Endometriosis Online Communities: A Quantitative Analysis

Federica Bologna, Rosamond Thalken, Kristen Pepin, Matthew Wilkens
In: medRxiv · 2024 · doi:10.1101/2024.02.27.24303445 · W4392281236
preprint OA: green CC0
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⚙ AI-generated summary by claude@2026-06, 2026-06-06 ⓘ

This study used topic modeling and machine learning to analyze two online endometriosis communities, finding users discuss symptoms, appointments, and seek empathy while seeking experiential knowledge and emotional connections.

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⚙ AI-generated deep summary by claude@2026-06, 2026-06-06 ⓘ

This paper analyzes two endometriosis online health communities, r/Endo and r/endometriosis, using topic modeling and supervised machine learning to link post subject matter (“topics”) and mentioned roles/relationships (“personas”) with the type of support sought (“intent”). Posts most often discussed medical stories, medical appointments, sharing symptoms, menstruation, and empathy; notably, in posts about medical appointments, users were more likely to mention the online communities than medical professionals, and medical professionals were the least likely persona associated with empathy. The authors also found that posts mentioning partner or family focused on life issues, especially fertility, and that users sought experiential treatment and healthcare process knowledge alongside venting and emotional connection. The paper’s major limitation is that it is based on content posted in these specific communities rather than a representative sample of all endometriosis patients. This paper is centrally about endometriosis — it quantitatively characterizes what people discuss and what kinds of support they seek in endometriosis online communities.

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Abstract

Abstract Background Endometriosis is a chronic condition that affects 10% of people with a uterus. Due to the complex social and psychological impacts caused by the condition, people with endometriosis often turn to online health communities (OHCs) for support. Objective Prior work identifies a lack of large-scale analyses of endometriosis patient experiences and of OHCs. Our study fills this gap by investigating aspects of the condition and aggregate user needs that emerge from two endometriosis OHCs, r/Endo and r/endometriosis . Methods We leverage topic modeling and supervised machine learning to identify associations between a post’s subject matter (“topics”), the people and relationships (“personas”) mentioned, and the type of support the post seeks (“intent”). Results The most discussed topics in posts are medical stories, medical appointments, sharing symptoms, menstruation , and empathy . In addition, when discussing medical appointments , users are more likely to mention the endometriosis OHCs than medical professionals . Furthermore, medical professional is the least likely of any persona to be associated with empathy . Posts that mention partner or family are likely to discuss topics from the life issues category, in particular fertility . Lastly, we find that while users seek experiential knowledge regarding treatments and healthcare processes, they also wish to vent and to establish emotional connections about the life-altering aspects of the condition. Conclusions Endometriosis OHCs provide members a space where they can discuss care pathways, learn to manage symptoms, and receive validation. Our results emphasize the need for greater empathy within clinical settings, easier access to appointments, more information on care pathways, and further support for patient loved ones. In addition, this study demonstrates the value of quantitative analyses of OHCs: they can support and extend findings from small-scale studies about patient experiences and provide insight into hard-to-reach groups. Lastly, analyses of OHCs can help design interventions to improve care, as argued in previous studies.

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Condition tags

endometriosis

Citation neighborhood

Papers in the corpus that this work cites (lower rings, blue) and that cite this one (upper rings, green). Dot size scales with the paper's in-corpus citation count — bigger dot = more influential within the endo/adeno field. Click a dot to open that paper. [ expand to 2 hops ] — adds papers reached through this work's immediate citers/citees. Heavier; up to 60 extra dots.

References (68)

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