It's about time: Emphasizing temporal dynamics in dynamic personality regulation.

Abstract

People change over time. These changes are thought to represent some self-regulatory, dynamic processes. However, dynamic processes need to be distinguished from mere stochastic variation. Just as the Brownian motion of a dust mote does not help us understand the basic principles of classical physics, neither does random variation within an individual describe the complexity of self-regulatory processes. This regulation implies solving the problem of competing goals and desires within the constraints of situational presses. And what people feel, think, and do at one moment affects what they feel, think and do in the next moment. Thus, describing and explaining change over time must focus on dynamics in response to environmental cues and competing internal states. That is, we must include time and change over time in our models. We will outline the constructs needed to examine time explicitly in models of personality regulation, distinguishing between those that are not inherently temporal from those that are. We will discuss how computational modeling approaches may be used to study temporal dynamics and explain personality consistency and change. We will consider different time scales and discuss how an information processing perspective may inform choices regarding time scale and corresponding contexts for empirical studies.