Considerations for Measuring Caregiver Talk in Interactions With Infants at Elevated and Population-Level Likelihood...

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.

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.

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.

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.

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