Keynote Speaker - Tom Hollenstein
Emotion Dynamics on State Space
The emphasis of my talk was to review the past decade of research using state space grids to capture emotional dynamics in interpersonal interactions.
I began by arguing that because emotional and regulatory processes are ongoing as part of a perpetual feedback loop the dynamic changes in emotional states reflect the outcome of this feedback balance. In particular, a branch of my research program is dedicated to understanding these dynamics in the context of interpersonal interactions. In order to do this, I employ state space grids using the freely available program GridWare (www.statespacegrids.org), a dynamic systems based technique that allows for the visualization and measurement of categorical state changes on a two-dimensional space (Figure 1). The cells on the state space represent the intersection of one person’s emotional state (e.g., mother on the x-axis) and another person’s emotional state (e.g., child on the y-axis). From this, measures of content (e.g., which cells are visited most often) and structure (e.g., variability) can be used to test hypotheses about individual differences in interpersonal dynamics.
The emphasis of my talk was to review the past decade of research using state space grids to capture emotional dynamics in interpersonal interactions.
I began by arguing that because emotional and regulatory processes are ongoing as part of a perpetual feedback loop the dynamic changes in emotional states reflect the outcome of this feedback balance. In particular, a branch of my research program is dedicated to understanding these dynamics in the context of interpersonal interactions. In order to do this, I employ state space grids using the freely available program GridWare (www.statespacegrids.org), a dynamic systems based technique that allows for the visualization and measurement of categorical state changes on a two-dimensional space (Figure 1). The cells on the state space represent the intersection of one person’s emotional state (e.g., mother on the x-axis) and another person’s emotional state (e.g., child on the y-axis). From this, measures of content (e.g., which cells are visited most often) and structure (e.g., variability) can be used to test hypotheses about individual differences in interpersonal dynamics.
I then reviewed studies that explored the relative flexibility of parent child dyads in relation to socioemotional functioning and psychopathology. In general, greater flexibility has been associated with better functioning. This work is now framed within the Flex3 model (Figure 2) that describes and defines flexibility more formally and distinguishes three types.
Finally, I reviewed two recent expansions of the state space grid method. First, I showed how it can be used for the analysis of triadic interactions. Second, I showed how grids can be used to depict multi-step sequences.
State space grid analysis is a useful technique in interpersonal research (in fact I was pleasantly surprised to see other presentations using grids at the conference). The software program, GridWare, is freely available on the web (www.statespacegrids.org) and now there is a book that is essentially a “workshop in a box” for those who want to use this technique. I am happy to facilitate if anyone is interested in applying this technique to their own research.
I was quite honored to be invited and welcomed by the SITAR community. The overlap with my methodological and theoretical approach was palpable and I enjoyed discussing the research being conducted by SITAR members.
State space grid analysis is a useful technique in interpersonal research (in fact I was pleasantly surprised to see other presentations using grids at the conference). The software program, GridWare, is freely available on the web (www.statespacegrids.org) and now there is a book that is essentially a “workshop in a box” for those who want to use this technique. I am happy to facilitate if anyone is interested in applying this technique to their own research.
I was quite honored to be invited and welcomed by the SITAR community. The overlap with my methodological and theoretical approach was palpable and I enjoyed discussing the research being conducted by SITAR members.