JMIR Res Protoc. 2020 Aug 26;9(8):e15623. doi: 10.2196/15623.
Insights From Twitter Conversations on Lupus and Reproductive Health: Protocol for a Content Analysis.
JMIR research protocols
Oleg Stens, Michael H Weisman, Julia Simard, Katja Reuter
Affiliations
Affiliations
- Department of Internal Medicine, Harbor-UCLA Medical Center, Torrance, CA, United States.
- David Geffen School of Medicine at UCLA, Los Angeles, CA, United States.
- Division of Epidemiology, Department of Health Research and Policy, Stanford University, Palo Alto, CA, United States.
- Institute for Health Promotion and Disease Prevention Research, Department of Preventive Medicine, Keck School of Medicine of USC, Los Angeles, CA, United States.
- Southern California Clinical and Translational Science Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, United States.
PMID: 32844753
PMCID: PMC7481870 DOI: 10.2196/15623
Abstract
BACKGROUND: Systemic lupus erythematosus (SLE) is the most common form of lupus. It is a chronic autoimmune disease that predominantly affects women of reproductive age, impacting contraception, fertility, and pregnancy. Although clinic-based studies have contributed to an increased understanding of reproductive health care needs of patients with SLE, misinformation abounds and perspectives on reproductive health issues among patients with lupus remain poorly understood. Social networks such as Twitter may serve as a data source for exploring how lupus patients communicate about their health issues, thus adding a dimension to enrich our understanding of communication regarding reproductive health in this unique patient population.
OBJECTIVE: The objective of this study is to conduct a content analysis of Twitter data published by users in English in the United States from September 1, 2017, to October 31, 2018, in order to examine people's perspectives on reproductive health among patients with lupus.
METHODS: This study will analyze user-generated posts that include keywords related to lupus and reproductive health from Twitter. To access public Twitter user data, we will use Symplur Signals, a health care social media analytics platform. Text classifiers will be used to identify topics in posts. Posts will be classified manually into the a priori and emergent categories. Based on the information available in a user's Twitter profile (ie, username, description, and profile image), we will further attempt to characterize the user who generated the post. We will use descriptive statistics to analyze the data and identify the most prevalent topics in the Twitter content among patients with lupus.
RESULTS: This study has been funded by the National Center for Advancing Translational Science (NCATS) through their Clinical and Translational Science Awards program. The Institutional Review Board at the University of Southern California approved the study (HS-18-00912). Data extraction and cleaning are complete. We obtained 47,715 Twitter posts containing terms related to "lupus" from users in the United States, published in English between September 1, 2017, and October 31, 2018. We will include 40,885 posts in the analysis, which will be completed in fall 2020. This study was supported by funds from the has been funded by the National Center for Advancing Translational Science (NCATS) through their Clinical and Translational Science Awards program.
CONCLUSIONS: The findings from this study will provide pilot data on the use of Twitter among patients with lupus. Our findings will shed light on whether Twitter is a promising data source for learning about reproductive health issues expressed among patients with lupus. The data will also help to determine whether Twitter can serve as a potential outreach platform for raising awareness of lupus and reproductive health and for implementing relevant health interventions.
INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/15623.
©Oleg Stens, Michael H Weisman, Julia Simard, Katja Reuter. Originally published in JMIR Research Protocols (http://www.researchprotocols.org), 26.08.2020.
Keywords: Twitter; fertility; infodemiology; infoveillance; listening; lupus; monitoring; patient opinion; reproductive health; social media; social network; surveillance
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