Rosie the Chatbot: Leveraging Automated and Personalized Health Information Communication to Reduce Disparities in Maternal and Child Health

聊天机器人 Rosie：利用自动化和个性化的健康信息通信来减少母婴健康差异

• 批准号: 10173272
• 负责人: Elizabeth Marie Aparicio
• 金额: $ 59.76万
• 依托单位: UNIV OF MARYLAND, COLLEGE PARK
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-24 至 2026-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10173272
• 关键词: Address; Algorithms; Anxiety; Appointment; Artificial Intelligence; Back to Sleep; Behavioral Sciences; Biometry; Breastfed infant; Child; Childbirth; Color; Communication; Communities; Complex; Computer software; Development; Discrimination; Emergency department visit; Ensure; Epidemiology; Experimental Designs; Family; Focus Groups; Friends; Geography; Goals; Grant; Health; Health Professional; Health behavior; Home visitation; Hour; Immunization; Individual; Infant Mortality; Informatics; Internet; Intervention; Knowledge; Left; Libraries; Maternal Mortality; Maternal and Child Health; Medical; Medicine; Methodology; Methods; Misinformation; Mothers; Natural Language Processing; Participant; Population; Postpartum Depression; Pregnancy; Preventive; Procedures; Public Health; Quality of life; Randomized; Randomized Controlled Trials; Resources; Risk; Role; Sampling; Technology; Testing; Text Messaging; Time; Underserved Population; Visit; Vulnerable Populations; Well Child Visits; Woman; base; care outcomes; chatbot; checkup examination; community clinic; computer science; coping; cost; cost effective; design; disparity reduction; ethnic minority population; family support; flexibility; health care service organization; health disparity; health organization; improved; infant nutrition; infant outcome; maternal outcome; new technology; online community; open source; patient oriented; personalized approach; phrases; population based; programs; prototype; racial and ethnic; racial and ethnic disparities; recruit; response; scale up; screening guidelines; stressor; tool; virtual; web page

PROJECT SUMMARY/ABSTRACT This proposal has the potential to alter the way health information is presented to vulnerable populations. Our proposal promotes a more flexible and tailored approach to reach underserved groups. Racial/ethnic minority women are at increased risk for postpartum depression, and their children as less likely to have had well-child checkups in the past year. Moreover, racial/ethnic disparities are still prevalent for maternal and infant mortality as well as various health behaviors such as safe sleep practices, breastfeeding, and infant nutrition. Currently, some popular programs involve resource-intensive home visits (limited in scale due to staff and cost constraints) or non-personalized text messages (may not directly address an individual’s questions). We propose the development of a chatbot that addresses both of these possible limitations by representing a scalable tool that can have widespread reach across geographies and is personalized and responsive to an individual’s specific informational needs. We have built a prototype of the chatbot, Rosie, capable of engaging in live question-and-answer sessions. Rosie is able to respond to 334 popular questions that new mothers may have. Pretests with mother groups and Mary’s Center patients have showed a positive reception to the chatbot. Over the course of the grant, we will leverage recent advances in natural language processing and the emergence of efforts to aggregate massive amounts of health information, to assemble a comprehensive health information library. We will further refine Rosie’s dialogue analyzer and response inference engine to robustly recognize and respond to user’s questions in the various and complex ways they can phrase a question. We will test the hypothesis that Rosie may lower risk of postpartum depression, decrease emergency room visits, and increase attendance of well-baby visits. We will employ primarily a virtual recruitment strategy to conduct a randomized controlled trial to evaluate the impact of this intervention on maternal and infant outcomes. Our investigative team—comprised of experts in the field of epidemiology, computer science, biostatistics, and maternal and child health experts—is uniquely suited to implement the study aims. Our Specific Aims are: 1) Develop technology for a chatbot, Rosie, that will provide health informational support to vulnerable mothers the moment they need it; 2) Evaluate the use of Rosie on maternal and infant outcomes; and 3) Release an open-source packet for the construction of a chatbot. Rosie provides informational support to vulnerable moms the moment they need it and safeguards new moms from misinformation that is common on the web with the ultimate goal of closing the gap in maternal and infant outcomes. Results and tools developed from this proposal can be utilized to inform population-based strategies to reduce health disparities and improve health.

项目摘要/摘要 该提案有可能改变对脆弱人群的健康信息的方式。我们的 提案促进了一种更灵活，更量身定制的方法，以吸引服务不足的群体。种族/族裔少数民族 妇女患产后抑郁症的风险增加，她们的孩子不太可能有孩子 过去一年的检查。此外，孕产妇和婴儿死亡率仍然普遍存在种族/族裔差异 以及各种健康行为，例如安全的睡眠习惯，母乳喂养和婴儿营养。现在， 一些受欢迎的计划涉及资源密集型家庭访问（由于员工和成本而导致的规模限制 约束）或非个人化文本消息（可能不会直接解决个人的问题）。我们 提议开发聊天机器人，该聊天机器人通过代表一个来解决这两个可能的限制 可扩展工具可以在整个地理上具有宽度范围，并且是个性化的，并且对 个人的特定信息需求。我们已经建立了聊天机器人Rosie的原型，能够参与 在现场问答环节中。罗西能够回答新妈妈可能的334个流行问题 有。对母亲团体和玛丽中心患者的预测试对聊天机器人表示积极接待。 在赠款的过程中，我们将利用自然语言处理的最新进展和 努力汇总大量健康信息的努力，组装全面的 健康信息库。我们将进一步完善Rosie的对话分析仪和响应推理引擎 坚强地识别并以各种复杂的方式来回答用户的问题 问题。我们将检验以下假设：罗西可能会降低产后抑郁症的风险，减少紧急情况 室访，增加出现良好的访问。我们将采用主要的虚拟招聘策略 进行随机对照试验来评估这种干预对母乳和婴儿的影响 结果。我们的调查团队 - 由流行病学，计算机科学领域的专家， 生物统计学以及母婴健康专家非常适合实施这项研究的目的。我们的 具体目的是：1）为聊天机器人Rosie开发技术，该技术将为健康提供支持 他们需要的那一刻脆弱的母亲； 2）评估Rosie在物物和婴儿结果上的使用； 3）释放一个开源数据包，用于建造聊天机器人。罗西提供信息支持 他们需要的那一刻，并保护新妈妈免受常见的误解 在网络上，其最终目标是缩小母亲和婴儿结果的差距。结果和工具 可以从该提案中开发出来，以告知基于人群的策略以减少健康差异 并改善健康。