Klosterkotter, Joachim; Schultze-Lutter, Frauke; Bechdolf, Andreas; Ruhrmann, Stephan (2011). Prediction and prevention of schizophrenia: what has been achieved and where to go next? World psychiatry, 10(3), pp. 165-174. Milano: Masson Italy
Full text not available from this repository. (Request a copy)In modern medicine, vigorous efforts are being made in the prediction and prevention of diseases. Mental disorders are suitable candidates for the application of this program. The currently known neurobiological and psychosocial risk indicators for schizophrenia do not have a predictive power sufficient for selective prevention in asymptomatic patients at risk. However, once predictive basic and later pre-psychotic high risk symptoms of psychosis develop into the five-year initial prodrome, the impending outbreak of the disease can be predicted with high accuracy. Research findings suggest a differential strategy of indicated prevention with cognitive behavioral therapy in early initial prodromal states and low dosage atypical antipsychotics in late initial prodromal states. The most important future tasks are the improvement of the predictive power by risk enrichment and stratification, as well as the confirmation of the existing and the development of new prevention strategies, with a stronger focus on the etiology of the disorder. In addition, the prediction and prevention approach would benefit from the inclusion of risk symptoms in the DSM-5 criteria.
Item Type: |
Journal Article (Further Contribution) |
|---|---|
Division/Institute: |
04 Faculty of Medicine > University Psychiatric Services > University Hospital of Child and Adolescent Psychiatry and Psychotherapy |
UniBE Contributor: |
Schultze-Lutter, Frauke |
Subjects: |
600 Technology > 610 Medicine & health |
ISSN: |
1723-8617 |
Publisher: |
Masson Italy |
Language: |
English |
Submitter: |
Myriam Pyrlik |
Date Deposited: |
04 Oct 2013 14:18 |
Last Modified: |
05 Dec 2022 14:05 |
Web of Science ID: |
000295902000002 |
URI: |
https://boris.unibe.ch/id/eprint/5798 (FactScience: 210633) |
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