Jessica Nathalie Rivera Rivera, Katarina E AuBuchon, Marjanna Smith, Claire Starling, Karen G Ganacias, Aimee Danielson, Loral Patchen, Janine A Rethy, H Joseph Blumenthal, Angela D Thomas, Hannah Arem
{"title":"为分娩者和新生儿护理者开发和完善聊天机器人:混合方法研究。","authors":"Jessica Nathalie Rivera Rivera, Katarina E AuBuchon, Marjanna Smith, Claire Starling, Karen G Ganacias, Aimee Danielson, Loral Patchen, Janine A Rethy, H Joseph Blumenthal, Angela D Thomas, Hannah Arem","doi":"10.2196/56807","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>The 42 days after delivery (\"fourth trimester\") are a high-risk period for birthing individuals and newborns, especially those who are racially and ethnically marginalized due to structural racism.</p><p><strong>Objective: </strong>To fill a gap in the critical \"fourth trimester,\" we developed 2 ruled-based chatbots-one for birthing individuals and one for newborn caregivers-that provided trusted information about postbirth warning signs and newborn care and connected patients with health care providers.</p><p><strong>Methods: </strong>A total of 4370 individuals received the newborn chatbot outreach between September 1, 2022, and December 31, 2023, and 3497 individuals received the postpartum chatbot outreach between November 16, 2022, and December 31, 2023. We conducted surveys and interviews in English and Spanish to understand the acceptability and usability of the chatbot and identify areas for improvement. We sampled from hospital discharge lists that distributed the chatbot, stratified by prenatal care location, age, type of insurance, and racial and ethnic group. We analyzed quantitative results using descriptive analyses in SPSS (IBM Corp) and qualitative results using deductive coding in Dedoose (SocioCultural Research Consultants).</p><p><strong>Results: </strong>Overall, 2748 (63%) individuals opened the newborn chatbot messaging, and 2244 (64%) individuals opened the postpartum chatbot messaging. A total of 100 patients engaged with the chatbot and provided survey feedback; of those, 40% (n=40) identified as Black, 27% (n=27) identified as Hispanic/Latina, and 18% (n=18) completed the survey in Spanish. Payer distribution was 55% (n=55) for individuals with public insurance, 39% (n=39) for those with commercial insurance, and 2% (n=2) for uninsured individuals. The majority of surveyed participants indicated that chatbot messaging was timely and easy to use (n=80, 80%) and found the reminders to schedule the newborn visit (n=59, 59%) and postpartum visit (n=66, 66%) useful. Across 23 interviews (n=14, 61% Black; n=4, 17% Hispanic/Latina; n=2, 9% in Spanish; n=11, 48% public insurance), 78% (n=18) of interviewees engaged with the chatbot. Interviewees provided positive feedback on usability and content and recommendations for improving the outreach messages.</p><p><strong>Conclusions: </strong>Chatbots are a promising strategy to reach birthing individuals and newborn caregivers with information about postpartum recovery and newborn care, but intentional outreach and engagement strategies are needed to optimize interaction. Future work should measure the chatbot's impact on health outcomes and reduce disparities.</p>","PeriodicalId":36223,"journal":{"name":"JMIR Pediatrics and Parenting","volume":"7 ","pages":"e56807"},"PeriodicalIF":2.1000,"publicationDate":"2024-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Development and Refinement of a Chatbot for Birthing Individuals and Newborn Caregivers: Mixed Methods Study.\",\"authors\":\"Jessica Nathalie Rivera Rivera, Katarina E AuBuchon, Marjanna Smith, Claire Starling, Karen G Ganacias, Aimee Danielson, Loral Patchen, Janine A Rethy, H Joseph Blumenthal, Angela D Thomas, Hannah Arem\",\"doi\":\"10.2196/56807\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>The 42 days after delivery (\\\"fourth trimester\\\") are a high-risk period for birthing individuals and newborns, especially those who are racially and ethnically marginalized due to structural racism.</p><p><strong>Objective: </strong>To fill a gap in the critical \\\"fourth trimester,\\\" we developed 2 ruled-based chatbots-one for birthing individuals and one for newborn caregivers-that provided trusted information about postbirth warning signs and newborn care and connected patients with health care providers.</p><p><strong>Methods: </strong>A total of 4370 individuals received the newborn chatbot outreach between September 1, 2022, and December 31, 2023, and 3497 individuals received the postpartum chatbot outreach between November 16, 2022, and December 31, 2023. We conducted surveys and interviews in English and Spanish to understand the acceptability and usability of the chatbot and identify areas for improvement. We sampled from hospital discharge lists that distributed the chatbot, stratified by prenatal care location, age, type of insurance, and racial and ethnic group. We analyzed quantitative results using descriptive analyses in SPSS (IBM Corp) and qualitative results using deductive coding in Dedoose (SocioCultural Research Consultants).</p><p><strong>Results: </strong>Overall, 2748 (63%) individuals opened the newborn chatbot messaging, and 2244 (64%) individuals opened the postpartum chatbot messaging. A total of 100 patients engaged with the chatbot and provided survey feedback; of those, 40% (n=40) identified as Black, 27% (n=27) identified as Hispanic/Latina, and 18% (n=18) completed the survey in Spanish. Payer distribution was 55% (n=55) for individuals with public insurance, 39% (n=39) for those with commercial insurance, and 2% (n=2) for uninsured individuals. The majority of surveyed participants indicated that chatbot messaging was timely and easy to use (n=80, 80%) and found the reminders to schedule the newborn visit (n=59, 59%) and postpartum visit (n=66, 66%) useful. Across 23 interviews (n=14, 61% Black; n=4, 17% Hispanic/Latina; n=2, 9% in Spanish; n=11, 48% public insurance), 78% (n=18) of interviewees engaged with the chatbot. Interviewees provided positive feedback on usability and content and recommendations for improving the outreach messages.</p><p><strong>Conclusions: </strong>Chatbots are a promising strategy to reach birthing individuals and newborn caregivers with information about postpartum recovery and newborn care, but intentional outreach and engagement strategies are needed to optimize interaction. Future work should measure the chatbot's impact on health outcomes and reduce disparities.</p>\",\"PeriodicalId\":36223,\"journal\":{\"name\":\"JMIR Pediatrics and Parenting\",\"volume\":\"7 \",\"pages\":\"e56807\"},\"PeriodicalIF\":2.1000,\"publicationDate\":\"2024-11-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"JMIR Pediatrics and Parenting\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2196/56807\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"PEDIATRICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"JMIR Pediatrics and Parenting","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2196/56807","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"PEDIATRICS","Score":null,"Total":0}
Development and Refinement of a Chatbot for Birthing Individuals and Newborn Caregivers: Mixed Methods Study.
Background: The 42 days after delivery ("fourth trimester") are a high-risk period for birthing individuals and newborns, especially those who are racially and ethnically marginalized due to structural racism.
Objective: To fill a gap in the critical "fourth trimester," we developed 2 ruled-based chatbots-one for birthing individuals and one for newborn caregivers-that provided trusted information about postbirth warning signs and newborn care and connected patients with health care providers.
Methods: A total of 4370 individuals received the newborn chatbot outreach between September 1, 2022, and December 31, 2023, and 3497 individuals received the postpartum chatbot outreach between November 16, 2022, and December 31, 2023. We conducted surveys and interviews in English and Spanish to understand the acceptability and usability of the chatbot and identify areas for improvement. We sampled from hospital discharge lists that distributed the chatbot, stratified by prenatal care location, age, type of insurance, and racial and ethnic group. We analyzed quantitative results using descriptive analyses in SPSS (IBM Corp) and qualitative results using deductive coding in Dedoose (SocioCultural Research Consultants).
Results: Overall, 2748 (63%) individuals opened the newborn chatbot messaging, and 2244 (64%) individuals opened the postpartum chatbot messaging. A total of 100 patients engaged with the chatbot and provided survey feedback; of those, 40% (n=40) identified as Black, 27% (n=27) identified as Hispanic/Latina, and 18% (n=18) completed the survey in Spanish. Payer distribution was 55% (n=55) for individuals with public insurance, 39% (n=39) for those with commercial insurance, and 2% (n=2) for uninsured individuals. The majority of surveyed participants indicated that chatbot messaging was timely and easy to use (n=80, 80%) and found the reminders to schedule the newborn visit (n=59, 59%) and postpartum visit (n=66, 66%) useful. Across 23 interviews (n=14, 61% Black; n=4, 17% Hispanic/Latina; n=2, 9% in Spanish; n=11, 48% public insurance), 78% (n=18) of interviewees engaged with the chatbot. Interviewees provided positive feedback on usability and content and recommendations for improving the outreach messages.
Conclusions: Chatbots are a promising strategy to reach birthing individuals and newborn caregivers with information about postpartum recovery and newborn care, but intentional outreach and engagement strategies are needed to optimize interaction. Future work should measure the chatbot's impact on health outcomes and reduce disparities.