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Treffer: Information Needs for Artificial Intelligence Chatbot on Prenatal Care Among Women of Advanced Maternal Age: A Thematic Analysis.

Title:
Information Needs for Artificial Intelligence Chatbot on Prenatal Care Among Women of Advanced Maternal Age: A Thematic Analysis.
Authors:
Bang U; Kongju National University, Gongju, South Korea., Kim HK; Kongju National University, Gongju, South Korea., Jeong GH; Hallym University, Chuncheon, South Korea.
Source:
Nursing open [Nurs Open] 2026 Feb; Vol. 13 (2), pp. e70454.
Publication Type:
Journal Article
Language:
English
Journal Info:
Publisher: John Wiley & Sons, Inc Country of Publication: United States NLM ID: 101675107 Publication Model: Print Cited Medium: Internet ISSN: 2054-1058 (Electronic) Linking ISSN: 20541058 NLM ISO Abbreviation: Nurs Open Subsets: MEDLINE
Imprint Name(s):
Original Publication: [Hoboken, NJ] : John Wiley & Sons, Inc., [2014]-
MeSH Terms:
Prenatal Care*/methods , Prenatal Care*/standards , Artificial Intelligence*/standards , Artificial Intelligence*/trends , Pregnant People*/psychology , Maternal Age* , Needs Assessment*, Interviews as Topic/methods ; Humans ; Female ; Pregnancy ; Adult ; Qualitative Research ; Middle Aged ; Advanced Maternal Age ; Generative Artificial Intelligence
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Grant Information:
RS-2023-00239284 National Research Foundation
Contributed Indexing:
Keywords: advanced maternal age; artificial intelligence; need assessment; prenatal care; qualitative study
Entry Date(s):
Date Created: 20260212 Date Completed: 20260212 Latest Revision: 20260215
Update Code:
20260215
PubMed Central ID:
PMC12895358
DOI:
10.1002/nop2.70454
PMID:
41676898
Database:
MEDLINE

Weitere Informationen

Aim: This study aimed to investigate the information needs for artificial intelligence chatbot-based interventions on prenatal care among pregnant women of advanced maternal age.
Design: This study employed a qualitative research method using thematic analysis.
Methods: Participants were pregnant women of advanced maternal age aged 35 and older who attended childbirth classes or used midwifery services in three cities. Participants were recruited through purposive sampling from September 23, 2023, to February 24, 2024, until saturation was reached. Semi-structured interviews were conducted with a total of 13 participants. The analysis was conducted in accordance with Braun and Clarke's six phases of thematic analysis: familiarisation with the data, generating initial codes, searching for themes, reviewing themes, defining and naming themes, and producing the report.
Results: Four central themes were identified that described prenatal care information needs for AI chatbots, as follows: (1) Information needs for an AI chatbot supporting advanced maternal age pregnancy; (2) childcare; (3) postpartum recovery; and (4) breastfeeding promotion.
Conclusion: These findings highlight the importance of developing an accessible, interactive, and empathetic AI chatbot-based prenatal care application that can provide reliable information and support to improve maternal and fetal health among women of advanced maternal age.
Implications for the Profession And/or Patient Care: The themes identified in this study offer concrete guidance for developing an AI chatbot that delivers relevant support for postpartum recovery, breastfeeding, newborn emergencies, and child health management among pregnant women of advanced maternal age.
Reporting Method: The study follows the Consolidated Criteria for Reporting Qualitative Research (COREQ) guidelines.
Patient or Public Contribution: No patient or public contribution.
(© 2026 The Author(s). Nursing Open published by John Wiley & Sons Ltd.)