Modeling Dyadic Processes Using Hidden Markov Models: A Time Series Approach to Mother-Infant Interactions During Infant Immunization

Cynthia Stifter, Michael Rovine

Research output: Contribution to journalArticle

6 Citations (Scopus)

Abstract

The focus of the present longitudinal study, to examine mother-infant interaction during the administration of immunizations at 2 and 6months 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 6months. Two of the states at 2months and three of the states at 6months 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.

Original languageEnglish (US)
Pages (from-to)298-321
Number of pages24
JournalInfant and Child Development
Volume24
Issue number3
DOIs
StatePublished - May 1 2015

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Mother-Child Relations
Immunization
Crying
Mothers
Individuality
Longitudinal Studies
Parents

All Science Journal Classification (ASJC) codes

  • Developmental and Educational Psychology

Cite this

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