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Sponsored Artificial Intelligence: A Modern Approach, Global Edition Artificial Intelligence: A Modern Approach, Global Edition

Author

Diana L. Robins

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Review Jul 2026

Preliminary Reliability and Validity of the M-CHAT-S, a New Autism Screening Tool for School-Aged Children

Identifying autism early is critical for ensuring timely access to appropriate educational and clinical supports. Current autism screening practices primarily focus on toddlers; universal practices for identifying the substantial portion of autistic children who arrive at school age without a diagnosis are lacking. This study evaluates the preliminary reliability and validity of the Modified Checklist for Autism in Toddlers–School Age version (M-CHAT-S), a novel screener designed for early school-age children, with separate versions for verbally fluent and minimally verbal children. A total of 165 caregivers and 107 educators completed the M-CHAT-S, along with the Social Responsiveness Scale, Second Edition (SRS-2), to test convergent validity, and the Child Behavior Checklist (CBCL), to test discriminant validity. Findings demonstrate strong internal consistency across versions (Cronbach’s α = .79–.92) and robust construct validity. Children with preexisting autism diagnoses scored higher on the M-CHAT-S than nonautistic children. Both test–retest reliability and interrater reliability were in the moderate range. Despite these limitations, the M-CHAT-S demonstrates promise as a screening tool that could facilitate earlier identification of autistic children in school settings. Future research will involve a partnership with school districts to support school-based validation and implementation. Lay Abstract Children with disabilities have a right to a free and appropriate public education in the United States. Children who are not identified by the time of school entry are likely to miss out on appropriate services and supports to which they would otherwise be legally entitled. Many studies show that a large portion of individuals who are ultimately diagnosed with autism are not identified until by the time they start school.Screening tools can help identify children who may be on the autism spectrum. Universal autism screening is currently recommended for toddlers, but not school-age children. To address this gap, we developed the Modified Checklist for Autism in Toddlers-School Age version (M-CHAT-S) for children in early elementary school. This study tested the consistency and accuracy of the M-CHAT-S for both verbally fluent and minimally verbal children.We asked 165 caregivers and 107 educators to complete the M-CHAT-S and compared their responses to other well-established measures of autism traits and behavior. Overall, we found that the M-CHAT-S had good reliability, meaning that the items in the measure were consistent with each other. Children with a known autism diagnosis scored higher on the M-CHAT-S than non-autistic children. M-CHAT-S scores were more strongly related to another autism screening tool (the SRS-2) than to a survey of general behavior (the CBCL). However, test-retest reliability (whether the same rater’s score stayed consistent over time) and interrater reliability (whether two different raters agreed on scores) were lower than expected.These results suggest that the M-CHAT-S may be a useful tool for identifying autistic children in early school years. Future research will involve partnering with school districts to be able to reach as many children as possible, including autistic children who have not yet been identified. If validated further, this tool could help schools and families recognize children who need autistic support, leading to earlier access to services.

Ashley de Marchena, A. Wieckowski, Alexia F Dickerson et al. · 0 citations
Aug 2026

From Waiting to Action: Why the Autism Field Must Embrace Efficient Service Delivery Models for Diagnostic Assessment.

Waiting lists for an autism evaluation delay timely diagnosis and entry into autism-specific early intervention. To solve this crisis, our field must increase capacity by embracing efficient diagnostic processes. Traditional diagnostic pathways involve complex evaluations and rely on a highly trained but limited pool of specialists, which elongate wait times. Evidence suggests that emerging approaches, including telehealth assessments, primary care diagnosis, and tiered models, reduce barriers. We guide readers through five core issues critical to updating the standard of care for early autism assessment: (1) What are the consequences of maintaining the status quo? (2) What do families prioritize? (3) What evidence supports efficient diagnostic models? (4) What are the consequences of reducing accuracy? and (5) What level of assessment depth is needed to inform action? Our team contends that the critical advantages of adopting efficient service delivery models far outweigh the disadvantages. Collaboration across disciplines, and trust in families' insights, will help build capacity. We conclude with actionable recommendations for clinicians and policymakers in support of adopting these models.Lay AbstractThe growing demand for autism diagnostic services has outpaced available resources. This creates significant delays in first diagnosis and entry into early intervention services (early diagnosis and intervention improve outcomes). Expert diagnosticians in the field have debated - and tested - streamlined and flexible alternative diagnostic processes to speed up access to services; we believe that the advantages of such approaches outweigh the disadvantages, and that evidence supports updating our current standards.

Ashley de Marchena, A. Wieckowski, B. Freedman et al. · 0 citations