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User Guide for the Social Media Medical Literature Series (Part 1): How to Interpret Health Information Available on Platforms



This series contains two articles about health information on social media platforms. This is the first article in which we present a framework for clinicians to evaluate and interpret data directly derived from these platforms. The second article provides a framework for clinicians to evaluate and interpret studies that have used such data.1

Social media and network websites, commonly referred to as Web V.2.0, were first introduced in 2004 and have since gained prominence in contemporary culture. In 2017, about 70% of Americans used social media platforms to communicate – up from 5% in 2005.2 Over 40% of health care consumers use social media platforms for health information, and around 90% of consumers in the 18-24 age group believe that health information is disseminated through social media.2 The use of social media for health topics includes blogging, microblogging, social networks, professional networks, video / audio media, collaborative projects, virtual games and social worlds. The challenge has therefore evolved from finding information to assessing its credibility and relevance. There is a significant risk of disseminating misleading information that could affect patient awareness, adherence, and medical care.3-7

When social media information influences the beliefs and actions of patients in healthcare, clinicians must grapple with the consequences. Clinicians therefore need a framework to aid in the interpretation of data on these platforms as well as the studies that analyze them. To develop this framework, we used previously validated tools, including the Health on the Net (HON) Code of Conduct8th; DISCERN criteria9; Journal of the American Medical Association benchmark criteria10; and the Minervations validation tool for health websites (Randomized Evaluation of COVID-19 Therapy (LIDA) tool).11th These instruments have been identified as the most widely used instruments.12-14

Clinical scenario

A doctor discussing the COVID-19 vaccine with an elderly patient with multiple comorbidities finds that the patient …


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