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Speeded Matching (SpM) is a new processing speed match-to-sample test within the NIH Toolbox Cognitive Battery. It was designed to developmentally extend feasibility to younger children or individuals with intellectual or developmental disabilities (IDD). SpM reduces cognitive demands to tapping an identical match as opposed to judging and indicating whether two stimuli are identical. In this study, we piloted SpM among 148 participants with fragile X syndrome, Down syndrome, or other intellectual disabilities (chronological age mean = 17.8 years, sd = 5.4; nonverbal mental age mean = 65 months, sd = 19.4). SpM had a high feasibility (96%) and internal consistency (rxx = 0.98). It converged well with other measures of processing speed, fluid cognition, and nonverbal mental age and diverged appropriately from crystallized cognitive skills. The correlation between nonverbal mental age and SpM in the IDD sample was not significantly different than the correlation between chronological age and SpM in a separate sample of 118 neurotypical children (age mean = 3.9 years sd = 0.8). This study provides initial evidence for the reliability and validity of the new SpM task, which may be appropriate as an outcome measure of processing speed for future clinical trials. It is more feasible than tasks designed for adults; it is brief, easy to administer, and engaging for young children and older individuals with lower mental ages associated with IDD.

BackgroundConcerns have been raised that scores on standard measures of autism spectrum disorder (ASD) symptoms may differ as a function of sex. However, these findings are hindered by small female samples studied thus far. The current study evaluated if, after accounting for age, IQ, and language level, sex affects ASD severity estimates from diagnostic measures among children with ASD.MethodsData were obtained from eight sources comprising 27 sites. Linear mixed-effects models, including a random effect for site, were fit for 10 outcomes (Autism Diagnostic Observation Schedule [ADOS] domain-level calibrated severity scores, Autism Diagnostic Interview-Revised [ADI-R] raw scores by age-based algorithm, and raw scores from the two indices on the Social Responsiveness Scale [SRS]). Sex was added to the models after controlling for age, NVIQ, and an indicator for language level.ResultsSex significantly improved model fit for half of the outcomes, but least square mean differences were generally negligible (effect sizes [ES] < 0.20), increasing to small to moderate in adolescence (ES < 0.40). Boys received more severe RRB scores than girls on both the ADOS and ADI-R (age 4 + algorithm), and girls received more severe scores than boys on both SRS indices, which emerged in adolescence.ConclusionsThis study combined several available databases to create the largest sample of girls with ASD diagnoses. We found minimal differences due to sex beyond other known influences on ASD severity indicators. This may suggest that, among children who ultimately receive a clinical ASD diagnosis, severity estimates do not systematically differ to such an extent that sex-specific scoring procedures would be necessary. However, given the limitations inherent in clinically ascertained samples, future research must address questions about systematic sex differences among children or adults who do not receive clinical diagnoses of ASD. Moreover, while the

Testing cognitive skill development is important for diagnostic, prognostic, and monitoring purposes, especially for young children and individuals with neurodevelopmental disorders. Developmental tests have been created for infants and toddlers, while traditional IQ tests are often employed beginning in the later preschool period. However, IQ tests rely on developmental skills that are rapidly changing during early childhood. Here, we introduce the idea of prerequisite skills in developmental domains, which are discrete skills required for, but not explicitly tested by, traditional IQ tests. Focusing on general cognition, particularly among children with a chronological or mental age under 4 years, may fail to capture important nuances in skill development. New skill-based assessments are needed in general, and in particular for categorization, which is foundational to higher-order cognitive skills. Novel measures quantifying categorization skills would provide a more sensitive measure of development for young children and older individuals with low developmental levels.