Sensing Technologies for Maternal Depression Treatment (StandStrong)

PROJECT SUMMARY/ABSTRACT There is a high global burden of untreated postpartum depression. Untreated postpartum depression presents acute and long-term risks to a mother’s mental and physical health, as well as her child’s survival, health, and development. Although there is increasing willingness among funders and health systems to involve nonspecialists, such as community health workers, in the delivery of psychological interventions for postpartum depression, the outcomes of these non-specialist interventions have been mixed. Digital technology, specifically the use of passive sensing data collection to learn more about a mother’s life and support behavior change, has the potential to improve the effectiveness of psychological interventions delivered by non-specialists. For the proposed R21/R33, we will build on preliminary development work of Sensing Technologies for Maternal Depression Treatment (StandStrong) to demonstrate feasibility, acceptability, and functionality for postpartum depression treatment. StandStrong is a digital platform consisting of two mobile apps, internet-of-things (IoT) passive sensors, and a data analysis engine built using modern machine learning approaches. StandStrong incorporates passive sensing data collection from mothers and their infants that can be monitored by nonspecialist counselors and then incorporated to better personalize psychological treatment. For Aim 1 (R21 phase), we will use human-centered design to iteratively refine the StandStrong platform and associated implementation material. For Aim 2 (R21 phase), we will evaluate the StandStrong platform and associated contents according to acceptability, feasibility, usage, benefit, and validity. If milestones are met for the R21, we will proceed to the R33 stage. In the R33 stage, for Aim 3 we will conduct a pilot randomized controlled trial (RCT) comparing a psychological treatment as usual with the psychological treatment supplemented by the StandStrong passive sensing platform with 112 depressed mothers (56 in each arm). For Aim 4 of the R33 phase, we will identify parameters for sustainability and scalability, as well as costing the intervention, to ultimately prepare for a fully-powered RCT in the United States with future R01 funding. Successful completion contributes to the NIMH’s 2020 Strategic Plan to tailor existing interventions and develop innovative service deliver for mental health interventions. This project will contribute to NIMH’s Opportunities and Challenges of Developing Information Technologies through improving treatment of mental health conditions through use of passive sensing technologies.