Schizophrenia : evolution and synthesis

Schizophrenia : evolution and synthesis / edited by Steven M. Silverstein, Bita Moghaddam, and Til Wykes ; program advisory committee, Anil K. Malhotra, John McGrath, Andreas Meyer-Lindenberg, Bita Moghaddam, Steven M. Silverstein, Til Wykes.

Despite major advances in methodology and thousands of published studies every year, treatment outcomes in schizophrenia have not improved over the last 50 years. Moreover, we still lack strategies for prevention and we do not yet understand how the interaction of genetic, developmental, and environ...

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Bibliographic Details
Other Authors: Silverstein, Steven M. (Editor), Moghaddam, Bita (Editor), Wykes, Til (Editor)
Format: eBook
Language:English
Published: Cambridge, Massachusetts ; London, England : The MIT Press, [2013]
Series:Strüngmann Forum reports.
Subjects:
Schizophrenia.
Schizophrenia > Etiology.
Clinical medicine > Decision making.
Mathematical models.
mathematical models.
HEALTH & FITNESS > Diseases > General.
MEDICAL > Clinical Medicine.
MEDICAL > Diseases.
MEDICAL > Evidence-Based Medicine.
MEDICAL > Internal Medicine.
Mathematical models
Clinical medicine > Decision making
Schizophrenia
Schizophrenia > Etiology
Online Access:Click for online access
Table of Contents:
  • Schizophrenia
  • Heterogeneity
  • What kind of a thing is schizophrenia?
  • How the diagnosis of schizophrenia impeded the advance of knowledge (and what to do about it)
  • What dimensions of heterogeneity are relevant for treatment outcome?
  • Which aspects of heterogeneity are useful to translational success?
  • Risk and resilience
  • How should resilience factors be incorporated in treatment development?
  • Insights into new treatments for early psychosis from genetic, neurodevelopment, and cognitive neuroscience research
  • From epidemiology to mechanisms of illness
  • How can risk and resilience factors be leveraged to optimize discovery pathways?
  • Models
  • Human cell models for schizophrenia
  • How can animal models be better utilized?
  • How can computational models be better utilized for understanding and treating schizophrenia?
  • How can models be better utilized to enhance outcome?
  • Development and treatment
  • Why Kraepelin was right
  • What will the next generation of psychosocial treatments look like?
  • Creative solutions to overcoming barriers in treatment utilization
  • What is necessary to enhance development and utilization of treatment?

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