Maximizing exposure therapy: an inhibitory learning approach

Abstract

Exposure therapy is an effective approach for treating anxiety disorders, although a substantial number of individuals fail to benefit or experience a return of fear after treatment. Research suggests that anxious individuals show deficits in the mechanisms believed to underlie exposure therapy, such as inhibitory learning. Targeting these processes may help improve the efficacy of exposure-based procedures. Although evidence supports an inhibitory learning model of extinction, there has been little discussion of how to implement this model in clinical practice. The primary aim of this paper is to provide examples to clinicians for how to apply this model to optimize exposure therapy with anxious clients, in ways that distinguish it from a 'fear habituation' approach and 'belief disconfirmation' approach within standard cognitive-behavior therapy. Exposure optimization strategies include (1) expectancy violation, (2) deepened extinction, (3) occasional reinforced extinction, (4) removal of safety signals, (5) variability, (6) retrieval cues, (7) multiple contexts, and (8) affect labeling. Case studies illustrate methods of applying these techniques with a variety of anxiety disorders, including obsessive-compulsive disorder, posttraumatic stress disorder, social phobia, specific phobia, and panic disorder.

Keywords: Affect labeling; Deepened extinction; Expectancy violation; Exposure therapy; Inhibitory learning; Multiple contexts; Occasional reinforced extinction; Retrieval cues; Safety signals.