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The Spread of Sleep Loss Influences Drug Use in Adolescent Social Networks

Overview of attention for article published in PLOS ONE, March 2010
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Title
The Spread of Sleep Loss Influences Drug Use in Adolescent Social Networks
Published in
PLOS ONE, March 2010
DOI 10.1371/journal.pone.0009775
Pubmed ID
Authors

Sara C. Mednick, Nicholas A. Christakis, James H. Fowler

Abstract

Troubled sleep is a commonly cited consequence of adolescent drug use, but it has rarely been studied as a cause. Nor have there been any studies of the extent to which sleep behavior can spread in social networks from person to person to person. Here we map the social networks of 8,349 adolescents in order to study how sleep behavior spreads, how drug use behavior spreads, and how a friend's sleep behavior influences one's own drug use. We find clusters of poor sleep behavior and drug use that extend up to four degrees of separation (to one's friends' friends' friends' friends) in the social network. Prospective regression models show that being central in the network negatively influences future sleep outcomes, but not vice versa. Moreover, if a friend sleeps </=7 hours, it increases the likelihood a person sleeps < or =7 hours by 11%. If a friend uses marijuana, it increases the likelihood of marijuana use by 110%. Finally, the likelihood that an individual uses drugs increases by 19% when a friend sleeps < or =7 hours, and a mediation analysis shows that 20% of this effect results from the spread of sleep behavior from one person to another. This is the first study to suggest that the spread of one behavior in social networks influences the spread of another. The results indicate that interventions should focus on healthy sleep to prevent drug use and targeting specific individuals may improve outcomes across the entire social network.

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Geographical breakdown

Country Count As %
United States 9 3%
Ireland 2 <1%
United Kingdom 2 <1%
Italy 1 <1%
Brazil 1 <1%
Sweden 1 <1%
Malaysia 1 <1%
France 1 <1%
Finland 1 <1%
Other 2 <1%
Unknown 238 92%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 49 19%
Researcher 40 15%
Student > Master 27 10%
Student > Bachelor 22 8%
Professor > Associate Professor 21 8%
Other 51 20%
Unknown 49 19%
Readers by discipline Count As %
Psychology 52 20%
Medicine and Dentistry 31 12%
Social Sciences 30 12%
Computer Science 17 7%
Agricultural and Biological Sciences 9 3%
Other 51 20%
Unknown 69 27%