Twitter, once the place you went for things like breaking news and celebrity gossip, is now helping us to better understand the relationship between insomnia and social media.
Researchers have built the beginnings of “digital phenotype” of insomnia and other sleep disorders based on data from Twitter. The study, published in the Journal of Medical Internet Research, is one of the first to look at relationships between social media use and sleep issues, and, based on assessments the sentiments expressed in users’ tweets, gives preliminary hints that patients with sleep disorders may be a greater risk of psychosocial issues.
The study, conducted by Boston Children’s Informatics Program and researchers at Merck, is the product of a Boston Children’s/Merck collaboration on social media and sleep announced in 2014.
Insomnia and other sleep issues affect between 50 and 70 million Americans. Apart from their impact on productivity, accidents and risky behaviors, chronic sleep disorders also contribute to diabetes, cardiovascular disease and depression.
“Sleep deprivation and chronic sleep disorders are not well understood,” said John Brownstein, who directs the hospital’s Computational Epidemiology Group. “We wanted to see if we could use new forms of online data, such as Twitter, to characterize the sleep disordered individual and possibly uncover new, previously-undescribed populations of patients suffering sleep problems.”
The research team used publically available anonymous data from Twitter to create a group of 896 active Twitter users whose tweets contained sleep-related words (e.g., “can’t sleep,” “insomnia”), or hashtags (e.g., #cantsleep, #teamnosleep), 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.
The resulting profile of a Twitter user with sleep issues–compared to a Twitter user without–looked like this:
Taken together, the data suggest that Twitter users suffering from a sleep disorder are less active on Twitter on average but tweet more during traditional sleeping hours. The increase in negative sentiment in their tweets suggests that sleep-disordered users could be at an increased risk for psychosocial issues.
“These findings are preliminary and observational only, and need to be studied further,” Brownstein cautioned. “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.”
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