ArticleDigital health
Breast cancer prevention and treatment misinformation on Twitter: An analysis of two languages.
Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Investigating Online Discussions About Cancer Screening on Twitter (Subsequently Rebranded as X): Corpus Analysis.JMIR infodemiology · 2026Article
- Online Health Misinformation Susceptibility Increases Health Risk Behaviors and Vaccine Hesitancy: Evidence from Greece.Healthcare (Basel, Switzerland) · 2026Article
- Expert and Patient Evaluation of an Education Tool for Breast Cancer Patients on Endocrine Therapy: Assessment of Usability, Knowledge and Medication Beliefs.Journal of cancer education : the official journal of the American Association for Cancer Education · 2026Article
- Identifying Misinformation About Unproven Cancer Treatments on Social Media Using User-Friendly Linguistic Characteristics: Content Analysis.JMIR infodemiology · 2025Article
- Selling Misleading "Cancer Cure" Books on Amazon: Systematic Search on Amazon.com and Thematic Analysis.Journal of medical Internet research · 2024Article
- Results of the Italian cross-sectional web-based survey "Nutrition and breast cancer, what would you like to know?" An attempt to collect and respond to patients' information needs, through social media.Frontiers in oncology · 2024Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: To determine the prevalence and types of misinformation on Twitter related to breast cancer prevention and treatment; and compare the differences between the misinformation in English and Malay tweets. Methods: A total of 6221 tweets related to breast cancer posted between 2018 and 2022 were collected. An oncologist and two pharmacists coded the tweets to differentiate between true information and misinformation, and to analyse the misinformation content. Binary logistic regression was conducted to identify determinants of misinformation. Results: There were 780 tweets related to breast cancer prevention and treatment, and 456 (58.5%) contain misinformation, with significantly more misinformation in Malay compared to English tweets (OR = 6.18, 95% CI: 3.45-11.07, Conclusion: Misinformation on breast cancer prevention and treatment is prevalent on social media, with significantly more misinformation in Malay compared to English tweets. Our results highlighted that patients need to be educated on digital health literacy, with emphasis on utilising reliable sources of information and being cautious of any promotional materials that may contain misleading information. More studies need to be conducted in other languages to address the disparity in misinformation.
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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.