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: 10857727
• 负责人: Kamal Gautam
• 金额: $ 30.87万
• 依托单位: GEORGE WASHINGTON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-01 至 2026-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10857727
• 关键词: Accelerometer; Acute; Anthropology; Behavior monitoring; Behavioral; Biometry; Bluetooth; Cellular Phone; Child; Clinical Research; 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; Psyche structure; Psychiatry; Qualitative Research; Randomized; Randomized, Controlled Trials; Readiness; Research; Resource-limited setting; Risk; Safety; Services; Social Environment; South Africa; Speech; Strategic Planning; Suicide; Technology; Testing; Theory of Change; Time; Visualization; Work; arm; behavior change; behavioral and social science; child depression; convolutional neural network; digital; digital mental health; digital platform; digital technology; experimental arm; health economics; human centered design; implementation cost; implementation science; improved; innovation; intervention cost; literacy; low and middle-income countries; mHealth; maternal depression; maternal morbidity; mobile application; physical conditioning; post intervention; privacy preservation; psychologic; recruit; sensor; sensor technology; smart watch; sound; teenage mother; therapy development; treatment as usual; treatment planning; trial comparing; usability; wearable device; 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.

项目摘要/摘要 未经治疗的产后抑郁症在全球范围内负担很高。未经治疗的产后抑郁症 对母亲的身心健康以及其子女的生存、健康和 发展虽然供资者和卫生系统越来越愿意让非政府组织参与， 专家，如社区卫生工作者，在提供心理干预产后 抑郁症，这些非专家干预的结果是喜忧参半。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和支持行为变化， 提高非专家提供的心理干预的有效性的潜力。为 建议R21/R33，我们将建立在产妇传感技术的初步开发工作， 低资源环境下的抑郁症治疗（StandStrong），以证明可行性，可接受性， 产后抑郁症的治疗。StandStrong是一个数字平台，由两个 移动的应用程序、物联网（IoT）无源传感器和使用现代机器构建的数据分析引擎 学习方法。StandStrong集成了从母亲和婴儿那里收集的被动传感数据 可以由非专业顾问进行监测，然后结合起来，以更好地个性化心理治疗。 治疗对于目标1（R21阶段），我们将使用以人为本的设计来迭代地完善StandStrong 平台和相关实施材料。对于目标2（R21阶段），我们将评估StandStrong 平台和相关内容，根据可接受性，可行性，用途，效益和有效性。如果里程碑 如果R21符合要求，我们将进入R33阶段，在该阶段，我们将进行一项试验性随机对照研究， 一项随机对照试验（RCT），比较了常规心理治疗与 Stand Strong被动传感平台，112名抑郁母亲（每组56名）。对于目标3（R33阶段）， 我们将通过政策、医疗保健和 电信利益相关者，以及成本的干预和建设移动健康的研究能力。成功 完成有助于NIMH的2020年战略计划，以调整现有的干预措施，并开发创新的 为不同人群提供服务。该项目将有助于NIMH的机遇和挑战， 发展信息技术，通过使用被动治疗改善精神疾病 传感技术