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Tweeting back: predicting new cases of back pain with mass social media data.

Authors :
Lee, Hopin
McAuley, James H.
Hübscher, Markus
Allen, Heidi G.
Kamper, Steven J.
Moseley, G. Lorimer
Source :
Journal of the American Medical Informatics Association; May2016, Vol. 23 Issue 3, p644-648, 5p, 1 Diagram, 1 Chart, 1 Graph
Publication Year :
2016

Abstract

<bold>Background: </bold>Back pain is a global health problem. Recent research has shown that risk factors that are proximal to the onset of back pain might be important targets for preventive interventions. Rapid communication through social media might be useful for delivering timely interventions that target proximal risk factors. Identifying individuals who are likely to discuss back pain on Twitter could provide useful information to guide online interventions.<bold>Methods: </bold>We used a case-crossover study design for a sample of 742 028 tweets about back pain to quantify the risks associated with a new tweet about back pain.<bold>Results: </bold>The odds of tweeting about back pain just after tweeting about selected physical, psychological, and general health factors were 1.83 (95% confidence interval [CI], 1.80-1.85), 1.85 (95% CI: 1.83-1.88), and 1.29 (95% CI, 1.27-1.30), respectively.<bold>Conclusion: </bold>These findings give directions for future research that could use social media for innovative public health interventions. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
10675027
Volume :
23
Issue :
3
Database :
Complementary Index
Journal :
Journal of the American Medical Informatics Association
Publication Type :
Academic Journal
Accession number :
116910481
Full Text :
https://doi.org/10.1093/jamia/ocv168