Facebook activity might help predict mental and physical health, study says

20 Juin, 2019, 22:12 | Auteur: Yves Courtet
  • Facebook activity might help predict mental and physical health, study says

The new study builds on this research, suggesting that there's potential for the development of an optional system, in which a patient's social media posts are analyzed for additional, potentially valuable information.

Carried out by researchers at the University of Pennsylvania and Stony Brook University, the new study analyzed the complete Facebook post history of 999 patients, a total of around 20 million words, who had agreed to have their electronic medical record data linked to their Facebook profiles. The findings also revealed Facebook data was better at predicting 10 of the conditions compared to demographic information.

The researchers wanted to see whether data from Facebook alone could indicate 21 specific physical and mental health conditions.

The researchers used an automated data collection technique and analyzed the entire Facebook post history of almost 1,000 patients who agreed to have their electronic medical record data linked to their profiles.

For example, "drink" and "bottle" were shown to be more predictive of alcohol abuse.

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The researchers then constructed three modules to analyze their predictive power for the sufferers: one module just analyzing the Facebook post language, another that used demographics like age and sex, and the last that mixed the two datasets. Also, people who used words like "dumb" followed by curse words were more likely to abuse drugs or suffer psychoses. "This is the first study to show that language on Facebook can predict diagnoses within people's health record, revealing new opportunities to personalise care and understand how patients' ordinary daily lives relate to their health", the University of Pennsylvania School of Medicine and Stony Brook University researchers said in the published study.

For example, the people that often used religious words like "God" or "pray" in their posts were 15X more vulnerable to diabetes than those who used these terms the least.

"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", said Dr Raina Merchant, who is the director of Penn Medicine's Center for Digital Health and led the study.

The researchers built three models to analyse whether the posts could predict medical conditions across 21 broad categories. It follows a previous study carried out past year by some of the same team which suggested that social media posts could help predict a diagnosis of depression.

"One challenge with this is that there is so much data and we, as providers, aren't trained to interpret it ourselves - or make clinical decisions based on it", Merchant explained.

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