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Reducing the age of first autism diagnosis facilitates access to critical early intervention services. A current "waitlist crisis" for autism diagnostic evaluation thus demands that we consider novel use of available clinical resources. Previous work has found that expert autism clinicians can identify autism in young children with high specificity after only a brief observation; rapid identification by non-experts remains untested. In the current study, 252 children ages 12-53 months presented for a comprehensive autism diagnostic evaluation. We found that junior clinicians in training to become autism specialists (n = 29) accurately determined whether or not a young child would be diagnosed with autism in the first five minutes of the clinic visit in 75% of cases. Specificity of brief observations was high (0.92), suggesting that brief observations may be an effective tool for triaging young children toward autism-specific interventions. In contrast, the lower negative predictive value (0.71) of brief observations, suggest that they should not be used to rule out autism. When trainees expressed more confidence in their initial impression, their impression was more likely to match the final diagnosis. These findings add to a body of literature showing that clinical observations of suspected autism should be taken seriously, but lack of clinician concern should not be used to rule out autism or overrule other indicators of likely autism, such as parent concern or a positive screening result.

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Importance: The Modified Checklist for Autism in Toddlers (M-CHAT) and the M-CHAT, Revised With Follow-up (M-CHAT-R/F)-henceforth referred to as M-CHAT(-R/F)-are the most commonly used toddler screeners for autism spectrum disorder (ASD). Their use often differs from that in the original validation studies, resulting in a range of estimates of sensitivity and specificity. Also, given the variability in reports of the clinical utility of the M-CHAT(-R/F), researchers and practitioners lack guidance to inform autism screening protocols. Objective: To synthesize variability in sensitivity and specificity of M-CHAT(-R/F) across multiple factors, including procedures for identifying missed cases, likelihood level, screening age, and single compared with repeated screenings. Data Sources: A literature search was conducted with PubMed, Web of Science, and Scopus to identify studies published between January 1, 2001, and August 31, 2022. Study Selection: Articles were included if the studies used the M-CHAT(-R/F) (ie, original or revised version) to identify new ASD cases, were published in English-language peer-reviewed journals, included at least 10 ASD cases, reported procedures for false-negative case identification, screened children by 48 months, and included information (or had information provided by authors when contacted) needed to conduct the meta-analysis. Data Extraction and Synthesis: The systematic review and meta-analysis was conducted within the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guideline. The Quality Assessment of Diagnostic Accuracy Studies-2 tool evaluated bias in sample selection. Data extraction and quality assessment were performed by 2 authors independently. The overall diagnostic accuracy of the M-CHAT(-R/F) was assessed with the hierarchic summary receiver operating characteristic (HSROC) model. Main Outcomes and Measures: Sensitivity, specificity, diagnostic odds ratios, and HSROC curves of M-CHAT(-R/F). Results: The review included 50 studies with 51 samples. The pooled sensitivity of M-CHAT(-R/F) was 0.83 (95% CI, 0.77-0.88), and the pooled specificity was 0.94 (95% CI, 0.89-0.97). Heterogeneity analyses revealed greater diagnostic accuracy for low- vs high-likelihood samples, a concurrent vs prospective case confirmation strategy, a large vs small sample size, use of M-CHAT(-R/F) Follow-up, and non-English vs English only. Conclusions and Relevance: Overall, results of this study suggest the utility of the M-CHAT(-R/F) as an ASD screener. The wide variability in psychometric properties of M-CHAT(-R/F) highlights differences in screener use that should be considered in research and practice.

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Early detection of autism provides access to early intervention and subsequently fewer lifelong challenges. However, disparities in screening have been associated with socioeconomic status (SES) and race, and disparities in surveillance have been associated with clinician knowledge and beliefs about autism identification. The present study examines associations between demographic variables and clinician beliefs, and agreement between screening results and clinician surveillance. Surveillance included activities used by the primary care clinicians (PCCs) to assess risk for autism. PCCs reported their beliefs about autism screening and identification, their sex, race, years in practice, and racial distribution of their patient population. Children's demographic information was also collected. PCCs identified children as having, or not having, an increased likelihood of autism, and parents of children completed an autism screener. Agreement between screening and surveillance results were examined across PCC, practice, and child demographics. Higher confidence in autism knowledge and screening resources, female PCC sex, and majority White practice patient demographics all predicted agreement between screening and surveillance. Female child sex and higher maternal education also predicted agreement between screening and surveillance. These findings highlight the importance of PCC screening beliefs and child and PCC demographics on the autism identification process.