From the lab to the clinic: Advancing pain exposure using principles of functional analysis

Abstract

In this article, we use the example of pain exposure therapy to illustrate how behavioral pain treatments can be systematically personalized following the principles of functional analysis. Based on the fear-avoidance model, pain exposure therapy has evolved as a mechanistically-based treatment to modify the mechanism of avoidance learning with the aim to reduce disability levels. We first present experimental evidence on avoidance learning from a general psychological perspective. We then illustrate how functional analysis can help therapists understand and address individual drivers of pain avoidance behavior. Finally, we explore how the network theory can translate the principles of functional analysis into statistical parameters using intensive longitudinal data, potentially making exposure experiments more relevant to the daily lives of individuals.