Follow-Up of Children With Autism Spectrum Disorder 1 Year After Early Behavioral Intervention

Brief Report: Machine Learning for Estimating Prognosis of Children with Autism Receiving Early Behavioral Intervention-A Proof of Concept

Although early behavioral intervention is considered as empirically-supported for children with autism, estimating treatment prognosis is a challenge for practitioners. One potential solution is to use machine learning to guide the prediction of the response to intervention. Thus, our study compared five machine algorithms in estimating treatment prognosis on two outcomes (i.e., adaptive functioning and autistic symptoms) in children with autism receiving early behavioral intervention in a community setting. Each machine learning algorithm produced better predictions than random sampling on both outcomes. Those results indicate that machine learning is a promising approach to estimating prognosis in children with autism, but studies comparing these predictions with those produced by qualified practitioners remain necessary.

Changes in Autistic Symptoms and Adaptive Functioning of Children Receiving Early Behavioral Intervention in a Community Setting: A Latent Growth Curve Analysis

Despite showing effects in well-controlled studies, the extent to which early intensive behavioral intervention (EBI) produces positive changes in community-based settings remains uncertain. Thus, our study examined changes in autistic symptoms and adaptive functioning in 233 children with autism receiving EBI in a community setting. The results revealed nonlinear changes in adaptive functioning characterized by significant improvements during the intervention and a small linear decrease in autistic symptoms from baseline to follow-up. The intensity of intervention, initial age, IQ and autistic symptoms were associated either with progress during the intervention or maintenance during the follow-up. The next step to extend this line of research involves collecting detailed data about intervention strategies and implementation fidelity to produce concrete recommendations for practitioners.

Developmental and behavioral groupings can predict changes in adaptive behavior over time in young children with neurodevelopmental disorders

The heterogeneity within, and the overlap between, diagnostic categories for neurodevelopmental disorders (NDDs) remain poorly understood. Developmental trajectories may diverge among children with the same diagnosis, who may also respond very differently to treatment. In a previous study, we used statistical clustering methods in a sample of 194 preschoolers who were referred for NDD assessment. We identified three distinct subgroups based on multiple developmental and behavioral variables. The present study aimed to identify: (1) early developmental markers at the surveillance and screening period that are predictive of subgroup membership at the diagnostic period (i.e., around age 5), (2) associations between subgroups and the evolution of adaptive behavior over the course of two years, and (3) predictors of adaptive behavior change. Subgroup membership was the only significant predictor of adaptive behavior change over time, which suggests that a clustering method based on developmental and behavioral profiles may be useful in treatment planning.

Overall prognosis of preschool autism spectrum disorder diagnoses

BACKGROUND

Autism spectrum disorder is a neurodevelopmental disorder characterised by social communication difficulties, restricted interests and repetitive behaviours. The clinical pathway for children with a diagnosis of autism spectrum disorder is varied, and current research suggests some children may not continue to meet diagnostic criteria over time.

OBJECTIVES

The primary objective of this review was to synthesise the available evidence on the proportion of preschool children who have a diagnosis of autism spectrum disorder at baseline (diagnosed before six years of age) who continue to meet diagnostic criteria at follow-up one or more years later (up to 19 years of age).

SEARCH METHODS

We searched MEDLINE, Embase, PsycINFO, and eight other databases in October 2017 and ran top-up searches up to July 2021. We also searched reference lists of relevant systematic reviews.

SELECTION CRITERIA

Two review authors independently assessed prospective and retrospective follow-up studies that used the same measure and process within studies to diagnose autism spectrum disorder at baseline and follow-up. Studies were required to have at least one year of follow-up and contain at least 10 participants. Participants were all aged less than six years at baseline assessment and followed up before 19 years of age.

DATA COLLECTION AND ANALYSIS

We extracted data on study characteristics and the proportion of children diagnosed with autism spectrum disorder at baseline and follow-up. We also collected information on change in scores on measures that assess the dimensions of autism spectrum disorder (i.e. social communication and restricted interests and repetitive behaviours). Two review authors independently extracted data on study characteristics and assessed risk of bias using a modified quality in prognosis studies (QUIPS) tool. We conducted a random-effects meta-analysis or narrative synthesis, depending on the type of data available. We also conducted prognostic factor analyses to explore factors that may predict diagnostic outcome.

MAIN RESULTS

In total, 49 studies met our inclusion criteria and 42 of these (11,740 participants) had data that could be extracted. Of the 42 studies, 25 (60%) were conducted in North America, 13 (31%) were conducted in Europe and the UK, and four (10%) in Asia. Most (52%) studies were published before 2014. The mean age of the participants was 3.19 years (range 1.13 to 5.0 years) at baseline and 6.12 years (range 3.0 to 12.14 years) at follow-up. The mean length of follow-up was 2.86 years (range 1.0 to 12.41 years). The majority of the children were boys (81%), and just over half (60%) of the studies primarily included participants with intellectual disability (intelligence quotient < 70). The mean sample size was 272 (range 10 to 8564). Sixty-nine per cent of studies used one diagnostic assessment tool, 24% used two tools and 7% used three or more tools. Diagnosis was decided by a multidisciplinary team in 41% of studies. No data were available for the outcomes of social communication and restricted and repetitive behaviours and interests. Of the 42 studies with available data, we were able to synthesise data from 34 studies (69% of all included studies; n = 11,129) in a meta-analysis. In summary, 92% (95% confidence interval 89% to 95%) of participants continued to meet diagnostic criteria for autism spectrum disorder from baseline to follow-up one or more years later; however, the quality of the evidence was judged as low due to study limitations and inconsistency. The majority of the included studies (95%) were rated at high risk of bias. We were unable to explore the outcomes of change in social communication and restricted and repetitive behaviour and interests between baseline and follow-up as none of the included studies provided separate domain scores at baseline and follow-up. Details on conflict of interest were reported in 24 studies. Funding support was reported by 30 studies, 12 studies omitted details on funding sources and two studies reported no funding support. Declared funding sources were categorised as government, university or non-government organisation or charity groups. We considered it unlikely funding sources would have significantly influenced the outcomes, given the nature of prognosis studies.

AUTHORS' CONCLUSIONS

Overall, we found that nine out of 10 children who were diagnosed with autism spectrum disorder before six years of age continued to meet diagnostic criteria for autism spectrum disorder a year or more later, however the evidence was uncertain. Confidence in the evidence was rated low using GRADE, due to heterogeneity and risk of bias, and there were few studies that included children diagnosed using a current classification system, such as the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) or the eleventh revision of the International Classification of Diseases (ICD-11). Future studies that are well-designed, prospective and specifically assess prognosis of autism spectrum disorder diagnoses are needed. These studies should also include contemporary diagnostic assessment methods across a broad range of participants and investigate a range of relevant prognostic factors.

Ethical Issues in ABA-based Service Provision for Autism in Limited-Resource Contexts: A Case Example of the People’s Republic of China

Recommendations for intervention for young children with autism spectrum disorders (ASD) focus on early, intensive, and often individual intervention based on methods of applied behavior analysis. In much of the world, there are few options for early intervention. This article examines this question: in a context where intensive and high staff-to-student ratio intervention is not possible, how can provision of high-quality evidence-based intervention be ensured? We consider the case of China, where intervention for young children with autism is provided at diverse educational organizations, and funding limitations impact teacher-to-student ratio. Due to challenges, rigorous use of evidence-based methods often lags behind best practices. This article presents an ethical analysis of the choices educators face and research-based recommendations consistent with the ethical analysis. Given the current context, we recommend a socially valid approach of systematically using group instruction based on ABA principles to increase the effectiveness and intensity of each aspect of intervention programs. While focused on the case of China, recommendations and analysis have implications for other settings with limited resources.

Treatment of Preschool Children With Autism Spectrum Disorder: A Trial to Evaluate a Learning Style Profile Intervention Program in China

OBJECTIVE

To investigate whether the provision of learning style profile (LSP) training improves development in preschool children with autism spectrum disorder (ASD) in China and to describe the characteristics of children who benefit from the intervention.

METHODS

Eighty-one children aged 36 to 72 months who were diagnosed with ASD for the first time were recruited for the intervention group. All of them received 24 weeks of LSP training, consisting of hospital- and home-based training. Twenty-one children with ASD of the same age in the control group had never received any intervention after diagnosis but underwent an assessment. Assessments were conducted at baseline and 24 weeks later. Differences in the developmental level and severity of ASD symptoms over time and between groups were analyzed by repeated standardized measures. Secondary analyses examined age effects among the 36- 48-, 48- 60-, and 60-72-month age groups.

RESULTS

Within-group comparison of the intervention group revealed significant treatment effects after the intervention, according to: language, social and adaptive developmental quotients (DQs) of the China Developmental Scale; total Childhood Autism Rating Scale (CARS) score; and hyperactivity, peer problems, total difficulties, and prosocial behavior scores of the Strengths and Difficulties Questionnaire (SDQ). Similar gains were observed in gross and fine motor DQs of the China Developmental Scale and emotional symptoms and conduct problems scores of the SDQ; however, the differences between these pre- and postintervention scores did not reach statistical significance. Comparisons among the three age groups in the intervention groups demonstrated a significant age effect on adaptive DQs of the China Developmental Scale; total CARS score; hyperactivity, peer problems and total difficulties scores of the SDQ. Comparison between the intervention and control groups revealed significant treatment effects on language, social and adaptive DQs of the China Developmental Scale; total CARS score; and emotional symptoms, conduct problems, hyperactivity, peer problems, total difficulties, and prosocial behavior scores of the SDQ after the intervention. Similar gains were observed in gross and fine motor DQs of the China Developmental Scale, although differences between the two groups did not reach statistical significance.

CONCLUSION

Our findings suggest that LSP training can effectively improve social behavior and reduce the severity of ASD symptoms in children with ASD. Our data also highlight the importance of early intervention.