Published on in Vol 12, No 3 (2010): Jul-Sep

Online Social and Professional Support for Smokers Trying to Quit: An Exploration of First Time Posts From 2562 Members

Online Social and Professional Support for Smokers Trying to Quit: An Exploration of First Time Posts From 2562 Members

Online Social and Professional Support for Smokers Trying to Quit: An Exploration of First Time Posts From 2562 Members

Journals

  1. van Mierlo T, Fournier R, Jean-Charles A, Hovington J, Ethier I, Selby P, Colizza V. I'll Txt U if I Have a Problem: How the Société Canadienne du Cancer in Quebec Applied Behavior-Change Theory, Data Mining and Agile Software Development to Help Young Adults Quit Smoking. PLoS ONE 2014;9(3):e91832 View
  2. 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
  3. Jones E, Storksdieck M, Rangel M. How Social Networks May Influence Cancer Patients' Situated Identity and Illness-Related Behaviors. Frontiers in Public Health 2018;6 View
  4. Epstein M, Oesterle S, Haggerty K. Effectiveness of Facebook Groups to Boost Participation in a Parenting Intervention. Prevention Science 2019;20(6):894 View
  5. Cole-Lewis H, Perotte A, Galica K, Dreyer L, Griffith C, Schwarz M, Yun C, Patrick H, Coa K, Augustson E. Social Network Behavior and Engagement Within a Smoking Cessation Facebook Page. Journal of Medical Internet Research 2016;18(8):e205 View
  6. Daneshvar H, Anderson S, Williams R, Mozaffar H. How Can Social Media Lead to Co-Production (Co-Delivery) of New Services for the Elderly Population? A Qualitative Study. JMIR Human Factors 2018;5(1):e5 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. Chuang K, Yang C. Interaction Patterns of Nurturant Support Exchanged in Online Health Social Networking. Journal of Medical Internet Research 2012;14(3):e54 View
  9. Cobb N, Mays D, Graham A. Sentiment Analysis to Determine the Impact of Online Messages on Smokers' Choices to Use Varenicline. JNCI Monographs 2013;2013(47):224 View
  10. Kurko T, Linden K, Kolstela M, Pietilä K, Airaksinen M. Is nicotine replacement therapy overvalued in smoking cessation? Analysis of smokers' and quitters' communication in social media. Health Expectations 2015;18(6):2962 View
  11. Moorhead S, Hazlett D, Harrison L, Carroll J, Irwin A, Hoving C. A New Dimension of Health Care: Systematic Review of the Uses, Benefits, and Limitations of Social Media for Health Communication. Journal of Medical Internet Research 2013;15(4):e85 View
  12. Granado-Font E, Ferré-Grau C, Rey-Reñones C, Pons-Vigués M, Pujol Ribera E, Berenguera A, Barrera-Uriarte M, Basora J, Valverde-Trillo A, Duch J, Flores-Mateo G. Coping Strategies and Social Support in a Mobile Phone Chat App Designed to Support Smoking Cessation: Qualitative Analysis. JMIR mHealth and uHealth 2018;6(12):e11071 View
  13. 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
  14. Veuillotte I, Morel G, Pitois S, Haler R, Mercier P, Aubry C, Cannet D. General practice and the Internet revolution. Use of an Internet social network to communicate information on prevention in France. Health Informatics Journal 2015;21(1):3 View
  15. Risson V, Ghodge B, Bonzani I, Korn J, Medin J, Saraykar T, Sengupta S, Saini D, Olson M. Linked Patient-Reported Outcomes Data From Patients With Multiple Sclerosis Recruited on an Open Internet Platform to Health Care Claims Databases Identifies a Representative Population for Real-Life Data Analysis in Multiple Sclerosis. Journal of Medical Internet Research 2016;18(9):e249 View
  16. Zhang M, Yang C. The differences of user behavior between forum and Facebook for smoking cessation intervention. Proceedings of the American Society for Information Science and Technology 2012;49(1):1 View
  17. 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
  18. van Mierlo T, Voci S, Lee S, Fournier R, Selby P. 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. Journal of Medical Internet Research 2012;14(3):e66 View
  19. 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
  20. van Mierlo T, Fournier R, Ingham M, Wallace G. Targeting Medication Non-Adherence Behavior in Selected Autoimmune Diseases: A Systematic Approach to Digital Health Program Development. PLOS ONE 2015;10(6):e0129364 View
  21. 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
  22. Cobb N, Graham A, Byron M, Niaura R, Abrams D. Online Social Networks and Smoking Cessation: A Scientific Research Agenda. Journal of Medical Internet Research 2011;13(4):e119 View
  23. 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
  24. Keller P, Schillo B, Kerr A, Lien R, Saul J, Dreher M, Lachter R. Increasing reach by offering choices: Results from an innovative model for statewide services for smoking cessation. Preventive Medicine 2016;91:96 View
  25. van Mierlo T. The 1% Rule in Four Digital Health Social Networks: An Observational Study. Journal of Medical Internet Research 2014;16(2):e33 View
  26. Glover M, Bosman A, Wagemakers A, Kira A, Paton C, Cowie N. An innovative team-based stop smoking competition among Māori and Pacific Island smokers: rationale and method for the study and its evaluation. BMC Public Health 2013;13(1) View
  27. Bornkessel A, Furberg R, Lefebvre R. Social Media: Opportunities for Quality Improvement and Lessons for Providers—A Networked Model for Patient-Centered Care Through Digital Engagement. Current Cardiology Reports 2014;16(7) View
  28. Amato M, Papandonatos G, Cha S, Wang X, Zhao K, Cohn A, Pearson J, Graham A. Inferring Smoking Status from User Generated Content in an Online Cessation Community. Nicotine & Tobacco Research 2019;21(2):205 View
  29. Tapi Nzali M, Bringay S, Lavergne C, Mollevi C, Opitz T. What Patients Can Tell Us: Topic Analysis for Social Media on Breast Cancer. JMIR Medical Informatics 2017;5(3):e23 View
  30. McKelvey K, Ramo D. Conversation Within a Facebook Smoking Cessation Intervention Trial For Young Adults (Tobacco Status Project): Qualitative Analysis. JMIR Formative Research 2018;2(2):e11138 View
  31. 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
  32. 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
  33. Cha S, Cohn A, Elmasry H, Graham A. A Preliminary Exploration of Former Smokers Enrolled in an Internet Smoking Cessation Program. JMIR Research Protocols 2016;5(2):e119 View
  34. 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
  35. Andrade E, Evans W, Barrett N, Edberg M, Cleary S. Strategies to Increase Latino Immigrant Youth Engagement in Health Promotion Using Social Media: Mixed-Methods Study. JMIR Public Health and Surveillance 2018;4(4):e71 View
  36. 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
  37. 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
  38. 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
  39. 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
  40. Cheung Y, Chan C, Lai C, Chan W, Wang M, Li H, Chan S, Lam T. Using WhatsApp and Facebook Online Social Groups for Smoking Relapse Prevention for Recent Quitters: A Pilot Pragmatic Cluster Randomized Controlled Trial. Journal of Medical Internet Research 2015;17(10):e238 View
  41. Schneider A, von Krogh G, Jäger P. “What’s coming next?” Epistemic curiosity and lurking behavior in online communities. Computers in Human Behavior 2013;29(1):293 View
  42. 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
  43. Shah A, Yan X, Qayyum A. Social Network Analysis of an Online Smoking Cessation Community to Identify Users’ Smoking Status. Healthcare Informatics Research 2021;27(2):116 View
  44. Qian Y, Gui W, Ma F, Dong Q. Exploring features of social support in a Chinese online smoking cessation community: A multidimensional content analysis of user interaction data. Health Informatics Journal 2021;27(2):146045822110214 View
  45. Storman D, Jemioło P, Swierz M, Sawiec Z, Antonowicz E, Prokop-Dorner A, Gotfryd-Burzyńska M, Bala M. Meeting the Unmet Needs of Individuals With Mental Disorders: Scoping Review on Peer-to-Peer Web-Based Interactions. JMIR Mental Health 2022;9(12):e36056 View
  46. Struik L, Khan S, Assoiants A, Sharma R. Assessment of Social Support and Quitting Smoking in an Online Community Forum: Study Involving Content Analysis. JMIR Formative Research 2022;6(1):e34429 View
  47. Yegnanarayanan V, Krithicaa Narayanaa Y, Anitha M, Ciurea R, Marceanu L, Balas V. Graph theoretical way of understanding protein-protein interaction in ovarian cancer. Journal of Intelligent & Fuzzy Systems 2022;43(2):1877 View
  48. TAKAHASHI A, SUEKI H, ITO J. Rapid E-mail Response to First-Contact E-mails Increases Consultation Continuation Rates for Suicide Prevention. Asian Journal of Human Services 2021;20(0):19 View
  49. Rondina R, van Mierlo T, Fournier R. Testing Behavioral Nudges and Prompts in Digital Courses for the Self-guided Treatment of Depression and Anxiety: Protocol for a 3-Arm Randomized Controlled Trial. JMIR Research Protocols 2022;11(8):e37231 View
  50. Chen X, Al-Worafi Y. Online health communities influence people’s health behaviors in the context of COVID-19. PLOS ONE 2023;18(4):e0282368 View
  51. He W, Wang Q, Lam T, Chan C, Luk T, Wang M, Chan S, Cheung Y. Effectiveness of Instant Messaging-Based Online Group Support for Preventing Smoking Relapse: a Pragmatic Randomized Controlled Trial. International Journal of Mental Health and Addiction 2024 View
  52. van Mierlo T, Rondina R, Fournier R. Nudges and Prompts Increase Engagement in Self-Guided Digital Health Treatment for Depression and Anxiety: Results From a 3-Arm Randomized Controlled Trial. JMIR Formative Research 2024;8:e52558 View
  53. Liu X, Zhou Y, Wang Z, Kumar A, Biswas B. Disease Topic Modeling of Users' Inquiry Texts: A Text Mining-Based PQDR-LDA Model for Analyzing the Online Medical Records. IEEE Transactions on Engineering Management 2024;71:6319 View

Books/Policy Documents

  1. Zhang M, Yang C, Li J. Social Computing, Behavioral - Cultural Modeling and Prediction. View
  2. Graham A, Cobb C, Cobb N. Handbook of Health Decision Science. View