Predicting risk of psychosis in primary care

A qualitative study

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This study explores how clinical prediction models can support general practitioners (GPs) in identifying people who may be at increased risk of developing psychosis during routine primary care consultations.

The authors discuss the opportunities and challenges of implementing risk prediction tools in primary care, highlighting their potential to improve referral pathways, reduce delays in diagnosis and facilitate earlier access to specialist mental health services. The study emphasises that integrating digital prediction models into everyday healthcare could strengthen preventive approaches and improve patient outcomes.

By focusing on the role of primary care in early detection, this research demonstrates how evidence-based digital tools can help bridge the gap between routine healthcare and specialist mental health services, supporting more timely and personalised care.

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