Medical Mistrust in Online Endometriosis and Menopause Communities: A Comparative Analysis [ID 3948]

In: Obstetrics & Gynecology · 2026 · vol. 147(5S) , pp. 12S · doi:10.1097/aog.0000000000006265.29 · W7160027629
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Abstract

INTRODUCTION: Endometriosis and menopause are conditions where patients report barriers or unmet needs, often going online to seek support or express mistrust. Medical mistrust limits effective patient engagement. We analyzed women's health Reddit e-communities to assess mistrust patterns. METHODS: Using the Python Reddit API Wrapper (PRAW), we collected the 1,000 most recent posts from Endometriosis and Menopause subreddits. A subset of 200 posts per condition was reviewed independently by two coders drawn from a trained reviewer pool. Posts were labeled for Medical Mistrust using a framework adapted from the Group-Based Medical Mistrust Scale, with discrepancies reconciled by consensus. Interrater reliability was assessed with percent agreement and Cohen’s kappa (κ). A chi-squared test compared the prevalence between conditions. VADER sentiment analysis characterized the overall tone. RESULTS: In reconciled coding, 16.8% of endometriosis posts (35/208) and 7.8% of menopause posts (16/205) expressed mistrust (χ 2 =6.95, P =.008). Endometriosis posts were more than twice as likely to contain mistrust compared with menopause posts (odds ratio 2.39). Interrater reliability was moderate for endometriosis (κ=0.54) and substantial for menopause (κ=0.78). Sentiment analysis showed endometriosis posts were negative (−0.294) while menopause posts were neutral to mildly positive (+0.076). CONCLUSIONS/IMPLICATIONS: Endometriosis communities expressed mistrust more frequently and with lower reviewer concordance, suggesting greater complexity in how mistrust is communicated. These differences underscore the need for condition-specific education and engagement strategies in women’s health. Future research could explore thematic analysis or a better understanding of condition-specific mistrust. This could enable the development and testing of tailored interventions for health education, patient engagement, and e-community moderation strategies.
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Introduction

Endometriosis and menopause are conditions where patients report barriers or unmet needs, often going online to seek support or express mistrust. Medical mistrust limits effective patient engagement. We analyzed women's health Reddit e-communities to assess mistrust patterns.

Methods

Using the Python Reddit API Wrapper (PRAW), we collected the 1,000 most recent posts from Endometriosis and Menopause subreddits. A subset of 200 posts per condition was reviewed independently by two coders drawn from a trained reviewer pool. Posts were labeled for Medical Mistrust using a framework adapted from the Group-Based Medical Mistrust Scale, with discrepancies reconciled by consensus. Interrater reliability was assessed with percent agreement and Cohen’s kappa (κ). A chi-squared test compared the prevalence between conditions. VADER sentiment analysis characterized the overall tone.

Results

In reconciled coding, 16.8% of endometriosis posts (35/208) and 7.8% of menopause posts (16/205) expressed mistrust (χ2=6.95, P=.008). Endometriosis posts were more than twice as likely to contain mistrust compared with menopause posts (odds ratio 2.39). Interrater reliability was moderate for endometriosis (κ=0.54) and substantial for menopause (κ=0.78). Sentiment analysis showed endometriosis posts were negative (−0.294) while menopause posts were neutral to mildly positive (+0.076). CONCLUSIONS/IMPLICATIONS: Endometriosis communities expressed mistrust more frequently and with lower reviewer concordance, suggesting greater complexity in how mistrust is communicated. These differences underscore the need for condition-specific education and engagement strategies in women’s health. Future research could explore thematic analysis or a better understanding of condition-specific mistrust. This could enable the development and testing of tailored interventions for health education, patient engagement, and e-community moderation strategies.

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