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Lay Summary: Specialists conduct autism evaluations using tools that are expensive and difficult to get trained on. Families often wait a long time and travel far to get a diagnosis for their child. To help with this problem, primary care practitioners can be trained to provide evaluations in local communities. However, usable and accurate tools developed for non-specialists are needed. The Screening Tool for Autism in Toddlers and Young Children (STAT) was created for this purpose, but limited research has been done on accuracy of the tool in community primary care. This study tested the STAT when used by primary care practitioners as part of a diagnostic evaluation in 130, 14- to 48-month-old children. We tested (1) STAT agreement with the Autism Diagnostic Observation Schedule, Second Edition (ADOS-2), and diagnosis based on an expert research evaluation, and (2) the relationship between STAT classification, primary care practitioner diagnosis, and expert diagnosis. STAT classification matched the ADOS-2 in 77% of cases and expert diagnosis in 78% of cases. Autistic children incorrectly classified by the STAT were older, had higher developmental and adaptive skills, and fewer autism symptoms. In 86% of cases, the STAT classification agreed with primary care practitioner diagnosis. STAT classification, primary care practitioner diagnosis, and expert diagnosis agreed in 73% of cases. Overall, the STAT shows good accuracy when used by primary care practitioners as part of a community primary care autism evaluation., Competing Interests: Declaration of conflicting interestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Importance: Finding effective and scalable solutions to address diagnostic delays and disparities in autism is a public health imperative. Approaches that integrate eye-tracking biomarkers into tiered community-based models of autism evaluation hold promise for addressing this problem., Objective: To determine whether a battery of eye-tracking biomarkers can reliably differentiate young children with and without autism in a community-referred sample collected during clinical evaluation in the primary care setting and to evaluate whether combining eye-tracking biomarkers with primary care practitioner (PCP) diagnosis and diagnostic certainty is associated with diagnostic outcome., Design, Setting, and Participants: Early Autism Evaluation (EAE) Hub system PCPs referred a consecutive sample of children to this prospective diagnostic study for blinded eye-tracking index test and follow-up expert evaluation from June 7, 2019, to September 23, 2022. Participants included 146 children (aged 14-48 months) consecutively referred by 7 EAE Hubs. Of 154 children enrolled, 146 provided usable data for at least 1 eye-tracking measure., Main Outcomes and Measures: The primary outcomes were sensitivity and specificity of a composite eye-tracking (ie, index) test, which was a consolidated measure based on significant eye-tracking indices, compared with reference standard expert clinical autism diagnosis. Secondary outcome measures were sensitivity and specificity of an integrated approach using an index test and PCP diagnosis and certainty., Results: Among 146 children (mean [SD] age, 2.6 [0.6] years; 104 [71%] male; 21 [14%] Hispanic or Latine and 96 [66%] non-Latine White; 102 [70%] with a reference standard autism diagnosis), 113 (77%) had concordant autism outcomes between the index (composite biomarker) and reference outcomes, with 77.5% sensitivity (95% CI, 68.4%-84.5%) and 77.3% specificity (95% CI, 63.0%-87.2%). When index diagnosis was based on the combination of a composite biomarker, PCP diagnosis, and diagnostic certainty, outcomes were concordant with reference standard for 114 of 127 cases (90%) with a sensitivity of 90.7% (95% CI, 83.3%-95.0%) and a specificity of 86.7% (95% CI, 70.3%-94.7%)., Conclusions and Relevance: In this prospective diagnostic study, a composite eye-tracking biomarker was associated with a best-estimate clinical diagnosis of autism, and an integrated diagnostic model including PCP diagnosis and diagnostic certainty demonstrated improved sensitivity and specificity. These findings suggest that equipping PCPs with a multimethod diagnostic approach has the potential to substantially improve access to timely, accurate diagnosis in local communities.

Objectives: To evaluate the diagnostic accuracy of the Early Autism Evaluation (EAE) Hub system, a statewide network that provides specialized training and collaborative support to community primary care providers in the diagnosis of young children at risk for autism spectrum disorder (ASD)., Methods: EAE Hub clinicians referred children, aged 14 to 48 months, to this prospective diagnostic study for blinded follow-up expert evaluation including assessment of developmental level, adaptive behavior, and ASD symptom severity. The primary outcome was agreement on categorical ASD diagnosis between EAE Hub clinician (index diagnosis) and ASD expert (reference standard)., Results: Among 126 children (mean age: 2.6 years; 77% male; 14% Latinx; 66% non-Latinx white), 82% (n = 103) had consistent ASD outcomes between the index and reference evaluation. Sensitivity was 81.5%, specificity was 82.4%, positive predictive value was 92.6%, and negative predictive value was 62.2%. There was no difference in accuracy by EAE Hub clinician or site. Across measures of development, there were significant differences between true positive and false negative (FN) cases (all Ps < .001; Cohen's d = 1.1-1.4), with true positive cases evidencing greater impairment., Conclusions: Community-based primary care clinicians who receive specialty training can make accurate ASD diagnoses in most cases. Diagnostic disagreements were predominately FN cases in which EAE Hub clinicians had difficulty differentiating ASD and global developmental delay. FN cases were associated with a differential diagnostic and phenotypic profile. This research has significant implications for the development of future population health solutions that address ASD diagnostic delays., (Copyright © 2023 by the American Academy of Pediatrics.)

Lay Abstract: The diagnosis of autism spectrum disorder (ASD) has traditionally been made through in-person evaluation. While the COVID-19 pandemic disrupted access to ASD services, there has been remarkable growth in research focused on novel ASD diagnostic practices, including the use of telemedicine. We implemented a standard ASD tele-assessment evaluation procedure, including use of a novel remote clinician-coached, caregiver-delivered ASD assessment tool (TELE-ASD-PEDS; TAP), with the goal of continuing to provide diagnostic services to young children and their families during the pandemic. We examined the relationship between child characteristics and diagnostic outcome for 335 children, ages 14-78 months, who received ASD tele-assessment conducted by psychologists and pediatricians in an outpatient clinic of a Midwestern academic medical center. We found that clinicians could make a determination about ASD diagnosis for most children (85%) evaluated using tele-assessment. Child clinical characteristics, including TAP scores and clinician ratings of ASD symptoms, were related to diagnostic outcome (i.e. diagnosis of ASD, no ASD, and Unsure about ASD). When all clinical characteristics were examined together, the presence of specific repetitive behaviors predicted ASD diagnosis. We also found that the TAP is effective for making an ASD diagnosis when used as part of comprehensive tele-assessment evaluation in children ⩾ 36 months of age with delayed language. Our study adds to an increasing body of research supporting use of tele-assessment for diagnosis of ASD. Although further research is needed, telemedicine may help families from different backgrounds and geographic locations to access high-quality diagnostic services.

Introduction: We report caregiver agreement to attend telehealth neurodevelopmental consultation during COVID-19, demographic differences in agreement, reasons families declined, and clinical access metrics before and during COVID-19., Method: Data were gathered from telehealth referrals and consultations from April to July 2020. Schedulers documented agreement status and reasons for the decline. Wait time, lag time, and missed appointment rates were calculated to measure access., Results: Ninety-one percent agreed to attend telehealth consultation; 55% of those who declined preferred in-person services. There were no demographic differences between those who accepted, declined, or did not respond. The median wait time from referral to appointment was 60 days. Missed appointment rates were consistent with prepandemic rates., Discussion: Findings support literature suggesting patients are agreeable to telehealth. They diverged from evidence suggesting telehealth reduces missed appointments. Overall, results indicate telehealth is an acceptable alternative; however, further telehealth innovation is needed to address existing disparities., (Copyright © 2022 National Association of Pediatric Nurse Practitioners. Published by Elsevier Inc. All rights reserved.)

Adolescents with autism often experience pronounced difficulties with social communication, and novel interventions designed to improve core abilities are greatly needed. This study examines if providing immediate video feedback, an extension of video self-modeling, can aid adolescents with autism to self-identify strengths and irregularities from their social interactions. Using multiple baseline design across four participants, individuals engaged in naturalistic conversations wearing video recording glasses. During the intervention, videos were reviewed immediately and participants recognized when they were not following typical social-communicative convention. Based on observational data coded from videos, all four participants modified their behavior during subsequent conversations. Although adolescents with autism may hypothetically know to behave, viewing themselves on video may provide practical cues to support social insight and behavioral change.