Sensing Technologies for maternal depression treatment in low resource settings (StandStrong)

资源匮乏地区孕产妇抑郁症治疗的传感技术 (StandStrong)

• 批准号: 10268579
• 负责人: Brandon Alan Kohrt
• 金额: $ 21.53万
• 依托单位: GEORGE WASHINGTON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-01 至 2023-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10268579
• 关键词: Accelerometer; Acute; Anthropology; Behavior monitoring; Behavioral; Biometry; Bluetooth; Car Phone; Cellular Phone; Child; Clinical Sciences; Communities; Community Health Aides; Data; Data Analyses; Data Collection; Development; Devices; Educational workshop; Effectiveness; Enrollment; Exposure to; Family member; Geography; Global Positioning System; Goals; Health; Health system; Healthcare; Human; Husband; Infant; Information Technology; Internet of Things; Intervention; Learning; Life; Machine Learning; Maternal Mortality; Measurement; Mental Depression; Mental Health; Mental disorders; Modernization; Monitor; Mothers; Movement; National Institute of Mental Health; Nepal; Outcome; Pattern; Phase; Phenotype; Physical activity; Policies; Population Heterogeneity; Postpartum Depression; Prevalence; Principal Component Analysis; Process; Professional counselor; Psychiatry; Qualitative Research; Randomized; Randomized Controlled Trials; Readiness; Research; Resources; Risk; Safety; Services; Social Environment; South Africa; Speech; Strategic Planning; Suicide; Technology; Testing; Time; Visualization; Work; arm; behavior change; behavioral/social science; child depression; convolutional neural network; design; digital; digital mental health; experimental arm; health economics; implementation cost; implementation science; improved; innovation; intervention cost; literacy; low and middle-income countries; mHealth; maternal depression; maternal morbidity; mobile application; physical conditioning; privacy preservation; psychologic; recruit; sensor; sensor technology; smart watch; sound; teenage mother; theories; therapy development; treatment as usual; treatment planning; trial comparing; usability; willingness; young mother

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 non- specialists, 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 in Low Resource Settings (StandStrong) to demonstrate feasibility, acceptability, and functionality for postpartum depression treatment in Nepal. 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 non-specialist 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 which 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 3 (R33 phase), we will identify parameters for sustainability and scalability through engagement of policy, healthcare, and telecom stakeholders, as well as costing the intervention and building mHealth research capacity. Successful completion contributes to the NIMH's 2020 Strategic Plan to tailor existing interventions and develop innovative service deliver for diverse populations. This project will contribute to NIMH's Opportunities and Challenges of Developing Information Technologies through improving treatment of mental illness through use of passive sensing technologies.

项目总结/文摘