Classifying and characterizing the development of adaptive behavior in a naturalistic longitudinal study of young children with autism

Abstract

Background: Adaptive behavior, or the ability to function independently in ones' environment, is a key phenotypic construct in autism spectrum disorder (ASD). Few studies of the development of adaptive behavior during preschool to school-age are available, though existing data demonstrate that the degree of ability and impairment associated with ASD, and how it manifests over time, is heterogeneous. Growth mixture models are a statistical technique that can help parse this heterogeneity in trajectories.

Methods: Data from an accelerated longitudinal natural history study (n = 105 children with ASD) were subjected to growth mixture model analysis. Children were assessed up to four times between the ages of 3 to 7.99 years.

Results: The best fitting model comprised two classes of trajectory on the Adaptive Behavior Composite score of the Vineland Adaptive Behavior Scale, Second Edition-a low and decreasing trajectory (73% of the sample) and a moderate and stable class (27%).

Conclusions: These results partially replicate the classes observed in a previous study of a similarly characterized sample, suggesting that developmental trajectory may indeed serve as a phenotype. Further, the ability to predict which trajectory a child is likely to follow will be useful in planning for clinical trials.

Keywords: Adaptive behavior; Autism spectrum disorders; Longitudinal studies.

Fig. 1

Final GMM solution. a The estimated proportion of class membership was 73% for class 1 and 27% for class 2. The slope and quadratic terms were significant for class 1, but not for class 2 (see Additional file 1: Table S2 for parameter estimates). The trajectories observed by Szatmari et al. [30], by modal class assignment, are superimposed with dotted lines. b Observed ABC scores by most likely class assignment

Fig. 2

Phenotypic data over time, by most likely class assignment. Mean (95% confidence interval) scores on cognitive tests, ADOS CSS, and CBCL are shown for each class. Most-likely assignment was class 1 for 76% of the sample and class 2 for 24%. Sample size for each age cohort varies (see Additional file 1: Table S4)