This paper is in the following e-collection/theme issue:

ISRII Theme Issue 2012 (9)

Published on in Vol 14, No 3 (2012): May-Jun

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

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

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

Authors of this article:

Trevor van Mierlo1 Author Orcid Image ;   Sabrina Voci2 ;   Sharon Lee3 ;   Rachel Fournier4 Author Orcid Image ;   Peter Selby2, 5
Article Authors Cited by (48) Tweetations (11) Metrics

Journals

  1. Christensen H, Calear A, Andersson G, Thorndike F, Tait R. Beyond Efficacy: The Depth and Diversity of Current Internet Interventions. Journal of Medical Internet Research 2012;14(3):e92 View
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  3. Ramo D, Liu H, Prochaska J. A Mixed-Methods Study of Young Adults' Receptivity to Using Facebook for Smoking Cessation: If You Build It, Will They Come?. American Journal of Health Promotion 2015;29(4):e126 View
  4. van Mierlo T, Hyatt D, Ching A. Employing the Gini coefficient to measure participation inequality in treatment-focused Digital Health Social Networks. Network Modeling Analysis in Health Informatics and Bioinformatics 2016;5(1) View
  5. van Mierlo T, Hyatt D, Ching A, Fournier R, Dembo R. Behavioral Economics, Wearable Devices, and Cooperative Games: Results From a Population-Based Intervention to Increase Physical Activity. JMIR Serious Games 2016;4(1):e1 View
  6. Cheung Y, Chan C, Ho K, Fok W, Conway M, Wong C, Li W, Wang M, Lam T. Effectiveness of WhatsApp online group discussion for smoking relapse prevention: protocol for a pragmatic randomized controlled trial. Addiction 2020;115(9):1777 View
  7. O'Neill B, Ziebland S, Valderas J, Lupiáñez-Villanueva F. User-Generated Online Health Content: A Survey of Internet Users in the United Kingdom. Journal of Medical Internet Research 2014;16(4):e118 View
  8. Graham A, Jacobs M, Cohn A, Cha S, Abroms L, Papandonatos G, Whittaker R. Optimising text messaging to improve adherence to web-based smoking cessation treatment: a randomised control trial protocol. BMJ Open 2016;6(3):e010687 View
  9. Campos P, Gomide M. O Programa Nacional de Controle do Tabagismo (PNCT) na perspectiva social: a análise de redes, capital e apoio social. Cadernos Saúde Coletiva 2015;23(4):436 View
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  11. Zhao K, Wang X, Cha S, Cohn A, Papandonatos G, Amato M, Pearson J, Graham A. A Multirelational Social Network Analysis of an Online Health Community for Smoking Cessation. Journal of Medical Internet Research 2016;18(8):e233 View
  12. Pearson J, Amato M, Papandonatos G, Zhao K, Erar B, Wang X, Cha S, Cohn A, Graham A. Exposure to positive peer sentiment about nicotine replacement therapy in an online smoking cessation community is associated with NRT use. Addictive Behaviors 2018;87:39 View
  13. Ziebland S, Powell J, Briggs P, Jenkinson C, Wyke S, Sillence E, Harris P, Perera R, Mazanderani F, Martin A, Locock L, Kelly L, Booth M, Gann B, Newhouse N, Farmer A. Examining the role of patients’ experiences as a resource for choice and decision-making in health care: a creative, interdisciplinary mixed-method study in digital health. Programme Grants for Applied Research 2016;4(17):1 View
  14. Demment M, Graham M, Olson C. How an Online Intervention to Prevent Excessive Gestational Weight Gain Is Used and by Whom: A Randomized Controlled Process Evaluation. Journal of Medical Internet Research 2014;16(8):e194 View
  15. Yang Q. Are Social Networking Sites Making Health Behavior Change Interventions More Effective? A Meta-Analytic Review. Journal of Health Communication 2017;22(3):223 View
  16. Graham A, Zhao K, Papandonatos G, Erar B, Wang X, Amato M, Cha S, Cohn A, Pearson J, Amblard F. A prospective examination of online social network dynamics and smoking cessation. PLOS ONE 2017;12(8):e0183655 View
  17. Ramo D, Thrul J, Chavez K, Delucchi K, Prochaska J. Feasibility and Quit Rates of the Tobacco Status Project: A Facebook Smoking Cessation Intervention for Young Adults. Journal of Medical Internet Research 2015;17(12):e291 View
  18. Zhang F, Li S, Yu Z. The super user selection for building a sustainable online social network marketing community. Multimedia Tools and Applications 2019;78(11):14777 View
  19. van Mierlo T, Hyatt D, Ching A. Mapping Power Law Distributions in Digital Health Social Networks: Methods, Interpretations, and Practical Implications. Journal of Medical Internet Research 2015;17(6):e160 View
  20. Graham A, Papandonatos G, Cha S, Erar B, Amato M, Cobb N, Niaura R, Abrams D. Improving Adherence to Smoking Cessation Treatment: Intervention Effects in a Web-Based Randomized Trial. Nicotine & Tobacco Research 2016:ntw282 View
  21. Healey B, Hoek J, Edwards R, Shahab L. Posting Behaviour Patterns in an Online Smoking Cessation Social Network: Implications for Intervention Design and Development. PLoS ONE 2014;9(9):e106603 View
  22. Stearns M, Nambiar S, Nikolaev A, Semenov A, McIntosh S. Towards evaluating and enhancing the reach of online health forums for smoking cessation. Network Modeling Analysis in Health Informatics and Bioinformatics 2014;3(1) View
  23. van Mierlo T, Li X, Hyatt D, Ching A. Demographic and Indication-Specific Characteristics Have Limited Association With Social Network Engagement: Evidence From 24,954 Members of Four Health Care Support Groups. Journal of Medical Internet Research 2017;19(2):e40 View
  24. Gopalsamy R, Semenov A, Pasiliao E, McIntosh S, Nikolaev A. Engagement as a Driver of Growth of Online Health Forums: Observational Study. Journal of Medical Internet Research 2017;19(8):e304 View
  25. Pagoto S, Waring M. A Call for a Science of Engagement: Comment on Rus and Cameron. Annals of Behavioral Medicine 2016;50(5):690 View
  26. Wang X, Zhao K, Cha S, Amato M, Cohn A, Pearson J, Papandonatos G, Graham A. Mining user-generated content in an online smoking cessation community to identify smoking status: A machine learning approach. Decision Support Systems 2019;116:26 View
  27. Graham A, Papandonatos G, Zhao K. The failure to increase social support: it just might be time to stop intervening (and start rigorously observing). Translational Behavioral Medicine 2017;7(4):816 View
  28. van Agteren J, Lawn S, Bonevski B, Smith B. Kick.it: The development of an evidence-based smoking cessation smartphone app. Translational Behavioral Medicine 2018;8(2):243 View
  29. Carron-Arthur B, Cunningham J, Griffiths K. 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 Interventions 2014;1(4):165 View
  30. Joglekar S, Sastry N, Coulson N, Taylor S, Patel A, Duschinsky R, Anand A, Jameson Evans M, Griffiths C, Sheikh A, Panzarasa P, De Simoni A. 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. Journal of Medical Internet Research 2018;20(7):e238 View
  31. Carron-Arthur B, Reynolds J, Bennett K, Bennett A, Griffiths K. What’s all the talk about? Topic modelling in a mental health Internet support group. BMC Psychiatry 2016;16(1) View
  32. Saul J, Amato M, Cha S, Graham A. Engagement and attrition in Internet smoking cessation interventions: Insights from a cross-sectional survey of “one-hit-wonders”. Internet Interventions 2016;5:23 View
  33. Welding K, De Leon E, Cha S, Johnson M, Cohen J, Graham A. Weekly enrollment and usage patterns in an Internet smoking cessation intervention. Internet Interventions 2017;9:100 View
  34. De Simoni A, Shah A, Fulton O, Parkinson J, Sheikh A, Panzarasa P, Pagliari C, Coulson N, Griffiths C. Superusers’ Engagement in Asthma Online Communities: Asynchronous Web-Based Interview Study. Journal of Medical Internet Research 2020;22(6):e18185 View
  35. Carron-Arthur B, Reynolds J, Bennett K, Bennett A, Cunningham J, Griffiths K. Community Structure of a Mental Health Internet Support Group: Modularity in User Thread Participation. JMIR Mental Health 2016;3(2):e20 View
  36. Post S, Taylor S, Sanders A, Goldfarb J, Hunt Y, Augustson E. If You Build (and Moderate) It, They Will Come: The Smokefree Women Facebook Page. JNCI Monographs 2013;2013(47):206 View
  37. Jake-Schoffman D, Carrera Seoane M, Cooper K, Rajoria M, McVay M. Engaging adults with obesity in organic online communities to support weight loss: a mixed methods pilot study. Psychology & Health 2024;39(4):536 View
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  39. Teckchandani T, Shields R, Andrews K, Maguire K, Jamshidi L, Nisbet J, Afifi T, Lix L, Stewart S, Sauer-Zavala S, Krakauer R, Neary J, Krätzig G, Carleton R. Trouble with the curve: the 90–9-1 rule to measure volitional participation inequalities among Royal Canadian Mounted Police cadets during training. Frontiers in Psychiatry 2024;15 View
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