ArticleJAMA network open2020
Assessment of Beliefs and Attitudes About Statins Posted on Twitter: A Qualitative Study.
Article in JAMA network open, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
46 citing papers in PubMed.
- AI-Driven Topic Modeling and Sentiment Analysis of Systemic Lupus Erythematosus Discussions on Social Media: Cross-Platform Study.Journal of medical Internet research · 2026Article
- Large Language Model-Based Analysis of Statin Therapy Discussions and Sentiment on Social Media: Cross-Sectional Observational Study.Journal of medical Internet research · 2026Observational
- Exploring Pain on Social Media: Observational Study on Perceptions and Discussions of Chronic Pain Conditions.JMIR infodemiology · 2025Observational
- Article
- Analysis of User-Generated Posts on Social Media of Adjuvant Analgesics: A Machine Learning Study.International journal of medical sciences · 2025Article
- Article
- Impact of a patient-centered tool to reduce misconceptions about coronary artery disease and its treatment: The CAD roadmap.PEC innovation · 2024Article
- Mapping global public perspectives on mRNA vaccines and therapeutics.NPJ vaccines · 2024Article
- Assessment of beliefs and attitudes towards benzodiazepines using machine learning based on social media posts: an observational study.BMC psychiatry · 2024Observational
- Mpox Discourse on Twitter by Sexual Minority Men and Gender-Diverse Individuals: Infodemiological Study Using BERTopic.JMIR public health and surveillance · 2024Article
- Understanding public perceptions and discussions on diseases involving chronic pain through social media: cross-sectional infodemiology study.BMC musculoskeletal disorders · 2024Article
- Artificial Intelligence in Cardiovascular Disease Prevention: Is it Ready for Prime Time?Current atherosclerosis reports · 2024Review
- Reporting of Ethical Considerations in Qualitative Research Utilizing Social Media Data on Public Health Care: Scoping Review.Journal of medical Internet research · 2024Article
- Statin Twitter: Human and Automated Bot Contributions, 2010 to 2022.Journal of the American Heart Association · 2024Article
- Social Media Posts on Statins: What Can We Learn About Patient Experiences and Perspectives?Journal of the American Heart Association · 2024Article
- Non adherence to lipid-lowering therapy and strategies to improve adherence.Indian heart journal · 2024Review
- Contraceptive content shared on social media: an analysis of Twitter.Contraception and reproductive medicine · 2024Article
- Spatiotemporal trends in COVID-19 vaccine sentiments on a social media platform and correlations with reported vaccine coverage.Bulletin of the World Health Organization · 2024Article
- Regional insights on tobacco-related tweets: unveiling user opinions and usage patterns.Frontiers in public health · 2024Article
- Exploring Perceptions About Paracetamol, Tramadol, and Codeine on Twitter Using Machine Learning: Quantitative and Qualitative Observational Study.Journal of medical Internet research · 2023Observational
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Importance: Statins are prescribed to help lower cholesterol levels but have poor adherence rates. Attitudes or beliefs toward medications are important to ascertain because they may be associated with patient behavior. Objective: To identify health-related discussion in Twitter posts mentioning a statin and analyze the content within these posts. Design, Setting, and Participants: This qualitative study included 11 852 posts related to 1 of 8 statins (7 licensed for use in the United States and 5 licensed in the United Kingdom) collected from May 10, 2013, to August 28, 2018. Twitter posts were identified as health related or not, and if health related, whether they were posted by a statin user, someone who knows a statin user, a health care professional, or undetermined. The health-related tweets were classified by the type of information posted, such as a belief about the medication, an adverse event, a question, or a reference to the cost of the medication. Data were analyzed from January 22 to November 19, 2019. Main Outcomes and Measures: The number of posts by each user type identified and the categories identified by analyzing the content. Results: Of the 11 852 Twitter posts about statins, 5201 (43.9%) were health related. The most frequent posts provided resource information, such as a link to a journal article (1824 of 5201 [35.1%]). The second most frequent type of health-related posts included personal beliefs or attitudes toward statins (1097 of 5201 [21.1%]). Personal experiences of adverse events (353 of 5201 [6.8%]), discussions about dosage (320 of 5201 [6.2%]), and questions about statins (191 of 5201 [3.7%]) followed. Posts indicated polarized beliefs and attitudes to statins from saving lives to causing death. Some beliefs, such as the direct confirmation that the use of statins mitigates the effects of an unhealthy diet, have not been extensively highlighted as common practice in the literature. Conclusion and Relevance: This qualitative content analysis of Twitter posts about statins provides insights into beliefs about statins. Patient perspectives gathered from social media may help to inform research and improve public health messages and communication between health care professionals and patients.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.