Evidence map›Paper›PMID 41995996›Full record

ArticlePrevention science : the official journal of the Society for Prevention Research2026

Designing Rosie the Chatbot with and for Pregnant and New Mothers of Color:  a Community-Engaged Study Leveraging Artificial Intelligence and Prevention Science to Improve Maternal and Child Health Outcomes.

Elizabeth M Norell, Amara Channell Doig, Michelle Jasczynski, Alexis S Hunter, Francia Ximena Marin Gutierrez, Heran Mane, Sourabh Mane, Xiaohe Yue, Quynh C Nguyen

Abstract read
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In one paragraph

Article in Prevention science : the official journal of the Society for Prevention Research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Elizabeth M NorellDepartment of Behavioral and Community Health School of Public Health, University of Maryland, College Park, 4200 Valley Dr, College Park, MD, 20742, USA. aparicio@umd.edu.ORCID 0000-0001-8924-5757
Amara Channell DoigDepartment of Behavioral and Community Health School of Public Health, University of Maryland, College Park, 4200 Valley Dr, College Park, MD, 20742, USA.
Michelle JasczynskiDepartment of Behavioral and Community Health School of Public Health, University of Maryland, College Park, 4200 Valley Dr, College Park, MD, 20742, USA.
Alexis S HunterDepartment of Behavioral and Community Health School of Public Health, University of Maryland, College Park, 4200 Valley Dr, College Park, MD, 20742, USA.
Francia Ximena Marin GutierrezDepartment of Behavioral and Community Health School of Public Health, University of Maryland, College Park, 4200 Valley Dr, College Park, MD, 20742, USA.
Heran ManeDepartment of Epidemiology and Biostatistics School of Public Health, University of Maryland, College Park, 4200 Valley Dr, College Park, MD, 20742, USA.
Sourabh ManeCollege of Information, University of Maryland, College Park, 4130 Campus Dr, College Park, MD, 20742, USA.
Xiaohe YueDepartment of Epidemiology and Biostatistics School of Public Health, University of Maryland, College Park, 4200 Valley Dr, College Park, MD, 20742, USA.
Quynh C NguyenDepartment of Epidemiology and Biostatistics School of Public Health, University of Maryland, College Park, 4200 Valley Dr, College Park, MD, 20742, USA.

Funding

NIMHD NIH HHS 5R01MD016037
6 · The paper itself

Abstract

Maternal and child health is widely recognized as a marker for a healthy society. According to the Centers for Disease Control and Prevention, the US maternal mortality rates have remained high, with over 1200 maternal deaths occurring in 2021. Recognizing that systemic racism is embedded at all levels of the public health and medical fields, intervention is needed at all levels of the socio-ecological model. Developing health communication tools for pregnant women and new parents is one leverage point in the numerous changes that must occur across public health and medical fields to achieve maternal and child equity. The current study employed focus groups to inform development of an interactive question-and-answer chatbot called Rosie. Participants (n = 30) were all pregnant and new mothers of color residing in the United States. Data were collected in virtual focus groups (N = 6) and transcribed verbatim. Template analysis of focus group transcripts produced three themes in women's health information needs and preferences: (1) Pregnancy and New Parenthood Challenges, (2) Sources of Information and Support, and (3) Chatbot Design. Chatbots as a purveyor of health education information were perceived as a promising approach among our pregnant and new mothers of color participants, who had an array of needs that could be addressed by an intervention such as a chatbot. This technology has broad applicability in the health sphere and may serve as an important supplement to both clinical care and existing early childhood intervention services.

Indexed as

Artificial IntelligenceChild HealthMaternal HealthMothersAdultFemaleFocus GroupsHumansPregnancyUnited StatesAIArtificial intelligenceCommunity-engaged researchHealth disparitiesMaternal and child health

Identifiers

PMID41995996
PMCPMC13198457

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.