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General medicine
Users' Guides to the Medical Literature series on social media (part 1): how to interpret healthcare information available on platforms
  1. Ryan S D'Souza1,
  2. Lubna Daraz2,
  3. W. Michael Hooten1,
  4. Gordon Guyatt3,
  5. Mohammad Hassan Murad4
  1. 1 Department of Anesthesiology and Perioperative Medicine, Mayo Clinic Hospital, Rochester, Minnesota, USA
  2. 2 School of Library and Information Science, University of Montreal, Montreal, Quebec, Canada
  3. 3 Department of Health Research Methods, Evidence, and Impact (HEI), McMaster University, Hamilton, Ontario, Canada
  4. 4 Kern Center for the Science of Healthcare Delivery, Mayo Clinic Hospital, Rochester, Minnesota, USA
  1. Correspondence to Dr Mohammad Hassan Murad, Kern Center for the Science of Healthcare Delivery, Mayo Clinic Hospital, Rochester, Minnesota, USA; murad.mohammad{at}mayo.edu

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Introduction

This series includes two articles about health information on social media platforms. This is the first article in which we present a framework for clinicians to appraise and interpret data directly derived from these platforms. The second article provides a framework for clinicians to appraise and interpret studies that 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, approximately 70% of Americans used social media platforms to communicate—an increase from 5% in 2005.2 Over 40% of healthcare consumers use social media platforms for healthcare information, and approximately 90% of consumers in the 18–24 year age group believe healthcare information conveyed on social media.2 Use of social media for health-related issues includes blogging, microblogging, social networks, professional networks, video/audio media, collaborative projects, virtual gaming and social worlds. The challenge has therefore evolved from finding information to assessing its credibility and relevance. A substantial risk of disseminating misleading information exists, which may adversely influence patients’ perceptions, adherence and medical care.3–7

When information from social media influences patients’ healthcare beliefs and actions, clinicians must deal with the consequences. Clinicians therefore require a framework to help interpret data on these platforms as well as the studies that analyse them. To develop this framework, we used previously validated instruments including the Health on the Net (HON) Code of Conduct8; DISCERN criteria9; Journal of the American Medical Association benchmark criteria10; and the minervation validation instrument for healthcare web sites (Randomised Evaluation of COVID-19 Therapy (LIDA) instrument).11 These tools have been identified as the most widely used instruments.12–14

Clinical scenario

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

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Footnotes

  • Contributors RSD helped perform background of research, study conception and design, search strategy data collection, generation of figures, analysis and interpretation of data, and drafted manuscript. LD helped perform background of research, drafted portion of the manuscript, and revised manuscript. WMH helped perform background of research, study conception, and revised the manuscript critically for intellectual content and gave final approval of the manuscript. GG helped perform background of research, study conception, wrote portions of the manuscript, and revised the manuscript critically for intellectual content and gave final approval of the manuscript. MHM helped with study conception and design, background of research, analysis and interpretation of data, drafted manuscript, and revised the manuscript critically for intellectual content and gave final approval of the manuscript. All authors made substantial contributions to conception and design, acquisition of data, or analysis and interpretation of data; took part in drafting the article or revising it critically for important intellectual content; agreed to submit to the current journal; gave final approval of the version to be published; and agree to be accountable for all aspects of the work.

  • Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

  • Competing interests None declared.

  • Provenance and peer review Not commissioned; externally peer reviewed.

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