International Journal of Behavioral Medicine

, Volume 24, Issue 5, pp 703–712 | Cite as

Investigating Patterns of Participation in an Online Support Group for Problem Drinking: a Social Network Analysis

  • Karen UrbanoskiEmail author
  • Trevor van Mierlo
  • John Cunningham



This study contributes to emerging literature on online health networks by modeling communication patterns between members of a moderated online support group for problem drinking. Using social network analysis, we described members’ patterns of joint participation in threads, parsing out the role of site moderators, and explored differences in member characteristics by network position.


Posts made to the online support group of Alcohol Help Centre during 2013 were structured as a two-mode network of members (n = 205) connected via threads (n = 506). Metrics included degree centrality, clique membership, and tie strength.


The network consisted of one component and no cliques of members, although most made few posts and a small number communicated only with the site’s moderators. Highly active members were older and tended to have started posting prior to 2013. The distribution of members across threads varied from threads containing posts by one member to others that connected multiple members. Moderators accounted for sizable proportions of the connectivity between both members and threads.


After 5 years of operation, the AHC online support group appears to be fairly cohesive and stable, in the sense that there were no isolated subnetworks comprised of specific types of members or devoted to specific topics. Participation and connectedness at the member-level was varied, however, and tended to be low on average. The moderators were among the most central in the network, although there were also members who emerged as central and dedicated contributors to the online discussions across topics. Study findings highlight a number of areas for consideration by online support group developers and managers.


Social network analysis Online support groups Alcohol Internet-based interventions 


Compliance with Ethical Standards


This study did not receive dedicated funding. KU is supported by a Canada Research Chair in Substance Use, Addictions and Health Services Research from the Canadian Institutes for Health Research.

Conflict of Interest

TvM is the CEO and Founder of Evolution Health Systems Inc., the owner of Alcohol Help Center as well as other eHealth and mHealth platforms. KU and JC declare that they have no conflict of interest.

Ethical Approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed Consent

Subjects consented to their data being used for research purposes by endorsing a checkbox in the online platform.


  1. 1.
    Moos RH. Theory-based processes that promote the remission of substance use disorders. Clin Psychol Rev. 2007;27(5):537–51. doi: 10.1016/j.cpr.2006.12.006.CrossRefPubMedGoogle Scholar
  2. 2.
    van Mierlo T. The 1 % rule in four digital health social networks: an observational study. J Med Internet Res. 2014;16(2):e33. doi: 10.2196/jmir.2966.CrossRefPubMedPubMedCentralGoogle Scholar
  3. 3.
    Carron-Arthur B, Cunningham JA, Griffiths KM. Describing the distribution of engagement in an internet support group by post frequency: a comparison of the 90-9-1 principle and Zipf’s law. Internet Interv. 2014;1:165–8.CrossRefGoogle Scholar
  4. 4.
    Healey B, Hoek J, Edwards R. Posting behaviour patterns in an online smoking cessation social network: implications for intervention design and development. PLoS One. 2014;9(9):e106603. doi: 10.1371/journal.pone.0106603.CrossRefPubMedPubMedCentralGoogle Scholar
  5. 5.
    van Mierlo T, Hyatt D, Ching AT. Mapping power law distributions in digital health social networks: methods, interpretations, and practical implications. J Med Internet Res. 2015;17(6):e160. doi: 10.2196/jmir.4297.CrossRefPubMedPubMedCentralGoogle Scholar
  6. 6.
    Carron-Arthur B, Ali K, Cunningham JA, Griffiths KM. Quantifiable participation styles in online health communities—from “Help-seekers” to “Influential Users”: a systematic review. 2016.Google Scholar
  7. 7.
    Cobb NK, Graham AL, Abrams DB. Social network structure of a large online community for smoking cessation. Am J Public Health. 2010;100(7):1282–9. doi: 10.2105/AJPH.2009.165449.CrossRefPubMedPubMedCentralGoogle Scholar
  8. 8.
    Chomutare T, Arsand E, Fernandez-Luque L, Lauritzen J, Hartvigsen G. Inferring community structure in healthcare forums. An empirical study. Methods Inf Med. 2013;52(2):160–7. doi: 10.3414/ME12-02-0003.CrossRefPubMedGoogle Scholar
  9. 9.
    Durant KT, McCray AT, Safran C. Social network analysis of an online melanoma discussion group. AMIA Jt Summits Transl Sci Proc. 2010;2010:6–10.PubMedGoogle Scholar
  10. 10.
    Myneni S, Cobb NK, Cohen T. Finding meaning in social media: content-based social network analysis of QuitNet to identify new opportunities for health promotion. Stud Health Technol Inform. 2013;192:807–11.PubMedGoogle Scholar
  11. 11.
    Luke DA, Harris JK. Network analysis in public health: history, methods, and applications. Annu Rev Public Health. 2007;28:69–93. doi: 10.1146/annurev.publhealth.28.021406.144132.CrossRefPubMedGoogle Scholar
  12. 12.
    Borgatti SP, Mehra A, Brass DJ, Labianca G. Network analysis in the social sciences. Science. 2009;323(5916):892–5. doi: 10.1126/science.1165821.CrossRefPubMedGoogle Scholar
  13. 13.
    Gruzd A, Haythornthwaite C. Enabling community through social media. J Med Internet Res. 2013;15(10):e248. doi: 10.2196/jmir.2796.CrossRefPubMedPubMedCentralGoogle Scholar
  14. 14.
    Cunningham JA, van Mierlo T, Fournier R. An online support group for problem drinkers: AlcoholHelpCenter.Net. Patient Educ Couns. 2008;70(2):193–8. doi: 10.1016/j.pec.2007.10.003.CrossRefPubMedGoogle Scholar
  15. 15.
    Cunningham JA, Wild TC, Cordingley J, van Mierlo T, Humphreys K. A randomized controlled trial of an internet-based intervention for alcohol abusers. Addiction. 2009;104(12):2023–32. doi: 10.1111/j.1360-0443.2009.02726.x.CrossRefPubMedPubMedCentralGoogle Scholar
  16. 16.
    Cunningham JA, Wild TC, Cordingley J, Van Mierlo T, Humphreys K. Twelve-month follow-up results from a randomized controlled trial of a brief personalized feedback intervention for problem drinkers. Alcohol Alcohol. 2010;45(3):258–62. doi: 10.1093/alcalc/agq009.CrossRefPubMedPubMedCentralGoogle Scholar
  17. 17.
    Cunningham JA. Comparison of two internet-based interventions for problem drinkers: randomized controlled trial. J Med Internet Res. 2012;14(4):e107. doi: 10.2196/jmir.2090.CrossRefPubMedPubMedCentralGoogle Scholar
  18. 18.
    de Nooy W, A M, V B. Exploratory social network analysis with Pajek. 2nd Ed. ed. New York: Cambridge University Press; 2011.Google Scholar
  19. 19.
    Hanneman RA, Riddle M. Introduction to social network methods. Riverside, CA: University of California, Riverside ( published in digital form at∼hanneman/ )2005.
  20. 20.
    Bennett GG, Glasgow RE. The delivery of public health interventions via the internet: actualizing their potential. Annu Rev Public Health. 2009;30:273–92. doi: 10.1146/annurev.publhealth.031308.100235.CrossRefPubMedGoogle Scholar
  21. 21.
    Funk KL, Stevens VJ, Appel LJ, et al. Associations of internet website use with weight change in a long-term weight loss maintenance program. J Med Internet Res. 2010;12(3):e29. doi: 10.2196/jmir.1504.CrossRefPubMedPubMedCentralGoogle Scholar
  22. 22.
    Kerr C, Murray E, Noble L, et al. The potential of web-based interventions for heart disease self-management: a mixed methods investigation. J Med Internet Res. 2010;12(4):e56. doi: 10.2196/jmir.1438.CrossRefPubMedPubMedCentralGoogle Scholar
  23. 23.
    Robroek SJ, Brouwer W, Lindeboom D, Oenema A, Burdorf A. Demographic, behavioral, and psychosocial correlates of using the website component of a worksite physical activity and healthy nutrition promotion program: a longitudinal study. J Med Internet Res. 2010;12(3):e44. doi: 10.2196/jmir.1402.CrossRefPubMedPubMedCentralGoogle Scholar
  24. 24.
    Brouwer W, Oenema A, Raat H, et al. Characteristics of visitors and revisitors to an internet-delivered computer-tailored lifestyle intervention implemented for use by the general public. Health Educ Res. 2010;25(4):585–95. doi: 10.1093/her/cyp063.CrossRefPubMedGoogle Scholar
  25. 25.
    Young C. Community management that works: how to build and sustain a thriving online health community. J Med Internet Res. 2013;15(6):e119. doi: 10.2196/jmir.2501.CrossRefPubMedPubMedCentralGoogle Scholar
  26. 26.
    Lindsay S, Smith S, Bellaby P, Baker R. The health impact of an online heart disease support group: a comparison of moderated versus unmoderated support. Health Educ Res. 2009;24(4):646–54. doi: 10.1093/her/cyp001.CrossRefPubMedGoogle Scholar
  27. 27.
    Campbell AN, Nunes EV, Matthews AG, et al. Internet-delivered treatment for substance abuse: a multisite randomized controlled trial. Am J Psychiatry. 2014;171(6):683–90. doi: 10.1176/appi.ajp.2014.13081055.CrossRefPubMedPubMedCentralGoogle Scholar
  28. 28.
    Chung JE. Social networking in online support groups for health: how online social networking benefits patients. J Health Commun. 2014;19(6):639–59. doi: 10.1080/10810730.2012.757396.CrossRefPubMedGoogle Scholar
  29. 29.
    Welbourne JL, Blanchard AL, Wadsworth MB. Motivations in virtual health communities and their relationship to community, connectedness and stress. Comput Hum Behav. 2013;29(1):129–39. doi: 10.1016/j.chb.2012.07.024.CrossRefGoogle Scholar
  30. 30.
    Albert R, Barabasi AL. Statistical mechanics of complex networks. Rev Mod Phys. 2002;74(1):47.CrossRefGoogle Scholar
  31. 31.
    Cobb NK, Graham AL, Byron MJ, Niaura RS, Abrams DB, Workshop P. Online social networks and smoking cessation: a scientific research agenda. J Med Internet Res. 2011;13(4):e119. doi: 10.2196/jmir.1911.CrossRefPubMedPubMedCentralGoogle Scholar

Copyright information

© International Society of Behavioral Medicine 2016

Authors and Affiliations

  • Karen Urbanoski
    • 1
    Email author
  • Trevor van Mierlo
    • 2
    • 3
  • John Cunningham
    • 4
    • 5
  1. 1.Centre for Addictions Research of British ColumbiaUniversity of VictoriaVictoriaCanada
  2. 2.Evolution Health Systems Inc.TorontoCanada
  3. 3.Henley Business SchoolUniversity of ReadingOxfordshireUK
  4. 4.Centre for Addiction and Mental HealthTorontoCanada
  5. 5.National Institute for Mental Health ResearchAustralian National UniversityCanberraAustralia

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