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

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Bottema-Beutel, K., Guo, R., Braun, C., Dunham-Carr, K., Markfeld, J. E., Pulliam, G., Clark, S. M., Keçeli-Kaysılı, B., Feldman, J. I., & Woynaroski, T. (2024). Considerations for Measuring Caregiver Talk in Interactions With Infants at Elevated and Population-Level Likelihood for Autism: Deriving Stable Estimates. Journal of Speech, Language, and Hearing Research, 68(1), 234-247. https://doi.org/10.1044/2024_jslhr-24-00312

Publication date: 16 Dec 2024 Added to AutiHub: 9 Sep 2026 Type: Article Article language: English
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Authors

Publication authors
10
Publication authors identified as autistic
1 / 10 (10.0%)
  1. Kristen Bottema-Beutel
  2. Ruoxi Guo
  3. Caroline Braun *
  4. Kacie Dunham-Carr
  5. Jennifer E. Markfeld
  1. Grace Pulliam
  2. S. Madison Clark
  3. Bahar Keçeli-Kaysılı
  4. Jacob I. Feldman
  5. Tiffany Woynaroski

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. Supplemental Material: https://doi.org/10.23641/asha.27996875

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These indicators describe the bibliography cited by this publication. An author name is counted each time it appears in one cited reference, so the same person can be counted more than once. Names not yet linked to an author already present in AutiHub are treated as unknown, not as non-autistic. Last computed: 12 Sep 2026 01:05.

Cited references
59
With a DOI
46
Without a DOI, from raw bibliography text
12
2 / 59 (3.4%) cited references include at least one author identified as autistic.
References with data to complete
5 / 59 (8.5%)
References with detected author names
54 / 59 (91.5%)
Without detected author names
5
Without a structured title
3
Without a stable identifier
12
References with raw author names still to review
3
References with external metadata lookup issues
0
These indicators apply to cited references displayed on this page, after technical duplicates have been merged. A reference without a DOI can still support author statistics when a title and author names are available.
Author names detected in the cited bibliography
253
From DOI or external metadata
253
From validated raw bibliography text
0
Raw names already validated
0
Raw names still to review
12
64 / 253 (25.3%) names are linked to an author already present in AutiHub. 189 / 253 (74.7%) names are not yet linked.
Names linked to a person identified as autistic
4 / 253 (1.6%)
Calculated across all author names detected in the cited bibliography. Among names linked to an author already present in AutiHub: 4 / 64 (6.2%). Distinct people identified as autistic: 4 / 205 (2.0%).
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