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.

项目总结/摘要 这项建议有可能改变向弱势群体提供卫生信息的方式。我们 该提案提倡采取更灵活和更有针对性的办法，帮助得不到充分服务的群体。种族/族裔少数 妇女患产后抑郁症的风险增加，她们的孩子不太可能有健康的孩子。 去年的检查。此外，在孕产妇和婴儿死亡率方面， 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的家访（由于人员和成本，规模有限 限制）或非个性化文本消息（可能无法直接解决个人的问题）。我们 我建议开发一个聊天机器人，通过代表一个 可扩展的工具，可以在不同的地理位置广泛使用，并且是个性化的， 个人的具体信息需求。我们已经建立了一个聊天机器人的原型，罗西，能够参与 在现场问答环节。罗西能够回答334个流行的问题，新妈妈可能会 有.对母亲团体和玛丽中心患者的预测试显示出对聊天机器人的积极接受。 在赠款的过程中，我们将利用自然语言处理的最新进展， 出现了努力汇集大量的健康信息，以汇集一个全面的 健康信息图书馆我们将进一步完善Rosie的对话分析器和响应推理引擎， 鲁棒地识别和响应用户的问题，在各种复杂的方式，他们可以短语， 问题我们将检验罗茜可能降低产后抑郁症的风险， 房间访问，并增加婴儿访问的出席率。我们将主要采用虚拟招聘策略 进行一项随机对照试验，以评估这种干预对母婴的影响， 结果。我们的调查团队由流行病学、计算机科学、 生物统计学和孕产妇和儿童健康专家，是唯一适合实现研究目标。我们 具体目标是：1）为聊天机器人Rosie开发技术，为以下人员提供健康信息支持： 在弱势母亲需要的时候提供帮助; 2）评估Rosie的使用对孕产妇和婴儿结局的影响; 以及3）发布用于构建聊天机器人的开源包。罗西提供信息支持 在脆弱的妈妈们需要的时候提供给她们，保护新妈妈们免受常见的错误信息的伤害。 最终目标是缩小母婴之间的差距。成果和工具 从这一建议中发展出来的信息可以用来为基于人口的战略提供信息，以减少健康差距 并改善健康。