Considerations for Measuring Caregiver Talk in Interactions With Infants at Elevated and Population-Level Likelihood for Autism: Deriving Stable Estimates.

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Title: Considerations for Measuring Caregiver Talk in Interactions With Infants at Elevated and Population-Level Likelihood for Autism: Deriving Stable Estimates.
Authors: Bottema-Beutel, Kristen1 kristen.bottema-beutel@bc.edu, Guo, Ruoxi1, Braun, Caroline1, Dunham-Carr, Kacie2,3, Markfeld, Jennifer E.2,4, Pulliam, Grace2,3, Clark, S. Madison5,6, Keçeli-Kaysılı, Bahar6, Feldman, Jacob I.4,6, Woynaroski, Tiffany3,4,6,7,8
Source: Journal of Speech, Language & Hearing Research. Jan2025, Vol. 68 Issue 1, p234-247. 14p.
Subject Terms: *Longitudinal method, *Communication, *Research methodology, *Asperger's syndrome, *Psychology of caregivers, *Caregiver attitudes, *Children, Treatment of autism, Research funding, Interviewing, Questionnaires, Descriptive statistics, Analysis of variance, Data analysis software, Video recording
Abstract: Purpose: This study aims to help researchers design observational measurement systems that yield sufficiently stable scores for estimating caregiver talk among caregivers of infant siblings of autistic and non-autistic children. Stable estimates minimize error introduced by facets of the measurement system, such as variability between coders or measurement sessions. Method: Analyses of variance were used to partition error variance between coder and session and to derive g coefficients. Decision studies determined the number of sessions and coders over which scores must be averaged to achieve sufficiently stable g coefficients (0.80). Twelve infants at elevated likelihood of an autism diagnosis and 12 infants with population-level likelihood of autism diagnosis participated in two semistructured observation sessions when the children were 12--18 months of age and again 9 months later. Caregiver follow-in talk was coded from these sessions. Results: Two sessions and one coder were needed to achieve sufficient stability for follow-in talk and follow-in comments for both groups of infants at both time points. However, follow-in directives did not reach sufficient stability for any combination of sessions or coders for the population-level likelihood group at either time point, or for the elevated likelihood group at Time 2. Conclusion: Researchers should plan to collect at least two sessions to derive sufficiently stable estimates of caregiver talk in infants at elevated and general population--level likelihood for autism. [ABSTRACT FROM AUTHOR]
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Database: Education Research Complete
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Abstract:Purpose: This study aims to help researchers design observational measurement systems that yield sufficiently stable scores for estimating caregiver talk among caregivers of infant siblings of autistic and non-autistic children. Stable estimates minimize error introduced by facets of the measurement system, such as variability between coders or measurement sessions. Method: Analyses of variance were used to partition error variance between coder and session and to derive g coefficients. Decision studies determined the number of sessions and coders over which scores must be averaged to achieve sufficiently stable g coefficients (0.80). Twelve infants at elevated likelihood of an autism diagnosis and 12 infants with population-level likelihood of autism diagnosis participated in two semistructured observation sessions when the children were 12--18 months of age and again 9 months later. Caregiver follow-in talk was coded from these sessions. Results: Two sessions and one coder were needed to achieve sufficient stability for follow-in talk and follow-in comments for both groups of infants at both time points. However, follow-in directives did not reach sufficient stability for any combination of sessions or coders for the population-level likelihood group at either time point, or for the elevated likelihood group at Time 2. Conclusion: Researchers should plan to collect at least two sessions to derive sufficiently stable estimates of caregiver talk in infants at elevated and general population--level likelihood for autism. [ABSTRACT FROM AUTHOR]
ISSN:10924388
DOI:10.1044/2024_JSLHR-24-00312