Integrating dynamic psychophysiological indices across time and contexts: Elucidating mechanisms, risk markers, and intervention targets.

Abstract

Why should researchers measure psychophysiological processes repeatedly over time? The study of psychophysiology inherently involves sampling biological processes as they manifest over time. The most common approach is to use a brief sample to make conclusions about how individuals or groups differ. Although these types of between-subject comparisons have utility for understanding individual and group differences, many of the important conceptual questions in the field involve processes that are dynamic, varying within individuals over time. Using examples from the literature on affect regulation, this conceptual review contrasts three types of study designs: the classic single-observation design and the aggregated and temporally linked repeated observation designs, which have great promise for measuring variables that fluctuate dynamically over time. Importantly, these designs can be integrated to elucidate research questions about risk (when and for whom will the likelihood of an unwanted outcome occurring increase?), mechanisms (how and why does a change in psychophysiology contribute to a change in another process of interest?), and interventions (how and when should interventions take place to modify an outcome?). Researchers are encouraged to implement intensive sampling in their research, which can be conducted in traditional laboratory settings (e.g., fMRI, event-related brain potentials, and heart rate variability) and in ecologically valid contexts in everyday life using ambulatory assessment.