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Citing this Article

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Published on 07.03.16 in Vol 18, No 3 (2016): March

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

Works citing "Collective-Intelligence Recommender Systems: Advancing Computer Tailoring for Health Behavior Change Into the 21st Century"

Rajani Shankar Sadasivam, Sarah L Cutrona, Rebecca L Kinney, Benjamin M Marlin, Kathleen M Mazor, Stephenie C Lemon, Thomas K Houston

J Med Internet Res 2016 (Mar 07); 18(3):e42 

According to Crossref, the following articles are citing this article (DOI 10.2196/jmir.4448):

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

  1. Hartzler AL, BlueSpruce J, Catz SL, McClure JB. Prioritizing the mHealth Design Space: A Mixed-Methods Analysis of Smokers’ Perspectives. JMIR mHealth and uHealth 2016;4(3):e95
    CrossRef
  2. . UNDERSTANDING HINDSIGHT, INSIGHT AND FORSIGHT DATA TO LARGE-SCALE DISTRIBUTED DATA INTELLIGENCE (ALGORITHMS) MACHINE: A SCALE-OUT REVIEW. i-manager’s Journal on Pattern Recognition 2017;4(3):32
    CrossRef
  3. Weng S, Yang M, Hsiao P. A factor-identifying study of the user-perceived value of collective intelligence based on online social networks. Internet Research 2018;28(3):696
    CrossRef
  4. 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
  5. Sadasivam RS, Borglund EM, Adams R, Marlin BM, Houston TK. Impact of a Collective Intelligence Tailored Messaging System on Smoking Cessation: The Perspect Randomized Experiment. Journal of Medical Internet Research 2016;18(11):e285
    CrossRef
  6. Sanchez Bocanegra CL, Sevillano Ramos JL, Rizo C, Civit A, Fernandez-Luque L. HealthRecSys: A semantic content-based recommender system to complement health videos. BMC Medical Informatics and Decision Making 2017;17(1)
    CrossRef
  7. Hors-Fraile S, Rivera-Romero O, Schneider F, Fernandez-Luque L, Luna-Perejon F, Civit-Balcells A, de Vries H. Analyzing recommender systems for health promotion using a multidisciplinary taxonomy: A scoping review. International Journal of Medical Informatics 2018;114:143
    CrossRef
  8. 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
  9. Castillo VH, Martínez-García AI, Soriano-Equigua L, Maciel-Mendoza FM, Álvarez-Flores JL, Juárez-Ramírez R. An interaction framework for supporting the adoption of EHRS by physicians. Universal Access in the Information Society 2019;18(2):399
    CrossRef
  10. Ashrafian H, Darzi A. Transforming health policy through machine learning. PLOS Medicine 2018;15(11):e1002692
    CrossRef
  11. 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
  12. Short CE, James EL, Rebar AL, Duncan MJ, Courneya KS, Plotnikoff RC, Crutzen R, Bidargaddi N, Vandelanotte C. Designing more engaging computer-tailored physical activity behaviour change interventions for breast cancer survivors: lessons from the iMove More for Life study. Supportive Care in Cancer 2017;25(11):3569
    CrossRef
  13. . Online Information and Communication Systems to Enhance Health Outcomes Through Communication Convergence. Human Communication Research 2017;43(4):518
    CrossRef
  14. 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
  15. 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
  16. . A future of digital leadership that is behavioural by design. Future Healthcare Journal 2020;7(3):194
    CrossRef
  17. Leung YW, Wouterloot E, Adikari A, Hirst G, de Silva D, Wong J, Bender JL, Gancarz M, Gratzer D, Alahakoon D, Esplen MJ. Natural Language Processing–Based Virtual Cofacilitator for Online Cancer Support Groups: Protocol for an Algorithm Development and Validation Study. JMIR Research Protocols 2021;10(1):e21453
    CrossRef
  18. 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
  19. 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
  20. Doreswamy N, Horstmanshof L. Human Decision-making in an Artificial Intelligence–Driven Future in Health: Protocol for Comparative Analysis and Simulation. JMIR Research Protocols 2022;11(12):e42353
    CrossRef
  21. 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
  22. 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
  23. 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
  24. Leung YW, Ng S, Duan L, Lam C, Chan K, Gancarz M, Rennie H, Trachtenberg L, Chan KP, Adikari A, Fang L, Gratzer D, Hirst G, Wong J, Esplen MJ. Therapist Feedback and Implications on Adoption of an Artificial Intelligence–Based Co-Facilitator for Online Cancer Support Groups: Mixed Methods Single-Arm Usability Study. JMIR Cancer 2023;9:e40113
    CrossRef
  25. Woodman RJ, Mangoni AA. A comprehensive review of machine learning algorithms and their application in geriatric medicine: present and future. Aging Clinical and Experimental Research 2023;35(11):2363
    CrossRef

According to Crossref, the following books are citing this article (DOI 10.2196/jmir.4448):

  1. Rana SP, Dey M, Prieto J, Dudley S. Recommender System with Machine Learning and Artificial Intelligence. 2020. :215
    CrossRef
  2. Kreps GL, Wright K, Burke-Garcia A. Environmental Health Literacy. 2019. Chapter 10:265
    CrossRef
  3. . Information Literacy in Everyday Life. 2019. Chapter 14:144
    CrossRef
  4. Cheung KL, Hors-Fraile S, de Vries H. Digital Health. 2021. :159
    CrossRef
  5. Meriem H, Abdelwahed EH, Qassimi S. Advanced Intelligent Systems for Sustainable Development (AI2SD’2020). 2022. Chapter 22:277
    CrossRef
  6. Hao L, Goetze S, Hawley M. HCI International 2023 – Late Breaking Papers. 2023. Chapter 36:536
    CrossRef
  7. Samih A, Hamane Z, Ghadi A, Fennan A. International Conference on Advanced Intelligent Systems for Sustainable Development (AI2SD’2023). 2024. Chapter 25:261
    CrossRef