Identifying Childhood Expressive Language Features That Best Predict Adult Language and Communication Outcome in Individuals With Autism Spectrum Disorder

LeGrand, Kaya J; Weil, Lisa Wisman; Lord, Catherine; Luyster, Rhiannon

doi:10.1044/2021_jslhr-20-00544

Cited by 15 publications

(6 citation statements)

References 70 publications

(111 reference statements)

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“…For instance, the probability that an increase of 15 in social skills standard scores was associated with a grammaticality judgment A’ score increase ≥ 1 was 5%, indicating a very low probability of even a small association between performance on these measures. These results suggest that grammaticality judgment performance is not meaningfully associated with social skills in individuals similar to our participant sample, and that these measures may not be sensitive to associations between language and social function observed in prior work (e.g., between VABS expressive language and VABS socialization, Park et al, 2012, and between verb diversity and ADOS scores, LeGrand et al, 2021).…”

Section: Bayesian Analysis Step 3: Interpreting Resultscontrasting

confidence: 59%

A Bayesian statistics tutorial for clinical research: Prior distributions and meaningful results for small clinical samples

et al. 2023

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ObjectivesBayesian statistics provides an effective, reliable approach for research with small clinical samples and yields clinically meaningful results that can bridge research and practice. This tutorial demonstrates how Bayesian statistics can be effectively and reliably implemented with a small, heterogeneous participant sample to promote reproducible and clinically relevant research.Methods/ResultsWe tested example research questions pertaining to language and clinical features in autism spectrum disorder (ASD; n = 20), a condition characterized by significant heterogeneity. We provide step‐by‐step instructions and visualizations detailing how to (1) identify and develop prior distributions from the literature base, (2) evaluate model convergence and reliability, and (3) compare models with different prior distributions to select the best performing model. Moreover, in step three, we demonstrate how to determine whether a sample size is sufficient for reliably interpreting model results. We also provide instructions detailing how to examine results with varied bounds of clinical interest, such as the probability that an effect will reflect at least one standard deviation change in scores on a standardized assessment. This information facilitates generalization and application of Bayesian results to a variety of clinical research questions and settings.ConclusionThe tutorial concludes with suggestions for future clinical research, ensuring the utility of our step‐by‐step instructions for a broad clinical audience.

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Section: Bayesian Analysis Step 3: Interpreting Resultscontrasting

confidence: 59%

A Bayesian statistics tutorial for clinical research: Prior distributions and meaningful results for small clinical samples

et al. 2023

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“…One benefit of assessing receptive vocabulary using eye gaze is that performance on noun trials predicts later language and developmental outcomes (e.g., [ 10 ]); in theory, such information may have a role in clinical decision-making. Although verbs may be particularly powerful predictors of later language skills [ 18 , 19 ], whether eye gaze measures for receptive verb vocabulary can predict later language abilities is yet unstudied. We propose future work considering whether verb processing (latency, for older children) and broader processing abilities (start time of individualized response window) predict later outcomes.…”

Section: Discussionmentioning

confidence: 99%

“…We argue that verbs are critically important to consider. Verb meanings are strongly tied to the structure of the sentences in which they appear, and verb knowledge is a better predictor of later language outcomes than noun knowledge [ 18 , 19 ]. Moreover, limited verb knowledge is considered a warning sign for a later diagnosis of language disorder [ 20 ], and it has been hypothesized that understanding late talkers’ verb vocabularies, in particular, may help researchers and clinicians ultimately distinguish between those at greatest risk for language disorder and those likely to “catch up” to typically developing peers [ 21 ].…”

Section: Introductionmentioning

confidence: 99%

Assessing receptive verb knowledge in late talkers and autistic children: advances and cautionary tales

Horvath,

Arunachalam

2023

J Neurodevelop Disord

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Purpose Using eye-tracking, we assessed the receptive verb vocabularies of age-matched late talkers and typically developing children (experiment 1) and autistic preschoolers (experiment 2). We evaluated how many verbs participants knew and how quickly they processed the linguistic prompt. Our goal is to explore how these eye-gaze measures can be operationalized to capture verb knowledge in late talkers and autistic children. Method Participants previewed two dynamic scenes side-by-side (e.g., “stretching” and “clapping”) and were then prompted to find the target verb's referent. Children’s eye-gaze behaviors were operationalized using established approaches in the field with modifications in consideration for the type of stimuli (dynamic scenes versus static images) and the populations included. Accuracy was calculated as a proportion of time spent looking to the target, and linguistic processing was operationalized as latency of children’s first look to the target. Results In experiment 1, there were no group differences in the proportion of verbs known, but late talkers required longer to demonstrate their knowledge than typically developing children. Latency was predicted by age but not language abilities. In experiment 2, autistic children’s accuracy and latency were both predicted by receptive language abilities. Conclusion Eye gaze can be used to assess receptive verb vocabulary in a variety of populations, but in operationalizing gaze behavior, we must account for between- and within-group differences. Bootstrapped cluster-permutation analysis is one way to create individualized measures of children’s gaze behavior, but more research is warranted using an individual differences approach with this type of analysis.

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“…Early expressive language is a predictor of long‐term social‐communicative, cognitive and adaptive outcomes for autistic children (Arnett et al., 2020; LeGrand et al., 2021). Delays in language acquisition are common in autistic children and approximately 65% of autistic children are minimally verbal before 5 years old (Maltman et al., 2021).…”

Section: Introductionmentioning

confidence: 99%

Prelinguistic communication complexity predicts expressive language in initial minimally verbal autistic children

Liu,

Brady,

Boorom

et al. 2023

Intl J Lang & Comm Disor

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BackgroundPrelinguistic communication complexity refers to the use of different communication forms such as eye gaze, gestures and vocalisations and the degree to which these forms are coordinated and how directed to a communication partner. To date, little is known about the relationship between prelinguistic communication complexity and expressive language in minimally verbal autistic children.AimsTo test the hypothesis that prelinguistic communication complexity predicts expressive language 12 months later in autistic children and explore whether there are any differences in specific prelinguistic intentional communicative behaviours that are related to later expressive language levels.Methods & ProceduresThis longitudinal study examined 37 minimally verbal autistic children (29–71 months old). The Communication Complexity Scale (CCS) was used to measure participants’ prelinguistic communication behaviours, which were extracted from a semi‐structured play interaction at Time 1. The Chinese Communicative Development Inventory (CCDI) was used to examine participants’ expressive language at Time 1 and Time 2 (12 months later). According to Time 2 vocabulary size, participants were divided into two groups: Low CCDI, between 0 and 62 words, and High CCDI, more than 100 words. Linear regression was used to examine the relationship between early prelinguistic communication complexity and later expressive language. Binary logistic regression was used to determine which of the early communication behaviours were uniquely significantly related to later expressive language levels.Outcomes & ResultsThere was a significant positive relationship between prelinguistic communication complexity and expressive language 12 months later, even after controlling for age and concurrent language. Findings revealed a group difference in the frequency of gesture and vocalisation combinations between the Low and High CCDI groups at Time 1. Gesture‐vocalisation combinations also predicted better expressive language levels at Time 2.Conclusions & ImplicationsOur findings suggest that it may be beneficial to incorporate different complex communication behaviours into prelinguistic intervention targets for minimally verbal autistic children. The CCS hierarchies can be used as a reference for the intervention goals of minimally verbal autistic children. These findings highlight the importance of targeting gesture and vocalisation combinations when autistic children transition from single prelinguistic communication behaviours to multimodal behaviours.What this paper addsWhat is already known on this subject Children use eye gaze, gestures and vocalisations to communicate with others before they learn spoken language. There is strong evidence suggest that the frequency of prelinguistic communication predicts later linguistic achievements in autistic children. However, less is known about whether prelinguistic communication complexity also predicts later language and which specific behaviours are most predictive of language outcomes.What this study adds Minimally verbal autistic children who exhibit more complex prelinguistic communication behaviours have better expressive language 12 months later. Gestures combined with vocalisations predict better expressive language in minimally verbal autistic children.What are the clinical implications of this work? When identifying intervention targets for minimally verbal autistic children, the clinicians may reference the prelinguistic communication behaviours from the CCS. The gesture and vocalisation combinations are the key behaviours when targets transit from single form to two‐form behaviours.

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Identifying Childhood Expressive Language Features That Best Predict Adult Language and Communication Outcome in Individuals With Autism Spectrum Disorder

Cited by 15 publications

References 70 publications

A Bayesian statistics tutorial for clinical research: Prior distributions and meaningful results for small clinical samples

A Bayesian statistics tutorial for clinical research: Prior distributions and meaningful results for small clinical samples

Assessing receptive verb knowledge in late talkers and autistic children: advances and cautionary tales

Prelinguistic communication complexity predicts expressive language in initial minimally verbal autistic children

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