Using generalizability theory to evaluate the comparative reliability of developmental measures in neurogenetic syndrome and low-risk populations.

backgroundThe lack of available measures that can reliably characterize early developmental skills in children with neurogenetic syndromes (NGS) poses a significant challenge for research on early development in these populations. Although syndrome-specific measures may sometimes be necessary, a more cost- and time-efficient solution would be to identify existing measures that are appropriate for use in special populations or optimize existing measures to be used in these groups. Reliability is an important metric of psychometric rigor to consider when auditing and optimizing assessment tools for NGS. In this study, we use Generalizability Theory, an extension of classical test theory, as a novel approach for more comprehensively characterizing the reliability of existing measures and making decisions about their use in the field of NGS research.

methodsWe conducted generalizability analyses on a popular early social communication screener, the Communication and Symbolic Behavior Scales-Infant-Toddler Checklist (CSBS-ITC), collected on 172 children (41 Angelman syndrome, 30 Prader-Willi syndrome, 42 Williams syndrome, 59 low-risk controls).

resultsOverall, the CSBS-ITC demonstrated at least adequate reliability in the NGS groups included in this study, particularly for the Prader-Willi and Williams syndrome groups. However, the sources of systematic error variance in the CSBS-ITC varied greatly between the low-risk control and NGS groups. Moreover, as unassessed in previous research, the CSBS-ITC demonstrated substantial differences in variance sources among the NGS groups. Reliability of CSBS-ITC scores was highest when averaging across all measurement points for a given child and was generally similar or better in the NGS groups compared to the low-risk control group.

conclusionsOur findings suggest that the CSBS-ITC communicates different information about the reliability of stability versus change, in low-risk control and NGS samples, respectively, and that psychometric approaches like Generalizability Theory can provide more complete information about the reliability of existing measures and inform decisions about how measures are used in research on early development in NGS.