Predicting Expressive Language From Early Vocalizations in Young Children With Autism Spectrum Disorder: Which Vocal Measure Is Best?

Does Gestural Communication Influence Later Spoken Language Ability in Minimally Verbal Autistic Children?

PURPOSE

The current study examined the predictive role of gestures and gesture-speech combinations on later spoken language outcomes in minimally verbal (MV) autistic children enrolled in a blended naturalistic developmental/behavioral intervention (Joint Attention, Symbolic Play, Engagement, and Regulation [JASPER] + Enhanced Milieu Teaching [EMT]).

METHOD

Participants were 50 MV autistic children (40 boys), ages 54-105 months (M = 75.54, SD = 16.45). MV was defined as producing fewer than 20 spontaneous, unique, and socially communicative words. Autism symptom severity (Autism Diagnostic Observation Schedule-Second Edition) and nonverbal cognitive skills (Leiter-R Brief IQ) were assessed at entry. A natural language sample (NLS), a 20-min examiner-child interaction with specified toys, was collected at entry (Week 1) and exit (Week 18) from JASPER + EMT intervention. The NLS was coded for gestures (deictic, conventional, and representational) and gesture-speech combinations (reinforcing, disambiguating, supplementary, other) at entry and spoken language outcomes: speech quantity (rate of speech utterances) and speech quality (number of different words [NDW] and mean length of utterance in words [MLUw]) at exit using European Distributed Corpora Project Linguistic Annotator and Systematic Analysis of Language Transcripts.

RESULTS

Controlling for nonverbal IQ and autism symptom severity at entry, rate of gesture-speech combinations (but not gestures alone) at entry was a significant predictor of rate of speech utterances and MLUw at exit. The rate of supplementary gesture-speech combinations, in particular, significantly predicted rate of speech utterances and NDW at exit.

CONCLUSION

These findings highlight the critical importance of gestural communication, particularly gesture-speech (supplementary) combinations in supporting spoken language development in MV autistic children.

Effects of a Contingent Responses Intervention on the Quantity and Quality of Vocalizations of Preschool Children with Autism Spectrum Disorder

Multiple contemporary theories emphasize the quantity and quality of child vocalizations for promoting spoken language acquisition. Yet, empirical evidence for facilitating vocal development is strikingly lacking including for children with autism spectrum disorder (ASD) who have difficulty developing language. We evaluate use of contingent responses and vocal enhancement strategies to increase the quantity and quality of child vocalizations to which adults can respond with language-facilitating input for children with ASD. Three preschool children with ASD and minimal verbal skills participated. Using an alternating treatments design embedded within a multiple probe across participants design, we compared using contingent responses with and without vocal enhancement strategies versus a non-contingent control condition. Based on visual analysis and effect sizes, all participants showed a functional relation between both active intervention conditions and quantity of vocalizations, as predicted. For quality of vocalizations, changes under the active intervention conditions were less pronounced than those observed for quantity. Two participants showed a functional relation between at least one quality variable and the active interventions. Our hypothesis that vocal enhancement strategies would exhibit a value-added effect was partially supported for quantity and quality. Findings support using contingent responses to improve the quantity and to some degree the quality of vocalizations in young children with ASD and minimal verbal skills. Support for the added value of vocal enhancement strategies was mixed. Refining the intervention strategies is warranted to meet the needs of the understudied population of children with ASD and minimal verbal skills.

The Stability and Validity of Automated Indices of Vocal Development in Infants With Autistic and Non-Autistic Siblings

PURPOSE

This study evaluates the extent to which automated indices of vocal development are stable and valid for predicting language in infants at increased familial likelihood for autism and/or language impairment and relatively lower likelihood infants.

METHOD

A group of infants with autistic siblings (Sibs-autism; 20 infants) and a comparison group of infants with non-autistic siblings (Sibs-NA; 20 infants) wore Language ENvironment Analysis (LENA) recording devices for 16 hr on 2 days within a 1-week period. Extant software was used to derive several putative indices of vocal development from these recordings. Stability of these variables was examined across and within groups. Expressive and receptive language aggregates were calculated for each participant. Multiple regression analyses were used to (a) evaluate zero-order correlations for variables derived from LENA recordings with concurrent and future language and (b) test whether those associations were moderated by group status.

RESULTS

Both stability and validity differed by variable and group status. All variables reached acceptable stability in the Sibs-autism group within two to three observations, whereas stability of most variables was attenuated in the Sibs-NA group. No variables were associated with concurrent language in the theoretically motivated direction across groups, but two variables were strongly associated with concurrent expressive language in only the Sibs-NA group. Additionally, two variables were associated with later expressive language, though these correlations were again stronger in the Sibs-NA versus Sibs-autism group.

CONCLUSIONS

Although selected automated indices of vocal development were stable in Sibs-autism and/or valid for predicting expressive language within Sibs-NA, no scores showed strong, theoretically motivated associations with language within the Sibs-autism group. Automated indices of vocal development may, thus, have limited validity or clinical utility for predicting language development in infants at elevated familial likelihood for autism.

SUPPLEMENTAL MATERIAL

https://doi.org/10.23641/asha.24415735.

The Influence of Communication Sample Length on Reliability and Convergent Validity of Vocal Measures Derived From the Communication Complexity Scale

PURPOSE

This study examines the effects of communication sample length on the reliability and convergent validity of six vocal measures for children with autism spectrum disorder (ASD) with minimal verbal skills. The results are expected to inform recommendations for the length of communication samples for clinical and research purposes.

METHOD

Participants included 31 children with ASD (24 boys and seven girls; M _age = 6;7 [years;months], SD = 17 months) with minimal verbal skills. We coded six vocal measures that focus on vocalizations and early word productions from the Communication Complexity Scale (CCS) scripted administration protocol. To evaluate reliability of different sample lengths, we calculated intraclass correlation coefficients between the full CCS sample and 1-, 3-, 7-, 10-, and 20-min samples. To examine convergent validity, we calculated correlations between the six vocal measures for each sample length.

RESULTS

When coded from 10-min samples from the beginning of the CCS, all of the vocal measures exhibit adequate reliability with the full CCS sample. Some vocal measures exhibit adequate reliability with samples as short as 3 min. For convergent validity, all of the correlations between the vocal measures exceed .40 and are statistically significant for the 10-min samples except for some of the correlations with the proportion of communicative vocalizations. Similar results were found for other sample lengths.

CONCLUSION

Findings support coding 10-min segments from the CCS scripted administration protocol to evaluate the vocal development skills of children with ASD with minimal verbal skills.

SUPPLEMENTAL MATERIAL

https://doi.org/10.23641/asha.20999938.

Describing (pre)linguistic oral productions in 3- to 5-year-old autistic children: A cluster analysis

LAY ABSTRACT

For most autistic children, spoken language emergence and development happen after the age of 3. Once they start developing and using spoken language, some eventually manage to reach typical levels of language abilities, while others remain minimally speaking into adulthood. It is therefore difficult to consider young autistic preschoolers as a homogeneous group in terms of spoken language levels. In our study, we breakdown a representative and inclusive group of children on the spectrum aged from 3 to 5 into five subgroups that correspond to different linguistic profiles. To do so, we qualitatively described children's (pre)verbal productions elicited during interactions with a parent and with an experimenter. We then used a type of statistical analysis called cluster analysis to group together the children that had a similar expressive (pre)linguistic behavior. Using this analysis, we were able to delineate five linguistic profiles with qualitatively different patterns of vocal production. Two of these profiles are composed of speaking children; the three others are composed of non- or minimally speaking children. Our findings show that traditional binary division of speaking versus nonspeaking autistic children is not precise enough to describe the heterogeneity of early spoken language in young autistic children. They also support the use of qualitative descriptions of vocal productions and speech to accurately document children's level of language, which could, in turn, help design very finely tailored language intervention specific to each child.

Using big data from long-form recordings to study development and optimize societal impact

Big data are everywhere. In this chapter, we focus on one source: long-form, child-centered recordings collected using wearable technologies. Because these recordings are simultaneously unobtrusive and encompassing, they may be a breakthrough technology for clinicians and researchers from several diverse fields. We demonstrate this possibility by outlining three applications for the recordings-clinical treatment, large-scale interventions, and language documentation-where we see the greatest potential. We argue that incorporating these recordings into basic and applied research will result in more equitable treatment of patients, more reliable measurements of the effects of interventions on real-world behavior, and deeper scientific insights with less observational bias. We conclude by outlining a proposal for a semistructured online platform where vast numbers of long-form recordings could be hosted and more representative, less biased algorithms could be trained.

Vocal development in a large-scale crosslinguistic corpus

This study evaluates whether early vocalizations develop in similar ways in children across diverse cultural contexts. We analyze data from daylong audio recordings of 49 children (1-36 months) from five different language/cultural backgrounds. Citizen scientists annotated these recordings to determine if child vocalizations contained canonical transitions or not (e.g., "ba" vs. "ee"). Results revealed that the proportion of clips reported to contain canonical transitions increased with age. Furthermore, this proportion exceeded 0.15 by around 7 months, replicating and extending previous findings on canonical vocalization development but using data from the natural environments of a culturally and linguistically diverse sample. This work explores how crowdsourcing can be used to annotate corpora, helping establish developmental milestones relevant to multiple languages and cultures. Lower inter-annotator reliability on the crowdsourcing platform, relative to more traditional in-lab expert annotators, means that a larger number of unique annotators and/or annotations are required, and that crowdsourcing may not be a suitable method for more fine-grained annotation decisions. Audio clips used for this project are compiled into a large-scale infant vocalization corpus that is available for other researchers to use in future work.

Describing Vocalizations in Young Children: A Big Data Approach Through Citizen Science Annotation

Purpose Recording young children's vocalizations through wearables is a promising method to assess language development. However, accurately and rapidly annotating these files remains challenging. Online crowdsourcing with the collaboration of citizen scientists could be a feasible solution. In this article, we assess the extent to which citizen scientists' annotations align with those gathered in the lab for recordings collected from young children. Method Segments identified by Language ENvironment Analysis as produced by the key child were extracted from one daylong recording for each of 20 participants: 10 low-risk control children and 10 children diagnosed with Angelman syndrome, a neurogenetic syndrome characterized by severe language impairments. Speech samples were annotated by trained annotators in the laboratory as well as by citizen scientists on Zooniverse. All annotators assigned one of five labels to each sample: Canonical, Noncanonical, Crying, Laughing, and Junk. This allowed the derivation of two child-level vocalization metrics: the Linguistic Proportion and the Canonical Proportion. Results At the segment level, Zooniverse classifications had moderate precision and recall. More importantly, the Linguistic Proportion and the Canonical Proportion derived from Zooniverse annotations were highly correlated with those derived from laboratory annotations. Conclusions Annotations obtained through a citizen science platform can help us overcome challenges posed by the process of annotating daylong speech recordings. Particularly when used in composites or derived metrics, such annotations can be used to investigate early markers of language delays.

A home-based longitudinal study of vocalization behaviors across infants at low and elevated risk of autism

BACKGROUND AND AIMS

The purpose of this exploratory study was to expand existing literature on prelinguistic vocalizations by reporting results of the first home-based longitudinal study examining a wide variety of behaviors and characteristics, including early vocalizations, across infants at low and elevated risk of autism spectrum disorder (ASD). The study of vocalizations and vocalization changes across early developmental periods shows promise in reflecting early clinically significant differences across infants at low and elevated risk of ASD. Observations of early vocalizations and their differences during infancy could provide a reliable and essential component of an early developmental profile that would lower the average diagnostic age for ASD. However, studies employing observation of vocalization behaviors have been limited and often conducted in laboratory settings, reducing the external generalization of the findings.

METHODS

The present study was conducted to determine the consistency of previous findings with longitudinal data collected in home environments. Infants in the present study represented elevated risk from two etiological backgrounds, (a) infants born prematurely and with low birth weight and (b) infants who had an older sibling diagnosed with ASD. All data were collected in the infants' homes and compared with data collected from infants with low likelihood of ASD. The study included 44 participants (31 in the low-risk sample, 13 in the high-risk sample) with vocalization behaviors observed at 6- and 12-months through 20-min semi-structured play interactions with caregivers. Observations were video-recorded and later coded for speech and non-speech vocalizations.

RESULTS

Differences in the 6-month vocalization behaviors were not statistically significant across risk levels of ASD. By 12 months; however, risk group differences were evident in the total number of vocalizations overall with specific differences across groups representing moderate to large, clinically relevant effects. Infants at low risk of ASD demonstrated significantly greater developmental change between 6- and 12-months than did the infants at high risk. Data were also reviewed for differences across high-risk group etiologies.

CONCLUSIONS

The present study was unique and innovative in a number of ways as the first home-based longitudinal study examining infant vocal behaviors across low and high risk of ASD. Many of the present study findings were consistent with previous cross-sectional investigations of infants at elevated risk for ASD, indicating support for further home-based longitudinal study in this area. Findings also indicated some preliminary subgroup differences between high-risk etiologies of ASD. Vocalization differences across high risk groups had not been previously addressed in the literature.

IMPLICATIONS

Vocalization differences are notable by 12-months of age between infants at low and elevated risk of ASD and infants at high risk demonstrated reduced developmental changes between 6- and 12-months compared to the infants at low risk. Observation of early infant vocalization behaviors may reasonably occur in the home, providing early childhood professionals and researchers with empirical support for data collection of child-caregiver interactions in this setting. Potential differences across high-risk etiologies warrant further investigation.