News Release 

'Crowd-diagnosis' thousands seek out diagnoses from strangers on social media

Elevated Science Communications

Physician-diagnosis, self-diagnosis, and a new study published in the Journal of the American Medical Association led by Dr. Alicia Nobles and Dr. John W. Ayers of UC San Diego discovered a new type of diagnosis. Crowd-diagnosis: when the public seeks out medical diagnoses from strangers on social media.

Crowd-Diagnosis, A Case Study Using Reddit and STDs

Sexually transmitted diseases (STDs) are at an all time high according to the Centers for Disease Control. "We've seen substantial increases in the number of patients in our STD clinics," said Dr. Davey Smith, study coauthor and Chief of Infectious Diseases and Global Public Health at UC San Diego. "But statistically we should be seeing more. Shame or a lack of access means many are missing an opportunity to get professional, life-saving help."

Where are those falling through the cracks turning? "Leaders take it for granted that the public is relying on Dr. Google for all of their health concerns," said Dr. Nobles a Research Fellow who co-lead the study. "But people also want a sense of connection! The reason social media sites are so popular is they offer real interactions with real people. For those same reasons some may choose to seek out medical help on social media platforms."

Reddit is a social media website that rivals Twitter with 330 million active users and is the 6th most visited website in the United States, ranked ahead of even Wikipedia, Twitter, and Amazon. Reddit is organized into communities focused on specific topics, many of which deal exclusively with health. The team monitored all r/STD posts, where users can find "anything and everything STD related," from its inception in November 2010 through February 2019. The team found that use of r/STD rapidly increased, with the number of posts doubling since November 2018.

Among all posts to r/STD 58 percent were explicitly requesting a crowd-diagnosis. Among those 31 percent included a picture of the symptoms.

"Our case study is especially conservative at estimating how common crowd-diagnoses may be because no one would expect that thousands of people would be willing to share pictures of their you-know-what on social media rather than seeing a trained physician," said Dr. Eric Leas, an Assistant Professor in the Department of Family Medicine and Public Health and study coauthor. "Imagine all the other crowd-diagnoses the public are seeking on Reddit, Twitter and the like for STDs and other conditions. "

Crowd-Diagnosis Requested, Diagnosis Received

87 percent of all crowd-diagnoses requested received a reply, many of which received multiple replies. The median time for the first response was 3 hours with some posts receiving a reply in less than 1 minute.

"Crowd-diagnoses are becoming popular because strangers are so willing to try to help. 79 percent of requested crowd-diagnoses were answered in less than a day. Try getting a doctor's opinion in that time," said study co-author Dr. Ayers, the Vice Chief of Innovation in the Division of Infectious Disease and Global Public Health at UC San Diego who co-lead the study. Adding, "but fast doesn't mean accurate."

Crowd-Diagnoses to Replace Physician-Diagnoses

The team also found 20 percent of crowd-diagnosis requests were made after already obtaining a physician-diagnosis.

"On one occasion a patient had received an HIV diagnosis but turned to a crowd-diagnosis to be convinced the doctor was wrong," said Dr. Ayers. "People when faced with life altering information often want to delude themselves and in some cases they are finding it on social media."

Moreover, the team notes that the types of treatments recommended often go against a doctor's orders. "Apple cider vinegar cures all according to the crowd on social media," added Dr. Nobles.

Easy Crowd-Diagnoses, Real Dangers

"Although crowd-diagnoses have the benefits of anonymity, speed, and multiple opinions, many are wildly inaccurate," said Dr. Christopher Longhurst, professor of biomedical informatics at UC San Diego Health and study coauthor.

Dr. Nobles chiming in said "A misdiagnosis could result in the continued spread of the disease, but may also have a ripple effect for the millions who view the post and perceive they have a similar condition which they then wrongly self-diagnose."

"Even if users responding to a crowd-diagnosis were trained experts, social media was not designed to deliver health care," added Dr. Smith. "I personally would not feel comfortable responding with a diagnosis to many of the requests we observed nor would I be able to ensure that those I diagnosed received safe and effective treatment. But in the future that may be possible."

Can Crowd-Diagnoses Ever Benefit Public Health?

Studying crowd-diagnoses can be an important tool for healthcare planning added Dr. Longhurst. "By studying crowd-diagnoses broadly we could identify what conditions and what types of information the public is willing to share and build out evidence-based resources to match those needs. Few clinicians would have expected so much unmet demand for remote treatment referral among patients with potential STDs."

"It is our responsibility to ensure that the thousands or millions seeking out crowd-diagnoses get help. By partnering with social media companies we can combat the spread of misinformation or mis-diagnoses and ensure life-saving help is found. Social media platforms could be improved to facilitate more reliable and actionable crowd-diagnoses. For instance, experts could moderate requests for crowd-diagnoses, resulting in social media being a vehicle to connect the public to professional healthcare," added Dr. Ayers.

"It is critically important that health leaders become aware of and respond to our discovery of crowd-diagnoses," concluded Dr. Nobles. "There are problems with crowd-diagnoses as they exist, but there is tremendous potential to leverage this phenomena to substantially improve public health."

###

Disclaimer: AAAS and EurekAlert! are not responsible for the accuracy of news releases posted to EurekAlert! by contributing institutions or for the use of any information through the EurekAlert system.