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Twitter Could Lead to Improved Research on Sleep Disorders

June 11, 2015
by Gabriel Perna
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Researchers at Boston Children’s Hospital recently reported that important data on sleep disorders could be found in the Twittersphere.

The researchers built a "digital phenotype" of insomnia and other sleep disorders based on data from Twitter. The digital phenotype was a baseline profile of what a person suffering insomnia or other sleep disorders "looks" like on social media. They took publically available anonymized data from Twitter to create a virtual cohort of 896 active Twitter users whose tweets contained sleep-related words or the names of common sleep aids or medications. They then compared data from that cohort to those of a second group of 934 users who did not tweet using sleep-related terms.

With this data, they created a profile of a user with sleep issues with the following characteristics:

  • They have been active on Twitter for a relatively long time
  • They have fewer followers and follows fewer people
  • They post few tweets per day on average
  • They’re more active on Twitter between 6:00 pm and 5:59 am
  • They’re more active on Twitter on weekends and early weekdays
  • They’re more likely to post tweets with negative sentiment

The researchers, from Boston Children’s Informatics Program as well as researchers at the pharmaceutical company, Merck, say the social media data could help overcome traditional limitations of population-level research on sleep disorders. Those limitations are traditional data is time- and resource intensive, expensive, suffer from long lag times before reporting and can’t be expanded to the larger U.S. population.

"These findings are preliminary and observational only, and need to be studied further," stated John Brownstein, Ph.D. of the Informatics Program. "But they suggest that social media can be a useful addition to our toolkit for studying the patient experience and behavioral epidemiology of sleep disorders."

The research was published in the Journal of Medical Internet Research.

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