949- (professor directing dissertation)","Terry, Nicole Patton (university representative)","Farquharson, Kelly (committee member)","Wood, Carla (committee member)","Florida State University (degree granting institution)","College of Communication and Information (degree granting college)","School of Communication Science and Disorders (degree granting department)"],"dc:date":["2023"],"dc:description":["Students with developmental language disorder (DLD) have difficulty understanding and using oral language, and these difficulties negatively impact academic achievement. DLD has a prevalence of 7-8% of school-age students, yet research has shown that less than half of those students are receiving services. Implementation of a screening tool in early elementary school has the potential to improve identification challenges of DLD in schools. The purpose of this study was to evaluate a comprehensive language screening battery that included seven language measures. The study aimed to identify what language measures were most predictive of overall language ability and determine what language measures resulted in the highest diagnostic accuracy for DLD. One hundred and twenty-six students were administered a screening battery that included sentence repetition, nonword repetition, listening comprehension, expressive vocabulary, receptive vocabulary, synonyms, and paired associate learning. All students were then administered the Core Language subtests from the Clinical Evaluation of Language Fundamentals-5th Edition (CELF-5). The CELF-5 served as the reference standard to evaluate the screening battery. A dominance analysis was performed to determine the relative importance of all measures as well as determine what models explained the most variance in the outcome. A series of logistic regressions were then used to determine what measures predicted DLD. Predicted probabilities from the logistic regressions were entered into ROC curve analyses to analyze diagnostic accuracy of various models. Results of the dominance analysis revealed that sentence repetition was the most dominant predictor of language ability. Adding additional measures to sentence repetition slightly increased the amount of variance explained, but the changes in R2 were not significant. Results of the logistic regression revealed that sentence repetition was the only consistent predictor of DLD. Preliminary results indicate that including additional measures with a sentence repetition task increases diagnostic accuracy. 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