Explaining differences in age at autism spectrum disorder diagnosis: a critical review

Caregiver Narratives of Children with Autism Spectrum Disorder: Exploring Symptom Recognition, Diagnosis, and Interventions

The diagnosis of autism spectrum disorder (ASD) poses myriad challenges for families, yet there is a scarcity of research focusing on their journey from recognizing initial anomalies to implementing interventions. This qualitative study examines how caregivers in Sylhet, Bangladesh, perceive and manage ASD in their children, including early symptom identification, diagnostic processes, and intervention strategies. Data for this study were collected through semi-structured interviews, case studies, and observations involving 22 caregivers of children with ASD. Participants were chosen using purposive-convenience sampling, and data collection continued until interpretive saturation was achieved. The study findings unveil nuanced caregiver perceptions of ASD causation, influenced by sociocultural factors, religious beliefs, and genetic predispositions. These determinants wield significant influence over treatment modalities and the child's developmental trajectory. Importantly, the prevalence of supernatural beliefs and myths often surpasses biomedical explanations, highlighting gaps in awareness, educational outreach, and understanding of ASD. Nevertheless, religious beliefs and rituals concurrently serve as adaptive coping mechanisms, offering solace amidst uncertainty. Furthermore, a striking observation emerges: despite parents frequently identifying anomalies in their children within a 24-month, a substantial delay of 3 to 5 years persists between initial symptom recognition and formal diagnosis. This delay predominantly stems from caregiver hesitancy driven by societal stigmatization, familial dismissal attitudes, and limited diagnostic and specialized services. This study highlights the challenging diagnostic journey and caregiving for children with ASD in Bangladesh, stressing the need for systemic improvements in services, awareness, and research to enhance the well-being of individuals with ASD.

Child Age at Time of First Maternal Concern and Time to Services Among Children with Autism Spectrum Disorder

OBJECTIVE

Early treatment of autism spectrum disorder (ASD) can improve developmental outcomes. Children with ASD from minority families often receive services later. We explored factors related to child's age at time of mother's first concerns about child's development and subsequent time to service initiation among children with ASD.

METHODS

Analysis included 759 preschool-age children classified with ASD based on comprehensive evaluations. Factors associated with retrospectively reported child age at time of first maternal concern and subsequent time to service initiation were investigated using multiple linear regression and Cox proportional hazards.

RESULTS

Earlier maternal concern was associated with multiparity, ≥1 child chronic condition, externalizing behaviors, and younger gestational age, but not race/ethnicity. Time to service initiation was longer for children of non-Latino Black or other than Black or White race and higher developmental level and shorter for children with ≥1 chronic condition and older child age at first maternal concern.

CONCLUSION

Parity, gestational age, and child health and behavior were associated with child age at first maternal concern. Knowledge of child development in multiparous mothers may allow them to recognize potential concerns earlier, suggesting that first time parents may benefit from enhanced education about normal development. Race/ethnicity was not associated with child's age when mothers recognized potential developmental problems; hence, it is unlikely that awareness of ASD symptoms causes racial/ethnic disparities in initiation of services. Delays in time to service initiation among children from racial/ethnic minority groups highlight the need to improve their access to services as soon as developmental concerns are recognized.

Access to Part C, Early Intervention for children younger than 4 years evaluated for autism spectrum disorder

LAY ABSTRACT

Health disparities are defined as preventable differences in the opportunities to achieve optimal health outcomes experienced by marginalized and underrepresented communities. For families with autistic children, health disparities limit accessing early intervention services-which have been found to improve quality of life and other outcomes. One specific early intervention service in the United States is Individuals with Disabilities Education Act, Part C Early Intervention programs, which are federally funded interventions for children birth-to-three with developmental delays. This study adds to this topic by examining which factors impact accessing Part C, Early Intervention services for children who were evaluated for autism. Results showed that only half of the sample received these services despite there being concerns about development for all children. In addition, results showed that those who identified as Black had decreased odds of having accessed Part C, Early Intervention compared to those who identified as White. These results suggest that there are disparities when it comes to accessing important early intervention services that may be negatively impacting the Black autistic community.

Trajectories of adaptive functioning from early childhood to adolescence in autism: Identifying turning points and key correlates of chronogeneity

Background

Previous research has demonstrated heterogeneous adaptive outcomes across the autism spectrum; however, the current literature remains limited in elucidating turning points and associated factors for longitudinal variability (chronogeneity). To address these empirical gaps, we aimed to provide a finer-grained characterization of trajectories of adaptive functioning from early childhood to adolescence in autism.

Methods

Our sample (N = 406) was drawn from an inception cohort of children diagnosed Autistic at ages 2-5. Adaptive functioning was assessed with Vineland Adaptive Behavior Scales (VABS, 2nd Edition) across 6 visits from the time of diagnosis by age 18. Parallel-process latent growth curve modeling were used to estimate domain-level VABS trajectories, followed by latent class growth analysis to identify trajectory subgroups. Child characteristics at diagnosis, family demographics, and participation outcomes at adolescence were compared across subgroups.

Results

Piecewise latent growth models best described VABS trajectories with two turning points identified at around ages 5-6 and 9-10, respectively reflecting transitions into school age and early adolescence. We parsed four VABS trajectory subgroups that vary by level of functioning and change rate for certain domains and periods. Around 16% of the sample exhibited overall adequate functioning (standard score >85) with notable early growth and social adaptation during adolescence. About 21% showed low adaptive functioning (standard score ≤70), with decreasing slopes by age 6 followed by improvements in communication and daily-living skills by age 10. The other two subgroups (63% in total) were characterized by adaptive functioning between low and adequate levels, with relatively stable trajectories entering school age. These subgroups differed most in their cognitive ability at diagnosis, household income, and social participation in adolescence.

Conclusions

We identified key individual and family characteristics and time windows associated with distinct adaptive functioning trajectories, which have important implications for providing timely and tailored supports to Autistic people across developmental stages.

Predicting autism traits from baby wellness records: A machine learning approach

LAY ABSTRACT

Timely identification of autism spectrum conditions is a necessity to enable children to receive the most benefit from early interventions. Emerging technological advancements provide avenues for detecting subtle, early indicators of autism from routinely collected health information. This study tested a model that provides a likelihood score for autism diagnosis from baby wellness visit records collected during the first 2 years of life. It included records of 591,989 non-autistic children and 12,846 children with autism. The model identified two-thirds of the autism spectrum condition group (boys 63% and girls 66%). Sex-specific models had several predictive features in common. These included language development, fine motor skills, and social milestones from visits at 12-24 months, mother's age, and lower initial growth but higher last growth measurements. Parental concerns about development or hearing impairment were other predictors. The models differed in other growth measurements and birth parameters. These models can support the detection of early signs of autism in girls and boys by using information routinely recorded during the first 2 years of life.

The Influence of Social and Developmental Factors on the Timing of Autism Spectrum Disorder Diagnosis of Preschool-Aged Children: Evidence from a Specialized Chilean Center

We investigated the influence of developmental and social factors on the age of autism diagnosis (AoD) in a cohort of toddlers living in Chile. A cross-sectional study was conducted among 509 preschool children diagnosed with autism spectrum disorder [M = 40.2 months (SD = 8.6), girls: 32%] in the neurodevelopmental unit of a university clinic in Santiago, Chile (2015-2023). Structural changes in the annual trend of AoD were tested. Generalized linear models (gamma distribution) with and without interaction terms were used for the multivariate analysis, adjusting for gender, residential area, year of diagnosis, developmental variables (language regression, delayed walking, and use of expressive verbal language), and primary caregiver age and education level (CEL). 95% confidence intervals of the unstandardized regression coefficients (B) were calculated using 1000 bootstrap resampling to estimate associations. AoD increased between 2021-2022 and decreased in 2023. Female gender (B = 2.72 [1.21-4.23]), no history of language regression (B = 3.97 [1.66-6.28]), and the presence of expressive verbal language at diagnosis (B = 1.57 [0.05-3.08]) were associated with higher AoD. Children whose caregivers had tertiary education were diagnosed earlier than those with ≤ 12 years of formal education. Although the influence of CEL increased with caregiver age, differences between CEL groups were significant only for caregivers aged ≥ 30 years. Improved education and early screening for clinical features of autism among healthcare professionals and the community, with a focus on young children without highly apparent developmental concerns and those from vulnerable social groups, are warranted.

Differential Performance of Social Communication Questionnaire Items in African American/Black vs. White Children

Screening for autism spectrum disorder (ASD) is an essential early step in the identification process and inaccurate screening may lead to significant delays in the onset of treatment. Past research has highlighted discrepancies in the performance of ASD screening tools such as the Social Communication Questionnaire (SCQ) among certain racial and ethnic groups. The current study explored the functioning of the SCQ among African American/Black and White respondents based on item level performance on the measure. Differential Item Functioning (DIF) analyses showed that 16 (41%) items of the SCQ functioned differently for African American/Black respondents when compared to White respondents. Implications, such as the potential for delayed diagnosis and treatment, and the influence on downstream outcomes, are discussed.

The Pediatric Autism Research Cohort (PARC) Study: protocol for a patient-oriented prospective study examining trajectories of functioning in children with autism

INTRODUCTION

The developmentally variable nature of autism poses challenges in providing timely services tailored to a child's needs. Despite a recent focus on longitudinal research, priority-setting initiatives with stakeholders highlighted the importance of studying a child's day-to-day functioning and social determinants of health to inform clinical care. To address this, we are conducting a pragmatic multi-site, patient-oriented longitudinal investigation: the Pediatric Autism Research Cohort (PARC) Study. In young children (<7 years of age) newly diagnosed with autism, we will: (1) examine variability in trajectories of adaptive functioning from the point of diagnosis into transition to school; and (2) identify factors associated with trajectories of adaptive functioning.

METHODS AND ANALYSIS

We aim to recruit 1300 children under 7 years of age with a recent (within 12 months) diagnosis of autism from seven sites: six in Canada; one in Israel. Participants will be followed prospectively from diagnosis to age 8 years, with assessments at 6-month intervals. Parents/caregivers will complete questionnaires administered via a customized online research portal. Following each assessment timepoint, families will receive a research summary report describing their child's progress on adaptive functioning and related domains. Analysis of the longitudinal data will map trajectories and examine child, family and service characteristics associated with chronogeneity (interindividual and intraindividual heterogeneity over time) and possible trajectory turning points around sensitive periods like the transition to school.

ETHICS AND DISSEMINATION

Ethics approvals have been received by all sites. All parents/respondents will provide informed consent when enrolling in the study. Using an integrated knowledge translation approach, where stakeholders are directly engaged in the research process, the PARC Study will identify factors associated with trajectories of functioning in children with autism. Resulting evidence will be shared with government policy makers to inform provincial and national programs. Findings will be disseminated at conferences and published in peer-reviewed journals.

Diagnostic error in mental health: a review

Diagnostic errors are associated with patient harm and suboptimal outcomes. Despite national scientific efforts to advance definition, measurement and interventions for diagnostic error, diagnosis in mental health is not well represented in this ongoing work. We aimed to summarise the current state of research on diagnostic errors in mental health and identify opportunities to align future research with the emerging science of diagnostic safety. We review conceptual considerations for defining and measuring diagnostic error, the application of these concepts to mental health settings, and the methods and subject matter focus of recent studies of diagnostic error in mental health. We found that diagnostic error is well understood to be a problem in mental healthcare. Although few studies used clear definitions or frameworks for understanding diagnostic error in mental health, several studies of missed, wrong, delayed and disparate diagnosis of common mental disorders have identified various avenues for future research and development. Nevertheless, a lack of clear consensus on how to conceptualise, define and measure errors in diagnosis will pose a barrier to advancement. Further research should focus on identifying preventable missed opportunities in the diagnosis of mental disorders, which may uncover generalisable opportunities for improvement.

Clinical, socio-demographic, and parental correlates of early autism traits in a community cohort of toddlers

Identifying factors linked to autism traits in the general population may improve our understanding of the mechanisms underlying divergent neurodevelopment. In this study we assess whether factors increasing the likelihood of childhood autism are related to early autistic trait emergence, or if other exposures are more important. We used data from 536 toddlers from London (UK), collected at birth (gestational age at birth, sex, maternal body mass index, age, parental education, parental language, parental history of neurodevelopmental conditions) and at 18 months (parents cohabiting, measures of socio-economic deprivation, measures of maternal parenting style, and a measure of maternal depression). Autism traits were assessed using the Quantitative Checklist for Autism in Toddlers (Q-CHAT) at 18 months. A multivariable model explained 20% of Q-CHAT variance, with four individually significant variables (two measures of parenting style and two measures of socio-economic deprivation). In order to address variable collinearity we used principal component analysis, finding that a component which was positively correlated with Q-CHAT was also correlated to measures of parenting style and socio-economic deprivation. Our results show that parenting style and socio-economic deprivation correlate with the emergence of autism traits at age 18 months as measured with the Q-CHAT in a community sample.

A Prediction Model of Autism Spectrum Diagnosis from Well-Baby Electronic Data Using Machine Learning

Early detection of autism spectrum disorder (ASD) is crucial for timely intervention, yet diagnosis typically occurs after age three. This study aimed to develop a machine learning model to predict ASD diagnosis using infants' electronic health records obtained through a national screening program and evaluate its accuracy. A retrospective cohort study analyzed health records of 780,610 children, including 1163 with ASD diagnoses. Data encompassed birth parameters, growth metrics, developmental milestones, and familial and post-natal variables from routine wellness visits within the first two years. Using a gradient boosting model with 3-fold cross-validation, 100 parameters predicted ASD diagnosis with an average area under the ROC curve of 0.86 (SD < 0.002). Feature importance was quantified using the Shapley Additive explanation tool. The model identified a high-risk group with a 4.3-fold higher ASD incidence (0.006) compared to the cohort (0.001). Key predictors included failing six milestones in language, social, and fine motor domains during the second year, male gender, parental developmental concerns, non-nursing, older maternal age, lower gestational age, and atypical growth percentiles. Machine learning algorithms capitalizing on preventative care electronic health records can facilitate ASD screening considering complex relations between familial and birth factors, post-natal growth, developmental parameters, and parent concern.

Predictors of age at diagnosis in autism spectrum disorders: the use of multiple regression analyses and a classification tree on a clinical sample

The increasing prevalence of autism spectrum disorders (ASD) has led to worldwide interest in factors influencing the age of ASD diagnosis. Parents or caregivers of 237 ASD children (193 boys, 44 girls) diagnosed using the Autism Diagnostic Observation Schedule (ADOS) completed a simple descriptive questionnaire. The data were analyzed using the variable-centered multiple regression analysis and the person-centered classification tree method. We believed that the concurrent use of these two methods could produce robust results. The mean age at diagnosis was 5.8 ± 2.2 years (median 5.3 years). Younger ages for ASD diagnosis were predicted (using multiple regression analysis) by higher scores in the ADOS social domain, higher scores in ADOS restrictive and repetitive behaviors and interest domain, higher maternal education, and the shared household of parents. Using the classification tree method, the subgroup with the lowest mean age at diagnosis were children, in whom the summation of ADOS communication and social domain scores was ≥ 17, and paternal age at the delivery was ≥ 29 years. In contrast, the subgroup with the oldest mean age at diagnosis included children with summed ADOS communication and social domain scores < 17 and maternal education at the elementary school level. The severity of autism and maternal education played a significant role in both types of data analysis focused on age at diagnosis.

Explaining differences in autism detection timing: Age of diagnosis and associated individual and socio-familial factors in Chinese children

LAY ABSTRACT

Timely detection is an issue of paramount importance in the care of children with autism spectrum disorder. Whether the delayed autism spectrum disorder diagnosis can be explained by children's clinical presentations and socio-familial status in China is a question to be addressed. We investigated 1235 autism spectrum disorder children from 132 rehabilitation organisations in Shenzhen, China. These children were found to have a mean age of diagnosis of 31.4 ± 12.7 months and a median age of diagnosis of 30.0 months. The majority of these children were able to receive their diagnosis during toddlerhood. However, about one in six were not diagnosed until they entered preschool or later, thus missing the golden window of opportunity for early intervention. The age of diagnosis was likely to be late if the children were older, were less severe and presented with no intellectual impairment. The odds of having a delayed autism spectrum disorder diagnosis were more than 9 times higher among migrant autism spectrum disorder children than among those with local household registrations, thus underscoring the importance of identifying culturally sensitive socio-economic determinants in autism spectrum disorder detection, as these factors are likely to affect the quality of life of many autism spectrum disorder children and their families.

Demographic and autism characteristics as predictors of age of autism diagnosis of individuals with autism in Paraguay

LAY ABSTRACT

Autism is a lifelong condition characterized by repetitive behaviors and social communication differences. The reported cases of autism increased globally in the past years. Detecting autism early and providing appropriate supports promptly are crucial for better outcomes. Yet, little research focuses on what factors interplay in the diagnostic process of autistic children in Paraguay. We gathered data from 176 caregivers of autistic children under 18 years in Paraguay. Through a detailed analysis, we found that child's age, child's age at the caregiver's first concerns about their development, and the child's verbal skills are key in predicting the age of autism diagnosis in Paraguay. Educating caregivers and professionals about autism and social communication development can help identify autism early and provide timely support.

Understanding autism diagnosis in primary care: Rates of diagnosis from 2004 to 2019 and child age at diagnosis

LAY ABSTRACT

The current demand for autism diagnostic services exceeds the ability of the workforce to assess and diagnose children in a timely manner. One solution may be to equip primary care providers (PCPs) with the tools and expertise needed to diagnose autism within their practice. PCPs are often trusted professionals who have many touchpoints with children during early development, in which they can identify early signs of autism. Recent initiatives have focused on bolstering PCPs' diagnostic capabilities; however, no studies have examined how the rates of autism diagnosis in primary care have changed over time. We aimed to evaluate whether autism diagnosis in primary care has changed over time and how diagnosis in primary care relates to a child's age at the time of diagnosis. We found that the likelihood of a child being diagnosed by a PCP decreased by about 2% with every passing year from 2004 to 2019 when accounting for demographic characteristics. In our sample, PCPs diagnosed children approximately 1 year earlier than non-PCPs (e.g., psychologists and psychiatrists). Further research is needed to understand why the proportion of children diagnosed by PCPs decreases over time. However, this decrease suggests more work is needed to get capacity-building initiatives into community primary care practice. Though we must continue to find effective ways to build community PCPs' ability to diagnose autism, the present findings support the crucial role PCPs can play in early autism diagnosis.

Age at autism spectrum disorder diagnosis and its association with child and family characteristics in a tertiary care hospital in Malaysia

Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder. Despite the absence of a cure, early diagnosis and intensive early intervention can improve the outcomes. However, little is known about the median age at ASD diagnosis in Malaysia or the child/family characteristics associated with early diagnosis. Therefore, this study aimed to determine the median age at ASD diagnosis among Malaysian children presenting to the country's largest public tertiary neurodevelopmental center and to investigate the possible demographic, child, and family characteristics associated with an early age at diagnosis. Data were collected between February 2017 and February 2019 from a database maintained by the child development unit of the country's largest publicly funded tertiary hospital, containing data from an ethnically diverse population. Among Malaysian children attending the clinic, the median age at ASD diagnosis was 48 months. Early autism diagnosis (<36 months of age) was associated with increased severity of social communication and interaction impairments, coexisting intellectual impairment, children from high socioeconomic status families, and children who receive joint care from their families and a maid or babysitter. The study findings highlight the socioeconomic inequalities in the country, a lack of parental awareness of early ASD signs, and the presence of cultural influences on the age at diagnosis of ASD.

Validating the International Classification of Functioning, Disability and Health Core Sets for Autism in a Sample of Australian School-Aged Children on the Spectrum

Assessing functioning of children on the autism spectrum is necessary to determine the level of support they require to participate in everyday activities across contexts. The International Classification of Functioning, Disability and Health (ICF) is a comprehensive biopsychosocial framework recommended for classifying health-related functioning in a holistic manner, across the components of body functions, activities and participation, and environmental factors. The ICF Core Sets (ICF-CSs) are sub-sets of relevant codes from the broader framework that provide a basis for developing condition-specific measures. This study combined the ICF-CSs for autism, attention deficit hyperactivity disorder (ADHD) and cerebral palsy (CP) to validate the ICF-CSs for autism in an Australian sample of school-aged children. This cross-sectional study involved caregivers of school-aged children on the spectrum (n = 70) completing an online survey and being visited in their homes by an occupational therapist to complete the proxy-report measure based on the ICF-CSs for autism, ADHD and CP. Absolute and relative frequencies of ratings for each of the codes included in the measure were calculated and reported, along with the number of participants who required clarification to understand the terminology used. Findings indicate that the body functions and activities and participation represented in the ICF-CSs for autism were the most applicable for the sample. However, findings relating to environmental factors were less conclusive. Some codes not currently included in the ICF-CSs for autism may warrant further investigation, and the language used in measures based on the ICF-CSs should be revised to ensure clarity.

Expert Clinician Certainty in Diagnosing Autism Spectrum Disorder in 16-30-Month-Olds: A Multi-site Trial Secondary Analysis

Differential diagnosis of young children with suspected autism spectrum disorder (ASD) is challenging, and clinician uncertainty about a child's diagnosis may contribute to misdiagnosis and subsequent delays in access to early treatment. The current study was designed to replicate and expand a recent report in this Journal (McDonnell et al. in J Autism Dev Disord 49:1391-1401, https://doi.org/10.1080/15374416.2020.1823850 , 2019), in which only 60% of diagnoses were made with complete certainty by clinicians evaluating 478 toddlers and preschool children referred for possible ASD to specialized clinics. In this study, secondary analyses were performed on diagnostic, demographic and clinical data for 496 16-30-month-old children who were consecutive referrals to a 6-site clinical trial executed by specialized centers with experienced clinicians following best-practice procedures for the diagnosis of ASD. Overall, 70.2% of diagnoses were made with complete certainty. The most important factor associated with clinician uncertainty was mid-level autism-related symptomatology. Mid-level verbal age equivalents were also associated with clinician uncertainty, but measures of symptomatology were stronger predictors. None of the socio-demographic variables, including sex of the child, was significantly associated with clinician certainty. Close to one third of early diagnoses of ASD are made with a degree of uncertainty. The delineation of specific ranges on the ADOS-2 most likely to result in clinician uncertainty identified in this study may provide an opportunity to reduce random subjectivity in diagnostic decision-making via calibration of young-child diagnostic thresholds based on later-age longitudinal diagnostic outcome data, and via standardization of decision-making in regard to clinical scenarios frequently encountered by clinicians.

Mapping autism's research landscape: trends in autism screening and its alignment with sustainable development goals

Introduction

Autism Spectrum Disorder is a complex neurodevelopmental syndrome that profoundly affects social interactions, communication, and sensory perception. The research traced the evolution of autism research from 2011-2022, specifically focusing on the screening and diagnosis of children and students.

Methods

Through an analysis of 12,262 publications using the PRISMA framework, bibliographic coupling, science mapping, and citation analysis, this study illuminates the growth trajectory of ASD research and significant disparities in diagnosis and services.

Results

The study indicates an increasing trend in autism research, with a strong representation of female authorship. Open Access journals show a higher average citation impact compared to their closed counterparts. A keyword co-occurrence analysis revealed four central research themes: Child Development and Support Systems, Early Identification and Intervention, Prevalence and Etiology, and Mental Health. The pandemic's onset has prioritized research areas like mental health, telehealth, and service accessibility.

Discussion

Recommendations on a global level stress the importance of developing timely biological markers for ASD, amplifying Disability Inclusion research, and personalizing mental health services to bridge these critical service gaps. These strategies, underpinned by interdisciplinary collaboration and telehealth innovation, particularly in low-resource settings, can offer a roadmap for inclusive, context-sensitive interventions at local levels that directly support SDG3's aim for health and well-being for all.

Age of autism diagnosis in Latin American and Caribbean countries

LAY ABSTRACT

An earlier diagnosis of autism spectrum disorder might lead to earlier intervention. However, people living in Latin American and Caribbean countries do not have much knowledge about autism spectrum disorder symptoms. It has been suggested that the older a child is when diagnosed, the fewer opportunities he or she will have to receive services. We asked 2520 caregivers of autistic children in six different Latin America and Caribbean Countries, the child's age when they noticed some developmental delays and their child's age when they received their first autism spectrum disorder diagnosis. Results indicate that, on average, caregivers were concerned about their child's development by 22 months of age; however, the diagnosis was received when the child was 46 months of age. In addition, older children with better language abilities and public health coverage (opposed to private health coverage) were diagnosed later. On the contrary, children with other medical problems and more severe behaviors received an earlier diagnosis. In our study, children were diagnosed around the time they entered formal schooling, delaying the access to early intervention programs. In summary, the characteristics of the autistic person and the type of health coverage influence the age of diagnosis in children living in Latin America and Caribbean Countries.

The Importance of Language Delays as an Early Indicator of Subsequent ASD Diagnosis in Public Healthcare Settings

Previous studies have reported that ASD children with more severe symptoms are diagnosed earlier. However, previous studies in community settings have mostly relied on retrospective parental reports without the use of quantitative standardized test scores. Here, we evaluated the association of language, cognitive, and ASD severity standardized scores with the age of diagnosis in 1-6-year-old children diagnosed in a public healthcare setting. The results revealed that language scores were the strongest variable associated with the age of diagnosis, explaining ~ 30% of the variability across children. Indeed, all children diagnosed before 30-months of age exhibited moderate-to-severe language delays. These results further substantiate the prominence of language delay as a highly visible symptom associated with earlier ASD diagnosis in community clinical settings.

Improving early detection, diagnosis and intervention for children with autism spectrum disorder: A cross-sectional survey in China

BACKGROUND

Detection and diagnosis of autism spectrum disorder (ASD) are prerequisites for early interventions. However, few studies focused on this topic.

AIM

This study aims to characterize the timing from symptom detection to intervention in children with ASD and identify predictors of age at ASD diagnosis, presence of intervention, and the time lag between detection and diagnosis.

METHODS AND PROCEDURES

A cross-sectional survey was conducted with 303 parents (111 fathers and 192 mothers, 21-54 years) of children with ASD in Guangzhou, China.

OUTCOMES AND RESULTS

The median time from symptom observation to the first doctor visit was 3 months, while the time to ASD diagnosis averaged 6 months. Most children (76.24 %) were diagnosed within one year after detection, and 25.58 % had no intervention after diagnosis. Predictors of earlier ASD diagnosis included ASD-related symptoms identified at an older age, less serious symptoms, and initial symptoms with atypical motor development and sensory anomalies. ASD-related symptoms observed at an older age, initial symptoms with social deficits, sensory anomalies, and without language impairment, primary caregivers other than parents, families with lower income, and less social support utilization increased the odds of a time lag between detection and diagnosis. Children with fathers having lower education were less likely to receive interventions.

CONCLUSIONS AND IMPLICATIONS

Earlier ASD identification and intervention might be facilitated by health education on typical symptoms of ASD for parents with young children and incorporating ASD screening during routine health examinations for children. For children whose primary caregivers are not their parents and from lower-income families, additional support may be required for timely diagnosis after reporting ASD-related symptoms. Moreover, more intervention supports are expected for children whose fathers have lower education levels. Helping families take full advantage of support is also important for early diagnosis and intervention.

Obtaining a First Diagnosis of Autism Spectrum Disorder: Descriptions of the Diagnostic Process and Correlates of Parent Satisfaction from a National Sample

Obtaining an autism spectrum disorder (ASD) diagnosis is often challenging for parents. The purpose of this study was to better understand this process and examine how elements of the process may influence parent satisfaction. A total of 406 parents of autistic children participated. Participants were administered a survey covering the ASD diagnostic process. Parents had developmental concerns early but experienced long wait times and usually attended many appointments. Mean diagnostic age was 3.26 years and overall delay was 1.20 years. Stress and being told there was "no problem" were significantly associated with parental satisfaction with the process. Findings provide insight into challenges experienced by families of autistic children and can help pinpoint areas where the diagnostic process may be improved.

Machine Learning Differentiation of Autism Spectrum Sub-Classifications

PURPOSE

Disorders on the autism spectrum have characteristics that can manifest as difficulties with communication, executive functioning, daily living, and more. These challenges can be mitigated with early identification. However, diagnostic criteria has changed from DSM-IV to DSM-5, which can make diagnosing a disorder on the autism spectrum complex. We evaluated machine learning to classify individuals as having one of three disorders of the autism spectrum under DSM-IV, or as non-spectrum.

METHODS

We employed machine learning to analyze retrospective data from 38,560 individuals. Inputs encompassed clinical, demographic, and assessment data.

RESULTS

The algorithm achieved AUROCs ranging from 0.863 to 0.980. The model correctly classified 80.5% individuals; 12.6% of individuals from this dataset were misclassified with another disorder on the autism spectrum.

CONCLUSION

Machine learning can classify individuals as having a disorder on the autism spectrum or as non-spectrum using minimal data inputs.

Autistic Traits and College Adjustment

This study evaluated the association of autistic traits (RAADS-14) with academic and social outcomes among college students using data from an online survey (N = 2,736). In the academic domain, the total trait score and all subscale scores (mentalizing deficits, social anxiety, sensory reactivity) were associated with course failure and academic difficulties independent of an autism diagnosis; the total score and mentalizing deficits also predicted lower grade point average (GPA). In the social domain, the total trait score and subscale scores were associated with lower odds of having a confidant, lower friendship quality, and higher odds of social exclusion. Subgroup analyses revealed that autistic traits had more consistently negative associations with social outcomes for students without an autism diagnosis than for students with a diagnosis. Associations were also more often significant for women than men. These results support the development of programs and services for students with autistic traits regardless of diagnostic status.

Delay from Screening to Diagnosis in Autism Spectrum Disorder: Results from a Large National Health Research Network

To examine delay from developmental screening to autism diagnosis, we used real-world health care data from a national research network to estimate the time between these events. We found an average delay of longer than 2 years from first screening to diagnosis, with no significant differences observed by sex, race, or ethnicity.

A Scoping Review of Diagnosis of Autism Spectrum Disorder in Primary Care

INTRODUCTION

This scoping review was performed to collect, examine, and present literature on interventions promoting the diagnosis of Autism Spectrum Disorder (ASD) in U.S. primary health care settings.

METHOD

The literature searched was from 2011-2022, in the English language, in PubMed, CINAHL, Psych INFO, Cochrane, and Web of Science, for persons with autism or ASD aged ≤ 18 years.

RESULTS

Six studies met the search criteria, including a quality improvement project, a feasibility study, a pilot study, and three primary care provider (PCP) intervention trials. Measured outcomes included: accuracy of diagnosis (n = 4), practice change maintenance (n = 3), time to diagnosis (n = 2), specialty clinic appointment wait time (n = 1), PCP comfort making ASD diagnosis (n = 1), and increased ASD diagnosis (n = 1).

DISCUSSION

Results inform future implementation of PCP ASD diagnosis for the most obvious cases of ASD and research evaluating PCP training, using longitudinal measures of PCP knowledge of ASD and intention to diagnose.

The first six months of life: A systematic review of early markers associated with later autism

There is now good evidence that behavioural signs of autism spectrum conditions (autism) emerge over the first two years of life. Identifying clear developmental differences early in life may facilitate earlier identification and intervention that can promote longer-term quality of life. Here we present a systematic review of studies investigating behavioural markers of later autism diagnosis or symptomology taken at 0-6 months. The following databases were searched for articles published between 01/01/2000 and 15/03/2022: Embase, Medline, Scopus, PubMed, PsycINFO, CINAHL, Web of Science and Proquest. Twenty-five studies met inclusion criteria: assessment of behaviour at 0-6 months and later assessment of autism symptomology or diagnosis. Studies examined behaviours of attention, early social and communication behaviours, and motor behaviours, as well as composite measures. Findings indicated some evidence of measures of general attention, attention to social stimuli, and motor behaviours associated with later autism diagnosis or symptomology. Findings were inconsistent regarding social and communication behaviours, with a lack of repeated or validated measures limiting drawing firm conclusions. We discuss implications of the findings and suggest recommendations for future research.

Sociocultural factors associated with detection of autism among culturally and linguistically diverse communities in Australia

BACKGROUND

The age at which parents or caregivers first develop concerns about their child's development has significant implications on formal diagnosis and intervention. This study aims to determine the sociocultural factors that are associated with the age and type of first concern reported by parents of autistic children among culturally and linguistically diverse (CALD) communities in Australia. We also assessed whether sociocultural factors predict autism traits measured in terms of social affect (SA), restricted and repetitive behaviours (RRB), and calibrated severity scores (CSS).

METHODS

This study is a secondary data analysis of the data collected from six Autism Specific Early Learning and Care Centres (ASELCCs) as part of the Autism Co-operative Research Centre (CRC) program between 2015 and 2019. Data analysed in this study included a family history questionnaire with sociodemographic and sociocultural information, parent-reported age and type of first concern, and clinician/researcher administered Autism Diagnostic Observation Schedule - Second Edition (ADOS-2) which includes standardised domain-wise scores of social affect (SA) and restricted and repetitive behaviours (RRB) as well as calibrated severity scores (CSS), a measure of severity of autism. Primary analysis included multivariable linear regression models to examine the predictive influence of sociodemographic and sociocultural factors on the dependant variables of age of concern (AOC) and the autism traits (SA, RRB, and CSS).

RESULTS

The mean AOC in the sample was 18.18 months and the most common concerns were speech/language delay, limited social interaction, and hyperactivity/behavioural changes. The multivariable linear regression models showed factors such as increase in age of child, those from a CALD background, annual family income, sibling's autism diagnosis, and developmental concerns to be significantly associated with parental AOC. Additionally, we also found that increase in child's age and CALD status to be significant predictors of autism trait (RRB) and severity measured in terms of the CSS score. Further, females (compared to males) were associated with higher difficulties with social communication and interaction skills.

CONCLUSION

Understanding key factors that contribute to early identification of autism can help tailor awareness programs for parents and caregivers, whilst also informing the development of services focused on serving all CALD communities.

Autistic clinical profiles, age at first concern, and diagnosis among children with autism spectrum disorder

Background

To explore the relationship between autistic clinical profiles and age at first concern and diagnosis among children with autism spectrum disorder. The clinical profiles included the severity of autism, cognition, adaptability, language development, and regression.

Methods

The multivariate linear regression model was used to examine the association of diagnostic age and first-concern age with autistic clinical profiles and with further stratification analysis.

Results

A total of 801 autistic children were included. Language delay and regression were associated with earlier diagnostic age (language delay: crudeβ: -0.80, 95%CI%: -0.92--0.68; regression: crudeβ: -0.21, 95%CI%: -0.43--0.00) and the age of first concern of autistic children (language delay: crudeβ: -0.55, 95%CI%: -0.65--0.45; regression: crudeβ: -0.17, 95%CI%: -0.34--0.00). After stratification by sex, language delay tended to be more associated with the earlier diagnostic age among boys (crudeβ: -0.85, 95%CI%: -0.98--0.72) than among girls (crudeβ: -0.46, 95%CI%: -0.77--0.16). After stratification by maternal education level or family income level, language delay was most associated with the earlier diagnostic age in autistic children from families with higher socioeconomic levels.

Conclusion

Language delay, rather than other symptoms, promoted an earlier diagnostic age. Among male autistic children or children from families with higher socioeconomic levels, language delay was most significantly associated with an earlier age of diagnosis. Cognitive delay, or adaptive delay, was associated with a later age at diagnosis and presented only in autistic children from families with lower socioeconomic levels. There may be sex or socioeconomic inequality in the diagnostic age for autistic children. More publicity and public education about the diversity of autistic symptoms are urgently needed in the future, especially for low-socioeconomic families.

Autism Prevalence and the Intersectionality of Assigned Sex at Birth, Race, and Ethnicity on Age of Diagnosis

PURPOSE

An official autism diagnosis is required to access timely intervention and is associated with better long-term wellbeing and mental health. Certain demographic characteristics, such as being female or a racially or ethnically minoritized youth, have been associated with significant diagnostic lag. However, it remains unclear how assigned sex, race, and ethnicity interact with each other in predicting the prevalence and age of autism diagnosis.

METHODS

To examine the interactions between assigned sex, race, and ethnicity, we used data from the National Survey of Children's Health (NSCH; 2016 > 2021).

RESULTS

One in 38 children had an autism diagnosis and 3.8 males were diagnosed per 1 female. Hierarchical linear regressions yielded diagnostic delays in some females, particularly those who were non-Hispanic white, Black, and Asian. Ethnic and racial minority children had significantly earlier diagnoses than white and non-Hispanic children when not accounting for sex.

CONCLUSION

This study demonstrates slight increases in reported autism prevalence, a diagnostic lag in some autistic females that was strongly associated with ethnicity, and earlier diagnoses in racial and ethnic minority youth, a finding that may be explained by factors associated with phenotypic differences. This study has important implications for the diagnosis of minority autistic youth, particularly females and females who are non-Hispanic, who may experience a greater propensity for diagnostic delays.

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.

ADHD and ASD symptoms in young males with fragile X syndrome: associations with early trajectories of inhibitory control

Inhibitory control (IC), the ability to suppress inappropriate responses, emerges late in the first year of life and improves across typical development, concurrent with brain maturation. The development of IC is critical to various social-emotional and behavioral functions, with IC difficulties being linked to numerous neurodevelopmental disorders, including attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD). Fragile X syndrome (FXS) is a single-gene disorder characterized by IC difficulties, and elevated rates of ADHD and ASD, making it a useful model for understanding the early development and consequences of IC. In this longitudinal study, we characterized IC trajectories across multiple time points between 16 and 71 months of age in young males with FXS (n = 79) relative to neurotypical (NT) controls (n=49). To explore the association between behavioral outcomes and IC, we identified a subsample of 50 children with longitudinal IC data and an outcome assessment for ADHD and ASD symptoms at age 5 (FXS: n = 26, NT: n = 24). Results indicated that, compared to their NT peers, young males with FXS exhibit differences in IC as early as 24 months, with group differences increasing through age 5. Additionally, we determined that lower IC levels at 24 months were associated with later ADHD symptoms and a decreasing slope in IC over time was associated with later ASD symptoms in male children with FXS. These findings help refine early developmental phenotypes of FXS and highlight IC as a potential target for early detection and intervention of ASD and ADHD symptoms in male children with FXS.

Association between maternal labour epidural analgesia and autistic traits in offspring

STUDY OBJECTIVE

Studies investigating associations between maternal epidural analgesia (MEA) and autism spectrum disorder (ASD) in the offspring are conflicting and lack prospective neurobehavioral follow-up assessments for autistic traits. We aim to prospectively investigate associations between MEA and autistic traits in the offspring.

DESIGN

Prospective neurobehavioral observational cohort study.

SETTING

Singaporean tertiary healthcare institutions.

PATIENTS

Participants recruited were singleton non-IVF children, >36 weeks gestation, delivered via normal vaginal delivery by mothers >18 years of age, delivered in Singapore from June 2009-September 2010 and followed up over 7 years.

INTERVENTIONS

Exposure to maternal epidural analgesia during delivery.

MEASUREMENTS

The primary outcome is an abnormal Social Responsiveness Scale (SRS) T score at 7 years (≥60 points). Secondary outcomes include the diagnosis of ASD and abnormal scores for autistic traits assessed via a neurobehavioral battery comprising: CBCL (child behavioural checklist), Q-CHAT (Quantitative Checklist for Autism in Toddlers), and Bayley-III. Multivariable analyses adjusting for maternal and offspring characteristics were performed.

MAIN RESULTS

704 out of 769 mother-child dyads recruited fulfilled the criteria for analysis. 365/704 mothers received MEA. The incidence of an abnormal SRS score at 7 years in offspring exposed to MEA was 19.9%, and 26.1% in non-exposed offspring (p = 0.154). Multivariable analysis did not demonstrate a significant association between MEA and abnormal SRS scores at 7 years (O.R.0.726, 95% C·I. 0.394-1.34, p = 0.305). After adjustment for maternal and fetal demographics, exposure to MEA was not significantly associated with an abnormal screen in all other tests for autistic traits. The clinical incidence of ASD was 1.76% in children without exposure to MEA, and 2.32% in children with MEA exposure (p = 0.506).

CONCLUSIONS

MEA is not significantly associated with the development of ASD and autistic traits in offspring, assessed over 7 years. Results should be taken into perspective given our wide confidence intervals and small cohort size.

Functional MRI responses to naturalistic stimuli are increasingly typical across early childhood

While findings show that throughout development, there are child- and age-specific patterns of brain functioning, there is also evidence for significantly greater inter-individual response variability in young children relative to adults. It is currently unclear whether this increase in functional "typicality" (i.e., inter-individual similarity) is a developmental process that occurs across early childhood, and what changes in BOLD response may be driving changes in typicality. We collected fMRI data from 81 typically developing 4-8-year-old children during passive viewing of age-appropriate television clips and asked whether there is increasing typicality of brain response across this age range. We found that the "increasing typicality" hypothesis was supported across many regions engaged by passive viewing. Post hoc analyses showed that in a priori ROIs related to language and face processing, the strength of the group-average shared component of activity increased with age, with no concomitant decline in residual signal or change in spatial extent or variability. Together, this suggests that increasing inter-individual similarity of functional responses to audiovisual stimuli is an important feature of early childhood functional brain development.

What does receiving autism diagnosis in adulthood look like? Stakeholders' experiences and inputs

INTRODUCTION

The age of diagnosis is crucial for optimal health outcomes; however, some individuals with Autism Spectrum Disorder (ASD) may not be diagnosed until adulthood. Limited information is available about the lived experience of receiving a diagnosis during adulthood. Thus, we aimed to investigate stakeholders' experiences about the ASD diagnosis during adulthood.

METHOD

We interviewed 18 individuals including 13 adults with ASD who had received a late diagnosis during adulthood and 5 parents of individuals with ASD from various Canadian provinces.

RESULTS

Using a thematic analysis, three main themes emerged: (a) noticing differences and similarities, (b) hindering elements to diagnosis, and (c) emotional response to diagnostic odyssey.

CONCLUSION

This study adds to the literature about experiences of receiving ASD diagnosis in adulthood. Given the impact of diagnosis on individuals, it is important to minimize the barriers to ensure individuals who require ASD-related supports can access them in a timely and effective manner. This study highlights the importance of receiving an ASD diagnosis and facilitates positive health outcomes. The findings from the current study can be used to guide adult diagnostic processes and practices to help make ASD diagnosis more accessible.

A Convolutional Neural Network-Based Connectivity Enhancement Approach for Autism Spectrum Disorder Detection

Autism spectrum disorder (ASD) represents an ongoing obstacle facing many researchers to achieving early diagnosis with high accuracy. To advance developments in ASD detection, the corroboration of findings presented in the existing body of autism-based literature is of high importance. Previous works put forward theories of under- and over-connectivity deficits in the autistic brain. An elimination approach based on methods that are theoretically comparable to the aforementioned theories proved the existence of these deficits. Therefore, in this paper, we propose a framework that takes into account the properties of under- and over-connectivity in the autistic brain using an enhancement approach coupled with deep learning through convolutional neural networks (CNN). In this approach, image-alike connectivity matrices are created, and then connections related to connectivity alterations are enhanced. The overall objective is the facilitation of early diagnosis of this disorder. After conducting tests using information from the large multi-site Autism Brain Imaging Data Exchange (ABIDE I) dataset, the results show that this approach provides an accurate prediction value reaching up to 96%.

Should We Continue to Tell Autistic People that Their Brains are Different?

Autism is often considered to reflect categorically 'different brains'. Neuropsychological research on autism spectrum disorder (ASD) however, has struggled to define this difference, or derive clear-cut boundaries between autism and non-autism. Consequently, restructuring or disbanding the ASD diagnosis is becoming increasingly advocated within research. Nonetheless, autism now exists as a salient social construction, of which 'difference' is a key facet. Clinical and educational professionals must influence this cautiously, as changes to autism's social construction may counterproductively affect the quality of life of autistic people. This paper therefore reviews ASD's value as both neuropsychological and social constructs. Although lacking neuropsychological validity, the autism label may be beneficial for autistic self-identity, reduction of stigma, and administering support. Whilst a shift away from case-control ASD research is warranted, lay notions of 'different brains' may be preserved.

Oscillatory biomarkers of autism: evidence from the innate visual fear evoking paradigm

Autism spectrum disorder (ASD) is a neurodevelopmental disorder with multiple associated deficits in both social and cognitive functioning. Diagnosing ASD usually relies on subjective clinical competencies, and research on objective criteria for diagnosing ASD in the early stage is still in its infancy. A recent animal study showed that the looming-evoked defensive response was impaired in mice with ASD, but whether the effect will be observed in human and contribute to finding a robust clinical neural biomarker remain unclear. Here, to investigate the looming-evoked defense response in humans, electroencephalogram responses toward looming and corresponding control stimuli (far and missing type) were recorded in children with ASD and typical developed (TD) children. Results revealed that alpha-band activity in the posterior brain region was strongly suppressed after looming stimuli in the TD group, but remained unchanged in the ASD group. This method could be a novel, objective way to detect ASD earlier. These findings suggest that further investigation of the neural mechanism underlying innate fear from the oscillatory view could be a helpful direction in the future.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11571-022-09839-6.

Adapting the preschool environment to the needs of children on the autism spectrum in Sweden: A quasi-experimental study

BACKGROUND

Children on the autism spectrum may receive Early Intensive Behavioural Intervention (EIBI) in Sweden to support development by providing learning opportunities. However, research suggests a need to improve the quality of their learning environment.

AIM

This pre-registered study (#NCT03634761) aimed to evaluate the Swedish Autism Program Environment Rating Scale (APERS-P-SE) as a means to promote the quality of the pre-school learning environment for children on the autism spectrum, along with outcomes for these children, and their pre-school staff.

MATERIAL AND METHODS

In a quasi-experimental study, pre-school staff (n = 35) conducted either EIBI supported by in-service training and on-site coaching based on APERS-P-SE assessment (at k = 9 preschools) or EIBI only (k = 8), during an 8-months period.

RESULTS

The quality of the immediate learning environment (primary outcome) increased significantly in the EIBI/APERS-P-SE preschools. However, changes in child and pre-school staff measures were not significant.

CONCLUSIONS AND SIGNIFICANCE

In-service training and on-site coaching based on APERS-P-SE assessments can increase the quality of the learning environment in Swedish pre-school. Studies of longer duration and larger sample size are required to determine if using the APERS-P-SE can also achieve desired behavioural change for children-, and impact pre-school staff applying EIBI.

Do Savant Syndrome and Autism Spectrum Disorders Share Sex Differences? A Comprehensive Review

Savant syndrome was described before autism. However, they soon became closely associated, as many of their symptoms (intellectual disability, repetitive behaviors, alterations in social communication, and islets of abilities) overlap. Only a few women with autism have been diagnosed with savant syndrome. The theories or hypotheses that attempt to explain savant syndrome, which are common in autism, present differential treatment according to sex. We postulate that savant syndrome associated with autism as well as autism in general is underdiagnosed in women.

Early Identification of Children at Risk of Communication Disorders: Introducing a Novel Battery of Dynamic Assessments for Infants

PURPOSE

Many children with communication disorders (CDs) experience lengthy gaps between parental reporting of concerns and formal identification by professionals. This means that children with CDs are denied access to early interventions that may help support the development of communication skills and prevent possible negative sequelae associated with long-term outcomes. This may be due, in part, to the lack of assessment instruments available for children younger than 3 years of age. This study therefore reports on promising preliminary data from a novel set of valid dynamic assessment (DA) measures designed for infants.

METHOD

We recruited 53 low-risk children and two groups of children considered to be at high risk for CDs (n = 17, social high risk, and n = 22, language high risk) due to family members with language and social communication difficulties. The children were between 1 and 2 years of age and were assessed using a battery of five DA tasks related to receptive vocabulary, motor imitation, response to joint attention, turn taking, and social requesting. A set of standardized measures were also used.

RESULTS

The DA tasks showed high levels of interrater reliability and relationships with age across a cross-sectional sample of children from the low-risk group. Three tasks showed moderate to strong correlations with standardized measures taken at the same age, with particularly strong correlations between the DA of receptive vocabulary and other receptive language measures. The DA of receptive vocabulary was also the only task to discriminate between the three risk groups, with the social high risk group scoring lower.

CONCLUSIONS

These results provide preliminary information about early DA tasks, forming the basis for further research into their utility. DA tasks might eventually facilitate the development of new methods for detecting CDs in very young children, allowing earlier intervention and support.

Application of symbolic play test in identification of autism spectrum disorder without global developmental delay and developmental language disorder

BACKGROUND

Children with autism spectrum disorders (ASD) usually experience difficulty regarding symbolic play. However, studies on whether symbolic play test (SPT) can differentiate between ASD and other developmental disorders are inconsistent, and evaluating the application value of the SPT in the identification of ASD without global developmental delay (GDD) and developmental language disorder (DLD) is necessary.

METHODS

A total of 200 children were selected as the research participants. There were 100 cases of ASD without GDD and 100 cases of DLD. All children were tested by SPT and Children Neuropsychological and Behavioral Scale-Revision (CNBS-R2016). Binomial logistic regression was used for multivariate analysis. The receiver operating characteristic (ROC) curve was used to evaluate the value of SPT in identifying ASD without GDD and DLD.

RESULTS

SPT equivalent age was lower than chronological age in the two groups, the difference between the ASD without GDD group was greater than that in the DLD group, and the proportion of SPT equivalent age retardation was higher than that in the DLD group; the differences were statistically significant. Logistic regression analysis showed that there was a difference in SPT equivalent age between DLD and ASD without GDD. When the cut-off value of the SPT was 8.5, the largest area under the ROC curve was 0.723, and the sensitivity and specificity for the diagnosis of ASD without GDD were 0.720 and 0.620 respectively.

CONCLUSIONS

Symbolic play ability in ASD children is worse than that of DLD children at comparable development levels. SPT may be helpful to distinguish ASD without GDD from children with DLD.

Centering the Inner Experience of Autism: Development of the Self-Assessment of Autistic Traits

Current tools for identifying autism are critiqued for their lack of specificity and sensitivity, especially in autistic people who are older, have higher verbal ability or significant compensatory skills, and are not cisgender boys. This may reflect the following: the historical focus of autism research on White (cisgender) male, upper and middle class children; limited interest in the inner, lived experience of autism; and the predominance of a deficit-based model of autism. We report here on the first attempt of which we are aware to develop a clinical self-report measure of autistic traits as described by autistic people. We believe this is an advance in methodology because prior work in the development of autistic trait/diagnostic measures has prioritized the perspectives of nonautistic clinicians and scientists. The measure was developed under the leadership of two autistic researchers and constructed by leveraging descriptions of autism by autistic people to generate items designed to encompass the range of the autistic experience, using strength-based, accessible language. The team utilized iterative feedback from a panel of autistic experts to refine and enhance the measure, called the Self Assessment of Autistic Traits (SAAT). It is intended for people 16 years or older and uses a format that is designed to increase its accessibility and acceptability for autistic respondents. Future work will report on the preliminary psychometrics of the SAAT, with a long-term goal of advancing our understanding of the inner autistic experience and enhancing the clinical and scientific assessment of autism.

The Development and Validation of a Subscale for the School-Age Child Behavior CheckList to Screen for Autism Spectrum Disorder

The first aim of this study was to construct/validate a subscale-with cut-offs considering gender/age differences-for the school-age Child Behavior CheckList (CBCL) to screen for Autism Spectrum Disorder (ASD) applying both data-driven (N = 1666) and clinician-expert (N = 15) approaches. Further, we compared these to previously established CBCL ASD profiles/subscales and DSM-oriented subscales. The second aim was to cross-validate results in two truly independent samples (N = 2445 and 886). Despite relatively low discriminative power of all subscales in the cross-validation samples, results indicated that the data-driven subscale had the best potential to screen for ASD and a similar screening potential as the DSM-oriented subscales. Given beneficial implications for pediatric/clinical practice, we encourage colleagues to continue the validation of this CBCL ASD subscale.

Predictors of an earlier diagnosis of Autism Spectrum Disorder in children and adolescents: a systematic review (1987-2017)

Autism Spectrum Disorder (ASD) is an early onset neurodevelopmental disorder in which the first signs generally emerge at approximately 12 months of age but its diagnosis is feasible only from the age of 18 months. According to the literature, the average age of diagnosis ranges from 2.7 to 7.2 years, which raises the question of factors associated with early diagnosis as a condition for early intervention. In this systematic review, we aim to identify clinical, social, and environmental factors associated with the age at which the diagnosis of ASD is confirmed in children. A literature search was performed in the Pubmed, Web of Sciences, PsycInfo, and Cochrane databases. Among the 530 publications identified, 50 were selected according to the inclusion criteria. This review focuses on studies conducted in 21 countries using data collected over a period from 1987 to 2017. These studies were published before December 31st, 2019. The results suggest that the diagnosis of ASD occurs earlier if there is a delay in social communication or the presence of intellectual disability. There is a low level of evidence concerning associations between the age at diagnosis and sex, race, parental education, or socioeconomic status and accessibility to health care. Further studies using large and well-characterized data sets are needed to simultaneously explore clinical and socio-environmental factors involved in early diagnosis.

Translating advances in developmental social neuroscience into greater access to early diagnosis in autism spectrum disorder

Early identification and diagnosis of autism spectrum disorder (ASD) is necessary to promote access to early treatment, a critical factor in optimizing children's lifetime outcomes. And yet, diagnosis is often late, delaying interventions to a time in which symptoms have aggravated and communication skills already show impairing differences. This review illustrates progress in developmental social neuroscience that shows promise in generating novel tools for objective and cost-effective early diagnosis of ASD. We focus on research of social visual engagement, which is the way infants and toddlers look at and learn from their social environment. Moment-by-moment quantification of social visual engagement is yielding measures that are beginning to approximate best-practice procedures used by experienced clinicians in the assessment of young children. This progress and potential solutions have public health import ance because experienced clinicians are limited in number, and specialized clinical assessment services tend to be lengthy, costly, and plagued by extended wait time, all of which contributing to limited access, particularly in the case of low-resource families. The research reviewed here illustrates a wider effort to advance biomarker-based measurements intended to develop better and more efficient tools and procedures for screening, diagnosing and monitoring treatment response in children with ASD. The advent of such tools could increase access to early diagnostic services and promote efficiencies in early treatment delivery, with the ultimate goal of ensuring that children with ASD are afforded the services they need to thrive.

Invisible Disabilities and Inequality

In this address, I consider the realized and potential contributions of sociological social psychology to research on inequality based on invisible disabilities and the challenges that invisible disabilities pose to current social psychological theories. Drawing from the social structure and personality framework, I advance the general notion of invisible disability as a dimension of inequality, consider how four basic social psychological processes (social categorization, identity, status, and stigmatization) have and can help us understand how invisible disabilities shape outcomes over the life course, and suggest new lines of research social psychologists could pursue. I close with brief comments about the benefits of such an agenda for sociological social psychology as well as how these lines of research can inform theories of stratification.