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Dissemination of Health Information Through Social Networks: Twitter and Antibiotics

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Date 2010 Mar 30
PMID 20347636
Citations 161
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Abstract

Background: This study reviewed Twitter status updates mentioning "antibiotic(s)" to determine overarching categories and explore evidence of misunderstanding or misuse of antibiotics.

Methods: One thousand Twitter status updates mentioning antibiotic(s) were randomly selected for content analysis and categorization. To explore cases of potential misunderstanding or misuse, these status updates were mined for co-occurrence of the following terms: "cold + antibiotic(s)," "extra + antibiotic(s)," "flu + antibiotic(s)," "leftover + antibiotic(s)," and "share + antibiotic(s)" and reviewed to confirm evidence of misuse or misunderstanding.

Results: Of the 1000 status updates, 971 were categorized into 11 groups: general use (n = 289), advice/information (n = 157), side effects/negative reactions (n = 113), diagnosis (n = 102), resistance (n = 92), misunderstanding and/or misuse (n = 55), positive reactions (n = 48), animals (n = 46), other (n = 42), wanting/needing (n = 19), and cost (n = 8). Cases of misunderstanding or abuse were identified for the following combinations: "flu + antibiotic(s)" (n = 345), "cold + antibiotic(s)" (n = 302), "leftover + antibiotic(s)" (n = 23), "share + antibiotic(s)" (n = 10), and "extra + antibiotic(s)" (n = 7).

Conclusion: Social media sites offer means of health information sharing. Further study is warranted to explore how such networks may provide a venue to identify misuse or misunderstanding of antibiotics, promote positive behavior change, disseminate valid information, and explore how such tools can be used to gather real-time health data.

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References
1.
Akhtar-Danesh N, Baumann A, Cordingley L . Q-methodology in nursing research: a promising method for the study of subjectivity. West J Nurs Res. 2008; 30(6):759-73. DOI: 10.1177/0193945907312979. View

2.
Fjeldsoe B, Marshall A, Miller Y . Behavior change interventions delivered by mobile telephone short-message service. Am J Prev Med. 2009; 36(2):165-73. DOI: 10.1016/j.amepre.2008.09.040. View

3.
Keller M, Blench M, Tolentino H, Freifeld C, Mandl K, Mawudeku A . Use of unstructured event-based reports for global infectious disease surveillance. Emerg Infect Dis. 2009; 15(5):689-95. PMC: 2687026. DOI: 10.3201/eid1505.081114. View

4.
Franklin V, Waller A, Pagliari C, Greene S . "Sweet Talk": text messaging support for intensive insulin therapy for young people with diabetes. Diabetes Technol Ther. 2004; 5(6):991-6. DOI: 10.1089/152091503322641042. View

5.
Rodgers A, Corbett T, Bramley D, Riddell T, Wills M, Lin R . Do u smoke after txt? Results of a randomised trial of smoking cessation using mobile phone text messaging. Tob Control. 2005; 14(4):255-61. PMC: 1748056. DOI: 10.1136/tc.2005.011577. View