Treffer: Identifying early language predictors: A replication of Gasparini et al. (2023) confirming applicability in a general population cohort.
Title:
Identifying early language predictors: A replication of Gasparini et al. (2023) confirming applicability in a general population cohort.
Authors:
Gasparini L; Department of Paediatrics, The University of Melbourne, Parkville, VIC, Australia.; Murdoch Children's Research Institute, Parkville, VIC, Australia., Shepherd DA; Department of Paediatrics, The University of Melbourne, Parkville, VIC, Australia.; Murdoch Children's Research Institute, Parkville, VIC, Australia., Wang J; Department of Paediatrics, The University of Melbourne, Parkville, VIC, Australia.; Murdoch Children's Research Institute, Parkville, VIC, Australia., Wake M; Department of Paediatrics, The University of Melbourne, Parkville, VIC, Australia.; Murdoch Children's Research Institute, Parkville, VIC, Australia.; Liggins Institute, The University of Auckland, Grafton, Auckland, New Zealand., Morgan AT; Murdoch Children's Research Institute, Parkville, VIC, Australia.; Department of Audiology and Speech Pathology, The University of Melbourne, Parkville, VIC, Australia.; Royal Children's Hospital Melbourne, Parkville, VIC, Australia.
Source:
International journal of language & communication disorders [Int J Lang Commun Disord] 2024 Nov-Dec; Vol. 59 (6), pp. 2352-2366. Date of Electronic Publication: 2024 Jul 01.
Publication Type:
Journal Article
Language:
English
Journal Info:
Publisher: Wiley Country of Publication: United States NLM ID: 9803709 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1460-6984 (Electronic) Linking ISSN: 13682822 NLM ISO Abbreviation: Int J Lang Commun Disord Subsets: MEDLINE
Imprint Name(s):
Publication: 2011- : Malden, MA : Wiley
Original Publication: London : Taylor & Francis for the Royal College of Speech & Language Therapists, c1998-
Original Publication: London : Taylor & Francis for the Royal College of Speech & Language Therapists, c1998-
MeSH Terms:
References:
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Bishop, D.V.M., Snowling, M.J., Thompson, P.A. & Greenhalgh, T., & the CATALISE‐2 consortium. (2017) Phase 2 of CATALISE: a multinational and multidisciplinary Delphi consensus study of problems with language development: terminology. Journal of Child Psychology and Psychiatry, 58(10), 1068–1080. https://doi.org/10.1111/jcpp.12721.
Borovsky, A., Thal, D. & Leonard, L.B. (2021) Moving towards accurate and early prediction of language delay with network science and machine learning approaches. Scientific Reports, 11(1), 8136. https://doi.org/10.1038/s41598‐021‐85982‐0.
Botting, N., Conti‐Ramsden, G. & Faragher, B. (2001) Psycholinguistic Markers for Specific Language Impairment (SLI). The Journal of Child Psychology and Psychiatry and Allied Disciplines, 42(6), 741–748. Cambridge Core. https://doi.org/10.1017/S0021963001007600.
Breiman, L. (2001) Random forests. Machine Learning, 45, 5–32. https://doi.org/10.1023/A:1010933404324.
Calder, S.D., Brennan‐Jones, C.G., Robinson, M., Whitehouse, A. & Hill, E. (2022) The prevalence of and potential risk factors for Developmental Language Disorder at 10 years in the Raine Study. Journal of Paediatrics and Child Health, 16149. https://doi.org/10.1111/jpc.16149.
Clifford, S.A., Davies, S. & Wake, M. (2019) Child Health CheckPoint: cohort summary and methodology of a physical health and biospecimen module for the Longitudinal Study of Australian Children. BMJ Open, 9(Suppl 3), 3–22. https://doi.org/10.1136/bmjopen‐2017‐020261.
Conti‐Ramsden, G. & Durkin, K. (2012) Postschool Educational and Employment Experiences of Young People With Specific Language Impairment. Language, Speech, and Hearing Services in Schools, 43(4), 507–520. https://doi.org/10.1044/0161‐1461(2012/11‐0067).
Council on Children With Disabilities, Section on Developmental Behavioral Pediatrics, Bright Futures Steering Committee, & Medical Home Initiatives for Children with Special Needs Project Advisory Committee. (2006) Identifying infants and young children with developmental disorders in the medical home: an algorithm for developmental surveillance and screening. Pediatrics, 118(1), 405–420. https://doi.org/10.1542/peds.2006‐1231.
Donolato, E., Toffalini, E., Rogde, K., Nordahl‐Hansen, A., Lervåg, A., Norbury, C. & Melby‐Lervåg, M. (2023) Oral language interventions can improve language outcomes in children with neurodevelopmental disorders: a systematic review and meta‐analysis. Campbell Systematic Reviews, 19(4), e1368. https://doi.org/10.1002/cl2.1368.
Eadie, P., Conway, L., Hallenstein, B., Mensah, F., McKean, C. & Reilly, S. (2018) Quality of life in children with developmental language disorder: quality of life in children with DLD. International Journal of Language & Communication Disorders, 53(4), 799–810. https://doi.org/10.1111/1460‐6984.12385.
Edwards, B. (2014) Growing Up in Australia: the Longitudinal Study of Australian Children: entering adolescence and becoming a young adult. Family Matters, 95, 5–14.
Feltner, C., Wallace, I.F., Nowell, S.W., Orr, C.J., Raffa, B., Middleton, J.C., Vaughan, J., Baker, C., Chou, R. & Kahwati, L. (2024) Screening for speech and language delay and disorders in children 5 years or younger: evidence report and systematic review for the US preventive services task force. JAMA, 331(4), 335. https://doi.org/10.1001/jama.2023.24647.
Gasparini, L., Shepherd, D.A., Bavin, E.L., Eadie, P., Reilly, S., Morgan, A.T. & Wake, M. (2023) Using machine‐learning methods to identify early life predictors of 11‐year language outcome. Journal of Child Psychology & Psychiatry, 64(8), 1242–1252. https://doi.org/10.1111/jcpp.13733.
Gasparini, L., Shepherd, D.A., Lange, K., Wang, J., Verhoef, E., Bavin, E.L., Reilly, S., St Pourcain, B., Wake, M. & Morgan, A.T. (2023) Combining genetic and behavioral predictors of 11‐year language outcome: A multi‐cohort study [Preregistration]. Open Science Framework. https://osf.io/mrxdg/.
Klem, M., Melby‐Lervåg, M., Hagtvet, B., Lyster, S.H., Gustafsson, J. & Hulme, C. (2015) Sentence repetition is a measure of children's language skills rather than working memory limitations. Developmental Science, 18(1), 146–154. https://doi.org/10.1111/desc.12202.
Law, J., Rush, R., Anandan, C., Cox, M. & Wood, R. (2012) Predicting language change between 3 and 5 years and its implications for early identification. Pediatrics, 130(1), e132–e137. https://doi.org/10.1542/peds.2011‐1673.
Lever, J., Krzywinski, M. & Altman, N. (2016) Model selection and overfitting. Nature Methods, 13(9), 703–704. https://doi.org/10.1038/nmeth.3968.
Liaw, A. & Wiener, M. (2002) Classification and regression by RandomForest. R News, 2(3), 18–22.
McGregor, K.K. (2020) How we fail children with developmental language disorder. Language, Speech, and Hearing Services in Schools, 51(4), 981–992. https://doi.org/10.1044/2020_LSHSS‐20‐00003.
McKean, C., Mensah, F.K., Eadie, P., Bavin, E.L., Bretherton, L., Cini, E. & Reilly, S. (2015) Levers for language growth: characteristics and predictors of language trajectories between 4 and 7 years. PLoS ONE, 10(8), e0134251. https://doi.org/10.1371/journal.pone.0134251.
McKean, C., Wraith, D., Eadie, P., Cook, F., Mensah, F. & Reilly, S. (2017) Subgroups in language trajectories from 4 to 11 years: the nature and predictors of stable, improving and decreasing language trajectory groups. Journal of Child Psychology and Psychiatry, 58(10), 1081–1091. https://doi.org/10.1111/jcpp.12790.
Norbury, C.F., Gooch, D., Wray, C., Baird, G., Charman, T., Simonoff, E., Vamvakas, G. & Pickles, A. (2016) The impact of nonverbal ability on prevalence and clinical presentation of language disorder: evidence from a population study. Journal of Child Psychology and Psychiatry, 57(11), 1247–1257. https://doi.org/10.1111/jcpp.12573.
Pearson Education. (2008) Clinical Evaluation of Language Fundamentals–Fourth Edition Technical Report. https://www.pearsonassessments.com/content/dam/school/global/clinical/us/assets/celf‐4/celf‐4‐technical‐report.pdf.
R Core Team. (2020) R: A language and environment for statistical computing (3.6.3) [Computer software]. R Foundation for Statistical Computing. https://www.Rproject.org/.
Reilly, S., McKean, C. & Levickis, P. (2014) Late talking: Can it predict later language difficulties? (Research Snapshot 2; pp. 1–2). Centre for Research Excellence in Child Language. https://www.mcri.edu.au/sites/default/files/media/documents/crec_rs2_late‐talkers‐1_design_v0.1_0.pdf.
Rice, M.L., Hoffman, L. & Wexler, K. (2009) Judgments of omitted BE and DO in questions as extended finiteness clinical markers of specific language impairment (SLI) to 15 years: a study of growth and asymptote. Journal of Speech, Language, and Hearing Research, 52(6), 1417–1433. https://doi.org/10.1044/1092‐4388(2009/08‐0171).
Rock, D.A. & Pollack, J.M. (2002) Early Childhood Longitudinal Study—Kindergarten Class of 1998–99 (ECLS‐K): Psychometric Report for Kindergarten through First Grade. Working Paper Series. (NCES‐WP‐2002‐05; p. 199). National Center for Education Statistics (ED). https://files.eric.ed.gov/fulltext/ED470320.pdf.
RStudio Team. (2020) RStudio: Integrated development environment for R (1.3.959) [Computer software]. RStudio, PBC. http://www.rstudio.com/.
Rudolph, J.M. & Leonard, L.B. (2016) Early Language Milestones and Specific Language Impairment. Journal of Early Intervention, 38(1), 41–58. https://doi.org/10.1177/1053815116633861.
Sansavini, A., Favilla, M.E., Guasti, M.T., Marini, A., Millepiedi, S., Di Martino, M.V., Vecchi, S., Battajon, N., Bertolo, L., Capirci, O., Carretti, B., Colatei, M.P., Frioni, C., Marotta, L., Massa, S., Michelazzo, L., Pecini, C., Piazzalunga, S., Pieretti, M., … & Lorusso, M.L. (2021) Developmental language disorder: early predictors, age for the diagnosis, and diagnostic tools. A scoping review. Brain Sciences, 11(5), 654. https://doi.org/10.3390/brainsci11050654.
Semel, E., Wiig, E.H. & Secord, W.A. (2006) Clinical evaluation of language fundamentals—fourth edition, Australian Standardised Edition, 4th edition. Marrickville, Australia: Harcourt Assessment. https://www.pearsonclinical.com.au/products/view/86.
Smith, J., Wang, J., Grobler, A.C., Lange, K., Clifford, S.A. & Wake, M. (2019) Hearing, speech reception, vocabulary and language: population epidemiology and concordance in Australian children aged 11 to 12 years and their parents. BMJ Open, 9(Suppl 3), 85–94. https://doi.org/10.1136/bmjopen‐2018‐023196.
Stott, C.M., Merricks, M.J., Bolton, P.F. & Goodyer, I.M. (2002) Screening for Speech and Language Disorders: the reliability, validity and accuracy of the General Language Screen. International Journal of Language & Communication Disorders, 37(2), 133–151. https://doi.org/10.1080/13682820110116785.
Strobl, C., Hothorn, T. & Zeileis, A. (2009) Party on! A new, conditional variable‐importance measure for random forests available in the party package. The R Journal, 1(2), 14–17.
Tomblin, J.B., Smith, E. & Zhang, X. (1997) Epidemiology of specific language impairment: prenatal and perinatal risk factors. Journal of Communication Disorders, 30(4), 325–344. https://doi.org/10.1016/S0021‐9924(97)00015‐4.
van der Laan, M.J., Polley, E.C. & Hubbard, A.E. (2007) Super learner. Statistical Applications in Genetics and Molecular Biology, 6(1), Article25. https://doi.org/10.2202/1544‐6115.1309.
von Elm, E., Altman, D.G., Egger, M., Pocock, S.J., Gøtzsche, P.C. & Vandenbroucke, J.P., & for the STROBE initiative. (2007) The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. The Lancet, 370(9596), 1453–1457. https://doi.org/10.1016/S0140‐6736(07)61602‐X.
Wake, M., Tobin, S., Girolametto, L., Ukoumunne, O.C., Gold, L., Levickis, P., Sheehan, J., Goldfeld, S. & Reilly, S. (2011) Outcomes of population based language promotion for slow to talk toddlers at ages 2 and 3 years: let's Learn Language cluster randomised controlled trial. BMJ, 343(Aug 18 2), d4741–d4741. https://doi.org/10.1136/bmj.d4741.
Wallace, I.F., Berkman, N.D., Watson, L.R., Coyne‐Beasley, T., Wood, C.T., Cullen, K. & Lohr, K.N. (2015) Screening for speech and language delay in children 5 years old and younger: a systematic review. Pediatrics, 136(2), e448–e462. https://doi.org/10.1542/peds.2014‐3889.
West, G., Snowling, M.J., Lervåg, A., Buchanan‐Worster, E., Duta, M., Hall, A., McLachlan, H. & Hulme, C. (2021) Early language screening and intervention can be delivered successfully at scale: evidence from a cluster randomized controlled trial. Journal of Child Psychology and Psychiatry, 62(12), 1425–1434. https://doi.org/10.1111/jcpp.13415.
Wiig, E.H., Semel, E. & Secord, W.A. (2013) Clinical evaluation of language fundamentals–fifth edition (CELF‐5). NCS Pearson. https://www.pearsonclinical.com.au/store/auassessments/en/Store/Professional‐Assessments/Speech‐%26‐Language/Clinical‐Evaluation‐of‐Language‐Fundamentals‐Australian‐and‐New‐Zealand‐Fifth‐Edition/p/P100010122.html?tab=product‐details.
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Borovsky, A., Thal, D. & Leonard, L.B. (2021) Moving towards accurate and early prediction of language delay with network science and machine learning approaches. Scientific Reports, 11(1), 8136. https://doi.org/10.1038/s41598‐021‐85982‐0.
Botting, N., Conti‐Ramsden, G. & Faragher, B. (2001) Psycholinguistic Markers for Specific Language Impairment (SLI). The Journal of Child Psychology and Psychiatry and Allied Disciplines, 42(6), 741–748. Cambridge Core. https://doi.org/10.1017/S0021963001007600.
Breiman, L. (2001) Random forests. Machine Learning, 45, 5–32. https://doi.org/10.1023/A:1010933404324.
Calder, S.D., Brennan‐Jones, C.G., Robinson, M., Whitehouse, A. & Hill, E. (2022) The prevalence of and potential risk factors for Developmental Language Disorder at 10 years in the Raine Study. Journal of Paediatrics and Child Health, 16149. https://doi.org/10.1111/jpc.16149.
Clifford, S.A., Davies, S. & Wake, M. (2019) Child Health CheckPoint: cohort summary and methodology of a physical health and biospecimen module for the Longitudinal Study of Australian Children. BMJ Open, 9(Suppl 3), 3–22. https://doi.org/10.1136/bmjopen‐2017‐020261.
Conti‐Ramsden, G. & Durkin, K. (2012) Postschool Educational and Employment Experiences of Young People With Specific Language Impairment. Language, Speech, and Hearing Services in Schools, 43(4), 507–520. https://doi.org/10.1044/0161‐1461(2012/11‐0067).
Council on Children With Disabilities, Section on Developmental Behavioral Pediatrics, Bright Futures Steering Committee, & Medical Home Initiatives for Children with Special Needs Project Advisory Committee. (2006) Identifying infants and young children with developmental disorders in the medical home: an algorithm for developmental surveillance and screening. Pediatrics, 118(1), 405–420. https://doi.org/10.1542/peds.2006‐1231.
Donolato, E., Toffalini, E., Rogde, K., Nordahl‐Hansen, A., Lervåg, A., Norbury, C. & Melby‐Lervåg, M. (2023) Oral language interventions can improve language outcomes in children with neurodevelopmental disorders: a systematic review and meta‐analysis. Campbell Systematic Reviews, 19(4), e1368. https://doi.org/10.1002/cl2.1368.
Eadie, P., Conway, L., Hallenstein, B., Mensah, F., McKean, C. & Reilly, S. (2018) Quality of life in children with developmental language disorder: quality of life in children with DLD. International Journal of Language & Communication Disorders, 53(4), 799–810. https://doi.org/10.1111/1460‐6984.12385.
Edwards, B. (2014) Growing Up in Australia: the Longitudinal Study of Australian Children: entering adolescence and becoming a young adult. Family Matters, 95, 5–14.
Feltner, C., Wallace, I.F., Nowell, S.W., Orr, C.J., Raffa, B., Middleton, J.C., Vaughan, J., Baker, C., Chou, R. & Kahwati, L. (2024) Screening for speech and language delay and disorders in children 5 years or younger: evidence report and systematic review for the US preventive services task force. JAMA, 331(4), 335. https://doi.org/10.1001/jama.2023.24647.
Gasparini, L., Shepherd, D.A., Bavin, E.L., Eadie, P., Reilly, S., Morgan, A.T. & Wake, M. (2023) Using machine‐learning methods to identify early life predictors of 11‐year language outcome. Journal of Child Psychology & Psychiatry, 64(8), 1242–1252. https://doi.org/10.1111/jcpp.13733.
Gasparini, L., Shepherd, D.A., Lange, K., Wang, J., Verhoef, E., Bavin, E.L., Reilly, S., St Pourcain, B., Wake, M. & Morgan, A.T. (2023) Combining genetic and behavioral predictors of 11‐year language outcome: A multi‐cohort study [Preregistration]. Open Science Framework. https://osf.io/mrxdg/.
Klem, M., Melby‐Lervåg, M., Hagtvet, B., Lyster, S.H., Gustafsson, J. & Hulme, C. (2015) Sentence repetition is a measure of children's language skills rather than working memory limitations. Developmental Science, 18(1), 146–154. https://doi.org/10.1111/desc.12202.
Law, J., Rush, R., Anandan, C., Cox, M. & Wood, R. (2012) Predicting language change between 3 and 5 years and its implications for early identification. Pediatrics, 130(1), e132–e137. https://doi.org/10.1542/peds.2011‐1673.
Lever, J., Krzywinski, M. & Altman, N. (2016) Model selection and overfitting. Nature Methods, 13(9), 703–704. https://doi.org/10.1038/nmeth.3968.
Liaw, A. & Wiener, M. (2002) Classification and regression by RandomForest. R News, 2(3), 18–22.
McGregor, K.K. (2020) How we fail children with developmental language disorder. Language, Speech, and Hearing Services in Schools, 51(4), 981–992. https://doi.org/10.1044/2020_LSHSS‐20‐00003.
McKean, C., Mensah, F.K., Eadie, P., Bavin, E.L., Bretherton, L., Cini, E. & Reilly, S. (2015) Levers for language growth: characteristics and predictors of language trajectories between 4 and 7 years. PLoS ONE, 10(8), e0134251. https://doi.org/10.1371/journal.pone.0134251.
McKean, C., Wraith, D., Eadie, P., Cook, F., Mensah, F. & Reilly, S. (2017) Subgroups in language trajectories from 4 to 11 years: the nature and predictors of stable, improving and decreasing language trajectory groups. Journal of Child Psychology and Psychiatry, 58(10), 1081–1091. https://doi.org/10.1111/jcpp.12790.
Norbury, C.F., Gooch, D., Wray, C., Baird, G., Charman, T., Simonoff, E., Vamvakas, G. & Pickles, A. (2016) The impact of nonverbal ability on prevalence and clinical presentation of language disorder: evidence from a population study. Journal of Child Psychology and Psychiatry, 57(11), 1247–1257. https://doi.org/10.1111/jcpp.12573.
Pearson Education. (2008) Clinical Evaluation of Language Fundamentals–Fourth Edition Technical Report. https://www.pearsonassessments.com/content/dam/school/global/clinical/us/assets/celf‐4/celf‐4‐technical‐report.pdf.
R Core Team. (2020) R: A language and environment for statistical computing (3.6.3) [Computer software]. R Foundation for Statistical Computing. https://www.Rproject.org/.
Reilly, S., McKean, C. & Levickis, P. (2014) Late talking: Can it predict later language difficulties? (Research Snapshot 2; pp. 1–2). Centre for Research Excellence in Child Language. https://www.mcri.edu.au/sites/default/files/media/documents/crec_rs2_late‐talkers‐1_design_v0.1_0.pdf.
Rice, M.L., Hoffman, L. & Wexler, K. (2009) Judgments of omitted BE and DO in questions as extended finiteness clinical markers of specific language impairment (SLI) to 15 years: a study of growth and asymptote. Journal of Speech, Language, and Hearing Research, 52(6), 1417–1433. https://doi.org/10.1044/1092‐4388(2009/08‐0171).
Rock, D.A. & Pollack, J.M. (2002) Early Childhood Longitudinal Study—Kindergarten Class of 1998–99 (ECLS‐K): Psychometric Report for Kindergarten through First Grade. Working Paper Series. (NCES‐WP‐2002‐05; p. 199). National Center for Education Statistics (ED). https://files.eric.ed.gov/fulltext/ED470320.pdf.
RStudio Team. (2020) RStudio: Integrated development environment for R (1.3.959) [Computer software]. RStudio, PBC. http://www.rstudio.com/.
Rudolph, J.M. & Leonard, L.B. (2016) Early Language Milestones and Specific Language Impairment. Journal of Early Intervention, 38(1), 41–58. https://doi.org/10.1177/1053815116633861.
Sansavini, A., Favilla, M.E., Guasti, M.T., Marini, A., Millepiedi, S., Di Martino, M.V., Vecchi, S., Battajon, N., Bertolo, L., Capirci, O., Carretti, B., Colatei, M.P., Frioni, C., Marotta, L., Massa, S., Michelazzo, L., Pecini, C., Piazzalunga, S., Pieretti, M., … & Lorusso, M.L. (2021) Developmental language disorder: early predictors, age for the diagnosis, and diagnostic tools. A scoping review. Brain Sciences, 11(5), 654. https://doi.org/10.3390/brainsci11050654.
Semel, E., Wiig, E.H. & Secord, W.A. (2006) Clinical evaluation of language fundamentals—fourth edition, Australian Standardised Edition, 4th edition. Marrickville, Australia: Harcourt Assessment. https://www.pearsonclinical.com.au/products/view/86.
Smith, J., Wang, J., Grobler, A.C., Lange, K., Clifford, S.A. & Wake, M. (2019) Hearing, speech reception, vocabulary and language: population epidemiology and concordance in Australian children aged 11 to 12 years and their parents. BMJ Open, 9(Suppl 3), 85–94. https://doi.org/10.1136/bmjopen‐2018‐023196.
Stott, C.M., Merricks, M.J., Bolton, P.F. & Goodyer, I.M. (2002) Screening for Speech and Language Disorders: the reliability, validity and accuracy of the General Language Screen. International Journal of Language & Communication Disorders, 37(2), 133–151. https://doi.org/10.1080/13682820110116785.
Strobl, C., Hothorn, T. & Zeileis, A. (2009) Party on! A new, conditional variable‐importance measure for random forests available in the party package. The R Journal, 1(2), 14–17.
Tomblin, J.B., Smith, E. & Zhang, X. (1997) Epidemiology of specific language impairment: prenatal and perinatal risk factors. Journal of Communication Disorders, 30(4), 325–344. https://doi.org/10.1016/S0021‐9924(97)00015‐4.
van der Laan, M.J., Polley, E.C. & Hubbard, A.E. (2007) Super learner. Statistical Applications in Genetics and Molecular Biology, 6(1), Article25. https://doi.org/10.2202/1544‐6115.1309.
von Elm, E., Altman, D.G., Egger, M., Pocock, S.J., Gøtzsche, P.C. & Vandenbroucke, J.P., & for the STROBE initiative. (2007) The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. The Lancet, 370(9596), 1453–1457. https://doi.org/10.1016/S0140‐6736(07)61602‐X.
Wake, M., Tobin, S., Girolametto, L., Ukoumunne, O.C., Gold, L., Levickis, P., Sheehan, J., Goldfeld, S. & Reilly, S. (2011) Outcomes of population based language promotion for slow to talk toddlers at ages 2 and 3 years: let's Learn Language cluster randomised controlled trial. BMJ, 343(Aug 18 2), d4741–d4741. https://doi.org/10.1136/bmj.d4741.
Wallace, I.F., Berkman, N.D., Watson, L.R., Coyne‐Beasley, T., Wood, C.T., Cullen, K. & Lohr, K.N. (2015) Screening for speech and language delay in children 5 years old and younger: a systematic review. Pediatrics, 136(2), e448–e462. https://doi.org/10.1542/peds.2014‐3889.
West, G., Snowling, M.J., Lervåg, A., Buchanan‐Worster, E., Duta, M., Hall, A., McLachlan, H. & Hulme, C. (2021) Early language screening and intervention can be delivered successfully at scale: evidence from a cluster randomized controlled trial. Journal of Child Psychology and Psychiatry, 62(12), 1425–1434. https://doi.org/10.1111/jcpp.13415.
Wiig, E.H., Semel, E. & Secord, W.A. (2013) Clinical evaluation of language fundamentals–fifth edition (CELF‐5). NCS Pearson. https://www.pearsonclinical.com.au/store/auassessments/en/Store/Professional‐Assessments/Speech‐%26‐Language/Clinical‐Evaluation‐of‐Language‐Fundamentals‐Australian‐and‐New‐Zealand‐Fifth‐Edition/p/P100010122.html?tab=product‐details.
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Grant Information:
Victorian Government's Operational Infrastructure Support Program; 1195955 NHMRC Investigator grant; MCRI PhD Top Up Scholarship; Australian Government Research Training Program (RTP) Scholarship
Contributed Indexing:
Keywords: SuperLearner; language disorders; longitudinal studies; machine learning; random forests; sensitivity and specificity
Entry Date(s):
Date Created: 20240701 Date Completed: 20241115 Latest Revision: 20241115
Update Code:
20250114
DOI:
10.1111/1460-6984.13086
PMID:
38948964
Database:
MEDLINE
Weitere Informationen
Background: Identifying language disorders earlier can help children receive the support needed to improve developmental outcomes and quality of life. Despite the prevalence and impacts of persistent language disorder, there are surprisingly no robust predictor tools available. This makes it difficult for researchers to recruit young children into early intervention trials, which in turn impedes advances in providing effective early interventions to children who need it.
Aims: To validate externally a predictor set of six variables previously identified to be predictive of language at 11 years of age, using data from the Longitudinal Study of Australian Children (LSAC) birth cohort. Also, to examine whether additional LSAC variables arose as predictive of language outcome.
Methods & Procedures: A total of 5107 children were recruited to LSAC with developmental measures collected from 0 to 3 years. At 11-12 years, children completed the Clinical Evaluation of Language Fundamentals, 4th Edition, Recalling Sentences subtest. We used SuperLearner to estimate the accuracy of six previously identified parent-reported variables from ages 2-3 years in predicting low language (sentence recall score ≥ 1.5 SD below the mean) at 11-12 years. Random forests were used to identify any additional variables predictive of language outcome.
Outcomes & Results: Complete data were available for 523 participants (52.20% girls), 27 (5.16%) of whom had a low language score. The six predictors yielded fair accuracy: 78% sensitivity (95% confidence interval (CI) = [58, 91]) and 71% specificity (95% CI = [67, 75]). These predictors relate to sentence complexity, vocabulary and behaviour. The random forests analysis identified similar predictors.
Conclusions & Implications: We identified an ultra-short set of variables that predicts 11-12-year language outcome with 'fair' accuracy. In one of few replication studies of this scale in the field, these methods have now been conducted across two population-based cohorts, with consistent results. An imminent practical implication of these findings is using these predictors to aid recruitment into early language intervention studies. Future research can continue to refine the accuracy of early predictors to work towards earlier identification in a clinical context.
What This Paper Adds: What is already known on the subject There are no robust predictor sets of child language disorder despite its prevalence and far-reaching impacts. A previous study identified six variables collected at age 2-3 years that predicted 11-12-year language with 75% sensitivity and 81% specificity, which warranted replication in a separate cohort. What this study adds to the existing knowledge We used machine learning methods to identify a set of six questions asked at age 2-3 years with ≥ 71% sensitivity and specificity for predicting low language outcome at 11-12 years, now showing consistent results across two large-scale population-based cohort studies. What are the potential or clinical implications of this work? This predictor set is more accurate than existing feasible methods and can be translated into a low-resource and time-efficient recruitment tool for early language intervention studies, leading to improved clinical service provision for young children likely to have persisting language difficulties.
(© 2024 The Author(s). International Journal of Language & Communication Disorders published by John Wiley & Sons Ltd on behalf of Royal College of Speech and Language Therapists.)