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Updated: Jan 3, 2026

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
Published on: May 15, 2020
Transitioning to age inclusive early intervention for psychosis
Ciarán O'Driscoll1, Katherine Free2, Angelica Attard3
1Research Department of Clinical, Educational and Health Psychology, University College London, London, UK.
Aim:
Early Intervention in psychosis Services (EIS) have previously restricted access based on age. However, there is now a move to age inclusive service. We aimed to examine differences between early and late onset (>35 years) psychosis to see if a threshold was valid. We also investigated the potential of a statistical modelling method to identify group characteristics which may be missed using a descriptive approach.
Methods:
Routine clinical data (n = 343), from an EIS, comprising socio-demographic, clinical, physical and treatment variables, were examined using descriptive and classification and regression tree (CART) analysis.
Results:
The findings suggest that age differences were best explained by social factors. There was no emerging evidence that the differences exhibited had a fundamental impact on the clinical outcomes of the clients in terms of support beyond EIS (ie, hospitalization and home treatment team involvement) and pharmacological and psychological interventions. CART analysis revealed distinct service user characteristics associated with the clinical outcomes.
Conclusion:
There was no evidence to support a clinical cut off based on age providing support for age inclusive services. However, in the transition to age inclusive service delivery, EIS need to consider social/life stage variables, adapting provision where service delivery may operate a youth focused model. Routine analysis of clinical data should employ methods to identify groups of service users who may require adjusted service provision.
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