Sensing Technologies for Maternal Depression Treatment in Low-Resource Settings
Overview
- Phase
- Not Applicable
- Intervention
- Not specified
- Conditions
- Post Partum Depression
- Sponsor
- George Washington University
- Enrollment
- 120
- Locations
- 1
- Primary Endpoint
- Patient Health Questionnaire-9 (PHQ-9)
- Status
- Recruiting
- Last Updated
- 10 months ago
Overview
Brief Summary
In certain low- and middle- income country settings, there is a disproportionate level of untreated postpartum depression that presents both acute and long-term risks to a mother's well-being. Although there is increasing willingness among health systems to involve non-specialists, such as community health workers, in the delivery of psychosocial interventions for postpartum depression, the effectiveness of these interventions has been mixed. The incorporation of digital technology, though, has the potential to improve the effectiveness of non-specialist-delivered interventions.
The goal of this clinical trial is to evaluate the acceptability and clinical efficacy of the StandStrong intervention- a non-specialist, passive sensing technology-informed (i.e., digital) mental health intervention- as compared to a standard non-specialist mental health intervention among postpartum-depressed mothers in Nepal. Successful completion of the trial will contribute to the optimization of psychosocial intervention delivery for the postpartum context in low- and middle-income country settings.
Detailed Description
Among certain low- and middle- income countries, there is a disproportionate level of untreated postpartum depression that presents both acute and long-term risks to a mother's well-being and her child's survival, health, and development. Although there is increasing willingness among health systems to involve non-specialists, such as community health workers, in the delivery of psychosocial interventions for postpartum depression, the outcomes of these interventions have been mixed. Digital technology, specifically the use of passive sensing data collection to quantitatively asses a mother's health and monitor behavior change, has the potential to improve the effectiveness of non-specialist-delivered interventions. Per this clinical trial, our research team will expand upon previous pilot work and evaluate the StandStrong intervention, a passive sensing technology-informed intervention adapted for postpartum depression. StandStrong- a passive sensing technology platform that consists of passive sensors (i.e., smartphone and GPS beacon), a passive sensing data visualization application, and a passive data analysis engine based in a modern machine-learning approach- transmits passive sensing data from a given mother and her infant to a trained, albeit non-specialist provider who interprets such data and then personalizes the intervention for her. Throughout the trial, the intervention within which this data will be integrated is Problem Management Plus (PM+). Validated across multiple low- and middle-income country settings, PM+ is World Health Organization-developed, five-session task-sharing intervention for mild to moderate distress. Per the (manualized) intervention, trained non-specialist providers coach eligible clients to address practical problems and/or distress in their daily lives via the use of fundamental cognitive behavioral strategies (e.g., deep breathing and stress management, behavioral activation, strengthening of social support, etc.). In particular, our team will conduct a double-arm, single-blind, individual-randomized controlled trial (RCT) that evaluates the clinical efficacy of platform-informed delivery of the intervention as compared to standard delivery of the intervention. We hypothesize that platform-informed delivery will more significantly reduce severity of symptoms- such as depression, anxiety, and quality of life- associated with postpartum depression relative to standard delivery; moreover, we imagine that platform-informed delivery will prove both cost-effective and scalable. Moreover, we will pose recommendations for platform and intervention implementation within the Nepal health system relative to the RE-AIM framework (i.e., Reach; Effectiveness; Adoption; Implementation; Maintenance). Successful completion of the trial will contribute to the optimization of psychosocial intervention delivery for the postpartum context in low- and middle-income country settings.
Investigators
Brandon A Kohrt, MD, PhD
Professor of Psychiatry and Behavioral Health, Global Health, and Anthropology
George Washington University
Eligibility Criteria
Inclusion Criteria
- •Mother Age: 15-39 years
- •Infant Age: Within 1st 1000 days of life
- •Mother PHQ-9 Score: 8+
- •Access to a technology charging modality within home
- •Will remain in the study area for a minimum of 6 months after enrollment
Exclusion Criteria
- •Mother PHQ-9 Score: Less Than 8
- •Different permanent residences of mother and infant at time of recruitment
- •Acute medical need or hospitalization of mother or infant at time of recruitment
- •Presentation of psychotic symptoms (as indicated by the psychosis module of the locally validated Community Informant Detection Tool) at time of recruitment
Outcomes
Primary Outcomes
Patient Health Questionnaire-9 (PHQ-9)
Time Frame: 20 Weeks Following Baseline Assessment
9-item self-report scale that assesses severity of depression symptoms * Minimum Value = 0 * Maximum Value = 27 * Higher scores indicate increased severity of depression symptoms
Secondary Outcomes
- Generalized Anxiety Disorder-7 (GAD-7)(20 Weeks Following Baseline Assessment)
- Psychological Outcome Profiles Questionnaire (PSYCHLOPS)(20 Weeks Following Baseline Assessment)
- World Health Organization Disability Assessment Schedule (WHODAS)(20 Weeks Following Baseline Assessment)