Theory-Based Intervention for Transforming Harmful Behavior: The Goal-Directed Predictive Processing Approach

Abstract

Human behavior can sometimes cause harm to the behaving individual, other organisms, or their environment. Psychological science plays a crucial role in understanding and addressing these harmful behaviors by providing direction to behavior change interventions. However, the field of psychology encompasses numerous theories, and translating these theories into effective practices can be challenging. In this paper, we introduce the Goal-Directed Predictive Processing (GDPP) framework, an integrative approach that combines key principles from predictive processing and goal-directed theories. The GDPP framework bridges recent theoretical advancements with practical application, offering a user-friendly model to assist practitioners across various domains. It emphasizes assessing inference chains that underlie harmful behaviors in risk situations, mapping out alternative inference chains in relation to expected surprise and self-concept beliefs, and designing targeted interventions to influence these predictive processes. We illustrate the application of this framework in the context of harmful alcohol consumption and depressive behavior.

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