Data Entry: Please note that the research database will be replaced by UNIverse by the end of October 2023. Please enter your data into the system https://universe-intern.unibas.ch. Thanks
Neurocognition and Motor Functioning in the Prediction of Psychosis
Editor(s)
Riecher-Rössler, Anita; McGorry, Patrick D.
Book title
Early Detection and Intervention in Psychosis. state of the art and future perspectives
Edition
1
Publisher
Karger
Place of publication
Basel
Pages
116-132
ISSN/ISBN
978-3-318-05620-4 ; 978-3-318-05621-1
Series title
Key issues in mental health
Number
181
Abstract
Meta-analyses suggest that - among help-seeking individuals - only about one third of those meeting internationally established criteria for an at-risk mental state (ARMS) for psychosis will later develop psychosis and about one third is having a clinical remission within 2 years. Hence, further risk stratification among ARMS individuals is urgently needed to improve the cost-benefit ratio of preventive interventions. Cognitive and motor functioning deficits are promising candidates for improving the prediction of psychosis in ARMS individuals because they are hallmark features of schizophrenic psychoses, they precede the onset of frank psychosis by many years, and they can be assessed at relatively low costs. In this chapter, we critically evaluate the potential of cognitive and motor functioning parameters for improving the prediction of psychosis in ARMS individuals. We first summarize current evidence on cognitive and motor functioning differences between ARMS individuals who later developed psychosis and those who did not and then address the question whether cognitive and motor functioning variables are independently associated with transition to psychosis. Specifically, we review all available studies that included cognitive and/or motor functioning variables into prediction models integrating variables from multiple domains and thereby evaluate their added predictive value. Finally, we provide a detailed discussion of methodological issues in the current research and give recommendations for improvements.
