R03 – Discovering the Capacity of Primary Care Frontline Staff to Deliver a Low-Intensity, Technology-Enhanced Intervention to Treat Geriatric Depression
- Brenna Renn, PhD, Acting Assistant Professor, Psychiatry and Behavioral Sciences
- Oleg Zaslavsky, PhD, MHA, RN, Assistant Professor, Biobehavioral Nursing and Health Informatics
Older adults with depression typically present to primary care rather than specialty mental health treatment and are often un- or undertreated, as the demand for mental health services is greater than the supply of trained providers. Technology is one method to improve access to care by making evidence-based psychosocial interventions (EBPIs) readily accessible. A second method comes from global mental health research, demonstrating that task-sharing can equip non-specialists to provide effective mental health care. This study combines these two approaches, exploring how technology-enhanced EBPI could be used by frontline primary care staff (e.g., nurses, medical assistants) to expand workforce capacity to deliver acceptable, sustainable, and effective treatment for depression. Specifically, we will use task-sharing to deliver Mobile Motivational Physical Activity Targeted Intervention (MobMPATI), which is based on behavioral activation for depression and uses wearable accelerometer technology to trigger personalized activity goal monitoring. This proposal uses the Discover, Design/Build, Test (DDBT) framework, which leverages user-centered design and implementation science to discover implementation barriers to using task-sharing to deliver MobMPATI in primary care, to design an implementation strategy to support MobMPATI delivery, and to conduct a pilot usability trial to test the implementation strategy with the most suitable frontline staff.