Diagnostic Accuracy of the Social Attention and Communication Surveillance-Revised With Preschool Tool for Early Autism Detection in Very Young Children

Can combining existing behavioral tools improve identification of infants at elevated likelihood of autism in the first year of life?

LAY ABSTRACT

Many families have concerns about their infants' development in the first year of life. Current screeners cannot tell whether these differences might be related to autism, developmental delays, or likely to resolve on their own. As a result, many families are told to "wait and see." In this study, we looked at whether combining multiple behavior measures can improve prediction of outcomes in toddlerhood. This could help to provide families with more information about the significance of early behavioral differences. We assessed 256 infants with an older autistic sibling at 6, 9, and 12 months. We created three markers of behavioral differences at these ages. We looked at whether infants who had two or more markers were more likely to be on the autism spectrum or have other developmental differences than to have typically developing outcomes at 36 months. We found that very few infants had more than one marker at any age. However, infants who showed two or more markers were more likely to be on the spectrum or have other developmental differences at 36 months than infants who showed only one marker. These findings suggest that when behavioral differences are present on multiple measures, there is no need to wait and see before referring for services.

An association between auditory responsiveness of children and duration of entertainment screen time in the early years of life

OBJECTIVE

To examine whether the responsiveness of young children to simple sounds was associated with entertainment screen time (EST), opportunities for social interaction, and social and communication skills.

DESIGN

Parents completed a questionnaire covering, for years one and two, the number of times the child met with other children; the number of words the child spoke; and the daily amount of EST. Social, attention and communication skills were assessed.

STUDY SAMPLE

Participants were 118 children, aged 15 to 46 months. They were initially assessed behaviourally using simple sounds. Children who responded to such sounds were denoted the Responsive group. Children who did not were assessed using familiar songs and denoted the Unresponsive group.

RESULTS

The two groups did not differ significantly in mean age or the number of opportunities to meet other children. The Unresponsive group had significantly fewer words than the Responsive group at 12 and 24 months and had significantly higher EST than the Responsive group for years 1 and 2. The Unresponsive group showed lower social, attention and communication skills than the Responsive group.

CONCLUSIONS

High EST was associated with poorer auditory and social skills. Hence, it may be wise to limit the EST of young children.

Machine Learning Prediction of Autism Spectrum Disorder From a Minimal Set of Medical and Background Information

Importance

Early identification of the likelihood of autism spectrum disorder (ASD) using minimal information is crucial for early diagnosis and intervention, which can affect developmental outcomes.

Objective

To develop and validate a machine learning (ML) model for predicting ASD using a minimal set of features from background and medical information and to evaluate the predictors and the utility of the ML model.

Design, Setting, and Participants

For this diagnostic study, a retrospective analysis of the Simons Foundation Powering Autism Research for Knowledge (SPARK) database, version 8 (released June 6, 2022), was conducted, including data from 30 660 participants after adjustments for missing values and class imbalances (15 330 with ASD and 15 330 without ASD). The SPARK database contains participants recruited from 31 university-affiliated research clinicals and online in 26 states in the US. All individuals with a professional ASD diagnosis and their families were eligible to participate. The model performance was validated on independent datasets from SPARK, version 10 (released July 21, 2023), and the Simons Simplex Collection (SSC), consisting of 14 790 participants, followed by phenotypic associations.

Exposures

Twenty-eight basic medical screening and background history items present before 24 months of age.

Main Outcomes and Measures

Generalizable ML prediction models were developed for detecting ASD using 4 algorithms (logistic regression, decision tree, random forest, and eXtreme Gradient Boosting [XGBoost]). Performance metrics included accuracy, area under the receiver operating characteristics curve (AUROC), sensitivity, specificity, positive predictive value (PPV), and F1 score, offering a comprehensive assessment of the predictive accuracy of the model. Explainable AI methods were applied to determine the effect of individual features in predicting ASD as secondary outcomes, enhancing the interpretability of the best-performing model. The secondary outcome analyses were further complemented by examining differences in various phenotypic measures using nonparametric statistical methods, providing insights into the ability of the model to differentiate between different presentations of ASD.

Results

The study included 19 477 (63.5%) male and 11 183 (36.5%) female participants (mean [SD] age, 106 [62] months). The mean (SD) age was 113 (68) months for the ASD group and 100 (55) months for the non-ASD group. The XGBoost (termed AutMedAI) model demonstrated strong performance with an AUROC score of 0.895, sensitivity of 0.805, specificity of 0.829, and PPV of 0.897. Developmental milestones and eating behavior were the most important predictors. Validation on independent cohorts showed an AUROC of 0.790, indicating good generalizability.

Conclusions and Relevance

In this diagnostic study of ML prediction of ASD, robust model performance was observed to identify autistic individuals with more symptoms and lower cognitive levels. The robustness and ML model generalizability results are promising for further validation and use in clinical and population settings.

Leisure, Employment, Community Participation, and Quality of Life in Primary Caregivers of Autistic Children: A Qualitative Study

PURPOSE

In prioritising the needs of their autistic children, parents often modify their own participation across leisure, social, and workforce activities. Few studies have examined the impact these modifications have on caregiver quality of life (QoL). The aim in the current study was to examine how parenting their autistic child/ren impacts parent's participation and QoL.

METHODS

Twenty primary caregivers (29-48 years, all female) of autistic children (7-11 years) were interviewed online about their participation in leisure, community, and employment activities including the impact of COVID-19.

RESULTS

Five themes with underlying subthemes were identified using reflexive thematic analysis. The themes were: (1) Reflecting on the important things in life, (2) Getting access to everything needed, (3) Barriers to participation in meaningful activities, (4) Facilitators of participation in meaningful activities, and (5) Participation through the COVID-19 pandemic.

CONCLUSION

The findings highlight the importance of regular participation in meaningful activities for parents of autistic children and the support needed by them, particularly single parents, to achieve balance between meeting caring responsibilities and their own participation needs.

Child and caregiver predictors of primary caregiver participation in families of school-aged Autistic children

Engaging in meaningful activities (e.g., leisure, spiritual, fitness) significantly affects caregivers' quality of life (QoL), yet the determinants of participation in caregivers of Autistic children remain largely unknown. The current study examined child and caregiver correlates of primary caregiver participation in meaningful activities. One hundred and six primary caregivers of Autistic children (7-12 years) were recruited from three unique cohorts of Autistic children in this cross-sectional study. Primary caregivers completed online questionnaires measuring occupational gaps (i.e., desired activities caregivers are not participating in), QoL, parenting stress, perceived family outcomes, and social support. In addition to undertaking direct assessments of children's cognition and language, primary caregivers also reported on their child's adaptive behavior, social-emotional skills, and participation. Caregivers reporting fewer occupational gaps (i.e., ≤2 desired activities) were more likely to have Autistic children with no co-occurring conditions, who were older, and with better adaptive behaviors, social-emotional skills, and more frequent home and school participation, compared to caregivers reporting many gaps (i.e., ≥3 desired activities). Caregivers with fewer occupational gaps also reported improved QoL, parenting stress, social support, perceived community inclusiveness, and family outcomes. Logistic regression analysis identified child age, child adaptive behavior, social-emotional skills, home participation, and the caregivers' perceived family outcomes and QoL as important predictors of their occupational gaps. The findings demonstrate that caregiver participation in desired activities was associated with increased functional ability and independence of the child, as well as their perceived capacity to meet their child's needs. Supporting parents' sense of efficacy in meeting their children's needs and building their skills and knowledge will serve to improve both caregiver and child outcomes.

Early Detection of 5 Neurodevelopmental Disorders of Children and Prevention of Postnatal Depression With a Mobile Health App: Observational Cross-Sectional Study

BACKGROUND

Delay in the diagnosis of neurodevelopmental disorders (NDDs) in toddlers and postnatal depression (PND) is a major public health issue. In both cases, early intervention is crucial but too rarely implemented in practice.

OBJECTIVE

Our goal was to determine if a dedicated mobile app can improve screening of 5 NDDs (autism spectrum disorder [ASD], language delay, dyspraxia, dyslexia, and attention-deficit/hyperactivity disorder [ADHD]) and reduce PND incidence.

METHODS

We performed an observational, cross-sectional, data-based study in a population of young parents in France with at least 1 child aged <10 years at the time of inclusion and regularly using Malo, an "all-in-one" multidomain digital health record electronic patient-reported outcome (PRO) app for smartphones. We included the first 50,000 users matching the criteria and agreeing to participate between May 1, 2022, and February 8, 2024. Parents received periodic questionnaires assessing skills in neurodevelopment domains via the app. Mothers accessed a support program to prevent PND and were requested to answer regular PND questionnaires. When any PROs matched predefined criteria, an in-app recommendation was sent to book an appointment with a family physician or pediatrician. The main outcomes were the median age of the infant at the time of notification for possible NDD and the incidence of PND detection after childbirth. One secondary outcome was the relevance of the NDD notification by consultation as assessed by health professionals.

RESULTS

Among 55,618 children median age 4 months (IQR 9), 439 (0.8%) had at least 1 disorder for which consultation was critically necessary. The median ages of notification for probable ASD, language delay, dyspraxia, dyslexia, and ADHD were 32.5 (IQR 12.8), 16 (IQR 13), 36 (IQR 22.5), 80 (IQR 5), and 61 (IQR 15.5) months, respectively. The rate of probable ADHD, ASD, dyslexia, language delay, and dyspraxia in the population of children of the age included between the detection limits of each alert was 1.48%, 0.21%, 1.52%, 0.91%, and 0.37%, respectively. Sensitivity of alert notifications for suspected NDDs as assessed by the physicians was 78.6% and specificity was 98.2%. Among 8243 mothers who completed a PND questionnaire, highly probable PND was detected in 938 (11.4%), corresponding to a reduction of -31% versus our previous study without a support program. Suspected PND was detected a median 96 days (IQR 86) after childbirth. Among 130 users who filled in the satisfaction survey, 99.2% (129/130) found the app easy to use and 70% (91/130) reported that the app improved follow-up of their child. The app was rated 4.8/5 on Apple's App Store.

CONCLUSIONS

Algorithm-based early alerts suggesting NDDs were highly specific with good sensitivity as assessed by real-life practitioners. Early detection of 5 NDDs and PNDs was efficient and led to a possible 31% reduction in PND incidence.

TRIAL REGISTRATION

ClinicalTrials.gov NCT06301087; https://www.clinicaltrials.gov/study/NCT06301087.

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.

Leisure, community, workforce participation and quality of life in primary and secondary caregivers of autistic children

Parents of Autistic children often modify their participation in leisure, social, and employment activities to meet the caregiving needs of their child. However, few studies have examined the impact this has on caregiver quality of life (QoL). The aim in the current study was to examine the role of participation in a range of activities on QoL amongst primary and secondary caregivers of school-aged Autistic children. Eighty-eight primary (93% mothers) and 63 secondary (91% fathers) caregivers of Autistic children (aged 7- to 12-years) participated in this cross-sectional study, with time pressure, participation, social support, parenting stress, and QoL measured via an online questionnaire. Compared to secondary caregivers, primary caregivers reported fewer employment hours, increased time pressure, less participation in desired activities, and higher perceived responsibility of domestic and child-rearing tasks. Similar levels of leisure frequency, parenting stress, and QoL were identified by both caregivers. Hierarchical regression revealed caregiver participation as important for QoL in both primary and secondary caregivers. However, when measures of caregiver well-being were added to the model, the unique contribution of participation to QoL was reduced, particularly for secondary caregivers. Overall, the findings demonstrate that despite differences in caregiver roles and responsibilities, participation in meaningful activities was important for QoL in all caregivers.

Screening for Autism: A Review of the Current State, Ongoing Challenges, and Novel Approaches on the Horizon

Screening for autism is recommended in pediatric primary care. However, the median age of autism spectrum disorder (ASD) diagnosis is substantially higher than the age at which autism can reliably be identified, suggesting room for improvements in autism recognition at young ages, especially for children from minoritized racial and ethnic groups, low-income families, and families who prefer a language other than English. Novel approaches are being developed to utilize new technologies in aiding in autism recognition. However, attention to equity is needed to minimize bias. Additional research on the benefits and potential harms of universal autism screening is needed. The authors provide suggestions for pediatricians who are considering implementing autism-screening programs.

Screening and diagnostic tools for autism spectrum disorder: Systematic review and meta-analysis

INTRODUCTION

Autism Spectrum Disorder (ASD) is a heterogeneous neurodevelopmental disorder, with main manifestations related to communication, social interaction, and behavioral patterns. The slight dynamics of change in the child over time require that the onset of clinical manifestations presented by the child be more valued, with the aim of stabilizing the condition. Faced with a variety of methods for diagnosing ASD, the question arises as to which method should be used. This systematic review aims to recommend the best tools to perform screening and diagnosis.

METHODOLOGY

This systematic review followed the PRISMA guidelines. The databases MEDLINE, Embase, CENTRAL (Cochrane), and Lilacs were accessed, and gray and manual searches were performed. The search strategy was created with terms referring to autism and the diagnosis/broad filter. The studies were qualitatively evaluated and quantitatively. Statistical analysis was performed using Meta-diSc-2.0 software, the confidence interval was 95 %.

RESULTS

The M-CHAT-R/F tool demonstrated a sensitivity of 78 % (95 % CI 0.57‒0.91) and specificity of 0.98 (95 % CI 0.88-1.00). The diagnostic tools demonstrated sensitivity and specificity respectively of: ADOS, sensitivity of 87 % (95 % CI 0.79‒0.92) and specificity 75 % (95 % CI 0.73‒0.78); ADI-R demonstrated test sensitivity of 77 % (95 % CI 0.56‒0.90) and specificity 68 % (95 % CI 0.52‒0.81), CARS test sensitivity was 89 % (95 % CI 0.78‒0.95) and specificity 79 % (95 % CI 0.65‒0.88).

CONCLUSION

It is mandatory to apply a screening test, the most recommended being the M-CHAT-R/F. For diagnosis CARS and ADOS are the most recommended tools.

Feasibility of a 2-minute eye-tracking protocol to support the early identification of autism

We tested the potential for Gazefinder eye-tracking to support early autism identification, including feasible use with infants, and preliminary concurrent validity of trial-level gaze data against clinical assessment scores. We embedded the ~ 2-min 'Scene 1S4' protocol within a comprehensive clinical assessment for 54 consecutively-referred, clinically-indicated infants (prematurity-corrected age 9-14 months). Alongside % tracking rate as a broad indicator of feasible assessment/data capture, we report infant gaze data to pre-specified regions of interest (ROI) across four trial types and associations with scores on established clinical/behavioural tools. Most infants tolerated Gazefinder eye-tracking well, returning high overall % tracking rate. As a group, infants directed more gaze towards social vs. non-social (or more vs. less socially-salient) ROIs within trials. Behavioural autism features were correlated with increased gaze towards non-social/geometry (vs. social/people) scenes. No associations were found for gaze directed to ROIs within other stimulus types. Notably, there were no associations between developmental/cognitive ability or adaptive behaviour with gaze towards any ROI. Gazefinder assessment seems highly feasible with clinically-indicated infants, and the people vs. geometry stimuli show concurrent predictive validity for behavioural autism features. Aggregating data across the ~ 2-min autism identification protocol might plausibly offer greater utility than stimulus-level analysis alone.

Correlation Between Gaze Behaviors and Social Communication Skills of Young Autistic Children: A Meta-Analysis of Eye-Tracking Studies

This meta-analysis examined correlations between eye-tracking measures of gaze behaviors manifested during dynamic salient social stimuli and behavioral assessment measures of social communication skills of young autistic children. We employed a multilevel model with random effects to perform three separate meta-analyses for correlation between social communication skills and (a) all gaze behaviors, (b) gaze duration, and (c) gaze transition. Subsequently, we performed meta-regression to assess the role of four moderators, including age, continuum of naturalness of stimuli, gaze metric, and area of interest, on correlation effect sizes that were heterogeneous at the population level. A total of 111 correlation coefficients from 17 studies for 1132 young autistic children or children with high-likelihood for autism (Mage range = 6-95 months) were included in this meta-analysis. The correlation effect sizes for all three meta-analyses were significant, supporting the relation between improved gaze behaviors and better social communication skills. In addition, age, gaze metric, and area of interest were significant moderators. This suggests the importance of identifying meaningful gaze behaviors related to social communication skills and the increasingly influential role of gaze behaviors in shaping social communication skills as young autistic children progress through the early childhood stage. The continuum of naturalness of stimuli, however, was revealed to trend towards having a significant moderating effect. Lastly, it is important to note the evidence of potential publication bias. Our findings are discussed in the context of early identification and intervention and unraveling the complex nature of autism.

Two-Year Autism Risk Screening and 3-Year Developmental Outcomes in Very Preterm Infants

Importance

Use of the Modified Checklist for Autism in Toddlers, Revised With Follow-Up, a 2-stage parent-report autism risk screening tool, has been questioned due to reports of poor sensitivity and specificity. How this measure captures developmental delays for very preterm infants may provide support for continued use in pediatric care settings.

Objective

To determine whether autism risk screening with the 2-stage parent-report autism risk screening tool at age 2 years is associated with behavioral and developmental outcomes at age 3 in very preterm infants.

Design, Setting, and Participants

Neonatal Neurobehavior and Outcomes for Very Preterm Infants was a longitudinal, multisite cohort study. Enrollment occurred April 2014 to June 2016, and analyses were conducted from November 2022 to May 2023. Data were collected across 9 university-affiliated neonatal intensive care units (NICUs). Inclusion criteria were infants born less than 30 weeks' gestational age, a parent who could read and speak English and/or Spanish, and residence within 3 hours of the NICU and follow-up clinic.

Exposures

Prematurity and use of the 2-stage parent-report autism risk screening tool at age 2 years.

Main Outcomes and Measures

Outcomes include cognitive, language, motor composites on Bayley Scales for Infant and Toddler Development, third edition (Bayley-III) and internalizing, externalizing, total problems, and pervasive developmental disorder (PDD) subscale on the Child Behavior Checklist (CBCL) at age 3 years. Generalized estimating equations tested associations between the 2-stage parent-report autism risk screening tool and outcomes, adjusting for covariates.

Results

A total of 467 children (mean [SD] gestational age, 27.1 [1.8] weeks; 243 male [52%]) were screened with the 2-stage parent-report autism risk screening tool at age 2 years, and outcome data at age 3 years were included in analyses. Mean (SD) maternal age at birth was 29 (6) years. A total of 51 children (10.9%) screened positive on the 2-stage parent-report autism risk screening tool at age 2 years. Children with positive screening results were more likely to have Bayley-III composites of 84 or less on cognitive (adjusted odds ratio [aOR], 4.03; 95% CI, 1.65-9.81), language (aOR, 5.38; 95% CI, 2.43-11.93), and motor (aOR, 4.74; 95% CI, 2.19-10.25) composites and more likely to have CBCL scores of 64 or higher on internalizing (aOR, 4.83; 95% CI, 1.88-12.44), externalizing (aOR, 2.69; 95% CI, 1.09-6.61), and PDD (aOR, 3.77; 95% CI, 1.72-8.28) scales.

Conclusions and Relevance

Results suggest that the 2-stage parent-report autism risk screening tool administered at age 2 years was a meaningful screen for developmental delays in very preterm infants, with serious delays detected at age 3 years.

Investigating autism knowledge, self-efficacy, and confidence following maternal and child health nurse training for the early identification of autism

Introduction

Early identification of children with a high likelihood of autism can lead to referral for diagnostic services and access to early supports, resulting in improved outcomes for children and families. Maternal and Child Health Nurses (MCHNs) in Victoria, Australia, are well-placed to monitor infants and toddlers for signs of autism, given children and caregivers attend free, regular, well-baby consultations from birth through to school age. This study aimed to identify the impact of personal and workplace factors on MCHNs' competencies of autism knowledge, self-efficacy in identifying autistic infants and toddlers, and confidence in speaking to parents/caregivers about autism. Additionally, the study sought to identify which personal and workplace factors might predict increased competency in these areas.

Methods

After identifying training needs and current competency levels via a training needs analysis (TNA), 1,428 MCHNs received training on the early signs of autism and in the use of the Social Attention and Communication Surveillance-Revised (SACS-R) tool for early autism identification; the training program was known as Monitoring of Social Attention, Interaction, and Communication (MoSAIC).

Results

Previous MCHN autism training and knowledge of autism community resources significantly contributed to increased MCHN self-efficacy in identifying autistic infants and toddlers, while knowledge of community resources was the best predictor of confidence in speaking with parents/caregivers about autism. Perceived self-efficacy and confidence in speaking with parents/caregivers about autism significantly increased following the MoSAIC autism training.

Discussion

Targeted autism training for primary health practitioners is an important first step for early autism identification and initiating conversations with parents/caregivers.

Diagnosis and Assessment of Autism Spectrum Disorder in South Korea

Autism spectrum disorder (ASD) is diagnosed by the clinical decision of a trained professional based on the Diagnostic and Statistical Manual for Mental Disorders, Fifth Edition or International Classification of Diseases 11th Revision diagnostic criteria. To obtain information for diagnostic formulation, professionals should explore detailed developmental history, and can use structured or semi-structured assessment tools to observe interaction between the child and parents or strangers. Diagnostic assessment should include a profile of the strength and weaknesses of the individual and should be conducted using an optimal approach by a multidisciplinary team with appropriate techniques and experience. Assessment of language, cognitive, neuropsychological, and adaptive functioning should be conducted in ASD individuals prior to establishing an individualized treatment plan. Genetic testing, brain magnetic resonance imaging or electroencephalogram testing can be considered for identification of underlying causes.

Screening for Autism Spectrum Disorder in Young Children: Still Not Enough Evidence

BACKGROUND

Early detection of autism spectrum disorder (ASD) has the potential to significantly reduce the impact of the condition, however previous reviews have found little evidence to support screening programs for ASD in young children.

METHODS

We conducted a review with the aim of updating evidence on 3 aspects: (a) diagnostic stability of ASD in young children; (b) accuracy of ASD screening tools in young children; and (c) the benefits of early interventions in screen-detected young children with ASD.

RESULTS

A total of 33 studies were included in our review. Five studies looking at diagnostic stability reported estimates ranging from 71.9% to 100%, however the majority only included a follow-up of 24 months and all studies raised concerns regarding the risk of bias due particularly to lack of blinding, sample size, and patient flow. A total of 25 studies, reported in 26 articles, were identified that reported accuracy data on 11 screening tools. Most of the reports were concerned with versions of M-CHAT, reporting sensitivity estimates from 0.67 to 1.0; however, many of these were deemed to be of high risk of bias due to lack of blinding and follow-up. Four studies reported on early interventions in screen-detected children; however, the majority did not find significant improvements on the relevant outcomes.

CONCLUSIONS

Overall, the evidence on screening for ASD in young children captured by this review is not conclusive regarding the 3 aspects of screening in this population. Future studies should attempt to ensure blinded diagnostic assessments, include longer follow-up periods and limit attrition.

Development of Deep Ensembles to Screen for Autism and Symptom Severity Using Retinal Photographs

Importance

Screening for autism spectrum disorder (ASD) is constrained by limited resources, particularly trained professionals to conduct evaluations. Individuals with ASD have structural retinal changes that potentially reflect brain alterations, including visual pathway abnormalities through embryonic and anatomic connections. Whether deep learning algorithms can aid in objective screening for ASD and symptom severity using retinal photographs is unknown.

Objective

To develop deep ensemble models to differentiate between retinal photographs of individuals with ASD vs typical development (TD) and between individuals with severe ASD vs mild to moderate ASD.

Design, Setting, and Participants

This diagnostic study was conducted at a single tertiary-care hospital (Severance Hospital, Yonsei University College of Medicine) in Seoul, Republic of Korea. Retinal photographs of individuals with ASD were prospectively collected between April and October 2022, and those of age- and sex-matched individuals with TD were retrospectively collected between December 2007 and February 2023. Deep ensembles of 5 models were built with 10-fold cross-validation using the pretrained ResNeXt-50 (32×4d) network. Score-weighted visual explanations for convolutional neural networks, with a progressive erasing technique, were used for model visualization and quantitative validation. Data analysis was performed between December 2022 and October 2023.

Exposures

Autism Diagnostic Observation Schedule-Second Edition calibrated severity scores (cutoff of 8) and Social Responsiveness Scale-Second Edition T scores (cutoff of 76) were used to assess symptom severity.

Main Outcomes and Measures

The main outcomes were participant-level area under the receiver operating characteristic curve (AUROC), sensitivity, and specificity. The 95% CI was estimated through the bootstrapping method with 1000 resamples.

Results

This study included 1890 eyes of 958 participants. The ASD and TD groups each included 479 participants (945 eyes), had a mean (SD) age of 7.8 (3.2) years, and comprised mostly boys (392 [81.8%]). For ASD screening, the models had a mean AUROC, sensitivity, and specificity of 1.00 (95% CI, 1.00-1.00) on the test set. These models retained a mean AUROC of 1.00 using only 10% of the image containing the optic disc. For symptom severity screening, the models had a mean AUROC of 0.74 (95% CI, 0.67-0.80), sensitivity of 0.58 (95% CI, 0.49-0.66), and specificity of 0.74 (95% CI, 0.67-0.82) on the test set.

Conclusions and Relevance

These findings suggest that retinal photographs may be a viable objective screening tool for ASD and possibly for symptom severity. Retinal photograph use may speed the ASD screening process, which may help improve accessibility to specialized child psychiatry assessments currently strained by limited resources.

General practitioners' perspectives regarding early developmental surveillance for autism within the australian primary healthcare setting: a qualitative study

BACKGROUND

Significant challenges remain in the early identification of child developmental disabilities in the community. Implementing supports and services early in the life course has been shown to promote positive developmental outcomes for children at high likelihood of developmental disabilities, including autism. As part of a cluster randomised controlled trial, this study seeks to examine and compare the perspectives and experiences of Australian general practitioners (GPs) in relation to a digital developmental surveillance program for autism and usual care pathway, in general practice clinics.

METHODS

A qualitative research methodology with semi-structured interviews and thematic inductive analysis underpinned by grounded theory was utilised. All GPs from South Western Sydney (NSW) and Melbourne (Victoria) who participated in the main program ("GP Surveillance for Autism") were invited to the interview. GPs who provided consent were interviewed either over online or in-person meeting. Interviews were audio-recorded, transcribed, and coded using NVivo12 software. Inductive interpretive approach was adopted and data were analysed thematically.

RESULTS

Twenty-three GPs across the two sites (NSW: n = 11; Victoria: n = 12) agreed to be interviewed; data saturation had reached following this number of participants. Inductive thematic coding and analysis yielded eight major themes and highlighted common enablers such as the role of GPs in early identification and subsequent supports, enhanced communication between clinicians/professionals, relationship-building with patients, and having standardised screening tools. Specific facilitators to the feasibility and acceptability of a digital screening program for the early identification of developmental disabilities, including the early signs of autism, and encouraging research and education for GPs. However, several practical and socioeconomic barriers were identified, in addition to limited knowledge and uptake of child developmental screening tools as well as COVID-19 lockdown impacts. Common and specific recommendations involve supporting GPs in developmental/paediatrics training, streamlined screening process, and funding and resources in the primary healthcare services.

CONCLUSIONS

The study highlighted the need for practice and policy changes, including further training of GPs alongside sufficient time to complete developmental checks and appropriate financial remuneration through a Medicare billing item. Further research is needed on implementation and scale up of a national surveillance program for early identification of developmental disabilities, including autism.

Debate: Neurodiversity, autism and healthcare

We are at a time of unparalleled flux in our understanding of what autism is and now to respond to it, including our understanding of the role of clinical services. For any clinician working in the context of child development and child mental health services, the majority experience is probably of overwhelming demand, and then perhaps confusion. Referrals for neurodevelopmental conditions, and particularly autism, have become an increasing proportion of UK CAMHS referrals in recent years-with the consequent lengthening of wait times extending to years, sometimes equivalent to the whole length of a child's life up until that point. Services are struggling to develop response strategies to meet user frustration, a task not helped by the fact that most interventions in current use have no good evidence of effectiveness. Consequently, a plethora of local approaches and initiatives have developed. In this article I address these clinical and related issues. I discuss current different uses of the term autism, the relation to intellectual disability, and introduce a conceptualisation of autism as emergent and transactional, which is consistent with current developmental and intervention science. This could bridge between neurodiversity and clinical perspectives and implies a framing of early intervention support that has strong clinical trials evidence and provides the basis for a rational and pre-emptive evidenced care pathway, which I describe.

Development, delivery, and evaluation of a training program for the early identification of autism: Monitoring of Social Attention, Interaction, and Communication

Introduction

Early identification of Autistic children is an important precursor to diagnosis, and access to supports and services. Here we describe the training of the maternal and child health (MCH) workforce in the state of Victoria, Australia in the early identification of infants and toddlers with a high likelihood of autism.

Methods

In 2019, 1,428 MCH nurses completed early autism training held at venues across the state, with an additional 82 nurses completing online-only training. A training needs analysis enabled the research team to determine the workforce's current skill and knowledge levels, and to identify knowledge gaps, training needs and workplace barriers. The professional development program, known as Monitoring of Social Attention, Interaction, and Communication (MoSAIC), comprised: online pre-workshop modules; a face-to-face instructor-led workshop, which included the use of the Social Attention and Communication-Revised (SACS-R) tool; and online post-workshop modules, which included a recording of a face-to-face workshop with all accompanying resources. This was the first time that the MCH workforce received this training package. Attendees were asked to complete a training satisfaction survey immediately following the face-to-face instructor-led workshop and a follow-up survey regarding their autism knowledge and SACS-R implementation 4-6 weeks after the workshop.

Results

Over 90% (n = 325) of MCH nurses who completed the training satisfaction survey agreed or strongly agreed with statements that the training was clear and of high quality. Most nurses also reported that the training was well-presented and that they would recommend it to a colleague. In the 6 months following the training, a total of 82,581 SACS-R assessments were conducted by the MCH workforce, reflecting that MCH nurses had successfully integrated SACS-R assessments into their work practice after receiving the early autism identification training.

Discussion

This study demonstrated that training on the early identification of autism can be successfully designed, customized, and delivered to a large primary healthcare workforce for universal developmental surveillance of autism.

Who Is Attending? The Role of Child Ethnicity and Maternal Demographics in Research Engagement and Early Identification of Autism

Inequitable access to early autism developmental surveillance is evident globally. However, there is limited research examining autism diagnosis, ethnicity, and community profiles when engaging in research for the early identification of autism. We aimed to understand the relationships between child ethnicity, maternal demographics, and autism diagnosis, comparing retrospective data from the 2016 census for eight local government areas (LGAs) in Victoria, Australia. Maternal and child health (MCH) nurses monitored 13,511 children under 42 months for the early signs of autism using the Social Attention Communication Surveillance-Revised (SACS-R) and SACS-R Preschool (SACS-PR) tools during well-child checks. Of these, 340 children with a "high likelihood" of autism attended developmental assessments. Participants' maternal ethnicity ('European maternal ethnicity', EME; 'non-European maternal ethnicity,' N-EME; 'mixed maternal ethnicity,' MME'), socioeconomic factors, and autism prevalence were compared to their LGA community. Results indicated that study participants were representative of their LGA communities, though bi- and multilingualism was higher in our cohort. Differences in current maternal employment, maternal education, annual family income, and autism prevalence were found between the N-EME, EME, and MME groups. Our study found that research engagement was driven by maternal education, maternal employment, and annual family income, and further research is required to understand these relationships.

Efficacy of very early interventions on neurodevelopmental outcomes for infants and toddlers at increased likelihood of or diagnosed with autism: A systematic review and meta-analysis

The aim of this systematic review was to determine the efficacy of very early interventions for infants and toddlers at increased likelihood of or diagnosed with autism for autism symptomatology, developmental outcomes and/or neurocognitive markers. Eight databases were searched (14 April 2022) with inclusion criteria: (i) RCTs with care as usual (CAU) comparison group, (ii) participants at increased likelihood of or diagnosed with autism and aged <24 months corrected age (CA), (iii) parent-mediated and/or clinician directed interventions, and (iv) outcome measures were autism symptomatology, cognition, language, adaptive skills, or neurocognitive assessments (EEG and eye tracking). Quality was assessed using Risk of Bias 2 and GRADE. Nineteen publications from 12 studies reported on 715 infants and toddlers. There was low to moderate certainty evidence that clinician-assessed outcomes did not show significant treatment effects for: autism symptomatology (ADOS CSS: MD -0.08, 95% CI -0.61, 0.44, p = 0.75), cognitive outcome (Mullen Scales of Early Learning-Early Learning Composite (MSEL-ELC): SMD 0.05, 95% CI -0.19, 0.29, p = 0.67), receptive language (MSEL-Receptive Language: SMD 0.04, 95% CI -0.21, 0.3, p = 0.74) or expressive language (MSEL-Expressive Language: SMD 0.06, 95% CI -0.1, 0.23, p = 0.45). Neurocognitive outcomes (EEG and eye tracking) were heterogeneous, with inconsistent findings. There is low to moderate certainty evidence that very early interventions have limited impact on neurodevelopmental outcomes by age 3 years.

Estimated Therapy Costs and Downstream Cost Consequences of iBASIS-Video Interaction to Promote Positive Parenting Intervention vs Usual Care Among Children Displaying Early Behavioral Signs of Autism in Australia

Importance

The growing global prevalence of autism spectrum disorder (ASD) is associated with increasing costs for support services. Ascertaining the effects of a successful preemptive intervention for infants showing early behavioral signs of autism on human services budgets is highly policy relevant.

Objective

To estimate the net cost impact of the iBASIS-Video Interaction to Promote Positive Parenting (iBASIS-VIPP) intervention on the Australian government.

Design, Setting, and Participants

Infants (aged 12 months) showing early behavioral indicators of autism were recruited through community settings into the multicenter Australian iBASIS-VIPP randomized clinical trial (RCT), a 5- to 6-month preemptive parent-mediated intervention, between June 9, 2016, and March 30, 2018, and were followed up for 18 months to age 3 years. This economic evaluation, including cost analysis (intervention and cost consequences) and cost-effectiveness analyses of iBASIS-VIPP compared with usual care (treatment as usual [TAU]), modeled outcomes observed at age 3 through to 12 years (13th birthday) and was conducted from April 1, 2021, to January 30, 2023. Data analysis was conducted from July 1, 2021, to January 29, 2023.

Exposures

iBASIS-VIPP intervention.

Main Outcomes and Measures

To project the diagnostic trajectory and associated disability support costs drawing on the Australian National Disability Insurance Scheme (NDIS), the main outcome was the differential treatment cost of iBASIS-VIPP plus TAU vs TAU and disability-related government costs modeled to age 12 years, using a clinical diagnosis of ASD and developmental delay (with autism traits) at 3 years. Costs were calculated in Australian dollars and converted to US dollars. Economic performance was measured through the following: (1) differential net present value (NPV) cost (iBASIS-VIPP less TAU), (2) investment return (dollars saved for each dollar invested, taking a third-party payer perspective), (3) break-even age when treatment cost was offset by downstream cost savings, and (4) cost-effectiveness in terms of the differential treatment cost per differential ASD diagnosis at age 3 years. Alternate values of key parameters were modeled in 1-way and probabilistic sensitivity analysis, the latter identifying the likelihood of an NPV cost savings.

Results

Of the 103 infants enrolled in the iBASIS-VIPP RCT, 70 (68.0%) were boys. Follow-up data at age 3 years were available for 89 children who received TAU (44 [49.4%]) or iBASIS-VIPP (45 [50.6%]) and were included in this analysis. The estimated mean differential treatment cost was A $5131 (US $3607) per child  for iBASIS-VIPP less TAU. The best estimate of NPV cost savings was A $10 695 (US $7519) per child (discounted at 3% per annum). For each dollar invested in treatment, a savings of A $3.08 (US $3.08) was estimated; the break-even cost occurred at age 5.3 years (approximately 4 years after intervention delivery). The mean differential treatment cost per lower incident case of ASD was A $37 181 (US $26 138). We estimated that there was an 88.9% chance that iBASIS-VIPP would deliver a cost savings for the NDIS, the dominant third-party payer.

Conclusions and Relevance

The results of this study suggest that iBASIS-VIPP represents a likely good-value societal investment for supporting neurodivergent children. The estimated net cost savings were considered conservative, as they covered only third-party payer costs incurred by the NDIS and outcomes were modeled to just age 12 years. These findings further suggest that preemptive interventions may be a feasible, effective, and efficient new clinical pathway for ASD, reducing disability and the costs of support services. Long-term follow-up of children receiving preemptive intervention is needed to confirm the modeled results.

The Utility of Natural Language Samples for Assessing Communication and Language in Infants Referred with Early Signs of Autism

Natural Language Sampling (NLS) offers clear potential for communication and language assessment, where other data might be difficult to interpret. We leveraged existing primary data for 18-month-olds showing early signs of autism, to examine the reliability and concurrent construct validity of NLS-derived measures coded from video-of child language, parent linguistic input, and dyadic balance of communicative interaction-against standardised assessment scores. Using Systematic Analysis of Language Transcripts (SALT) software and coding conventions, masked coders achieved good-to-excellent inter-rater agreement across all measures. Associations across concurrent measures of analogous constructs suggested strong validity of NLS applied to 6-min video clips. NLS offers benefits of feasibility and adaptability for validly quantifying emerging skills, and potential for standardisation for clinical use and rigorous research design.

Predictive Value of Early Autism Detection Models Based on Electronic Health Record Data Collected Before Age 1 Year

Importance

Autism detection early in childhood is critical to ensure that autistic children and their families have access to early behavioral support. Early correlates of autism documented in electronic health records (EHRs) during routine care could allow passive, predictive model-based monitoring to improve the accuracy of early detection.

Objective

To quantify the predictive value of early autism detection models based on EHR data collected before age 1 year.

Design, Setting, and Participants

This retrospective diagnostic study used EHR data from children seen within the Duke University Health System before age 30 days between January 2006 and December 2020. These data were used to train and evaluate L2-regularized Cox proportional hazards models predicting later autism diagnosis based on data collected from birth up to the time of prediction (ages 30-360 days). Statistical analyses were performed between August 1, 2020, and April 1, 2022.

Main Outcomes and Measures

Prediction performance was quantified in terms of sensitivity, specificity, and positive predictive value (PPV) at clinically relevant model operating thresholds.

Results

Data from 45 080 children, including 924 (1.5%) meeting autism criteria, were included in this study. Model-based autism detection at age 30 days achieved 45.5% sensitivity and 23.0% PPV at 90.0% specificity. Detection by age 360 days achieved 59.8% sensitivity and 17.6% PPV at 81.5% specificity and 38.8% sensitivity and 31.0% PPV at 94.3% specificity.

Conclusions and Relevance

In this diagnostic study of an autism screening test, EHR-based autism detection achieved clinically meaningful accuracy by age 30 days, improving by age 1 year. This automated approach could be integrated with caregiver surveys to improve the accuracy of early autism screening.

Case report: Preemptive intervention for an infant with early signs of autism spectrum disorder during the first year of life

Autism spectrum disorder (ASD) includes neurodevelopmental conditions traditionally considered to bring life long disabilities, severely impacting individuals and their families. Very early identification and intervention during the very first phases of life have shown to significantly diminish symptom severity and disability, and improve developmental trajectories. Here we report the case of a young child showing early behavioral signs of ASD during the first months of life, including diminished eye contact, reduced social reciprocity, repetitive movements. The child received a pre-emptive parent mediated intervention based on the Infant Start, an adaptation of the Early Start Denver Model (ESDM), specifically developed for children with ASD signs during the first year of life. The child here described received intervention from 6 to 32 months of age, in combination with educational services. Diagnostic evaluations performed at several time points (8, 14, 19, and 32 months) showed progressive improvements in his developmental level and ASD symptoms. Our case study supports the possibility of identifying ASD symptoms and providing services as soon as concerns emerge even during the first year of life. Our report, in combination with recent infant identification and intervention studies, suggests the need for very early screening and preemptive intervention to promote optimal outcomes.

Caregiver sensitivity predicts infant language use, and infant language complexity predicts caregiver language complexity, in the context of possible emerging autism

While theory supports bidirectional effects between caregiver sensitivity and language use, and infant language acquisition-both caregiver-to-infant and also infant-to-caregiver effects-empirical research has chiefly explored the former unidirectional path. In the context of infants showing early signs of autism, we investigated prospective bidirectional associations with 6-min free-play interaction samples collected for 103 caregivers and their infants (mean age 12-months; and followed up 6-months later). We anticipated that measures of caregiver sensitivity/language input and infant language would show within-domain temporal stability/continuity, but also that there would be predictive associations from earlier caregiver input to subsequent child language, and vice versa. Caregiver sensitive responsiveness (from the Manchester Assessment of Caregiver-Infant interaction [MACI]) predicted subsequent infant word tokens (i.e., amount of language, coded following the Systematic Analysis of Language Transcripts [SALT]). Further, earlier infant Mean Length of Utterance (MLU; reflecting language complexity, also derived from SALT coding) predicted later caregiver MLU, even when controlling for variability in infant ages and clear within-domain temporal stability/continuity in key measures (i.e., caregiver sensitive responsiveness and infant word tokens; and infant and caregiver MLU). These data add empirical support to theorization on how caregiver input can be both supportive of, and potentially influenced by, infant capacities, when infants have social-communication differences and/or communication/language delays suggestive of possible emerging autism.

Parental experience of an early developmental surveillance programme for autism within Australian general practice: a qualitative study

OBJECTIVES

Implementing support and services early in the life course has been shown to promote positive developmental outcomes for children at high likelihood of developmental conditions including autism. This study examined parents'/caregivers' experiences and perceptions about a digital developmental surveillance pathway for autism, the autism surveillance pathway (ASP), and usual care, the surveillance as usual (SaU) pathway, in the primary healthcare general practice setting.

DESIGN

This qualitative study involves using a convenience selection process of the full sample of parents/caregivers that participated in the main programme, 'General Practice Surveillance for Autism', a cluster-randomised controlled trial study. All interviews were audio-recorded, transcribed and coded using NVivo V.12 software. An inductive thematic interpretive approach was adopted and data were analysed thematically.

PARTICIPANTS

Twelve parents/caregivers of children with or without a developmental condition/autism (who participated in the main programme) in South Western Sydney and Melbourne were interviewed.

SETTINGS

All interviews were completed over the phone.

RESULTS

There were seven major themes and 20 subthemes that included positive experiences, such as pre-existing patient-doctor relationships and their perceptions on the importance of knowing and accessing early support/services. Barriers or challenges experienced while using the SaU pathway included long waiting periods, poor communication and lack of action plans, complexity associated with navigating the healthcare system and lack of understanding by general practitioners (GPs). Common suggestions for improvement included greater awareness/education for parents/carers and the availability of accessible resources on child development for parents/caregivers.

CONCLUSION

The findings support the use of digital screening tools for developmental surveillance, including for autism, using opportunistic contacts in the general practice setting.

TRIAL REGISTRATION NUMBER

ANZCTR (ACTRN12619001200178).

Insights on dental care management and prevention in children with autism spectrum disorder (ASD). What is new?

Autistic subjects represent a severe concern to dentistry due to the considerable difficulty in managing their oral health, maintaining routine toothbrushing, and preventing dental and periodontal problems. The social and economic burden of managing dental care in autism spectrum disorder (ASD) children is particularly cumbersome for families and public and private health expenditure, especially when children reach the dentist following a late diagnosis with evident oral health problems. An early diagnosis of ASD helps dentists better address these children's oral health. Unfortunately, insufficient attention is paid to the training and education of general pediatricians, dentists, and dental hygienists, allowing them to get to approach the different clinical aspects of ASD. Usually, children diagnosed with ASD are scheduled for dental appointments like their neurotypical peers, whereas their needs are typically complex and personalized. Scant attention is also devoted to these patients by commercial manufacturers of dental products and devices for oral hygiene and prevention of caries and periodontal diseases, leaving parents without the support and often failing when they address the oral health of autistic children. The difficulties of oral care do not derive simply from the behavior of ASD patients, as is commonly assumed, and therefore cannot be overcome solely by the patience and attention of parents and dentists. Genetics, dietary habits, sensory impairments, and cognition disorders are other causes contributing in various degrees to the impact on the mood and psychological reactions of autistic children towards dentists. How can we prevent teeth caries, periodontal disorders, and other oral health impairments by properly managing ASD children? This manuscript gives an up-to-date overview of these problems and helps to provide good remarks.

Developmental Surveillance Program Useful in Early Identification of Autism

According to this study: Results of a community-based study provide strong support for the use of the developmental surveillance program for early identification of autism in the general population.

Early Detection of Neurodevelopmental Disorders of Toddlers and Postnatal Depression by Mobile Health App: Observational Cross-sectional Study

Background

Delays in the diagnosis of neurodevelopmental disorders (NDDs) in toddlers and postnatal depression (PND) in mothers are major public health issues. In both cases, early intervention is crucial.

Objective

We aimed to assess if a mobile app named Malo can reduce delay in the recognition of NDD and PND.

Methods

We performed an observational, cross-sectional, data-based study in a population of young parents with a minimum of 1 child under 3 years of age at the time of inclusion and using Malo on a regular basis. We included the first 4000 users matching the criteria and agreeing to participate between November 11, 2021, and January 14, 2022. Parents received monthly questionnaires via the app, assessing skills on sociability, hearing, vision, motricity, language of their infants, and possible autism spectrum disorder. Mothers were also requested to answer regular questionnaires regarding PND, from 4-28 weeks after childbirth. When any patient-reported outcomes matched predefined criteria, an in-app notification was sent to the user, recommending the booking of an appointment with their family physician or pediatrician. The main outcomes were the median age of the infant at the time of notification for possible NDD and the median time of PND notifications after childbirth. One secondary outcome was the relevance of the NDD notification for a consultation as assessed by the physicians.

Results

Among 4242 children assessed by 5309 questionnaires, 613 (14.5%) had at least 1 disorder requiring a consultation. The median age of notification for possible autism spectrum, vision, audition, socialization, language, or motor disorders was 11, 9, 17, 12, 22, and 4 months, respectively. The sensitivity of the alert notifications of suspected NDDs as assessed by the physicians was 100%, and the specificity was 73.5%. Among 907 mothers who completed a PND questionnaire, highly probable PND was detected in 151 (16.6%) mothers, and the median time of detection was 8-12 weeks.

Conclusions

The algorithm-based alert suggesting NDD was highly sensitive with good specificity as assessed by real-life practitioners. The app was also efficient in the early detection of PND. Our results suggest that the regular use of this multidomain familial smartphone app would permit the early detection of NDD and PND.

Trial Registration

ClinicalTrials.gov NCT04958174; https://clinicaltrials.gov/ct2/show/NCT04958174