Provider perspectives on equity in use of mobile health autism screening tools.

Families may find information about autism online, and health care and education providers may use online tools to screen for autism. However, we do not know if online autism screening tools are easily used by families and providers. We interviewed primary care and educational providers, asking them to review results from online tools that screen for autism.

Consistency and reliability of automated language measures across expressive language samples in autism.

Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder with substantial clinical heterogeneity, especially in language and communication ability. There is a need for validated language outcome measures that show sensitivity to true change for this population. We used Natural Language Processing to analyze expressive language transcripts of 64 highly-verbal children and young adults (age: 6-23 years, mean 12.

Serving young children with communication disabilities from Latinx backgrounds and their families with equity: Provider perspectives.

Introduction: Latinx children with communication disorders from birth to age 5 and their families are increasingly served in United States (US) educational and medical settings where longstanding structural barriers threaten their access to equitable assessment and intervention. However, little is known about providers' perceptions serving this highly diverse population as they relate to reducing disparities in care for communication disorders.

Methods: This exploratory qualitative study interviewed 24 speech-language pathologists (SLPs) and early intervention (EI)/early childhood special education (ECSE) developmental specialists serving young Latinx children with communication disorders to offer targeted recommendations toward improving equity.

Mobile and online consumer tools to screen for autism do not promote equity.

Many parents wonder if their child might have autism. Many parents use their smartphones to answer health questions. We asked, "How easy or hard is it for parents to use their smartphones to find 'tools' to test their child for signs of autism?" After doing pretend parent searches, we found that only one in 10 search results were tools to test children for autism.

Pragmatic Language Markers of Autism Diagnosis and Severity.

Purpose: Assessment of pragmatic language difficulties is limited with conventional tests but can be performed with informant reports. We evaluated the performance of a parent-completed language scale in differentiating autism from typical development (TD) and another neurodevelopmental disorder. Specifically, we aimed to gauge the respective values of structural and pragmatic language scores for diagnostic discrimination and for predicting severity of social impairment in autistic children.

"Um" and "Uh" Usage Patterns in Children with Autism: Associations with Measures of Structural and Pragmatic Language Ability.

Pragmatic language difficulties, including unusual filler usage, are common among children with Autism Spectrum Disorder (ASD). This study investigated "um" and "uh" usage in children with ASD and typically developing (TD) controls. We analyzed transcribed Autism Diagnostic Observation Schedule (ADOS) sessions for 182 children (117 ASD, 65 TD), aged 4 to 15.

Automated Scoring of Tablet-Administered Expressive Language Tests.

Speech and language impairments are common pediatric conditions, with as many as 10% of children experiencing one or both at some point during development. Expressive language disorders in particular often go undiagnosed, underscoring the immediate need for assessments of expressive language that can be administered and scored reliably and objectively. In this paper, we present a set of highly accurate computational models for automatically scoring several common expressive language tasks.

A Pseudo-Value Approach to Analyze the Semantic Similarity of the Speech of Children With and Without Autism Spectrum Disorder.

Conversational impairments are well known among people with autism spectrum disorder (ASD), but their measurement requires time-consuming manual annotation of language samples. Natural language processing (NLP) has shown promise in identifying semantic difficulties when compared to clinician-annotated reference transcripts. Our goal was to develop a novel measure of lexico-semantic similarity - based on recent work in natural language processing (NLP) and recent applications of pseudo-value analysis - which could be applied to transcripts of children's conversational language, without recourse to some ground-truth reference document.

Evaluating atypical language in autism using automated language measures.

Measurement of language atypicalities in Autism Spectrum Disorder (ASD) is cumbersome and costly. Better language outcome measures are needed. Using language transcripts, we generated Automated Language Measures (ALMs) and tested their validity.

Improving ASR Systems for Children with Autism and Language Impairment Using Domain-Focused DNN Transfer Techniques.

This study explores building and improving an automatic speech recognition (ASR) system for children aged 6-9 years and diagnosed with autism spectrum disorder (ASD), language impairment (LI), or both. Working with only 1.5 hours of target data in which children perform the Clinical Evaluation of Language Fundamentals Recalling Sentences task, we apply deep neural network (DNN) weight transfer techniques to adapt a large DNN model trained on the LibriSpeech corpus of adult speech.

Automated Scoring of Clinical Expressive Language Evaluation Tasks.

Many clinical assessment instruments used to diagnose language impairments in children include a task in which the subject must formulate a sentence to describe an image using a specific target word. Because producing sentences in this way requires the speaker to integrate syntactic and semantic knowledge in a complex manner, responses are typically evaluated on several different dimensions of appropriateness yielding a single composite score for each response. In this paper, we present a dataset consisting of non-clinically elicited responses for three related sentence formulation tasks, and we propose an approach for automatically evaluating their appropriateness.

Automatic Assessment of Language Ability in Children with and without Typical Development.

This study describes a fully automated method of expressive language assessment based on vocal responses of children to a sentence repetition task (SRT), a language test that taps into core language skills. Our proposed method automatically transcribes the vocal responses using a test-specific automatic speech recognition system. From the transcriptions, a regression model predicts the gold standard test scores provided by speech-language pathologists.

Early Intervention Referral Outcomes for Children at Increased Risk of Experiencing Developmental Delays.

Objectives: The primary goal was to examine outcomes of Part C early intervention (EI) referrals from a high-risk infant follow-up program and factors associated with success. A secondary aim was to determine how many referred children not evaluated by EI would have likely qualified by either automatically meeting state eligibility criteria with a condition associated with "high-probability" for developmental delays or having test scores evidencing developmental delays.

Methods: Participants included 77 children referred directly to EI from a high-risk infant follow-up program.

Modifying a general social-emotional measure for early autism screening.

Broadband social-emotional screening tools are designed to evaluate a child's social development and interactions. Such tools are expected to have reasonable sensitivity for identifying children at risk for autism spectrum disorder (ASD) but would also likely over-estimate risk for ASD since other conditions can also affect social development. In this study, a subset of ASD items from one general social-emotional screening measure, the Ages & Stages Questionnaires: Social Emotional, 2nd edition, was analyzed to determine if use of an ASD subscale might improve prediction of ASD risk for young children.

Part C Early Intervention Enrollment in Low Birth Weight Infants At-Risk for Developmental Delays.

Objectives To investigate enrollment patterns in Part C Early Intervention (EI) for low birth weight (LBW) infants (≤2500 g). A secondary aim is to characterize LBW infants that are not enrolled in EI, but would qualify by meeting criteria for a condition associated with a "high-probability" for developmental delays (i.e.

Characteristics of the rhythmic organization of vocal babbling: implications for an amodal linguistic rhythm.

Vocal babbling involves production of rhythmic sequences of a mouth close-open alternation giving the perceptual impression of a sequence of consonant-vowel syllables. Petitto and co-workers have argued vocal babbling rhythm is the same as manual syllabic babbling rhythm, in that it has a frequency of 1 cycle per second. They also assert that adult speech and sign language display the same frequency.