Cross-sectional and longitudinal assessment of cognitive development in Williams syndromeFarran, E. K., Purser, H. R. M., Jarrold, C., Thomas, M. S. C., Scerif, G., Stojanovik, V. ORCID: https://orcid.org/0000-0001-6791-9968 and Van Herwegen, J. (2023) Cross-sectional and longitudinal assessment of cognitive development in Williams syndrome. Developmental Science, 27 (1). e13421. ISSN 1467-7687
It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing. To link to this item DOI: 10.1111/desc.13421 Abstract/SummaryWilliams syndrome (WS) is a rare genetic syndrome. As with all rare syndromes, obtaining adequately powered sample sizes is a challenge. Here we present legacy data from seven UK labs, enabling the characterisation of cross-sectional and longitudinal developmental trajectories of verbal and non-verbal development in the largest sample of individuals with WS to-date. In Study 1, we report cross-sectional data from between N=102 and N=209 children and adults with WS on measures of verbal and non-verbal ability. In Study 2, we report longitudinal data from N=17 to N=54 children and adults with WS who had been tested on at least three timepoints on these measures. Data support the WS characteristic cognitive profile of stronger verbal than non-verbal ability, and shallow developmental progression for both domains. Both cross-sectional and longitudinal data demonstrate steeper rates of development in the child participants than the adolescent and adults in our sample. Cross-sectional data indicate steeper development in verbal than non-verbal ability, and that individual differences in the discrepancy between verbal and non-verbal ability are largely accounted for by level of intellectual functioning. A diverging developmental discrepancy between verbal and non-verbal ability, whilst marginal, is not mirrored statistically in the longitudinal data. Cross-sectional and longitudinal data are discussed with reference to validating cross-sectional developmental patterns using longitudinal data and the importance of individual differences in understanding developmental progression.
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