A Vulnerability Approach to Heterogeneity in Addiction

Abstract

Addiction exhibits pronounced heterogeneity across symptoms, substances, neurobiology, contexts, and treatment outcomes, constituting a persistent challenge for unified theoretical explanation. Addressing this challenge, this work examines how such variability can be systematically understood without reducing addiction to a single social, biological, or psychological mechanism. After outlining the scope of heterogeneity in addiction, the analysis turns to computational models of decision‑making—particularly Redish et al.’s vulnerability framework—as a powerful account of how failures within learning and choice systems generate addictive behavior. It is argued, however, that decision‑making models alone are insufficient unless they account for the contextual conditions in which choices are made. In response, an extended vulnerability framework is developed in which addictive behavior emerges when action selection becomes constrained by contextual and choice‑based vulnerabilities over time. This framework is then linked to precision medicine approaches, which naturally operationalize heterogeneity through individualized diagnosis and treatment. The work concludes by identifying limits of the framework and directions for future research, proposing vulnerability as a unifying lens through which addiction’s complexity can be understood.