Evidence map›Paper›PMID 38214963›Full record

ArticleJMIR formative research2024

Rosie, a Health Education Question-and-Answer Chatbot for New Mothers: Randomized Pilot Study.

Quynh C Nguyen, Elizabeth M Aparicio, Michelle Jasczynski, Amara Channell Doig, Xiaohe Yue, Heran Mane, Neha Srikanth, Francia Ximena Marin Gutierrez, Nataly Delcid, Xin He and 1 more

Registry-linked trialOpen access · goldAbstract read
In one paragraph

Article in JMIR formative research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06053515 (Rosie the Chatbot), which is not on this map. Cited by 17 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 1 pooled it
6.1field-weighted citation impact, top 3% of its field
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.

NCT06053515 nacompletednot on this map

Rosie the Chatbot: Leveraging Automated and Personalized Health Information Communication to Reduce Disparities in Maternal and Child Health

TypeinterventionalSponsorUniversity of Maryland, College ParkRan2023 to 2026Enrolled400ConditionsPregnancy, Postpartum Depression, Infant Development, Infant ConditionsArmsRosie the Chatbot
3 · Its place in the literature

Who cites it

17 citing papers in PubMed, 1 synthesis or guideline pooled it, 14 citations in OpenAlex.

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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

11 authors at 1 institution in 1 country.

Quynh C NguyenDepartment of Epidemiology and Biostatistics, University of Maryland School of Public Health, College Park, MD, United States.ORCID https://orcid.org/0000-0003-4745-6681
Elizabeth M AparicioDepartment of Behavioral and Community Health, University of Maryland School of Public Health, College Park, MD, United States.ORCID https://orcid.org/0000-0001-8924-5757
Michelle JasczynskiDepartment of Behavioral and Community Health, University of Maryland School of Public Health, College Park, MD, United States.ORCID https://orcid.org/0000-0001-8479-6779
Amara Channell DoigDepartment of Behavioral and Community Health, University of Maryland School of Public Health, College Park, MD, United States.ORCID https://orcid.org/0000-0002-1546-3003
Xiaohe YueDepartment of Epidemiology and Biostatistics, University of Maryland School of Public Health, College Park, MD, United States.ORCID https://orcid.org/0000-0001-5922-1949
Heran ManeDepartment of Epidemiology and Biostatistics, University of Maryland School of Public Health, College Park, MD, United States.ORCID https://orcid.org/0000-0001-8859-3282
Neha SrikanthDepartment of Computer Science, University of Maryland Institute for Advanced Computer Studies, University of Maryland, College Park, MD, United States.ORCID https://orcid.org/0000-0001-7456-7470
Francia Ximena Marin GutierrezDepartment of Behavioral and Community Health, University of Maryland School of Public Health, College Park, MD, United States.ORCID https://orcid.org/0009-0008-5802-6488
Nataly DelcidDepartment of Epidemiology and Biostatistics, University of Maryland School of Public Health, College Park, MD, United States.ORCID https://orcid.org/0009-0007-8822-0137
Xin HeDepartment of Epidemiology and Biostatistics, University of Maryland School of Public Health, College Park, MD, United States.ORCID https://orcid.org/0000-0002-9814-1666
Jordan Boyd-GraberDepartment of Computer Science, University of Maryland Institute for Advanced Computer Studies, University of Maryland, College Park, MD, United States.ORCID https://orcid.org/0000-0002-7770-4431
University of Maryland, College Park · US

Funding

Rosie the Chatbot: Leveraging Automated and Personalized Health Information Communication to Reduce Disparities in Maternal and Child HealthR01MD016037 · NIMHD · UNIV OF MARYLAND, COLLEGE PARK · PI NGUYEN, THU, NORELL, ELIZABETH MARIE · 2021 to 2025
$3.3M
Neighborhood Looking Glass: 360 Degree Automated Characterization of the Built Environment for Neighborhood Effects ResearchR01LM012849 · NLM · UNIV OF MARYLAND, COLLEGE PARK · PI NGUYEN, QUYNH · 2018 to 2021
$1.3M
NIMHD NIH HHS R01 MD016037NLM NIH HHS R01 LM012849
6 · The paper itself

Abstract

backgroundStark disparities exist in maternal and child outcomes and there is a need to provide timely and accurate health information.

objectiveIn this pilot study, we assessed the feasibility and acceptability of a health chatbot for new mothers of color.

methodsRosie, a question-and-answer chatbot, was developed as a mobile app and is available to answer questions about pregnancy, parenting, and child development. From January 9, 2023, to February 9, 2023, participants were recruited using social media posts and through engagement with community organizations. Inclusion criteria included being aged ≥14 years, being a woman of color, and either being currently pregnant or having given birth within the past 6 months. Participants were randomly assigned to the Rosie treatment group (15/29, 52% received the Rosie app) or control group (14/29, 48% received a children's book each month) for 3 months. Those assigned to the treatment group could ask Rosie questions and receive an immediate response generated from Rosie's knowledgebase. Upon detection of a possible health emergency, Rosie sends emergency resources and relevant hotline information. In addition, a study staff member, who is a clinical social worker, reaches out to the participant within 24 hours to follow up. Preintervention and postintervention tests were completed to qualitatively and quantitatively evaluate Rosie and describe changes across key health outcomes, including postpartum depression and the frequency of emergency room visits. These measurements were used to inform the clinical trial's sample size calculations.

resultsOf 41 individuals who were screened and eligible, 31 (76%) enrolled and 29 (71%) were retained in the study. More than 87% (13/15) of Rosie treatment group members reported using Rosie daily (5/15, 33%) or weekly (8/15, 53%) across the 3-month study period. Most users reported that Rosie was easy to use (14/15, 93%) and provided responses quickly (13/15, 87%). The remaining issues identified included crashing of the app (8/15, 53%), and users were not satisfied with some of Rosie's answers (12/15, 80%). Mothers in both the Rosie treatment group and control group experienced a decline in depression scores from pretest to posttest periods, but the decline was statistically significant only among treatment group mothers (P=.008). In addition, a low proportion of treatment group infants had emergency room visits (1/11, 9%) compared with control group members (3/13, 23%). Nonetheless, no between-group differences reached statistical significance at P<.05.

conclusionsRosie was found to be an acceptable, feasible, and appropriate intervention for ethnic and racial minority pregnant women and mothers of infants owing to the chatbot's ability to provide a personalized, flexible tool to increase the timeliness and accessibility of high-quality health information to individuals during a period of elevated health risks for the mother and child.

trial registrationClinicalTrials.gov NCT06053515; https://clinicaltrials.gov/study/NCT06053515.

Indexed as

chatbothealth disparitieshealth equityhealth informaticshealth informationmaternal and child healthmobile phonenewborn carepatient educationpostpartum careprenatal carepreventive health care

Identifiers

PMID38214963
PMCPMC10818229
OpenAlexW4388981553

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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.