A Micro-level Analysis of Behavioral Dynamics in Parent-Child Synchrony

Authors

Kadie L. Ausherman, University of Nebraska-LincolnFollow

Date of this Version

8-2014

Document Type

Article

Comments

A THESIS Presented to the Faculty of The Graduate College at the University of Nebraska In Partial Fulfillment of Requirements For the Degree of Master of Science, Major: Child, Youth, and Family Studies, Under the Supervision of Professors Allison Reisbig and Julia Torquati. Lincoln, NE: August, 2014

Copyright (c) 2014 Kadie L. Ausherman

Abstract

This study investigates parent-child synchrony, a multilevel construct that has not been operationalized in a precise or standardized way. Synchrony is frequently discussed theoretically, yet there still lacks a clear means of measuring it, even on the behavioral level. When parent-child synchrony is operationalized in a study, it is rarely analyzed in such a way that reflects the dyadic dynamics that unfold as the parent and child are interacting. The aim of this study is to operationalize parent-child synchrony in terms of the dyadic behavior patterns. An overview of the current literature with regard to synchrony as a multilevel construct is included. The methodology for this study consists of video-recording four parent-child dyads while they are interacting in response to a series of prompts. Segments for synchrony and asynchrony were coded second by second by the primary researcher and an independent coder. Consensus codes were analyzed using a time series analysis, specifically, transitional probabilities, which allows behavior patterns to be identified. Significant results were found for two selected behavior patterns, one in synchronous segments and one in asynchronous segments. Transitional probabilities were significant for Collaboration (a dyadic code) to follow Parent Facilitation (an individual code) after a two second lag in the synchronous segments, and for Separate Attention (a dyadic code) to follow Parent Suppress (an individual code) after a two second lag in asynchronous segments. Yule’s Q was calculated as an effect size measure, and most of the significant results also had large effect sizes. This study demonstrates that behavior patterns can be utilized to differentiate between synchronous and asynchronous interactions. Implications for future research and clinical interventions are extensive and potentially consequential for the field.

Advisers: Allison Reisbig and Julia Torquati