Literature DB >> 22142603

[Laypersons can seek help from their Facebook friends regarding medical diagnosis].

Lars Folkestad1, Jacob Broder Brodersen, Peter Hallas, Mikkel Brabrand.   

Abstract

INTRODUCTION: In contrast to Internet search engines, social media on the Internet such as Facebook, Twitter, etc. reach a large number of people, who are ready to help answering questions. This type of information aggregation has been dubbed "crowdsourcing" i.e. outsourcing a task to a large group of people or community (a crowd) through an open call. Our aim was to explore whether laypersons via Facebook friends could crowd source their way to a medical diagnosis based on a brief medical history, posted as a status update on Facebook.
MATERIAL AND METHODS: The participants posted a brief case story on their Facebook profile and asked their "Facebook friends" to come up with possible diagnoses.
RESULTS: The correct diagnosis was suggested in five of the six case stories, and the correct diagnosis was made after a median of ten minutes. The quality of the responses varied from relevant differential diagnoses to very silly diagnostic suggestions.
CONCLUSION: Based on this study, we believe that laypersons can use his or her "Facebook friends" to identify the need to see a doctor for their symptoms rather than relying on them to give them a specific diagnosis for their symptoms.

Entities:  

Mesh:

Year:  2011        PMID: 22142603

Source DB:  PubMed          Journal:  Ugeskr Laeger        ISSN: 0041-5782


  3 in total

1.  How Twitter Is Studied in the Medical Professions: A Classification of Twitter Papers Indexed in PubMed.

Authors:  Shirley Ann Williams; Melissa Terras; Claire Warwick
Journal:  Med 2 0       Date:  2013-07-18

Review 2.  Applications of crowdsourcing in health: an overview.

Authors:  Kerri Wazny
Journal:  J Glob Health       Date:  2018-06       Impact factor: 4.413

3.  Mapping of Crowdsourcing in Health: Systematic Review.

Authors:  Perrine Créquit; Ghizlène Mansouri; Mehdi Benchoufi; Alexandre Vivot; Philippe Ravaud
Journal:  J Med Internet Res       Date:  2018-05-15       Impact factor: 5.428

  3 in total

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