Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6826691 | Schizophrenia Research | 2012 | 8 Pages |
Abstract
Integrative modeling of multivariate data from familial, neurobiological, socioenvironmental, cognitive and clinical domains represents a powerful approach to prediction of psychosis development. The high specificity and low sensitivity found using a combination of such variables suggests that their utility may be in confirmatory testing among already selected high-risk individuals, rather than for initial screening. These findings also highlight the importance of data from a broad array of etiologic and risk factors, even within a familial high-risk population. With further refinement and validation, such methods could form key components of early detection, intervention and prevention programs.
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Authors
Jai Shah, Shaun M. Eack, Debra M. Montrose, Neeraj Tandon, Jean M. Miewald, Konasale M. Prasad, Matcheri S. Keshavan,