Superusers in social networks for smoking cessation: analysis of demographic characteristics and posting behavior from the Canadian Cancer Society's smokers' helpline online and StopSmokingCenter.net
- PMID: 22732103
- PMCID: PMC3414904
- DOI: 10.2196/jmir.1854
Superusers in social networks for smoking cessation: analysis of demographic characteristics and posting behavior from the Canadian Cancer Society's smokers' helpline online and StopSmokingCenter.net
Abstract
Background: Online social networks are popular components of behavior-change websites. Research has identified the participation of certain network members who assume leadership roles by providing support, advice, and direction to other members. In the literature, these individuals have been variously defined as key players, posters, active users, or caretakers. Despite their identification, very little research has been conducted on the contributions or demographic characteristics of this population. For this study, we collectively categorized key players, posters, active users, and caretakers as superusers.
Objectives: To analyze data from two large but distinct Web-assisted tobacco interventions (WATI) to help gain insight into superuser demographic characteristics and how they use social networks.
Methods: We extracted cross-sectional data sets containing posting behaviors and demographic characteristics from a free, publicly funded program (the Canadian Cancer Society's Smokers' Helpline Online: SHO), and a free, privately run program (StopSmokingCenter.net: SSC).
Results: Within the reporting period (SHO: June 26, 2008 to October 12, 2010; SSC: May 17, 2007 to October 12, 2010), 21,128 individuals registered for the SHO and 11,418 registered for the SSC. Within the same period, 1670 (7.90%) registrants made at least one post in the SHO social network, and 1627 (14.25%) registrants made at least one post in the SSC social network. SHO and SSC superusers accounted for 0.4% (n = 95) and 1.1% (n = 124) of all registrants, and 5.7% (95/1670) and 7.62% (124/1627) of all social network participants, and contributed to 34.78% (29,422/84,599) and 46.22% (61,820/133,753) of social network content, respectively. Despite vast differences in promotion and group management rules, and contrary to the beliefs of group moderators, there were no statistically significant differences in demographic characteristics between the two superuser groups.
Conclusions: To our knowledge, this is the first study that compared demographic characteristics and posting behavior from two separate eHealth social networks. Despite vast differences in promotional efforts and management styles, both WATI attracted superusers with similar characteristics. As superusers drive network traffic, organizations promoting or supporting WATI should dedicate resources to encourage superuser participation. Further research regarding member dynamics and optimization of social networks for health care purposes is required.
Conflict of interest statement
Trevor van Mierlo is the CEO of Evolution Health Systems Inc. and the owner of StopSmokingCenter.net and other eHealth software platforms. Peter Selby received funds from Schering Canada to provide buprenorphine training, and received honoraria for consultant work, grant funding, advisory board, and/or lectureships from Johnson & Johnson Consumer Health Care Canada; Pfizer Inc, Canada; Sanofi-Synthelabo, Canada; GSK, Canada; Genpharm and Prempharm, Canada; CTI; Evolution Health Systems Inc., Canada; Health Canada; Smoke-Free Ontario; and Canadian Institutes of Health Research. Funding was in compliance with the Canadian Medical Association and the Canadian Psychiatric Association guidelines and recommendations for interaction with the pharmaceutical industry. Sharon Lee is employed by the Canadian Cancer Society. Rachel Fournier is employed by Evolution Health Systems Inc. Sabrina Voci has no interests to declare. None of the authors received any tobacco industry funds.
Figures






Similar articles
-
Online social and professional support for smokers trying to quit: an exploration of first time posts from 2562 members.J Med Internet Res. 2010 Aug 18;12(3):e34. doi: 10.2196/jmir.1340. J Med Internet Res. 2010. PMID: 20719739 Free PMC article.
-
How Online Communities of People With Long-Term Conditions Function and Evolve: Network Analysis of the Structure and Dynamics of the Asthma UK and British Lung Foundation Online Communities.J Med Internet Res. 2018 Jul 11;20(7):e238. doi: 10.2196/jmir.9952. J Med Internet Res. 2018. PMID: 29997105 Free PMC article.
-
Demographic and Indication-Specific Characteristics Have Limited Association With Social Network Engagement: Evidence From 24,954 Members of Four Health Care Support Groups.J Med Internet Res. 2017 Feb 17;19(2):e40. doi: 10.2196/jmir.6330. J Med Internet Res. 2017. PMID: 28213340 Free PMC article.
-
A review of web-assisted tobacco interventions (WATIs).J Med Internet Res. 2008 Nov 6;10(5):e39. doi: 10.2196/jmir.989. J Med Internet Res. 2008. PMID: 19000979 Free PMC article. Review.
-
A Review of the Theoretical Basis, Effects, and Cost Effectiveness of Online Smoking Cessation Interventions in the Netherlands: A Mixed-Methods Approach.J Med Internet Res. 2017 Jun 23;19(6):e230. doi: 10.2196/jmir.7209. J Med Internet Res. 2017. PMID: 28645889 Free PMC article. Review.
Cited by
-
Optimising text messaging to improve adherence to web-based smoking cessation treatment: a randomised control trial protocol.BMJ Open. 2016 Mar 30;6(3):e010687. doi: 10.1136/bmjopen-2015-010687. BMJ Open. 2016. PMID: 27029775 Free PMC article. Clinical Trial.
-
Mapping Power Law Distributions in Digital Health Social Networks: Methods, Interpretations, and Practical Implications.J Med Internet Res. 2015 Jun 25;17(6):e160. doi: 10.2196/jmir.4297. J Med Internet Res. 2015. PMID: 26111790 Free PMC article.
-
Trouble with the curve: the 90-9-1 rule to measure volitional participation inequalities among Royal Canadian Mounted Police cadets during training.Front Psychiatry. 2024 May 28;15:1297953. doi: 10.3389/fpsyt.2024.1297953. eCollection 2024. Front Psychiatry. 2024. PMID: 38863607 Free PMC article.
-
The failure to increase social support: it just might be time to stop intervening (and start rigorously observing).Transl Behav Med. 2017 Dec;7(4):816-820. doi: 10.1007/s13142-016-0458-9. Transl Behav Med. 2017. PMID: 28070778 Free PMC article.
-
Effectiveness of WhatsApp online group discussion for smoking relapse prevention: protocol for a pragmatic randomized controlled trial.Addiction. 2020 Sep;115(9):1777-1785. doi: 10.1111/add.15027. Epub 2020 Mar 20. Addiction. 2020. PMID: 32107817 Free PMC article.
References
-
- Centers for Disease Control and Prevention (CDC) Vital signs: current cigarette smoking among adults aged ≥ 18 years --- United States, 2009. MMWR Morb Mortal Wkly Rep. 2010 Sep 10;59(35):1135–40. http://www.cdc.gov/mmwr/preview/mmwrhtml/mm5935a3.htmmm5935a3 - PubMed
-
- Health Canada. 2010. Sep 27, [2011-05-25]. Canadian Tobacco Use Monitoring Survey (CTUMS) 2009. http://www.hc-sc.gc.ca/hc-ps/tobac-tabac/research-recherche/stat/ctums-e....
-
- World Health Organization. 1999. [2011-09-27]. The World Health Report 1999: Making a Difference http://www.who.int/whr/1999/en/whr99_en.pdf.
-
- Fiore MD, Jaen CR, Baker TB, Baily WC, Benowitz NL, Currey SJ, Dorfman SF, Froelicher ES, Goldstein MG, Healton CG, Henderson PN, Heyman RB, Koh HK, Kottke TE, Lando HA, Mecklenburg RE, Mermelstein RJ, Mullen PD, Orleans CT, Robinson L, Stitzer ML, Tommasello AC, Villejo L, Wewers ME. US Department of Health and Human Services, Public Health Services. 2008. May, [2011-05-25]. Treating Tobacco Use and Dependence: 2008 Update http://www.surgeongeneral.gov/tobacco/treating_tobacco_use08.pdf.
-
- Lemmens V, Oenema A, Knut IK, Brug J. Effectiveness of smoking cessation interventions among adults: a systematic review of reviews. Eur J Cancer Prev. 2008 Nov;17(6):535–44. - PubMed
Publication types
MeSH terms
LinkOut - more resources
Full Text Sources
Medical
Research Materials