Involvement opportunity: Predicting the risk of relapse in people with first episode psychosis

Title: Predicting the risk of relapse in people with first episode psychosis

Summary: Preventing and minimising the impact of relapse is an important component of early intervention in psychosis. Around 50% of people with first episode psychosis (FEP) will experience a psychotic relapse in the first two years following remission of their initial episode. Relapse has a negative impact on the individual’s social functioning, education, and employment opportunities. It increases the need for more intensive care in the community or hospitalisation, and is linked to poorer long-term outcomes. Early identification of individuals who are likely to relapse would allow a more personalised approach to care, enabling early intervention services to match resources and interventions to those who would most benefit from them. However, at present, it is not possible to predict which individuals are more likely to experience a psychotic relapse following their initial episode.

The aim of this study is to create a tool which predicts the risk of relapse in people with FEP. To obtain data for the study, we will use the CRATE tool, a software which anonymises mental health records by removing information that might identify an individual patient. We will develop a statistical model which estimates the risk of relapse for an individual within two years of their initial episode of psychosis. To produce these estimates, the model will use information about factors that are known to affect relapse risk from previous research. We will then test the model’s predictions on data from another group of people with FEP (for example from a different early intervention service) to assess how accurate they are. The model developed in this study can be translated into an online tool, which uses information about an individual to estimate how likely they are to experience a relapse within two years of their initial psychosis episode.

Future work will involve testing and improving the tool in larger samples, as well as assessing its acceptability and clinical usefulness for individuals with psychosis and healthcare professionals who will be using it. If successfully implemented in early intervention services, the tool that can provide reliable and individualised information about relapse risk to people with FEP, their families, and healthcare professionals. In addition, the tool can be used as a guide for clinicians working in early intervention services, allowing them to make more informed and accurate treatment decisions. By helping clinicians target resources and interventions to those who are most likely to relapse, and therefore most likely to benefit from them, the tool will allow a personalised approach to treatment and relapse prevention.

Research Team: Aida Seyedsalehi (PhD student, University of Oxford), Dr Graham Murray (Associate Professor, University of Cambridge; Honorary Consultant Psychiatrist, CPFT)

Involvement: We are seeking people with lived experience of psychosis including family members and/or carers with relevant experience to be involved in the design of this study. Input from people with experience of accessing early intervention services would be particularly helpful as this study is focusing on this setting. The researchers are in the process of developing a protocol for the project and would find it particularly helpful to have input regarding the design of the research (particularly in the selection of predictors to be included in the model). An online meeting will take place in the end of July or August. Further involvement opportunities will be discussed during the meeting but could include involvement in the implementation of the model in clinical practice.

Time commitment: At this stage, up to 4 hrs to discuss, provide feedback in writing and shape the design of the project. Depending on availability, a virtual 1.5hrs meeting will take place end of July or August.

Payment: Members will receive £15 per hour for their time and contribution. Please note, this income may have implications for those claiming benefits. All income must be declared to the Inland Revenue.

If you’re interested please email Iliana at

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