Issues of COVID-19-related distance learning for children with neuronopathic mucopolysaccharidoses.

The COVID-19 pandemic has impacted the education of children around the world, forcing a large proportion of teaching to be carried out remotely. The implications of this disruption have yet to be fully elucidated, but initial assessments suggest that COVID-19-related school closures and reliance on virtual learning may have a long-term negative impact on educational attainment and future earnings as well as life expectancy of children in the United States. Among children with neurodegenerative disorders, such as neuronopathic mucopolysaccharidoses (MPS disorders), the effects of the pandemic are likely to be even greater. We aim to shine a spotlight on the impact of COVID-19 on the education, treatment and general wellbeing of children and families affected by MPS disorders by highlighting the important role that educators and therapists play in supporting the neurocognitive function and quality of life of children with neuronopathic MPS disorders. This article will serve as a resource that caregivers, educators, clinicians and therapists can use when considering how best to advocate for children with neuronopathic MPS disorders in circumstances where in-school teaching or in-clinic treatment is compromised or not possible. Given that the current pandemic is likely to have a prolonged course and impact and that similar epidemics and pandemics are a near certainty in the future, it is essential that steps are taken to support the learning and care of children with neuronopathic MPS disorders. We must prioritize strategies to safely resume this fragile community's access to in-person education and supportive care, and to address gaps that have emerged during prolonged pauses in access, whenever possible.

Sex differences in scores on standardized measures of autism symptoms: a multisite integrative data analysis.

BACKGROUND: Concerns have been raised that scores on standard measures of autism spectrum disorder (ASD) symptoms may differ as a function of sex. However, these findings are hindered by small female samples studied thus far. The current study evaluated if, after accounting for age, IQ, and language level, sex affects ASD severity estimates from diagnostic measures among children with ASD. METHODS: Data were obtained from eight sources comprising 27 sites. Linear mixed-effects models, including a random effect for site, were fit for 10 outcomes (Autism Diagnostic Observation Schedule [ADOS] domain-level calibrated severity scores, Autism Diagnostic Interview-Revised [ADI-R] raw scores by age-based algorithm, and raw scores from the two indices on the Social Responsiveness Scale [SRS]). Sex was added to the models after controlling for age, NVIQ, and an indicator for language level. RESULTS: Sex significantly improved model fit for half of the outcomes, but least square mean differences were generally negligible (effect sizes [ES] < 0.20), increasing to small to moderate in adolescence (ES < 0.40). Boys received more severe RRB scores than girls on both the ADOS and ADI-R (age 4 + algorithm), and girls received more severe scores than boys on both SRS indices, which emerged in adolescence. CONCLUSIONS: This study combined several available databases to create the largest sample of girls with ASD diagnoses. We found minimal differences due to sex beyond other known influences on ASD severity indicators. This may suggest that, among children who ultimately receive a clinical ASD diagnosis, severity estimates do not systematically differ to such an extent that sex-specific scoring procedures would be necessary. However, given the limitations inherent in clinically ascertained samples, future research must address questions about systematic sex differences among children or adults who do not receive clinical diagnoses of ASD. Moreover, while the current study helps resolve questions about widely used diagnostic instruments, we could not address sex differences in phenotypic aspects outside of these scores.

The Intersection of Systemic, Child, and Evaluation Factors in the Prediction of Autism Special Education Eligibility; Examining the Role of Race and Ethnicity.

Though there is evidence autism identification has been inequitable for populations who are culturally and linguistically minoritized, there is limited research that explains the issue of disproportionality and factors contributing to its occurrence, especially within an educational setting. To explore contributors to racial/ethnic disparities in autism special education eligibility, the current investigation evaluated child and evaluation characteristics as they relate to the absence of autism eligibility. Data were obtained from the Autism and Developmental Disabilities Monitoring (ADDM) Network Study and included children with behavioral characteristics consistent with autism and educational evaluation records. Despite documented characteristics consistent with autism, only 72% of the sample received educational services under autism eligibility. To characterize children without autism eligibility, hierarchical logistic regression was used to evaluate factors documented in evaluation records predicting the absence of autism eligibility. Factors influencing autism eligibility included behavioral characteristics documented, evaluation components completed, intellectual ability, and clinical diagnoses present. There was no unique contribution of race/ethnicity in predicting the absence of autism eligibility when accounting for these previous predictors, but many of these predictors differed by racial/ethnic group. Disproportionality in autism may be the manifestation of inequitable evaluation experiences, including experiencing less comprehensive evaluations, and not receiving an autism specific assessment. Though race/ethnicity did not uniquely contribute to the absence of autism eligibility above and beyond those combined factors, it is important to evaluate and reduce inequities experienced within the autism identification process for populations who are culturally and linguistically minoritized.

Why are only some children with autism spectrum disorder misclassified by the social communication questionnaire? An empirical investigation of individual differences in sensitivity and specificity in a clinic-referred sample.

BACKGROUND: The Social Communication Questionnaire (SCQ) is a checklist for autism spectrum disorder (ASD) commonly used in research and clinical practice. While the original validation study suggested that the SCQ was an accurate ASD screener with satisfactory sensitivity and specificity, subsequent studies have yielded mixed results, with some revealing low sensitivity, low specificity, and low utility in some settings. METHOD: The present study examined the psychometric properties of the SCQ as well as the individual difference characteristics of 187 individuals with and without autism spectrum disorder (ASD) who were misclassified or accurately classified by the SCQ in a clinic-referred sample. RESULTS: The SCQ showed suboptimal sensitivity and specificity, regardless of age and sex. Compared to true positives, individuals classified as false positives displayed greater externalizing and internalizing problems, whereas individuals classified as false negatives displayed better social communication and adaptive skills. CONCLUSIONS: The findings suggest that non-autistic developmental and behavioral individual difference characteristics may explain high rates of misclassification using the SCQ. Clinicians and researchers could consider using the SCQ in combination with other tools for young children with internalizing and externalizing symptoms and other more complex clinical presentations.

Patterns of Special Education Eligibility and Age of First Autism Spectrum Disorder (ASD) Identification Among US Children with ASD.

The study examined timing of autism spectrum disorder (ASD) identification in education versus health settings for 8-year-old children with ASD identified through records-based surveillance. The study also examined type of ASD symptoms noted within special education evaluations. Results indicated that children with records from only education sources had a median time to identification of ASD over a year later than children with records from health sources. Black children were more likely than White children to have records from only education sources. Restricted and repetitive behaviors were less frequently documented in educational evaluations resulting in developmental delay eligibility compared to specific ASD eligibility among children with ASD. Future research could explore strategies reduce age of identification in educational settings and increase equitable access to health evaluations.

Agreement of parent-reported cognitive level with standardized measures among children with autism spectrum disorder.

Assessing cognitive development is critical in clinical research of autism spectrum disorder (ASD). However, collecting cognitive data from clinically administered assessments can add a significant burden to clinical research in ASD due to the substantial cost and time required, and it is often prohibitive in large-scale studies. There is a need for more efficient, but reliable, methods to estimate cognitive functioning for researchers, clinicians, and families. To examine the degree to which caregiver estimates of cognitive level agree with actual measured intelligence/developmental scores and understand factors that may impact that agreement, 1,555 autistic individuals (81.74% male; age 18 months-18 years) were selected from a large cohort (Simons Foundation Powering Autism Research for Knowledge, SPARK). Results suggest that querying parents about recent testing results and developmental diagnoses can provide valid and useful information on cognitive ability. The agreement of parental estimates varied with age, measured cognitive ability, autistic traits, and adaptive skills. In the context of large-scale research efforts, parent-reported cognitive impairment may be a good proxy for categorical IQ range for survey-based studies when specific IQ scores are not available, circumventing the logistical and financial obstacles of obtaining neuropsychological or neurodevelopmental testing.

The Prevalence and Characteristics of Children With Profound Autism, 15 Sites, United States, 2000-2016.

OBJECTIVES: Autism spectrum disorder (autism) is a heterogeneous condition that poses challenges in describing the needs of individuals with autism and making prognoses about future outcomes. We applied a newly proposed definition of profound autism to surveillance data to estimate the percentage of children with autism who have profound autism and describe their sociodemographic and clinical characteristics. METHODS: We analyzed population-based surveillance data from the Autism and Developmental Disabilities Monitoring Network for 20 135 children aged 8 years with autism during 2000-2016. Children were classified as having profound autism if they were nonverbal, were minimally verbal, or had an intelligence quotient <50. RESULTS: The percentage of 8-year-old children with profound autism among those with autism was 26.7%. Compared with children with non-profound autism, children with profound autism were more likely to be female, from racial and ethnic minority groups, of low socioeconomic status, born preterm or with low birth weight; have self-injurious behaviors; have seizure disorders; and have lower adaptive scores. In 2016, the prevalence of profound autism was 4.6 per 1000 8-year-olds. The prevalence ratio (PR) of profound autism was higher among non-Hispanic Asian/Native Hawaiian/Other Pacific Islander (PR = 1.55; 95 CI, 1.38-1.73), non-Hispanic Black (PR = 1.76; 95% CI, 1.67-1.86), and Hispanic (PR = 1.50; 95% CI, 0.88-1.26) children than among non-Hispanic White children. CONCLUSIONS: As the population of children with autism continues to change, describing and quantifying the population with profound autism is important for planning. Policies and programs could consider the needs of people with profound autism across the life span to ensure their needs are met.

Statewide county-level autism spectrum disorder prevalence estimates-seven U.S. states, 2018.

PURPOSE: Autism spectrum disorder (ASD) prevalence information is necessary for identifying community needs such as addressing disparities in identification and services. METHODS: Seven Autism and Developmental Disabilities Monitoring (ADDM) Network sites participated in a pilot project to link statewide health and education data to generate statewide and county-level prevalence estimates for a broader age range for their states for the first time. RESULTS: Statewide prevalence of ASD for ages 3-21 years in 2018 ranged from 1.5% in Tennessee and Wisconsin to 2.3% in Arizona. The median county-level prevalence of ASD was 1.4% of residents ages 3-21 years. More boys than girls had ASD at all sites, and prevalence was lower among non-Hispanic Black, Hispanic, Asian/Pacific Islander, and American Indian/Alaska Native residents compared to non-Hispanic White residents at most sites. ASD prevalence estimates for children aged 8 years were similar to 2018 ADDM Network estimates that used record review to provide more in-depth information, but showed greater variation for children aged 4 years. CONCLUSIONS: Linkage of statewide data sets provides less detailed but actionable local information when more resource-intensive methods are not possible.

Prevalence and Characteristics of Autism Spectrum Disorder Among Children Aged 8 Years - Autism and Developmental Disabilities Monitoring Network, 11 Sites, United States, 2020.

Problem/Condition: Autism spectrum disorder (ASD). Period Covered: 2020. Description of System: The Autism and Developmental Disabilities Monitoring (ADDM) Network is an active surveillance program that provides estimates of the prevalence of ASD among children aged 8 years. In 2020, there were 11 ADDM Network sites across the United States (Arizona, Arkansas, California, Georgia, Maryland, Minnesota, Missouri, New Jersey, Tennessee, Utah, and Wisconsin). To ascertain ASD among children aged 8 years, ADDM Network staff review and abstract developmental evaluations and records from community medical and educational service providers. A child met the case definition if their record documented 1) an ASD diagnostic statement in an evaluation, 2) a classification of ASD in special education, or 3) an ASD International Classification of Diseases (ICD) code. Results: For 2020, across all 11 ADDM sites, ASD prevalence per 1,000 children aged 8 years ranged from 23.1 in Maryland to 44.9 in California. The overall ASD prevalence was 27.6 per 1,000 (one in 36) children aged 8 years and was 3.8 times as prevalent among boys as among girls (43.0 versus 11.4). Overall, ASD prevalence was lower among non-Hispanic White children (24.3) and children of two or more races (22.9) than among non-Hispanic Black or African American (Black), Hispanic, and non-Hispanic Asian or Pacific Islander (A/PI) children (29.3, 31.6, and 33.4 respectively). ASD prevalence among non-Hispanic American Indian or Alaska Native (AI/AN) children (26.5) was similar to that of other racial and ethnic groups. ASD prevalence was associated with lower household income at three sites, with no association at the other sites.Across sites, the ASD prevalence per 1,000 children aged 8 years based exclusively on documented ASD diagnostic statements was 20.6 (range = 17.1 in Wisconsin to 35.4 in California). Of the 6,245 children who met the ASD case definition, 74.7% had a documented diagnostic statement of ASD, 65.2% had a documented ASD special education classification, 71.6% had a documented ASD ICD code, and 37.4% had all three types of ASD indicators. The median age of earliest known ASD diagnosis was 49 months and ranged from 36 months in California to 59 months in Minnesota.Among the 4,165 (66.7%) children with ASD with information on cognitive ability, 37.9% were classified as having an intellectual disability. Intellectual disability was present among 50.8% of Black, 41.5% of A/PI, 37.8% of two or more races, 34.9% of Hispanic, 34.8% of AI/AN, and 31.8% of White children with ASD. Overall, children with intellectual disability had earlier median ages of ASD diagnosis (43 months) than those without intellectual disability (53 months). Interpretation: For 2020, one in 36 children aged 8 years (approximately 4% of boys and 1% of girls) was estimated to have ASD. These estimates are higher than previous ADDM Network estimates during 2000-2018. For the first time among children aged 8 years, the prevalence of ASD was lower among White children than among other racial and ethnic groups, reversing the direction of racial and ethnic differences in ASD prevalence observed in the past. Black children with ASD were still more likely than White children with ASD to have a co-occurring intellectual disability. Public Health Action: The continued increase among children identified with ASD, particularly among non-White children and girls, highlights the need for enhanced infrastructure to provide equitable diagnostic, treatment, and support services for all children with ASD. Similar to previous reporting periods, findings varied considerably across network sites, indicating the need for additional research to understand the nature of such differences and potentially apply successful identification strategies across states.

Early Identification of Autism Spectrum Disorder Among Children Aged 4 Years - Autism and Developmental Disabilities Monitoring Network, 11 Sites, United States, 2020.

Problem/Condition: Autism spectrum disorder (ASD). Period Covered: 2020. Description of System: The Autism and Developmental Disabilities Monitoring Network is an active surveillance program that estimates prevalence and characteristics of ASD and monitors timing of ASD identification among children aged 4 and 8 years. In 2020, a total of 11 sites (located in Arizona, Arkansas, California, Georgia, Maryland, Minnesota, Missouri, New Jersey, Tennessee, Utah, and Wisconsin) conducted surveillance of ASD among children aged 4 and 8 years and suspected ASD among children aged 4 years. Surveillance included children who lived in the surveillance area at any time during 2020. Children were classified as having ASD if they ever received 1) an ASD diagnostic statement in an evaluation, 2) a special education classification of autism (eligibility), or 3) an ASD International Classification of Diseases (ICD) code (revisions 9 or 10). Children aged 4 years were classified as having suspected ASD if they did not meet the case definition for ASD but had a documented qualified professional's statement indicating a suspicion of ASD. This report focuses on children aged 4 years in 2020 compared with children aged 8 years in 2020. Results: For 2020, ASD prevalence among children aged 4 years varied across sites, from 12.7 per 1,000 children in Utah to 46.4 in California. The overall prevalence was 21.5 and was higher among boys than girls at every site. Compared with non-Hispanic White children, ASD prevalence was 1.8 times as high among Hispanic, 1.6 times as high among non-Hispanic Black, 1.4 times as high among Asian or Pacific Islander, and 1.2 times as high among multiracial children. Among the 58.3% of children aged 4 years with ASD and information on intellectual ability, 48.5% had an IQ score of ≤70 on their most recent IQ test or an examiner's statement of intellectual disability. Among children with a documented developmental evaluation, 78.0% were evaluated by age 36 months. Children aged 4 years had a higher cumulative incidence of ASD diagnosis or eligibility by age 48 months compared with children aged 8 years at all sites; risk ratios ranged from 1.3 in New Jersey and Utah to 2.0 in Tennessee. In the 6 months before the March 2020 COVID-19 pandemic declaration by the World Health Organization, there were 1,593 more evaluations and 1.89 more ASD identifications per 1,000 children aged 4 years than children aged 8 years received 4 years earlier. After the COVID-19 pandemic declaration, this pattern reversed: in the 6 months after pandemic onset, there were 217 fewer evaluations and 0.26 fewer identifications per 1,000 children aged 4 years than children aged 8 years received 4 years earlier. Patterns of evaluation and identification varied among sites, but there was not recovery to pre-COVID-19 pandemic levels by the end of 2020 at most sites or overall. For 2020, prevalence of suspected ASD ranged from 0.5 (California) to 10.4 (Arkansas) per 1,000 children aged 4 years, with an increase from 2018 at five sites (Arizona, Arkansas, Maryland, New Jersey, and Utah). Demographic and cognitive characteristics of children aged 4 years with suspected ASD were similar to children aged 4 years with ASD. Interpretation: A wide range of prevalence of ASD by age 4 years was observed, suggesting differences in early ASD identification practices among communities. At all sites, cumulative incidence of ASD by age 48 months among children aged 4 years was higher compared with children aged 8 years in 2020, indicating improvements in early identification of ASD. Higher numbers of evaluations and rates of identification were evident among children aged 4 years until the COVID-19 pandemic onset in 2020. Sustained lower levels of ASD evaluations and identification seen at a majority of sites after the pandemic onset could indicate disruptions in typical practices in evaluations and identification for health service providers and schools through the end of 2020. Sites with more recovery could indicate successful strategies to mitigate service interruption, such as pivoting to telehealth approaches for evaluation. Public Health Action: From 2016 through February of 2020, ASD evaluation and identification among the cohort of children aged 4 years was outpacing ASD evaluation and identification 4 years earlier (from 2012 until March 2016) among the cohort of children aged 8 years in 2020 . From 2016 to March 2020, ASD evaluation and identification among the cohort of children aged 4 years was outpacing that among children aged 8 years in 2020 from 2012 until March 2016. The disruptions in evaluation that coincided with the start of the COVID-19 pandemic and the increase in prevalence of suspected ASD in 2020 could have led to delays in ASD identification and interventions. Communities could evaluate the impact of these disruptions as children in affected cohorts age and consider strategies to mitigate service disruptions caused by future public health emergencies.

Factors associated with use of medication for behavioral challenges in adults with intellectual and developmental disability.

BACKGROUND/AIMS: Persons with intellectual or developmental disabilities and who exhibit challenging behaviors are often prescribed medication to control behavior. Little is known about the environmental factors that may be associated with taking these medications. METHODS AND OUTCOMES: This study examined the association between individual and intermediate or environmental factors and the documented use of medication for clients with intellectual or developmental disabilities (IDD) who exhibit challenging behavior, using the 2014-15 National Core Indicators Adult Consumer Survey dataset. RESULTS AND CONCLUSIONS: Individual-level variables associated with a higher likelihood of taking medication for persons with IDD exhibiting challenging behaviors included being of younger age, male gender, having moderate or severe intellectual disability, being ambulatory, communicating verbally, having a behavioral plan, requiring support for behavioral challenges, and having a history of mental illness. Environment-level variables included infrequently eating out and having less everyday choice. This study found that restrictions in opportunities to make choices in their life was associated with a greater likelihood of being on a medication for persons with IDD who exhibit challenging behavior. Living in group home settings also increased the likelihood of medication use. A limitation of the study is a lack of information on why medications were prescribed and whether they were intended to treat the challenging behavior. IMPLICATIONS: This work has important implications for health providers, as addressing malleable social factors may provide an avenue for reducing challenging behaviors without the need for medication.

Clinical considerations when conducting diagnostic evaluations to identify autism spectrum disorder in young children.

OBJECTIVE: This paper provides clinical guidance supported by the literature on conducting diagnostic evaluations for young children suspected of having autism spectrum disorder (ASD). METHOD: Authors provided a summary of clinical recommendations and evidence-based strategies for providing diagnostic evaluations for young children suspected of having ASD that are supported by the existing literature. RESULTS: ASD is a complex condition that typically presents in the first couple years of a child's life. While many children can be accurately diagnosed by age 2, the majority of children are diagnosed much later. This article provides recommendations for evidence-based clinical practices to support accurate early identification and diagnosis in young children with autism. Recommended practices and measures for screening, comprehensive diagnostic evaluation, and differential diagnosis of ASD in early childhood are discussed. CONCLUSIONS: Early identification of ASD is important to promote improved outcomes related to early intervention. There are a variety of tools and practices available to support neuropsychologists in providing accurate early diagnosis and appropriate developmental monitoring for children suspected of ASD and related neurodevelopmental conditions. There is a need for continued efforts regarding awareness of ASD in early childhood and targeted training in ASD for neuropsychologists and other disciplines who support families of young children with disabilities.

The role of intellectual disability with autism spectrum disorder and the documented cooccurring conditions: A population-based study.

Previous research has identified that patterns of cooccurring conditions (CoCs) associated with autism spectrum disorder (ASD) differ based on the presence of intellectual disability (ID). This study explored the association of documented CoCs among 8-year-old children with ASD and ID (ASD+ID, n = 2416) and ASD without ID (ASD-ID, n = 5372) identified by the Autism and Developmental Disabilities Monitoring Network, surveillance years (SYs) 2012 and 2014. After adjusting for demographic variables, record source, surveillance site, and SY, children with ASD+ID, as compared with children with ASD-ID, were more likely to have histories of nonspecific developmental delays and neurological disorders documented in their records but were less likely to have behavioral and psychiatric disorders. ID plays a key role on how children with ASD would experience other CoCs. Our results emphasize how understanding the pattern of CoCs in ASD+ID and ASD-ID can inform comprehensive and multidisciplinary approaches in assessment and management of children in order to develop targeted interventions to reduce possible CoCs or CoCs-related impairments.

Height and BMI in fragile X syndrome: A longitudinal assessment.

OBJECTIVE: Previously reported data regarding growth parameters in individuals with fragile X syndrome (FXS) are inconsistent. A longitudinal analysis of height and BMI in a large number of individuals with FXS was conducted. METHODS: Age- and sex-specific z scores for height and BMI of 1,223 individuals with FXS were calculated based on published normative data. Mixed-effect linear regression models were fit separately for males and females, and z scores for height and weight were regressed against age and adjusted for intellectual disability (ID) and psychotropic medication use. RESULTS: Mean height z score for both sexes decreased with age and was lower than normative data. Mean BMI z score was greater than normative data in both sexes, and this disparity increased with age. BMI z score in females was greater for those with moderate or severe ID than those with no or mild ID. Individuals taking antipsychotics had higher BMI z scores than those taking no or other medications; those taking anticonvulsants or stimulants had lower BMI z scores. CONCLUSIONS: Individuals with FXS are at elevated risk for overweight and obesity. The risk is higher in individuals taking antipsychotics and among females with severe ID. These findings warrant increased attention to obesity prevention for all individuals with FXS.

Diagnostic Evaluations of Autism Spectrum Disorder during the COVID-19 Pandemic.

A global pandemic has significantly impacted the ability to conduct diagnostic evaluations for autism spectrum disorder (ASD). In the wake of the coronavirus, autism centers and providers quickly needed to implement innovative diagnostic processes to adapt in order to continue serve patient needs while minimizing the spread of the virus. The International Collaborative for Diagnostic Evaluation of Autism (IDEA) is a grassroots organization that came together to discuss standards of care during the pandemic and to provide a forum wherein providers communicated decisions. This white paper is intended to provide examples of how different centers adjusted their standard approaches to conduct diagnostic evaluations for ASD during the pandemic and to provide insight to other centers as they go through similar challenges.

Corrigendum: Bias in measurement of autism symptoms by spoken language level and non-verbal mental age in minimally verbal children with neurodevelopmental disorders.

[This corrects the article DOI: 10.3389/fpsyg.2022.927847.].

Bias in measurement of autism symptoms by spoken language level and non-verbal mental age in minimally verbal children with neurodevelopmental disorders.

Increasing numbers of children with known genetic conditions and/or intellectual disability are referred for evaluation of autism spectrum disorder (ASD), highlighting the need to refine autism symptom measures to facilitate differential diagnoses in children with cognitive and language impairments. Previous studies have reported decreased specificity of ASD screening and diagnostic measures in children with intellectual disability. However, little is known about how cognitive and language abilities impact the measurement of specific ASD symptoms in this group. We aggregated a large sample of young children (N = 1196; aged 31-119 months) to examine measurement invariance of ASD symptoms among minimally verbal children within the context of the Autism Diagnostic Observation Schedule (ADOS) Module 1. Using confirmatory factor analysis (CFA) and moderated non-linear factor analysis (MNLFA), we examined how discrete behaviors were differentially associated with the latent symptom domains of social communication impairments (SCI) and restricted and repetitive behaviors (RRB) across spoken language levels and non-verbal mental age groupings. While the two-factor structure of SCI and RRB held consistently across language and cognitive levels, only partial invariance was observed for both ASD symptom domains of SCI and RRB. Specifically, four out of the 15 SCI items and one out of the three RRB items examined showed differential item functioning between children with "Few to No Words" and those with "Some Words"; and one SCI item and one RRB item showed differential item functioning across non-verbal mental age groups. Moreover, even after adjusting for the differential item functioning to reduce measurement bias across groups, there were still differences in ASD symptom domain scores across spoken language levels. These findings further underscore the influence of spoken language level on measurement of ASD symptoms and the importance of measuring ASD symptoms within refined spoken language levels, even among those with minimal verbal abilities.

Age of Initial Identification of Autism Spectrum Disorder in a Diverse Urban Sample.

This paper examines age of autism spectrum disorder (ASD) identification and related factors in a diverse urban sample, focusing on ASD identification in the East African Somali community. The overall average age of initial ASD identification was 4.8 years. Somali children received an initial clinical diagnosis of Autistic Disorder later than White children, and Somali children diagnosed with ASD born outside of Minnesota (MN) received their first comprehensive evaluation later than Somali children diagnosed with ASD born in MN. Most children had noted developmental concerns before age 3, with no significant racial or ethnic differences in those concerns. The current study contributes to a limited number of studies on early ASD identification in culturally and linguistically diverse populations.

Impact of Working Together for adults with autism spectrum disorder: a multifamily group intervention.

BACKGROUND: Adults with autism spectrum disorder (ASD) have lower engagement in their communities, higher rates of unemployment/underemployment, and continued difficulties with challenging behavior compared to their neurotypical peers. Multi-family psychoeducation emphasizes education and problem-solving with the goal of improving these outcomes for the individual with the disability. METHODS: Using a randomized waitlist control design, the present study evaluated a multi-family group psychoeducation intervention, Working Together, for adults on the autism spectrum without intellectual disability (n = 40). Five waves of data were collected at 3-month intervals. In this design, families in the intervention condition participated in intervention during the 6 months between baseline and time 3 data collection; the waitlist control condition received the intervention immediately after the time 3 data collection. We compared these two conditions, intervention group (n = 20) vs waitlist control group (n = 20), on key outcomes for the adults with ASD: engagement in work-related activities, engagement in meaningful activities, and behavior problems. RESULTS: Results indicated medium to large effect sizes associated with the Working Together intervention across key outcomes, including adults on the spectrum experiencing significant increases in meaningful activities and decreases in internalizing problems. Although increases in work-related activities were not statistically significant, an observed one-half of a standard deviation difference from before to after the intervention indicated clinically significant change. We also found maintenance of the treatment effect through 6 months post-treatment for the intervention group and replication of the treatment effect within the control group after they received the intervention. CONCLUSION: Working Together is a promising multi-family group psychoeducation intervention designed to improve functioning during adulthood. These findings highlight the need for more intervention services research during adulthood and specifically the need for family-centered supports.

Extracting Latent Subdimensions of Social Communication: A Cross-Measure Factor Analysis.

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.