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Your Facebook profile can predict diabetes, depression, other medical conditions, study says

Your Facebook profile can be quite revealing. It may even be able to predict some medical conditions, according to a new report.

Your Facebook profile can be quite revealing. It may even be able to predict some medical conditions, according to a new report.

Researchers from Penn Medicine and Stony Brook University recently conducted a study, published in the PLOS ONE journal, to determine if social media posts can be indicators of 21 health conditions, including diabetes, anxiety, depression and psychosis.

To do so, they examined the entire Facebook post history of nearly 1,000 patients who agreed to have their electronic medical record data linked to their profiles. Researchers then built three models to assess the subjects’ “predictive power.” One evaluated their Facebook post language; the second looked at demographics, such as age and sex; and the last one combined the first two datasets. After analyzing the results, they found all 21 conditions were predictable from the social media network alone. In fact, researchers said 10 of the conditions were better predicted through Facebook data than demographic information.

The study revealed those who used “drink” and “bottle” had an increased risk of alcohol abuse. Those who used religious language, such as “God” and “pray,” were 15 times more likely to have diabetes. And terms expressing hostility, like expletives, were more predictive of drug abuse and psychoses.

“Our digital language captures powerful aspects of our lives that are likely quite different from what is captured through traditional medical data,” senior author Andrew Schwartz said in a statement. “Many studies have now shown a link between language patterns and specific disease, such as language predictive of depression or language that gives insights into whether someone is living with cancer. However, by looking across many medical conditions, we get a view of how conditions relate to each other, which can enable new applications of AI for medicine.”

The scientists now plan to investigate whether managing this data is feasible by asking patients to share their social media content directly to their doctors.

“This work is early, but our hope is that the insights gleaned from these posts could be used to better inform patients and providers about their health,” lead author Raina Merchant added. “As social media posts are often about someone’s lifestyle choices and experiences or how they’re feeling, this information could provide additional information about disease management and exacerbation.”