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: 10654862
• 负责人: Elizabeth Marie Aparicio
• 金额: $ 60.47万
• 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/10654862
• 关键词: Address; Algorithms; Anxiety; Appointment; Artificial Intelligence; Back to Sleep; Behavioral Sciences; Biometry; Breast Feeding; Child; Childbirth; 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; Minority Women; Misinformation; Mothers; Natural Language Processing; Participant; Population; Postpartum Depression; Pregnancy; Preventive; Procedures; Public Health; Quality of life; Randomized; Randomized, Controlled Trials; Reduce health disparities; Resources; Risk; Role; Sampling; Technology; Testing; Text Messaging; Underserved Population; Visit; Vulnerable Populations; Well Child Visits; Woman; care outcomes; chatbot; checkup examination; community clinic; computer science; coping; cost; cost effective; design; disparity reduction; ethnic disparity; ethnic minority; family support; flexibility; health care service organization; health organization; improved; infant nutrition; infant outcome; maternal outcome; new technology; open source; outcome disparities; patient oriented; personalized approach; phrases; population based; programs; prototype; racial disparity; racial health disparity; racial minority; recruit; response; scale up; screening guidelines; stressor; tool; virtual; web page; women of color

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 这项提议有可能改变向弱势人群提供卫生信息的方式。我们的 Proposal促进了一种更灵活和量身定制的方法，以接触到服务不足的群体。种族/少数民族 女性患产后抑郁症的风险更高，她们的孩子生下好孩子的可能性也更小 过去一年的体检。此外，在孕产妇和婴儿死亡率方面，种族/族裔差异仍然普遍存在。 以及各种健康行为，如安全睡眠习惯、母乳喂养和婴儿营养。目前， 一些受欢迎的项目涉及资源密集型家访(由于人员和成本的原因，规模有限 限制)或非个性化文本消息(可能不能直接回答个人的问题)。我们 建议开发一个聊天机器人，通过表示一个 可扩展的工具，可在不同的地理位置广泛覆盖，并可个性化并响应 个人特定的信息需求。我们已经建造了聊天机器人Rosie的原型，它能够参与 在现场问答环节。罗西能够回答334个新妈妈可能会提出的流行问题 有。对母亲团体和玛丽中心患者的预测测试显示，聊天机器人受到了积极的欢迎。 在拨款过程中，我们将利用自然语言处理方面的最新进展和 出现了聚合海量健康信息的努力，以汇集全面的 健康信息图书馆。我们将进一步改进Rosie的对话分析器和响应推理引擎，以 以各种复杂的方式坚定地识别和回答用户的问题 问题。我们将验证罗西可以降低产后抑郁症风险，减少紧急情况的假设 探访房间，并增加探望健康婴儿的出勤率。我们将主要采用虚拟招聘战略 进行一项随机对照试验，以评估该干预措施对母婴的影响 结果。我们的调查团队-由流行病学、计算机科学、 生物统计学和妇幼保健专家是唯一适合实施这项研究目标的机构。我们的 具体目标是：1)开发聊天机器人Rosie的技术，该技术将为 2)评估罗西对母婴结局的影响； 3)发布构建聊天机器人的开源包。罗西提供信息支持 在脆弱的母亲需要的时候提供给他们，并保护新母亲免受常见的错误信息的影响 最终目标是缩小母婴结局的差距。结果和工具 根据这一建议制定的可用于指导基于人口的战略，以减少健康差距 并改善健康状况。