Related Experiment Video
Updated: May 19, 2026
07:31
Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
Published on: May 15, 2020
Chances and risks of predicting psychosis.
Stephan Ruhrmann1, Joachim Klosterkötter, Mitja Bodatsch
1Department of Psychiatry and Psychotherapy, University of Cologne, 50924 Cologne, Germany. stephan.ruhrmann@uk-koeln.de
European Archives of Psychiatry and Clinical Neuroscience
|August 31, 2012
Summary
Preventing psychosis shows promise, but prediction errors can cause harm. Careful risk assessment is crucial to balance intervention benefits against potential harms for individuals at risk.
Area of Science:
- Psychiatry and Mental Health
- Clinical Psychology
- Neuroscience
Background:
- Psychosis prevention is a key strategy, but predictive models have inherent error probabilities.
- False risk attribution can lead to unnecessary stress, anxiety, and interventions.
- Clinical risk samples often present with existing psychopathology and impairments.
Purpose of the Study:
- To explore the benefits and costs of psychosis prevention strategies.
- To address challenges in differentiating normal from clinically relevant mental states.
- To investigate the impact of stigmatization in psychosis risk assessment.
Main Methods:
- Review of current strategies for psychosis prevention.
- Analysis of the implications of prediction error in risk assessment.
- Discussion on the need for advanced risk algorithms and multi-step detection.
Main Results:
- Weighing benefits and costs of preventive interventions is essential due to prediction errors.
- Psychotic-like phenomena are common in adolescents, complicating risk assessment.
- Severe risk states may lead to self-stigmatization, independent of diagnosis.
Conclusions:
- Preventive measures should integrate treatment for current complaints to minimize futile interventions.
- Improved validity of risk criteria requires advanced algorithms and risk stratification.
- The decision to implement preventive measures must balance intervention costs against avoiding severe outcomes.
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