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Depression is a common problem for adults on the autism spectrum, but little is known about depression-related service receipt in this group. To understand depression diagnostic and treatment status better, we collected information on current depressive symptoms, depression diagnosis, and treatment status of 315 young adults with a childhood diagnosis of autism from the Simons Foundation Powering Autism Research for Knowledge registry. About two-thirds (65.4%) of the adults had been diagnosed with depression, and 46.7% currently met clinical cut-offs for depression on depressive symptoms measures. Among the currently depressed, the majority (83.0%) had a formal depression diagnosis. Despite being no more likely than males to be currently depressed, females (biological sex) were more likely to have received a depression diagnosis. As for depression treatment, 58.5% of currently depressed adults were currently being treated, and 68% had previously received treatment. Medication was the most common form of treatment, followed by individual therapy. Likelihood of receiving depression treatment was higher among those with a formal depression diagnosis and with higher levels of education. Adults reported several barriers to accessing treatment for depression, including financial and insurance issues, accessibility to appropriate care, and professionals’ lack of understanding about depression in autism. Lay abstract Depression is common among adults on the autism spectrum, but little is known about the extent to which these adults living in the community access diagnostic and treatment services for depression. To address this gap, we surveyed 315 adults on the autism spectrum on depression symptoms, diagnosis, and services. About half of the sample had scores on standard depression measures that suggested they were currently depressed ( n = 147, 46.7%). Among the currently depressed, most of them had received a depression diagnosis from a professional. Depressed females were about 3.5 times more likely than depressed males to have a depression diagnosis. More than half of the currently depressed adults on the autism spectrum reported receiving depression treatment at the time of the study, while about two-thirds had previously received treatment. Those with a depression diagnosis were more likely to have received treatment, and those who had some education beyond high school were more likely to be currently receiving treatment. Financial and insurance issues were the most common barriers that adults reported in accessing treatment for depression.

This study examined COVID-19-related distress among adults with autism spectrum disorder and its associations with demographic and mental health information. A sample of 275 adults (ages 18–35) in the United States, all capable of providing self-reports, was recruited from a large national registry. Adults completed online surveys of mental health symptoms just before COVID-19 was declared a pandemic. Two months later, they completed the same surveys of mental health symptoms, and also reported about distress they had experienced as a result of the COVID-19 pandemic. Nearly two-thirds (65.9%) endorsed some form of COVID-related distress with a little over half reporting any individual form of distress. Although depressive and anxiety symptoms did not change from Time 1 to Time 2 on average, higher levels of COVID-related distress was associated with an increase in depressive and anxiety symptoms between Time 1 and Time 2. In addition, women and those who reported higher anxiety symptoms before the pandemic were more likely to report some form of COVID-related distress. The findings suggest that as this global crisis continues to unfold, it will be critical to ensure that adults with autism spectrum disorder who were experiencing mental health challenges prior to the pandemic receive appropriate monitoring. Lay abstract This study used data collected from 275 adults in the United States with autism spectrum disorder both before the pandemic and then 10 weeks into the pandemic to assess COVID-19-related distress and its impact. Two-thirds of those surveyed reported some type of distress related to the pandemic (i.e. difficulty coping or negative impact on emotional and mental health). While there were no changes in depressive and anxiety symptoms from prior to COVID-19 to 10 week later in the group as a whole, self-reported distress predicted increases in both anxiety and depression across the two timepoints. Furthermore, adults with higher levels of anxiety prior to the pandemic were more likely to report distress, and women were more likely to report a negative impact of the pandemic on their emotional and mental health. Findings highlight the importance of monitoring with adults with autism spectrum disorder to assess their need for mental health support, and providing ongoing support to those who already experience anxiety even before the pandemic.

Objective Social communication deficits associated with autism spectrum disorder (ASD) are commonly represented as a single behavioral domain. However, increased precision of measurement of social communication is needed to promote more nuanced phenotyping, both within the autism spectrum and across diagnostic boundaries. Method A large sample (N = 1,470) of 4- to 10-year-old children was aggregated from across 4 data sources, and then randomly split into testing and validation samples. A total of 57 selected social communication items from 3 widely used autism symptom measures (the Autism Diagnostic Observation Scale [ADOS], Autism Diagnostic Interview−Revised [ADI-R], and Social Responsiveness Scale [SRS]) were analyzed in the multi-trait/multi-method factor analysis framework. The selected model was then confirmed with the validation sample. Results The 4−substantive factor model, with 3 orthogonal method factors, was selected using the testing sample based on fit indices and then confirmed with the validation sample. Two of the factors, “Basic Social Communication Skills” and “Interaction Quality,” were similar to those identified in a previous analysis of the ADOS, Module 3. Two additional factors, “Peer Interaction and Modification of Behavior” and “Social Initiation and Affiliation,” also emerged. Factor scores showed nominal correlations with age and verbal IQ. Conclusion Identification of subdimensions could inform the creation of better conceptual models of social communication impairments, including mapping of how the cascading effects of social communication deficits unfold in ASD versus other disorders. Especially if extended to include both older and younger age cohorts and individuals with more varying developmental levels, these efforts could inform phenotype-based exploration for biological and genetic mechanisms by pinpointing specific mechanisms that contribute to various types of social communication deficits.

Machine learning (ML) models have demonstrated the power of utilizing clinical instruments to provide tools for domain experts in gaining additional insights toward complex clinical diagnoses. In this context these tools desire two additional properties: interpretability, being able to audit and understand the decision function, and robustness, being able to assign the correct label in spite of missing or noisy inputs. This work formulates diagnostic classification as a decision-making process and utilizes Q-learning to build classifiers that meet the aforementioned desired criteria. As an exemplary task, we simulate the process of differentiating Autism Spectrum Disorder from Attention Deficit-Hyperactivity Disorder in verbal school aged children. This application highlights how reinforcement learning frameworks can be utilized to train more robust classifiers by jointly learning to maximize diagnostic accuracy while minimizing the amount of information required.

Currently available treatments for depression show limited effectiveness in adults with autism spectrum disorders (ASD) based on measures of symptom changes and clinician impressions. Perceived helpfulness is another metric that has been found to be useful for understanding treatment outcomes in the general population, but it has not yet been explored in adults with ASD. Thus, the current study collected online survey data to examine patient-perceived treatment helpfulness in a sample of 144 adults with ASD who reported that they were currently receiving community-based treatment for depression. Findings indicate that while there was variability in the levels of perceived helpfulness for both medication and individual therapy, most adults with ASD perceived treatment to be at least moderately helpful. Notably, adults with ASD reported having been in treatment for a prolonged duration (5 to 6 years). Ordinal logistic regression models showed that adults with more depressive symptoms perceived treatments to be less helpful (i.e., medications: odds ratio [OR] = 0.92, 95% confidence interval[CI] = 0.89-0.95; individual therapy: OR = 0.95, 95% CI = 0.92-0.99). Moreover, women perceived medication as more helpful than men (OR = 2.33, 95% CI = 1.13-4.82). Other individual (i.e., age, race, education level) and treatment (i.e., treatment length, concurrent treatment) characteristics were not significantly associated with perceived helpfulness. These findings suggest that future studies may want to use perceived helpfulness, in addition to traditionally used objective outcomes, to understand patients' treatment experience and evaluate depression treatments for adults with ASD. LAY SUMMARY: Adults with autism are much more likely to be depressed than those without autism; therefore, effective depression treatments are necessary to improve mental health outcomes in this group. This online survey study found that most adults with autism felt that the depression treatments they were receiving in the community (i.e., medication and individual therapy) were helpful. Females and those with fewer symptoms of depression felt treatments were more helpful compared with males and those with more symptoms of depression. Our findings suggest that when examining whether treatments for depression are effective, it may be important to measure adults' feelings about the helpfulness of the treatments in addition to measuring changes in symptoms of depression.

UCLA PEERS® for Adolescents is a widely applied program among a number of social skills training programs developed over the years. We synthesized current research evidence on the PEERS program to evaluate the treatment effect on four commonly used outcome measures. 12 studies met inclusion criteria for the review and nine met the criteria for meta-analysis. Results showed moderate to large pooled effects across measures and informants in favor of the PEERS program, with the largest effect seen in social knowledge improvement and the smallest effect in the frequency of get-togethers. The heterogeneity of effects across studies were examined and the limitations of the current evidence were discussed.

Emerging research suggests social attention in autism spectrum disorder (ASD) girls is enhanced relative to ASD boys but may also be affected by the type of social and nonsocial content presented. This study examined how biological sex and gender norms interact to influence visual attention in 79 school-aged children observing scenes that included gender-associated toys and actors of both sexes. Attention to social (faces) and object activity (hands with toys) stimuli was measured. Previously described distinctions between social attention in ASD boys and girls were replicated, with ASD girls looking more at faces than ASD boys. Irrespective of diagnosis, males and females attended more to actors that shared their same sex, and attended more to toys with gender-associations that were consistent with their own sex, suggesting that social and object salience increases for children under sex-consistent conditions. Importantly, ASD and typically developing (TD) children increased their gaze to faces when male actors were shown playing with female-associated toys, suggesting that both groups of children are sensitive to societal messages about the acceptability of males playing with female-associated toys. Our findings provide further evidence of heightened attention to faces in ASD girls relative to ASD boys, and indicate that social attention in ASD and TD children is influenced by who (male or female actor) and what (male- or female-associated toy) is being observed. Collectively, these results present a nuanced profile of attention in ASD that adds to a growing body of research indicating subtle phenotypic differences in ASD girls that may impact identification, assessment, and intervention. Autism Res 2020, 13: 763-776.. © 2019 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: Sex differences observed in typical development may also be present in individuals with autism. In this study, we developed an eye-tracking paradigm featuring videos of boys and girls playing with toys that varied in their gender associations. Attention to faces differed between autistic and non-autistic children but was also influenced by the sex of the actor and gender-association of toys. Autistic females demonstrated subtle attention differences that distinguished them from autistic males and may influence referral, diagnosis, and intervention.

In "The Need for a Clinically Useful Schema of Social Communication," Blank etal. present an observation and coding method (The Initiating, Responding, Expectancy Violations [IREV] schema) for identifying "expectancy violations (EVs)," which may signal clinically significant departures from normal social communication behavior (eg, in individuals with autism spectrum disorder [ASD]).1 The authors point out that "historically, observation of a patient's (social communication) has not been part of the routine psychiatric mental status examination," and argue that this is an important missed opportunity for clinicians. Several direct observation methods exist for identifying and/or monitoring changes in social communication deficits associated with ASD.2 Despite their established diagnostic validity, it remains true that these measures used in isolation will result in a relatively high rate of "false positives"-usually comprising children who are better described with other diagnoses (eg, intellectual disability, language disorder, attention-deficit/hyperactivity disorder [ADHD]).2 This underscores the critical importance of context when interpreting observed social communication deficits.

Although reduced social attention and increased nonsocial attention have been reported in individuals with autism spectrum disorder (ASD), the studies have relied on predominantly male samples and have been underpowered to examine sex differences. These processes may differ for females with ASD, who have been shown to be dissimilar to males in social motivation and nonsocial features, including circumscribed interests (CI). The goal of this study was to compare social and nonsocial visual attention between males and females with ASD on a validated eye-tracking paradigm. Eighty-five school-aged (6-10 years) males and females with and without ASD completed a paired preference task of face and object stimuli (half of which related to common CI). After covarying for chronological and mental age, the presence of concurrently presented CI images reduced prioritization and attention to faces for males more than females, replicating previous findings. ASD females maintained comparable attention patterns to typically developing females, suggesting that previous findings of reduced social attention and increased attention to CI-related objects in autism may be specific to males. These findings are also inconsistent with the "extreme male brain" theory of autism. The more normative orienting and attention to social stimuli for females with ASD may indicate distinct phenotypic characteristics relative to males and possibly serve as a protective effect. Autism Res 2018, 11: 1264-1275. © 2018 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: As autism is more commonly diagnosed in males, less is known about females with autism. Two areas of interest include the interests held by individuals with autism and how socially motivated they are. We used eye tracking as a way to understand these two areas. Our data reveal that elementary school-aged females (6-10 years) with autism attended to faces comparatively to females without autism, suggesting that (1) they were more socially motivated than males with autism and (2) the images of common interests were less motivating to them.

Recent studies suggest that circumscribed interests (CI) in females with Autism Spectrum Disorder (ASD) may align more closely with interests reported in typical female development than those typically reported for ASD males. We used eye-tracking to quantify attention to arrays containing combinations of male, female and neutral images in elementary-aged males and females with and without ASD. A number of condition × sex effects emerged, with both groups attending to images that corresponded with interests typically associated with their biological sex. Diagnostic effects reported in similar studies were not replicated in our modified design. Our findings of more typical attention patterns to gender-typical images in ASD females is consistent with evidence of sex differences in CI and inconsistent with the "Extreme Male Brain" theory of ASD.

Children with autism spectrum disorder (ASD) present with heterogeneous levels of abilities and deficits. The identification of subgroups within a specific age range could be useful for understanding prognosis and treatment planning. We applied Hierarchical Clustering on Principal Components (HCPC) with a sample of 188 preschoolers with ASD and identified three distinct subgroups based on multiple developmental and behavioral domains. Cluster 1 was characterized by relatively high cognitive, language and adaptive abilities, and relatively low levels of social symptoms, repetitive behaviors, and sensory issues within the sample. Cluster 2 was characterized by similarly high cognitive, language and adaptive abilities compared to Cluster 1, but more severe social deficits as well as repetitive and sensory behaviors. Finally, Cluster 3 was characterized by lower cognitive, language and adaptive abilities, and more severe social, repetitive, and sensory symptoms. These findings provide insights into how considering multiple developmental and behavioral domains and core autism symptoms simultaneously can distinguish subgroups of young children with ASD and provide more comprehensive developmental profiles. Moreover, the unique profile of children in Cluster 2 highlighted the usefulness of including different measures and informants when evaluating the abilities and deficits of preschoolers with ASD and the importance of understanding the relationships among different developmental and behavioral factors in this specific population. Autism Res 2020, 13: 796-809. © 2020 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: Children with autism exhibit a range of abilities and deficits in different developmental and behavioral areas, making it difficult to tailor treatment and predict outcomes. We identified three distinct subgroups among 188 preschoolers with autism spectrum disorder distinguished by the combination of measures from multiple developmental and behavioral domains. The findings revealed the importance of comprehensive profiling of the child's abilities and deficits to inform subgrouping within autism.

Background Sleep problems are common in individuals with ASD. This study examined the relationships between bedtime consistency, cognitive functioning, comorbid diagnoses, intervention, demographics and sleep duration in children with ASD. Method Cross-sectional data from 1683 children with ASD in the 2016 and 2017 National Survey of Children's Health were analyzed. The sample was 80 % male, 46 % non-Hispanic white, and mean age was 10.5 (SD 4.1) years. All data were parent report. Multiple linear regression was performed. Results ASD severity was associated with shorter sleep duration, and bedtime consistency was associated with longer sleep duration. Age moderated the effects of both bedtime consistency and ADD/ADHD on sleep duration. Both the positive effect of bedtime consistency and the negative effect of ADD/ADHD on sleep duration became less pronounced with age. Conclusion Although the challenges related to sleep and behavior may differ by age of the child, bedtime consistency could be a good target to improve sleep duration for all children with ASD. Future studies, especially longitudinal studies, on sleep habits and sleep hygiene, in conjunction with other measures of sleep patterns (e.g., night wakings) and correlates of sleep problems, may provide further evidence for the importance of good sleep practices and guide sleep treatment in children with ASD.

Impaired predictive coding has been proposed as a framework to explain discrepancies between expectations and outcomes in autism spectrum disorder (ASD) that may contribute to core symptoms of the disorder. However, no eye tracking study has directly addressed this framework in the context of visual predictions of social and nonsocial stimuli. The current study used eye tracking to examine violations of learned visual associations of both social and nonsocial stimuli. Twenty-six adolescents with ASD and 18 typically developing control (TDC) adolescents completed an outcome expectation eye tracking task in which predictive cues correctly (80% of trials) or incorrectly (20% of trials) indicated the location (left or right) of forthcoming social or nonsocial stimuli. During violation trials, individuals with ASD focused their gaze relatively more often on stimuli presented on locations that violated the learned association and less often on locations that corresponded with the learned association. This finding was not moderated by stimulus type (i.e., social vs. nonsocial). Additionally, participants who looked at incorrectly predicted locations more often had significantly greater ASD symptom severity. These results are consistent with theories that characterize ASD as a disorder of prediction and have potential implications for understanding symptoms related to prediction errors in individuals with ASD. Autism Res 2019, 12: 878-883. © 2019 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: Individuals with autism spectrum disorder (ASD) exhibit impairments making predictions that may impact learning. In this study, we used eye tracking methodology and found that individuals with ASD were less likely to look at the predicted location when a visual routine was violated. This pattern was evident for both social and nonsocial images and was associated with greater ASD symptom severity. These findings provide additional support for predictive challenges in ASD.