Background: Recovery, the optimal goal in treatment, is the attainment of both symptomatic and functional remission over a sustained period of time. Identification of factors that promote recovery can help develop interventions that facilitate good outcomes for people with first episode psychosis.

Aim: To examine long-term outcomes within a cohort of people with first episode psychosis in relation to symptom remission, functioning and recovery, 10 years after diagnosis.

Method: The study had a prospective design. Participants from the OPUS trial (1998-2000) (n=496) completed a series of interviews and questionnaires to measure current levels of psychopathology and social/vocational functioning, ten years after diagnosis. Predictors of recovery were identified using socio-demographic and clinical characteristics collected at baseline.

Results: A total of 304 participants were interviewed, giving a follow-up rate of 61%. A total of 42 people (14%) met the criteria for symptomatic and psychosocial recovery at 10 years. A multivariable binary logistic regression analysis indicated that baseline predictors accounted for 22% of the variance of full recovery. Lower severity of negative symptoms at baseline (Odds Ratio (OR) 0.53, 95% confidence interval CI 0.36-0.78, p<0.001) and earlier age of diagnosis (OR 0.92, 95% CI 0.86-0.99, p<0.05) predicted better rates of recovery at 10 years.

Conclusion: Results of this study indicated that negative symptoms could play a central role in the process of recovery from schizophrenia. A challenge for clinicians and researchers is to understand the mechanisms behind negative symptoms and develop interventions that can prevent or ameliorate these symptoms in order to promote recovery.

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.schres.2013.07.031DOI Listing

Publication Analysis

Top Keywords

predictors recovery
8
episode psychosis
8
people episode
8
recovery years
8
recovery
6
recovery episode
4
psychosis opus
4
opus cohort
4
cohort year
4
year follow-up
4

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!