Scientists interested in describing the complexity of human interaction have begun to realize the necessity of collecting intensive longitudinal data to enable them to describe the dynamics of the interaction process. These data can take the form of a daily diary of marital interactions, an hourly account of the behavior of an unruly student, a second to second account of a parent-infant interaction, a continuous time measure of physiological characteristics, or a dose-to-dose account of the effect of a drug or treatment regimen. Unlike the more common approaches to the study of development that may use a single, simple model to describe average group trends, dynamic models can accommodate differences in how individuals change. They can be used to describe how a process unfolds for each individual, to show how individuals differ in that process, and to predict how that process will evolve. Once these dynamics are understood, the opportunity exists to develop a control model with the intent of moving the process toward a desired outcome.
As part of this project, the investigators plan to adapt, modify, and when necessary develop new dynamic and control models appropriate for the needs of developmental researchers. To accomplish these goals, this project brings together members of the engineering, applied developmental statistics, and developmental science research communities to develop models that will specifically address questions related to differences in the way individuals develop and interact.
To demonstrate this model data from the Infant and Child Temperament Study will be assessed to determine the individual differences in how an infant develops the ability to self-regulate emotion. The state-space implementation of this model will allow more flexibility and a richer description of the dynamics of the process by producing a model that can change and develop as the process changes. This approach leads directly to the optimal control/process adjustment model in which individuals can be assessed to determine whether they moving in the direction of a desired outcome. If they are off target, critical control variable values can be assessed and changed. The results of these changes can then be assessed to determine if the individual is back on target. To demonstrate this model, the investigators will assess parent-infant interaction data related to the parents' ability to soothe a distressed child. A model will be developed that will allow investigators to assess which combinations of parent behavior and infant response result in decreasing the child's distress. This model can then be used to provide online assessment to parents that will give them useful feedback during the course of the subsequent interactions suggesting whether their behavior should lead to success and whether and how they should modify that behavior. This general analytic approach will allow researchers to model many different situations in which such feedback can help optimize the quality of an interaction. These can include marital interactions, parent/child relationships, interactions between teachers and students, and encounters between therapists and clients. These methods will also be appropriate for optimizing individual outcomes based on drug treatments, physical therapies, medical treatments, and combinations of different treatment regimens.