Li, Elizabeth; McCollum, James; Krieger, Josh; Winter, Sophia E; Duane, Daniel; Silberschatz, George; (2025) Predict to Control, Test to Master: Integrating Predictive Processing and Control–Mastery Theory in Understanding How Psychotherapy Works. Journal of Psychotherapy Integration 10.1037/int0000386. (In press).

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Abstract

This article explores how integrating predictive processing framework and control–mastery theory offers a novel account of how psychotherapy works. Predictive processing proposes that the brain continually generates predictions about sensory inputs based on prior experiences to anticipate and respond effectively to its environment. When actual experiences differ, prediction errors prompt updates to the brain’s internal model of the world, thereby improving future predictions and supporting adaptive behavior. In cases of psychopathology, however, entrenched negative predictions may persist, offering temporary reduction in uncertainty despite being ultimately harmful. This short-term predictability and stability may outweigh change processes, leading to persistent distress. Yet, predictive processing leaves open the question of why some individuals seek therapy to challenge such beliefs, despite their bringing a semblance of security. Control–mastery theory complements predictive processing by emphasizing the patient’s intrinsic motivation and active role in challenging and revising pathogenic beliefs through patient testing in psychotherapy. We argue that effective psychotherapy depends not only on the therapist’s provision of experiences that generate salient prediction errors, but also on the patient’s motivation and readiness to engage in revising deeply ingrained beliefs. Drawing on a clinical case of a woman in her 30s, we illustrate how early trauma shapes maladaptive generative models, constraining relational expectations. In therapy, attuned responses generate salient prediction errors, disconfirming maladaptive priors and updating generative models. Through implicit testing and integration of disconfirmatory experiences, the patient revises her internal predictive model, reducing maladaptive prediction errors and fostering therapeutic change.

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