Predictive power of psychometric assessments to identify young learners in need of early intervention: data from the Birth to Twenty Plus Cohort, South Africa
OUTPUT TYPE: Journal Article
PUBLICATION YEAR: 2015
TITLE AUTHOR(S): L.Richter, M.Mabaso, C.Hsiao
KEYWORDS: BIRTH TO TEN NOW BIRTH TO TWENTY (BT20), EARLY CHILDHOOD, PSYCHOMETRIC TESTING
DEPARTMENT: Public Health, Societies and Belonging (HSC)
Print: HSRC Library: shelf number 8931
HANDLE: 20.500.11910/1692
URI: http://hdl.handle.net/20.500.11910/1692
If you would like to obtain a copy of this Research Output, please contact Hanlie Baudin at researchoutputs@hsrc.ac.za.
Abstract
The use of psychometric assessments during early childhood to predict children's later outcomes is vital for early intervention. This study evaluates the predictive power of eight psychometric assessments administered during early childhood as screening measures for identifying those in need of early interventions to prevent late school entry and grade repetition. The measures are the Bayley Scales of Infant Development and the Griffiths Mental Development Scales at 6 months and 1 year; the Vineland Social Maturity Scale and the Behaviour Screening Questionnaire at 2 years and 4 years; the Revised Denver Prescreening Developmental Questionnaire at 5 years; and the Conners' Teacher Rating Scale, the Draw-a-Person, and the Raven's Coloured Progressive Matrices at 7 years. We used receiver operating characteristic curve analysis to examine predictive values of the measures, and the area under the curve to assess sensitivity and specificity. Findings suggest that with a moderate degree of diagnostic accuracy, the Bayley Scales of Infant Development at Year 1 with receiver operating characteristic curve and the Conners' Teacher Rating Scale at Year 7 with receiver operating characteristic curve can be used as screening measures to identify children at risk of late school entry. The Conners' Teacher Rating Scale at Year 7 predicted grade repetition with a moderate degree of accuracy. The only statistically significant covariate-adjusted model showed that young maternal age and low socioeconomic status had a negative influence on the age at school entry as predicted by Bayley Scales of Infant Development at Year 1. This study is the first of its kind in South Africa, and contributes to the conceptual and empirical literature on children's developmental assessment.-
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