Neuroscience-informed psychoeducation for addiction: a conceptual and feasibility study

Over the past few decades, our understanding of substance use disorders (SUD) has been reshaped by evidence from neuroscience, which suggests that SUD are characterized by specific neuromarkers that transcend traditional diagnostic boundaries and act as pre-diagnostic markers that could be targeted...

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Main Authors: Tara Rezapour, Kayla L. McLean, Elena Psederska, Khashayar Niki Maleki, Hamed Ekhtiari, Jasmin Vassileva
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-02-01
Series:Frontiers in Psychiatry
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Online Access:https://www.frontiersin.org/articles/10.3389/fpsyt.2025.1527828/full
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Summary:Over the past few decades, our understanding of substance use disorders (SUD) has been reshaped by evidence from neuroscience, which suggests that SUD are characterized by specific neuromarkers that transcend traditional diagnostic boundaries and act as pre-diagnostic markers that could be targeted through preventive attempts. Connectivity-based neuromarkers or brain networks have emerged as a promising framework, providing new insights into the neurocognitive mechanisms of SUD. Utilizing this data-driven framework assists prevention and intervention developers in offering a non-judgmental insight for adolescents regarding the potential vulnerability of neurocognitive systems to continued substance use. Given the importance of such awareness, this paper proposes a neural network-informed approach based on research domain criteria (RDoC) to characterize the content of neuroscience-informed psychoeducation designed for SUD. Furthermore, we argue that various features related to content and structure need to be considered when developing such interventions delivered through digital platforms (e.g., apps and websites). Finally, we introduce a theory-driven app called “NIPA”, developed with the aim of increasing adolescents’ awareness and resilience to the effects of drugs and other emotional triggers on brain and cognitive functions.
ISSN:1664-0640