Rates and Predictors of Disengagement and Strength of Engagement for People With a First Episode of Psychosis Using Early Intervention Services: A Systematic Review of Predictors and Meta-analysis of Disengagement Rates

Abstract

AbstractDisengagement is a problem in early intervention for psychosis services; identifying predictors is important to maximise mental-health care.AimTo establish the average disengagement rate, time to disengage, and predictors of disengagement or strength of engagement.MethodsPapers were identified from 5 databases and citation searches; chosen if they reported dis/engagement in early intervention services, discarded if they didn't give a clear definition of disengagement. The studies were rated for quality and a systematic review identified predictors of engagement; meta-analysis established the average disengagement rate. Meta-regression evaluated associations between disengagement and year of study or length of follow up.Results26 papers were reviewed comprising over 6800 participants, meta-analysis of 15 eligible cohorts found that the average disengagement rate was 15.60% (95% confidence intervals 11.76%–20.45%), heterogeneity was considerable, important to note when reporting as a global average. Higher disengagement rates were associated with earlier studies and length of follow up; causal factors are unclear due to the lack of data and complex interaction between clinical and methodological issues. Robust predictors of disengagement were substance use, contact with the criminal justice system, medication non-adherence, and lower symptom severity.ConclusionsDisengagement rates have declined although the cause is not clear partly due to methodological variation, we suggest a guide for defining disengagement. Underpinning reasons for disengagement could include people who struggle to engage (substance users), don’t want to engage (medication non-adherence) or feel they don’t need to engage (lower symptomology). Future research should focus on minority status, education/employment during treatment, and digital technologies.