Explore our sister journals here.

Maintenance Notice

Due to necessary scheduled maintenance, the JMIR Publications website will be unavailable from Wednesday, July 01, 2020 at 8:00 PM to 10:00 PM EST. We apologize in advance for any inconvenience this may cause you.

Who will be affected?

Citing this Article

Right click to copy or hit: ctrl+c (cmd+c on mac)

Published on 08.11.16 in Vol 18, No 11 (2016): November

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

Works citing "Impact of a Collective Intelligence Tailored Messaging System on Smoking Cessation: The Perspect Randomized Experiment"

Rajani Shankar Sadasivam, Erin M Borglund, Roy Adams, Benjamin M Marlin, Thomas K Houston

J Med Internet Res 2016 (Nov 08); 18(11):e285 

According to Crossref, the following articles are citing this article (DOI 10.2196/jmir.6465):

(note that this is only a small subset of citations)

  1. Kruse G, Park ER, Shahid NN, Abroms L, Haberer JE, Rigotti NA. Combining Real-Time Ratings With Qualitative Interviews to Develop a Smoking Cessation Text Messaging Program for Primary Care Patients. JMIR mHealth and uHealth 2019;7(3):e11498
    CrossRef
  2. Hors-Fraile S, Malwade S, Luna-Perejon F, Amaya C, Civit A, Schneider F, Bamidis P, Syed-Abdul S, Li Y, de Vries H. Opening the Black Box: Explaining the Process of Basing a Health Recommender System on the I-Change Behavioral Change Model. IEEE Access 2019;7:176525
    CrossRef
  3. Wang X, Zhao K, Cha S, Amato MS, Cohn AM, Pearson JL, Papandonatos GD, Graham AL. Mining user-generated content in an online smoking cessation community to identify smoking status: A machine learning approach. Decision Support Systems 2019;116:26
    CrossRef
  4. Faro JM, Orvek EA, Blok AC, Nagawa CS, McDonald AJ, Seward G, Houston TK, Kamberi A, Allison JJ, Person SD, Smith BM, Brady K, Grosowsky T, Jacobsen LL, Paine J, Welch Jr JM, Sadasivam RS. Dissemination and Effectiveness of the Peer Marketing and Messaging of a Web-Assisted Tobacco Intervention: Protocol for a Hybrid Effectiveness Trial. JMIR Research Protocols 2019;8(7):e14814
    CrossRef
  5. Cheung KL, Durusu D, Sui X, de Vries H. How recommender systems could support and enhance computer-tailored digital health programs: A scoping review. DIGITAL HEALTH 2019;5:205520761882472
    CrossRef
  6. Herbst E, McCaslin SE, Hassanbeigi Daryani S, Laird KT, Hopkins LB, Pennington D, Kuhn E. A Qualitative Examination of Stay Quit Coach, A Mobile Application for Veteran Smokers With Posttraumatic Stress Disorder. Nicotine & Tobacco Research 2020;22(4):560
    CrossRef
  7. . Peer Influence of Online Comments in Newspapers: Applying Social Norms and the Social Identification Model of Deindividuation Effects (SIDE). Social Science Computer Review 2019;37(4):551
    CrossRef
  8. Triantafyllidis AK, Tsanas A. Applications of Machine Learning in Real-Life Digital Health Interventions: Review of the Literature. Journal of Medical Internet Research 2019;21(4):e12286
    CrossRef
  9. Cheung KL, Wijnen B, de Vries H. A Review of the Theoretical Basis, Effects, and Cost Effectiveness of Online Smoking Cessation Interventions in the Netherlands: A Mixed-Methods Approach. Journal of Medical Internet Research 2017;19(6):e230
    CrossRef
  10. Faro JM, Nagawa CS, Allison JA, Lemon SC, Mazor KM, Houston TK, Sadasivam RS. Comparison of a Collective Intelligence Tailored Messaging System on Smoking Cessation Between African American and White People Who Smoke: Quasi-Experimental Design. JMIR mHealth and uHealth 2020;8(4):e18064
    CrossRef
  11. Hors-Fraile S, Malwade S, Spachos D, Fernandez-Luque L, Su C, Jeng W, Syed-Abdul S, Bamidis P, Li Y. A recommender system to quit smoking with mobile motivational messages: study protocol for a randomized controlled trial. Trials 2018;19(1)
    CrossRef
  12. . Increasing the Impact of JMIR Journals in the Attention Economy. Journal of Medical Internet Research 2019;21(10):e16172
    CrossRef
  13. Calero Valdez A, Ziefle M. The users’ perspective on the privacy-utility trade-offs in health recommender systems. International Journal of Human-Computer Studies 2019;121:108
    CrossRef
  14. Hurley NC, Spatz ES, Krumholz HM, Jafari R, Mortazavi BJ. A Survey of Challenges and Opportunities in Sensing and Analytics for Risk Factors of Cardiovascular Disorders. ACM Transactions on Computing for Healthcare 2021;2(1):1
    CrossRef
  15. Faro JM, Nagawa CS, Orvek EA, Smith BM, Blok AC, Houston TK, Kamberi A, Allison JJ, Person SD, Sadasivam RS. Comparing recruitment strategies for a digital smoking cessation intervention: Technology-assisted peer recruitment, social media, ResearchMatch, and smokefree.gov. Contemporary Clinical Trials 2021;103:106314
    CrossRef
  16. Wolff J, Pauling J, Keck A, Baumbach J. Success Factors of Artificial Intelligence Implementation in Healthcare. Frontiers in Digital Health 2021;3
    CrossRef
  17. De Croon R, Van Houdt L, Htun NN, Štiglic G, Vanden Abeele V, Verbert K. Health Recommender Systems: Systematic Review. Journal of Medical Internet Research 2021;23(6):e18035
    CrossRef
  18. Rodriguez DV, Lawrence K, Luu S, Yu JL, Feldthouse DM, Gonzalez J, Mann D. Development of a computer-aided text message platform for user engagement with a digital Diabetes Prevention Program: a case study. Journal of the American Medical Informatics Association 2021;29(1):155
    CrossRef
  19. Zhou Q, Chen Z, Cao Y, Peng S. Clinical impact and quality of randomized controlled trials involving interventions evaluating artificial intelligence prediction tools: a systematic review. npj Digital Medicine 2021;4(1)
    CrossRef
  20. Siontis GCM, Sweda R, Noseworthy PA, Friedman PA, Siontis KC, Patel CJ. Development and validation pathways of artificial intelligence tools evaluated in randomised clinical trials. BMJ Health & Care Informatics 2021;28(1):e100466
    CrossRef
  21. Bickel WK, Tomlinson DC, Craft WH, Ma M, Dwyer CL, Yeh Y, Tegge AN, Freitas-Lemos R, Athamneh LN. Predictors of smoking cessation outcomes identified by machine learning: A systematic review. Addiction Neuroscience 2023;6:100068
    CrossRef
  22. Naegelin M, Weibel RP, Kerr JI, Schinazi VR, La Marca R, von Wangenheim F, Hoelscher C, Ferrario A. An interpretable machine learning approach to multimodal stress detection in a simulated office environment. Journal of Biomedical Informatics 2023;139:104299
    CrossRef
  23. Lisowska A, Wilk S, Peleg M. SATO (IDEAS expAnded wiTh BCIO): Workflow for designers of patient-centered mobile health behaviour change intervention applications. Journal of Biomedical Informatics 2023;138:104276
    CrossRef
  24. Hors-Fraile S, Candel MJJM, Schneider F, Malwade S, Nunez-Benjumea FJ, Syed-Abdul S, Fernandez-Luque L, de Vries H. Applying Collective Intelligence in Health Recommender Systems for Smoking Cessation: A Comparison Trial. Electronics 2022;11(8):1219
    CrossRef
  25. Faro JM, Chen J, Flahive J, Nagawa CS, Orvek EA, Houston TK, Allison JJ, Person SD, Smith BM, Blok AC, Sadasivam RS. Effect of a Machine Learning Recommender System and Viral Peer Marketing Intervention on Smoking Cessation. JAMA Network Open 2023;6(1):e2250665
    CrossRef
  26. Chen J, Houston TK, Faro JM, Nagawa CS, Orvek EA, Blok AC, Allison JJ, Person SD, Smith BM, Sadasivam RS. Evaluating the use of a recommender system for selecting optimal messages for smoking cessation: patterns and effects of user-system engagement. BMC Public Health 2021;21(1)
    CrossRef
  27. Honka AM, Nieminen H, Simila H, Kaartinen J, Gils MV. A Comprehensive User Modeling Framework and a Recommender System for Personalizing Well-Being Related Behavior Change Interventions: Development and Evaluation. IEEE Access 2022;10:116766
    CrossRef
  28. Lee DN, Sadasivam RS, Stevens EM. Developing Mood-Based Computer-Tailored Health Communication for Smoking Cessation: Feasibility Randomized Controlled Trial. JMIR Formative Research 2023;7:e48958
    CrossRef
  29. Trinkley KE, An R, Maw AM, Glasgow RE, Brownson RC. Leveraging artificial intelligence to advance implementation science: potential opportunities and cautions. Implementation Science 2024;19(1)
    CrossRef
  30. Killian JA, Jain M, Jia Y, Amar J, Huang E, Tambe M. New Approach to Equitable Intervention Planning to Improve Engagement and Outcomes in a Digital Health Program: Simulation Study. JMIR Diabetes 2024;9:e52688
    CrossRef
  31. Sadasivam RS, Nagawa CS, Wijesundara JG, Flahive J, Nguyen HL, Larkin C, Faro JM, Balakrishnan K, Ha DA, Nguyen CK, Vuong A, Phan PT, Pham QPL, Allison JJ, Houston TK. Peer Texting to Promote Quitline Use and Smoking Cessation Among Rural Participants in Vietnam: Randomized Clinical Trial. International Journal of Public Health 2024;69
    CrossRef

According to Crossref, the following books are citing this article (DOI 10.2196/jmir.6465):

  1. Harrer M, Terhorst Y, Baumeister H, Ebert DD. Digitale Gesundheitsinterventionen. 2023. Chapter 27:465
    CrossRef
  2. Hao L, Goetze S, Hawley M. HCI International 2023 – Late Breaking Papers. 2023. Chapter 36:536
    CrossRef