NEW YORK (Reuters Health) - Information published online can reveal your mental health by identifying the main symptoms of depression three months before the doctor's official diagnosis, US experts said.T he researchers developed an algorithm based on artificial intelligence, which they believe can scan people's publications on their accounts via social media, and warn them if there are symptoms of mental illness.
Symptoms included signs of hostility, loneliness and words such as "tears" and "emotions" as well as excessive use of self and the pronoun "I".
"What people write about social media and the Internet is a very difficult aspect of life in medicine and research," said Andrew Schwartz, lead author and lead researcher at the University of Pennsylvania and Stony Brook University.
"It is relatively untapped compared to the biophysical markers of the disease," Schwartz said. "For conditions like depression, anxiety and post-traumatic stress disorder, for example, there are more signs in the way people express themselves digitally."
The research team said social media data contained signs closer to the genome, as those data had surprisingly similar genome-style methods, so owning social networking data could be an effective way to find early signs of mental illness.
Depression seems to be one of those diseases that can be discovered in this way, as people change their way of using social media.
A total of 1,200 participants in the study agreed to provide a digital archive for their use of Facebook and their medical records. Of those, only 114 were depressed in their medical records, and each was compared with 5 non-depressed individuals to test the accuracy of the program.
By analyzing 52,4292 participation by volunteers in the study via their Facebook accounts in the years before their diagnosis of depression, the team identified "language signs associated with depression".
The study also found that its program was more accurate in diagnosing depression, using social media signals in the six months prior to the onset of signs of the disease.The researchers identified the most frequently used words and phrases and then put 200 subjects to explain what they called "language signs associated with depression", which allowed the program to detect early warning signs of depression in individuals by posting on Facebook before they were officially diagnosed in their medical records by three months .
The research team explained that these early signs of the disease include emotional, cognitive and personal processes such as enmity, loneliness, sadness and meditation.
This can help to report the onset of depression in people at risk, enabling the early diagnosis and treatment of the disease, which reduces its impact on education, employment and social relations.
The researchers say the program can be improved by integrating phone use data or facial recognition software to analyze images published on Facebook.
Source: Daily Mail
