Breast cancer on social media: a quali-quantitative study on the credibility and content type of the most shared news stories

Abstract Background Female breast cancer was the most diagnosed cancer in 2020, with more than two million new cases worldwide. Access to scientifically correct information can assist patients in early detection or prevention of the disease. However, misinformation on social networking sites (SNSs) about breast cancer can be propagated rapidly, posing a threat to health communication efforts. The aim of this study is to analyse the characteristics of the most shared news stories referencing the disease that circulated on SNSs, including the credibility of this content. Methods This is an exploratory quali-quantitative study. Data collection was conducted between June 2019 and June 2020. We performed statistical and content analysis of the stories that had at least 1,000 total shares. Each story was classified in accordance to the following aspects: credibility; type of rumour; source; content type; mentions prevention or early detection/screening exams. Results The abundance of news stories in our sample (n = 1,594) were not classified according to their credibility, as they do not address science, risk factors, prevention, treatment, or other aspects which can be assessed for scientific accuracy. However, content classified as “rumours” are 3.29 times more shared than those considered scientifically correct. Regarding content type, most stories are classified as ‘real-life story’ or ‘solidarity’ (67.69%). In our sample, 5.08% of the total comment on prevention and 19.7% reference early detection. Conclusion We consider it can be a good strategy, in SNSs, to combine content of greater popularity, such as real-life stories, with subjects that can make a difference in a patient’s life, such as early detection, breast cancer symptoms and disease prevention strategies. Doctors, scientists and health journalists can expand the dialogue with the lay public regarding breast cancer, helping to counteract online misinformation.

Abstract licence: CC BY-NC-ND

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