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Modeling Dyadic Processes Using Hidden Markov Models: A Time Series Approach to Mother–Infant Interactions During Infant Immunization
Author(s) -
Stifter Cynthia A.,
Rovine Michael
Publication year - 2015
Publication title -
infant and child development
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.87
H-Index - 57
eISSN - 1522-7219
pISSN - 1522-7227
DOI - 10.1002/icd.1907
Subject(s) - dyad , psychology , crying , infant crying , developmental psychology , normative , hidden markov model , series (stratigraphy) , social psychology , artificial intelligence , computer science , philosophy , paleontology , epistemology , biology
The focus of the present longitudinal study, to examine mother–infant interaction during the administration of immunizations at 2 and 6 months of age, used hidden Markov modelling, a time series approach that produces latent states to describe how mothers and infants work together to bring the infant to a soothed state. Results revealed a four‐state model for the dyadic responses to a 2‐month inoculation whereas a six‐state model best described the dyadic process at 6 months. Two of the states at 2 months and three of the states at 6 months suggested a progression from high‐intensity crying to no crying with parents using vestibular and auditory soothing methods. The use of feeding and/or pacifying to soothe the infant characterized one 2‐month state and two 6‐month states. These data indicate that with maturation and experience, the mother–infant dyad is becoming more organized around the soothing interaction. Using hidden Markov modelling to describe individual differences, as well as normative processes, is also presented and discussed. Copyright © 2015 John Wiley & Sons, Ltd.