Mihaela D Barokova1, Chelsea La Valle1, Sommer Hassan1,2, Collin Lee1,3, Mengyuan Xu1,4, Riley McKechnie1,5, Emily Johnston1, Manon A Krol1,6, Jennifer Leano1, Helen Tager-Flusberg1. 1. Department of Psychological and Brain Sciences, Center for Autism Research Excellence, Boston University, Boston, Massachusetts, USA. 2. Easy Speech Pathology Clinic, Palm Desert, California, USA. 3. Rosemead School of Psychology, Biola University, La Mirada, California, USA. 4. 1500 Commerce Park Dr, Reston, VA, 20191, USA. 5. Laboratories of Cognitive Neuroscience, Division of Developmental Medicine, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts, USA. 6. Donders Institute, Radboudumc, Nijmegen, The Netherlands.
Abstract
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.
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.
Authors: Angela John Thurman; Jamie O Edgin; Stephanie L Sherman; Audra Sterling; Andrea McDuffie; Elizabeth Berry-Kravis; Debra Hamilton; Leonard Abbeduto Journal: J Neurodev Disord Date: 2021-04-08 Impact factor: 4.025
Authors: Laura Del Hoyo Soriano; Lauren Bullard; Cesar Hoyos Alvarez; Angela John Thurman; Leonard Abbeduto Journal: Front Rehabil Sci Date: 2021-11-18
Authors: Laura Del Hoyo Soriano; Lauren Bullard; Angela John Thurman; Cesar Hoyos Alvarez; Leonard Abbeduto Journal: Dev Neurorehabil Date: 2021-06-25 Impact factor: 2.308