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)

基本信息

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
项目类别：
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

项目摘要

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.

项目概要/摘要未经治疗的产后抑郁症给全球带来了沉重的负担。未经治疗的产后抑郁症对母亲的身心健康以及孩子的生存、健康和健康造成严重和长期的风险发展。尽管资助者和卫生系统越来越愿意让非社区卫生工作者等专家为产后提供心理干预对于抑郁症，这些非专业干预措施的结果好坏参半。数字技术，特别是使用被动传感数据收集来更多地了解母亲的生活并支持行为改变，提高非专家心理干预效果的潜力。对于拟议的R21/R33，我们将在孕产妇传感技术的初步开发工作的基础上资源匮乏地区的抑郁症治疗 (StandStrong)，以证明可行性、可接受性和尼泊尔产后抑郁症治疗的功能。 StandStrong 是一个数字平台，由两个部分组成移动应用程序、物联网 (IoT) 无源传感器以及使用现代机器构建的数据分析引擎学习方法。 StandStrong 整合了来自母亲及其婴儿的被动传感数据收集可以由非专业咨询师进行监控，然后将其纳入以更好地个性化心理治疗。对于Aim 1（R21阶段），我们将采用以人为本的设计来迭代完善StandStrong 平台和相关实施材料。对于目标 2（R21 阶段），我们将评估 StandStrong 根据可接受性、可行性、用途、效益和有效性评估平台和相关内容。如果里程碑如果满足 R21 的要求，我们将进入 R33 阶段，在该阶段我们将进行随机对照试验试验（RCT）比较常规心理治疗与补充心理治疗 StandStrong 被动传感平台有 112 名抑郁母亲（每只手臂 56 名）。对于目标 3（R33 阶段），我们将通过政策、医疗保健和其他方面的参与来确定可持续性和可扩展性的参数电信利益相关者，以及干预成本和移动医疗研究能力建设。成功的完成有助于 NIMH 的 2020 年战略计划，以调整现有干预措施并开发创新为不同人群提供服务。该项目将为 NIMH 的机遇和挑战做出贡献通过使用被动疗法改善精神疾病的治疗来发展信息技术传感技术。