Predicting Initial Client Engagement with Community Mental Health Services by Routinely Measured Data

Engagement is a determinant of how well a person will respond to professional input. This study investigates whether, in practice, routinely measured data predict initial client engagement with community mental health services. Engagement, problem severity, client characteristics, and duration before the first contact were measured at team entrance with clients (n = 529) of three community mental health teams. Regression analysis was used to predict engagement. Gender, age, referrer, having children, having a partner, and ethnicity showed a minor relationship with engagement. Higher problem severity measured by the team members with the Health of the Nation Outcome Scales, being referred for having psychiatric problems and/or causing severe and long-lasting trouble (as ‘assessed’ by the often non-professional referrer), and a longer duration between enrollment and the first conversation with a client, were indicative for a lower engagement. The final model explained 19.2 % of the variance in engagement. It can be concluded that initial client engagement with community mental health services can be predicted, in part, by routinely measured data. The findings can be used by community mental healthcare teams to create an awareness system.