Category: Autism Spectrum and Developmental Disorders
Of the increasing number of children identified with an Autism Spectrum Disorder (ASD), the fastest growing sub-group is those without co-occurring intellectual disability (ID; Baio, 2014). Executive Function (EF) problems are a hallmark impairment in ASD linked to key outcomes, such as decreased adaptive ability (Pugliese et al., 2015), co-occurring psychopathology (Lawson et al., 2015; Wallace et al., 2016), decreased job success (Hume, Loftin, & Lantz, 2009), and poorer quality of life (Bishop-Fitzpatrick et al., 2016). Cross-sectional data indicate age-related increases in parent reported EF problems in ASD compared to typically developing children and adolescents (Rosenthal et al., 2013), but we do not yet know how EF changes over time in ASD. This study characterizes longitudinal change in EF in 155 youth with ASD without ID evaluated on multiple occasions using the parent report Behavior Rating Inventory of Executive Function (BRIEF).
Participants were 151 children and adolescents (28 females) assessed at 358 time points between the ages of 6 and 17 at their first BRIEF evaluation (M = 9.37 years, SD = 3.21) and 6 to 24 at their last BRIEF administration (M = 13.46 years, SD = 3.65). Participants were evaluated on multiple occasions (M = 2.37 occasions, SD = 0.88) separated by at least 6 months (M = 2.13 years, SD = 1.82). Trained and experienced clinicians diagnosed all participants with ASD using DSM-5 criteria. All participants met criteria established by the NICHD/NIDCD Collaborative Programs for Excellence in Autism (Lainhart et al., 2006) using the Autism Diagnostic Interview and/or the Autism Diagnostic Observation Schedule. All participants possessed a full scale/verbal IQ estimate at or above 70.
Multilevel models nested within participants were used to examine the linear effect of age on BRIEF scores. The time observations were based on age and centered such that 0 corresponded to the first observation. Models were built sequentially and tested for improvement in model fit (change in -2*log likelihood). Global EF problems resulted in a fixed quadratic random linear model (fixed linear time (FLT) p>0.05 and random linear time (RLT) and fixed quadratic time (FQT) p.05; FQT p.05; RLT p.05) showed that problems did not change over time and remained elevated across development. Analysis for this abstract is ongoing and will include adult versions of the BRIEF to increase observations, therefore, results may change. Longitudinal modeling of executive function can inform clinicians of skills to target during treatment at critical developmental periods.
Cara Pugliese– Children's National Health System
Alaina Pearce– Georgetown University
Mary Skapek– Children's National Health System
Anna Armour– Children's National Health System
Meghan Collins– National Institute of Mental Health
Jason Crutcher– National Institute of Mental Health
Alex Martin– National Insitute of Mental Health
Wallace Gregory– The George Washington University
Laura Anthony– Associate Professor, Children's National Health System, Rockville, Maryland
Lauren Kenworthy– Associate Professor, Children's National Health System, Rockville, Maryland