Department of Medicine, Stanford University, Stanford, California.
Department of Information Technology & Digital Innovation, Leiden University Medical Center (LUMC), Leiden, the Netherlands.
JAMA Netw Open. 2023 Apr 3;6(4):e239747. doi: 10.1001/jamanetworkopen.2023.9747.
Despite 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.
To 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 PARTICIPANTS: This 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.
Statin-related posts and comments containing the terms statin and cholesterol.
Statin-related topics and thematic groups.
A 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.
Results 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.
尽管有令人信服的证据表明他汀类药物是安全的，通常耐受性良好，并能降低心血管事件，但即使是在风险最高的患者中，他汀类药物的使用也不足。社交媒体可能提供了当代公众对他汀类药物看法的深入了解。
从 Reddit 上十多年来与他汀类药物相关的讨论中，对他汀类药物的公众看法进行描述和分类，Reddit 是一个广泛使用的社交媒体平台。
设计、设置和参与者：本定性研究分析了 2009 年 1 月 1 日至 2022 年 7 月 12 日期间在社交媒体平台上所有与他汀类药物相关的讨论。确定了他汀类药物和胆固醇相关的社区，以创建与他汀类药物相关的讨论列表。开发了一个人工智能 (AI) 管道，将这些讨论聚类为特定主题和总体主题组。该管道由一个半监督自然语言处理模型（BERT [来自 Transformers 的双向编码器表示]）、降维技术和聚类算法组成。使用预先训练的 BERT 模型为每个讨论标记情绪为积极、中性或消极。
与他汀类药物相关的帖子和评论，其中包含他汀类药物和胆固醇这两个术语。
与他汀类药物相关的主题和主题组。
共确定了 5188 名作者的 10233 个独特的与他汀类药物相关的讨论（961 个帖子和 9272 条评论）。与他汀类药物相关的讨论数量平均（SD）每年增加 32.9%（41.1%）。共确定了 100 个讨论主题，并将其分为 6 个总体主题组：（1）生酮饮食、糖尿病、补充剂和他汀类药物；（2）他汀类药物不良反应；（3）他汀类药物犹豫；（4）临床试验评估；（5）制药行业偏见和他汀类药物；（6）红曲米和他汀类药物。情感分析显示，大多数讨论的情绪为中性（66.6%）或负面（30.8%）。
本研究结果表明，人工智能方法具有分析大型、当代、公开可用的社交媒体数据并生成公众对他汀类药物看法见解的潜力。这些信息可能有助于指导解决他汀类药物使用和依从性障碍的策略。
