ArticleJMIR pediatrics and parenting2024
Development and Refinement of a Chatbot for Birthing Individuals and Newborn Caregivers: Mixed Methods Study.
Article in JMIR pediatrics and parenting, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- SurgiGuide: enhancing perioperative patient education with a rule-based digital agent in elective colorectal surgery.Journal of anesthesia, analgesia and critical care · 2026Article
- Increasing Use of a Postpartum and Newborn Chatbot among Birthing Individuals and Caregivers: Development and Implementation Study.JMIR pediatrics and parenting · 2026Article
- Clinician and patient perspectives on digital technology platforms for healthcare delivery.Frontiers in digital health · 2026Article
- Designing conversational intelligence: effect of large language models (GPT-driven) platforms for precision maternal and newborn health engagement: a systematic review.Oxford open digital health · 2026Review
- Toward a National Health Digital and Data Architecture: Laying the Foundation for Digital Transformation: Commission on Investment Imperatives for a Healthy Nation.NAM perspectives · 2026Review
Corrections and comments
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Authors and funding
11 authors.
Funding
Abstract
backgroundThe 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.
objectiveTo 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.
methodsA 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).
resultsOverall, 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.
conclusionsChatbots 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.
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