Literature DB >> 25138105

Misclassification due to age grouping in measures of child development.

Scott Veldhuizen1, Christine Rodriguez2, Terrance J Wade3, John Cairney4.   

Abstract

PURPOSE: Screens for developmental delay generally provide a set of norms for different age groups. Development varies continuously with age, however, and applying a single criterion for an age range will inevitably produce misclassifications. In this report, we estimate the resulting error rate for one example: the cognitive subscale of the Bayley Scales of Infant and Toddler Development (BSID-III).
DESIGN: Data come from a general population sample of 594 children (305 male) aged 1 month to 42.5 months who received the BSID-III as part of a validation study. We used regression models to estimate the mean and variance of the cognitive subscale as a function of age. We then used these results to generate a dataset of one million simulated participants and compared their status before and after division into age groups. Finally, we applied broader age bands used in two other instruments and explored likely validity limitations when different instruments are compared.
RESULTS: When BSID-III age groups are used, 15% of cases are missed and 15% of apparent cases are false positives. Wider age groups produced error rates from 27% to 46%. Comparison of different age groups suggests that sensitivity in validation studies would be limited, under certain assumptions, to 70% or less. IMPLICATIONS: The use of age groups produces a large number of misclassifications. Although affected children will usually be close to the threshold, this may lead to misreferrals. Results may help to explain the poor measured agreement of development screens. Scoring methods that treat child age as continuous would improve instrument accuracy. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Entities:  

Keywords:  Measurement; Neurodevelopment; Screening

Mesh:

Year:  2014        PMID: 25138105     DOI: 10.1136/archdischild-2014-306548

Source DB:  PubMed          Journal:  Arch Dis Child        ISSN: 0003-9888            Impact factor:   3.791


  2 in total

1.  Validation and adaptation of rapid neurodevelopmental assessment instrument for infants in Guatemala.

Authors:  L Thompson; R A Peñaloza; K Stormfields; R Kooistra; G Valencia-Moscoso; H Muslima; N Z Khan
Journal:  Child Care Health Dev       Date:  2015-08-06       Impact factor: 2.508

2.  Prediction of childhood brain outcomes in infants born preterm using neonatal MRI and concurrent clinical biomarkers (PREBO-6): study protocol for a prospective cohort study.

Authors:  Joanne M George; Alex M Pagnozzi; Samudragupta Bora; Roslyn N Boyd; Paul B Colditz; Stephen E Rose; Robert S Ware; Kerstin Pannek; Jane E Bursle; Jurgen Fripp; Karen Barlow; Kartik Iyer; Shaneen J Leishman; Rebecca L Jendra
Journal:  BMJ Open       Date:  2020-05-12       Impact factor: 2.692

  2 in total

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