Agreement between concern about autism spectrum disorder at the time of referral and diagnosis, and factors associated with agreement

Access to child developmental assessment services in culturally and linguistically diverse metropolitan Sydney: a retrospective cohort analysis

BACKGROUND

Despite the increasing prevalence of neurodevelopmental disorders (NDD), data regarding access to child development services have remained limited globally. Long wait times are a major barrier to developmental assessments, impacting on care and outcomes. The aim is to retrospectively analyse the demographic profile and prioritisation of patients seen at a child developmental assessment service (CDAS) in a vulnerable region of Sydney, and explore factors affecting wait times.

METHODS

Data was collated and analysed for 2354 patients from 2018 to 2022. Socio-Economic Indexes for Areas (SEIFA) were collated from the Australian Bureau of Statistics. Descriptive statistics were used for demographic data and various statistical methods were used to analyse the relationships and impact of factors likely to affect wait lists.

RESULTS

The median age was 51 months (IQR41-61) and males comprised 73.7% of the cohort. 64% of children were from culturally and linguistically diverse backgrounds (CALD) and 47% lived in the most disadvantaged suburbs. The median wait time was 302.5 days (IQR175-379) and 70% of children were seen within 12 months. CALD patients and children over 5-years had shorter wait times. Most children with Global Developmental Delay (GDD) were from the lowest four SEIFA deciles and waited longer for an appointment. 42.6% were seen within the priority allocated time or sooner. Children with ASD and/or severe GDD were prioritised to be seen earlier. Overall, the study could not demonstrate any difference in the wait times according to the prioritisation groups.

CONCLUSION

This study provides insights into the profile, prioritisation processes and wait lists of children seen by CDAS in South Western Sydney with high rates of social vulnerability and presents an argument to discuss benchmarking targets with service providers. It identifies the need to prioritise children living in suburbs with socioeconomic disadvantage and refine prioritisation and data collection processes to improve wait times.

Mental health concerns in children with neurodevelopmental conditions attending a developmental assessment service

Children with neurodevelopmental conditions (NDCs) experience co-occurring mental health concerns. Little research has examined mental health symptoms in children attending developmental assessment services. This study profiled mental health symptoms in children with NDCs attending a hospital-based diagnostic service for their first diagnostic assessment. Participants were 232 children aged 1.96-17.51 years. Mental health concerns were assessed using the Child Behavior Checklist (CBCL), a caregiver-rated, questionnaire-based assessment of behavioural and emotional difficulties. Subclinical or clinically elevated internalising, externalising and total scores on the CBCL were reported in over one third of children. These increased prevalence rates remained after excluding items specifically relating to neurodevelopmental concerns. More school-aged females reported elevated internalising problems, relative to males (67 % vs 48 %). The number of diagnoses impacted symptoms, with children who received two or more DSM-5 diagnoses showing a greater rate of subclinical or clinically elevated scores, relative to children who received one DSM-5 diagnosis. Our findings demonstrate that children attending developmental assessment services have considerable mental health needs. It is critical that mental health concerns are identified and addressed in children when they first present to developmental assessment services, and that service providers are equipped to provide appropriate resources and pathways to ongoing care.

Do Referral Factors Predict a Probable Autism Spectrum Disorder Diagnosis? A DBPNet Study

OBJECTIVE

To determine the proportion of children referred to academic medical centers with concerns about autism spectrum disorders (ASDs) who received a probable ASD diagnosis, identify factors predicting ASD diagnosis, and describe the children with ASD concerns who were not found to have autism.

METHODS

A total of 55 developmental-behavioral pediatricians (DBP) at 12 academic sites in the DBPNet research network recorded data on ≤15 consecutive new patients. They coded presumed diagnoses after their first visit with the child.

RESULTS

Of 784 new visits, 324 (41%) had concern for ASD; of these, 221 (68%) were presumptively ASD+; 103 (32%) were ASD-. In a mixed model accounting for clustering within site and covariates significant in bivariate analysis, significant predictors of receiving a presumptive ASD diagnoses were socialization concerns, languages other than English spoken in the home, and coming for second opinion. Also concern for "other behavior problems" (not mood, oppositionality, anxiety, attention, or repetitive behaviors) predicted not receiving ASD diagnoses. This model was not clinically useful because it misclassified 26.9% of children. ASD- children <4 years old had more language delay and less cognitive impairment and socialization concern than their ASD+ age peers. ASD- children ≥4 years old were more likely to have attention-deficit /hyperactivity disorder (ADHD) and learning disability with normal cognition than their ASD+ age peers.

CONCLUSIONS

Two thirds of children referred to academic centers with concern for ASD received a presumptive diagnosis of ASD. While those with ASD were not easily distinguished from those without ASD at referral, virtually all children with ASD concerns had multiple DBP diagnoses made and required DBP follow-up care.

Associations Among Referral Concerns, Screening Results, and Diagnostic Outcomes of Young Children Assessed in a Statewide Early Autism Evaluation Network

OBJECTIVES

To examine associations between referral concerns, screening results, and diagnostic outcomes for young children evaluated across a statewide primary care network for early screening and diagnosis of autism spectrum disorder (ASD).

STUDY DESIGN

The Early Autism Evaluation Hub system was developed to increase developmental screening and improve access to timely ASD evaluations in local communities. In 2019, 858 children (ages 18-48 months; 40% diagnosed with ASD) received ASD evaluations across 12 Early Autism Evaluation Hubs. Data on primary care provider (PCP)- and caregiver-reported referral concerns, Modified Checklist for Autism in Toddlers, Revised with Follow-Up (MCHAT-R/F) and Ages and Stages Questionnaire, Third Edition (ASQ-3), and diagnostic outcome were collected.

RESULTS

Among children evaluated, there was low concordance between PCP and caregiver referral concern. Although a positive MCHAT-R/F screen was associated with PCP but not caregiver-reported ASD referral concern, there was a significant linear relationship between MCHAT-R/F raw scores and both PCP and caregiver ASD referral concern. A different pattern of ASQ-3 delays was found to be associated with PCP-reported as compared with caregiver-reported ASD referral concern. Finally, PCP-reported ASD referral concern, positive MCHAT-R/F, and ASQ-3 Communication and Personal Social delays were associated with a significantly higher likelihood of subsequent ASD diagnosis.

CONCLUSIONS

Understanding how community PCPs use surveillance and screening data, the extent to which PCPs and caregivers have shared understanding and engage in collaborative decision-making about evaluation referral, and how these factors relate to diagnostic outcomes has the potential to impact educational efforts for both PCPs and caregivers of young children, as well as inform the development of more efficacious early identification approaches.

The Route to Autism Spectrum Diagnosis in Pediatric Practice in Bulgaria

Diagnosis of autism spectrum disorder (ASD) before the age of three years is a challenge. Analyzing the present practice may help reaching that goal. Aim: To investigate developmental abnormalities and diagnostic pathway of ASD patients in pediatric practice. Methods: Retrospective cross-sectional study of 192 children aged 13 months to 17 years 11 months (average 4 years 9 months), investigated in an outpatient and hospital setting from January 2015 to June 2018 by a semi-structured history and clinical examination, and diagnosed with ASD by Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) criteria. Results: Behavioral peculiarities were detected in the history of the first two years of life in 74.8% of the subjects. The first developmental abnormalities were noticed by the parents at ages from 8 to 36 months (mean 15.6 months) and were predominantly in speech (in 94.6%) and non-verbal communication (11.3%). Developmental regression was reported in 42.1% of the patients occurring between the ages of 6 and 50 months (mean 17.9 months), affecting most commonly speech (88.4% of cases), non-verbal communication (29.2%), and behavior (12.8%). By history, the first manifestations of ASD were noticed at ages from 8 months to 84 months (mean 18.5 months), and were disorders of expressive speech (in 66.7% of cases), receptive speech (in 45.8%), non-verbal communication (35.4%), behavior (27.6%), play (8.9%), socialization (5.7%), and joint attention (2.1%). The most common motive for specialized consultation was delay in language development—in 84.6% of children. The age of ASD diagnosis varied between 12 and 132 months (mean 39.7 months), and the time period between first ASD manifestations and diagnosis was in the range of 0 to 79 months (mean 23.3 months). Many symptoms of abnormal social communication, unnoticed by parents, were detected objectively in more than 95% of the cases—absent or rare spontaneous or reciprocal smile; lack of sharing of interest or affect; abnormal eye contact; lack of finger pointing; lack of gaze to a pointed object; poor facial expressions; lack of imaginary play, etc. Conclusions: Almost two years are needed for diagnosing abnormal development in other domains besides speech in ASD patients. Diagnosis before the age of three years can be achieved by focusing parents’ and pediatricians’ attention on social communication and behavior in patients with speech delay or developmental regression.

Referral, Assessment and Use of Screening Measures Related to Autism Spectrum Disorder at a Tertiary Hospital Setting

Children with developmental concerns in Australia continue to experience inequitable healthcare and service-related delays, even when diagnostic risk is identified. This study sought to explore service and demographic pathway factors leading up to autism spectrum disorder (ASD) assessment, including value of screening measures applied at triage. Following a trial of centralised intake for referred young children with suspected ASD, observational, retrospective pathway data was explored using bivariate and regression analyses. The mean age of 159 children referred with autism symptoms was 3.6 years, and 64% were diagnosed with ASD. Service allocation was associated with diagnosis, whilst screening tool results were not. Improved pathways are needed to limit wasted waiting times and direct each child to needs-based services.

Atypicalities in sleep and semantic consolidation in autism

Sleep is known to support the neocortical consolidation of declarative memory, including the acquisition of new language. Autism spectrum disorder (ASD) is often characterized by both sleep and language learning difficulties, but few studies have explored a potential connection between the two. Here, 54 children with and without ASD (matched on age, nonverbal ability and vocabulary) were taught nine rare animal names (e.g., pipa). Memory was assessed via definitions, naming and speeded semantic decision tasks immediately after learning (pre‐sleep), the next day (post‐sleep, with a night of polysomnography between pre‐ and post‐sleep tests) and roughly 1 month later (follow‐up). Both groups showed comparable performance at pre‐test and similar levels of overnight change on all tasks; but at follow‐up children with ASD showed significantly greater forgetting of the unique features of the new animals (e.g., pipa is a flat frog). Children with ASD had significantly lower central non‐rapid eye movement (NREM) sigma power. Associations between spindle properties and overnight changes in speeded semantic decisions differed by group. For the TD group, spindle duration predicted overnight changes in responses to novel animals but not familiar animals, reinforcing a role for sleep in the stabilization of new semantic knowledge. For the ASD group, sigma power and spindle duration were associated with improvements in responses to novel and particularly familiar animals, perhaps reflecting more general sleep‐associated improvements in task performance. Plausibly, microstructural sleep atypicalities in children with ASD and differences in how information is prioritized for consolidation may lead to cumulative consolidation difficulties, compromising the quality of newly formed semantic representations in long‐term memory.

Risk Assessment for Parents Who Suspect Their Child Has Autism Spectrum Disorder: Machine Learning Approach

Background

Parents are likely to seek Web-based communities to verify their suspicions of autism spectrum disorder markers in their child. Automated tools support human decisions in many domains and could therefore potentially support concerned parents.

Objective

The objective of this study was to test the feasibility of assessing autism spectrum disorder risk in parental concerns from Web-based sources, using automated text analysis tools and minimal standard questioning.

Methods

Participants were 115 parents with concerns regarding their child’s social-communication development. Children were 16- to 30-months old, and 57.4% (66/115) had a family history of autism spectrum disorder. Parents reported their concerns online, and completed an autism spectrum disorder-specific screener, the Modified Checklist for Autism in Toddlers-Revised, with Follow-up (M-CHAT-R/F), and a broad developmental screener, the Ages and Stages Questionnaire (ASQ). An algorithm predicted autism spectrum disorder risk using a combination of the parent's text and a single screening question, selected by the algorithm to enhance prediction accuracy.

Results

Screening measures identified 58% (67/115) to 88% (101/115) of children at risk for autism spectrum disorder. Children with a family history of autism spectrum disorder were 3 times more likely to show autism spectrum disorder risk on screening measures. The prediction of a child’s risk on the ASQ or M-CHAT-R was significantly more accurate when predicted from text combined with an M-CHAT-R question selected (automatically) than from the text alone. The frequently automatically selected M-CHAT-R questions that predicted risk were: following a point, make-believe play, and concern about deafness.

Conclusions

The internet can be harnessed to prescreen for autism spectrum disorder using parental concerns by administering a few standardized screening questions to augment this process.