Background The accuracy of any screening instrument designed to detect psychopathology among children is ideally assessed through rigorous comparison to ‘gold standard’ tests and interviews. Such comparisons typically yield estimates of what we refer to as ‘standard indices of diagnostic accuracy,’ including sensitivity, specificity, positive predictive value (PPV) and negative predictive value. However, whereas these statistics were originally designed to detect binary signals (e.g., diagnosis present or absent), screening questionnaires commonly used in psychology, psychiatry, and pediatrics typically result in ordinal scores. Thus, a threshold or ‘cut score’ must be applied to these ordinal scores before accuracy can be evaluated using such standard indices. To better understand the tradeoffs inherent in choosing a particular threshold, we discuss the concept of ‘threshold probability.’ In contrast to PPV, which reflects the probability that a child whose score falls at or above the screening threshold has the condition of interest, threshold probability refers specifically to the likelihood that a child whose score is equal to a particular screening threshold has the condition of interest. Method The diagnostic accuracy and threshold probability of two well-validated behavioral assessment instruments, the Child Behavior Checklist Total Problem Scale and the Strengths and Difficulties Questionnaire total scale were examined in relation to a structured psychiatric interview in three de-identified datasets. Results Although both screening measures were effective in identifying groups of children at elevated risk for psychopathology in all samples (odds ratios ranged from 5.2 to 9.7), children who scored at or near the clinical thresholds that optimized sensitivity and specificity were unlikely to meet criteria for psychopathology on gold standard interviews. Conclusions Our results are consistent with the view that screening instruments should be interpreted probabilistically, with attention to where along the continuum of positive scores an individual falls.

There is a critical need for evidence-based, broadband behavioral, and ASD screening measures for use in pediatric and early educational settings to ensure that young children at risk for developing social-emotional disorders and/or ASD are provided with early intervention services to optimize long-term outcomes. The BITSEA is a 42-item screener designed to identify social-emotional/behavioral problems and delays/deficits in social-emotional competence among 11-to-48-month-olds; 19 items describe behaviors consistent with ASD. Secondary data analysis was employed to develop cut-scores for ASD subscales using Receiver Operating Curves, discriminating children with (n=223) and without (n=289) ASD. Cut-scores demonstrated moderate-to-high discriminative power, sensitivity, specificity, and PPV. Findings highlight feasibility of using a broadband social-emotional competence and behavior problem screener to improve early detection of ASD.

Over the past 5 years, a great deal of information about the early course of autism spectrum disorder (ASD) has emerged from longitudinal prospective studies of infants at high risk for developing ASD based on a previously diagnosed older sibling. The current article describes early ASD symptom presentations and outlines the rationale for defining a new disorder, Early Atypical Autism Spectrum Disorder (EA-ASD) to accompany ASD in the new revision of the ZERO TO THREE Diagnostic Classification of Mental Health and Developmental Disorders of Infancy and Early Childhood (DC:0–5) (in press) alternative diagnostic classification manual. EA-ASD is designed to identify children who are 9 to 36 months of age presenting with a minimum of (a) two social-communication symptoms and (b) one repetitive and restricted behavior symptom as well as (c) evidence of impairment, with the intention of providing these children with appropriately tailored services and improving the likelihood of optimizing their development.

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