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The goal of this review is to highlight the maturation of psychological pain as a novel mental health construct and propose an immediate clinical application for informing risk prediction and need-based stratification within complex heterogeneous psychiatric populations. This comes at a moment when prediction and prevention strategies specific to negative clinical outcomes in common mental disorders has not kept pace with other medical morbidities. Technological advances in next generation risk stratification methodologies utilizing genomics, neuroimaging, and biomarkers continue to yield encouraging progress to bridge this gap. As these technologies gradually reach performance and cost-basis milestones to allow broad adoption, readily available and validated psychometric assessment methodologies may assist in meeting the urgency of the moment while presenting highly favorable cost/benefit ratios. While previously studied primarily as an indicator of suicide risk, psychological pain is now recognized to be an important element across multiple psychiatric disorders. When systematically assessed at point of treatment entry, it can identify individuals with enhanced symptom acuity who are at increased risk for treatment failure, treatment dropout, suicide and various other negative clinical outcomes. Data exploring the predictive value of stratifying substance abuse patients by psychological pain yielded significant information specific to risk for dropout (treatment failure) and likelihood of future suicide events in depressive clinical populations months and even years prior to the clinical events. This information, available at treatment outset, can be utilized to improve the precision and effectiveness of resource allocation as well as provide the option to focus high intensity clinical interventions on an individualized basis which otherwise would be impractical if applied equally to the general population. Suggested strategies applying this approach to depressed and substance abusing treatment populations are described.
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