| Background | Aim | Methods | Comparative Data | Expected Outcomes |
In recent years, do-it-yourself (DIY) medical movements and direct-to-consumer (DTC) health technologies have made information, products and services available to the public that were previously sequestered in the “ivory tower” of science and medicine. Internet forums and social media groups have facilitated the rise of online patient communities, where scientific and medical information is shared outside of the physician’s office. In this new paradigm, the doctor is just one voice in a competing marketplace of expertise.
While previous studies have examined online communities related to various diseases, there has been little research on online pregnancy forums—despite the fact that pregnant women are increasingly turning to technology to supplement maternal healthcare. To date, most studies of digital health in pregnancy have used self-report measures such as surveys to assess whether and why women turn to online health information. In these studies, women report finding digital health information about pregnancy to be immediate, reassuring, detailed, and entertaining; they also value how it offers a variety of perspectives on their health issues, effectively providing access to dozens of second opinions.
Although online pregnancy forums are rapidly growing in popularity—for example, the WhatToExpect.com forum for women due August 2018 contains approximately 600,000 posts, as compared to 150,000 posts for the August 2016 forum—there has been little analyses of their content. These forums, which operate as self-contained communities that provide peer-to-peer counsel and social support, provide a unique window into online health discussions amongst pregnant women. By analyzing these publicly available data, we hope to better understand expectant mothers’ health concerns and identify issues that are not being raised in the clinical care setting but are instead being discussed online.
The goal of this study is to explore the health content of online pregnancy forums on the WhattoExpect.com online birth club forums using a topic modeling approach, and to compare this data to the typical symptoms that women experience by month, as outlined by the American College of Obstetricians and Gynecologists (ACOG).
We will identify usable, health-related posts on the WhattoExpect.com site that meet data structure requirements to form a compiled database. We will analyze the content of the online pregnancy forums using topic modeling to gain a better understanding of what pregnant women are discussing, by trimester. Using comparative data from patient-oriented literature published by ACOG, we will explore differences that exist between online discussion topics and typical symptoms that women experience by trimester.
These results of the topic modelling will be initially compared to data published by ACOG, which is the leading professional association for maternal healthcare providers in the United States. ACOG publishes patient-facing literature, including a book entitled “Your Pregnancy and Childbirth: Month to Month” (Revised Sixth Edition, 2016) which outlines common symptoms by month as well as expectations for prenatal care visits. If, after the initial analyses, we deem it necessary to obtain additional comparative data, we can (a) survey obstetricians, to obtain a measure of their perceptions of the most common symptoms by trimester; or (b) conduct observations and surveys amongst patients, to understand both their common symptoms as well as their Internet use throughout pregnancy.
This study will illuminate how non-traditional data sources such as online pregnancy forums are transforming the patient-physician relationship in the realm of obstetrics. The results will identify any unmet needs for patients as they obtain OB care, to improve patient satisfaction during pregnancy visits, and to elucidate ways in which the patient-physician relationship within obstetrics has evolved in the digital age. Our findings will ultimately benefit approximately 5 million U.S. women who are pregnant at any given time, by better aligning expectations of healthcare providers and patients in the future.