EITM: Recognizing, Modeling, and Simulating Coupled Processes in Dyadic Interaction

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There is a substantial literature showing the correspondence between the quality of relationships within a family and the incidence of physical and psychological maladies among its members. This study addresses two fundamental questions: "What patterned behaviors between family members, either adults or adults with their children, are associated with relationship quality" and "Can these patterns be quantified sufficient to be reproduced in computer simulations?" Our research efforts to answer these questions are organized in four steps. First, we use existing observational data collected from the behavioral interactions of married couples to determine which behavioral clusters-their timing and flow-in the interaction are most associated with the quality of the relationship. Second, we then use these extracted behavior sets to construct pattern recognition software (e.g., Hidden Markov Models) to discriminate distressed from non-distressed relationships. Third, the discriminating patterns then become the blueprint for constructing computer simulations of dyadic interaction; we will develop computer simulations that reproduce the sequencing of patterns seen in distressed and non-distressed married couples. Finally, using existing data, we will apply the developed methodology of pattern extraction and computer simulation to behaviors observed in parent-child interactions. The broader impacts of this research are twofold: first, by utilizing pattern recognition technology, we advance the state of the art for quantifying observational data of human interaction, and second, the classification of patterns and testing via computer simulation is the first step in developing a computer-based recognition system for identifying at-risk populations.