ArticleFrontiers in physiology2022
Investigating pregnant women's health information needs during pregnancy on internet platforms.
Article in Frontiers in physiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Internet use for pregnancy-related information and its correlates among women attending antenatal care in Mogadishu, Somalia.PLOS digital health · 2026Article
- The Effect of E-Healthy Diet Literacy on Sustainable Nutrition Behaviors in Pregnant Women.Public health nutrition · 2026Article
- Comprehensiveness, quality, and readability of non-invasive prenatal testing information on Japanese medical institution websites.PEC innovation · 2026Article
- Online health information seeking preferences among pregnant women: a discrete choice experiment.Frontiers in public health · 2026Article
- Operation status, quality, and premature birth information in obstetrics and gynecology facility websites in Korea: an evaluation study.Women's health nursing (Seoul, Korea) · 2025Article
- Internet-based pregnancy information seeking in Lebanon: a cross-sectional study.BMC pregnancy and childbirth · 2025Article
- Folic Acid Mitigates Sertraline-Induced Liver Damage in Adult Female Albino Rats During Pregnancy and Postpartum: A Biochemical and Histological Study.Medicina (Kaunas, Lithuania) · 2025Article
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial intelligence gives pregnant women another avenue for receiving healthcare information. With the advancement of information and communication technology, searching online for pregnancy information has become commonplace during COVID-19. This study aimed to explore pregnant women's information-seeking behavior based on data mining and text analysis in China. Posts on maternal and infant-related websites were collected during 1 June 2020, and 31 January 2021. A total of 5,53,117 valid posts were obtained. Based on the data, we performed correlation analysis, topic analysis, and sentiment analysis. The correlation analysis showed the positive effects of population, population with a college education or above, and GDP on post counts. The topic analysis extracted six, nineteen, eighteen, thirteen, eleven, sixteen, thirteen, sixteen, nineteen, and fourteen topics in different months of pregnancy, reflecting different information needs in various pregnancy periods. The results of sentiment analysis show that a peak of the posts emerged in the second month of pregnancy and the proportion of emotionally positive posts reached its peak in the sixth month of pregnancy. The study provides important insights for understanding pregnant women's information-seeking behavior.
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Registered trials
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