Conversational Language Is a Predictor of Vocational Independence and Friendships in Adults with ASD

Friedman, Laura; Sterling, Audra; DaWalt, Leann Smith; Mailick, Marsha R.

doi:10.1007/s10803-019-04147-1

Cited by 31 publications

(20 citation statements)

References 49 publications

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“…Expressive language is among the most heterogeneous characteristics in autism spectrum disorder (ASD) and one of the strongest predictors of future outcomes [Friedman, Sterling, Dawalt, & Mailick, 2019; Howlin, Goode, Hutton, & Rutter, 2004; Venter, Lord, & Schopler, 1992]. This is why language and communication are often targets of interventions for both younger and older children [e.g., Kasari, Gulsrud, Wong, Kwon, & Locke, 2010; Tager‐Flusberg & Kasari, 2013].…”

Section: Introductionmentioning

confidence: 99%

Eliciting Language Samples for Analysis (ELSA): A New Protocol for Assessing Expressive Language and Communication in Autism

et al. 2020

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Expressive language and communication are among the key targets of interventions for individuals with autism spectrum disorder (ASD), and natural language samples provide an optimal approach for their assessment. Currently, there are no protocols for collecting such samples that cover a wide range of ages or language abilities, particularly for children/adolescents who have very limited spoken language. We introduce a new protocol for collecting language samples, eliciting language samples for analysis (ELSA), and a novel approach for deriving basic measures of verbal communicative competence from it that bypasses the need for time‐consuming transcription. Study 1 presents ELSA‐adolescents (ELSA‐A), designed for minimally and low‐verbal older children/adolescents with ASD. The protocol successfully engaged and elicited speech from 46 participants across a wide range of ages (6;6–19;7) with samples averaging 20–25 min. The collected samples were segmented into speaker utterances (examiner and participant) using real‐time coding as one is listening to the audio recording and two measures were derived: frequency of utterances and conversational turns per minute. These measures were shown to be reliable and valid. For Study 2, ELSA was adapted for younger children (ELSA‐Toddler [ELSA‐T]) with samples averaging 29 min from 19 toddlers (2;8–4;10 years) with ASD. Again, measures of frequency of utterances and conversational turns derived from ELSA‐T were shown to have strong psychometric properties. In Study 3, we found that ELSA‐A and ELSA‐T were equivalent in eliciting language from 17 children with ASD (ages: 4;0–6;8), demonstrating their suitability for deriving robust objective assessments of expressive language that could be used to track change in ability over time. We introduce a new protocol for collecting expressive language samples, ELSA, that can be used with a wide age range, from toddlers (ELSA‐T) to older adolescents (ELSA‐A) with ASD who have minimal or low‐verbal abilities. The measures of language and communication derived from them, frequency of utterances, and conversational turns per minute, using real‐time coding methods, can be used to characterize ability and chart change in intervention research. Lay Summary We introduce a new protocol for collecting expressive language samples, ELSA, that can be used with a wide age range, from toddlers (ELSA‐T) to older adolescents (ELSA‐A) with autism spectrum disorder who have minimal or low‐verbal abilities. The measures of language and communication derived from them, frequency of utterances and conversational turns per minute, using real‐time coding methods, can be used to characterize ability and chart change in intervention research.

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Section: Introductionmentioning

confidence: 99%

Eliciting Language Samples for Analysis (ELSA): A New Protocol for Assessing Expressive Language and Communication in Autism

et al. 2020

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“…Pragmatic, semantic, and syntactic language usage predicts social skills in children with ASD 6 and pragmatic language impairments have been linked to an increased prevalence of anxiety disorders among children with ASD 7 . Conversational language ability is a significant predictor of job independence and friendship in adults with ASD, both of which are metrics for measuring quality of life 8 . The presence of communication difficulties is a hallmark of autism, and as such are important targets for evaluation and intervention.…”

Section: Introductionmentioning

confidence: 99%

Evaluating atypical language in autism using automated language measures

Salem

MacFarlane

Adams

et al. 2021

Sci Rep

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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. 169 participants (96 ASD, 28 TD, 45 ADHD) ages 7 to 17 were evaluated with the Autism Diagnostic Observation Schedule. Transcripts of one task were analyzed to generate seven ALMs: mean length of utterance in morphemes, number of different word roots (NDWR), um proportion, content maze proportion, unintelligible proportion, c-units per minute, and repetition proportion. With the exception of repetition proportion (p $$= .07$$ = . 07 ), nonparametric ANOVAs showed significant group differences (p$$< 0.01$$ < 0.01 ). The TD and ADHD groups did not differ from each other in post-hoc analyses. With the exception of NDWR, the ASD group showed significantly (p$$< 0.01$$ < 0.01 ) lower scores than both comparison groups. The ALMs were correlated with standardized clinical and language evaluations of ASD. In age- and IQ-adjusted logistic regression analyses, four ALMs significantly predicted ASD status with satisfactory accuracy (67.9–75.5%). When ALMs were combined together, accuracy improved to 82.4%. These ALMs offer a promising approach for generating novel outcome measures.

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“…Autism spectrum condition (ASC) is a complex, heterogeneous neurodevelopmental challenge that affects 1 in 54 children (Maenner et al, 2020), and is characterized by social communication difficulties and repetitive behaviors (American Psychiatric Association, 2013). The majority of individuals with ASC acquire spoken language (Rose, Trembath, Keen, & Paynter, 2016; Tager‐Flusberg & Kasari, 2013), but nonetheless face a variety of challenges in fitting into society (Friedman, Sterling, DaWalt, & Mailick, 2019; Müller, Schuler, & Yates, 2008; Rotheram‐Fuller, Kasari, Chamberlain, & Locke, 2010). Girls are diagnosed less often with ASC than are boys (Baio et al, 2018) even when they have comparable symptom profiles (Dworzynski, Ronald, Bolton, & Happé, 2012), which may be due to minimally understood sex differences in the way ASC manifests (Cola et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

Natural language markers of social phenotype in girls with autism

Song

Cola

Plate

et al. 2020

Child Psychology Psychiatry

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Background Girls with autism spectrum condition (ASC) are chronically underdiagnosed compared to boys, which may be due to poorly understood sex differences in a variety of domains, including social interest and motivation. In this study, we use natural language processing to identify objective markers of social phenotype that are easily obtained from a brief conversation with a nonexpert. Methods 87 school‐aged children and adolescents with ASC (17 girls, 33 boys) or typical development (TD; 15 girls, 22 boys) were matched on age (mean = 11.35 years), IQ estimates (mean = 107), and – for ASC participants – level of social impairment. Participants engaged in an informal 5‐min ‘get to know you’ conversation with a nonexpert conversation partner. To measure attention to social groups, we analyzed first‐person plural pronoun variants (e.g., ‘we’ and ‘us’) and third‐person plural pronoun variants (e.g., ‘they’ and ‘them’). Results Consistent with prior research suggesting greater social motivation in autistic girls, autistic girls talked more about social groups than did ASC boys. Compared to TD girls, autistic girls demonstrated atypically heightened discussion of groups they were not a part of (‘they’, ‘them’), indicating potential awareness of social exclusion. Pronoun use predicted individual differences in the social phenotypes of autistic girls. Conclusions Relatively heightened but atypical social group focus is evident in autistic girls during spontaneous conversation, which contrasts with patterns observed in autistic boys and TD girls. Quantifying subtle linguistic differences in verbally fluent autistic girls is an important step toward improved identification and support for this understudied sector of the autism spectrum.

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Conversational Language Is a Predictor of Vocational Independence and Friendships in Adults with ASD

Cited by 31 publications

References 49 publications

Eliciting Language Samples for Analysis (ELSA): A New Protocol for Assessing Expressive Language and Communication in Autism

Eliciting Language Samples for Analysis (ELSA): A New Protocol for Assessing Expressive Language and Communication in Autism

Evaluating atypical language in autism using automated language measures

Natural language markers of social phenotype in girls with autism

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