The development of social media as an important source of information for patients and clinical practitioners is changing the way scientific findings are presented and consumed both in traditional and social media. Spin, overstatements and misleading headlines is not an uncommon way to attract a larger audience size and increase the revenue from advertising.

Haber et al. (1) performed a systematic review of the 50 most shared academic peer-reviewed articles that associated an exposure with a health outcome during 2015 on Facebook and Twitter and the media articles covering them.

Of the 50 academic studies and the related 68 media articles, 34% of the academic studies and 48% of the media articles overstated the empirical support of the presented findings. Of the academic articles, 70% were considered having low or very low strength of causal inference and only 6% were considered to have high strength. Of the media articles, 58% included an inaccurate description of the research question, results, intervention, or population of the academic study.

The authors conclude that there is a large disparity between the strength of language and the underlying strength of causal inference among the studies most shared on social media, but that more research is needed to clarify how academic institutions, media organisations, and social network sharing patterns impact causal inference and language as received by the research consumer.


  1. Haber N, Smith ER, Moscoe E, et al. Causal language and strength of inference in academic and media articles shared in social media (CLAIMS): A systematic review. PLOS ONE 2018; 13(5):e0196346.