Accepted for/Published in: Journal of Medical Internet Research
Date Submitted: Dec 16, 2024
Date Accepted: Mar 28, 2025
Patient Voices in Dialysis Care: A Sentiment Analysis and Topic Modeling Study of Social Media Discourse
ABSTRACT
Background:
End-stage kidney disease (ESKD) patients undergoing dialysis face significant physical, psychological, and social challenges that impact their quality of life. Social media platforms like X.com (formerly Twitter) have become important outlets for these patients to share experiences and exchange information.
Objective:
This study aimed to uncover key themes, emotions, and challenges expressed by the dialysis community on X.com over an 18-year period from April 2006 to August 2024 by leveraging natural language processing techniques, specifically sentiment analysis and topic modeling.
Methods:
Sentiment analysis using the VADER model classified the emotional tone of 7,543 dialysis-related posts. Latent Dirichlet Allocation (LDA) topic modeling was applied to 4,059 posts to discover latent semantic themes. Sentiment distribution across the identified topics was analyzed. An in-depth thematic analysis, supported by representative patient quotes, provided rich insights into the lived experiences of dialysis patients.
Results:
Sentiment analysis revealed 49.2% positive, 26.2% negative, and 24.7% neutral sentiment posts. LDA identified 8 key themes: medical procedures and outcomes, daily life impact, risks and complications, patient education and support, healthcare access and costs, symptoms and side effects, patient experiences and socioeconomic challenges, and diet and fluid management. Negative sentiment was high for daily life impact, while education and support skewed more positive. The thematic analysis highlighted the multidimensional nature of life on dialysis.
Conclusions:
This study provides a comprehensive, data-driven understanding of the complex lived experiences of dialysis patients shared on social media over an 18-year period. The findings underscore the need for more holistic, patient-centered care models and policies that address the multidimensional challenges illuminated by patients' voices. Social media data offers valuable insights for improving dialysis care and patient support.
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