Language ENvironment Analysis (LENA) in Phelan-McDermid Syndrome: Validity and Suggestions for Use in Minimally Verbal Children with Autism Spectrum Disorder

Hamrick L, Marklund E, Kalashnikova M, Guez A, Casillas M, Benetti L, van Alphen P, Cristia A. Everyday language input and production in 1,001 children from six continents

Language is a universal human ability, acquired readily by young children, who otherwise struggle with many basics of survival. And yet, language ability is variable across individuals. Naturalistic and experimental observations suggest that children's linguistic skills vary with factors like socioeconomic status and children's gender. But which factors really influence children's day-to-day language use? Here, we leverage speech technology in a big-data approach to report on a unique cross-cultural and diverse data set: >2,500 d-long, child-centered audio-recordings of 1,001 2- to 48-mo-olds from 12 countries spanning six continents across urban, farmer-forager, and subsistence-farming contexts. As expected, age and language-relevant clinical risks and diagnoses predicted how much speech (and speech-like vocalization) children produced. Critically, so too did adult talk in children's environments: Children who heard more talk from adults produced more speech. In contrast to previous conclusions based on more limited sampling methods and a different set of language proxies, socioeconomic status (operationalized as maternal education) was not significantly associated with children's productions over the first 4 y of life, and neither were gender or multilingualism. These findings from large-scale naturalistic data advance our understanding of which factors are robust predictors of variability in the speech behaviors of young learners in a wide range of everyday contexts.

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.

Early-onset catatonia associated with SHANK3 mutations: looking at the autism spectrum through the prism of psychomotor phenomena

Background

Individuals with Phelan-McDermid syndrome (PMS) present with a wide range of diagnoses: autism spectrum disorder, intellectual disability, or schizophrenia. Differences in the genetic background could explain these different neurodevelopmental trajectories. However, a more parsimonious hypothesis is to consider that they may be the same phenotypic entity. Catatonic disturbances occasionally reported from adolescence onwards in PMS prompts exploration of the hypothesis that this clinical entity may be an early-onset form of catatonia. The largest cohort of children with childhood catatonia was studied by the Wernicke-Kleist-Leonhard school (WKL school), which regards catatonia as a collection of qualitative abnormalities of psychomotricity that predominantly affecting involuntary motricity (reactive and expressive). The aim of this study was to investigate the presence of psychomotor signs in three young adults carrying a mutation or intragenic deletion of the SHANK3 gene through the prism of the WKL school conception of catatonia.

Methods

This study was designed as an exploratory case study. Current and childhood psychomotor phenomena were investigated through semi-structured interviews with the parents, direct interaction with the participants, and the study of documents reporting observations of the participants at school or by other healthcare professionals.

Results

The findings show catatonic manifestations from childhood that evolved into a chronic form, with possible phases of sub-acute exacerbations starting from adolescence.

Conclusion

The presence of catatonic symptoms from childhood associated with autistic traits leads us to consider that this singular entity fundamentally related to SHANK3 mutations could be a form of early-onset catatonia. Further case studies are needed to confirm our observations.

Consensus recommendations on communication, language and speech in Phelan-McDermid syndrome

Phelan-McDermid syndrome is a genetic condition primarily caused by a deletion on the 22q13.3 region or a likely pathogenic/pathogenic variant of SHANK3. The main features comprise global developmental delay, marked impairment or absence of speech, and other clinical characteristics to a variable degree, such as hypotonia or psychiatric comorbidities. A set of clinical guidelines for health professionals covering relevant aspects of clinical management have been written by the European PMS Consortium, and consensus has been reached regarding final recommendations. In this work, attention is given to communication, language and speech impairments in PMS, and the findings from available literature are presented. Findings from the literature review reveal marked speech impairment in up to 88% of deletions and 70% of SHANK3 variants. Absence of speech is frequent and affects 50%-80% of the individuals with PMS. Communicative skills in the expressive domain other than spoken language remain understudied, but some studies offer data on non-verbal language or the use of alternative/augmentative communication support. Loss of language and other developmental skills is reported in around 40% of individuals, with variable course. Deletion size and possibly other clinical variables (e.g., conductive hearing problems, neurological issues, intellectual disability, etc.) are related to communicative and linguistic abilities. Recommendations include regular medical check-ups of hearing and the assessment of other factors influencing communication, thorough evaluation of preverbal and verbal communicative skills, early intervention, and support via alternative/augmentative communication systems.

The home environment and its relation to vocalizations in the first year of life

Background

Prior data has shown that the home environment impacts child development; however, there remains a paucity of research on how the home environment relates to child and adult words. Therefore, the aim of this prospective and quantitative study was to examine the relationship between the home environment and the quantity of vocalizations or words, and conversational turns produced by infants and parents at 3 and 12 months of age.

Methods

Seventy-two (56% male) full-term infants were assessed at 3 and 12 months of age. The home environment was assessed in person via interview and observation of the child's home using the Infant-Toddler Home Observation for Measurement of the Environment (IT-HOME) Inventory subscales. Vocalizations were measured using the Language Environment Analysis (LENA) device, which measures the adult word count, child vocalization count and conversational turn count. These measures were then averaged for the most voluble, or vocal hour, in the recording period.

Results

At 3 months, IT-HOME Learning Materials scores were significantly associated with a decrease in adult words. We found a statistically significant difference in LENA outcomes between 3 and 12 months when stratified by sex. Specifically, male infants had significantly fewer vocalizations at 12 months when compared to 3 months, whereas females had more vocalizations. There was also a statistically significant difference in IT-HOME Learning Materials, Organization, Responsivity, and Total scores when comparing 3- and 12-month time points.

Conclusions

These findings reveal that the home environment changes significantly over the first year of life. At 3 months, Learning Materials in the home were related to adult words, while between 3 and 12 months, several aspects of the home significantly changed. Male children had reduced vocalizations between 3 and 12 months; whereas, female children had increased vocalizations during the same time points. Future research should focus on examining these outcomes with multiple measures, time points, and patient populations.

The utility of LENA as an indicator of developmental outcomes for young children with autism

BACKGROUND

There is growing understanding of the potential benefits of a multi-method approach to accurately capture language skills of children on the autism spectrum. Tools such as Language ENvironment Analysis (LENA) provide an efficient means of capturing and analysing early child vocalizations (CVs) and the language learning environment. While developed to capture whole-day recordings of child language in naturalistic settings, there is potential utility in capturing, but little knowledge about, primary LENA metrics-including CVs and conversational turns (CTs)-and novel metrics, such as vocalization ratios (VRs), sampled in clinical practice settings where children are often seen. Moreover, recent research indicates that the novel VR may offer a broad indicator of children's developmental level, beyond just their language abilities, a hypothesis yet to be investigated in a large sample of children for whom the LENA was designed (i.e., pre-schoolers).

AIMS

To explore the extent to which primary and novel LENA metrics collected during brief one-to-one clinical interaction was a useful indicator of developmental outcomes for children on the autism spectrum.

METHODS & PROCEDURES

Participants were recruited as part of an on-going research programme evaluating early intervention outcomes (n = 99; age 14-47 months). Language samples were collected at intake (T1) using the wearable LENA Digital Language Processors during a one-to-one, play-based assessment with a clinician. Direct (Mullen Scales of Early Learning-MSEL) and parent-report (Vineland Adaptive Behavior Scales-VABS) measures of verbal and non-verbal skills were also collected at intake (T1) and again at exit (T2), approximately 12 months later.

OUTCOMES & RESULTS

Few correlations were observed between child measures and CVs, a primary LENA metric. The novel VR metric was associated with concurrent direct assessment (MSEL) (and to a lesser extent parent report; VABS) measures of verbal and non-verbal skills, with moderate positive correlations found between VRs and all directly assessed subscale scores. However, VRs did not uniquely contribute to the prediction of child outcomes when baseline skills were also considered.

CONCLUSIONS & IMPLICATIONS

The novel VR may provide an insight into autistic children's overall development in addition to their language ability, suggesting that even when collected in a short recording format, LENA might be a useful component of a multi-method assessment approach.

WHAT THIS PAPER ADDS

What is already known on the subject To accurately capture language skills of children on the autism spectrum, multi-method approaches, including natural language sampling, are recommended. Tools such as LENA provide an efficient means of capturing and analysing naturalistic child language and the language learning environment. What this paper adds to existing knowledge This study demonstrates the potential benefits, and limitations, of using LENA to augment assessment of young children on the autism spectrum. Specifically, LENA provides a complementary, and low burden, method for capturing child language samples. What are the potential or actual clinical implications of this work? Novel metrics, such as the VR, collected during brief clinical interactions might be a useful component of a multi-method assessment approach for children on the autism spectrum.

Social visual attentional engagement and memory in Phelan-McDermid syndrome and autism spectrum disorder: a pilot eye tracking study

BACKGROUND

The current study used eye tracking to investigate attention and recognition memory in Phelan-McDermid syndrome (PMS), a rare genetic disorder characterized by intellectual disability, motor delays, and a high likelihood of comorbid autism spectrum disorder (ASD). Social deficits represent a core feature of ASD, including decreased propensity to orient to or show preference for social stimuli.

METHODS

We used a visual paired-comparison task with both social and non-social images, assessing looking behavior to a novel image versus a previously viewed familiar image to characterize social attention and recognition memory in PMS (n = 22), idiopathic ASD (iASD, n = 38), and typically developing (TD) controls (n = 26). The idiopathic ASD cohort was divided into subgroups with intellectual disabilities (ID; developmental quotient < 70) and without (developmental quotient > 70) and the PMS group into those with and without a co-morbid ASD diagnosis.

RESULTS

On measures of attention, the PMS group with a comorbid ASD diagnosis spent less time viewing the social images compared to non-social images; the rate of looking back and forth between images was lowest in the iASD with ID group. Furthermore, while all groups demonstrated intact recognition memory when novel non-social stimuli were initially presented (pre-switch), participants with PMS showed no preference during the post-switch memory presentation. In iASD, the group without ID, but not the group with ID, showed a novelty preference for social stimuli. Across indices, individuals with PMS and ASD performed more similarly to PMS without ASD and less similarly to the iASD group.

CONCLUSION

These findings demonstrate further evidence of differences in attention and memory for social stimuli in ASD and provide contrasts between iASD and PMS.

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.

Clinician Proposed Predictors of Spoken Language Outcomes for Minimally Verbal Children with Autism Spectrum Disorder

Our aim was to explore insights from clinical practice that may inform efforts to understand and account for factors that predict spoken language outcomes for children with Autism Spectrum Disorder who use minimal verbal language. We used a qualitative design involving three focus groups with 14 speech pathologists to explore their views and experiences. Using the Framework Method of analysis, we identified 9 themes accounting for 183 different participant references to potential factors. Participants highlighted the relevance of clusters of fine-grained social, communication, and learning behaviours, including novel insights into prelinguistic vocal behaviours. The participants suggested the potential value of dynamic assessment in predicting spoken language outcomes. The findings can inform efforts to developing clinically relevant methods for predicting children's communication outcomes.

A modular, extensible approach to massive ecologically valid behavioral data

We explore here the application of modern computer hardware and software to the collection and analysis of behavioral data. We discuss the issues of ecological validity, storage and processing, data permanence, automation, validity, and algorithmic determinism. Taking the modern landscape into account, we demonstrate several varying projects we have recently undertaken as proofs of concept of the viability and utility of this approach. In particular, we describe four research projects, which involve work on child-directed speech; the application of automatic methods to clinical populations, including children with hearing loss; quality control and the assessment of validity; and the sharing of data in a public database. We conclude by pointing out how the methodology described here can be extended to a wide variety of interdisciplinary and detailed projects that are likely to lead to better science and improved outcomes for populations served by the behavioral, social, and health sciences.

Profiles of vocalization change in children with autism receiving early intervention

Children with autism spectrum disorder (ASD) commonly present with comorbid language impairment, negatively impacting their learning and participation across settings. Addressing these needs requires a detailed understanding of their communication trajectories. In this study, we used the language environment and analysis (LENA) system to examine possible changes in children's (a) vocalizations and (b) ratio of speech to nonspeech vocalizations over a 10-month period. Data for 23 children with ASD (17M, 6F; ages 32-67 months) were analyzed, including monthly 3-hr in-class recordings and standardized measures of language, cognition, and ASD characteristics. Using hierarchical generalized linear models, we found significant time-trends for child vocalizations (P ≤ 0.001) and the vocalization ratio (P = 0.02), reflecting a waxing and waning pattern. Children with higher expressive language scores (Mullen scales of early learning, Vineland adaptive behavior scales - 2nd Ed.) and nonverbal cognition (Mullen scales of early learning), and fewer ASD characteristics (social communication questionnaire) demonstrated greater increases in the vocalization ratio over time (P values 0.04-0.01). Children with greater language and cognition difficulties were the most vocal, but produced a higher proportion of nonspeech vocalizations. The results demonstrate that significant fluctuations, as opposed to linear increases, may be observed in children with ASD receiving intervention, highlighting the value of assessment at multiple time-points. In addition, the findings highlight the need to consider both the quantity (vocalization counts) and quality (ratio of speech to nonspeech vocalizations) when interpreting LENA data, with the latter appearing to provide a more robust measure of communication. Autism Research 2019, 12: 830-842. © 2019 International Society for Autism Research, Wiley Periodicals, Inc. LAY ABSTRACT: In this study, we examined possible changes in speech and nonspeech vocalizations in 23 children with autism attending a comprehensive early intervention program over a 10-month period. Contrary to our expectation, we observed a waxing and waning pattern of change in children's vocalizations over time, rather than a steady increase. We also found evidence to suggest that looking at the quality of children's vocalizations (i.e., the ratio of speech to nonspeech vocalizations) provides a more accurate picture of children's development than simply looking at the quantity (i.e., how frequently they vocalize).

Language ENvironment analysis (LENA) system investigation of day long recordings in children: A literature review

The Language ENvironment Analysis (LENA) System is a relatively new recording technology that can be used to investigate typical child language acquisition and populations with language disorders. The purpose of this paper is to familiarize language acquisition researchers and speech-language pathologists with how the LENA System is currently being used in research. The authors outline issues in peer-reviewed research based on the device. Considerations when using the LENA System are discussed.