20448
Examining Factors Associated with Trajectories of Daily Living Skills in Preschool Children with ASD in Canada
Objectives: To examine the association of child and contextual factors associated with the developmental trajectories of personal care skills throughout the preschool years of children with ASD.
Methods: Longitudinal data were obtained from an inception cohort of 319 children across 5 Canadian sites and ascertained at diagnosis (from 2-4 years of age). Data were collected at 4 time points; baseline(T1), 6(T2) and 12(T3) months post-diagnosis, and at 6 years of age(T4). Child-level data at T1 included demographics, ADOS severity, and Problem Behaviors (Aberrant Behavior Checklist). A categorical variable was derived using the Merrill-Palmer-Revised (MPR) to identify groups with higher (>70) or lower (<70) intellectual ability. Contextual-level data included parent-informant measures related to demographics and stress (Parenting Stress Index and Symptom Checklist-90-Revised), as well as community-level data (i.e., site and T1 services). The dependent variable, the Vineland Adaptive Behavior Scales, 2nd ed. Personal Skills [PS] (raw score), was measured at each of T1 to T4.
Descriptive statistics and multi-level modeling (MLM) analyses were conducted. MLM model testing involved a “Step-up” approach, i.e., increasing the complexity of subsequent models by adding child and contextual variables in blocks. To determine if variables were associated with the PS trajectory, evidence for goodness of model fit was examined using the Bayesian information criterion (BIC).
Results: Sample description (mean [standard deviation]): Age of ASD diagnosis (38.4[8.5] months); ADOS severity score (7.6[1.7]) at T1; 84% were male; 72% had an MPR Developmental Index standard score <70 at T1; and 62% (MPR <70) and 25% (MPR >70) received Specialized ASD services at T1. PS raw score means [SD] over time were T1 (24[11.3]), T2 (32[12.9]), T3 (38[13.1]), and T4 (51[11.8]). Based on the intercept only model, 70% and 30% of the variance in PS raw scores could be attributed to differences between and within participants, respectively. Adding the child-level variables improved the model; however, incorporating parent- and community-level variables in blocks worsened the model fit. The only variables significantly associated with the PS trajectory were MPR (slope coeff=-0.400, SE=.16, p=0.011; quadratic coeff=.005, SE=.002, p=.018), and Age of diagnosis (intercept coeff=-0.329, SE=.17, p=0.048). Note that the mean baseline levels of PS did not differ significantly between MPR groups.
Conclusions: Child-level variables were associated with influencing PS trajectories, something that context-level variables were unable to demonstrate. Earlier diagnosis and lower intellectual ability were associated with a poorer rate of personal skill growth over time. In this sample, more participants with MPR (<70) had early specialized ASD services likely due to higher severity. These results are similar to findings from a sample of US preschool children with ASD. Next steps will explore other contextual factors potentially associated with personal skill trajectories (e.g., birth order or later preschool services).