Characterizing the early vocabulary profiles of preverbal and minimally verbal children with autism spectrum disorder / Eileen HAEBIG in Autism, 25-4 (May 2021)  

Public ISBD [article]  inAutism > 25-4 (May 2021) . - p.958-970 Titre : Characterizing the early vocabulary profiles of preverbal and minimally verbal children with autism spectrum disorder Type de document : texte imprimé Auteurs : Eileen HAEBIG, Auteur ; Eva JIMENEZ, Auteur ; Christopher R. COX, Auteur ; Thomas T. HILLS, Auteur Article en page(s) : p.958-970 Langues : Anglais (eng) Mots-clés : autism spectrum disorders  minimally verbal  preverbal  vocabulary Index. décimale : PER Périodiques Résumé : Although preverbal and minimally verbal children with autism spectrum disorder represent a significant portion of the autism spectrum disorder population, we have a limited understanding of and characterization of them. Although it is a given that their lexical profiles contain fewer words, it is important to determine whether (a) the words preverbal and minimally verbal children with autism spectrum disorder produce are similar to the first words typically developing children produce or (b) there are unique features of the limited words that preverbal and minimally verbal children with autism spectrum disorder produce. The current study compared the early word profiles of preverbal and minimally verbal children with autism spectrum disorder to vocabulary-matched typically developing toddlers. Children with autism spectrum disorder produced proportionally more verbs than typically developing toddlers. Also, children with autism spectrum disorder produced proportionally more action and food words, while typically developing toddlers produced proportionally more animal words, animal sounds and sound effects, and people words. Children with autism spectrum disorder also produced "mommy" and "daddy" at lower rates. Our findings identified several areas of overlap in early word learning; however, our findings also point to differences that may be connected to core weaknesses in social communication (i.e. people words). The findings highlight words and categories that could serve as useful targets for communication intervention with preverbal and minimally verbal children with autism spectrum disorder. En ligne : http://dx.doi.org/10.1177/1362361320973799 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=444 [article] Characterizing the early vocabulary profiles of preverbal and minimally verbal children with autism spectrum disorder [texte imprimé] / Eileen HAEBIG, Auteur ; Eva JIMENEZ, Auteur ; Christopher R. COX, Auteur ; Thomas T. HILLS, Auteur . - p.958-970. Langues : Anglais (eng) in Autism > 25-4 (May 2021) . - p.958-970 Mots-clés : autism spectrum disorders  minimally verbal  preverbal  vocabulary Index. décimale : PER Périodiques Résumé : Although preverbal and minimally verbal children with autism spectrum disorder represent a significant portion of the autism spectrum disorder population, we have a limited understanding of and characterization of them. Although it is a given that their lexical profiles contain fewer words, it is important to determine whether (a) the words preverbal and minimally verbal children with autism spectrum disorder produce are similar to the first words typically developing children produce or (b) there are unique features of the limited words that preverbal and minimally verbal children with autism spectrum disorder produce. The current study compared the early word profiles of preverbal and minimally verbal children with autism spectrum disorder to vocabulary-matched typically developing toddlers. Children with autism spectrum disorder produced proportionally more verbs than typically developing toddlers. Also, children with autism spectrum disorder produced proportionally more action and food words, while typically developing toddlers produced proportionally more animal words, animal sounds and sound effects, and people words. Children with autism spectrum disorder also produced "mommy" and "daddy" at lower rates. Our findings identified several areas of overlap in early word learning; however, our findings also point to differences that may be connected to core weaknesses in social communication (i.e. people words). The findings highlight words and categories that could serve as useful targets for communication intervention with preverbal and minimally verbal children with autism spectrum disorder. En ligne : http://dx.doi.org/10.1177/1362361320973799 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=444

Network Analysis of Autistic Language Learners Along the Small World Spectrum / Eileen HAEBIG in Autism Research, 18-8 (August 2025)  

Public ISBD [article]  inAutism Research > 18-8 (August 2025) . - p.1580-1594 Titre : Network Analysis of Autistic Language Learners Along the Small World Spectrum Type de document : texte imprimé Auteurs : Eileen HAEBIG, Auteur ; Stanley WEST, Auteur ; Eva JIMENEZ, Auteur ; Thomas T. HILLS, Auteur ; Christopher R. COX, Auteur Article en page(s) : p.1580-1594 Langues : Anglais (eng) Mots-clés : autism  children  semantic network modeling  semantic structure  word learning Index. décimale : PER Périodiques Résumé : ABSTRACT Recent network analyses of vocabulary growth revealed important relationships between the structure of the semantic environment and early vocabulary acquisition in non-autistic children. However, autistic children may be less likely to encode associated features of novel objects, suggesting divergent processes for acquiring semantic information about words. We examined the expressive vocabularies of 815 non-autistic and 163 autistic children (words produced: MAutistic 183.06, MNon-autistic 182.91). We estimated their trajectories of semantic development using network analyses. Network structure was based on child-oriented word associations. We analyzed networks according to indegree, average shortest path length, clustering coefficient, and small-world propensity (features holistically contributing to ?small-world? network structure). Analyses revealed that autistic and non-autistic children are sensitive to the structure of their semantic environment. However, group differences were observed, with an early peak in the autistic group's clustering coefficient (how closely connected groups of words are), followed by a sharp decline. Moreover, across each network metric, we found that autistic children had reduced small-world structure relative to non-autistic toddlers. Thus, group differences indicate that, although autistic children are learning from their semantic environment, they may be processing their semantic environment differently, the language input to which they are exposed differs relative to non-autistic children, or a combination of the two. En ligne : https://doi.org/10.1002/aur.70065 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=566 [article] Network Analysis of Autistic Language Learners Along the Small World Spectrum [texte imprimé] / Eileen HAEBIG, Auteur ; Stanley WEST, Auteur ; Eva JIMENEZ, Auteur ; Thomas T. HILLS, Auteur ; Christopher R. COX, Auteur . - p.1580-1594. Langues : Anglais (eng) in Autism Research > 18-8 (August 2025) . - p.1580-1594 Mots-clés : autism  children  semantic network modeling  semantic structure  word learning Index. décimale : PER Périodiques Résumé : ABSTRACT Recent network analyses of vocabulary growth revealed important relationships between the structure of the semantic environment and early vocabulary acquisition in non-autistic children. However, autistic children may be less likely to encode associated features of novel objects, suggesting divergent processes for acquiring semantic information about words. We examined the expressive vocabularies of 815 non-autistic and 163 autistic children (words produced: MAutistic 183.06, MNon-autistic 182.91). We estimated their trajectories of semantic development using network analyses. Network structure was based on child-oriented word associations. We analyzed networks according to indegree, average shortest path length, clustering coefficient, and small-world propensity (features holistically contributing to ?small-world? network structure). Analyses revealed that autistic and non-autistic children are sensitive to the structure of their semantic environment. However, group differences were observed, with an early peak in the autistic group's clustering coefficient (how closely connected groups of words are), followed by a sharp decline. Moreover, across each network metric, we found that autistic children had reduced small-world structure relative to non-autistic toddlers. Thus, group differences indicate that, although autistic children are learning from their semantic environment, they may be processing their semantic environment differently, the language input to which they are exposed differs relative to non-autistic children, or a combination of the two. En ligne : https://doi.org/10.1002/aur.70065 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=566

Vocabulary development in autistic children: a network growth analysis / Eileen HAEBIG in Journal of Child Psychology and Psychiatry, 67-6 (June 2026)  

Public ISBD [article]  inJournal of Child Psychology and Psychiatry > 67-6 (June 2026) . - p.844-858 Titre : Vocabulary development in autistic children: a network growth analysis Type de document : texte imprimé Auteurs : Eileen HAEBIG, Auteur ; Stanley WEST, Auteur ; Christopher R. COX, Auteur Article en page(s) : p.844-858 Langues : Anglais (eng) Mots-clés : Autism  word learning  semantic network modeling Index. décimale : PER Périodiques Résumé : Background Autistic children are typically late to develop their expressive vocabulary, but little is known about their early word learning process. This study compared three network growth models on their ability to account for the trajectories of expressive vocabulary acquisition in autistic and non-autistic children. Methods We studied expressive vocabularies using item-level data from a child vocabulary checklist (n?=?721 records from young autistic children; n?=?2,166 records from non-autistic toddlers). We estimated vocabulary growth trajectories for autistic and non-autistic children and assessed the goodness of fit of three models of vocabulary growth, with varying sensitivity to the structure of the environment and the learner's existing vocabulary knowledge. To do so, we first computed word-level acquisition norms that indicate the vocabulary size at which individual words tend to be learned by each group. Then we evaluated how well network growth models, based on natural language co-occurrence structure and word associations, accounted for variance in the autistic and non-autistic acquisition norms. Results Our word-level vocabulary size of acquisition norms closely aligned with age of acquisition data, indicating their utility when age of acquisition norms cannot be derived for neurodivergent populations. Furthermore, we extended key observations and demonstrated that the growth models explained similar amounts of variance in each group. Both groups are biased to learn words that have many connections to words that have been previously learned; however, even after accounting for this learning influence, autistic and non-autistic vocabulary growth trajectories receive an added boost in learning when words are connected to many other words in the learning environment, indicating a similar learning profile. Conclusions Both groups preferentially acquire new words by leveraging the semantic structure in the learning environment, indicating an overlap in theoretical accounts of vocabulary growth. En ligne : https://doi.org/10.1111/jcpp.70076 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=587 [article] Vocabulary development in autistic children: a network growth analysis [texte imprimé] / Eileen HAEBIG, Auteur ; Stanley WEST, Auteur ; Christopher R. COX, Auteur . - p.844-858. Langues : Anglais (eng) in Journal of Child Psychology and Psychiatry > 67-6 (June 2026) . - p.844-858 Mots-clés : Autism  word learning  semantic network modeling Index. décimale : PER Périodiques Résumé : Background Autistic children are typically late to develop their expressive vocabulary, but little is known about their early word learning process. This study compared three network growth models on their ability to account for the trajectories of expressive vocabulary acquisition in autistic and non-autistic children. Methods We studied expressive vocabularies using item-level data from a child vocabulary checklist (n?=?721 records from young autistic children; n?=?2,166 records from non-autistic toddlers). We estimated vocabulary growth trajectories for autistic and non-autistic children and assessed the goodness of fit of three models of vocabulary growth, with varying sensitivity to the structure of the environment and the learner's existing vocabulary knowledge. To do so, we first computed word-level acquisition norms that indicate the vocabulary size at which individual words tend to be learned by each group. Then we evaluated how well network growth models, based on natural language co-occurrence structure and word associations, accounted for variance in the autistic and non-autistic acquisition norms. Results Our word-level vocabulary size of acquisition norms closely aligned with age of acquisition data, indicating their utility when age of acquisition norms cannot be derived for neurodivergent populations. Furthermore, we extended key observations and demonstrated that the growth models explained similar amounts of variance in each group. Both groups are biased to learn words that have many connections to words that have been previously learned; however, even after accounting for this learning influence, autistic and non-autistic vocabulary growth trajectories receive an added boost in learning when words are connected to many other words in the learning environment, indicating a similar learning profile. Conclusions Both groups preferentially acquire new words by leveraging the semantic structure in the learning environment, indicating an overlap in theoretical accounts of vocabulary growth. En ligne : https://doi.org/10.1111/jcpp.70076 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=587

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