Mindfulness-Based Interventions for Drug Addiction: Insights from the Predictive Processing Framework

Drug addiction, a globally prevalent and burdensome psychiatric disorder, poses a significant challenge to conventional treatments, necessitating a deeper understanding of its mechanisms and exploration of alternative approaches for effective intervention. Despite initial success in research trials, mindfulness-based interventions (MBIs) have been met with skepticism due to a lack of comprehensive understanding of their underlying treatment mechanisms. The present paper argues that the predictive processing (PP) framework can provide unifying accounts of addiction and MBIs, and that a closer examination of the underlying mechanisms involved in both the disorder and the treatment can offer important insights for intervention and recovery. This paper highlights various features of the clinical profile of addiction within the PP framework, including poor self-control, cravings, and a lack of corrective learning. Further, it details a comprehensive account of three key mechanisms involved in the treatment action of MBIs: “being mode,” decentering, and reactivity. Future directions and treatment implications of this framework are discussed. The arguments presented in this paper bear significance for the optimization of addiction treatments with MBIs.