Usual care for youth with autism spectrum disorder: Community-based providers’ reported familiarity with treatment practices

ObjectiveTo examine patterns and predictors of familiarity with transdisciplinary psychosocial (e.g., non-pharmacologic) practices for practitioners treating youths with autism spectrum disorder (ASD) in the United States.MethodPractitioners (n = 701) from behavioral, education, medical, and mental health backgrounds who worked with youth (ages 7–22) with ASD completed the Usual Care for Autism Survey, which assessed provider demographics and self-reported familiarity with transdisciplinary treatment practices for the most common referral problems of ASD. We examined relations between provider-, setting-, and client-level characteristics with familiarity of key groups of the treatment practices (practice sets). Practice sets were identified using exploratory factor analysis (EFA), and demographic predictors of practice subsets were examined using generalized estimating equations (GEE).ResultsThe EFA yielded a three-factor solution: (1) environmental modifications/antecedent strategies; (2) behavior analytic strategies; and (3) cognitive strategies, with overall familiarity ranked in this order. Medical providers indicated the least familiarity across disciplines. More experience with ASD and treating those with intellectual disabilities predicted greater familiarity with only environmental modifications/antecedent strategies and behavior analytic, but not cognitive strategies. Experience treating low SES clients predicted familiarity with environmental modification and behavior analytic strategies while experience treating high SES clients predicted familiarity with behavior analytic and cognitive strategies.ConclusionThis is the first study to identify transdisciplinary, interpretable sets of practices for treating youth with ASD based on community providers’ reported familiarity. Results highlight factors associated with familiarity with practice sets, which is essential for mapping practice availability, and optimizing training and dissemination efforts for youth with ASD

Resting state EEG in youth with ASD: age, sex, and relation to phenotype

Background Identification of ASD biomarkers is a key priority for understanding etiology, facilitating early diagnosis, monitoring developmental trajectories, and targeting treatment efforts. Efforts have included exploration of resting state encephalography (EEG), which has a variety of relevant neurodevelopmental correlates and can be collected with minimal burden. However, EEG biomarkers may not be equally valid across the autism spectrum, as ASD is strikingly heterogeneous and individual differences may moderate EEG-behavior associations. Biological sex is a particularly important potential moderator, as females with ASD appear to differ from males with ASD in important ways that may influence biomarker accuracy. Methods We examined effects of biological sex, age, and ASD diagnosis on resting state EEG among a large, sex-balanced sample of youth with (N = 142, 43% female) and without (N = 138, 49% female) ASD collected across four research sites. Absolute power was extracted across five frequency bands and nine brain regions, and effects of sex, age, and diagnosis were analyzed using mixed-effects linear regression models. Exploratory partial correlations were computed to examine EEG-behavior associations in ASD, with emphasis on possible sex differences in associations. Results Decreased EEG power across multiple frequencies was associated with female sex and older age. Youth with ASD displayed decreased alpha power relative to peers without ASD, suggesting increased neural activation during rest. Associations between EEG and behavior varied by sex. Whereas power across various frequencies correlated with social skills, nonverbal IQ, and repetitive behavior for males with ASD, no such associations were observed for females with ASD. Conclusions Research using EEG as a possible ASD biomarker must consider individual differences among participants, as these features influence baseline EEG measures and moderate associations between EEG and important behavioral outcomes. Failure to consider factors such as biological sex in such research risks defining biomarkers that misrepresent females with ASD, hindering understanding of the neurobiology, development, and intervention response of this important population

Do Biological Sex and Early Developmental Milestones Predict the Age of First Concerns and Eventual Diagnosis in Autism Spectrum Disorder?

Despite advances in early detection, the average age of autism spectrum disorder (ASD) diagnosis exceeds 4 years and is often later in females. In typical development, biological sex predicts inter-individual variation across multiple developmental milestones, with females often exhibiting earlier progression. The goal of this study was to examine sex differences in caregiver-reported developmental milestones (first word, phrase, walking) and their contribution to timing of initial concerns expressed by caregivers and eventual age of diagnosis. 195 (105 males) children and adolescents aged 8 to 17 years with a clinical diagnosis of ASD were recruited to the study (mean IQ = 99.76). While developmental milestones did not predict timing of diagnosis or age parents first expressed concerns, females had earlier first words and phrases than males. There was a marginal difference in the age of diagnosis, with females receiving their diagnosis 1 year later than males. Despite sex differences in developmental milestones and diagnostic variables, IQ was the most significant predictor in the timing of initial concerns and eventual diagnosis, suggesting children with lower IQ, regardless of sex, are identified and diagnosed earlier. Overall, biological sex and developmental milestones did not account for a large proportion of variance for the eventual age of ASD diagnosis, suggesting other factors (such as IQ and the timing of initial concerns) are potentially more influential. LAY SUMMARY: In this study, a later age of diagnosis in females having ASD was confirmed; however, biological sex was not the stronger predictor of age of diagnosis. Parents reported that females learned language more quickly than males, and parents noted their first concerns when females were older than males. In this sample, the strongest predictor of age of diagnosis was the age of first concerns

Impact of autism genetic risk on brain connectivity: a mechanism for the female protective effect.

The biological mechanisms underlying the greater prevalence of autism spectrum disorder in males than females remain poorly understood. One hypothesis posits that this female protective effect arises from genetic load for autism spectrum disorder differentially impacting male and female brains. To test this hypothesis, we investigated the impact of cumulative genetic risk for autism spectrum disorder on functional brain connectivity in a balanced sample of boys and girls with autism spectrum disorder and typically developing boys and girls (127 youth, ages 8-17). Brain connectivity analyses focused on the salience network, a core intrinsic functional connectivity network which has previously been implicated in autism spectrum disorder. The effects of polygenic risk on salience network functional connectivity were significantly modulated by participant sex, with genetic load for autism spectrum disorder influencing functional connectivity in boys with and without autism spectrum disorder but not girls. These findings support the hypothesis that autism spectrum disorder risk genes interact with sex differential processes, thereby contributing to the male bias in autism prevalence and proposing an underlying neurobiological mechanism for the female protective effect