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The effect of artificial intelligence-empowered mobile health on psychological distress in women following abortion

Protocol for a mixed-methods study

Bibliographic Data

ID15528447
AuthorsWei Zhang (0000-0002-5458-9581, Inner Mongolia Maternal and Child Health), Yuqi Yang (0009-0006-6571-345X, Henan University of Science and Technology), Meimei Liu (0000-0003-1440-4754, Inner Mongolia Maternal and Child Health), Lirong Wang (0000-0002-9092-6282, Inner Mongolia Maternal and Child Health), Qing Lei (0000-0002-6679-1752, Inner Mongolia Maternal and Child Health), Qiumei Zhang (0000-0002-5343-828X, Inner Mongolia Maternal and Child Health), Jing Wang (0000-0002-7594-8539, Peking University), Hui Li (0000-0001-9355-1116, Shandong Provincial Hospital, corresponding author), Gumula Wuri (Inner Mongolia Maternal and Child Health, corresponding author)
Year2025
Volume16
Pages1665500-1665500
Publication date2025-11-18
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueFrontiers in Psychiatry (JOURNAL)
Journal identifiersISSN: 1664-0640 • E-ISSN: 1664-0640
PublisherFrontiers Media (PUBLISHER • CH)
DOI10.3389/fpsyt.2025.1665500
PMID41473756
OpenAlexW4417327854
LanguageEN
References cited46

This study pioneers an Artificial Intelligence-Empowered Mobile Health guided by Swanson's Theory of Caring, providing continuous post-abortion support to reduce psychological distress. It applies Large Language Models to Artificial Intelligence-Empowered Mobile Health for women experienced abortion, delivering timely, specialized care. This approach overcomes traditional barriers: offering real-time interaction, breaking spatiotemporal limits, lowering costs, and integrating expert knowledge to mitigate regional resource disparities, and also promoting health equity

Distress · Mental health · mHealth · Protocol (science · Psychological distress · Psychological health · Resource (disambiguation · Grief, Bereavement, and Mental Health · Mobile Health and mHealth Applications · Reproductive Health and Contraception

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