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Long-Term Trajectories of Multidimensional Outcomes in Psychosis Following Early Intervention During the Critical
Olivier Percie du Sert1,2, Joseph Ghanem1,3, Vanessa McGrory1,4
1Douglas Research Centre, Montreal, Quebec, Canada.
Introduction:
While early intervention services (EIS) have demonstrated short-term benefits, the long-term maintenance of these gains remains uncertain. Individuals with first-episode psychosis exhibit significant variability in their course of recovery. Understanding the risk and protective factors that shape long-term outcome trajectories is essential to predicting and promoting sustained recovery. Here, we present the protocol for an extended 10-year follow-up study of social, mental, cognitive, and physical health outcomes, supplemented through linkage with health administrative databases to offer a holistic perspective on long-term outcome trajectories.
Aim:
The primary objective of the study is to model the heterogeneity of long-term trajectories across multiple outcome dimensions over a 10-year follow-up period using data-driven methods.
Method:
The Prevention and Early Intervention Program for Psychoses (PEPP-Montreal) is a well-established, high-fidelity EIS program operating within a universal healthcare system and an epidemiologically defined catchment area in South-West Montréal, Canada. Between 2003 and 2018, PEPP-Montreal conducted a detailed two-year longitudinal assessment of 689 individuals aged 14-35 with first-episode affective or non-affective psychosis.
Discussion:
This study will help distinguish clinically meaningful subgroups, characterize their profiles, and identify early predictors of long-term outcomes while providing insight into the mechanisms of change within trajectories. In particular, the study will assess whether trajectories shaped during the critical period are sustained over the long term. To our knowledge, this represents the most comprehensive investigation of long-term trajectories following EIS in North America and is expected to lay the groundwork for optimizing EIS and developing personalized interventions.