How often do patients turn to social media for STD second opinions?

Publication
Article
Contemporary OB/GYN JournalVol 64 No 12
Volume 64
Issue 12

A recent research letter in JAMA looked at crowd-diagnoses via social media to determine whether they were for a second opinion after seeing a health care professional.

Young woman phone

©Samuel Borges Photography - shutterstock.com

Social media is ubiquitous today, but one area that has not been fully investigated is its effect on medical diagnoses. A recent research letter in JAMA looked at crowd-diagnoses via social media to determine whether they were for a second opinion after seeing a health care professional.

Methods
The authors focused their study on Reddit, a social media website with 330 million monthly active users that hosts more than 232 health forums. The research focused exclusively on the subreddit, (r/STD), which allows users to publicly share “stories, concerns, and questions” about “anything and everything STD [sexually transmitted disease]-related.”

The authors obtained all posts from the inception of the subreddit in November 2010 through February 2019. They then drew a random sample of 500 posts and independently coded whether each post requested a crowd-diagnosis, and if so, whether that request was made to obtain a second opinion after seeing a healthcare professional.

Findings
The r/STD subreddit included 16,979 total posts. There was an 80% agreement among all coders on crowd-diagnoses (Cohen κ = 0.73) and 88% agreement on whether the crowd-diagnoses were requests for a second opinion (Cohen κ = 0.53) among an overlapping sample of 50 posts.

The authors found that:

  • 58% (95% CI, 54%-63%) of posts requested a crowd-diagnosis and

  • 31% (95% CI, 26%-36%) of posts included an image of the physical signs.

  • 20% of those requesting a crowd-diagnosis posted to receive a second opinion after their initial diagnosis by a healthcare professional.

  • 87% (95% CI, 83%-91%) of all posts requesting a crowd-diagnosis received a reply. Median time for the first response was 3.04 hours (range, 59 seconds to 8.8 weeks), but 79% of requests (95% CI, 74%-84%) were answered in less than 1 day.

Conclusions
The authors admit that there are a few limitations to this study. It was limited to one social media platform and a single medical condition. Perhaps more importantly, the accuracy of the diagnoses and whether individuals acted on the provided advice were not investigated.

The authors suggest that health care professionals could “partner with social media outlets to promote the potential benefits of crowd-diagnosis while suppressing potential harms, for example by having trained professionals respond to posts to better diagnose and make referrals to health care centers.”

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