# R01-Signature Project: A hybrid implementation trial testing strategies to scale an evidence-based weight management program for persons with serious mental illness > **NIH NIH P50** · JOHNS HOPKINS UNIVERSITY · 2024 · $617,523 ## Abstract Obesity is highly prevalent among people with serious mental illness (SMI), and through its effects on other cardiovascular disease (CVD) risk factors, represents a principal cause of preventable death in this population. There is an urgent need to scale behavioral interventions that can effectively address obesity in persons with SMI, however, rigorous testing of implementation strategies is needed to address the numerous system-, organizational-, and individual-level barriers that hinder their widespread adoption and sustainment. One such behavioral intervention, tailored to address this population’s unique needs, demonstrated clinically significant weight loss in persons with SMI through the NIMH-funded ACHIEVE trial. During the ALACRITY Center’s initial funding period, our team adapted the ACHIEVE intervention so that it could be delivered by community mental health staff – resulting in the ACHIEVE-D weight management program – which incorporated implementation strategies such as training, coaching, and organizational strategy meetings to support intervention delivery. The pilot showed high levels of staff engagement and client participation, however, there were several barriers to program sustainment. In the proposed study, we will partner with community mental health organizations in New Jersey and Delaware, state leaders, and other partners to adapt and test strategies to support the implementation and sustainment of ACHIEVE-D, including: 1) Replicating Effective Programs (REP), the foundational implementation strategy that includes ACHIEVE-D program materials, training, and technical assistance, and 2) an enhanced implementation strategy package with: a) an internal facilitator to support site- level communication and coordination, leadership for implementation, and a supportive implementation climate, and b) bi-state learning networks to promote knowledge-sharing, peer influence, skill development, and high-quality relationships. We will test these multi-level strategies in a cluster-randomized Type 3 hybrid effectiveness-implementation trial. Our uniquely and highly qualified team propose the following Specific Aims: 1) establish a collaborative partnership with 32 community mental health programs (64 staff implementers and 320 clients participants) in New Jersey and Delaware and state mental health leadership to plan for ACHIEVE- D implementation and sustainment, integrating cost planning; 2) determine the effectiveness of the enhanced implementation strategy package (compared to REP alone) on the uptake and delivery of ACHIEVE-D at six months; measure implementation from 7 through 12 months; and 3) determine the costs, budget impact, and cost-effectiveness of deploying REP plus the enhanced implementation strategy package versus “standard” REP to support scaling and sustainment of ACHIEVE-D. By engaging with partners across two states to test multi-level strategies to inform implementation, sustainment, and scaling of an evidence-base... ## Key facts - **NIH application ID:** 10843612 - **Project number:** 2P50MH115842-05 - **Recipient organization:** JOHNS HOPKINS UNIVERSITY - **Principal Investigator:** Gail L. Daumit - **Activity code:** P50 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2024 - **Award amount:** $617,523 - **Award type:** 2 - **Project period:** 2018-08-15 → 2029-04-30 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10843612 ## Citation > US National Institutes of Health, RePORTER application 10843612, R01-Signature Project: A hybrid implementation trial testing strategies to scale an evidence-based weight management program for persons with serious mental illness (2P50MH115842-05). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10843612. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*