Pregnancy and health in the age of the Internet: A content analysis of online 'birth club' forums

Autor: Rebekah Choi, Holly W. Cummings, Graciela Gonzalez-Hernandez, Karen O'Connor, Anahita Davoudi, Anna Wexler, Davy Weissenbacher
Jazyk: angličtina
Rok vydání: 2020
Předmět:
Health Information Exchange
Maternal Health
Emotions
Social Sciences
Peer support
Miscarriage
Machine Learning
Labor and Delivery
Database and Informatics Methods
0302 clinical medicine
Pregnancy
Health care
Medicine and Health Sciences
Psychology
030212 general & internal medicine
Misinformation
Computer Networks
030219 obstetrics & reproductive medicine
Multidisciplinary
Obstetrics and Gynecology
Information Retrieval
Medicine
Female
Club
Research Article
Computer and Information Sciences
medicine.medical_specialty
Science
Research and Analysis Methods
Peer Group
03 medical and health sciences
medicine
Humans
Internet
business.industry
Public health
Parturition
Biology and Life Sciences
Social Support
medicine.disease
Pregnancy Complications
Abortion
Spontaneous
Family medicine
Birth
Women's Health
Pregnant Women
business
Postpartum period
Zdroj: PLoS ONE, Vol 15, Iss 4, p e0230947 (2020)
PLoS ONE
ISSN: 1932-6203
Popis: Background Although studies report that more than 90% of pregnant women utilize digital sources to supplement their maternal healthcare, little is known about the kinds of information that women seek from their peers during pregnancy. To date, most research has used self-report measures to elucidate how and why women to turn to digital sources during pregnancy. However, given that these measures may differ from actual utilization of online health information, it is important to analyze the online content pregnant women generate. Objective To apply machine learning methods to analyze online pregnancy forums, to better understand how women seek information from a community of online peers during pregnancy. Methods Data from seven WhatToExpect.com “birth club” forums (September 2018; January-June 2018) were scraped. Forum posts were collected for a one-year period, which included three trimesters and three months postpartum. Only initial posts from each thread were analyzed (n = 262,238). Automatic natural language processing (NLP) methods captured 50 discussed topics, which were annotated by two independent coders and grouped categorically. Results The largest topic categories were maternal health (45%), baby-related topics (29%), and people/relationships (10%). While pain was a popular topic all throughout pregnancy, individual topics that were dominant by trimester included miscarriage (first trimester), labor (third trimester), and baby sleeping routine (postpartum period). Conclusion More than just emotional or peer support, pregnant women turn to online forums to discuss their health. Dominant topics, such as labor and miscarriage, suggest unmet informational needs in these domains. With misinformation becoming a growing public health concern, more attention must be directed toward peer-exchange outlets.
Databáze: OpenAIRE
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