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Taking Language Samples Home: Feasibility, Reliability, and Validity of Child Language Samples Conducted Remotely with Video Chat Versus In-Person
- Source :
- Journal of Speech, Language, and Hearing Research, Journal of Speech, Language, and Hearing Research : JSLHR
- Publication Year :
- 2020
-
Abstract
- Purpose There has been increased interest in using telepractice for involving more diverse children in research and clinical services, as well as when in-person assessment is challenging, such as during COVID-19. Little is known, however, about the feasibility, reliability, and validity of language samples when conducted via telepractice. Method Child language samples from parent–child play were recorded either in person in the laboratory or via video chat at home, using parents' preferred commercially available software on their own device. Samples were transcribed and analyzed using Systematic Analysis of Language Transcripts software. Analyses compared measures between-subjects for 46 dyads who completed video chat language samples versus 16 who completed in-person samples; within-subjects analyses were conducted for a subset of 13 dyads who completed both types. Groups did not differ significantly on child age, sex, or socioeconomic status. Results The number of usable samples and percent of utterances with intelligible audio signal did not differ significantly for in-person versus video chat language samples. Child speech and language characteristics (including mean length of utterance, type–token ratio, number of different words, grammatical errors/omissions, and child speech intelligibility) did not differ significantly between in-person and video chat methods. This was the case for between-group analyses and within-child comparisons. Furthermore, transcription reliability (conducted on a subset of samples) was high and did not differ between in-person and video chat methods. Conclusions This study demonstrates that child language samples collected via video chat are largely comparable to in-person samples in terms of key speech and language measures. Best practices for maximizing data quality for using video chat language samples are provided.
- Subjects :
- Male
Linguistics and Language
Non-Randomized Controlled Trials as Topic
020205 medical informatics
PsyArXiv|Social and Behavioral Sciences|Developmental Psychology
02 engineering and technology
Interpersonal communication
computer.software_genre
Language and Linguistics
030507 speech-language pathology & audiology
03 medical and health sciences
Speech and Hearing
Videoconferencing
Speech Production Measurement
Transcription (linguistics)
0202 electrical engineering, electronic engineering, information engineering
Humans
Speech
bepress|Social and Behavioral Sciences|Psychology|Child Psychology
Longitudinal Studies
Socioeconomic status
Reliability (statistics)
Research Notes
Language Disorders
Language Tests
SARS-CoV-2
business.industry
Video chat
Speech Intelligibility
COVID-19
Infant
Reproducibility of Results
Telemedicine
PsyArXiv|Social and Behavioral Sciences
Child, Preschool
Data quality
bepress|Social and Behavioral Sciences
Feasibility Studies
Female
Artificial intelligence
0305 other medical science
Psychology
business
Mean length of utterance
computer
Child Language
Natural language processing
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- Journal of Speech, Language, and Hearing Research, Journal of Speech, Language, and Hearing Research : JSLHR
- Accession number :
- edsair.doi.dedup.....d7af6fd188fd03c35c412121891de5c6