7 research outputs found
Scatterplot of the relationship between Language Z score at 4 years (intercept) and rate of change in Language Z scores per year from 4–7 years (slope).
<p>Scatterplot of the relationship between Language Z score at 4 years (intercept) and rate of change in Language Z scores per year from 4–7 years (slope).</p
Multivariate growth trajectory models 1, 2 and 3: variance components for Mean CELF scaled standard score at 4 years (intercept) Growth rate per year 4–7 years (slope) and Pseudo R<sup>2</sup>.
<p>Multivariate growth trajectory models 1, 2 and 3: variance components for Mean CELF scaled standard score at 4 years (intercept) Growth rate per year 4–7 years (slope) and Pseudo R<sup>2</sup>.</p
Least-mutable predictors: measures, age of measurement, derivation and criteria and evidence for categorisation.
<p>Key to Criteria: 1) cannot be modified through intervention as the factor is biologically driven; 2) comorbid diagnoses such as ADHD, ASD or Learning Disability whose symptoms can be ameliorated to a degree but which cannot be removed entirely; and 4) it would be unethical or impracticable to target in an intervention.</p><p>*presented only where criteria for assignment to ‘least mutable’ category is number 3) evidence of limited responsiveness to intervention</p><p><sup>a</sup> KBIT-2—Kaufman, A. S., and N. L. Kaufman. (2004). <i>Kaufman Brief Intelligence Test</i>. <i>2nd ed</i>. Bloomington, MN: Pearson;</p><p><sup>b</sup>ATS—Prior, M., Sanson, A., & Oberklaid, F. (1989). The Australian temperament project. In G. Kohnstamm, J. Bates, &M. Rothbart (Eds.), <i>Temperament in childhood</i> (pp. 537–554). Chichester: Wiley</p><p>Least-mutable predictors: measures, age of measurement, derivation and criteria and evidence for categorisation.</p
Mutable-proximal predictors: measures, age of measurement, derivation and evidence for potential to be modified through intervention.
<p><sup>a</sup>SDQ—Goodman, R. (1997). The Strengths and Difficulties Questionnaire: a research note. <i>Journal of Child Psychology and Psychiatry</i>, <i>38</i>, 581–586;</p><p><sup>b</sup>GFTA—Goldman R, Fristoe M. (2000) <i>Goldman-Fristoe Test of Articulation 2</i>. <i>2nd edn</i>. Circle Pines, MN: American Guidance Service</p><p>Mutable-proximal predictors: measures, age of measurement, derivation and evidence for potential to be modified through intervention.</p
Mutable-distal predictors: measures, age of measurement, and derivation.
<p><sup>a</sup>Australian Bureau of Statistics. (2001). <i>Socio-Economic Indexes for Areas</i>. Canberra: Australian Bureau of Statistics.</p><p><sup>b</sup>MHVS Raven, J., Raven, J. C. and Court. J. H. (1998). Manual for Raven’s Progressive Matrices and Vocabulary Scales. Section 5: The Mill Hill Vocabulary Scale. San Antonio, TX: Harcourt Assessment;</p><p><sup>c</sup>WRAT—Wilkinson, G. S., and Robertson, G. J. (2006) <i>The Wide Range Achievement Test-4th edition</i> Lutz, FL: Psychological Assessment Resources</p><p>Mutable-distal predictors: measures, age of measurement, and derivation.</p
Random sample of ‘empirical growth’ plots—Individual OLS trajectories for 1 child in 10 (N = 83).
<p>Random sample of ‘empirical growth’ plots—Individual OLS trajectories for 1 child in 10 (N = 83).</p
Editorial Perspective: Maximising the benefits of intervention research for children and young people with developmental language disorder (DLD) – a call for international consensus on standards of reporting in intervention studies for children with and at risk for DLD
Developmental language disorder (DLD) is one of the most prevalent neurodevelopmental disorders (~8% at 5–6 years) with significant implications for the child or young person’s daily life and risks of substantial negative consequences for health, edu?cation, employment, well-being and social inclusion across the life course (Dubois, St-Pierre, Desmarais, & Guay, 2020; Eadie et al., 2021; McKean et al., 2017). </p