A Community-Engaged Process for Adapting a Cardiovascular Health Intervention for Persons with Serious Mental Illness.

Abstract

Introduction: People with serious mental illness experience grave disparities in cardiovascular disease risk factors. To promote scale-up of effective cardiovascular disease risk reduction interventions from clinical trials, it is important to involve end-users in adapting interventions to fit the needs of community-based settings.

Objective: We describe a novel, theory-informed process of garnering community input to adapt IDEAL Goals, an evidence-based intervention for improving cardiovascular disease risk factors in persons with serious mental illness.

Setting: Outpatient community mental health programs in Maryland and Michigan implementing behavioral health homes, which provide enhanced support to people living with both physical and mental illnesses.

Participants: Clinicians, frontline staff, and administrators from community mental health organizations and persons with serious mental illness.

Methods: Our approach to community engagement is based on the Replicating Effective Programs (REP) framework. During the REP preimplementation phase, we used 2 community engagement activities: (1) a "needs assessment" to identify anticipated implementation barriers and facilitators, and (2) "community working groups" to collaboratively engage with end-users in adapting the intervention and implementation strategies.

Main findings: We used the Stakeholder Engagement Reporting Questionnaire to describe our processes for conducting a needs assessment, involving site-level surveys (N=26) and individual interviews (N=94), and convening a series of community working groups with clinicians and staff (mean, 24 per meeting) and persons with serious mental illness (mean, 8 per meeting).

Conclusions: By specifying the nature and extent of our community engagement activities, we aim to contribute to the evidence base of how to better integrate and measure community-engaged processes in the adaptation of evidence-based interventions.