The Developmental Check-In: Development and initial testing of an autism screening tool targeting young children from underserved communities

Janvier, Yvette M.; Coffield, Caroline N; Harris, Jill; Mandell, David S.; Cidav, Zuleyha

doi:10.1177/1362361318770430

Cited by 20 publications

(14 citation statements)

References 47 publications

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“…Promising new methods include parent-report tools that are supported by picture or video models 26 and direct data gathering methods that leverage technological advances in computing and machine learning. 27,28 However, any new method should be tested in cohorts that are universally screened and systematically followed-up to reduce the bias associated with screening and following selected populations.…”

Section: Discussionmentioning

confidence: 99%

Accuracy of Autism Screening in a Large Pediatric Network

et al. 2019

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BACKGROUND: Universal screening is recommended to reduce the age of diagnosis for autism spectrum disorder (ASD). However, there are insufficient data on children who screen negative and no study of outcomes from truly universal screening. With this study, we filled these gaps by examining the accuracy of universal screening with systematic follow-up through 4 to 8 years. METHODS: Universal, primary care-based screening was conducted using the Modified Checklist for Autism in Toddlers with Follow-Up (M-CHAT/F) and supported by electronic administration and integration into electronic health records. All children with a well-child visit (1) between 16 and 26 months, (2) at a Children's Hospital of Philadelphia site after universal electronic screening was initiated, and (3) between January 2011 and July 2015 were included (N = 25 999). RESULTS: Nearly universal screening was achieved (91%), and ASD prevalence was 2.2%. Overall, the M-CHAT/F's sensitivity was 38.8%, and its positive predictive value (PPV) was 14.6%. Sensitivity was higher in older toddlers and with repeated screenings, whereas PPV was lower in girls. Finally, the M-CHAT/F's specificity and PPV were lower in children of color and those from lower-income households. CONCLUSIONS: Universal screening in primary care is possible when supported by electronic administration. In this "real-world" cohort that was systematically followed, the M-CHAT/F was less accurate in detecting ASD than in previous studies. Disparities in screening rates and accuracy were evident in traditionally underrepresented groups. Future research should focus on the development of new methods that detect a greater proportion of children with ASD and reduce disparities in the screening process. WHAT'S KNOWN ON THIS SUBJECT: Universal screening for autism spectrum disorder is recommended in primary care to facilitate early detection. However, the US Preventive Services Task Force concluded that there is currently insufficient data from primary care and with longitudinal follow-up to recommend universal screening. WHAT THIS STUDY ADDS: We examined the accuracy of autism screening in a diverse cohort screened nearly universally (91%) and followed-up systematically. The M-CHAT/F had lower sensitivity and positive predictive value than in previous studies; disparities were observed in screening rates and accuracy.

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Section: Discussionmentioning

confidence: 99%

Accuracy of Autism Screening in a Large Pediatric Network

et al. 2019

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“…Previous research found that families that worked with a patient navigator were more likely than families who received routine clinical care to complete an ASD diagnostic assessment and receive timely ASD diagnosis [Feinberg et al, 2016]. Other effective or promising intervention strategies to reduce disparities in ASD identification are using pictorial ASD screens to reduce linguistic and literacy demands [Janvier, Coffield, Harris, Mandell, & Cidav, 2019], asking healthcare providers to rate their likelihood of referral for certain disorders on a continuous rather than dichotomous scale [Begeer, Bouk, Boussaid, Terwogt, & Koot, 2009], and adopting a presumptive eligibility approach where early intervention services are based on an at-risk screen before diagnostic evaluation [Rotholz, Kinsman, Lacy, & Charles, 2017]. More research is needed on the utility of parent and provider education and stigma reduction in reducing disparities in ASD diagnosis.…”

Section: Discussionmentioning

confidence: 99%

Disparities in Documented Diagnoses of Autism Spectrum Disorder Based on Demographic, Individual, and Service Factors

et al. 2019

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The objectives of our study were to (a) report how many children met an autism spectrum disorder (ASD) surveillance definition but had no clinical diagnosis of ASD in health or education records and (b) evaluate differences in demographic, individual, and service factors between children with and without a documented ASD diagnosis. ASD surveillance was conducted in selected areas of Arizona, Arkansas, Colorado, Georgia, Maryland, Minnesota, Missouri, New Jersey, North Carolina, Tennessee, and Wisconsin. Children were defined as having ASD if sufficient social and behavioral deficits and/or an ASD diagnosis were noted in health and/or education records. Among 4,498 children, 1,135 (25%) had ASD indicators without having an ASD diagnosis. Of those 1,135 children without a documented ASD diagnosis, 628 (55%) were not known to receive ASD services in public school. Factors associated with not having a clinical diagnosis of ASD were non‐White race, no intellectual disability, older age at first developmental concern, older age at first developmental evaluation, special education eligibility other than ASD, and need for fewer supports. These results highlight the importance of reducing disparities in the diagnosis of children with ASD characteristics so that appropriate interventions can be promoted across communities. Autism Res 2020, 13: 464–473. © 2019 International Society for AutismResearch,Wiley Periodicals, Inc. Lay Summary Children who did not have a clinical diagnosis of autism spectrum disorder (ASD) documented in health or education records were more likely to be non‐White and have fewer developmental problems than children with a clinical diagnosis of ASD. They were brought to the attention of healthcare providers at older ages and needed fewer supports than children with a clinical diagnosis of ASD. All children with ASD symptoms who meet diagnostic criteria should be given a clinical diagnosis so they can receive treatment specific to their needs.

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“…As such, these results suggest that augmented assessment approaches are needed to reduce disparities to enhance early detection ( 53 ). To improve screening and diagnostic precision, new and innovative approaches could be developed that integrate the ASSC with video models ( 65 ), new technological advancements, as well as machine learning ( 52 , 66 , 67 ).…”

Section: Discussionmentioning

confidence: 99%

Autism Spectrum Screening Checklist (ASSC): The Development of a Scale to Identify High-Risk Individuals Within the Children's Mental Health System

et al. 2021

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Autism Spectrum Disorder (ASD) is a complex childhood onset neurodevelopmental disorder that has become the fastest growing developmental disability. Due to the increased demand for diagnostic assessments and subsequent increased wait times, standardized screening as part of regular clinical practice is needed. More specifically, there is an important need for the development of a more streamlined screening tool within an existing assessment system to identify those at greatest risk of having ASD. The current study utilized data from ~17,000 assessments obtained within the province of Ontario, based on the interRAI Child and Youth Mental Health (ChYMH) and Child and Youth Mental Health and Developmental Disability (ChYMH-DD), to develop a scale to identify children who have a higher likelihood of having autism. The scale was then tested on a trial population with data from the interRAI Early Years instrument. Further analyses examined the predictive validity of the scale. The Autism Spectrum Screening Checklist (ASSC) was found to be a good predictor of ASD with a sensitivity of 0.73 and specificity of 0.62, at the recommended cut-point of 2+. The results were consistent across several age ranges, specifically from 2 to 21 years of age. The ASSC scale provides an initial screen to help identify children and youth at heightened risk for autism within larger populations being assessed as part of routine practice. The main goal for the development and implementation of the ASSC scale is to harness the power of the existing interRAI assessment system to provide a more efficient, effective screening and referral process. This will ultimately help improve patient outcomes through needs-based care.

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The Developmental Check-In: Development and initial testing of an autism screening tool targeting young children from underserved communities

Cited by 20 publications

References 47 publications

Accuracy of Autism Screening in a Large Pediatric Network

Accuracy of Autism Screening in a Large Pediatric Network

Disparities in Documented Diagnoses of Autism Spectrum Disorder Based on Demographic, Individual, and Service Factors

Autism Spectrum Screening Checklist (ASSC): The Development of a Scale to Identify High-Risk Individuals Within the Children's Mental Health System

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