Rate and predictors of disengagement from a 2-year early intervention program for psychosis in Hong Kong

• Published in: Schizophrenia research Vol. 153; no. 1; pp. 204 - 208
• Main Authors: Chan, Tracey C.W, Chang, W.C, Hui, Christy L.M, Chan, Sherry K.W, Lee, Edwin H.M, Chen, Eric Y.H
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier B.V 01.03.2014; Elsevier
• Subjects: Adolescent; Adult and adolescent clinical studies; Biological and medical sciences; Cohort Studies; Disengagement; Early Diagnosis; Early Intervention (Education); Female; First-episode psychosis; Hong Kong - epidemiology; Humans; Male; Medical sciences; Medication Adherence; Patient Compliance; Predictive Value of Tests; Proportional Hazards Models; Psychiatric Status Rating Scales; Psychiatry; Psychology. Psychoanalysis. Psychiatry; Psychopathology. Psychiatry; Psychoses; Schizophrenia; Schizophrenia - diagnosis; Schizophrenia - epidemiology; Schizophrenia - therapy; Schizophrenic Psychology; Treatment adherence; Young Adult; Hong Kong; Asia; China; Schizophrenia; Treatment adherence; First-episode psychosis; Disengagement; Human; Psychosis; Decommitment; First episode; Treatment compliance; Early; Predictive factor
• ISSN: 0920-9964; 1573-2509
• DOI: 10.1016/j.schres.2014.01.033

Abstract Objectives This study aims to examine the prevalence and predictors of disengagement in a longitudinal cohort of first-episode psychosis (FEP) patients. Methods Seven hundred FEP patients aged 15 to 25 enrolled into the Early Assessment Service for Young People with Psychosis (EASY) from 2001 to 2003 were recruited into the study. Data on sociodemographics, clinical characteristics, baseline symptoms and functioning and medication adherence were collected. Rate and predictors of service disengagement were the outcomes of interest. Predictors were examined using Cox proportional hazards model. Results Ninety four patients (13%) were disengaged from the EASY program. Fewer negative symptoms at initial presentation, a diagnosis other than schizophrenia-spectrum disorder and poorer medication compliance in the first month of treatment were significant predictors of disengagement from service. Conclusions Early intervention teams should pay attention to factors associated with disengagement, and monitor at risk patients closely to detect signs of non-adherence.