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Predictors of disengagement from Early Intervention in Psychosis services.


ABSTRACT: BACKGROUND:The effectiveness of Early Intervention in Psychosis (EIP) services for individuals with a first episode of psychosis (FEP) could be thwarted by high rates of early disengagement.AimsTo investigate which factors predict disengagement with EIP services. METHOD:Using data from a naturalistic cohort of 786 EIP clients in East Anglia (UK), we investigated the association between sociodemographic and clinical predictors and disengagement using univariable and multivariable Cox proportional hazards models. RESULTS:Over half (54.3%) of our sample were discharged before receiving 3 years of EIP care, with 92 (11.7%) participants discharged due to disengagement. Milder negative symptoms, more severe hallucinations, not receiving an FEP diagnosis, polysubstance use and being employed were associated with greater disengagement. CONCLUSIONS:Our findings highlight heterogeneous reasons for disengagement with EIP services. For some patients, early disengagement may hinder efforts to sustain positive long-term EIP outcomes. Efforts to identify true FEP cases and target patients with substance use problems and more severe positive symptoms may increase engagement.Declaration of interestNone.

SUBMITTER: Solmi F 

PROVIDER: S-EPMC6071847 | biostudies-literature | 2018 Aug

REPOSITORIES: biostudies-literature

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Predictors of disengagement from Early Intervention in Psychosis services.

Solmi Francesca F   Mohammadi Abdolali A   Perez Jesus A JA   Hameed Yasir Y   Jones Peter B PB   Kirkbride James B JB  

The British journal of psychiatry : the journal of mental science 20180801 2


<h4>Background</h4>The effectiveness of Early Intervention in Psychosis (EIP) services for individuals with a first episode of psychosis (FEP) could be thwarted by high rates of early disengagement.AimsTo investigate which factors predict disengagement with EIP services.<h4>Method</h4>Using data from a naturalistic cohort of 786 EIP clients in East Anglia (UK), we investigated the association between sociodemographic and clinical predictors and disengagement using univariable and multivariable C  ...[more]

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