AJIC: American Journal of Infection Control
Volume 38, Issue 3 , Pages 182-188, April 2010

Dissemination of health information through social networks: Twitter and antibiotics

  • Daniel Scanfeld, MS, MA

      Affiliations

    • Integrated Program in Cellular, Molecular, Structural and Genetic Studies, Columbia University, New York, NY
    • Corresponding Author InformationAddress correspondence to Daniel Scanfeld, Fidock Lab, Columbia University Medical Center, Hammer HSC, Room 1502, 701 W 168th St, New York, NY 10032.
  • ,
  • Vanessa Scanfeld, MPP

      Affiliations

    • MixedInk, New York, NY
  • ,
  • Elaine L. Larson, RN, PhD, FAAN, CIC

      Affiliations

    • School of Nursing and Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY

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.

Key Words: Antibiotic, resistance, Web 2.0, Twitter

 

 Supported by Columbia University, The Center for Interdisciplinary Research to Reduce Antimicrobial Resistance, grant No. T90 NR010824: Training in Interdisciplinary Research to Reduce Antimicrobial Resistance (TIRAR).

 Conflicts of interest: None to report.

PII: S0196-6553(10)00034-9

doi:10.1016/j.ajic.2009.11.004

AJIC: American Journal of Infection Control
Volume 38, Issue 3 , Pages 182-188, April 2010