RESUMO
In order to provide more individualized support, it is imperative to further understand the effectiveness of different types of psychotherapy on the clinical areas of need common in autistic youth (Wood et al. in Behav Ther 46:83-95, 2015). Randomized controlled trials of psychotherapy for autistic youth were included if published in English, included random assignment to treatment or control group, required a previous diagnosis of autism, had a mean age of 6-17 years, and provided outcome measure data from both intervention and control groups. A total of 133 measures were coded across 29 studies and included 1464 participants with a mean age of 10.39 years (1.89). A small mean effect size (0.38,95% CI [0.26, 0.47]) was found overall, with the largest effects for cognitive behavioral therapies on autism-related clinical needs (0.81) and overall mental health (0.78). The results show the significant impact of psychotherapy interventions for autistic youth. Additional research should further assess the details of the most effective psychotherapies for each area of clinical need.
RESUMO
BACKGROUND: Intellectual disability affects approximately one third of individuals with autism spectrum disorder (autism). Yet, a major unresolved neurobiological question is what differentiates autistic individuals with and without intellectual disability. Intelligence quotients (IQs) are highly variable during childhood. We previously identified three subgroups of autistic children with different trajectories of intellectual development from early (2-3½ years) to middle childhood (9-12 years): (a) persistently high: individuals whose IQs remained in the normal range; (b) persistently low: individuals whose IQs remained in the range of intellectual disability (IQ < 70); and (c) changers: individuals whose IQs began in the range of intellectual disability but increased to the normal IQ range. The frontoparietal (FPN) and default mode (DMN) networks have established links to intellectual functioning. Here, we tested whether brain regions within the FPN and DMN differed volumetrically between these IQ trajectory groups in early childhood. METHODS: We conducted multivariate distance matrix regression to examine the brain regions within the FPN (11 regions x 2 hemispheres) and the DMN (12 regions x 2 hemispheres) in 48 persistently high (18 female), 108 persistently low (32 female), and 109 changers (39 female) using structural MRI acquired at baseline. FPN and DMN regions were defined using networks identified in Smith et al. (Proc Natl Acad Sci U S A 106:13040-5, 2009). IQ trajectory groups were defined by IQ measurements from up to three time points spanning early to middle childhood (mean age time 1: 3.2 years; time 2: 5.4 years; time 3: 11.3 years). RESULTS: The changers group exhibited volumetric differences in the DMN compared to both the persistently low and persistently high groups at time 1. However, the persistently high group did not differ from the persistently low group, suggesting that DMN structure may be an early predictor for change in IQ trajectory. In contrast, the persistently high group exhibited differences in the FPN compared to both the persistently low and changers groups, suggesting differences related more to concurrent IQ and the absence of intellectual disability. CONCLUSIONS: Within autism, volumetric differences of brain regions within the DMN in early childhood may differentiate individuals with persistently low IQ from those with low IQ that improves through childhood. Structural differences in brain networks between these three IQ-based subgroups highlight distinct neural underpinnings of these autism sub-phenotypes.