Large Language Model–Based Analysis of Statin Therapy Discussions and Sentiment on Social Media: Cross-Sectional Observational Study

Анализ обсуждений статиновой терапии и тональности высказываний в социальных сетях с использованием больших языковых моделей: поперечное наблюдательное исследование
Siru Liu, Jialin Liu
2026-04-10

Reddit discussionslarge language modelsmedication adherencesentiment analysisstatin therapy
Background: Statin therapy, despite proven cardiovascular benefits, remains underused. Social media platforms may capture patient perspectives that are less visible in clinical encounters. Objective: This study aimed to characterize themes, sentiment, and decision-making factors related to statin therapy through large language model (LLM)-based analysis of Reddit discussions. Methods: This cross-sectional observational study analyzed English-language Reddit posts and comments mentioning statins from January 2022 to May 2025, identified via keyword-based Reddit application programming interface searches (≤1000 posts per keyword). A total of 5328 retrieved discussions (n=1661, 31.2% posts and n=3667, 68.8% keyword-containing comments) from public subreddits were included. Themes, sentiments (positive, neutral, or negative), guideline-informed clinical relevance, information-seeking behavior, adverse effect mentions, decision factors, and adherence-related content were extracted using an LLM-based pipeline. Results: Among 5328 discussions, prominent topics included adverse effects (n=1697, 31.9%), decision-making references related to laboratory results and physician advice (n=2767, 51.9% and n=2034, 38.2%, respectively), and alternative approaches (n=2485, 46.6%). Overall sentiment was neutral in 34% (n=1812) of discussions, negative in 30.9% (n=1646), and positive in 16.9% (n=900); the remainder were mixed or unclear. Statin-directed sentiment was neutral in 44.1% (n=2350) of discussions, negative in 25.2% (n=1343), and positive in 12.5% (n=666); the remainder did not express statin-directed sentiment. High clinical relevance was identified in 12.6% (n=672) of discussions. Adherence-related issues were mentioned in 29.8% (n=1587) of discussions. Among adverse effect mentions, muscle pain (n=129, 7.6%) and fatigue (n=110, 6.5%) were common. Conclusions: LLM-enabled analysis of Reddit discourse highlights substantial negative sentiment, adherence-related concerns, and adverse effect narratives surrounding statin therapy. These findings suggest opportunities for patient-centered communication and shared decision-making strategies that address symptom attribution, uncertainty, and information needs in digital information environments.
1
Adherence-related concerns appeared in 29.8% of discussions; muscle pain and fatigue were common reported adverse effects, occurring in 7.6% and 6.5% of adverse-effect mentions, respectively.
2
Adverse effects were discussed in 31.9% of discussions, while laboratory results and physician advice influenced decision-making in 51.9% and 38.2%, respectively.
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Alternative approaches to statin therapy were mentioned in 46.6% of discussions, indicating substantial interest in nonstatin strategies.
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An LLM-based pipeline analyzed 5,328 English-language Reddit discussions about statins posted between January 2022 and May 2025.
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Only 12.6% of discussions were classified as having high clinical relevance, highlighting limits in the clinical applicability of social-media discourse.
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Overall sentiment was neutral in 34.0% of discussions and negative in 30.9%, whereas statin-directed sentiment was negative in 25.2% and positive in 12.5%.

English-language Reddit discussions about statin therapy

Themes, sentiment, decision-making factors, adverse-effect concerns, clinical relevance, information-seeking, and adherence-related content surrounding statin therapy

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2026-04-10
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Siru Liu
Jialin Liu
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