Artificial Intelligence–Enabled Analysis of Statin-Related Topics and Sentiments on Social Media

Author:

Somani Sulaiman1,van Buchem Marieke Meija234,Sarraju Ashish5,Hernandez-Boussard Tina146,Rodriguez Fatima7

Affiliation:

1. Department of Medicine, Stanford University, Stanford, California

2. Department of Information Technology & Digital Innovation, Leiden University Medical Center (LUMC), Leiden, the Netherlands

3. CAIRELab, LUMC, Leiden, the Netherlands

4. Department of Biomedical Data Science, Stanford University, Stanford, California

5. Department of Cardiovascular Medicine, Cleveland Clinic, Cleveland, Ohio

6. Department of Surgery, Stanford University School of Medicine, Stanford, California

7. Division of Cardiovascular Medicine and Cardiovascular Institute, Stanford University, Stanford, California

Abstract

ImportanceDespite compelling evidence that statins are safe, are generally well tolerated, and reduce cardiovascular events, statins are underused even in patients with the highest risk. Social media may provide contemporary insights into public perceptions about statins.ObjectiveTo characterize and classify public perceptions about statins that were gleaned from more than a decade of statin-related discussions on Reddit, a widely used social media platform.Design, Setting, and ParticipantsThis qualitative study analyzed all statin-related discussions on the social media platform that were dated between January 1, 2009, and July 12, 2022. Statin- and cholesterol-focused communities, were identified to create a list of statin-related discussions. An artificial intelligence (AI) pipeline was developed to cluster these discussions into specific topics and overarching thematic groups. The pipeline consisted of a semisupervised natural language processing model (BERT [Bidirectional Encoder Representations from Transformers]), a dimensionality reduction technique, and a clustering algorithm. The sentiment for each discussion was labeled as positive, neutral, or negative using a pretrained BERT model.ExposuresStatin-related posts and comments containing the terms statin and cholesterol.Main Outcomes and MeasuresStatin-related topics and thematic groups.ResultsA total of 10 233 unique statin-related discussions (961 posts and 9272 comments) from 5188 unique authors were identified. The number of statin-related discussions increased by a mean (SD) of 32.9% (41.1%) per year. A total of 100 discussion topics were identified and were classified into 6 overarching thematic groups: (1) ketogenic diets, diabetes, supplements, and statins; (2) statin adverse effects; (3) statin hesitancy; (4) clinical trial appraisals; (5) pharmaceutical industry bias and statins; and (6) red yeast rice and statins. The sentiment analysis revealed that most discussions had a neutral (66.6%) or negative (30.8%) sentiment.Conclusions and RelevanceResults of this study demonstrated the potential of an AI approach to analyze large, contemporary, publicly available social media data and generate insights into public perceptions about statins. This information may help guide strategies for addressing barriers to statin use and adherence.

Publisher

American Medical Association (AMA)

Subject

General Medicine

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